OPTIMUM UTILIZATION OF GROUND WATER IN KOBO VALLEY, EASTERN AMHARA, ETHIOPIA

A Thesis Presented to the Faculty of the Graduate School of Cornell University in the Partial Fulfillment of the Requirements for the Degree of Master of Professional Studies (MPS)

By Abrham Melesse Endalamaw August 2009

ABSTRACT

Shortage of precipitation in Kobo valley limits the production of vegetables during dry periods and the yield of cereals in the rainy periods. Irrigation from ground water could enable farmers to cultivate more than once a year. Since pumping has an effect on the ground water resources availability, effective management of water resources using reliable calculation of historical groundwater balances at local and sub- watershed scales is required (Kendy et al 2004). We used CropWat 4 Window to determine PET of the area and the Crop Water Requirement (CWR) of onion, tomato and pepper, which are cultivated using irrigation during dry months; T-M and simple water balance equations were used to quantify annual recharge to the water table and water table status under different irrigation scenarios. Although irrigation from the groundwater could ensure the food security of the area, different water management scenarios showed that the ground water table will be declining as a result. Recharge and water table calculations show that irrigation increases the recharge to the water table but at the same time reduces the overall water table depth due to pumping. Water table depth will not be depleted if irrigation follows the CWR of vegetables. Calculations for future water table levels indicate that, if the current irrigation rate is extended across all of the irrigable land in the area, the water table level will fall by 2 m per year. To protect against further water table decline, flashfloods should be captured and used to recharge to the ground water.

KEY Words: Recharge, water table, ground water balance, irrigation, crop water requirement, Kobo Girana Valley Development Project, Kobo, Ethiopia BIOGRAPHICAL SKETCH

The author was born at Woldia town, North Wollo Zone of the Amhara Regional State on February 23, 1983. He attended his elementary and junior secondary education at Sanka elementary and junior secondary school. After completion of elementary and junior secondary education, he attended high school at Woldia Senior Secondary.

The after a successful completion his high school study, he joined Arba Minch Water Technology Institute, currently named as Arba Minch University, in 2000/2001. He joined the department of Meteorology Science and graduated with a B.Sc degree in Meteorology science in 2005.

Right after graduation in 2005, he began working at Arba Minch University as a Graduate Assistant from 2005 to 2007 and as an Assistant Lecturer from 2007 to the start of this study. The author was working in different management positions in the department of Meteorology in addition to teaching.

He has research experience in the fields of meteorology, hydrology and agriculture in his future career. The impact of climate change on water resource and agricultural production is of the main interest of the author. He is interested to continue his PhD study as fast as possible in water resource topics.

iii

“This work is dedicated to my family, friends and who loved me. Special dedication goes to my mother Ertibam Alemu”

iv ACKNOWLEDGEMENTS

First I would like to thank Cornell University, Bahir Dar University and IWMI’s C19 for the financial support during this work.

I also thank Professor Tammo S. Steenhuis who provided me with invaluable ideas and advice over the course of this research.

I thank Dr. Amy S. Collick, who was the one that made this work successful by providing all she had to share with me.

I would also like to thank Ato Adinew Abate, Manager of KGVDP, who arranged for my access to facilities and written documents in the KGVDP office, in addition to his advice. Special thanks is also due to Girma Takele, Abera Getinet, Midgam Adinew, Esmael Sied, Yeshi, Menbere Belay, Merso, Hussien, Nejib, Desalegn, Wondewosen and all the other workers in the project office for their assistance providing information and helping me during my field visits.

Great appreciation and special thanks is given to Ato Biota Derebe, one of the farmers in the study area, who helped me during my field interviews. He worked with me constantly in the field without any payment.

v I also thank Ato Daniel G/Hiwot, Tadesse Alemayehu, Wondifraw Getnet, Mengistu Abate, Anteneh Zewde and others, who are my friends and staff members of the university. They provided moral support and helped edit the whole script of this work.

At last I thank Jesus, Lord of Kings, who protected me from danger from the beginning to the end of this work, and who is always ready to help me whenever I face difficulties.

Many thanks to my father Melesse Endalamaw, my mother Ertiban Alemu, my sisters Alemash Melesse and Destamariam Melesse, and my other family members who gave me moral support, and were dedicated to this work from the beginning to its end.

vi TABLE OF CONTENT

BIOGRAPHICAL SKETCH ...... iii ACKNOWLEDGEMENTS ...... v TABLE OF CONTENT ...... vii LIST OF FIGURES ...... x LIST OF TABLES ...... xiii LIST OF ABBREVIATIONS ...... xv CHAPTER ONE ...... 1 1. Introduction ...... 1 CHAPTER TWO ...... 4 2. Literature review ...... 4 Evapotranspiration ...... 4 Effect of irrigation on crop production ...... 6 Ground water recharge and discharge ...... 6 Crop water use and growth stage ...... 8 Crop water requirement ...... 8 Irrigation requirement of the crop ...... 9 Crop growing period ...... 9 Crop coefficient (Kc) ...... 11 Available water capacity ...... 11 Effective rainfall ...... 12 Methods of water distribution ...... 13 Irrigation scheduling ...... 13

vii Effect of irrigation on ground water table ...... 14 Plant water stress ...... 16 CHAPTER THREE ...... 18 3. The Study Area ...... 18 CHAPTER FOUR ...... 20 4. Data and methods ...... 20 Data ...... 20 Methods ...... 21 Assumptions ...... 27 CHAPTER FIVE ...... 28 5. Result and Discussion ...... 28 Potential evapotranspiration ...... 28 Growing pattern of the area ...... 29 Irrigation and Field water balance under different management scenarios ...... 30 Ground water recharge from rainfall and irrigation ...... 37 Effect of Irrigation with CWR of different crop water requirements on ground water recharge ...... 40 Future Irrigation scenario’s and ground water recharge ...... 43 Ground water table depth ...... 45 Effect of irrigation area on the ground water depth ...... 48 Ground water depth in the future ...... 51 Water table status under single and double cropping irrigation ...... 52 Water table status under single and double cropping irrigation for different area of irrigated field ...... 54

viii Water table status under single and double cropping irrigation for different CWR pumping ...... 57 CHAPTER SIX ...... 61 6. Conclusions and Recommendations ...... 61 Conclusions ...... 61 Recommendations ...... 61 REFERENCES ...... 63 APPENDICES ...... 68 8.1 Crop water requirements of different vegetables during one day interval irrigation scheduling as recommended by the CropWat soft ware...... 68 8.2 Irrigation scheduling of different vegetables during one day interval irrigation scheduling as recommended by the CropWat soft ware...... 80 8.3 Irrigation scheduling of different vegetables during rain-fed schedule ...... 92 8.4 Potential evapotranspiration of the Kobo area as computed by the CropWat software ...... 104 8.5 Mean annual, annual, mean monthly and monthly rainfall of Kobo from the NMA of Ethiopia for the Kobo Meteorological station ...... 105 8.6 Crop Coefficients (Kc), stages of development and growing periods of the vegetables in the Kobo valley ...... 106 8.7 Graphs showing the mean monthly values of different meteorological parameters used in the research ...... 107

ix LIST OF FIGURES

Figure 1: Mean monthly precipitation and potential evapo-transpiration of Kobo, where PET is computed by the Penmann-Montheth equation ...... 29 Figure 2: Crop growing Pattern of Kobo estimated from the ratio of the areal rainfall to PET...... 30 Figure 3: Mean annual recharge to the ground water when there is irrigation and if there is no irrigation at all. Irrigation is scheduled from March to mid July at the

rate of the current pumping. Red line (R pumping) is recharge from irrigation from

ground water pumping plus rainfall, and blue line (R RF) is recharge from areal rainfall alone or if there is no irrigation...... 38 Figure 4: Mean annual recharge to the ground water if irrigation was started in 1997, and recharge to the ground water when it is irrigated with the current pumping

rate (5mm/day for one cropping season) R pumping, and according to CropWat

software calculated onion crop water requirement R Onion CWR, tomato crop water

requirement, R Tomato CWR and pepper water requirement R Pepper CWR. the amount shown is the total recharge as a result of both rainfall and irrigation...... 41

Figure 5: Mean annual recharge to the ground water when irrigation has been stared in 2005 to 2007 as the actual condition in the area and recharge to the ground water

when it is irrigated with the current pumping amount R pumping, and according to

CropWat software calculated onion crop water requirement R Onion CWR, tomato

crop water requirement, R Tomato CWR and pepper water requirement R Pepper CWR. 42 Figure 6: Average monthly recharge to the ground water for the two scenarios; if there was irrigation since 1997 and if there was no irrigation to the present i.e. 2008.

