ADOPTING SOME IRRIGATION TECHNIQUES TO IMPROVE MAIZE WATER USE EFFICIENCY. A THESIS SUBMITTED TO THE FACULTY OF AGRICULTURAL SCIENCES UNIVERSITY OF SULAIMANI AS A PARTIAL FULFILLMENT OF THE REQUIRMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN SOIL AND WATER SCIENCE (IRRIGATION)

By

Farhan Ahmad Abdul-Rahman Qadr B. Sc. Soil Science 2007 Supervised by Dr. Salahadin Adbul-Aziz Mostafa Assistant Professor

June2013

Jozardan 2713

‫تنفيذ بعض التقنيات الرى لغرض رفع‬ ‫كفاءة أآلرواء للمحصول الذرة الصفراء‬ ‫رسالة مقدمة الى‬ ‫مجلس كلية فاكلتى العلوم الزراعية‪ -‬الجامعة السليمانية‬ ‫كجزء من متطلبات نيل درجة الماجستيرفى العلوم الزراعية‬ ‫(علم التربة والمياة – الرى)‬ ‫من قبل‬

‫فرحان امحد عبدالرمحن قادر‬ ‫بكالوريوس فى علم الرتبة – كلية الزراعة –جامعة السليمانية (‪)7002‬‬

‫باشراف‬ ‫أ‪ .‬م‪.‬د‪.‬صالح الدين عبدالعزيز مصطفى‬

‫حوزيران ‪ 7002‬ميالدي‬

‫جوزردان ‪ 7202‬الكردية‬

I certify that this thesis was prepared under my supervision at the University of Sulaimani, Faculty of Agricultural sciences as a partial requirement for the degree of Master in soil and water Science (Irrigation).

Supervisor: Asst. Prof. Dr. Slahadeen A. AL- Qassab College of Agriculture University of Mousel Date: / /2013

In view of the available recommendation, I forward this thesis for debate by the examining committee.

Dr. Kamil Sabir Said Head of Soil and Water Sciences Department Faculty of Agricultural Sciences University of Sulaimani Date: / /2013

We certify that we have read this thesis, and as examining committee examined the student in its contents, and that in our opinion it is adequate with Standing as a thesis for the degree of Master in soil and water Science (Irrigation).

Dr. Tariq Hama Karim

Dr. Esam M. Mohammed

Professor

Assistant Professor

Chairman

Member

/

/ 2013

/

Dr. Salahaddin A. Aziz

Dr. Slahadeen A. AL- Qassab

Lecturer

Assistant Professor

Member /

/ 2013

Member (Supervisor)

/ 2013

/

/ 2013

Date of thesis defense: 1/6/2013

Dr. Aram A. Muhammad Assistant Professor Dean of Faculty of Agricultural sciences / / 2013

DEDICATION

TO: Those who have knowledge, put it into practice and then teach it I dedicate this work.

((Farhan Ahmad))

ACKNOWLEDGEMENTS My grate thanks to Allah for giving me power and patience to perform this study. My sincere thanks and appreciations are extended to the presidency of University of Salahaddin and University of Sulaimani especially the deanery of the faculty of agriculture sciences for their facilities. I would like to express my sincere appreciation and gratitude to my supervisor, Dr. Slahadeen A. AL- Qassab, assistant professor of Soil Physic for his guidance, encouragement, supervision and constructive advice throughout the entire period of this study. Meanwhile sincere thanks are due to Dr. Mohammad Abdul Razaq, Lecture of soil and water sciences in faculty of Agriculture sciences for his indispensable help during the course of this study. Also I would like to acknowledge all the officials of the fields of the Technical Agriculture College of Halabja for their valuable helps. Acknowledgments are also extended to the soil laboratory staff of Halabja. I offer deep thanks to the official of the agro-meteorological center/ general directorate of agriculture and those of the Bakrajo agrometeorological station for providing me with most of collected meteorological data. I am greatly indebted to the member of examination committee for evaluating the content of the thesis and offering their valuable criticisms. Finally, I wish to express my heartfelt thanks to my brothers and sister for their praying, patience and encouragement.

NOTATIONS Abbreviations Details A Area of plot unit Cd numerator constant that changes with reference type and calculation time step Cn denumerator constant that changes with reference type and calculation time step Cp specific heat at constant pressure DI Deficit irrigation Dm Number of days to reach the root to maximum depth Dr Root zone depletion d Depth of water applied dr inverse relative distance Earth-Sun ETm Real evapotranspiration max ET adj Adjust Evapotranspiration under moisture stress ET os Grass evapotranspiration ET oT Alfalfa evapotranspiration Ep Pan evaporation standardized reference evapotranspiration for ETsz short (ETos) or tall (EToT) crop surfaces Actual vapor pressure Saturation vapor pressure saturation vapor pressure at daily minimum temperature saturation vapor pressure at daily maximum temperature G Soil heat flux Gs solar constant = 0.0820, I Number of days after planting J number of the day in the year Ks Moisture stress coefficient Kc Crop coefficient Kp Pan coefficient Ky Yield respons coefficient MRD Maximum root depth n actual duration of sunshine N maximum possible duration of sunshine or daylight hours p Depletion coefficient (fraction of TAW that a

UNITS m² s mˉ¹ K mm s³ Mgˉ¹ dˉ¹ MJ kg-1 °C-1

mm mm mm dˉ¹ mm dˉ¹ mm dˉ¹ mm dˉ¹ mm dˉ¹ mm dˉ¹ kPa kPa kPa kPa MJ m-2 min-1

100 cm hour hour

crop can extract water from the root zone without suffering water stress)

P PRDI RAW

atmospheric pressure Partial root dry irrigation Readily available water maximum relative humidity minimum relative humidity VIII

kPa mm % %

Abbreviations Details Ra extraterrestrial radiation Rs solar or shortwave radiation Rso clear-sky radiation

UNITS MJ m-2 day-1 MJ m-2 day-1 MJ m-2 day-1

Rn Rnl Rns RZD TAW T max T min

MJ m-2 day-1 MJ m-2 day-1 MJ m-2 day-1 cm mm °C °C Kelvin

Tmonth, i Tmonth, i-1

net radiation net outgoing long wave radiation net solar or shortwave radiation root zone depth Total available water Maximum temperature Minimum temperature maximum absolute temperature during the 24-hour period [K = °C + 273.16] minimum absolute temperature during the 24-hour period [K = °C + 273.16] mean air temperature of month i], mean air temperature of previous month [°C],

Tmonth, i+1

mean air temperature of next month

°C

T mean

Mean temperature

°C

U2

wind speed at 2 m height

m s-1

VPD

Vapor pressure deficit

kPa

V

Volume water applied

m³

Ya

Actual yield under moisture stress

Kg haˉ¹

Ym

Maximum crop yield without moisture stress

Kg haˉ¹

z

station elevation above sea level

m

Zr

Effective root zone depth

m

Kelvin °C °C

albedo or canopy reflection coefficient, which is 0.23 for the hypothetical grass reference crop Δ

slope of saturation vapor pressure curve

kPa °C-1

sunset hour angle

Rad

latitude

Rad

solar decimation

Rad

psychometric constant

kPa °C-1

latent heat of vaporization, 2.45

MJ kg-1

ratio molecular weight of water vapor/dry air θv FC = 0.622 θv FC

Volumetric water content at field capacity

m³ mˉ³

θv WP

Volumetric water content at wilting point

m³ mˉ³

θt

threshold soil water content below which m³ mˉ³ transpiration is reduced due to water stress IX

Abbreviations

Details Stefan-Boltzmann constant [4.903 *10-9]

UNITS MJ m-2 day-1

θv 0.75

Volumetric water content after %25 of m³ mˉ³ available water was depleted

θv 0.5

Volumetric water content after %50 of m³ mˉ³ available water was depleted

θv 0.25

Volumetric water content after %75 of m³ mˉ³ available water was depleted

X

SUMMARY A study was conducted at the experimental fields of the Technical College of agriculture at Halabja. Zea maize sp. (704) had been planted in the field condition during spring season. Five irrigation treatments had been selected with three replications. The first treatment was full irrigation (FI) which was irrigated to 100% of available water after consuming 50% of it. The second and third treatments were deficit irrigation (DI) which they were irrigated to 75% and 50% of available water after depletion of 50% and 75%, respectively. The fourth and fifth treatments were partial root zone drying irrigation (PRD) which was irrigated half area of plot to 75% and 50% of available water after depletion of 50% and 75%, respectively with half amount of irrigation water of the deficit irrigation treatments. The consumptive use was measured by the following method: FAO-PM grass, FAO-PM alfalfa equations and pan evaporation (Class A) method. The full irrigation treatment gave higher values for the following parameters (consumptive use, yield, biological yield and harvest index) and their values were (509.9 mm seasonˉ¹, 7600 Kg haˉ¹, 17683.3 Kg haˉ¹, 42.97%) respectively compared with the other treatments of the deficit and partial root zone drying irrigation treatments. The second and fourth treatments gave high values of field water use efficiency and third and fifth treatments gave high values of crop water use efficiency. Crop water use efficiency showed high values when the consumptive use was measured by pan evaporation method (Class A) through all irrigation treatments, while these values were decreased when the consumptive use was measured by the other methods. The values of yield response factor for all irrigation treatments were close to gether when the consumptive use was measured by the following methods: FAO-PM grass, FAO-PM alfalfa equations and pan evaporation (Class A) method. PRD treatments showed high concentration values of abscisic acid during the flowering stages (27.89 mg lˉ¹) for the fourth treatment and (36.71mg lˉ¹) for the fifth treatment, respectively. However the concentration value of this acid was lower in both full and deficit irrigation treatments compared with (PRD).

I

Introduction

INTRODUCTION Irrigated agriculture is the main user of the available water resources. About 70% of the total water withdrawals and 60-80% of total consumptive water use are consumed in irrigation (Huffaker and Hamilton, 2007). There is a conflict in global increase in food demand and decrease in water resources that should be resolved. Food security can be achieved by irrigated agriculture since irrigation on average double the crop yield compared to that usually is produced in rainfed conditions. The irrigated area should be increased by more than 20% and the irrigated crop yield should be increased by 40% by 2025 to secure the food for 8 billion peoples (Lascano and Sojka, 2007). Therefore, water resources should be used with a higher efficiency or productivity. To achieve this goal, improvement in agricultural water management is a promising way. Many investigations have been conducted to gain experiences in irrigation of crops to maximize performances, efficiency and profitability. However, investigations in water saving irrigation still are continued (Sleper et al., 2007). Full irrigation (FI) is used by farmers in non-limited or even water-limited areas. In this method, crops receive full evapotranspiration requirements to result the maximum yield. Nowadays, full irrigation is considered a luxury use of water that can be reduced with minor or no effect on profitable yield (Kang and Zhang, 2004). Water-saving irrigations are used to improve the water productivity (WP) in recent years. Deficit irrigation (DI) and partial root-zone drying irrigation (PRD) are the water-saving irrigation methods that cut down irrigation amounts of full irrigation to crops. The amounts of irrigation reduction is crop-dependent and generally accompanied by no or minor yield loss that increases the water productivity (Ahmadi et al., 2010a). Both (DI) and (PRD) are water-saving irrigation techniques being intensively studied in many regions of the world on a wide range of crops and fruit trees.

1

Introduction

Therefore this study was conducted and the primary objective was to use the (PRD) which is considered as a modified method of deficit irrigation and compared with the deficit and full irrigation methods and its effect on both water consumption and maize growth and yield.

2

Literature review

LITERATURE REVIEW 2.1 Deficit irrigation 2.1.1 Concept of deficit irrigation Deficit irrigation (DI) is a method of irrigation where the amount of water used is kept below the maximum level and the minor stress that develops has minimal effects on the yield. Studies have shown that DI is advantageous when properly applied. (English and Raja, 1996) described three DI case studies in which the reductions in irrigation costs were greater than the reductions in revenue due to reduced yields. DI can lead to increased profits where water costs are high or where water supplies are limited. Deficit irrigation has proved successful with a number of crops. These crops were relatively resistant to water stress, or they could avoid stress by deep rooting, giving access to soil moisture in deep soil layers. (Stegman,1982) reported that the yield of maize, sprinkler irrigated to induce a 30-40% depletion of available water between irrigations, was not statistically different from the yield obtained with trickle irrigation maintaining near zero water potential in the root zone. (Ziska and Hall, 1983) reported that cowpea had the ability to maintain seed yields when subjected to drought during the vegetative stage provided subsequent irrigation intervals did not exceed eight days. Similar findings have been reported for sugar beet (Winter, 1980) and wheat (Musick and Dusck, 1980). However, in drought susceptible crops like potatoes, deficit irrigation may be difficult to manage because reductions in tuber yield and quality can result from even brief periods of water stress following tuber set (Lynch et al., 1995), although in some cases, potatoes can tolerate limited deficit irrigation before tuber set without significant reductions in external and internal tuber quality (Shock et al., 1993). The Innovations for saving water irrigation agriculture and improving water use efficiency are of paramount importance in 3

Literature review

water-scarce regions. Conventional deficit irrigation program does not require the application of more than 50–70% of the water used in a fully irrigated program (Marsal et al., 2008). Deficit irrigation is one approach that can reduce water use without causing significant yield reduction (Kirda et al., 2005).

2.1.2 Advantages of deficit irrigation The advantages of correct applications of DI for certain crops (pandy et al., 2000; Fereres et al., 2007 and Greets et al., 2009) are: 

Maximization of the water productivity of water.



Allowing economic planning and stable income due to a stabilization of the harvest in comparison with rainfed cultivation.



Decreases the risk of certain diseases linked to high humidity (e.g. fungi) in comparison with full irrigation.



Reducing nutrient loss by leaching of the root zone, which results in better groundwater quality and lower fertilizer needs as for cultivation under full irrigation; and improves control over the sowing date and length of the growing period independent from the onset of the rainy season and therefore improves agricultural planning.

2.2 Partial root-zone drying irrigation (PRD) The irrigation technique for this method dependents on the regulation of the alternating wetting and drying process, so that each agricultural unit of land (furrows, strip, basin and border) is divided into two parts and the irrigation is after done 10 to 14 days depending on the soil type and crop beside the climate condition (Stoll et al., 2000) . On this aspect, only one part of the root zone will be irrigated with half amount of water and the other part will be left to drying to certain moisture content and then shifted the irrigation cycle to the other part and so on. In PRD treatment, one side of the row should be irrigated while the 4

Literature review

other kept dry. Shifting of PRD is depending on the water demand for irrigation, and usually is done when soil water content in dry side is reduced for 30% comparing to the wet side (after 5-10 days). PRD is commonly applied as part of a deficit irrigation program because it does not require the application of more than 50–70% of the water used in a fully irrigated program (Marsal et al., 2008), which involves irrigating only one part of the root zone in each irrigation event, leaving another part to dry to certain soil water content before rewetting by shifting irrigation to the dry side; therefore, PRD is a novel irrigation strategy since half of the roots is placed in drying soil and the other half is growing in irrigated soil (Ahmadi et al., 2010b)(Figure 1). Originally, the concept of PRD was first applied by (Grimes et al., 1968) in the USA on field cotton in alternate furrow irrigation and then followed by (Sepaskhah et al., 1976, Sepaskhah and Amin-Sichani 1976, and Samadi and Sepaskhah,1984) on beans through surface and subsurface drip irrigations in Iran. Later on, some extensive studies on PRD were conducted in Australia and the PRD term was used and developed for grape vines (Loveys et al., 2000 and Kriedmann and Goodwin, 2003).Wetting and drying each side of roots are dependent on crops, growing stage, evaporative demands, soil texture and soil water balance (Saeed et al., 2008). (Kriedmann and Goodwin, 2003) indicated that when soil water extraction from dry side is negligible, wetting should be changed from irrigated side to non-irrigated side. Abscisic acid (ABA) is a plant hormone that is produced in the roots in drying soils and is transported by water flow in xylem to the shoot for regulating the shoot physiology (Kang and Zhang, 2004). Therefore, in PRD roots sense the soil dried and induce ABA that reduce leaf expansion and stomata conductance and simultaneously the roots in wet soil absorb sufficient water to maintain a high water status in shoot (Zegbe et al., 2006; Liu et al., 2006a and Ahmadi et al., 2010a).

5

Literature review

(Figure 1): Schematic of the irrigation pattern in FI, DI, and PRD.

6

Literature review

2.2.1 Advantages of partial root zone drying irrigation 2.2.1.1 Chemical and hydraulic signaling in PRD Roots in drying soil produce more ABA than under normal conditions (Davies and Zhang, 1991) and it is moved as an anti-stress root chemical signal to shoot through transpiration stream and limits the stomatal conductance (Stoll et al., 2000; Kang and Zhang, 2004; Liu et al., 2005b; Liu et al., 2006a and Bauerle et al., 2006). It also resulted in leaf expansion rate in wheat (Ali et al., 1998), maize (Bahrun et al., 2002), soybean (Liu et al., 2005a), potato (Liu et al., 2006b), and tomato (Topcu et al., 2007). Decrease in leaf expansion declines the use of carbon and energy, and a higher proportion of the plant assimilates is distributed to the root system and support further root development (Taiz and Zeiger, 2006). At mild water stress, ABA is considered as a major chemical signal (CS) which acts earlier than the change in plant water status and hydraulic signal (HS). However, under severe water stress, both CS and HS may be involved in regulating plant physiological processes (Ali et al., 1999; Liu et al., 2003 and Liu et al., 2005b). In some plants CS and HS occur independent of each other, while in others they take place dependently (Tardieu and Davies, 1993; Comstock, 2002 and Wakrim et al., 2005). A balance between CS and HS occur in PRD. In PRD, roots on the irrigated side absorb enough water to maintain high shoot water potential, and the roots on the non-irrigated side produce ABA for possible reduction in stomata conductance. This mechanism optimizes water use and increases WP (Kang et al., 2000b; Sobeith et al., 2004; Zegbe et al., 2004; Zegbe et al., 2006; Liu et al., 2006b; Saeed et al., 2008 and Ahmadi et al., 2010b). Other chemical signals were reported to act such as pH, inorganic ion concentration, and other plant hormones (Wilkinson, 1999 and Stoll et al., 2000). Mild soil water stress reduces nutrient uptake and increases the xylem sap pH. This allows higher amounts of ABA in the leaf to be translocated to stomata through the transpiration stream (Davies et al., 2002; Dodd, 2003; Taiz 7

Literature review

and Zeiger, 2006). Higher pH in xylem sap considered as a drought signal for leaf elongation reduction through an ABA-dependent mechanism (Liu et al., 2003). It is also shown that xylem sap pH in barley (Bacon et al., 1998), maize (Bahrun et al., 2002), tomato (Halbrook et al., 2002 and Mingo et al., 2003), and soybean (Liu et al., 2003) increased as soil dried and this increase was correlated to increased ABA concentration in the xylem sap.

2.2.1.2 Root development and water uptake Root development and distribution are affected by spatial and temporal soil water distribution (Wang et al., 2006). Further, they affect water and nutrient uptake from the soil to maintain the physiological activities of the above-ground part of the crop. Mild water stress in soil leads to preferential root growth into the moist soil zone and water uptake through root system expansion and increasing root length density (RLD, cm root per cm³ soil) (Benjamin and Nielsen, 2006 and Songsri et al., 2008).Earlier studies indicated that PRD enhanced the extension and inhibition of primary and secondary roots, increased root growth, root mass, improve ABA-induced root hydraulic conductivity and increased the nutrient uptake(Kang et al., 2000b; Dry et al., 2000; Kang et al., 2000a; Mingo et al., 2004; Glinka, 1980; Taiz and Zeiger, 2006; Thompson et al., 2007 and Wang et al., 2009) respectively. Plant water uptake rate is enhanced after re-watering in water stress condition compared to full irrigation. This is obtained due to improvement of hydraulic conductivity of root system that is subjected to water stress (Kang and Zhang, 2004). This compensation in root hydraulic conductivity might be explained by new secondary roots and changes in the old roots when exposed to rewetting (Kang and Zhang, 2004). Furthermore, root hydraulic conductivity of apple, grape, peach and pear trees increased under restricted irrigation (Poni et al., 1992). It is proven by other studies that nutrient uptake is higher in PRD than FI for different field crops (Kirda et al., 2005; Li et al., 2007; Shahnazari et al., 8

Literature review

2008 and Wang et al., 2009). This is because the newly formed roots in PRD showed higher nutrient recovery from soil due to more available soil water (Kang and Zhang, 2004). The soil water in the irrigated side of PRD is depleted more effectively than corresponding side in FI (Kang et al., 2000b; Kang et al., 2003and Rodrigues et al., 2008). This indicated that the root system can partially compensate for the increasing limited water availability on the non-irrigated side of PRD due to an increase in root hydraulic conductivity. A larger hydraulic gradient in the soil-root interface was observed under PRD than under FI (Liu et al., 2006a). This explained the greater rate of water extraction from soil in PRD.