x Irrigation refers to the amount of water pumped out at the rate of what farmers are using for single growing season (5mm/day for the whole growing season) .. 43 Figure 7: Mean annual recharge to the ground water when irrigation has been stared in 2005 and continue to 2018 as the current pumping rate for one cropping season and (Blue line) and irrigation duration increased for two cropping season from 2008 to 2018 at the rate of current pumping rate (Red line)...... 44 Figure 8: Ground water table elevation from the well surface if irrigation was started

in 1997, GWTE Pumping, GWTE onion CWR, GWTE Tomato CWR, and GWTE pepper CWR indicating water table elevation during pumping with actual condition, onion crop water requirement, tomato crop water requirement and pepper crop water requirement respectively. Negative sign indicates depth from the surface ...... 45 Figure 9: Ground water table elevation from the well surface if irrigation was started

in 2005. GWTE Pumping, GWTE onion CWR, GWTE Tomato CWR, and GWTE pepper CWR indicating water table elevation during pumping with actual condition, onion crop water requirement, tomato crop water requirement and pepper crop water requirement respectively...... 48 Figure 10: Ground water table elevation from the well surface if irrigation was started

in 1997 for different irrigated to irrigable land area ratios. A irr and A total denotes irrigated and total irrigable land ...... 49 Figure 11 : Ground water table elevation from the well surface if irrigation was started

in 2005 for different irrigated to irrigable land area ratios. A irr and A total denotes irrigated and total irrigable land ...... 51

Figure 12: Ground water table elevation from the well surface. GWTE Twice Pumping, is water table elevation if irrigate for two cropping seasons in a year from 2008 to

xi 2018 and GWTE single Pumping is water table elevation if irrigate for one cropping season in a year from 2008 to 2018 ...... 53 Figure 13: Ground water table depth from the well surface for one irrigation period in a year under different irrigated to irrigable land area ratios...... 55 Figure 14: Ground water table depth from the well surface for two irrigation period in a year from 2008 to 2018 under different irrigated to irrigable land area ratios .. 56 Figure 15: Ground water table depth from 1997 to 2018 if irrigation started in 2005 to 2007 single and continue similarly up to 2018 ...... 57 Figure 16: GWTE from 1997 to 2018 if irrigation started in 2005 to 2007 single and twice a year from 2008 to 2018 ...... 59

xii LIST OF TABLES

Table 1 : Daily and mean monthly PET of Kobo computed by CROPWAT 4 Window ...... 28 Table 2: Ratio of mean monthly Rain Fall and Potential Evapo-Transpiration ...... 30 Table 3 : Field water balance under different water management during irrigation for the three vegetables grown in the area. All values are indicted in mm/stage days. See Appendix 8.6. Opti. indicates values when irrigated by the recommended irrigation amounts by the soft ware, Actual indicates values when irrigated by the current pumping rates...... 33 Table 4: Effect of irrigation on crop evapotranspiration and crop yield potential. All values are indicted in mm/stage days. See appendix 8.6 ...... 35 Table 5: Recharge and ground water table (GWTE) during different irrigation (pumping) amount. Actual pumping implies the amount of irrigation water pumped at rate of what farmers are pumping (5mm/day for all vegetables; onion CWR, tomato CWR and Pepper CWR are crop water requirements recommended by the CropWat software for onion, tomato and pepper respectively for one cropping season ...... 39 Table 6: Mean annual recharge to the ground water recharge during single and double cropping season irrigation, the amount of irrigation as the current pumping rate in the area (5 mm/day for the growth period) ...... 40 Table 7: Average annual change in storage from different irrigation area if irrigation has been started in 1997 ...... 48

xiii Table 8: Average annual change in storage from different irrigation area if irrigation were started in 2005 ...... 50 Table 9: Ground water recharge, change in storage and water table height for single and double irrigation scenarios. Single denote for irrigation period from March to mid July and for double irrigation duration the first irrigation is from mid November to mid February and the second irrigation is from mid March to end of June...... 54 Table 10: Average annual change in storage and water table depth after 11 years in the future (2018) for different irrigation area under single and double cropping season irrigation. Double irrigation starts in 2008 to 2018 ...... 55 Table 11: Average annual change in storage and water table depth after 11 years in the future (2018) if the area is irrigated by the current pumping rate, onion crop water requirement, tomato crop water requirement and pepper crop water requirement under single and double cropping season irrigation. Double irrigation starts in 2008 to 2018...... 58

xiv LIST OF ABBREVIATIONS

CWR Crop Water Requirement PET/Eto Potential Evapo-transpiration AET Actual Evapo-transpiration RF Rain fall/Precipitation ET Evapotranspiration

ET crop Crop evapotranspiration Kc crop coefficient SMD Soil moisture deficit TAW Total available water RAW Readily available water AWC Available water capacity KGVDP Kobo-Girana Valley Development project

xv CHAPTER ONE 1. Introduction

In many areas of the world where extensive irrigation is not possible or practical, the lack of sufficient water in the root zone of the soil can cause great societal disruption, especially to agricultural concerns. Even in areas like the northeastern United States, where mean monthly precipitation is relatively large and consistent throughout the annual cycle, precipitation variability on diverse time-scales characterizes the climate system (Leathers et al, 2000).

Parallel to population growth, food demand of people and consequently the water demand of all sectors are also increasing. Agricultural yield and productivity should be increased to provide a sustainable development and food security of the increasing population. That brings the need for effective and sustainable water resources utilization and enforces the 21st century countries to implement water saving technologies in irrigation practices (Cakmak et at, 2006).

Ground water is the principal source of fresh water for domestic, industrial, and agricultural use in many parts of the world. In addition, ground water supports freshwater ponds, wetlands, streams, and estuary environments, all of which represent specific and important habitats for native flora and fauna. Significant growth in the number of summer and permanent residents over the last 30 years has increased ground water use and placed stresses on ground water resources. In particular, there is concern over the extent of long-term declines in ground water and pond levels and in the quantity of stream flow, as well as about the possibility of saltwater intrusion from the surrounding ocean. The effects of increasing ground water withdrawals depend on

1 the location of wells, local hydro-geologic conditions, the amount and rate of withdrawals and whether or not the water is returned to the aquifer after use In view of increasing demand of water for various purposes like agricultural, domestic, industrial etc., a greater emphasis is being laid for a planned and optimal utilization of water resources (Kumar, 1993). Due to uneven distribution of rainfall both in time and space, the surface water resources are unevenly distributed. Also, increasing intensities of irrigation from surface water alone may result in alarming rise of water table creating problems of water logging and salinization, affecting crop growth adversely and rendering large areas unproductive. This has resulted in increased emphasis on development of ground water resources. The simultaneous development of ground water especially through dug wells and shallow tube wells will lower water table, provide vertical drainage and thus can prevent water logging and salinization. Areas which are already waterlogged can also be reclaimed. On the other hand continuous increased withdrawals from a ground water reservoir in excess of replenishable recharge may result in regular lowering of water table. In such a situation, a serious problem is created resulting in drying of shallow wells and increase in pumping head for deeper wells and tube wells. This has led to emphasis on planned and optimal development of water resources. An appropriate strategy will be to develop water resources with planning based on conjunctive use of surface water and ground water. For this the first task would be to make a realistic assessment of the surface water and ground water resources and then plan their use in such a way that full crop water requirements are met and there is neither water logging nor excessive lowering of ground water table. It is necessary to maintain the ground water reservoir in a state of dynamic equilibrium over a period of time and the water level fluctuations have to be kept within a particular range over the monsoon and non-monsoon seasons. Water balance techniques have been extensively used to make quantitative estimates

2 of water resources and the impact of man's activities on the hydrologic cycle. The study of water balance is defined as the systematic presentation of data on the supply and use of water within a geographic region for a specified period. With water balance approach, it is possible to evaluate quantitatively individual contribution of sources of water in the system, over different time periods, and to establish the degree of variation in water regime due to changes in components of the system.

3 CHAPTER TWO 2. Literature review Evapotranspiration The hydrologic cycle is a constant movement of water above, on, and below the earth's surface. It is a cycle that replenishes ground water supplies. It begins as water vaporizes into the atmosphere from vegetation, soil, lakes, rivers, snowfields and oceans-a process called evapotranspiration.

Evaporation and transpiration occur simultaneously and there is no easy way of distinguishing between the two processes. Apart from the water availability in the topsoil, the evaporation from a cropped soil is mainly determined by the fraction of the solar radiation reaching the soil surface. This fraction decreases over the growing period as the crop develops and the crop canopy shades more and more of the ground area. When the crop is small, water is predominately lost by soil evaporation, but once the crop is well developed and completely covers the soil transpiration becomes the main process. At sowing nearly 100% of ET comes from evaporation, while at full crop cover more than 90% of ET comes from transpiration (Natural Resources

Management and Environment Department, FAO, 2000).

Evapotranspiration is important in soil water and ground water balances, which require estimating evapotranspiration to determine water storage, which, in turn, can lead to technical measures for the improvement of irrigation drainage and ultimately can be used to increase crop yield (Verstraeten et al 2008).

Potential transpiration is defined as the maximum amount of water lost through transpiration by short green vegetables actively growing and fully covering the ground

4 surface with unlimited water supply. The Potential Evapo-Transpiration (PET) at a given place is the total amount of moisture that could be lost at a given place by evaporation and transpiration.

Next to rainfall, potential evapotranspiration (PET) is of special importance in a tropical environment. Both rainfall and PET are needed for the computation of the climate water balance in order to have a broad idea regarding the length of the growing season and the characteristics of the crops and their productivity. They also play a significant role in estimating water balance requirements for crop under irrigation. PET is an agro-climatic index and not an evaluation of the evapotranspiration actually taking place in a given area at a given time (FDRP, KGVDP Annex I, 1999)

The amount of evaporation actually occurring is largely regulated by the amount of energy supplied. Air temperature provides an indication of the solar energy received and so the potential evapo-transpiration at a given place can be determined from the weather variables which include minimum temperature, maximum temperature, wind speed, relative humidity, and the amount of net radiation (hours of sunshine). The actual evapo-transpiration (AET) at a given place is the total amount of moisture that is actually lost through evaporation and transpiration. It is the quantity of water evaporated by the soil and transpired by plants under existing meteorological and soil moisture conditions (Ziemer 1979).