2.2.1.3 Increasing water productivity In the literature, the term "water use efficiency" (WUE) is interchangeably used for crop yield per unit evapotranspiration. In this article, "water productivity" (WP) is defined as crop yield per unit applied irrigation water that is looking into the efficiency of applied irrigation water (Zhang, 2003). Partial stomata closure and reduced leaf area occurred due to increased ABA. These are the main physiological responses to decrease transpiration in plants under PRD and enhance WP (Davies et al., 2002). Therefore, a higher WP (or WUE) is obtained (Morison et al., 2008). WP has been increased considerably by using PRD on different crops (Sepaskhah and Kamgar-Haghighi, 1997; Davies et al., 2002; Zegbe et al., 2004; Sepaskhah and Khajehabdollahi, 2005; Shani-Dashtgol et al., 2006; Fereres and Sariano, 2007; Costa et al., 2007; Shahnazari et al., 2007; Geerts and Raes, 2009 and Ahmadi et al., 2010b). Recently, in a metaanalysis Sadras (2009) confirmed that use of PRD enhanced WP by 82% compared to FI with no significant reduction in yields. However, Liu et al. (2006b) indicated that PRD was less effective than DI in enhancing WUE, and Wakrim et al. (2005) and Kirda et al. (2005) confirmed that PRD resulted in 9

Literature review

lower WUE than DI in beans and maize, respectively. Nevertheless, more positive effect on fruit quality was occurred in PRD than in DI (Kang and Zhang, 2004; Kirda et al., 2004; Zegbe et al., 2004; Leib et al., 2006 and Shahnazari et al., 2007).

2.2.2 Effect of partial root zone drying in agriculture 2.2.2.1 Maize Applied partial root zone drying irrigation (PRD) in irrigated maize in an arid region in China. Irrigation was applied to furrow in three ways: alternate furrow irrigation (AFI), fixed furrow irrigation (FFI), and conventional furrow irrigation (CFI). Each irrigation method was further divided into three treatments with different irrigation amounts (45, 30, 22.5 mm). Furthermore, AFI maintained high grain yields coupled with a 50% reduction in the amount of irrigation water, while FFI and CFI both revealed a substantial reduction in yield with reduced irrigation water (Kang et al., 2000a and Kang et al., 2000b). PRD in a semi-arid region resulted in an average of 28% reduction in maize grain yield (reproductive crop and highly sensitive to water stress) with an average of 31% reduction in applied water at customized 7-day irrigation intervals (Sepaskhah and Khajehabdollahi, 2005). They showed the effects of partial root zone drying irrigation and conventional furrow irrigations on maize grain yield and WP at different irrigation intervals of 4, 7, and 10 days. It was indicated that partial root zone drying irrigation at 4-day intervals reduced the applied water by 6% with no grain yield reduction compared with conventional furrow irrigation at 7-day intervals.

(Sepaskhah and Parand, 2006) studied the effects of

alternate-furrow irrigation with supplemental every-furrow irrigation at different growth stages on grain yield of maize in a semi-arid region. The results indicated that under alternate-furrow irrigation with once or twice every-furrow irrigation at the tasseling or silking stages grain yields were statistically equal (about 11% reduction) to those obtained in every-furrow irrigation although the 01

Literature review

amounts of water used was 30% lower. (Yazar et al, 2009) showed the highest water use was observed in FI as 677 mm, the lowest was found in PRD-50 as 375 mm. PRD-100 and DI-50 resulted in similar water use (438 and 445 mm). The maximum grain yield was obtained from the FI as 10.40 t/ha, while DI-50 and PRD-100 resulted in similar grain yields of 7.72 and 7.74 t/ha, respectively. There was a significant difference among the treatments with respect to grain yields (P < 0.01). The highest water use efficiency (WUE) was found in PRD100 as 1.77 kg mˉ³, and the lowest one was found in FI as1.54 kgmˉ³. (Masoud and Ghodratolah, 2010) showed that there were no difference between both fixed furrows irrigation (FFI) and alternate furrows irrigation (AFI), but the performance of them decreased irrigated water at the rates of 26.2% and 23%,respectivelycomparing with FI and then yield at the rates of 11% and 13.6%, respectively. In this respect, FFI resulted in the highest water use efficiency for biological yield of (4.4 kg mˉ³) and economical (grain) yield of (1.91 kg mˉ³).

2.2.2.2 Other crops, vegetable and trees Sepaskhah and Ghasemi, (2008) studied the effects of partial root zone drying irrigation, and conventional furrow irrigations on grain yield and WP of grain sorghum at different irrigation intervals of 10, 15, and 20 days. It was indicated that partial root zone drying irrigation at 10-day intervals reduced the applied water by 11% with no yield reduction compared with conventional furrow irrigation at 15-day intervals. Partial root zone drying irrigation is also effective in increasing WP in winter wheat (reproductive crop) grown under rain-fed conditions with supplemental spring irrigation (Sepaskhah and Hosseini, 2008). For dry beans, Samadi and Sepaskhah (1984) studied PRD under furrow irrigation in a semi-arid area. They found 38% grain yield reduction under alternate furrow irrigation with 22% less water application. 00

Literature review

(Tang et al., 2005) reported that PRD reduced irrigation by 30% while cotton seed yield was reduced by 8% that was not statistically different from that in FI. The effects of PRD on physiological responses of potato in field conditions were studied and shown that both DI and PRD significantly reduced tuber yield compared with FI (Liu et al., 2006). Furthermore, PRD and DI used 37% less water than FI; however, WUE was similar for PRD and FI and significantly decreased in DI. (Jovanovic et al. 2010) reported that PRD saved irrigation water by 33% and 42% in potato in two consecutive years compared to FI. This resulted in 38% and 61% increase in WP for the two growing seasons, respectively. (Zegbe et al., 2004) conducted study on tomato using full irrigation (FI) and 50% of FI water applied as PRD. They showed that the fruit yields were the same for the treatments, but WUE for PRD plants were 70% higher than that obtained for FI plots. Most PRD studies on woody crops were done on grapes that seem to respond well to this kind of deficit irrigation strategy (Fernandez et al., 2006). The studies on grapes are exhaustive and there are many reports on the successful application of PRD on grapes in terms of increasing WP and fruit quality (Kang and Zhang, 2004 and Sadras, 2009). Partial root zone drying irrigation was compared with the fixed partial root zone irrigation (FPRD) and whole root zone irrigation (WRI) in a pear orchard in Australia using a flood irrigation system (Kang et al., 2002). The results indicated that yield was not reduced while the applied irrigation water was decreased by 52% and 23% and water use efficiency was increased by 28% and 12% in FPRD and PRD, respectively, compared with WRI. The first evaluation of PRD on olive trees was done by (Wahbi et al., 2005). They showed that PRD could maintain the yield and fruit quality, while reducing half of the irrigation water. They showed that the slight PRD-induced yield reduction (15-20%) compared to the full irrigation was achieved with 50% 01

Literature review

reduction in the total amount of water applied, which resulted in a water use efficiency increase by 60-70% under PRD compared to the FI.

2.3 Water use efficiency Water Use Efficiency (WUE) or water productivity has emerged from the ideas of drought resistance and drought tolerance (Passioura, 2006). At the beginning of the sixties of the last Century, water use efficiency has been generally defined in agronomy (Viets, 1962) as:

The term Water Use Efficiency can be used at wide range of scales; for example, it can be used at the farm, the field, the plant, or down to plant parts level, such as the leaf (Morison et al., 2008). In agriculture, WUE can be used at different levels; at leaf level (leaf photosynthesis rate per transpiration rate), at whole plant level (the ratio of total dry mass to water use) and at the final economic yield (crop grain per unit area to transpiration) (Hong-Xing et al., 2007; Ali and Talukder, 2008). Water productivity or water use efficiency has different meanings to different people (Pereira et al., 2002; Kijne et al., 2003; Passioura, 2006 and Ali and Talukder, 2008). For example, to irrigation engineer can mean the amount of water used to produce a crop (Ali and Talukder, 2008). The different proposed definitions of WUE are difficult to apply because a number of management factors can affect yield between irrigated and dry land agriculture. These factors include fertility, crop variety, pest management, sowing date, soil water content, planting density and rows pacing (Howell, 2001). In crop production, the aim of improving WUE, is to produce more economic yield with less water when water is a limiting factor (Boutraa and Sanders, 2001; Boutraa, 2010), such as in arid and semi arid regions across the globe. In crop production, WUE can be expressed by different indicators resulting in different options (Ali and Talukder, 2008): 03

Literature review

……. . (4) Equations 2 and 3 are appropriate in a single crop, while Eq. 4 is more appropriate for multiple cultures or under limiting water conditions without limiting land (Ali and Talukder, 2008). There is a substantial scope to improve water use efficiency in both rainfed and irrigated agriculture; particularly in Sub Saharan Africa and South Asia where crop production is reduced because of poor soil nutrient and low water supply (Rockstrom et al., 2003; Nangia et al., 2008).

2.4 Water saving Water saving agriculture, is a notion to describe the combination of agronomic, physiological, biotechnological/genetic and engineering approaches to reduce agricultural water use (Morison et al., 2008). Many workers focused on reducing the use of irrigation in hot, dry environment, as in these environments agricultural products require high water use due to the high rate of evapotranspiration (Wallace, 2000 and Gregory, 2004). Improving water use efficiency implies how effectively we can increase the outcome of the crop with the current available water (Passioura, 2006; Ali and Talukder, 2008). At the global level, the major grain exporters (USA, Canada, France, Australia and Argentina) produce grains in highly productive rainfed lands and the major grain importers rely on irrigation to produce grains (De Fraiture and Wichelns, 2010). The main strategy that needs to be implemented in improving water productivity in rainfed agriculture is the wise management of crops and water resources in addition to the improvement of the genetic makeup of crops to maximize the 04

Literature review

capture of water in plant biomass production (Passioura, 2006). Whereas, in irrigated land, there is a need to better manage and use water efficiently, not only because of water shortage but also to maintain and reserve the environment (Karoun and El-Mourid, 2009). Farmers are required to be motivated in order to increase water productivity through technical assistance, capacity building and the right incentives and policies (De Fraiture and Wichelns, 2010). Improving crop water productivity relies not only on water management, but it involves a range of practices. (Ali and Talukder, 2008) summarized the techniques and practices that can be used to improve water productivity. These include: deficit irrigation, proper sequencing of water deficit, surge irrigation in vertisol, increasing soil fertility, improving harvest index, manipulation of seedling age, wet-seeded or directed seeded rice, priming or soaking of seed, application of organic matter, tillage and sub-soiling, water harvesting, minimizing the transpiration, water saving irrigation, crop selection, modernization of irrigation system and integrating agriculture-aquaculture.

2.5 Inducement of abscisic acid under deficit irrigation 2.5.1 Abscisic acid Unlike the auxins, gibberellins, and cytokinins the abscisic acid is a single compound, originally because it was thought to play a major role in abscission of fruits. At about the same time, another group called it "dormin" because they thought to have a major role in bud dormancy. The name Abscisic acid (ABA) was coined by a compromise between the two groups. The ABA was generally thought to play mostly inhibitory roles, but had many promoting functions as well (Arteca, 1996).

05

Literature review

2.5.2Functions of Abscisic acid It is widely believed that the production of abscisic acid (ABA) in the drying roots and its transport to the leaves in the xylem stream play a dominant role in the chemical signaling of soil water status and in the control of stomata conductance ( Liu et al., 2005 and Dodd, 2007). Earlier studies have shown that both PRD and DI can induce the ABA-based root-to-shoot chemical signals regulating stomatal conductance and leaf expansion growth thereby increasing water use efficiency (WUE) (Dodd, 2007 and Wang et al., 2010a). However, accumulated evidence indicated that, at a similar degree of soil water deficit in the whole root zone, PRD plants process greater xylem ABA concentrations relative to DI plants and hence lead to a better control of plant water loss thereby causing further improvement to WUE (Dodd, 2007; 2009 and Wang et al., 2010a). In addition to ABA acting as the root-to-shoot signal, changes in the pH of the xylem sap commonly observed under drought stress can be another important signaling molecule and may act synergistically with ABA signaling. In many plant species, xylem sap pH becomes more alkaline when plants are drought-stressed, which leads to the accumulation of ABA in the apoplast resulting in enhanced stomatal closure and even reduced growth ( Davies et al., 2002).

2.6 Evapotranspiration Evapotranspiration (ET), also known as consumptive use (Watson and Burnett 1995), is the sum of the amount of water returned to the atmosphere through the processes of evaporation and transpiration (Hansen et al., 1980). The evaporation component of ET is comprised of the return of water back to the atmosphere through direct evaporative loss from the soil surface, standing water (depression storage), and water on surfaces (intercepted water) such as leaves or roofs (Hansen et al., 1980). Transpired water is that which is used by vegetation and subsequently lost to the atmosphere. This water enters the plant 06

Literature review

through the root zone, is used for various biological functions including photosynthesis, and then passes back out through the leaf stomates (Hansen et al., 1980). Transpiration will stop if the vegetation becomes stressed to the wilting point, which is the point in which there is in sufficient water left in the soil for a plant to transpire (Watson and Burnett 1995). The process of ET in general is controlled by several variables. For example, meteorological variables such as solar radiation, temperature, humidity, and wind speed all have significant roles in determining ET (Dingman, 1994, Allen et al., 1998 and Geiger, 2003). In addition, physical attributes of the vegetation and soil also are important to the ET process. For example, leaf shape, growth stage, crop height, and leaf albedo all are important factors in controlling transpiration functions (Allen et al. 1998). In water deficit settings, ET will be less than fully-irrigated conditions because deficit-irrigated plants cannot transpire water at the same rate as fully-watered, healthy, and actively growing plants (Irmak, 2009). In addition, stomata resistance is an important variable. Stomata resistance refers to the restriction of the guard cells around the opening of the stomata to the diffusion of water vapor back to the atmosphere (Geiger et al., 2003). Finally, soil characteristics such as heat capacity, albedo, and soil chemistry all can affect ET (Allen et al., 1998). These factors, combined with stomata resistance, are combined into a single term called the bulk surface resistance (Allen et al., 1998).

2.6.1 Reference evapotranspiration (ETo) Reference evapotranspiration (ETo) is the rate at which readily available soil water is vaporized from specified vegetated surfaces (Jensen et al., 1990). For convenience and reproducibility, the reference surface has recently been expressed as

a hypothetical crop (vegetative) surface

with specific

characteristics (Allen et al., 1994 and Allen et al., 1998). 07

Reference

Literature review

evapotranspiration is defined as the uniform surface of dense, actively growing vegetation having specified height and surface resistance, not short of soil water, and similar vegetation. Two surfaces have been used commonly as a reference surface: short clipped grass (0.12m) and alfalfa (0.50m) (Penman 1948, Blaney and Criddle 1950, Jensen and Haise 1963, Hargreaves 1974, Doorenbos and Pruitt 1977, Linacre 1977, Jensen et al., 1990, Allen et al., 1994, Allen et al., 1998, Pereira et al., 1999). Researchers have tended to choose the reference surface (grass or alfalfa) based on the availability of relevant data. Alfalfa has bulk stomata resistance and exchange values that are similar to many agricultural crops, but more experimental data exist on short clipped grass. Therefore, grass was selected as the primary reference surface by the FAO for international use (Pereira et al., 1999). Reference evapotranspiration from each of the two surfaces is modeled using a single Standardized Reference Evapotranspiration equation with appropriate constants and standardized computational procedures. As a part of the standardization, the ASCE Penman-Monteith (ASCE-PM) equation (Jensen et al., 1990) and associated equations for calculating aerodynamic and bulk surface resistance have been combined and condensed into a single equation that is applicable to both surfaces(Allen, et al., 2005).

2.6.2 Crop evapotranspiration under standard conditions (ETc): The crop evapotranspiration under standard conditions, denoted as (ETc) is the evapotranspiration from disease-free, well-fertilized crops, grown in large fields, under optimum soil water conditions, and achieving full production under the given climatic conditions (Allen et al., 1998).

08

Literature review

2.6.3 Crop coefficient Evapotranspiration for a specific crop, ET c, is estimated by multiplying the reference evapotranspiration, ETo, by a crop coefficient, Kc. Hence: ETc = Kc ETo ………… (5) Where

ETc : crop evapotranspiration, mm dˉ¹ Kc : crop coefficient ETo : reference evapotranspiration, mm dˉ¹

Crop coefficients (Kc) are dependent on crop type, stage of growth, canopy configuration and regional climate. Throughout the growing cycle, K c will change, increasing as the leaf area of the crop increases to a plateau when LAI > 3, then decreasing during senescence as the area of green leaf decreases. Crop coefficients values that can be used with (ET os) without adjustment include those reported in FAO-56 (Allen et al., 1998) and ASCE Manual 70 (Jensen et al., 1990). Crop Coefficients that can be used as is with ETos for most practical applications are those reported by FAO-24 (Doorenbos and Pruitt, 1977 and Martin and Gilley, 1993). Crop Coefficients based on the CIMIS Penman equation (Snyder and Pruitt, 1992) should not require adjustment for use with ETos. Kc values that can be used as is with (ET oT) for most practical applications are those reported by Wright (1982) and ASCE Manual 70 (Jensen et al., 1990). There is a tendency for relatively minor overestimation of ET using (Kc) from Wright (1982) with (EToT) in spring and fall. Thus, the (Kc) values by Wright (1981, 1982) have been converted for direct use with (ET oT), (Allen and Wright, 2002).

2.6.4 Crop evapotranspiration under non-standard conditions (ETc adj): The crop evapotranspiration under non-standard conditions (ETc adj) is the evapotranspiration from crops grown under management and environmental conditions that differ from the standard conditions. When cultivating crops in 09

Literature review

fields, the real crop evapotranspiration may deviate from ETc due to non-optimal conditions such as the presence of pests and diseases, soil salinity, low soil fertility, water shortage or water logging. This may result in scanty plant growth, low plant density and may reduce the evapotranspiration rate below ET c. The crop evapotranspiration under non-standard conditions is calculated by using a water stress coefficient Ks and adjusting Kc for all kinds of other stresses and environmental constraints on crop evapotranspiration (Allen et al., 1998) ETc adj = ETo Kc Ks ……………. (6) Where

ETc adj : adjust crop evapotranspiration, mm dˉ¹ Ks : water stress coefficient

2.6.5 Total available water (TAW) After heavy rainfall or irrigation, the soil will drain until field capacity is reached. Field capacity is the amount of water that a well-drained soil should hold against gravitational forces. In the absence of water supply, the water content in the root zone decreases as a result of water uptake by the crop. As water uptake progresses, the remaining water is held to the soil particles with greater force, lowering its potential energy and making it more difficult for the plant to extract it. The water uptake becomes zero when wilting point is reached. Wilting point is the water content at which plants will permanently wilt (Allen et al., 1998). The total available soil water or plant extractable water is the amount of water a crop can theoretically extract from the root zone. Since (i) the water content above field capacity cannot be retained in the soil and will be lost by drainage, and (ii) the water content below permanent wilting point is so strongly attached to the soil matrix that it cannot be extracted by plant roots, the total available soil water is the amount of water held in the root zone between field capacity and permanent wilting point (Dirk et al., 2010)

11

Literature review

Where

TAW : Total available water (mm) θv fc : Volumetric water content at field capacity (m³ mˉ³) θv wp : Volumetric water content at wilting point (m³ mˉ³) Zr: Effective root zone depth (m)

2.6.6 Readily available water (RAW) Although water is theoretically available until wilting point, crop water uptake is reduced well before wilting point is reached. Where the soil is sufficiently wet, the soil supplies water fast enough to meet the atmospheric demand of the crop, and water uptake equals ETc. As the soil water content decreases, water becomes more strongly bound to the soil matrix and is more difficult to extract. When the soil water content drops below a threshold value, soil water cannot longer be transported quickly enough towards the roots to respond to the transpiration demand and the crop begins to experience stress. The fraction of TAW that a crop can extract from the root zone without suffering water stress is the readily available soil water (Allen et al., 1998) that can be calculated by following equation:

Where

RAW: Readily available water, mm : Depletion coefficient

2.6.7 Depletion coefficient ( ) Average fraction of total available soil water (TAW) that can be depleted from the root zone before moisture stress (reduction in ET) occurs. Values for (ptable22) which taken from (Allen et al, 1998, Table 22)(appendix 10). The factor (p) differs from one crop to another. The factor (p) normally varies from 0.30 for shallow rooted plants at high rates of ETc (> 8 mm d-1) to 0.70 for deep rooted plants at low rates of ET c (< 3 mm d-1). A value of 0.50 for p is commonly used for many crops. 10

Literature review

The fraction (p) is a function of the evaporation power of the atmosphere. At low rates of ETc, the p values are higher than at high rates of ETc. For hot dry weather conditions, where ETc is high, p is 10-25% less than the table values, and the soil is still relatively wet when the stress starts to occur. When the crop evapotranspiration is low, (p) will be up to 20% more than the table values. Often, a constant value is used for p for a specific growing period, rather than varying the value each day. The value for (p) can be adjusted for different ET c according to a numerical approximation (Allen et al., 1998): p = pTable22 +0.04(5-ETc) ………… (9) Where

pTable22: (0.55) for maize crops ETc : crop evapotranspiration, mm dˉ¹

2.6.8 Water stress coefficient (Ks) The effects of soil water stress on crop ET are described by reducing the value for the crop coefficient. This is accomplished by multiplying the crop coefficient by the water stress coefficient. Water content in root zone can also be expressed by root zone depletion (Dr). At field capacity, the root zone depletion is zero (Dr = 0). When soil water is extracted by evapotranspiration, the depletion increases and stress will be induced when Dr becomes equal to RAW. After the root zone depletion exceeds RAW (the water content drops below the threshold

t)

(Allen et al., 1998). Above the upper threshold of soil

water content, water stress is nonexistent and Ks are (1). Below the lower threshold, the effect is maximum and Ks is (0), (Dirk, 2010). For Dr > RAW, Ks are given by: Ks Where

Ks: crop stress coefficient Dr: root zone depletion, mm 11

Literature review

2.6.9 Yield-moisture stress relationship A simple, linear crop-water production function was introduced by (Doorenbos and Kassam, 1979) to predict the reduction in crop yield when crop stress was caused by a shortage of soil water:

Where

: actual yield for treatment under stress, Kg hˉ¹ : Maximum yield under full evapotranspiration, Kg hˉ¹ : adjust evapotranspiration, mm dˉ¹ : Maximum evapotranspiration, mm dˉ¹

The crop yield response factor is a factor that describes the reduction in relative yield according to the reduction in relative ETc caused by soil water shortage. The crop yield response factor gives an indication of whether the crop is tolerant of water stress. A response factor greater than unity indicates that the expected relative yield decrease for a given evapotraspiration deficit is proportionately greater than the relative decrease in evapotranspiration (Kirda et al., 1999). In general, the decrease in yield due to water deficit during the vegetative and ripening period is relatively small, while during the flowering and yield formation periods, it will be large.

2.7 Methods of determination of reference evapotranspiration: 2.7.1 Direct methods 1- Lysimeters 2- Soil moisture 3-Experimental plot

13

Literature review

2.7.2 Indirect method According to Xinhua, 2007 the methods can be divided in to four groups:

1. Equation dependent on temperature: A- Jensen-Haise Model: Under situation of limited data, Jensen-Haise model is used for computing reference evapotranspiration as reported by (James, 1988) and is given as: ………….. (12) Where

Where

: reference evapotranspiration (mmdˉ¹) : Maximum air temperatures (°C) CT CT and are constants expressed as:

h: altitude of location (m) : Saturation vapor pressure at maximum air temperatures (KPa). : Saturation vapor pressure at minimum air temperatures (KPa).

B- FAO-24 Blaney-Criddle Models: (Doorenbos and Pruitt, 1977) presented the most fundamental revision of the Blaney-Criddle model since its introduction. The FAO-24 Blaney- Criddle model estimates a grass related reference crop evapotranspiration. The FAO-24 Blaney-Criddle model is based on the general linear relationship found between measured reference evapotranspiration and the Blaney-Criddle factor from many worldwide sites in various classifications based on ranges of daytime wind speed, minimum RH and sunshine expressed as n/N. The model is presented as follows …….. (13)

14

Literature review

b = 0.908 - 0.00483 RH

min

+ 0.7949 n/N + 0.768[ln (Ud+1)] ² - 0.0038 RH min

n/N - 0.000443 RH min. Ud+0.281[ln ( +1)] - 0.00975[ln (Ud+1)] [ln (RH min +1)]² [ln ( +1)] Where

RH min: minimum relative humidity (%) : Ratio of possible to actual sunshine, (hours) Ud : daytime wind speed at 2 m (m sˉ¹).

C- Hargreaves-Samani (1982): Parameters required (Net radiation, min/max temperature). ….. (14) Where

= reference evapotranspiration (mm dˉ¹) : Average air temperature (°C) Tmax: maximum temperature (°C) Tmin: maximum temperature (°C) Ra: is the extraterrestrial radiation (MJ mˉ²dˉ¹)

2. Equation dependent on radiation: A- Priestley-Taylor Model: (Priestley and Taylor, 1972) proposed a simplified version of the combination equation for use when surface areas are generally wet, which is a condition required for reference evapotranspiration. The aerodynamic component was multiplied by a coefficient

1, when general surrounding areas were wet or

under humid conditions. The model is given as follows. …… (15) Where

ET: evapotranspiration (mm day-1) = 1.26 : slope of the saturation vapor pressure function (kPa °Cˉ¹) Rn: net radiation (MJ mˉ² dˉ¹) G: soil heat flux density (MJ mˉ² dˉ¹) : psychometric constant (kPa °Cˉ¹) 15

Literature review

3. Pan evaporation equation: B- Christiansen Pan Evaporation Model: Christiansen equation for estimation of (ETo) is presented in (Jensen et al., 1990) in a following way: ETo = 0.755Ep Ct Cu Ch Cs…….. (16) The coefficients are dimensionless

Where T is the mean temperature (°C) and To = 20°C

Where U = is the mean wind speed at 2 m height (km hˉ¹) and Uo = 6.7 km hˉ¹. Ch Where, H is the mean relative humidity expressed decimally and Ho = 0.60 Cs Where S = percentage of possible sunshine, expressed decimally and So = 0.8.

C- FAO - 24 Pan Evaporation Model: Doorenbos and Pruitt, (1977) provided detailed guidelines for using evaporation data to estimate reference evapotranspiration. The FAO-24 coefficients relating USWB Class-A pan data to evapotranspiration from short (15-88 cm) irrigated grass turf are given. Some adjustments would be needed to relate to Kp for a taller reference crop (that is, alfalfa with full cover conditions) especially in hot, drier climates where height of crop and aerodynamic roughness have a greater effect on evapotranspiration than in humid climates. For taller and aerodynamically rougher crops, the values of Kp would be higher

16

Literature review

and would vary less with differences in weather conditions as compared to values for shorter and smoother grass surfaces. The relationship is as follows

Where

: reference evapotranspiration (mm dˉ¹), Kp: pan coefficient, Epan: pan evaporation from (mm dˉ¹).

Evaporation pans have been used to measure evaporation for over a century. The pan is regularly filled to a specified height, and the water loss (equal to evaporation) noted. The pan (Class-A) is considered to be the standard international pan. (Jones, 1992) suggests that the rate of evaporation depends on the: type of pan, type of pan environment, method of operating the pan, exchange of heat between pan and ground, solar radiation, air temperature, wind and temperature of the water surface. Pan evaporation rates are different to evapotranspiration rates. (Allen et al., 1998) provides a series of equations for Kp for different ground cover, fetch and climatic conditions. 4. Complex equation dependent on energy balance and mass transpiration (penman, 1948).

A- Penman FAO-24 Model: (Penman, 1948) originally proposed an equation for estimating evaporation from free-water surface and then applied empirical coefficients to convert estimated evaporation to reference evapotranspiration from vegetated surfaces. Penman assumed that the heat flux into and out of the soil is small enough to be conveniently ignored. By combination method, the reference evapotranspiration rate from a short green crop completely shading the ground and never short of Water is expressed in generalized form as follows (Doorenbos and Pruitt, 1977).

Where

ETo: reference evapotranspiration (mm dˉ¹) : Latent heat of vaporization (MJ kgˉ¹) : slope of the saturation vapor pressure function (kPa °Cˉ¹) 17

Literature review

Rn: net radiation (MJ mˉ² dˉ¹) G: soil heat flux density (MJ mˉ² dˉ¹) : psychometric constant (kPa °Cˉ¹) T: mean air temperature (°C) : Average 24-hour wind speed at 2 m height (m sˉ¹) : Vapor pressure deficit (kPa).

B- Penman-Monteith FAO-56 Model: Penman, (1948) did not include a surface resistance function for water vapour transfer. For practical applications, he proposed an empirical equation for the wind function. The combination equation with aerodynamic and surface resistance term is called the Penman-Monteith equation. This equation does not reconcile thermodynamic resistance to sensible heat and vapour transfer, and surface resistance to vapour transfer. The resulting model represents a basic general description of the evapotranspiration process as follows.

…………….. (20) Where : mean air density (kg mˉ³) cp : specific heat of air (J kgˉ¹ kˉ¹) ra and rs are the aerodynamic and surface resistances (s mˉ¹) Zm: the height of the wind measurement (m) Zh: the height of the humidity measurement (m) d : the zero plane displacement height (m) Zom: is the roughness length governing momentum transfer Zoh: is the roughness length governing heat and vapor transfer K: is von Karman’s constant (0.41) Uz: is the wind speed at height z. ‫٭‬ To adjust wind speed data obtained at elevations other than the standard height of 2 m, following equation is used (Allen et al., 1998) 18

Literature review

U2 = U z

............... (21)

Where U2 : wind speed at 2 m above ground surface (m sˉ¹) Uz : measured wind speed at m above ground surface (m s-1) Zw : height of wind measurement above ground surface (m)

C- Kimberly-Penman Model: Wright, (1982) presented variable wind function coefficients for reference evapotranspiration at Kimberly, Idaho, USA, expressed as fifth-order polynomials with calendar day, D, as the independent variable. The resulting equations were later simplified and known as Kimberly-Penman model. The model is given as follows.

Wf

‫٭‬

Wf = aw + bwU2 aw bw

}

D- ASCE Standardized penman montith (ASCE-EWRI,2005): The

ASCE

TC

standardized

procedure

computing

reference

evapotranspiration based on the Penman-Monteith and more specifically on simplifying the version of the Penman Monteith Equation recommended by ASCE (Jensen et al., 1990). The recommended general procedure is provided below

Rn …….. (23) 19

Literature review

Over the last 60 years, a large number of (ETo) methods have been developed. These methods are generally categorized as temperature, radiation, and combination-based according to the type of input data required. It is well recognized that if ET calculated by different methods, and for the same location and using the same meteorological dataset large variations will be obtained (Liu and Lin, 2005 and Suleiman and Hoogenboom, 2007) combination based Penman equation is considered the best method (Allen et al., 1998) across a wide range of climates and is recommended by the FAO as the standard method. Currently the standardized reference evapotranspiration equation has been recommended for use by the American Society of Civil Engineers (ASCE 2005). This method is a variation of the P-M method and attempts to standardize the use of one method among many users. The equation provides a recommended determination of reference ETo for a well-watered short or tall surface. It needs to be recognized that there is a difference between that of 'potential evapotranspiration' and that of 'reference evapotranspiration'. Potential ET is that considered from a wet surface that is non-specific as to crop type. Reference ET refers to the ET from a reference grass surface of specific characteristics and that is well watered (Allen et al.1998). The modern combination equation applied to standardized surfaces is currently referred to as the Penman-Monteith equation (P-M). It represents the state of the art in estimating hourly and daily ET. When applied to standardized surfaces it is now called the Standardized Reference ET Equation (ASCE-EWRI 2005). Daily (ETsz) was calculated from weather data using the standardized Reference Evapotranspiration Penman-Monteith method (ASCE-EWRI, 2005) as used the term (ETsz) refers to both (ETos) and (EToT). The value of (Cn) is a function of the time step and aerodynamic resistance (i.e., reference type) and (Cd) is a function of the time step, bulk surface resistance, and aerodynamic resistance presented in appendices (5 and 6). 31

Literature review

Mean saturation vapor pressure (es) Saturation vapor pressure represents the capacity of the air to hold water vapor. It can be calculated from the air temperature (Jensen et al., 1990). By the following equation:

Where : Saturation vapor pressure function (kPa) The mean saturation vapor pressure for a day, week, or month should be computed as the mean between the saturation vapor pressure at the mean daily maximum and minimum air temperatures for that period:

Slope of saturation vapor pressure curve (Δ) The slope of the saturation vapor pressure,

, can be calculated from the

mean temperature (Tmean) as follows (Murray, 1967):

Where = slope of the saturation vapor pressure-temperature curve (kPa °Cˉ¹) Actual vapor pressure (ea) derived from relative humidity data The actual vapor pressure can be calculated from the relative humidity (Allen et al., 1998). For RHmax and RHmin:

30

Literature review

Where : Actual vapor pressure [kPa], : Saturation vapor pressure at daily minimum temperature (kPa) ): saturation vapor pressure at daily maximum temperature (kPa) = daily maximum relative humidity (%) = daily minimum relative humidity (%) Vapor pressure deficit (VPD) The vapor pressure deficit is the difference between the saturation (e s) and actual vapor pressure (ea) for a given time period (Allen et al., 1998).

Extraterrestrial radiation for daily periods (Ra) The extraterrestrial radiation, Ra, for each day of the year and for different latitudes can be estimated from the solar constant, solar declination and the time of the year (Duffie and Beckman, 1980) by:

Where: Ra: extraterrestrial radiation [MJ mˉ² dˉ¹], Gs: solar constant [4.92 MJ mˉ² hˉ¹], dr: inverse relative distance factor (squared) for the earth-sun [unitless], ωs: sunset hour angle [radians], ϕ: latitude [radians], and δ: solar declination [radians]. The conversion from decimal degrees to radians is given by:

The inverse relative distance Earth-Sun, dr, and the solar declination () are given by:

31

Literature review

Where J is the number of the day in the year between 1 (1 January) and 365 or 366 (31 December). Values for J for all days of the year and an equation for estimating J are given in (Appendicse 7). The sunset hour angle

is given by:

Daylight hours (N) The daylight hours, N, are given by:

Where (

) is the sunset hour angle in radians. Mean values for N (15th day

of each month) for different latitudes are given in (Appendicse 8). Solar radiation (Rs) If the solar radiation, Rs, is not measured, it can be calculated with the Angstrom formula which relates solar radiation to extraterrestrial radiation and relative sunshine duration (Allen et al., 1998):

Clear-sky solar radiation (Rso) The calculation of the clear-sky radiation, Rso, when n = N, is required for computing net long wave radiation (Allen et al., 1996). 33

Literature review

Where: : Clear-sky solar radiation (MJ mˉ² dˉ¹) Z : station elevation above sea level (m) : Extraterrestrial radiation (MJ mˉ² dˉ¹) Net solar or net shortwave radiation (Rns) The net shortwave radiation resulting from the balance between incoming and reflected solar radiation (Jensen et al., 1990 and Wright., 1982) is given by:

Where: : Net solar or short-wave radiation (MJ mˉ² dˉ¹) : albedo or canopy reflection coefficient is fixed at 0.23 for the standardized short and tall reference surfaces (dimensionless) : The incoming solar radiation (MJ mˉ² dˉ¹) Net long wave radiation (Rnl) The rate of long wave energy emission is proportional to the absolute temperature of the surface raised to the fourth power. This relation is expressed quantitatively by the Stefan-Boltzmann law (Jensen et al., 1990 and Allen et al., 1998):

Where : Net outgoing long-wave radiation (MJ mˉ² dˉ¹) σ: Stefan-Boltzmann constant [4.901 x 10-9 MJ Kˉ mˉ² dˉ¹] : Cloudiness function (dimensionless) (limited to 0.05 ≤ fcd ≤ 1.0), : Actual vapor pressure (kPa)

34

Literature review

: Maximum absolute temperature during the 24-hour period (K), [K = °C + 273.16] ( ): Minimum absolute temperature during the 24-hour period (K), [K = °C + 273.16] An average of the maximum air temperature to the fourth power and the minimum air temperature to the fourth power is commonly used in the StefanBoltzmann equation for 24-hour time steps. The term expresses the correction for air humidity, and will be smaller if the humidity increases. The effect of cloudiness is expressed by (1.35 R s/Rso - 0.35). The term becomes smaller if the cloudiness increases and hence R s decreases. The smaller the correction terms, the smaller the net outgoing flux of long wave radiation. (Appendix 9) lists values for

for different air temperatures.

Net radiation (Rn) The net radiation (Rn) is the difference between the incoming net shortwave radiation (Rns) and the outgoing net long wave radiation (R nl) (Jensen et al., 1990 and Wright., 1982):

Soil heat flux (G) When assuming a constant soil heat capacity of 2.1 MJ m-3 °C-1 and an appropriate soil depth (Jensen et al., 1990).

Or, if Tmonth, i+1 is unknown:

Where T month,i mean air temperature of month i (°C) 35

Literature review

T month,i -1 = mean air temperature of previous month (°C) and T month,i +1 = mean air temperature of next month (°C) Atmospheric pressure (P) The mean atmospheric pressure at the weather site is predicted from site elevation using a simplified formulation of the Universal Gas Law (Burman et al., 1987):

Where: P = mean atmospheric pressure at station elevation z (kPa) z = weather site elevation above mean sea level (m). Latent heat of vaporization ( The latent heat of vaporization,

) , expresses the energy required to change a

unit mass of water from liquid to water vapor in a constant pressure and constant temperature process. The value of the latent heat varies as a function of temperature. At a high temperature, less energy will be required than at lower temperatures. As

varies only slightly over normal temperature ranges, a single

value of 2.45 MJ kg-1 is taken in the simplification of the FAO PenmanMonteith equation (Allen et al., 1998). Psychrometric constant ( ) The psychrometric constant,

is given by:

The specific heat at constant pressure is the amount of energy required to increase the temperature of a unit mass of air by one degree at constant pressure. Its value depends on the composition of the air, i.e., on its humidity (Burman et al., 1987). 36

Materials and methods

MATERIALS AND METHODS 3.1 Location and soil characteristics This research was conducted at one of

the fields of Technical Agriculture

college of Halabja, locating on 35°11'N latitude, 45°58'E longitude and the altitude of 690 m above mean sea level (figure 2). Some chemical and physical properties of the soil at depth of (50cm) of this location which were measured according to (Page, 1982 and Klute, 1986) are presented in (Table, 1) below. Table (1): Some physical and chemical properties of the study soil Physical properties Sand Silt Clay Soil texture Bulk density Field capacity, ( 33 kPa) Wilting point, (1500 kPa) Chemical properties Organic mater pH of soil ECe of soil pH of water EC of water Total Nitrogen Phosphors (Available) Potassium (soluble) Calcium (soluble) Magnesium (soluble) Sodium (soluble)

value 133.6 244.3 622.1 C 1200 320 188 20 7.57 1.4 7.7 1.05 20 19 13.7 7.5 2.8 6.3

73

Unit g kgˉ¹ g kgˉ¹ g kgˉ¹ Kg mˉ³ g kgˉ¹ g kgˉ¹ g kgˉ¹ dS mˉ¹ dS mˉ¹ mg kgˉ¹ mg kgˉ¹ Meq kgˉ¹ Meq kgˉ¹ Meq kgˉ¹ Meq kgˉ¹

Materials and methods

Figure (2): Location map of the experimental site

73

Materials and methods

3.2 Experimental design Three irrigation techniques

had been chosen, the first one was full

irrigation (FI) as (t1), the second was deficit irrigation (DI) with two levels of available water as (t2 and t3) and the third was partial root zone drying (PRD) with two levels of available water as (t4 and t5). Each treatment had three replications and a completely randomized block designs was used for the statistical analysis (figure 3).