5 Effect of irrigation on crop production The effects of irrigation on crop production are usually quantified using crop water production functions which relate crop yield to amounts of water applied (Sun et al, 2006 after Yaron and Bresler, 1983; English, 1990; English and Raja, 1996). The rational irrigation can significantly increase the grain yield (Hagan et al., 1967; Gajri et al., 1997; Huang et al., 2004). Hagan et al. (1967) also asserted that excessive irrigation delays the maturity of the plant and the harvesting season and decreases grain yield. Jin et al. (1999) reported that excessive irrigation led to a decrease of crop water use efficiency and that the effective deficit irrigation may result in higher production and crop water use efficiency. Kang et al. (2002) indicated that the responses of grain yield and water use efficiency to irrigation varied considerably due to differences in soil water content and irrigation schedules. Singh et al. (1991) concluded that the impact of limited irrigation and soil water deficit on crop yield or water use efficiency depends on the particular growth stage of the crop. The relationship between irrigation and ET is linear such that an increase in irrigation increases the ET. ET is driven by meteorological factors, crop factors and soil factors and is not only water consuming process but also an energy consuming process (Sun et al, 2006).

Ground water recharge and discharge Groundwater recharge is the replenishment of an aquifer with water from the land surface. It is usually expressed as an average rate of inches of water per year, similar to precipitation. Thus, the volume of recharge is the rate times the land area under consideration times the time period. In addition to precipitation, other sources of recharge to an aquifer are stream, lake or pond seepage, irrigation return flow (both from canals and fields), inter-aquifer flows, and urban recharge (from water mains,

6 septic tanks, sewers, drainage ditches). When the sole source of such potential recharge is precipitation, it is usually called potential natural recharge. Potential natural recharge does not consider the other sources of recharge mentioned previously. In contrast to natural recharge (which results from natural causes), artificial recharge is the use of water to artificially replenish the water supply in an aquifer will be done. In many arid and semi-arid regions where surface water resources are limited and ground water is the major source for agricultural, industrial and domestic water supplies, quantitative evaluation of spatial and temporal distribution of ground water recharge is a pre-requisite for operating ground water resources system in an optimal manner. The amount of water that may be extracted from an aquifer without causing depletion is primarily dependent upon the ground water recharge (Kumar, 1993). Effective management of limited water resources requires reliable calculation of historical groundwater balances at local, sub-watershed scales (Kendy et al 2004). The optimal exploitation of the groundwater requires a previous knowledge on the aquifers potentialities (Benjamin et al 2007).

The withdrawals associated with irrigation from ground water are a negative recharge and will be calculated according to the equation:

Net Recharge (ground water) = Precipitation - (ET x Adjustment Factor).

The ET adjustment factor will be applied according to the geographic location of the irrigated land being calculated and the application method used to apply water (Contor, 2002).

7 Crop water use and growth stage Crop water use, also known as evapo-transpiration (ET), is the water used by a crop for growth and cooling purposes. This water is extracted from the soil root zone by the root system, which represents transpiration and is no longer available as stored water in the soil. Consequently, the term "ET" is used interchangeably with crop water use. Crop water use (ET) at critical growth stages can be used in irrigation scheduling to avoid stressing crops. Water stress during critical growth periods reduces yield and the quality of the crops. Crop water use (ET) is weather dependent as well as soil, water and plant dependent. Periodically check soil water at different depths within the root zone and at different growth stages helps to avoid stressing the crop during critical growth stages (Al-Kaisi et al, 1991). The availability of water to crops depends on both soil properties and root distribution (Meyer et al 1990).

Crop water requirement Crop water requirement is defined as the depth of water needed to meet the water loss through evapo-transpiration (ETcrop) of a disease free crop growing in a large field under non-restricting soil conditions, including soil water and fertility, and achieving full production in a given growing environment.

Water is essential for plant growth. Without enough water, normal plant functions are disturbed, and the plant gradually wilts, stops growing, and dies. Plants are most susceptible to damage from water deficiency during the vegetative and reproductive stages of growth. Also, many plants are most sensitive to salinity during the germination and seedling growth stages.

8 The investigation of water requirements is the main step in the design and planning of an irrigation system. The irrigation requirement is, in general, the water required to meet the water loss through evaporation, unavoidable application losses and the other water needs of land preparation. The water requirement of crops may be contributed from different sources such as irrigation, effective rainfall, soil moisture storage and ground water contribution (FDRP, KGVDP Annex II, 1999).

Irrigation requirement of the crop A favorable method for raising the yield per unit area in arid and semi-arid areas is through irrigation (Toda 2005). For effectively and efficiently using the available water sources to meet the possibly variation of cropping pattern, irrigation management plays an important role. To facilitate the management practice, experimental data based the irrigation management model can be applied to estimate the crop water demand and upgrading the capability of irrigation management (Kuo et al 2001). In the case of irrigated agriculture, the irrigation requirement of a crop is defined as the part of the crop water requirement that should be fulfilled by irrigation. In other words, it is the water requirement of the crop that exceeds the sum of effective rainfall carry over soil moisture storage and ground water contribution.

Crop growing period The growing period is the part of the year during which the moisture supply from precipitation and soil water storage and the temperature are adequate for crop growth. A normal growing period comprises one or more humid periods besides moist periods. Intermediate growing periods consist of a transitional moist period only. During an

9 intermediate growing period, it is unlikely that the crop water requirement will be fully met. Yield expectations are therefore smaller than for normal growing period. Growing periods are composed of the different climatic types ; humid (H), moist humid or intermediate (I), moderately dry (D) and very dry periods (VD) which define more accurately the availability of water for plant growth rather than the rainfall alone

(FDRP, KGVDP, Annex I, 1999).

The rate at which vegetation cover develops and the time at which it attains effective full cover are affected by weather conditions in general and by mean daily air temperature in particular. Therefore, the length of time between planting and effective full cover will vary with climate, latitude, elevation and planting date. It will also vary with cultivar (crop variety). Generally, once the effective full cover for a plant canopy has been reached, the rate of further phenological development (flowering, seed development, ripening, and senescence) is more dependent on plant genotype and less dependent on weather.

The end of the mid-season and beginning of the late season is usually marked by senescence of leaves, often beginning with the lower leaves of plants. The length of the late season period may be relatively short (less than 10 days) for vegetation killed by frost (for example, maize at high elevations in latitudes > 40°N) or for agricultural crops that are harvested fresh (for example, table beets and small vegetables). High temperatures may accelerate the ripening and senescence of crops. Long duration of high air temperature (> 35°C) can cause some crops such as turf grass to go into dormancy. If severely high air temperatures are coupled with moisture stress, the dormancy of grass can be permanent for the remainder of the growing season.

10 Moisture stress or other environmental stresses will usually accelerate the rate of crop maturation and can shorten the mid and late season growing periods periods. (Natural Resources Management and Environment Department, FAO, 1975).

Crop coefficient (Kc) The effect of the crop characteristics on crop water requirements is accounted by the crop coefficient (Kc). The Kc value relates to the evapotranspiration of a disease free crop grown in a large field under optimum soil water and fertility conditions, achieving full production potential under a give growing environment. ET crop can be found by

ET crop =Kc*ETo,

Where Kc is experimentally derived crop coefficient. Kc values with growing stages for each crop and the distribution of crop coefficient during the growing cycle of the crop is called crop curve (Natural Resources Management and Environment

Department, FAO, 2000).

Available water capacity The dynamics of soil moisture represent a component of the overall water balance, and may be regarded as the single most important variable defining the fresh water availability (Krysanova et al., 2000). Soil moisture plays a critical role in crop growth and vegetation restoration in semi arid environment, and is also an important factor in hydrological modeling (Fu et. al., 2003).

11 Available water capacity (AWC) is the amount of water that the soil can store. It is the amount of water that is available for use by plants and is normally expressed as volume fractions or percentage. The soil moisture available to vegetation is the portion of soil moisture that is held between filed capacity and wilting point and hence soils with large differences between field capacity and wilting point generally favor plant growth.

Effective rainfall Scheduling irrigation based on crop demand requires an estimate of effective precipitation or rainfall. Effective rainfall estimates are also important for planning cropping sequences in both dry-land and irrigation crop production. Effective rainfall is the amount of rainfall stored in the crop root zone. Rainfall that runs off the soil surface or passes through the root zone does not contribute to crop growth and yield. Factors that influence effective rainfall are soil slope, soil texture and structure, plant cover or crop residue, and storm intensity and duration (Tsai et al, 2005)

Effective rainfall is portion of the rainfall that can enter in the soil and support crop evapotranspiration. Effective rainfall can be computed by different methods. Of these, the project (Kobo-Girana valley development project) has adapted the Method developed by USDA Soil Conservation Service. It estimates using the formula:

Effective Rainfall = Total Rainfall / 125 * (125 - 0.2 * Total Rainfall) ... (Total Rainfall < 250 mm) Effective Rainfall = 125 + 0.1 * Total Rainfall ………….... (Total Rainfall > 250 mm) (Feasibility study report for Kobo-Girana Valley Development Program. Volume II: water resource, Annex F: Irrigation)

12 Methods of water distribution There are varieties of methods by which water can be distributed in an irrigation system. In practice three different methods of water delivery are recognized: ¾ Continuous flow ¾ Rotational flow ¾ On demand flow Continuous flow: in this method, water is d distributed to the delivery point continuously in accordance with established proportion to the service area. This method allows/considers the minimum capacity of the system. The delivery point may be the field or the tertiary unit intake.