3.3 Field layout The field was ploughed twice and divided into 15 equal plots(5 treatments ×3 replication) with dimensions of 10 m length x 3 m width (in four furrows' with 0.75m spacing). Maize (hybrid 704)

was sown by spacing (25 cm) between

plants, on April 15, 2012. Germination of maize occurred after 5 days. Diammonium phosphate and urea were applied each at a rate of 1.5 kg per sub plot by broadcasting in the plots at the time of crop sowing. Gravimetric method was used to determine the moisture content of the soil. Well water was used as source of irrigation, by calculating the discharge of well and depending on the amount of water required for each treatment calculated the time of irrigation The

deficit irrigation

and partial root zone drying irrigation practice was

applied after 15 days of crop sowing on May 1, 2012 and subsequent samplings were taken before each irrigation. Weeds were removed manually as needed.

73

Materials and methods

R1 t1 (FI) (100%)

t2 (DI) (75%)

t4 (PRD) (75%)

t3 (DI) (50%)

t5 (PRD) (50%)

R2 t4 (PRD) (75%)

t1 (FI) (100%)

t5 (PRD) (50%)

t2 (DI) (75%)

t3 (DI) (50%)

R3 t3 (DI) (50%)

t5 (PRD) (50%)

(PRD)

dry

t4 (PRD) (75%)

t1 (FI) (100%)

t2 (DI) (75%)

(FI) and (DI)

wet

furrows width=0.75m

furrows length =10.0m

Figure (3): Layout of experiments design. 3.4 Irrigation treatment and moisture depletion To determine the amount of irrigation water for each treatment, the moisture content at both field capacity (tension 33 kPa) and wilting point (tension 1500 kPa) were measured and they were 32% and 18.8%(wt/wt) (klute, 1986), respectively. The differences between them are called total available water which is 13.2%. The soil samples were taken from each treatment by using a spiral auger to a depth depending on the root zone for measuring the moisture content before irrigation process. The equivalent depth of water was measured by depending on the depth of the effective root by using the following equation (Brog and Grimes, 1986): ………… (44) 04

Materials and methods

Where RZD: effective root zone depth (m) MRD: maximum root zone depth (m) I: number of day after planting Dm: number of day to reach the root to maximum depth The irrigation treatments were as follows: 1. Full irrigation treatment : (t1) Irrigation process was started when 50% of available water was depleted and then 50% of it was added to reach 100% of the available water. Then depth of irrigation water was calculated by (Kord et al., 1973) equation after modified according to treatments as follow:

Where d: depth of water applied (mm) : Volumetric water content at field capacity (m³ mˉ³) : Volumetric water content after %50 of available water was depleted (m³ mˉ³) : root zone depth (mm) When soil moisture reached to 25.4%, the irrigation process was started until the soil moisture reached to 32%. 2. Deficit irrigation (t2) The irrigation process was started when 50% of available water was consumed and then 25% of it was added to reach 75% of the available water. Then depth of irrigation water was calculated by the following equation.

Where : Volumetric water content after %25 of available water was depleted (m³ mˉ³) 04

Materials and methods

When soil moisture reached to 25.4%, the irrigation process was started until the soil moisture reached to 28.7 %. 3. Deficit irrigation (t3) The irrigation process was started when 75% of available water was consumed and then 25% of it was added to reach 50% of the available water. Then depth of irrigation water was calculated by the following equation:

Where : Volumetric water content after %75 of available water was depleted (m³ mˉ³) When soil moisture reached to 22.1%, the irrigation process was started until the soil moisture reached to 25.4 %. 4. Partial root zone drying (t4) The irrigation process was started when 50% of available water was consumed and then 25% of it was added to reach 75% of the available water. The depth of irrigation water was calculated by the following equation:

When soil moisture reached to 25.4%, the irrigation process was started until the soil moisture reached to 28.7 %. 5. Partial root zone drying (t5) The irrigation process was started when 50% of available was consumed and then 25% of it was added to reach 75% of the available water. The depth of irrigation water was calculated by the following equation:

04

Materials and methods

When soil moisture reached to 22.1%, the irrigation process was started until the moisture reached to 25.4%. After calculating the depth of the water (d) for each treatment, the amount of water (v) was calculated by multiplying irrigation depth by the area of plot (A) as follows:

Where V: Volume of water applied (m³) d: depth of water applied (m) A: area of experiment plot (m²) The amounts of water added for partial root zone drying treatments were equal the half amount of water added for deficit treatments as follows:

3.5 Determination of consumptive use: 3.5.1Evaporation pan method: Mean daily pan evaporations from the experimental station is shown from the appendix (4) were measured by pan evaporation (Class A). The evapotranspiration calculated by (Allen et al., 1998) equation by multiplying the pan evaporation with pan coefficient (Kp) .The value of (Kp) were used dependent on area of pan placed, wind speed, humidity and windward side distance of dry fallow are equal (0.55 and 0.6) appendix (3).

07

Materials and methods

3.5.2 Standardized Penman-Montieth reference (ETsz) method (ASCEEWRI, 2005): Daily (ETsz) was calculated from weather data using the standardized Reference Evapotranspiration Penman-Monteith method (ASCE-EWRI, 2005) as used

the term (ETsz) refers to both grass (ETos) and alfalfa (EToT) by

following equation.

3.6 Estimation of water stress coefficient (Ks) Water stress coefficient (Ks) can be calculated from the following equation (Allen et al., 1998): =

3.7 Estimation of Depletion coefficients (P)  For calculating the value of depletion coefficient (P) for grass crop, the equation below is used: – Where : Evapotranspiration (mm dˉ¹) calculated by FAO-PM grass equation for (t1) (FI)  For calculating the value of depletion coefficient (P) for alfalfa crop, the following equation is used: – 00

Materials and methods

: Evapotranspiration (mm dˉ¹) calculated by FAO-PM grass equation for (t1) (FI)  For calculating the value of depletion coefficient (P) for evaporation pan the equation below is used: – : Evapotranspiration (mm dˉ¹) calculated by pan evaporation (t1) (FI) The value of (Ptable22) for maize is taking from (Appendix 10), which is equal to (0.55).

 For estimating the value of real crop evapotranspiration (ETadj) for treatment (t2, t3, t4 and t5) by depending on water stress coefficient (Ks) for each treatment, this equation is used : ‫٭‬ 

………… (57)

Maximum values of both evapotranspiration and yield were taken from the first treatment (FI).

3.8 Water use efficiency 3.8.1 Field water use efficiency Field water use efficiency was estimated by this equation (Morison et al., 2008) for all treatment.

Where Y=grain yield (kg) and (WA) = amount of water applied (m³).

04

Materials and methods

3.8.2 Crop water use efficiency Crop water use efficiency was estimated by using this equation (Morison et al., 2008)

Where Y=grain yield (kg) and (ET) = evapotranspiration (mm seasonˉ¹).

3.9 Harvest index The harvest index is the ratio of the economic yield to total biomass of a given crop and all agricultural systems are interested for the useful part of the crop; e.g., grains, seeds, fruits, vegetables and so on (Boyer and Westgate, 2004).

3.10 Crop response factor Yield response factor for water (Ky) was estimated by using the equation reduction in relative yield Stewart’s model (Doorenbos and Kassam, 1979), as given below:

The estimated value of (Ky) depends on the maximum yield from full irrigation treatment and yield of treatments that exposed to stress (y2, y3, y4, y5) for second, third, fourth and fifth treatments, respectively, for each (FAO-PM grass, FAO-PM alfalfa and pan evaporation) methods.

3.11 Measurement of Abscisic acid concentration in maize leaves: Abscisic acid was measured according to Kelen method (Kelen et al,. 2004) by extraction of this hormone from leaves of maize, for all treatments, by using methanol (70%) in temperature (4°C) in dark medium, then separated by Ethel acetate and diethyl ether, after that the sample was dried by anhydrate sodium sulphate .Then the abscisic acid was determined by HPLC method after preparation the standard solution for this purpose.

04

Results and discussion

RESULTS AND DISCUSSION 4.1 Cumulative water applied and soil moisture: Figure (4) provides the summary of the seasonal amount of irrigation water applied. Treatments received irrigation water varying from low of 260 mm in (t5)PRD to high 1001 mm in non-stress treatment (t1) (FI). Deficit irrigation (t2, t3) received (638,522mm) of water and PRD (t4) received (319mm) of water. The irrigation treatments PRD (t4, t5), which received 50% less water than the DI (t2, t3), and DI (t2, t3) received, %63, %52of FI (t1).

The first treatment

irrigation was carried out on April 15, 2012, and the final application was done on July 27, 2012. Since the rainfall was not received during the maize growing season,

the

crop water consumption predominantly depended on the amount of the irrigation water supplied to the treatment plots.

In the (DI and PRD) treatment plots;

degree of the water stress gradually increased towards the end of the growing season and resulted in reduced crop yields. Water use was reported by (Kirda, et al., 2005) were vary from 483mm in PRD-50 and DI-50 to 654 mm in full irrigation treatment for surface irrigated corn in the first year and from 324 to 532 mm in the second year. Variation of cumulative water use of the maize crop during the growing season with respect to the treatments is shown in Figure 4. Crop water use was higher at full irrigation level (FI) than in the DI and PRD irrigation plots. As indicated in Figure 4, cumulative water use was similar in all treatment plots in germination stage due to applied similar amount of water for all treatments; then the treatments varied in water use according to type of treatments.

74

Results and discussion

cumulative depth of applied water (mm)

1200

1000

800 t1 (FI) t2 (DI 75)

600

t3(DI 50) t4(PRD 75)

400

t5(PRD 50) 200

0 27-Mar

16-Apr

06-May 26-May

15-Jun

05-Jul

25-Jul

14-Aug

Date

Figure (4): Cumulative depth of applied water under different irrigation treatments.

4.2 Water consumptive use estimated by different methods 4.2.1 FAO-PM-grass equation: 1. Germination stage (15-30 April):

the consumptive use values for all

treatments were low and almost equal (1.65 mm dˉ¹) compared with other values of the growth stage (Figure 5). These lower values may be due to low temperature, high humidity during this period and low value of crop factor (0.4) compared with other stage. beside that the irrigation processes were continued equally for all treatments during this stage. 2. Vegetative growth (1-31 May): Figure (5) shows an increasing tendency of the consumptive use values in this stage for all treatments except the fifth treatment (PRD) compared with germination stage. The increasing values due to the increased temperature and sunshine duration and decreased the humidity beside increased the value of crop factor (Kc=1.0) (Doorenbos, Pruitt., 1977). As shown in the first treatment (FI) gave a higher consumptive use value (6.5mm dˉ¹) compared to the other treatments because this treatment was not 74

Results and discussion

exposed to water stress (Ks=1.0), while the other treatments were exposed to water stress and their Ks were (0.79, 0.39, 0.33 and 0.16) for (t2, t4, t3 and t5) respectively. This caused decreasing the consumptive use values. 3. Flowering stage (1-30 June): Figure (5) shows an increasing tendency of the consumptive use values in this stage for all treatments except the fifth treatment (PRD) compared with germination and vegetative growth stages due to the increased temperature and sunshine duration and decreased the humidity beside increased the value of crop factor to (Kc=1.1) (Doorenbos, Pruitt., 1977). Shows that the first treatment (FI) gave higher consumptive use value (9.1mm dˉ¹) compared with other treatments because this treatment was not exposed to water stress and the value of (Ks=1). While the other treatments were exposed to water stress and their Ks were (0.7, 0.35, 0.3 and 0.15) for (t2, t4, t3 and t5) respectively. This caused decreasing the consumptive use values. 4.Harvesting stage (1-31 July): Figure (5) shows the decreasing of consumptive use values in this stage for all treatments compared with the other stages, due to the decreased the value of crop factor to (Kc=0.55) (Doorenbos, Pruitt., 1977). Beside the increased temperature and sunshine duration and decreased humidity. The consumptive use value for (t1) was higher than the other treatments because this treatment was not exposed to water stress and the value of (Ks=1).While the other treatments were exposed to water stress and their Ks were (0.85, 0.42, 0.34 and 0.17) for (t2, t4, t3 and t5) respectively. This caused decreasing the consumptive use values.

74

Results and discussion

10 9

consumptive use mm dˉ¹

8 7 6

t1

5

t2

4

t3 t4

3

t5 2 1 0 germination

vegetative

flowaring

harvesting

growth stage

Figure (5): Water consumptive use estimated by FAO-PM grass equation for all treatments during seasonal growth stages.

4.2.2 FAO-PM-alfalfa equation: 1. Germination stage (15-30 April): Figure (6) shows lower values of consumptive use for all treatments compared with other stages and they almost are equal (1.03 mm dˉ¹) due to lower meteorological data in mean air temperature and sunshine duration and high humidity (Appendix 4), in spite of the lower the value of crop factor compared with other stage (Kc=0.2) (Wright, 1981). The amount of water was added in all treatments equally. Because the value of consumptive use for all treatment are equal. 2. Vegetative growth (1-31 May): Figure (6) shows increasing consumptive use values in this stage for all treatments except fifth treatment (PRD) compared with germination stage due to the increased temperature and sunshine duration and decreased humidity, Also because of the increased value of crop factor (Kc=0.34) (Wright, 1981). The consumptive use value for (t1) was higher than the other treatments because this treatment was not exposed to stress and the 05

Results and discussion

value of (Ks=1). While the other treatments were exposed to water stress and their Ks were (0.93, 0.46, 0.36 and 0.18) for (t2, t4, t3 and t5) respectively. This caused decreasing the consumptive use values. 3.Flowering stage (1-30 June): Figure (6) shows increasing consumptive use values in this stage for all treatments compared with the other stages and due to the increased temperature and sunshine duration and decreased humidity, also the increased value of crop factor to (Kc=0.9) (Wright, 1981). The consumptive use value for (t1) was higher than

other treatment because this treatment was

not exposed to water stress and the value of (Ks=1). While the other treatments were exposed to water stress and their Ks were (0.65, 0.32, 0.29 and 0.14) for (t2, t4, t3 and t5) respectively. This caused decreasing the consumptive use values. 4.Harvesting stage (1-31 July): Figure (6) shows decreasing consumptive use values in this stage compared with flowering stage, due to the decreased the value of crop factor to (Kc=0.44) (Wright, 1981) and decreased crop stress. Beside of increased the temperature and sunshine duration and decreased the humidity. The consumptive use value for (t1) was higher than other treatment because this treatment was not exposed to water stress and the value of (Ks=1). While the other treatments were exposed to water stress and their Ks were (0.83, 0.41, 0.34 and 0.17) for (t2, t4, t3 and t5) respectively. This caused decreasing the consumptive use values.

05

Results and discussion

12 11

consumptive use mm dˉ¹

10 9 8 7

t1

6

t2

5

t3

4

t4

3

t5

2 1 0 germination

vegetative

flowaring

harvesting

growth stage

Figure (6): Water consumptive use estimated by FAO-PM alfalfa equation for all treatments during seasonal growth stages.

4.2.3 Evaporation pan method (Class A): 1. Germination stage (15-30 April): Figure (7) shows lower values of consumptive use for all treatments compared with other stages and almost all values

are equal (1.34 mm dˉ¹) due to lower meteorological data in mean air

temperature and sunshine duration and high humidity as shown in (Appendix 4) beside of the lower values of crop factor compared with other stages (Kc=0.4) (Doorenbos, Pruitt., 1977). Since the amount of water was added in all treatments equally, the values of consumptive use for all treatments are equals. 2.Vegetative growth (1-31 May):

Figure (7) shows an increasing tends of

consumptive use values in this stage for all treatments except the fifth treatment compared with germination stage due to the increased temperature and sunshine duration and decreased humidity, beside the increased value of crop factor (Kc=1.0) (Doorenbos, Pruitt., 1977). The consumptive use value for (t1) was higher than other treatment because this treatment was not exposed to stress and 05

Results and discussion

the value of (Ks=1). While the other treatments were exposed to water stress and their Ks were (0.85, 0.41, 0.34 and 0.17) for (t2, t4, t3 and t5) respectively. This caused decreasing of the consumptive use values. 3.Flowering stage(1-30 June): Figure (7) shows increasing of consumptive use values in this stage for all treatments except the fifth treatment (PRD) compared with germination stage and vegetative growth stages due to the increased the temperature and sunshine duration and decreased humidity, in spite of the increased value of crop factor to (Kc=1.1) (Doorenbos, Pruitt., 1977). The consumptive use value for (t1) was higher than other treatment because this treatment was not exposed to stress and the value of (Ks=1). While the other treatments were exposed to water stress and their Ks were (0.75, 0.37, 0.32, 0.16) for (t2, t4, t3 and t5), respectively. This caused decreasing of the consumptive use values. 4.Harvesting stage (1-31 July): Figure (7) shows decreasing consumptive use values in this stage compared with flowering stage, due to the decreased value of crop factor to (Kc=0.55) (Doorenbos, Pruitt., 1977). and decreased crop stress. Beside of increased the temperature and sunshine duration and decreased humidity, the consumptive use value for (t1) was higher than other treatment because this treatment was not exposed to stress and the value of (Ks=1). While the other treatments were exposed to water stress and their Ks values were (0.89, 0.44, 0.35 and 0.17) for (t2, t4, t3 and t5) respectively. This caused decreasing the consumptive use values.

05

Results and discussion

8

consumptive use mm dˉ¹

7 6 5

t1 t2

4

t3

3

t4

2

t5

1 0 germination

vegetative

flowaring

harvesting

growth stage

Figure (7): Water consumptive use estimated by evaporation pan (class A) method for all treatments during seasonal growth stages.

4.3 Estimation water stress for treatments under stress: 4.3.1 FAO-PM grass equation: 1. Deficit irrigation for second and third treatments : Figure (8) shows the depth of readily available water (RAW) which was (107.7, 58.21, 45.15 and 65.34) and (107.7, 38.8, 30.09 and 43.56) mm from the depth of total available water (TAW) gave (118.8 and 79.2) mm for both (t2 and t3) of the (DI) for the vegetative, flowering and harvesting stages respectively, but TAW in germination stage was 158.4 mm. The moisture stress coefficient (Ks) values were (1.0, 0.79, 0.70 and 0.85) and (1.0, 0.33, 0.30 and 0.34) respectively, while the moisture depletion (Dr) are (107.7, 79.2, 72 and 65) mm and (107.7, 66, 64 and 69) mm, respectively, and the depletion coefficient (p) were (0.68, 0.49, 0.38 and 0.55) for the t2 and t3 of the (DI) for sequential growth stages. By increased the water stress caused decreasing readily available water and plant cannot uptake water easily from soil, this is caused decreased 07

Results and discussion

vegetative maize growth and yield this is agreed with (Lack et al., 2011; Mohammad et al., 2012). 2. Partial root zone drying for fourth and fifth treatments : Figure (9)shows the depth of readily available water (RAW) values which were (107.7, 29.1, 22.57, and 32.67) and (107.7, 19.4, 15.05 and 21.78) mm from the total depth of the available water (TAW) giving (59.4 and 39.6)mm for both (t4 and t5) of the (PRD) for the vegetative, flowering and harvesting stage respectively, but TAW in germination stage was 158.4 mm. The moisture stress coefficient (Ks) values were (1.0, 0.39, 0.35 and 0.42) and (1.0, 0.16, 0.15 and 0.17) respectively, while the moisture depletion (Dr) values were (107.7, 47, 48 and 49) and (107.7, 37, 38 and 37) mm and the depletion coefficient (p) were (0.68, 0.49, 0.38 and 0.55) for the t4 and t5 of the (PRD) for sequential growth stages. By increased

water stress caused decreasing (RAW) and plant cannot

uptake water easily from soil, this is caused decreased vegetative maize growth and yield this is agreed with (Lack et al., 2011; Mohammad et al., 2012).