Rotational flow: in this method, irrigation supplies are rotated between delivery point (farm, block, field etc) according to pre-arranged schedule. The capacity of water distribution network in this method is much greater than the required for continuous flow.

On demand flow: in this method, irrigation supplies can be continuous or intermittent, it is entirely up to the demand made at the point of delivery. This is a method which gives users freedom to decide when to irrigate and how much to apply (FDRP, KGVDP, Annex F, 1999).

Irrigation scheduling Irrigation scheduling is the decision of when and how much water to apply to an irrigated crop to maximize net returns. The maximization of net returns requires a high

13 level of irrigation efficiency. This requires the accurate measurement of the volume of water applied or the depth of application.

It is also important to achieve a uniform water distribution across the paddock to maximize the benefits of irrigation scheduling. Accurate water application prevents over- or under-irrigation. Over-irrigation wastes water, energy and labor, leaches nutrients below the root zone and leads to water logging which reduces crop yields. Under-irrigation stresses the plant, resulting in yield reductions and decreased returns. To benefit from irrigation scheduling you must have an efficient irrigation system

(FDRP, KGVDP, Annex F, 1999). Irrigation scheduling has tremendous advantages when environmental, crop production and water use issues are considered. The advantages of irrigation scheduling include:

• The rotation of water amongst paddocks to minimize crop water stress and maximize yields.

• A reduction in energy, water and labor costs through less irrigation.

• A lowering of fertilizer costs through reduced surface runoff and deep drainage.

• Increased net returns through increased yields and improved crop quality.

• A minimization of water-logging problems.

• Assisting control of root zone salinity problems through controlled leaching.

• Additional crops through savings in irrigation water.

Effect of irrigation on ground water table Water is the most important limiting factor for agricultural production. To achieve higher grain yields (GY), farmers use water from rivers or pump groundwater to

14 irrigate winter wheat to offset the ET deficit. The excessive exploitation of groundwater resources from shallow and deep aquifers will cause the water table to fall and create many other environmental problems (E. Kendy et al, 2003 and Sun et al 2006). On the other hand indiscriminate use of irrigation water, particularly in existing areas of shallow water table, can result in further water table rise leading to water logging and secondary salinity problems (Schofield et al., 1989; Anderson et al., 1993).

Excess irrigation water builds up on impermeable soil layers forming a water table. If the water table rises into the root zone, plant growth will suffer as a portion of the roots are waterlogged. This is the case when farmers irrigate their field from surface water. If the water table is saline, which is often the case, capillary rise will lift salt into the root zone. This salt accumulates as the water is drawn off, and trees will soon show the symptoms of salt toxicity. Therefore, the water table does not have to reach the root zone to cause a loss in production (Bowman et al 1987).

Even though water tables may not presently be causing a problem, it is good practice to monitor their level. If there is a problem, monitoring can help to identify it. Test wells are an inexpensive method of checking the depth to the water table. A test well is a length of slotted PVC pipe installed vertically in the ground to about 2.7 meters. As the water table rises and falls, the level of water in the test well also rises and falls. This level can be easily read with a tape measure, float or measuring stick. At the beginning of an irrigation season, the water table is usually well below the surface and does not influence tree performance. The test well will show if a water table exists and if so at what depth.

15 Where water tables are present, test wells should be read before irrigation and one to two days after irrigation. This will assess the effect of irrigation on the table and can help to plan to maintain the depth of the water table below the root zone.

Plant water stress In many areas of the world where extensive irrigation is not possible or practical, the lack of sufficient water in the root zone of the soil can cause great societal disruption, especially to agricultural concerns (Leathers et al 2000). Plant water stress can be defined in a manner similar to the way stress is defined in the physical sciences. Therefore biological stress is “any change in environmental conditions that might reduce or adversely change a plant’s growth or development (its normal functions)” and biological strain is the reduced or changed function.

As water becomes limiting, crop temperatures rise because they cannot transpire enough water to keep themselves cool. Plant leaves open their stomata to admit carbon dioxide for photosynthesis and at the same time water vapor flows out of the leaf, which cools the leaf surface. When soil water becomes limiting, transpiration decreases, thus reducing the leaf cooling effect and causing the crop temperature to rise. This is why when you touch the leaves of a well-watered crop in sunlight on a hot sunny day they are cool, whereas a piece of green cardboard would feel hot.

The effect of soil drying on the transpiration rate requires consideration of the simultaneous interaction of the atmospheric demand, the water potential of the leaf, the resistance to water movement in the plant, and the soil water potential. For years there have been conflicting views about the manner in which transpiration rate responds to the drying of soil. There is increasing, evidence that the form of this

16 relationship can be explained in terms of varying climate, plant, and soil factors. Root density functions are often taken as a function of root biomass, and such data are often difficult to obtain. The development of root systems can be quite dynamic and vary with species, season, and depth (Khan et al 2004).

Plant stress is related to soil water content in two ways. 1. Soil water tension. The drier the soil the harder the plant has to work to extract water from the soil. 2. Void content for gas exchange. Roots need air for respiration. The wetter the soil, the less air is available.

The principles of economics should be used to determine the allowable level of stress that results in the best returns on capital and labor. Stress level is monitored by monitoring soil water content in the root zone. Although irrigation is an efficient measure, capable of decreasing water stress, Water use efficiency decreases with increasing in irrigation (Sun et al, 2006).

17 CHAPTER THREE 3. The Study Area The Kobo valley is part of the Kobo Girana Valley Development Project area in the North Eastern Amhara regional state, North Wollo Administrative Zone. It is located in a geographical zone of 11°56’ to 120°18’N and 39°23’ to 39°47’E. The valley is surrounded by Zoble Mountain in the east and the western escapement of the mainland in the west (FDRP, KGVDP, Annex-M, 1997). The valley and plain area are comprised of several low lying depositional areas distributed in the middle of the area extended from north to south. The mountain rises from 1500m to more than 3000m and the plain is characterized by flat topography not greater than 1500m altitude. The plain area is formed by the accumulation of sediments from the surrounding scraps in an old lake bed. River drainage in the study area originates in from the western scraps where the youthful streams have cut deep gorges through the strata they cross and flow to the east across the plain to the Afar Depression through the narrow outlets in the eastern scraps. Due to low gradient, the streams form wide flood plain, alluvial flats and swamps as they reach the plain and deposit huge quantity of sediments. The soil type, as the geologic and hydrogeology report of the project, is dominantly alluvial sediment deposit from the escarpment of mountains. The soil is rich in organic and inorganic material for the production of crops. (KGVDP feasibility report, volume II Water Resource and Engineering, Annex-B Regional Geology, 1996)

The principal feature of rainfall in the area is seasonal, poor distribution and variability from year to year. Rainfall distribution over the area is Bimodal, characterized by a short rainy season (Belg) and the long rainy season (Meher) that occurs in February-April and July-October respectively with a short dry spell (May-

18 June) in between. The mean daily monthly percentage of maximum possible sunshine hours is 64.5% and the maximum sunshine hour in a day is 7.74.

The main crops grown in the area before the KGVDP were Teff, Sorghum, Maize, and other cereals from July through November. Due to the low rainfall amount and high rate of evaporation and transpiration during the Belg rainy, there was no crop grown during this period i.e. farmers were producing once a year. But now, with the use of ground water since 2005, farmers are producing twice a year. In addition to the above cereals, cultivation of the most commercial crops in the country such as tomato, onion and pepper is possible during the dry season i.e. from March/April to June/July. As the KGVDP propose, starting from the current year (2009) farmers are going to produce three times a year.

Ground water table is supplied by recharge from the areal rainfall and lateral recharge from the surrounding mountain. This makes the area, higher ground water potential for crop production.

In the country, this area is the only area benefitted from ground water irrigation. Considering the effectiveness of the project, farmers and regional governments are drilling more deep well to cover the whole irrigable land in the valley.

19 CHAPTER FOUR 4. Data and methods Data Mean monthly values of maximum temperature, minimum temperature, precipitation, sunshine hours, relative humidity (RH) and wind speed, as well as soil type, common crops grown in the area and infiltration capacity of the soil are used for the estimation of PET, crop evapotranspiration, CWR, irrigation scheduling, and yield reduction due to water stress by CROPWAT 4 window. Temperature, RH, wind, precipitation and hours of sunshine data were taken from the Kobo Meteorological observatory station recorded values. Soil, crop, ground water table level and infiltration capacity data were taken from the previous feasibility study report documents prepared by the KGVDP. For the validation of the model output, ground water table depth of one of the wells (HG4) was measured during the research period by the researcher and the KGVDP. Eleven years of daily precipitation data from 1997 to 2007 was used for the estimation of ground water recharge from irrigation and precipitation and the associated ground table depth in each year. Due to the inability of the General Circulation Model to predict the next 11 years precipitation value, we used the recorded 11 years data for the next 11 years, from 2008 to 2018. Precipitation data from Combolcha, Waja and Sirinka were used to fill the missing Kobo precipitation data. Differences in adoption, awareness and benefits from irrigation technology among farmers were assessed by field interviews of the beneficiaries. Thirty-five farmers from different groups were interviewed at two command areas, i.e. farmers who benefited from HG 2 and HG 4 wells.