00

Results and discussion

θfc

θt

θwp

θfc

1.0 1.0 0.8

germination

θwp

0.6

Dr=107.7mm

0.4

RAW=107.7mm

0.2

vegetative growth

0.8 Ks 0.79 0.6

Ks

Dr=79.2

0.4

TAW=158.4mm

p=0.68

RAW=58.21

0.2

0.0

TAW=118.8

p=0.49

0.0 0

20

40

60

80

100

120

140

160

t2

0 10 20 30 40 50 60 70 80 90 100 110 119

t2 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 0.85 0.8

flowering

0.8 Ks 0.7 0.6

harvesting

Ks Dr=72mm

0.4

RAW=45.15mm

0.2

TAW=118.8mm

0.6

Dr=65mm

0.4 p=0.38

RAW=65.34mm

0.2

0.0

TAW=118.8mm

p=0.55

0.0 0 10 20 30 40 50 60 70 80 90 100 110 119

t2

0 10 20 30 40 50 60 70 80 90 100 110 119

t2 θfc

θt

θfc

θwp

θt

θwp

1.0

1.0 1.0 0.8

vegetative growth

0.8

germination Ks

Ks 0.6

Dr=107.7mm

0.4

RAW=107.7mm

0.2

0.6

TAW=158.4mm

RAW=38.8 Dr=66mm

0.4 0.33 0.2

p=0.68

TAW=79.2

p=0.49

0.0

0.0 0

20

40

60

80

100

120

140

0

160

10

20

30

40

50

60

70

80

t3

t3 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 0.8

flowering

0.8

harvesting

Ks

Ks 0.6 0.4 0.30 0.2

0.6

RAW=30.09 Dr=64mm

TAW=79.2

0.4 0.34 0.2

p=0.38

RAW=43.56 Dr=69mm

TAW=79.2

p=0.55

0.0

0.0 0

t3

θt

1.0

10

20

30

40

50

60

70

0

80

10

20

30

40

50

60

70

80

t3 Figure (8): Relationship between moisture stress coefficient (Ks), total available water (TAW), readily available water (RAW), moisture depletion (Dr) and depletion coefficient (p) which were calculated by FAO- PM Grass equation for second and third treatments (DI). 05

Results and discussion

θfc

θt

θwp

θfc

1.0 1.0 0.8

germination

θwp

0.8

Ks

vegetative growth

Ks 0.6

Dr=107.7mm

0.4

RAW=107.7mm

0.2

0.6

TAW=158.4mm

Dr=47mm

0.4 0.39 0.2

p=0.68

0.0

RAW=29.1mm TAW=59.4mm

p=0.49

0.0 0

20

40

60

80

100

120

140

160

t4

0

10

20

30

40

50

60

t4 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 flowering

0.8

harvesting

0.8

Ks

Ks 0.6

Dr=48mm

0.4 0.35 0.2

0.6 0.42 0.4

RAW=22.57mm TAW=59.4mm

p=0.38

Dr=49mm RAW=32.67mm

0.2

0.0

TAW=59.4mm

p=0.55

0.0 0

10

20

30

40

50

60

t4

0

10

20

30

40

50

60

t4 θfc

θt

θfc

θwp

θt

θwp

1.0

1.0 1.0 0.8

0.8

germination

vegetative growth

Ks

Ks 0.6

Dr=107.7mm

0.6

0.4

RAW=107.7mm

0.4

0.2

TAW=158.4mm

0

20

40

60

80

100

120

140

t5 θfc

θt

RAW=19.4mm Dr=37mm

0.2 0.16 0.0

p=0.68

0.0 160

TAW=39.6mm

0

10

p=0.49

20

30

40

t5

θwp

θfc

1.0

θt

θwp

1.0 0.8

flowering

0.8

harvesting

Ks

Ks 0.6

0.6

RAW=15.05mm Dr=38mm

0.2 0.15 0.0

TAW=39.6mm

0

RAW=21.78mm Dr=37mm

0.4

0.4

t5

θt

1.0

10

0.2 0.17 0.0

p=0.38

20

30

TAW=39.6mm

0

40

10

p=0.55

20

30

40

t5 Figure (9): Relationship between moisture stress coefficient (Ks), total available water (TAW), readily available water (RAW), moisture depletion (Dr) and depletion coefficient (p) which were calculated by FAO-PM Grass equation for fourth and fifth treatment (PRD). 04

Results and discussion

4.3.2FAO-PM alfalfa equation: 1. Deficit irrigation for second and third treatment: Figure (10) shows the depth of readily available water (RAW) values which were (110.9, 73.65, 38.01 and 62.96) and (110.9, 49.1, 25.35 and 41.97) mm from the total depth of the available water (TAW) giving (118.8 and 79.2) mm for both (t2 and t3) of the (DI) for the vegetative, flowering and harvesting stages respectively, but (TAW) in germination stage was 158.4 mm. The moisture stress coefficient (Ks) values were (1.0, 0.93, 0.65 and 0.83) and (1.0, 0.36, 0.29 and 0.34), while the moisture depletion (Dr) values were (110.9, 79.2, 70 and 72) (110.9, 69, 63 and 69) mm and the depletion coefficient (p) values were (0.70, 0.62, 0.32 and 0.53) for the t2 and t3 of the (DI) for sequential growth stages. By increased the water stress caused decreasing readily available water and plant cannot uptake water easily from soil, this is caused decreased vegetative maize growth and yield this is consistent with (Lack et al., 2011; Mohammad et al., 2012). 2. Partial root zone drying irrigation for fourth and fifth treatment : Figure (11) shows the depth of readily available water (RAW) values which were (110.9, 36.82, 19.0 and 31.48) and (110.9, 24.55, 12.67 and 20.98) mm from the total depth of the available water (TAW) giving (59.4 and 39.6) mm for both (t4 and t5) of the (PRD) for the vegetative, flowering and harvesting stages respectively, but (TAW) in germination stage was 158.4 mm. The

moisture

stress coefficient (Ks) values were (1.0, 0.46, 0.32 and 0.42) and (1.0, 0.18, 0.14 and 0.17), while the moisture depletion (Dr) values were (110.9, 49, 45 and 47) (110.9, 38, 38 and 37) mm and the depletion coefficient (p) values were (0.70, 0.62, 0.32 and 0.53) for the t4 and t5 of the (PRD) for sequential growth stages. By increased the water stress caused decreasing (RAW) and plant cannot uptake water easily from soil, this is caused decreased vegetative maize growth and yield this is agreed by (Lack et al., 2011; Mohammad et al., 2012). 04

Results and discussion

θfc

θt

θwp

θfc

1.0

θt

θwp

1.0

1.0 0.8

0.93 0.8

germination

Ks

vegetative growth

Ks 0.6

Dr=110.9mm

0.6

Dr=79.2mm

0.4

RAW=110.9mm

0.4

RAW=73.65mm

0.2

TAW=158.4mm

p=0.70

0.2

0.0

TAW=118.8mm

p=0.62

0.0 0

20

40

60

80

100

120

140

160

0 10 20 30 40 50 60 70 80 90 100 110 119

t2

t2 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 0.83 0.8

flowering

0.8 Ks 0.65 0.6

harvesting

Ks Dr=70mm

0.6

0.4

RAW=38.01mm

0.2

TAW=118.8mm

Dr=72mm

0.4 p=0.32

RAW=62.96mm

0.2

0.0

TAW=118.8mm

p=0.53

0.0 0 10 20 30 40 50 60 70 80 90 100 110 119

0 10 20 30 40 50 60 70 80 90 100 110 119

t2

t2 θfc

θt

θfc

θwp

θt

θwp

1.0

1.0 1.0 0.8

vegetative growth

0.8

germination Ks

Ks 0.6

Dr=110.9mm

0.4

RAW=110.9mm

0.2

0.6

TAW=158.4mm

RAW=49.1mm Dr=69mm

0.4 0.36 0.2

p=0.70

TAW=79.2

p=0.62

0.0

0.0 0

20

40

60

80

100

120

140

0

160

10

20

30

40

50

60

70

80

t3

t3 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 0.8

flowering

0.8

harvesting

Ks

Ks

0.6

0.6 RAW=25.35mm Dr=63mm 0.4 0.29 0.2 TAW=79.2mm

0.4 0.34 0.2

p=0.32

RAW=41.97 Dr=69mm

TAW=79.2 mm

p=0.53

0.0

0.0 0

10

20

30

40

50

60

70

0

80

10

20

30

40

50

60

70

80

T3

t3

Figure (10): Relationship between moisture stress coefficient (Ks), total available water (TAW), readily available water (RAW), moisture depletion (Dr) and depletion coefficient (p) which were calculated by FAO-PM alfalfa equation for second and third treatments (DI). 04

Results and discussion

θfc

θt

θwp

θfc

1.0 1.0 0.8

germination

0.8

Ks

θwp

vegetative growth

Ks 0.6

Dr=110.9mm

0.4

RAW=110.9mm

0.2

0.6 0.46 0.4

TAW=158.4mm

p=0.70

Dr=49mm RAW=36.82mm

0.2

0.0

TAW=59.4mm

p=0.62

0.0 0

20

40

60

80

100

120

140

160

t4

0

10

20

30

40

50

60

t4 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 flowering

0.8

harvesting

0.8

Ks

Ks 0.6

Dr=45mm

0.6 0.42 0.4

0.4 RAW=19.0mm 0.32 0.2 TAW=59.4mm

p=0.32

Dr=47mm RAW=31.48mm

0.2

0.0

TAW=59.4mm

p=0.53

0.0 0

10

20

30

40

50

60

t4

0

10

20

30

40

50

60

t4 θfc

θt

θfc

θwp

θt

θwp

1.0

1.0 1.0 0.8

0.8

germination

vegetative growth

Ks

Ks 0.6

Dr=110.9mm

0.6

0.4

RAW=110.9mm

0.4

0.2

TAW=158.4mm

0

20

40

60

80

100

120

140

t5 θfc

θt

RAW=24.55mm Dr=38mm

0.2 0.18 0.0

p=0.70

0.0 160

TAW=39.6mm

0

10

p=0.62

20

30

40

t5

θwp

θfc

1.0

θt

θwp

1.0 0.8

flowering

0.8

harvesting

Ks

Ks 0.6

0.6

RAW=12.67 Dr=38mm

0.2 0.14 0.0

TAW=39.6mm

0

RAW=20.98mm Dr=37mm

0.4

0.4

t5

θt

1.0

10

0.2 0.17 0.0

p=0.32

20

30

TAW=39.6mm

0

40

10

p=0.53

20

30

40

t5

Figure (11) Relationship between moisture stress coefficient (Ks), total available water (TAW), readily available water (RAW), moisture depletion (Dr) and depletion coefficient (p) which were calculated by FAO-PM alfalfa equation for fourth and fifth treatment(PRD). 55

Results and discussion

4.3.3 Pan Evaporation (Class A) equation: 1. Deficit irrigation for second and third treatment: Figure (12) shows the depth of readily available water (RAW) values which are (109.3, 65.34, 53.46 and 70.1) and ( 109.3, 43.56, 35.64 and 46.73) mm from the total depth of the available water (TAW) giving ( 118.8 and 79.2)mm for both (t2 and t3) of the (DI) for the vegetative, flowering and harvesting stages respectively, but (TAW) in germination stage was 158.4 mm. The moisture stress coefficient (Ks) value are (1.0, 0.85, 0.75 and 0.89) (1.0, 0.34, 0.32 and 0.35), while the moisture depletion (Dr) values were (109.3, 79.2, 72 and 79.2) and (109.3, 69, 66 and 69) mm and the depletion coefficient (p) values were (0.69, 0.55, 0.45 and 0.59) for the t2 and t3 of the (DI) for sequential growth stages. Increasing the water stress caused a decrease in the readily available water due the fact that the plant cannot uptake water easily from soil, this is caused decreased vegetative maize growth and yield the finding is agree with that observed by (Lack et al., 2011; Mohammad et al., 2012). 2. Partial root zone drying irrigation for fourth and fifth treatment : Figure (13) shows the depth of readily available water (RAW) values which were (109.3, 32.67, 26.73 and 35.04) and (109.3, 21.78, 17.82 and 23.36) mm from the total depth of the available water (TAW) giving (59.4 and 39.6) mm for both (t4 and t5) of the (PRD) for the vegetative, flowering and harvesting stages respectively, but (TAW) in germination stage was 158.4 mm. The

moisture

stress coefficient (Ks) value are (1.0, 0.42, 0.37 and 0.44) and (1.0, 0.17, 0.16 and 0.17), while the moisture depletion (Dr) values were (109.3, 48, 48 and 48) (109.3, 38, 38 and 38) mm and the depletion coefficient (p) values were (0.69, 0.55, 0.45 and 0.59) for the t4 and t5 of the (PRD) for sequential growth stages. By increased the water stress caused decreasing (RAW) and plant cannot uptake water easily from soil, this is caused decreased vegetative maize growth and yield this is agreed with (Lack et al., 2011; Mohammad et al., 2012).

55

Results and discussion

θfc

θt

θwp

θfc

1.0

θt

θwp

1.0

1.0 0.8

0.85 0.8

germination

Ks

vegetative growth

Ks 0.6

Dr=109.3mm

0.6

Dr=79.2mm

0.4

RAW=109.3mm

0.4

RAW=65.34mm

0.2

TAW=158.4mm

p=0.69

0.2

0.0

TAW=118.8mm

p=0.55

0.0 0

20

40

60

80

100

120

140

160

0 10 20 30 40 50 60 70 80 90 100 110 119

t2

t2 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 0.89 0.8

flowering

0.8 Ks 0.75 0.6

harvesting

Ks Dr=72mm

0.4

RAW=53.46mm

0.2

TAW=118.8mm

p=0.45

0.0

0.6

Dr=79.2mm

0.4

RAW=70.1mm

0.2

TAW=118.8mm

p=0.59

0.0 0 10 20 30 40 50 60 70 80 90 100 110 119

0 10 20 30 40 50 60 70 80 90 100 110 119

t2

t2 θfc

θt

θfc

θwp

θt

θwp

1.0

1.0 1.0 0.8

vegetative growth

0.8

germination Ks

Ks 0.6

Dr=109.3mm

0.4

RAW=109.3mm

0.2

0.6

TAW=158.4mm

RAW=43.56mm Dr=69mm

0.4 0.34 0.2

p=0.69

TAW=79.2mm

p=0.55

0.0

0.0 0

20

40

60

80

100

120

140

0

160

10

20

30

40

50

60

70

80

t3

t3 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 0.8

flowering

0.8

harvesting

Ks

Ks 0.6 0.4 0.32 0.2

0.6

RAW=35.64mm Dr=66mm

TAW=79.2mm

0.4 0.35 0.2

p=0.45

RAW=46.73mm Dr=69

TAW=79.2mm

p=0.59

0.0

0.0 0

10

20

30

40

50

60

70

0

80

10

20

30

40

50

60

70

80

t3

t3

Figure (12): Relationship between moisture stress coefficient (Ks), total available water (TAW), readily available water (RAW), moisture depletion (Dr) and depletion coefficient (p) which were calculated by evaporation pan (Class A) for second and third treatments(DI). 55

Results and discussion

θfc

θt

θwp

θfc

1.0

θt

θwp

1.0

1.0 0.8

germination

0.8

Ks

vegetative growth

Ks 0.6

Dr=109.3mm

0.4

RAW=109.3mm

0.2

0.6 0.42 0.4

TAW=158.4mm

p=0.69

Dr=48mm RAW=32.67mm

0.2

0.0

TAW=59.4mm

p=0.55

0.0 0

20

40

60

80

100

120

140

160

0

t4

10

20

30

40

50

60

t4 θfc

θt

θwp

θfc

1.0

θt

θwp

1.0 flowering

0.8

germination

0.8

Ks

Ks 0.6

Dr=48mm

0.4 0.37 0.2

0.6 0.44 0.4

RAW=26.73mm TAW=59.4mm

p=0.45

Dr=48mm RAW=35.04mm

0.2

0.0

TAW=59.4mm

p=0.59

0.0 0

10

20

30

40

50

60

0

t4

10

20

30

40

50

60

t4 θfc

θt

θfc

θwp

θt

θwp

1.0

1.0 1.0 0.8

0.8

germination

vegetative growth

Ks

Ks 0.6

Dr=109.3mm

0.6

0.4

RAW=109.3mm

0.4

0.2

TAW=158.4mm

0.2 0.17 0.0

p=0.69

0.0 0

20

40

60

80

100

120

140

θt

TAW=39.6mm

0

160

10

p=0.55

20

30

40

t5

t5 θfc

RAW=21.78mm Dr=38mm

θwp

θfc

1.0

θt

θwp

1.0 0.8

flowering

0.8

harvesting

Ks

Ks 0.6

0.6

RAW=17.82mm Dr=38mm

0.4

0.4 0.2 0.16 0.0

TAW=39.6mm

0

RAW=23.36mm Dr=38mm

10

0.2 0.17 0.0

p=0.45

20

30

TAW=39.6mm

0

40

10

p=0.59

20

30

40

t5

t5

Figure (13): Relationship between moisture stress coefficient (Ks), total available water (TAW), readily available water (RAW), moisture depletion (Dr) and depletion coefficient (p) which were calculated by evaporation pan (Class A) for second treatments (PRD). 55

Results and discussion

4.4 Effect of different treatments on water consumptive use values as estimated by variable method during seasonal growth stages: 1. Germination stage: FAO-PM grass equation gave higher water consumptive use value in this stage for all treatments compared with other methods (figure 14). However the lower value was recorded by

FAO-PM

alfalfa equation due to low value of the crop factor. 2. Vegetative growth stage: the consumptive use values were starting to increase in this stage because the plant consumed more water and hence more growth and more transpiration were processed. FAO-PM grass equation gave higher values of the consumptive use for all treatments compared with the other methods. 3. Flowering stage:

maximum values of the consumptive use could be

noticed in this stage for all treatments as shown in (Figure14). FAO-PM alfalfa equation gave higher values in all treatments compared with other methods. 4. Harvesting stage: as shown from (Figure14), increased the value of consumptive use for FAO-PM alfalfa in all treatments compared with other methods due to increased crop factor, temperature, and evapotranspiration and crop factor values. It caused the increased value of water consumptive use.

57

consumptive use mm dˉ¹

Results and discussion

12 10 8 6 4 2 0

t1 ET pan ET grass ET alfalfa germination vegetative

flowaring

harvesting

consumptive use mm dˉ¹

growth stage

8

t2

6 4

ET pan

2

ET grass

0 germination vegetative

flowaring

harvesting

ET alfalfa

consumptive use mm dˉ¹

growth stage

4

t3 ET pan

2

ET grass 0 germination vegetative

flowaring

harvesting

ET alfalfa

consumptive use mm dˉ¹

growth stage

4

t4 ET pan

2

ET grass

0 germination vegetative

flowaring

harvesting

ET alfalfa

water consumptive use mm dˉ¹

growth stage

2

t5 ET pan ET grass ET alfalfa

0 germination vegetative

flowaring

harvesting

growth stage

Figure (14): Water consumptive use which estimated by varying methods during seasonal growth stages for all treatments. 50

Results and discussion

Table (2): Seasonal water consumptive use as estimated by FAO-PM grass, FAO-PM alfalfa and pan evaporation (Class A) for all irrigation treatments Method

Pan

FAO-PM

evaporation

grass

FAO-PM-alfalfa

class A Treatment

Water consumptive use

mm seasonˉ¹

T1

526.46

648.33

597.86

T2

432.87

501.34

451.52

T3

189.98

223.51

199.3

T4

227.08

261.8

233.33

T5

106.24

124.1

107.22

4.5 Effect of different irrigation treatments on growth indicators: 1. Grain yield: The results of analysis of variance showed that the effect of irrigation on grain yield was significant at 1% probability level. The highest grain yield about (7600 Kg haˉ¹) was obtained in optimum irrigation treatment (t1). Drought severe stress reduced grain yield compared to the optimum irrigation condition, this reduction was mainly due to reduction in grain number per ear and average grain weight. Since drought stress causes a decrease in leaf area index (Jamieson et al., 1995 and Stone et al., 2001), a reduction in yield is observed because of low photosynthesis. (Pandey et al., 2000 and Lack et al., 2005) reported that the highest leaf area index for corn was obtained in wellirrigated conditions. While the fourth and fifth treatments gave the lowest significant values (2633 and 1865 Kg haˉ¹) respectively because these treatments

exposed to water stress which caused decreasing of grain yield 55

Results and discussion

significantly. Water stress occurred during different growth stages may reduce final grain yield and the extent of yield reduction depends not only on the severity of the stress, but also on stage of the plant development.

2. Biological yield: The results indicated that the variation of irrigation levels or amount of water applied effects on biological yield. The highest rate of biological yield was obtained from optimum irrigation treatments (full irrigation). Increasing amount of water applied improved the weight of stem and leaf mainly due to increased leaf area index and leaf area duration. The dry matter production of non-stressed plants is usually higher compared to stress plants. First treatment showed the highest value of biological yield weight (17683 Kg haˉ¹), compared with other treatments, and because this treatment did not exposed to water stress and having sufficient water content which increased leaf area, dry matter and grain yield. This result agreed with (Paez et al., 1995 and Sowder et al., 1997). The biological yield from deficit and partial root zone drying irrigation decreased due to the exposure of the plant to water stress especially in vegetative growth stage. This result is consistent with (Pandey et al., 2000).