20 Methods Calculation of missing precipitation data Data was missing for the following periods: September 1999 to January 2000, April 2001 to December 2001and August 2003 to September 2003. Since the normal precipitation of the nearby stations and Kobo meteorological station is more than 10%, normal ratio method was used to fill the missing precipitation data. The following formula was used:

------(1)

Where: Px and Nx are the values of the missing data and the normal precipitation of the station in question, respectively; P1, P2, P3 and Pn are the recorded precipitation values of the nearby stations 1, 2, 3 and nth stations, respectively, for n observation stations; and N1, N2, N3 and Nn are the normal precipitation of 1, 2, 3 and nth stations, respectively.

Potential evapotranspiration, crop water requirement and irrigation scheduling Potential evapotranspiration (PET) of the area is computed by using the CROPWAT 4 Window model developed by Food and Agriculture Organization (FAO, 1992). The model is also used for the computation of actual and reference crop evapotranspiration, crop water requirement (CWR), irrigation scheduling and total and stage yield reduction due to water stress. The model implements the modified Penman-Monteith equation. Mean monthly maximum and minimum temperature, precipitation, hours of sunshine, relative humidity and wind speed, soil type and infiltration capacity and cover crop were input data for the model. CROPWAT 4

21 window implements the following empirical formula to calculate PET and other characteristics of the area.

Δ γ ET = ()R − G + 15.36()()1+ 0.0062V e − e …….…-(2) Δ + γ n Δ + γ 2 s d

Where ET is potential evapotranspiration, cal/cm2/day (58 cal/cm2 = 1 mm), Δ is the slope of saturated vapor pressure curve at mean air temperature, γ is Psychometric constant, mb/oC, Rn is the net radiant energy at the earth's surface, cal/cm2/day, G is 2 the soil heat flux, cal/cm /day, V2 is the average wind speed at 2 m, km/day, es is the saturated vapor pressure at mean air temperature, mb, ed is the saturated vapor pressure at mean dew point temperature, mb.

Crop evapotranspiration can be calculated from the following equations:

ETc = (Kc + Ke) ETo …………………………………………………………… (3) ETa = (Ksg *Kc + Ke) ETo …………...... … (4)

Where Etc and ETa are crop evapotranspiration standard and adjusted for water stress, respectively, ETo is the reference crop evapotranspiration, Ks is the water stress coefficient, Kc is the crop coefficient, and Ke is the evaporation coefficient. Given the input of the requirement data, the CROPWAT model can be used to calculate crop-related data in every ten days period, such as: (1) crop coefficient, (2) crop leaf index, (3) crop evapotranspiration, (4) percolation, (5) effective rainfall, and (6) crop water requirements. Also, the model can be applied to estimate the irrigation schedule for each crop with 5 different options: in different irrigation management scenarios defined by irrigation manager, irrigation set at below or above critical soil

22 depletion (% RAM), irrigation set at fixed intervals per crop growing stage, irrigation set at deficit irrigation, and no irrigation. Afterwards, the CROPWAT model can simulate the on-farm crop water balance, including: irrigation times, dates and depths.

Growing period and pattern The growing period and pattern of the area is determined by using the ratio of the average monthly rainfall to the average monthly potential evapo-transpiration. For the determination of the crop growing period and growing pattern, critical ratio values were used as recommended by the FAO. It states that, for rain-fed agriculture, the area is double growing if the ratio has two peaks with a value above one in different periods in the year, single growing if the ratio has one peak with a value above one in a year or no growing period if the ratio has no peaks with a value above one in a year.

Ground water table computation The ground water recharge and ground water table level are calculated using the application of Thornthwaite Mather (T-M) procedure and a simple water balance equation that balances recharge and pumping. The equation uses monthly /daily potential evaporation and precipitation. The moisture status of the soil depends on the previous day moisture content (AW), the difference between precipitation and potential evapotranspiration and the available water capacity (AWC) of the soil. The AW is calculated by two different methods depending on whether the potential evaporation is greater than or less than the cumulative precipitation. Case 1: For the months that the potential evaporation is in excess of the precipitation (i.e., the soil is drying out) the AW at a given time t is given by the formula (Steenhuis and Van Der Molen. 1986), viz:

23 ………………………………………………… (5)

Where: AW t = the available water at time t (cm); AW t-Δt = the available water at time t-Δt (i.e., previous month; cm); PET = cumulative evaporation over time period t (cm); AWC = the available water capacity of the soil (cm) and P = precipitation over time period t (cm).

But in the case of irrigation application, the moisture status of the soil depends on the amount and the time of irrigation applied other than the PET and precipitation. Therefore equation 6 will be modified to account irrigation factor in the soil moisture, viz:

……………………….…………………… (6)

Case 2: For months when precipitation is in excess of the potential evapotranspiration, (i.e., the soil is wet) the AW at a given time t is given by the formula:

…………………………………………………… (7) And again in the case of irrigation application, the moisture status of the soil depends on the amount and the time of irrigation applied other than the PET and precipitation. Therefore equation 6 will be modified to account irrigation factor in the soil moisture, viz ……………………………………………... (8)

Hence the final soil moisture at the root zone is

24 ……………………………………………. (9)

Finally recharge to the ground water table is estimated by the equation: ………………………………. (10)

Therefore the general ground water balance equation for an unconfined aquifer is used to estimate the ground water table level when irrigation is applied. The ground water balance equation is given as:

…………………………………………………………………… (11)

Where, I = Inflow (cm) during time Δt, O = Outflow (cm) during time Δt and Δw = change in water level (cm). Considering the various inflow and outflow components, the ground water balance equation for a time period Δt is given as:

………………….………………………… (12)

Where; Ri = Recharge from Rainfall, Rr = recharge from field irrigation, Et=

Evapotranspiration, Tp = draft from ground water, Se =Influent recharge to rivers (Base flow to the river), ΔS = change in ground water storage Base flow to the river (Se) is estimated by Darcy’s law as:

……………………………………………………………………….. (13)

25 Where Q is the discharge or flow rate (cm3/month), K is hydraulic conductivity (cm/month); A is the cross sectional area (cm2); Δh is the head difference and Δ l is the distance from the well to the river. Hence, the depth of base flow per time is calculated by dividing equation 13 by the area. This gives:

………………………………………………………………. (14)

Where, Ht is the height after time t, HD is the height from the river to water table level and l is the horizontal distance from the river.

Finally, the ground water table height below the ground can be estimated elevation using simple water balance equation that balances the recharge, discharge and pumping of ground water.

………………………… (15)

Where Ht and Ht-Δt are ground water height below the ground at times t and t-Δt respectively. Ai and AT are irrigated and total irrigable areas respectively. Therefore, equating 14 and 15 gives,

……………... (16)

Equation 16 is used to estimate ground water table level under different scenarios. Hence the decline of the water table can be calculated by the formula

…………………………………………………………………… (17)

26 Where ………………………………………………………….. (18)

Assumptions It is assumed that the ground water table level before irrigation was applied was at equilibrium state, i.e. the recharge to the ground water and the base flows are equal. We also take the average ground water table as 18m below the surface of irrigated farm land.

For the development of future water table depth calculations, the daily rainfall from 1997 to 2007 is used for the period 2008 to 2018.

27 CHAPTER FIVE 5. Result and Discussion Potential evapotranspiration

The potential evapo-transpiration (ETO) of the area is computed by CropWat 4 window software, which uses the Penman-Monteith formula calculating ETO from temperature (minimum & maximum), wind speed at two meters above the surface, solar radiation and relative humidity data. As can be seen from Table 1, the highest PET occurs during May and is about 6 mm/day or 186 mm/month. The average PET of the area is 5 mm/day or 147 mm/month. The average annual PET of the area is 1799 mm. Comparison of the mean monthly rainfall and PET reveals that, for the maximum crop production in the area, irrigation is the most important parameter. As seen from Table 1 and Figure 1, except for the months from mid June to August, a substantial amount of water is needed to fill the evapo-transpiration needs of different crops.