3. Harvest index: Harvest index that is, assimilate distribution efficiency, decreased with decreasing amount of water applied (Table 3). Decrease in amount of water applied not only decreased biological yield, but also caused a tribulation in allocation of carbohydrates to grains and consequence harvest index decreased, the economic yield is very sensitive to the water balance in the plant and particularly during the reproductive stages. For example, water deficit conditions during germination (Boutraa et al., 2009) or early stages of plant growth result in early senescence (Boutraa and Sanders, 2001), which result in reducing grain filling and consequently yield loss. Water stress can affect plant reproduction and it causes ovary abortion (Boyer and Westgate, 2004), or pollen 54

Results and discussion

sterility. Improvement of harvest index by increasing the rate of grain filling and accelerating the mobilization of photoassimilates may improve water use efficiency in water scarce environments. First treatment (full irrigation) showed the highest value for harvested index (42%), compared with deficit and partial root zone drying irrigation treatments. harvest index value increased by increasing yield and dry matter or biological yield or both of them. This is consistent with (Kang et al., 2000).

Table (3): Average yield production, biological yield and harvest index. Treatment

Yield (kg

Biological yield

Harvest

haˉ¹)

(kg haˉ¹)

index (%)

T1

7600.0

a

17683 a

42.97

a

T2

5257.0

b

12988 b

40.47

b

T3

3638.0

d

11549 c

31.50

c

T4

2633.0

c

7369 d

35.73

d

T5

1865.0

e

6123 e

30.45

e

4.6 Water use efficiency 4.6.1 Field water use efficiency Statistical analysis showed the presence of significant differences in field water use efficiency at the level of probability 0.01 for different irrigation treatments (table 4). The second and fourth treatments of the (DI) and (PRD) showed the highest values (0.823 and 0.825 Kg mˉ³) respectively, compared with other treatments. These results obtained from the decreased amount of water applied in these two treatments which is consistent with (Sepaskhah and Kamgar-Haghighi, 1997; Davies et al., 2002; Zegbe et al., 2004; Sepaskhah and Khajehabdollahi, 2005; Shani-Dashtgol et al., 2006; Fereres and Sariano, 2007; Costa et al., 2007; Shahnazari et al., 2007; Geerts and Raes, 2009 and Ahmadi et al., 2010b). all noted that reducing the amount of irrigation water lead to high 54

Results and discussion

water use efficiency. The third and fifth treatments showed the lowest water use efficiency due to more exposed plant to water stress which was caused decreasing grain yield production. Generally, the fourth treatment in the partial root zone drying irrigation technique gave high water use efficiency values compared with other treatments. Table (4): Average values of field water use efficiency for all irrigation treatments:

Field water use efficiency Kg mˉ³ Treatment Average value

T1 0.760 b

T2

T3

0.823 a 0.696 c

T4

T5

0.825 a

0.714 c

4.6.2 Crop water use efficiency Statistical analysis showed the presence of significant differences in crop water use efficiency at the level of probability 0.01 for different irrigation treatments. Table (5) Shows that (t3) in deficit irrigation and (t5) of partial root zone drying irrigation treatments gave the highest water use efficiency value (1.78 and 1.66 Kg mˉ³) respectively, compared with other treatments for all methods. This is due to the consumption of less amount of water. Evaporation pan method gave the highest crop water use efficiency values compared with other methods.

54

Results and discussion

Table (5): Values of crop water use efficiency of irrigation treatments and for all consumptive use methods. Crop water use efficiency Kg mˉ³ Treatment

Pan evaporation

FAO-PM grass

FAO-PM alfalfa

Class A T1

1.44

c

1.17 c

1.27 c

T2

1.25

d

1.05 d

1.16 d

T3

1.91

a

1.62 a

1.82 a

T4

1.16

d

1.00 d

1.13 d

T5

1.74

b

1.50 b

1.74 b

4.7 Yield response factor (Ky) Figures (15, 16 and 17) shown the relationship between the relative reductions consumptive use [1- ETa/ET m] which were measured by FAO-PM grass equation, FAO-PM alfalfa equation and evaporation pan method and the relative yield reduction values [1-Ya/Ym]. The yield response factor (Ky) captures the essence of the complex linkages between production and water use by a crop, where many biological, physical and chemical processes are involved. This approach and the calculation procedures for estimating yield response to water were showed in (Doorenbos and Kassam, 1979). The (Ky) values are crop specific and vary over the growing season according to growth stages with: Ky >1: crop response is very sensitive to water deficit with proportional larger yield reductions when water use is reduced because of stress. Ky <1: crop is more tolerant to water deficit, and recovers partially from stress, exhibiting less than proportional reductions in yield with reduced water use. Ky =1: yield reduction is directly proportional to reduced water use. 45

Results and discussion

The Ky value may depend on maize genotype, the severity of the water stress, the climatic conditions, root growth and distribution, water stress compensation factor and the period of occurrence of the water stress during the growing season. The individual Ky value are in the magnitude of those reported by (Gencoglan and Yazar, 1999) as 1.08–1.61 (Yazar et al., 2002) as 0.98-1.23 (Istanbulluoglu et al., 2002) as 0.76 (Kirnak et al., 2003) as 0.77–0.81 (Cakir., 2004) as 0.81–1.36 (Dagdelen et al. 2006) as 1.03–1.04 (Yazar et al., 2009) as 1.06 and (Kiziloglu., 2009) as 1.26-1.51-1.86 for different regions.

4.7.1 FAO-PM grass equation: The relative reduction of the consumptive use values were 0.59 and 0.80) and the relative reduction of the yield values were

(0.22, 0.65, (0.30, 0.52,

0.65 and 0.75) for (t2,t3,t4 and t5) treatments, respectively, on these aspect, the yield response factor values (Ky) were (1.36, 0.80, 1.10 and 0.93) for (t2,t3,t4 and t5) respectively, (figure15). It can be noticed that the values of the yield response factor were decreased by reduction of water consumptive use. The (t3 andt5) treatments appeared to give the highest values for the relative reduction of the water consumptive use which were (0.65 and 0.80) respectively this means that it could be saved 65% and 80% of irrigation water and used it to irrigate another cultivated area , this is consistent and agreed with (Yialdirm, 1993and1996).

45

Results and discussion

0.0

0.2 0.22 0.4

0.2 0.3 0.4

0.6

0.8

0.0

1.0

0.2

0.2

Ky=1.36

0.4

0.6 0.65 0.8

1.0

Ky=0.80

0.4 0.52 0.6

0.6

0.8

0.8 1.0

1.0

Line 1:1

T3

T2

0.0

0.2

0.4 0.59 0.6

0.2

Line 1:1

0.8

1.0

0.0

Ky=01.10

0.2

0.4

0.4

0.6 0.65 0.8

0.6 0.75 0.8

0.2

0.4

0.6

0.80

1.0

Ky=0.93

Line 1:1 1.0

1.0

Line 1:1

T4 T5 Figure (15): Value of crop response factor (Ky) as estimated by FAO-PM grass equation.

4.7.2 FAO-PM-alfalfa equation: The relative reduction of the consumptive use values were

(0.24, 0.66,

0.59 and 0.82) and the relative reduction of the yield values were

(0.30, 0.52,

0.65 and 0.75) for second, third ,fourth and fifth treatments, respectively , on these aspect, the yield response factor values (Ky) were (1.25, 0.78, 1.08 and 0.91) for (t2,t3,t4 and t5), respectively, (figure16). It can be noticed that the values of the yield response factor were decreased by reduction of water consumptive use. The third and fifth treatments appeared to be highest values for the relative reduction of the water consumptive use which were (0.66 and 0.82), respectively which means that it could be saved 66% and 82% of 45

Results and discussion

irrigation water to be used to irrigate another cultivated area , this is consistent and agreed with (Yialdirm, 1993 and 1996).

0.0

0.2 0.24 0.4

0.2 0.3 0.4

0.6

0.8

0.0

1.0 0.2

Ky=1.25

0.4

0.6 0.66 0.8

1.0

Ky=0.78

0.4 0.52 0.6

0.6

0.8

0.8 1.0

1.0

Line 1:1

0.0

0.2

0.4 0.59 0.6

0.2

Line 1:1

T3

T2

0.8

1.0

0.0

Ky=1.08

0.2

0.4

0.4

0.6 0.65 0.8

0.6 0.75 0.8

1.0

0.2

Line 1:1

0.2

0.4

0.6

0.8 0.82 1.0

Ky=0.91

1.0

Line 1:1

T4 T5 Figure (16) Values of crop response factor (Ky) as estimated by FAO-PM alfalfa equation.

4.7.3 Pan evaporation equation: The relative reduction of the consumptive use values were 0.57 and 0.80) and the relative reduction of the yield values were

(0.17, 0.64, (0.30, 0.52,

0.65 and0.75) for (t2,t3,t4 and t5), respectively , on these aspect, the yield response factor values (Ky) were (1.76, 0.81, 1.14 and 0.93) for second, third, fourth and fifth treatment respectively, (figure17) It can be noticed that the values of the yield response factor were decreased by reduction of water consumptive use. The third and fifth treatments appeared to gain the highest 45

Results and discussion

values for the relative reduction of the water consumptive use which were (0.64 and 0.80), respectively which is means that it could be saved 64% and 80% of irrigation water to be used to irrigate another cultivated area, this is consistent and agreed with (Yialdirm, 1993and1996).

0.0 0.17 0.2 0.2 0.3 0.4

0.4

0.6

0.8

0.0

1.0 0.2

Ky=1.76

0.4

0.6 0.64 0.8

1.0

Ky=0.81

0.4 0.52 0.6

0.6

0.8

0.8 1.0

1.0

Line 1:1

0.0

0.2

0.4 0.57 0.6

0.2

Line 1:1

T3

T2

0.8

1.0

0.0

Ky=1.14

0.2

0.4

0.4

0.6 0.65 0.8

0.6 0.75 0.8

1.0

0.2

Line 1:1

1.0

0.2

0.4

0.6

0.8

1.0

Ky=0.93

Line 1:1

T4 T5 Figure (17): value of crop response factor (Ky) was estimated by Evaporation pan (Class A).

47

Results and discussion

4.8 Effect of irrigation treatments on Abscisic acid concentration during the flowering stage: Table (6) shows the concentrations of abscisic acid (ABA) during the flowering stage for all irrigation treatments in maize leave, it can be noticed that the full irrigation treatment (t1) showed the lowest value of ABA (10.15mg/L). The less concentration of Abscisic acid in full irrigation back to less exposed plant to water stress and less exudates of this acid from plant roots. This is consistent with (Kang, et al., 2002; Liu et al., 2005a; Dodd, 2007 and Wang et al., 2010a). while the PRD treatments (t4 and t5) showed the highest values of ABA (27.89 and 36.71 mg/L), respectively. This is due to the exposure of the plant to water stress and excreting (ABA) hormone.

Table (6): Concentration of abscisic acid in leave samples in flowering stage for all treatments. treatments

Abscisic acid concentration (mg/L)

T1

10.15

T2

18.23

T3

24.78

T4

27.89

T5

36.71

40

References

REFERENCES Ahmadi, S.H., M.N. Andersen, F. Plauborg, R.T. Poulsen, C.R.Jensen, A.R.Sepaskhah and S. Hansen, S., 2010a. Effects of irrigation strategies and soils on field grown potatoes: Gas exchange and xylem [ABA]. Agri. Water Management, 97: 1486-1494. Ahmadi, S.H., M.N. Andersen, F. Plauborg, R.T. Poulsen, C.R. Jensen, A.R. Sepaskhah and S. Hansen 2010b. Effects of irrigation strategies and soils on field grown potatoes: Yield and water productivity. Agri. Water Management. DOI 10.1`016/j.agwat.2010.07.007. Ali, M., C.R. Jensen and V.O. Mogensen, 1998. Early signals in field grown wheat in response to shallow soil drying. Australian Jour. of Plant Physio. 25: 871-882. Ali, M., C.R. Jensen, V.O. Mogensen, M.N. Andersen and I.E. Henson, 1999. Root signaling and osmotic adjustment during intermittent soil drying sustain grain yield of filed grown wheat. Field Crops Research, 62: 35-52. Ali, M.H. and M.S.U. Talukder, 2008. Increasing water productivity in crop production-A synthesis. Agric. Water Manage. 95: 1201-1213. Allen, R.G., Smith, M., Perrier, A., and Pereira, L.S. 1994. An update for the definition of reference evapotranspiration. ICID Bulletin. 43(2). 1-34. Allen, R. G., L. S. Pereira, D. Raes & Smith, M. 1998. Crop Evapotranpiration: Guildlines for computing crop water requirements, FAO Irrigation and Drainage Paper No 56. Food and Agriculture Organisation, Land and Water. Rome, Italy. Allen and Wright, 2002 Conversion of Wright (1981) and Wright (1982) alfalfabased crop coefficients for use with the ASCE Standardized PenmanMonteith Reference Evapotranspiration Equation. 87

References

Arteca, R. (1996). Plant Growth Substances: Principles and Applications. New York: Chapman & Hall. Bacon, M.A., S. Wilkinson and W.J. Davies, 1998. PH-regulated leaf cell expansion in droughted plants is abscisic acid dependent. Plant Physiology, 118: 1507-1515. Bahrun, A., C.R. Jensen, F. Asch and V.O. Mogensen. 2002. Drought-induced changes in xylem pH, ionic composition, and ABA concentration act as early signals in field-grown maize (Zea mays L.). Jour. Of Experimental Botany, 53: 251-263. Bauerle, W. L., W.W. Inman and J.B. Dudley. 2006. Leaf abscisic acid accumulation in response to substrate water content: Linking leaf gas exchange regulation with leaf abscisic acid concentration. Jour. of American Society of Horti. Sci. 131: 295-301. Benjamin, J.G., D.C. Nielsen. 2006. Water deficit effects on root distribution of soybean, field pea and chickpea. Field Crops Research, 97: 248-253. Blaney, H.F. and W.D. Criddle. 1950. Determining water requirements in irrigated areas from climatological and irrigation data. Soil Conservation Service Technical Paper 96. Soil Conservation Service, U.S. Dept. of Agriculture: Washington, D.C. Boutraa, T. and F.E. Sanders, 2001. Influence of water stress on grain yield and vegetative growth of two cultivars of bean (Phaseolus vulgaris L.). J. Agron. Crop Sci., 187: 251-257. Boutraa, T., 2010. Effects of water stress on root growth, water use efficiency, leaf area and chlorophyll content in the desert shrub Calotropis procera. J. Int. Environ. Appl. Sci., 5: 124-132. 87

References

Boutraa, T., A. Akhkha, A.K. Al-Shoaibi, O. Al-Sobhi and A. Alhejeli, 2009. Effect of osmotic stress induced by Polyethylene Glycol (PEG) on seed germination of some Saudi wheat cultivars. Biosci.Biotechnol. Res. Asia, 6: 123-126. Boyer, J.S. and M.E. Westgate, 2004. Grain yields with limited water. J. Exp. Bot., 55: 2385-2394. Brog, H. and O.W.Grimes. 1986. Depth development of root with time: an empirical description trans ASAE 29:194-197. Burman, R.D., Jensen, M.E., and Allen, R.G. 1987. "Thermodynamic factors in evapotranspiration." p. 28-30. In: L.G. James, and M.J. English (eds) Proc., Irrig. and Drain. Spec. Conf., ASCE, Portland, Oregon, July. Cakir, R. 2004. Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops Res. 89: 1–16. Christiansen, J.E. 1968. Pan evaporation and evapotranspiration from climatic data. J. Irrig. and Drain.Div., ASCE 94:243-265. Comstock, J.P.2002. Hydraulic and chemical signaling in the control of stomatal conductance and transpiration. Jour. of Experimental Botany. 53: 195-200. Costa, J.M., M.F.Ortuno and M.M. Chaves, 2007. Deficit irrigation as a strategy to save water: physiology and potential application to horticulture. Jour. of Integrative Plant Biology. 49: 1421-1434. Dagdelen, N., E. Yilmaz, F. Sezgin, and T. Gurbuz. 2006 Water-yield relation and water use efficiency of cotton (Gossypium hirsutum L.) and second crop corn (Zea mays L.) in western Turkey. Agric. Water Mgmt 82: 63–85.

78

References

Davies, W.J., and J.H. Zhang, 1991. Root signals and the regulation of growth and development of plants in drying soil. Annual Review of Plant Physiology and Plant Molecular Biology.42: 55-76. Davies, W.J. and S. Wilkinson, B.R. Loveys, 2002. Stomatal control by chemical signaling and the exploitation of this mechanism to increase water use efficiency in agriculture. New phytologist, 153: 449-460. De Fraiture, C. and D. Wichelns, 2010. Satisfying future water demands for agriculture. Agric. Water Manage., 97: 502-511. Dingman, S.L.1994. Physical Hydrology. Upper Saddle River, NJ: Prentice Hall. Dirk R, P. Steduto, T. C. Hsiao and E. Fereres., 2010. Reference Manual, Chapter 3 – AquaCrop, Version 3.1 January 2010 Dodd, I.C. 2003. Hormonal interactions and stomatal responses. Journal of plant growth regulation. 22: 32-46. Dodd, IC. 2007. Soil moisture heterogeneity during deficit irrigation alters root-toshoot signaling of abscisic acid. Functional Plant Biology34, 439–448 Dodd, I.C., 2009. Rhizosphere manipulations to maximize ‘crop per drop’ during deficit irrigation. Jour. of Experimental Botany. 60: 2454-2459. Doorenbos, J. and Pruitt, W. O., 1977. Crop water requirements. Irrigation and Drainage Paper No. 24, (rev.) FAO, Rome, Italy. 144 p. Doorenbos, J. and A.H. Kassam. 1979. Yield response to water. FAO Irrigation and Drainage Paper 33, Rome, 193 p. Dry, P.R., B.R. Loveys and H. During, 2000. Partial drying of the root zone of grape. II. Changes in the pattern of root development. Vitis. 39: 9-12.

78

References

Duffie, J.A. and W.A. Beckman. 1980. “Solar Engineering of Thermal Processes.” John Wiley and Sons, New York, p 1-109. English, M. and S.N. Raja, 1996. Perspectives on deficit irrigation. Agr. Water Manag. 32, 1-14. Fereres, E. and M.A. Soriano, 2007. Deficit irrigation for reducing agricultural water use. Jour. of Experimental Botany. 58: 147-159. Fernandez, J.E., A. Diaz-Espejo, J.M. Infante, P. Duran, M.J. Palomo, V. Chamorro, I.F. Giron and L. Villagarica, L., 2006. Water relations and gas exchange in olive trees under regulated deficit irrigation and partial root zone drying. Plant and Soil. 284: 273-291. Geerts, S. and D. Raes, 2009. Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas. Agri. Water Management. 96: 12751284. Geiger, R., R.H. Aron, and P. Todd hunter. 2003. The Climate near The Ground, 6th Ed. New York: Rowman and Littlefield. Gencoglan, C. and A. Yazar. 1999. Corn yield and water use water Kisintili applications to yield. Turkish Journal of Agriculture and Forestry 23: 233– 241. Glinka, Z., 1980. Abscisic acid promotes both volume flow and ion release to the xylem in sunflower roots. Plant Physio., 65: 537-540. Gregory, P.J., 2004. Agronomic Approaches to Increasing Water use Efficiency. In: Water Use Efficiency in Plant Biology, Bacon, M.A. (Ed.). Blackwell Publishing, Oxford, UK., pp: 142-170. Grimes, D.W., V.T.Walhood and W.L. Dickens. 1968. Alternate-furrow irrigation for San Joaquin valley cotton. California Agri. 22: 4-6. 78

References

Hansen, V.E., O.W. Israelsen, and G.E. Stringham. 1980. Irrigation Principles and Practices 4th Edition. New York, NY: John Wiley and Sons, Inc. Hargreaves, G.L and Z.A. Samani, 1982. Estimating potential evapotranspiration. Journal of Irrigation and Drainage Engineering, 108 (2), 225-230. Holbrook, N.M., V.R. Shashidhar, R.A. James and R. Munns. 2002. Stomatal control in tomato with ABA-deficient roots: response of grafted plants to soil drying. Jour.l of Experimental Botany. 53: 1503-1514. Hong-Xing, C., Z. Zheng-Bin, X. Ping, C. Li-Ye, S. Hong-Bo, L. Zhao-Hua and L. Jun-Hong, 2007. Mutual physiological genetic mechanism of plant high water use efficiency and nutrition use efficiency. Colloids Surf. B., 57: 1-7. Howell, T.A., 2001. Enhancing water use efficiency in irrigated agriculture. Agron. J., 93: 281-289. Huffaker, R. and J. Hamilton, 2007. Conlict. In: Irrig. of Agri. crops (Lascano, R.J., and Sojka, R.E. eds.), 2nd edition, Agronomy Monograph. 30. ASA-CSSASSSA publishing, 664p. Irmak,

S.