Table 1 : Daily and mean monthly PET of Kobo computed by CROPWAT 4 Window

Month PET (mm/day) PET (mm) Jan 3.91 121 Feb 4.44 124 Mar 5.1 158 Apr 5.53 166 May 5.99 186 Jun 5.86 176 July 5.34 166 Aug 4.69 145 Sept 4.48 134 Oct 4.4 136 Nov 4.27 128 Dec 3.82 118 Avg 4.9 147 Total 1,759

28

Figure 1: Mean monthly precipitation and potential evapo-transpiration of Kobo, where PET is computed by the Penmann-Montheth equation

Growing pattern of the area The assessment of the growing pattern of the area using the ratio of rain fall to PET reveals that, unless supplementary irrigation is supplied, there is only one cropping season. As seen from Table 2 and Figure 2 there is only one area with ratio greater than 0.5 which is from mid June through August. Although there is another peak from March through June, the value is less than 0.5. This shows that unless irrigation is supplied to the area, crop production will remain limited to one season. According to the assessment of the yield reduction during these months using the CropWat soft ware, the yield would be reduced by more than 50% if irrigation was not added for the currently cultivated vegetables using ground water irrigation, Table 4. These crops include onion, tomato and pepper. Hence, if rain-fed agriculture is concerned, the area is characterized by single growing area. But, if the potential ground water resource is used, the area can produce more than two times a year. Since 2005 the area has been producing twice a year with the aid of ground water irrigation during the moisture stressed periods. Comparisons of the crop water requirement for the three commercial

29 vegetables and the actual ground water delivered to the crops show that the amount of water extracted is more than the crop water requirement.

Table 2: Ratio of mean monthly Rain Fall and Potential Evapo-Transpiration

Month RF (mm/month) PET (mm/month) RF/PET Jan 19 121 0.16 Feb 7.26 124 0.06 Mar 30 158 0.2 Apr 64 166 0.42 May 36 186 0.22 Jun 13 176 0.09 Jul 172 166 1.22 Aug 231 145 1.65 Sep 48 134 0.36 Oct 49 136 0.35 Nov 25 128 0.2 Dec 29 118 0.25

Figure 2: Crop growing Pattern of Kobo estimated from the ratio of the areal rainfall to PET.

Irrigation and Field water balance under different management scenarios Irrigation is one of the key factors affecting whether actual ET is close to the potential rate. Components of a soil water balance as influenced by different irrigation

30 schedules in the three common vegetables (onion, tomato and pepper) grown during the dry periods is shown in Table 4. Crop evapotranspiration (Etc) under different treatments (i.e. without irrigation, irrigation with the current pumping rate and irrigation recommended by CropWat 4 Window) for each vegetable varies among the stages of development. Table 3 explains the effect of irrigation management scenarios on the field water balance and the crop evapotranspiration. The results are derived from the CropWat software for each stages of development, Appendices 1 to 3. Crop evapotranspiration (Etc) for onion varies from 60 mm when there is no irrigation to 62 mm for both irrigation treatments (current pumping rate and irrigation recommended by the soft ware) in the initial stage, similarly Etc varies from 95 to 114 mm in the development stage, 70 to 232 mm in the mid development stage, 29 to 129 mm in the late stage and 254 to 537 mm for the whole stage of development. Crop evapotranspiration (Etc) for tomato varies from 60 mm when there is no irrigation to 62 mm for both irrigation treatments (current pumping rate and irrigation recommended by the soft ware) in the initial stage, similarly Etc varies from 98 to 123 mm in the development stage, 73 to 270 mm in the mid development stage, 32 to 141 mm in the late stage and 263 to 595 mm for the whole stage of development. Crop evapotranspiration (Etc) for pepper varies from 60 when there is no irrigation to 61 mm for both irrigation treatments (current pumping rate and irrigation recommended by the soft ware) in the initial stage, and similarly Etc varies from 127 to 151 mm in the development stage, 74 to 216 mm in the mid development stage, 16 to 122 mm in the late stage and 274 to 550 mm for the whole stage of development. Net irrigation that is the amount of water supplied to the field varies among different irrigation managements and vegetable types. As can be seen from Tables 3 and 4 the net irrigation amount for the three vegetable during the current pumping rate and recommended by the soft ware irrigation scenarios are different. The net irrigation for

31 onion during current pumping rate is 645 mm and when it is irrigated by the amount recommended by the soft ware is 536 mm. The net irrigation for tomato during current pumping rate is 670 mm and when it is irrigated by the amount recommended by the soft ware is 594 mm. The net irrigation for pepper during current pumping rate is 670 mm and when it is irrigated by the amount recommended by the soft ware is 550 mm. irrigation amount recommended by the soft ware is equal to the crop water requirements of the vegetables, Tables 3 and 4. This shows that the Etc of the crop has attained its maximum with the recommended irrigation amount. Any further irrigation could not increase crop evapotranspiration rather it could be lost during irrigation. The most irrigated treatment gave the maximum ET, and rain-fed had the lowest ET. The results indicated that the ET of the vegetables was greatly affected by irrigation application (Sun et al 2006).

The rate of pumping from the ground water in the current condition is 5mm per day from the start of irrigation to its end. But irrigation amount recommended by the soft ware varies from stage to stage as the crop water requirements of the crop varies from stage to stage, Appendices 1 and 2. Irrigation starts on 5 th of March and ends on 12 th of July for onion, for tomato it starts on 5 th of March and ends on 17 th of July, and for pepper it starts on 1st of March and ends on 13 th of July.

32

Table 3 : Field water balance under different water management during irrigation for the three vegetables grown in the area. All values are indicted in mm/stage days. See Appendix 8.6. Opti. indicates values when irrigated by the recommended irrigation amounts by the soft ware, Actual indicates values when irrigated by the current pumping rates.

Crop Type Planting date Stage of Development PET CWR Irr. Req. Etc (mm) (mm) (mm) (mm) W/o Irrigation Opti Actual Initial stage 155 62 28 60 62 62 Development stage 166 114 58 95 114 114 Onion 5-Mar 33 Mid Season Stage 245 233 203 70 232 232 Late season stage 151 129 84 29 129 129 Total 716 537 374 254 537 537 Initial stage 155 62 28 60 62 62 Development stage 166 122 67 98 123 123 Tomato 5-Mar Mid Season Stage 256 269 240 73 270 270 Late season stage 167 141 78 32 141 141 Total 743 594 413 263 595 595 Initial stage 153 61 33 57 61 61 Development stage 221 151 81 127 151 151 Pepper 1-Mar Mid Season Stage 228 217 196 74 216 216 Late season stage 139 122 72 16 122 122 Total 741 551 382 274 550 550

Crop Planting Stage of Development SMD(mm) Net Irri. (mm) Loss(mm) Type date W/o W/o W/o Opti Actual Opti Actual Opti Actual Irrigation Irrigation Irrigation Initial stage 506 63 63 0 61 145 0 0 84 Onion 5-Mar Development stage 1152 114 114 0 114 150 0 0 37 Mid Season Stage 3532 232 256 0 232 215 0 0 0 Late season stage 2410 129 200 0 129 135 0 0 8 Total 7600 538 632 0 536 645 0 0 128 34 Initial stage 506 63 63 0 61 145 0 0 84 Development stage 1202 123 123 0 123 150 0 0 31 Tomato 5-Mar Mid Season Stage 3785 270 494 0 270 225 0 0 0 Late season stage 695 141 461 0 141 150 0 0 13 Total 6188 596 1141 0 594 670 0 0 128 Initial stage 543 63 63 0 61 145 0 0 84 Development stage 1802 151 151 0 151 200 0 0 50 Pepper 1-Mar Mid Season Stage 4225 216 254 0 216 200 0 0 0 Late season stage 581 122 183 0 122 125 0 0 5 Total 7150 552 651 0 550 670 0 0 139

Table 4: Effect of irrigation on crop evapotranspiration and crop yield potential. All values are indicted in mm/stage days. See appendix 8.6

Crop Type Planting date Kc RF PET CWR Irr. Req. Stage of Development (mm) (mm) (mm) (mm) Initial stage 0.4 36 155 62 28 Development stage 0.95 61 166 114 58 Onion 5-Mar Mid Season Stage 0.95 31 245 233 203 Late season stage 0.75 62 151 129 84 35 Total 191 716 537 374 Initial stage 0.4 36 155 62 28 Development stage 1.05 61 166 122 67 Tomato 5-Mar Mid Season Stage 31 256 269 240 Late season stage 0.65 94 167 141 78 Total 222 743 594 413 Initial stage 0.4 30 153 61 33 Development stage 0.95 78 221 151 81 Pepper 1-Mar Mid Season Stage 21 228 217 196 Late season stage 0.8 68 139 122 72 Total 198 741 551 382

Crop Planting Etc (mm) Etc/Etm (%) Yield Reduction (%) Type date Stage of Development W/o W/o W/o Opti Actual Opti Actual Opti Actual Irrigation Irrigation Irrigation Initial stage 60 62 62 97 100 100 1 0 0 Onion 5-Mar Development stage 95 114 114 83 100 100 14 0 0 Mid Season Stage 70 232 232 30 100 100 57 0 0 Late season stage 29 129 129 23 100 100 23 0 0 Total 254 537 537 58 100 100 58 0 0 36 Initial stage 60 62 62 97 100 100 1 0 0 Development stage 98 123 123 80 100 100 16 0 0 Tomato 5-Mar Mid Season Stage 73 270 270 27 100 100 60 0 0 Late season stage 32 141 141 23 100 100 21 0 0 Total 263 595 595 57 100 100 60 0 0 Initial stage 57 61 61 93 100 100 10 0 0 Development stage 127 151 151 84 100 100 10 0 0 Pepper 1-Mar Mid Season Stage 74 216 216 34 100 100 80 0 0 Late season stage 16 122 122 13 100 100 44 0 0 Total 274 550 550 56 100 100 53 0 0

Ground water recharge from rainfall and irrigation In Kobo valley, supplementary irrigation from ground water is supplied from March to mid July (KGVDP 2006). For the rest of the year, the farm land either produces cereal in the rainy season or is not cultivated. Comparison of ground water recharge for periods with irrigation and periods with no irrigation during the year reveal that recharge will increase from irrigation. Ground water recharge was calculated using the water balance model (Equation 10). The water balance model was used for two scenarios to calculate recharge: first, recharge from areal rainfall only (i.e. represent the situation some 10 years ago when there was no irrigation) and second, recharge from irrigation and rainfall. Recharge from irrigation indicates recharge to the water table if the farmlands are irrigated from the ground water at the rate of current pumping (i.e. 5 mm per day) for all vegetables for about four months from March to mid July. In the period before irrigation was used, crops were rain-fed and all fields were fallowed at least every Kiremit; the annual recharge to the aquifer was only from the areal rainfall. Hence, groundwater recharge was small and steady, pulsing only in response to intense rainfall during the Kiremit season. Annual and monthly ground water recharge amounts follow the amount and intensity of annual and monthly rainfall. Recharge to the ground water is always associated with the condition that, when the available water over a period is higher than the PET there is recharge. There is recharge to the water table from rainfall if the amount of rainfall is greater than the PET over a given period. For Kobo area, there is recharge from the rainfall during Kiremit season when rainfall is greater than the PET. The annual recharge to the water table from rainfall is contributed from the recharge during Kiremit season. From Figure 3, it is clear to see the trend of recharge follows exactly the available water either from irrigation or precipitation. Except for the year 2001 and 2002, ground water recharge is directly related to the available water. The recorded annual rainfall

37 in Kobo was 74 cm in 2001 and 61 cm in 2002. The computed annual recharge, by the T-M model in 2001, is 35 cm during the application of irrigation and 29 cm when there was no irrigation, and for 2002 the recharge is 13 cm during the application of irrigation and 26 cm when there is no irrigation. When rainfall decreases from 74cm in 2001 to 61cm in 2002 the recharge increases from 13 cm in 2001 to 26 cm in 2002 for the scenario where no irrigation water is applied.. The reason is that during 2001 most of the rainfall events were in the dry months while for the other years the rainfall was during the wet months. Details are given in Appendix 5.

Figure 3: Mean annual recharge to the ground water when there is irrigation and if there is no irrigation at all. Irrigation is scheduled from March to mid July at the rate of the current pumping. Red line (R pumping) is recharge from irrigation from ground water pumping plus rainfall, and blue line (R RF) is recharge from areal rainfall alone or if there is no irrigation.

Hence, most of the rainfall evaporates during the dry months rather than percolating, as the PET during the dry months is high. From the results obtained by T-M model, recharge increases if irrigation is added for crop production, Table 5 and Figure 3. In the previous section the start and end of irrigation for the three vegetables are

38 indicated. The total amount of rainfall during the growing period of the crops is 19 cm for onion, 22 cm for tomato and 20 cm for pepper, Table 4 and Appendices 1, 2, 3 and 6.

As Tables 3 and 5 show, under the “actual” pumping (i.e., what is currently used by farmers and consist of a daily application of 5mm/day), which is about 645 mm per cropping season for single cropping season, the actual evaporation by the crop (called crop water requirement in the tables) of the vegetables remain below the net irrigation applied to the field. Thus more water is added than evaporates and water will percolate downward. The greater the irrigation rate the more water percolates. This is shown in Table 5 and Figure 3 where the results obtained by T-M model, recharge increases if crops are irrigated. As we will see later that does not mean that the groundwater table increases as well because water is being pumped from the aquifer.

Table 5: Recharge and ground water table (GWTE) during different irrigation (pumping) amount. Actual pumping implies the amount of irrigation water pumped at rate of what farmers are pumping (5mm/day for all vegetables; onion CWR, tomato CWR and Pepper CWR are crop water requirements recommended by the CropWat software for onion, tomato and pepper respectively for one cropping season

Change in Change in water Amount Recharge Pumping storage table height (cm/year) (cm/year) (m/year) (m/year) Actual Pumping 65 39 0.16 0.53 Onion CWR 54 35 0.08 0.28 Tomato CWR 59 40 0.08 0.31 Pepper CWR 55 36 0.09 0.31

Kobo, especially in the research sub-watershed, has a recent history of irrigation. Irrigation using ground water was started during 2005 in a small part of the study area. Currently, more bore holes are being drilled to irrigate the whole plain area.

39 Effect of Irrigation with CWR of different crop water requirements on ground water recharge With the encouragement of regional and federal government financial and technical assistance, the quantity of groundwater extracted each year for irrigation has increased steadily. After irrigation, most crop requirements were met, as indicated by the leveling off of annual evapotranspiration rates (Tables 3, 5 and 6). Here it is interesting to see that changing cropping patterns can reverse recharge from the irrigated field (Table 6). Typical planting and harvesting dates for these vegetables is assumed as it indicated in the previous section. Ground water recharge is higher if we plant and irrigate tomato crops according to the crop water requirement (CWR, as calculated with the CropWat software) than if the same is done for onion and pepper crops, as the CWR of tomatoes is higher and length of growing season is higher. The results from Table 6 and Figure 4 indicate that recharge from irrigation to the aquifer can be minimized if we irrigate crops by their respective crop water requirements. Different crops have different water requirements so as to get maximum production. The difference in crop water requirements for different crops results in the difference in recharge response from different crops, although we can save more water if we irrigate crops by their crop water requirements (Kendy et al 2004). Figure 4 shows cumulative model calculated ground water recharge for the three crops.

Table 6: Mean annual recharge to the ground water recharge during single and double cropping season irrigation, the amount of irrigation as the current pumping rate in the area (5 mm/day for the growth period)

Irrigation amount Recharge Irrigation Rotation (cm/year) (cm/year) One cropping period 65 39 Two cropping period 114 46

40 The annual changes in groundwater storage were calculated by subtracting inflow (model-calculated Recharge) from outflow (pumping for irrigation plus base flow to the nearby river.

Figures 4 and 5 and Tables 3, 4 and 6 show that recharge is not directly related to the total amount of irrigation applied. Rather, it is a complex relationship of daily rainfall and irrigation. For the years from 1998 to 2004, recharge was greater under irrigation with tomato CWR (i.e., irrigation amounts calculated with the CropWat software) although the total irrigation was less than the actual pumping rate. This may be because the CWR of tomato during the mid development stage of the crop is higher than the actual pumping rate.

Figure 4: Mean annual recharge to the ground water if irrigation was started in 1997, and recharge to the ground water when it is irrigated with the current pumping rate (5mm/day for one cropping season) R pumping, and according to CropWat software calculated onion crop water requirement R Onion CWR, tomato crop water requirement, R Tomato CWR and pepper water requirement R Pepper CWR. the amount shown is the total recharge as a result of both rainfall and irrigation.

41

Figure 5: Mean annual recharge to the ground water when irrigation has been stared in 2005 to 2007 as the actual condition in the area and recharge to the ground water when it is irrigated with the current pumping amount R pumping, and according to CropWat software calculated onion crop water requirement R Onion CWR, tomato crop water requirement, R Tomato CWR and pepper water requirement R Pepper CWR.

Comparison of ground water recharge during irrigation period and periods without irrigation in a year reveal that recharge will increase from irrigation. Figure 6 shows that irrigation will increase recharge to 6 cm, while it was less than 2cm if irrigation were not applied from March to May. It is also possible to see the lag effect of irrigation to the ground water recharge. Although irrigation was ceased at the beginning of July, the recharge of July and the first week of August was shifted upwards from the base case, i.e. if irrigation were not supplied.

42

Figure 6: Average monthly recharge to the ground water for the two scenarios; if there was irrigation since 1997 and if there was no irrigation to the present i.e. 2008. Irrigation refers to the amount of water pumped out at the rate of what farmers are using for single growing season (5mm/day for the whole growing season)

Future Irrigation scenario’s and ground water recharge Water requirements of crops are met, in part, by rainfall, contribution of moisture from the soil profile and applied irrigation water. A part of the water applied to irrigated fields for growing crops is lost in consumptive use and the balance infiltrates as recharge to the ground water. The amount, period, and time of irrigation application to the agricultural field could be used to estimate the annual recharge to the ground water. In this study, irrigation is applied from March to mid July during one irrigation season for the three vegetables from 2005 to 2007. Moreover, these vegetables can be cultivated two times a year in addition to cereal production during the main rainy period (August to October).

Therefore, another irrigation period is proposed to be from mid November to mid March. This will not affect the cultivation of cereals in the main rainy season. As irrigation time increases, the amount of water delivered also increases. In this case, analysis is done in such a way that irrigation is applied from March to Mid July for the

43 single irrigation season and from November to mid March and from April to mid July for the double irrigation season. Table 6 shows when the irrigation depth, associated with increase of irrigation period, increases from 65 to 114 cm and the annual recharge to the ground water increases from 39 to 46 cm. This implies that, if we irrigate for longer time during a year, the recharge will be increased. This shows that indiscriminate use of irrigation water, has led to problems of rising water tables causing widespread land degradation (Schofield et al., 1989; Anderson et al., 1993).