2009.

Estimating

crop

evapotranspiration

from

reference

evapotranspiration and crop coefficients. University of Nebraska-Lincoln Extension Neb Guide G1994. Istanbulluoglu, A., I. Kocaman, and F. Konukcu. 2002. Water use-production relationship of maize under Tekirdag conditions in Turkey. Pak. J. Biol. Sci. 5 (3): 287–291. James, L. G. (1988). Principles of Farm Irrigation System Design. New York: John Willey and Sons Inc.

78

References

Jeminson, P.D, R.J.Martin, G.S. Francis and D.R. Wilson (1995). Drought effects on biomass production and radiation use efficiency in barley. Field Crop Res., 43: 77-86. Jensen, M.E. and Haise, H.R. 1963. Estimating evapotranspiration from solar radiation. J.Irrig. and Drain. Div., ASCE, 89:15-41. Jensen, M.E., R.D. Burman, and R.G. Allen (ed.). 1990. Evapotranspiration and irrigation water requirements. ASCE Manual 70. Jones, FE 1992 and Evaporation of water: with emphasis on applications and measurements, 1st edn, Lewis Publishers, Chelsea, Michigan. Jovanovic, Z., R.Stikic, B. Vucelic-Radovic, M. Paukovic, Z. Brocic, G.Matovic, S.Rovcanin and M. Mojevic, 2010. Partial root-zone drying increases WUE, N and antioxidant content in field potatoes. European Jour. of Agro. 33: 124-131. Kang, S.Z., Z.S. Liang, W. Hu and J. H Zhang, 1998. Water use efficiency of controlled alternate irrigation on root divided maize plants. Agri. Water Management. 38: 69-76. Kang, S.Z., Z.S. Liang, Y.H. Pan, P.Z. Shi and J.H. Zhang,

2000a. Alternate

furrow irrigation for maize production in an arid area. Agri. Water Management. 45: 267-274. Kang, S.Z., P. Shi, Y.H. Pan, Z.S. Liang, X.T. Hu and J. Zhang, 2000b. Soil water distribution, uniformity and water-use efficiency under alternate furrow irrigation in arid areas. Irrig. Science. 19: 181-190. Kang, S.Z., X.Hu,

I. Goodwin and P. Jerie, 2002. Soil water distribution, water

use, and yield response to partial root zone drying under a shallow groundwater table condition in a pear orchard. Scientia Horticulturae. 78

References

92: 277-291. Kang, S.Z., X. Hu, P. Jerie and J. H. Zhang, 2003. The effects of partial root zone drying on root, trunk sap flow and water balance in an irrigated pear (Pyrus communis L.) orchard. Jour. of Hydrology. 280: 192-206. Kang, S.Z. and J.H. Zhang, 2004. Controlled alternate partial root-zone irrigation: its physiological consequences and impact on water use efficiency. Jour. of Experimental Botany, 55: 2437-2446. Karoun, M. and M. El-Mourid, 2009. Improving water productivity of crops in the Mediterranean region: Case of cereals. Proceedings of the International Agriculture Durable en Region Mediteraneene, May 14-16, 2009, Rabat, Maroc, pp: 123-130. Kijne, J.W., R. Barker and D. Molden, 2003. Water Productivity in Agriculture: Limits and Opportunity for Improvement. CABI, Cambridge, UK., ISBN: 0 85199 669 8. Kirda, C,R. Kanber and K. Tulucu 1999.Yield response of cotton, maize, soybean, sugar beet, sunflower and wheat to deficit irrigation. In: C. Kirda, P. Moutonnet, C. Hera & D.R. Nielsen, eds. Crop yield response to deficit irrigation, Dordrecht, The Netherlands, Kluwer Academic Publishers. Kirda, C., M.Cetin, Y.Dasgan, S. Topcu, H. Kaman, B.Ekici, M.R. Derici, A.I. Ozguven, 2004. Yield response of greenhouse grown tomato to partial root drying and conventional deficit irrigation. Agri. Water Management, 69: 191-201. Kirda, C., S.Topcu, H. Kaman, A.C. Ulger, A. Yazici, M. Cetin, M.R. Derici, 2005. Grain yield response and N-fertilizer recovery of maize under deficit irrigation. Field Crops Research. 93: 132-141.

78

References

Kirnak, H., C. Kaya, D. Higgs, and I. Tas. 2003. Responses of drip irrigated bell peper to water stress and different nitrogen levels with or without mulch cover. Journal of Plant Nutrition 26 (2): 263-277, 2003 Kiziloglu, F.M., U. Sahin, Y. Kuslu and T. Tunc. 2009. Determining water-yield relationship, water use efficiency, and crop pan coefficients for silage maize in a semiarid region. Irrig. Sci. 27: 129–137. Klute, 1986. Soil physical properties and mineralogical analysis. Kriedmann, P.E. and I. Goodwin, 2003. Regulated deficit irrigation and partial root zone drying. Irrigation insights no. 4, Land and Water Australia, Canberra, 102p. Lack, S.H, A. Naderi, S.A. Siadat, A. Ayenehband and Gh.Noormohammadi. 2005. Effect of different levels of nitrogen and plant density on grain yield, its components and water use efficiency. Lack, S .H, H. Dashti, G.H. Abadooz and A. Modhej, 2011. Effect of different levels of irrigation and planting pattern on grain yield, yield components and water use efficiency of corn grain (Zea mays L.) hybrid SC. 704. African Journal of Agricultural Research Vol. 7(18), pp. 2873-2878, 12 May, 2012 Lascano, R.J. and R.E. Sojka, 2007. Preface. In: Irrigation of agricultural crops (Lascano, R.J., and Sojka, R.E. eds.), 2nd edition, Agronomy Monograph. 30. ASA-CSSA-SSSA publishing, 664p. Leib, B.G., H.W. Caspari, C.A. Redulla, P.K. Andrews and J. Jabro, 2006. Partial root zone drying and deficit irrigation of ‘Fuji’ apples in a semi-arid climate. Irrigation Science, 24: 85-99.

78

References

Li, F., J. Liang, Sh. Kang and J. Zhang, 2007. Benefits of alternate partial root-zone irrigation on growth, water and nitrogen use efficiencies modified by fertilization and soil water status in maize. Plant and Soil. 295: 279-291. Liu, F., Jensen, C.R. and Andersen, M.N., 2003. Hydraulic and chemical signals in the control of leaf expansion and stomatal conductance in soybean exposed to drought stress. Functional Plant Biology, 30: 65-73. Liu, F., M.N.Andersen, S.E. Jacobsen and C.R. Jensen, 2005a. Stomatal control and water use efficiency of soybean (Glycine max L. Merr) during progressive soil drying. Environ. and Experimental Botany. 54: 33-40. Liu, F., C.R. Jensen and M.N. Andersen, 2005b. A review of drought adaptation in crop plants: changes in vegetative and reproductive physiology induced by ABA-based chemical signals. Australian Jour. of Agri. Research, 56: 12451252. Liu, X.Y. and Lin, E. (2005): Performance of the Priestley-Taylor equation in the semiarid climate of North China, Agric. Water Manage. 71 (1), 1–17. Liu, F., A.Shahnazari, M.N. Andersen, S.E. Jacobsen, C.R. Jensen, 2006a. Physiological responses of potato (Solanum tubersum L.) to partial rootzone drying: ABA signaling, leaf gas exchange, and water use efficiency. Jour. of Experimental Botany, 57: 3727-3735. Liu, F., A.Shahnazari, M.N. Andersen, S.E. Jacobsen, C.R. Jensen, 2006b. Effects of deficit irrigation (DI) and partial root drying (PRD) on gas exchange, biomass partitioning, and water use efficiency in potato. Scientia Horticulturae, 109: 113-117. Loveys, B.R., M. Stoll, P.R. Dry and M.G. McCarthy2000. Using plant physiology to improve the water use efficiency of horticultural crops. Acta Horticulture, 537: 187-197. 78

References

Lynch DR, N. Foroud, GC. Kozub and BC. Farries, 1995. The effect of moisture stress at three growth stages on the yield components of yield and processing quality of eight potato cultivars. Amer. Potato J. 72: 375-386. Marsal J., Mata M., del Campo J., Arbones A., Vallverdú X., Girona J., Olivo N. (2008): Evaluation of partial root-zone drying for potential field use as a deficit irrigation technique in commercial vineyards according to two different pipeline layouts. Irrigation Science, 26: 347–356. Martin, D.L. and J.R. Gilley 1993. Irrigation Water Requirements. Chapter 2 of the SCS National Engineering Handbook, Soil Conservation Service, Washington D.C., 284 pp. Masoud, R. and S. Ghodratola 2010.Water Use Efficiency of Corn as Affected by Every Other Furrow Irrigation and Planting Density. World Applied Sciences Journal 11 (7): 826-829, 2010 ISSN 1818-4952 Mingo, D.M., M.A. Bacon and W.J. Davies 2003. Non-hydraulic regulation of fruit growth in tomato plants (Lycopersicon esculentum cv. Solairo) growing in drying soil. Journal of Experimental Botany, 54: 1205-1212. Mingo, D.M., J. Theobald, M.A. Bacon, W.J. Davies and I.C. Dodd,

2004.

Biomass allocation in tomato (Lycopersicon esculentum) plants grown under partial root zone drying: enhancement of root growth. Functional Plant Biology, 31: 971-978. Mohammed, K., T. Oweis, R. A. E. Enein and M. Sherif, 2012. Yield and water productivity of maize and wheat under deficit and raised bed irrigation practices in Egypt. African Journal of Agricultural Research Vol. 7(11), pp. 1755-1760, 19 March, 2012.

77

References

Morison, J.I.L., N.R. Baker, P.M. Mullineaux and W.J. Davies,

2008. Improving

water use in crop production. Philosophical Transactions of the Royal Society (London) B, 363: 639-658. Murray, F. W. 1967. “On the computation of saturation vapor pressure.” J. Appl. Meteorol., 6:203-204. Musick, J.I and DA.Dusck, 1980. Planting date and water deficit effects on development and yield of irrigated winter wheat. Agron. J. 72, 45-52. Nangia, V., H. Turral and D. Molden, 2008. Increasing water productivity with improved N fertilizer management. Irrig. Drain. Syst., 22: 193-207. Page, A.L., R.H. Miller and D.R. Keeney, 1982. Methods of Soil Analysis. 2nd Edn., Amercen Society of Agronomy, Madison, WI., USA. Sillanpaa, M., 1982. Micronutrients and the nutrient status of soils. A Global Study FAO Soils.Bulletin, No: 48, FAO, Rome, Italy. Uzoije, A.P. and A.A. Onunkwo, 2011. Soil quality modeling of a highly acidic Eutric-tropofluvent soil Int. J. Soil Sci., 6: 164-175. Paez, A, Gonzalez OME, X.Y. Rausquin, A. Salazar and A. Casanova (1995). Water stress and clipping management effects on Guinea grass. I. Growth and biomass allocation. Agron. J., 87: 698-706.

Pandey, R.K, J.W. Marienville and A. Adum (2000). Deficit irrigation and nitrogen effect on maize in a sahelian environment. I. Grain yield components. Agric. Water Manag, 46: 1-13.

Passioura, J., 2006. Increasing crop productivity when water is scarce-from breeding to field management. Agric. Water Manage. 80: 176-196.

77

References

Penman, H.L. 1948. Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London, A193: 120-146. Pereira, L.S., A. Perrier, R.G. Allen, and I. Alves. 1999. Evapotranspiration: Concepts and future trends. Journal of Irrigation and Drainage Engineering 125(2):45-51 Pereira, L., S.T. Oweis and A. Zairi, 2002. Irrigation management under water scarcity. Agric. Water Manage., 57: 175-206. Poni, S., M. Tagliavini D. Neri, Scudellari and M. Toselli 1992. Influence of root pruning and water-stress on growth and physiological factors of potted apple, grape, peach and pear trees. Scientia Horticuture, 52: 223-236.

Priestley, C.H.B. and Taylor, R.J. 1972. On the assessment of surface heat flux and evaporation using large scale parameters. Mon. Weath. Rev., 100: 81-92.

Rodrigues, M.L., T.P. Santos, A.P. Rodrigues, C.R. de Souza, C.M Lopes, J.P. Maroco, J.S. Pereira and M.M. Chaves.

2008. Hydraulic and chemical

signaling in the regulation of stomatal conductance and plant water use in field grapevines growing under deficit irrigation. Functional Plant Biology, 35: 565-579.

Rockstrom, J., J. Barron and P. Fox, 2003. Water Productivity in Rainfed Agriculture: Challenges and Opportunities for Smallholders Farmers in Drought-Prone Tropical Ecosystems. In: Water Productivity in Agriculture, Kjine, J.W., R. Barker and D. Molden (Eds.). CABI, Wallingford.

Sadras, V.O., 2009. Does partial root-zone drying improve irrigation water productivity in the field? A meta analysis. Irrigation Science, 27: 183-190.

78

References

Saeed, H., I.G. Grove, P.S. Kettlewell and N.W. Hall,

2008. Potential of partial

root zone drying as an alternative irrigation technique for potatoes (Solanum tuberosum). Annals of Applied Botany, 152: 71-80.

Samadi, A. and A.R. Sepaskhah,

1984. Effects of alternate furrow irrigation on

yield and water use efficiency of dry beans. Iran Agric. Research, 3: 95115.

Sepaskhah, A.R., S.A.Sichani and B. Bahrani,

1976. Subsurface and furrow

irrigation evaluation for bean production. Transactions of the ASAE, 19: 1089-1093.

Sepaskhah, A.R., A.A. Kamgar-Haghighi, A.A., 1997. Water use and yields of sugarbeet grown under every-other furrow irrigation with different irrigation intervals. Agri. Water Management, 34: 71-79. Sepaskhah, A.R. and M.H. Khajehabdollahi, 2005. Alternate furrow irrigation with different irrigation intervals for maize (Zea mays L.). Plant Production Science, 8: 592-600. Sepaskhah, A.R. and A.R. Parand. 2006. Effects of alternate furrow irrigation with supplemental every-furrow irrigation at different growth stages on the yield of maize (Zea mays L.). Plant production Science, 9: 415-421 Sepaskhah, A.R., S.N. Hosseini,

2008. Effects of alternate furrow irrigation and

nitrogen application rates on winter wheat (Triticum aestivum L.) yield, water- and nitrogen-use efficiencies. Plant Production Science, 11: 250259.

78

References

Sepaskhah, A.R and M.M. Ghasemi, , 2008. Every-other furrow irrigation with different irrigation intervals for sorghum. Pakistan Journal of Biological Science, 11: 9. 1234-1239. Shahnazari, A., F. Liu, M.N. Andersen, S.E. Jacobsen and C.R. Jensen,

2007.

Effects of partial root-zone drying on yield, tuber size and water use efficiency in potato under field conditions. Field Crops Research, 100: 117124. Shahnazari, A., S.H. Ahmadi, P.E. Lærke, F. Liu, F. Plauborg, S.E. Jacobsen, C.R. Jensen and M.N. Andersen,

2008. Nitrogen dynamics in the soil-plant

system under deficit and partial root-zone drying irrigation strategies in potatoes. Europ. Jour. of Agro., 28: 65-73. Shani-Dashtgol , A., S. Jaafari, N. Abbasi, A. Malaki,

2006. Effect of alternate

furrow irrigation (PRD) on yield quantity and quality of sugarcane in southern farm in Ahvaz. Proceeding of national conference on Irrigation and Drainage Networks Management. Shahid Chamran University of Ahvaz. 2-4 May, Pp: 565-572. [In Farsi]. Shock CC, ZA. Holmes, TD. Strieber, EP. Eldredge and P.Zhang 1993. The effect of timed water stress on quality, total solids and reducing sugar content of potatoes. Amer. Potato J. 70, 227-241. Sleper, D.A., S.L. Fales and M.E. Collins, 2007. Foreword. In: Irrigation of agricultural crops (R.J. Lascano and R.E. Sojka, eds.), 2nd edition, Agronomy Monograph no. 30. ASA-CSSA-SSSA publishing, 664p. Snyder, R.L. and Pruitt, W.O. 1992. Evapotranspiration data management in California. Proceedings of the Irrigation and Drainage sessions of ASCE Water Forum '92, T. Engman, ed. ASCE, New York, New York. p.128133. 78

References

Sobeih, W.Y., I.C. Dodd, M.A. Bacon, D. Grieson and W.J. Davies, 2004. Longdistance signals regulating stomatal conductance and leaf growth in tomato (Lycopersicon esculentum) plants subjected to partial root zone drying. Jour. of Experimental Botany, 55: 2353-2363. Songsri, P., S. Jogloy, N. Vorasoot, C. Akkasaeng, A. Patanothai and C.C. Holbrook,

2008. Root distribution of drought-resistant peanut genotypes

in response to drought. Jour. of Agro. and Crop Science, 194: 92-103.

Sowder, C. M., L. Tarpley, M.D.Vietor and F.R. Miller (1997). Leaf photo assimilation and partitioning in stress-tolerant sorghum. Crop Sci., 37: 833838.

Stoll, M., B. Loveys and P. Dry, 2000. Hormonal changes induced by partial root zone drying of irrigated grapevine. Jour. of Experimental Botany, 51: 16271634. Stegman EC. 1982. Corn grain yield as influenced by timing of evapotranspiration. Irri. Sci. 3, 75-87. Stone, P.J, D.R. Wilson, P.D. Jamieson and R.N. Gillespie RN (2001). Water deficit effects on sweet corn. Part II. Canopy development. Aust. J. Agric. Res., 52: 115-126. Suleiman, A. A. and Hoogenboom, G. (2007): Comparison of Priestley-Taylor and FAO-56

Penman-Monteith

for

daily

reference

evapotranspiration

estimation in Georgia, J. Irrig. Drain. Engg. 133 (2), 175–182. Taiz, L. and E. Zeiger. 2006. Plant physiology. SinauerAssociates, Inc., Publishers, 764p. Tang, L.S., Y. Li and J. Zhang, 2005. Physiological and yield responses of cotton under partial root zone irrigation. Field Crops Research, 94: 214-223. 78

References

Tardieu, F. and W.J. Davies, 1993. Integration of hydraulic and chemical signaling in the control of stomatal conductance and water status of droughted plants. Plant, Cell and Environment, 16: 341-349. Thompson, A.J., J. Andrews, B. J. Mulholland, J.M.T. McKee, H.W. Hilton, J.S. Horridge, G.D. Farquhar, R.C. Smeeton, I.R.A. Smillie, C.R. Black and I.B. Taylor,

2007. Overproduction of Abscisic acid in tomato increases

transpiration efficiency and root hydraulic conductivity and influences leaf expansion. Plant Physiology, 143: 1905-1917. Topcu, S., C. Kirda, Y. Dasgan, H. Kaman, M. Cetin, A. Yazici and M.A. Bacon, 2007. Yield response and N fertilizer recovery of tomato grown under deficit irrigation. Europ. Jour. of Agronomy, 26: 64-70. Wahbi, S., R.Wakrim, B. Aganchich, H. Tahi and R. Serraj, 2005. Effects of partial root zone drying (PRD) on adult olive tree (Olea europaea) in field conditions under arid climate I. Physiological and agronomic responses. Agriculture, Ecosystems and Environment, 106: 289-301. Wakrim, R., S.Wahbi, H. Tahi, B. Aganchich, R. Serraj, 2005. Comparative effects of partial root drying (PRD) and regulated deficit irrigation (RDI) on water relations and water use efficiency in common bean (Phaseolus vulgaris L.). Agri., Ecosystems & Environment, 106: 275-287. Wang , F.X., Y. Kang and S.P. Liu, 2006. Effects of drip irrigation frequency on soil wetting pattern and potato growth in North China Plain. Agri. Water Management, 79: 248-264. Wang, H., F. Liu, M.N. Andersen and C.R. Jensen, 2009. Comparative effects of partial root-zone drying and deficit irrigation on nitrogen uptake in potatoes (Solanum tuberosum L.). Irrigation Science, 27: 443-447.

78

References

Wang , Y.S, F.L. Liu, M.N. Andersen, C.R. Jensen CR. 2010a. Improved plant nitrogen nutrition contributes to higher water use efficiency in tomatoes under alternate partial root-zone irrigation. Functional Plant Biology 37, 175–182 Watson, I. and A.D. Burnett. 1995. Hydrology: An environmental approach. Boca Raton, FL: CRC Press. Wilkinson, S., 1999. PH as a stress signal. Plant Growth regulation, 29: 87-99. Zegbe, J.A., Behboudian, M.H., 2008. Plant water status, CO2 assimilation, yield, and fruit quality of 'Pacific RoseTM' apple under partial root zone drying. Advances in Horti. Sci., 22: 27-32. Winter, SR. 1980. Suitability of sugar beets for limited irrigation in semi-arid climate. Agron. J. 72, 649–653 Wright, J.L., 1981. Crop coefficients for estimates of daily crop evapotranspiration Irrig. Sched. for Water and Engergy Conserv. in the 80’s, ASAE, p. 18-26. Wright, J.L. 1982. New Evapotranspiration Crop Coefficients. Journal of Irrigation and Drainage Division, ASCE, 108:57-74. Yazar , A., S.M. Sezen, and B. Gencel. 2002. Drip irrigation of corn in the Southeast Anatolia Project (GAP) area in Turkey. Journal of Irrigation and Drain Engineering 51: 293–300. Yazar A, F. Gökçel1, and M.S. Sezen. 2009. Corn yield response to partial root zone drying and deficit irrigation strategies applied with drip system. Plant soil Environ. 55 (11): 494–503 Yildirm, Y.E. 1993. Yield response of maize to water stress under Ankara conditions. Ph. D. Thesis. Ankara University, Graduate School of Natural and Applied Sciences, Ankara-Turkey. 78

References

Yildirm, O., S. Kodal, F. Selenay, Y.E. Yıldırım and A. Ozturk. 1996. Corn grain yield response to adequate and deficit irrigation. Turkish. J. Agric. Forestry. 20: 283-288. Zegbe, J.A., M.H. Behboudian and B.E. Clothier, 2004. Partial root zone drying is a feasible option for irrigating processing tomatoes. Agri. Water Management, 68: 195-206. Zegbe, J.A., M.H. Behboudian and B.E. Clothier, 2006. Responses of 'Petopride' processing tomato to partial root zone drying at different phenological stages. Irrig. Science, 24: 203-210. Zhang, H., 2003. Improving water productivity through deficit irrigation: Examples from Syria, the north China Plain and Oregon, USA. In: Water Productivity in Agriculture: Limits and Opportunities for Improvement (Kijne, J.W., Barker, R., and Molden, D. eds). CABI publishing, 332p. Ziska, L.H. and A.E. Hall, 1983. Seed yields and water use of cowpeas (Vigna unguiculata L. Walp.) subjected to planned water deficit irrigation. Irri. Sci. 3, 237–245. .

78

Appendices

Appendix (1): Examples on calculation of (ETos, EToT) reference evapotranspiration for grass and alfalfa crop by dependent on Halabja meteorological data and adjusted for flowering stage in second treatments. Country: Iraq/Sulaimanya - Halabja

Period: Parameter Tmax Tmin Tmean

Longitude

latitude

altitude

45°58'E

35°11'N

690m

June 2012 result 40.1 26.5 2

unit °C °C °C

7.41

kPa kPa

From eq.24

3.46

kPa

From eq.25

5.43

kPa

From eq.26

0.286

kPa °Cˉ¹

From eq.27

1.04

kPa

From eq.29 2 From appendix 7 From eq.30

4.39

kPa

1 From eq.24

VPD

Radiation J for the 15th of June

166 0.612

Rad.

From eq.31

0.968

Rad.

From eq.32

0.406

From eq. 33 Gs constant

1.877 0.082 41.55

Rad. MJ mˉ²dˉ¹ MJ mˉ² dˉ¹

N for the 15th of June

14.35

hours

n= From eq.35

10.1 25.1

hours MJ mˉ² dˉ¹

From eq.36

31.74

MJ mˉ² dˉ¹

From eq.29

From appendix 8

79

Appendices From eq.37 From appendix 9 From appendix 9 From eq.38

19.25 47.21

6.1

MJ mˉ² dˉ¹ MJ mˉ² dˉ¹ °Cˉ¹ MJ mˉ² dˉ¹ °Cˉ¹ MJ mˉ² dˉ¹

From eq.39 From eq.40

13.15 0.616

MJ mˉ² dˉ¹ MJ mˉ² dˉ¹

39.53

From eq.42

kPa

From eq.43

0.062

kPa °Cˉ¹

3 From eq.23

8.3

mm dˉ¹

From eq.5 4 From eq.7 From eq.9

9.13

mm dˉ¹

118.8 0.38

mm

From eq.8 From eq.10

45.15 0.7

mm

6.39

mm dˉ¹

11.8

mm dˉ¹

10.62

mm dˉ¹

118.8 0.32 38.01 0.65

mm

6.9

mm dˉ¹

‫٭‬

From eq.57 5 From eq.23 From eq.5 6 From eq.7 From eq.9 From eq.8 From eq.10

‫٭‬

From eq.57

79

mm

Appendices

Appendix (2–A): Actual evapotranspiration for (1st treatment) estimated by FAO-PM grass equation and adjusted evapotranspiration for 2nd, 3rd , 4th and 5th treatments for all growth stage. Growth stage

ETos T1 mm/d Kc

Germination April15-30 Vegetative growth May1-31 Flowering June 1-30 Harvesting July1-31

4.15

0.4

1.65

1.0

6.5

1.0

6.5

0.79 5.13

0.33 2.14

0.39 2.53

0.16 1.07

8.3

1.1

9.13

0.7

6.39

0.30 2.74

0.35 3.19

0.15 1.37

8.7

0.55 4.78

0.85 4.06

0.34 1.62

0.42 2.03

0.17 0.81

ETm mm/d

T2 Ks

T3 Ks

ET adj mm/d 1.65 1.0

T4 Ks

ET adj mm/d 1.65 1.0

T5 Ks

ET adj mm/d 1.65 1.0

Appendix (2–B): Actual evapotranspiration for (1st treatment) estimated by FAO-PM alfalfa equation and adjusted 77

ET adj mm/d 1.65

Appendices

evapotranspiration for 2nd, 3rd , 4h and 5th treatments for all growth stage.

Growth stage

EToT

Germination April 15-30 Vegetative growth May 1-31 Flowering June 1-30 Harvesting July 1-31

5.81

0.2

9.24

0.34 3.14

0.93 2.92

0.36 1.13

0.46 1.46

0.18 0.56

11.8

0.9

0.65 6.92

0.29 3.08

0.32 3.46

0.14 1.54

12.21

0.44 5.37

0.83 4.45

0.34 1.82

0.41 2.22

0.17 0.91

mm/d

T1 Kc

ETm mm/d

1.03

10.62

T2 Ks

1.0

ET adj mm/d 1.03

011

T3 Ks

1.0

ET adj mm/d 1.03

T4 Ks

1.0

ET adj mm/d 1.03

T5 Ks

1.0

ET adj mm/d 1.03

Appendices

Appendix (2 –C): Actual evapotranspiration for (1st treatment) estimated by pan evaporation Class (A) and adjusted evapotranspiration for 2nd, 3rd, 4th and 5th treatments for all growth stage.

Growth stage

ETo T1 mm/d Kc

ETm mm/d

T2 Ks

T3 Ks

ET adj mm/d 1.46 1.0

T4 Ks

ET adj mm/d 1.46 1.0

T5 Ks

ET adj mm/d 1.46 1.0

ET adj mm/d 1.46

Germination 3.66 April 15-30

0.4

1.46

1.0

Vegetative growth May 1-31

5.0

1.0

5.0

0.85 4.25

0.34 1.7

0.42 2.12

0.17 0.85

Flowering June 1-30

6.87

1.1

7.56

0.75 5.67

0.32 2.42

0.37 2.83

0.16 1.21

Harvesting July 1-31/7

7.2

0.55 3.96

0.89 3.52

0.35 1.38

0.44 1.76

0.17 0.69

010

Appendices

Appendix (3): Pan coefficient (K pan) for class A pan for different ground cover and level of mean relative humidity and 24 hour wind (Allen, 1998). Class A pan RH mean % Wind m. sˉ¹

Light <2

Moderate 2-5

Strong 5-8

Very strong >8

Case A: Pan placed in short green cropped area low medium high < 40-70 > 70 40 Windward side distance of green crop m 1 .55 .65 .75 10 .65 .75 .85 100 .7 .8 .85 1000 .75 .85 .85 1 .5 .6 .65 10 .6 .7 .75 100 .65 .75 .8 1000 .7 .8 .8 1 .45 .5 .6 10 .55 .6 .65 100 .6 .65 .7 1000 .65 .7 .75 1 .4 .45 .5 10 .45 .55 .6 100 .5 .6 .65 1000

.55

.6

Case B1: Pan placed in fallow area low medium high < 40-70 > 70 40 Windward side distance of dry fallow m 1 10 100 1000 1 10 100 1000 1 10 100 1000 1 10 100

.7 .6 .55 .5 .65 .55 .5 .45 .6 .5 .45 .4 .5 .45 .4

.8 .7 .65 .6 .75 .65 .6 .55 .65 .55 .5 .45 .6 .5 .45

.85 .8 .75 .7 .8 .7 .65 .6 .7 .65 .6 .55 .65 .55 .5

1000

.35

.4

.45

.65

Appendix (4): Some selected meteorological data that have been provided by Halabja agro-meteorological station during seasonal growth at year 2012. Metrological data T max °C T min °C Precipitation (mm) Max Relative humidity (RH %) Min Relative humidity (RH %) Sunshine duration(hour) Pan evaporation (mm) Wind speed (m sˉ¹)

March 15.5 5.8 12.8 50.3 36.3 6.0 3.6 2.0

April 26 15.1 7 44 29.9 7.5 6.1 1.8

011

May 33 21.4 4.2 28 20.9 6.2 9.1 2.2

June 40.1 26.5 0 22.2 17.7 9.8 12.5 2.3

July 42.8 29.1 0 21.1 17.3 10.1 13.1 2.2

August 42.0 27.4 0 21.6 18 9.3 11.7 2.1

Appendices

Appendix (5): Values for Cn and Cd Calculation Time Step Daily Hourlydaytime Hourly-night time

Short Reference, ETos Cn Cd 900 0.34 37 0.24 37

0.96

Tall Reference, ETOT Cn Cd 1600 0.38 66 0.25 66

1.7

Units for ETos, ETOT

Units for Rn , G

mm.dˉ¹ mm.dˉ¹

MJ mˉ²dˉ¹ MJ mˉ²dˉ¹

mm.dˉ¹

MJ mˉ²dˉ¹

Appendix (6): ASCE Penman-Monteith Terms Standardized for Application of the Standardized Reference Evapotranspiration Equation Term Reference vegetation height, h height of air temperature and humidity measurements, zh height of wind measurements, zw zero plane displacement height Lambda Surface resistance, rs, daily Surface resistance, rs, daytime

ETos 0.12m 1.5-2.5m

EToT 0.5m 1.5-2.5m

2.0m 0.08m 2.45 MJ kgˉ¹ 70 s mˉ¹

2.0m 0.08m 2.45 MJ kgˉ¹ 45 s mˉ¹

50 s mˉ¹ 30 s mˉ¹

Surface resistance, rs, nighttime

200 s mˉ¹ 200 s mˉ¹

011

Appendices

Appendix (7): Number of the day in the year (J).

April

May

June

July

August

September

October

November

December

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

March

January 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

February

Day

32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 (60) -

60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90

91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 -

121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151

152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177, 178 179 180 181 -

182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212

213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243

244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 -

274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304

305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 -

335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365

011

Appendices

Appendix (8): Mean daylight hours (N) for different latitudes for the 15th of the month

1

Values for N on the 15th day of the month provide a good estimate (error < 1 %) of N averaged over all days within the month. Only for high latitudes greater than 55° (N or S) during winter month's deviations may be more than 1%.

011

Appendices

Appendix (9) Stefan-Boltzmann law value at different temperatures (°C) With = 4.903 10-9 MJ K-4 m-2 day-1 and TK = T [°C] + 273.16

T (°C) 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5

(MJ m-2 d-1) 27.70 27.90 28.11 28.31 28.52 28.72 28.93 29.14 29.35 29.56 29.78 29.99 30.21 30.42 30.64 30.86 31.08 31.30 31.52 31.74 31.97 32.19 32.42 32.65 32.88 33.11 33.34 33.57 33.81 34.04 34.28 34,52

T (°C) 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 24.5 25.0 25.5 26.0 26.5 27.0 27.5 28.0 28.5 29.0 29.5 30.0 30.5 31.0 31.5 32.0 32.5

(MJ m-2 d-1) 34.75 34.99 35.24 35.48 35.72 35.97 36.21 36.46 36.71 36.96 37.21 37.47 37.72 37.98 38.23 38.49 38.75 39.01 39.27 39.53 39.80 40.06 40.33 40.60 40.87 41.14 41.41 41.69 41.96 42.24 42.52 42.80

011

T (°C) 33.0 33.5 34.0 34.5 35.0 35.5 36.0 36.5 37.0 37.5 38.0 38.5 39.0 39.5 40.0 40.5 41.0 41.5 42.0 42.5 43.0 43.5 44.0 44.5 45.0 45.5 46.0 46.5 47.0 47.5 48.0 48.5

(MJ m-2 d-1) 43.08 43.36 43.64 43.93 44.21 44.50 44.79 45.08 45.37 45.67 45.96 46.26 46.56 46.85 47.15 47.46 47.76 48.06 48.37 48.68 48.99 49.30 49.61 49.92 50.24 50.56 50.87 51.19 51.51 51.84 52.16 52.49

Appendices

Appendix (10): Ranges of maximum effective rooting depth (Zr) and soil water depletion fraction for no stress (p), for common crops (Table22, Allen et al., 1998) Crop g. Fibre Crops Cotton Flax Sisal h. Oil Crops Castorbean (Ricinus) Rapeseed, Canola Safflower Sesame Sunflower i. Cereals Barley Oats Spring Wheat Winter Wheat Maize, Field (grain) (field corn) Maize, Sweet (sweet corn) Millet Sorghum - grain - sweet

Maximum Root Depth (m)

Depletion Fraction(p) (for ET » 5 mm/day)

1.0-1.7 1.0-1.5 0.5-1.0

0.65 0.50 0.80

1.0-2.0 1.0-1.5 1.0-2.0 1.0-1.5 0.8-1.5

0.50 0.60 0.60 0.60 0.45

1.0-1.5 1.0-1.5 1.0-1.5 1.5-1.8 1.0-1.7

0.55 0.55 0.55 0.55 0.55

0.8-1.2

0.50

1.0-2.0

0.55

1.0-2.0 1.0-2.0

0.55 0.50

019

Appendices

Appendix (11-A): Statistical analysis for maize yield. S.O.V Block Treatments Error Total

d.f 2 4 8 14

S.S 121000 62702391.6 4000 62827391.6

M.S 60500 15675597.9 500

F.Cal 121 31351.2**

Appendix (10-B): Statistical analysis for biological yield. S.O.V Method Treatments Error Total

d.f 2 4 8 14

S.S 100000 257351805.6 8990 257460795.6

M.S 50000 64337951.4 1123.75

F.Cal 44.49 57252.9**

Appendix (10-C): Statistical analysis for harvest index. S.O.V Method Treatments Error Total

d.f 2 4 8 14

S.S 0.00014 0.03523 0.0001 0.0359

M.S 0.00039 0.0088 0.0000137

F.Cal 28.46 642.33**

Appendix (10-D): Statistical analysis for field Water use efficiency. S.O.V block Treatments Error Total

d.f 2 4 8 14

S.S 0.0057 0.0422 0.0009 0.0488

019

M.S 0.00285 0.01055 0.0001

F.Cal 28.5 105.5**

Appendices

Appendix (10-E): Statistical analysis for crop water use efficiency by pan evaporation (class A) method. S.O.V Method Treatments Error Total

d.f 2 4 8 14

S.S 0.1073 1.2884 0.0052 1.4009

M.S 0.05365 0.3221 0.00065

F.Cal 82.53 495.53**

Appendix (10-F): Statistical analysis for crop water use efficiency by FAO-PM grass equation. S.O.V Method Treatments Error Total

d.f 2 4 8 14

S.S 0.0776 0.8858 0.0024 0.9658

M.S 0.0388 0.22145 0.0003

F.Cal 129.33 738.16**

Appendix (10-G): Statistical analysis for crop water use efficiency by FAO-PM alfalfa equation.

S.O.V Method Treatments Error Total

d.f 2 4 8 14

S.S 0.04626 1.3138 0.00044 1.2905

017

M.S 0.0231 0.3284 0.000055

F.Cal 420 5970.9**

Appendix (2 –A): Actual evapotranspiration for (1st treatment) estimated by FAO-PM grass equation and adjusted evapotranspiration for 2nd, 3rd , 4th and 5th treatments for all growth stage.

Growth stage

ETos mm dˉ¹

T1 Kc

T2 Ks

Germination April15-30 Vegetative growth May1-31 Flowering June 1-30 Harvesting July1-31

4.15

0.4

ETm mm dˉ¹ 1.65

6.5

1.0

6.5

0.79 5.13

0.33 2.14

0.39 2.53

0.16 1.07

8.3

1.1

9.13

0.7

6.39

0.30 2.74

0.35 3.19

0.15 1.37

8.7

0.55 4.78

0.85 4.06

0.34 1.62

0.42 2.03

0.17 0.81

1.0

ET adj mm dˉ¹ 1.65

T4 Ks 1.0

ET adj mm dˉ¹ 1.65

T5 Ks 1.0

ET adj mm dˉ¹ 1.65

99

1.0

ET adj mm dˉ¹ 1.65

T3 Ks

Appendix (2–B): Actual evapotranspiration for (1st treatment) estimated by FAO-PM alfalfa equation and adjusted evapotranspiration for 2nd, 3rd , 4h and 5th treatments for all growth stage.

Growth stage

EToT

Germination April 15-30 Vegetative growth May 1-31 Flowering June 1-30 Harvesting July 1-31

5.81

0.2

1.03

1.0

1.03

1.0

9.24

0.34

3.14

0.93

2.92

0.36 1.13

0.46 1.46

0.18 0.56

11.8

0.9

10.62

0.65

6.92

0.29 3.08

0.32 3.46

0.14 1.54

12.21

0.44

5.37

0.83

4.45

0.34 1.82

0.41 2.22

0.17 0.91

ETm mm dˉ¹

T2 Ks

ET adj mm dˉ¹

T3 Ks

ET adj mm dˉ¹

1.03

T4 Ks

1.0

ET adj mm dˉ¹

1.03

T5 Ks

1.0

ET adj mm dˉ¹

1.03

011

mm dˉ¹

T1 Kc

Appendix (2 –C): Actual evapotranspiration for (1st treatment) estimated by pan evaporation Class (A) and adjusted evapotranspiration for 2nd, 3rd , 4th and 5th treatments for all growth stage.

ETop mm dˉ¹

T1 Kc

ETm mm dˉ¹

T2 Ks

Germination 3.35 April 15-30

0.4

1.34

1.0

Vegetative growth May 1-31

5.0

1.0

5.0

Flowering June 1-30

6.87

1.1

Harvesting July 1-31/7

7.2

0.55

ET adj mm dˉ¹ 1.34

T3 Ks

ET adj mm dˉ¹

T4 Ks

1.0

1.34

1.0

0.85 4.25

0.34

1.7

7.56

0.75 5.67

0.32

3.96

0.89 3.52

0.35

ET adj mm dˉ¹ 1.34

T5 Ks

ET adj mm dˉ¹

1.0

1.34

0.42 2.12

0.17

0.85

2.42

0.37 2.83

0.16

1.21

1.38

0.44 1.76

0.17

0.69

010

Growth stage