The irrigation pattern of this area was single up to 2007. But starting from 2008, the government gave more emphasis to produce vegetables two times during the moisture deficit periods of the year. Hence, ground water recharge estimation for the coming 10 years was calculated. Figure 7 shows the annual recharge if irrigation is practiced once a year or twice a year. The T-M water balance model indicates that if irrigation duration increases recharge will also increase.

Figure 7: Mean annual recharge to the ground water when irrigation has been stared in 2005 and continue to 2018 as the current pumping rate for one cropping season and (Blue line) and irrigation duration increased for two cropping season from 2008 to 2018 at the rate of current pumping rate (Red line).

44 Ground water table depth Ground water table depth with time was estimated using the T-M equation, a simple water balance formula that balances inflow and outflow of the water in an area (Equation 15-18). Darcy’s law (Equation 14) was also used to estimate base flow to the river from the agricultural fields, since ground water table depth was higher than the river bed. Figure 8 and Table 5 show the ground water table depth in different irrigation management scenarios. Recharge and change in storage are related linearly for areas irrigated from river water, but for ground water irrigation the relationship among recharge, irrigation, change in storage and ground water depth is complex. It is a complex relationship of irrigation, rainfall and evapotranspiration (Kendy et al., 2002).

Figure 8: Ground water table elevation from the well surface if irrigation was started in 1997, GWTE Pumping, GWTE onion CWR, GWTE Tomato CWR, and GWTE pepper CWR indicating water table elevation during pumping with actual condition, onion crop water requirement, tomato crop water requirement and pepper crop water requirement respectively. Negative sign indicates depth from the surface

45 The difference in crop water requirements for different crops results in the difference of recharge response from different crops (Kendy et al 2004) and hence, the rate of ground water decline too. Figure 8 shows the estimated water table depth change due to different agricultural water use in Kobo. Ground water table will decline more for the current pumping practices than pumping the three crop water requirements recommended by the software is small. This is because, fields are irrigated with the crop water requirements of each vegetables and the difference in crop water requirements among these vegetables is also small. But the difference in the effect of ground water decline between the current pumping rate and pumping recommended by the software is high. This may be because of the difference in the irrigation amount and the difference between potential evapotranspiration and crop evapotranspiration of these vegetables is high. Crops transpire at their crop evapotranspiration rate if the available water is equal to the crop water requirement of the particular crop, but if there is much water above the CWR, more water will transpire and the ground water table will decline at a higher rate. On average, ground water table declines by 53 cm for current pumping rate, 0.28 cm for onion CWR, 0.31 cm for tomato CWR and 0.31 cm for pepper CWR per year (Tables 3, 4, 5 and 6). This implies that the more the ground water is pumped out, the higher the rate of decline, unlike recharge to the ground water. Although the rate of water table decline in pepper CWR should be less than that of tomato, it has higher value. The reason may be due to the longer growing period of pepper than tomato. This could affect the daily water balance and water table status of the area. The crop requirements, however, remained steady, as indicated by evapotranspiration rates, and the excess water percolated through fields and recharged aquifers at an accelerated rate. Irrigation with the CWR of each crop will decrease at about the same rate as pumping, so the net groundwater withdrawals

46 (evapotranspiration) remained relatively constant. Consequently, groundwater levels continued to decline, despite reduced pumping due to increased application efficiency.

Figure 9 shows water table depths when irrigation was started in 2005. It is assumed that the ground water table was 18m below the surface of the well during the start of operation. As from the report of well log and pumping tests done by the KGVDP, the average static water level of the wells is 18m. Measurement using GPS indicated that the bed floor of Hormat River is about 40m (vertical distance) from the surface of the well and 200 m away from the well (horizontal distance). Water flows out from the farmland to the river following the slope. This is one indication of ground water recharge to the river. Since water table depth is higher than the river bed water will flow to the river as a base flow. As it is clearly seen in the well logo report, water entering the area will either recharge the ground water table or discharge to the river as subsurface flow.

From Figure 9, water table level declined by 1.5m during the three year irrigation time of four months of irrigation per year. But if onion, tomato or pepper were cultivated and irrigated with the respective CWR, the water table level would decline by 86 cm for onion CWR, 87 cm for tomato CWR and 91 cm for pepper CWR during the three year irrigation time of four months irrigation per year. This shows onion contributes least to the decrease of water table level during pumping with its CWR.

47

Figure 9: Ground water table elevation from the well surface if irrigation was started in 2005. GWTE Pumping, GWTE onion CWR, GWTE Tomato CWR, and GWTE pepper CWR indicating water table elevation during pumping with actual condition, onion crop water requirement, tomato crop water requirement and pepper crop water requirement respectively.

Effect of irrigation area on the ground water depth Maximum crop production could be achieved if all agricultural land is used through intensive irrigation and crop management activities. Irrigation application to the total irrigable land could affect the plain ground and sub surface water balance. Figure 10 shows the effect of irrigating different proportions of agricultural land if irrigation had been started in 1997. Table 7 shows the average annual change in storage for different irrigated farm land if irrigation had been started in 1997.

Table 7: Average annual change in storage from different irrigation area if irrigation has been started in 1997

Area proportion Airr/Atotal=0.25 Airr/Atotal=0.5 Airr/Atotal=0.75 Airr/Atotal=1 Change in storage 0.00 -0.04 -0.16 -0.29 per year (m/year) Change in water table per year 0.00 0.13 0.53 0.95 (m/year) 2007 water table -18.0 -19.4 -23.8 -28.5 depth (m)

48

Figure 10: Ground water table elevation from the well surface if irrigation was started in 1997 for different irrigated to irrigable land area ratios. A irr and A total denotes irrigated and total irrigable land

As indicated by Table 7, change in ground water storage varies significantly for different irrigation areas. Ground water balances using different irrigated areas reveals that irrigating smaller areas of the total irrigable land will not have an effect on the annual ground water table. Irrigating 25% of the total irrigable land will not have an impact on the ground water table as far as ground water irrigation is concerned. But, if the area of irrigation increased to 50%, 75% and 100%, water table will be affected. The water table will be affected more (more sensitive) for irrigation areas of more than 75% of the total area. If irrigation had been started in 1997 with all irrigable field irrigated at the rate of current actual pumping, the water table would have declined to 28.5 m from the surface. This indicates that the water table would decline by 10.5 m in 11 years of irrigation. Hence, the ground water table declines by 13 cm for 50%, 53 cm for 75% and 95 cm for 100% of total irrigated area. However, the water table will not be affected if the total irrigated field is below 25% of the total irrigable area.

49 Although irrigating all areas for crop production is key factor for maximizing crop production and ensuring food security, ground water table is affected.

Table 8 and Figure 11 show the average change in ground water storage and annual water table depth for different irrigable areas if irrigation had been started in 2005 for single cropping irrigation patterns. This reflects the current scenario implemented by the project in the area. Irrigation was started in 2005 for some wells as a testing and awareness creation for the farmers. Now more bore holes are used for irrigation. There are about 39 bore hole ready for irrigation starting from 2009 (well completion report, 2008). Hence, monitoring ground water table and different components of ground water balance is important.

Table 8: Average annual change in storage from different irrigation area if irrigation were started in 2005

Area proportion Airr/Atotal=0.25 Airr/Atotal=0.5 Airr/Atotal=0.75 Airr/Atotal=1 Change in storage per year (m/year) 0.00 0.04 0.15 0.27 Change in water table per year (m/year) 0.00 0.13 0.49 0.91 2007 water table depth (m) -18.0 -18.4 -19.5 -20.7

As seen in Table 8, ground water table levels will decline by 13 cm if 50%, 49 cm if

75% and 91 cm if 100% of irrigable land is irrigated in the 3 year irrigation history of four months of irrigation in a year. Measurement of the water table depth in December 2008 on Hormat-Golina No.4 well indicated that the area irrigated is only 75% of the total area irrigable by the well. It decreased by about 50cm from the previous year. Water table depth at the well testing time was 17.5 m, and after one year it declined to 17.05 m.

50

Figure 11 : Ground water table elevation from the well surface if irrigation was started in 2005 for different irrigated to irrigable land area ratios. A irr and A total denotes irrigated and total irrigable land

Therefore, Tables 8 and 9, and Figures 10 and 11 indicate that ground water table level and change in ground water storage are sensitive to the area of farm land supplied by a ground water irrigation system. Best management practices that balance recharge, pumping and loss according to the crop water requirements of crops and crop rotation will decrease the decline of the water table level.

Ground water depth in the future Future ground water depth scenarios are developed by taking the rainfall in the previous 11 years as data to simulate the coming 11 years. This will have limitations since rainfall events change from year to year. But as annual ground water table and recharge from irrigation and rainfall will not vary significantly, rainfall data is extrapolated for this analysis. Future ground water table level predictions include the following scenarios: irrigation is used for a single cropping season at the rate of the current actual draft for different irrigated land areas, irrigation is used for two

51 cropping seasons in the moisture deficit periods for different areas of irrigated land and irrigation is used by CWR of the three vegetables.

Water table status under single and double cropping irrigation The cropping pattern of the area affects the amount of irrigation applied on the field. Long growing crops need more water than short growing crops, assuming the crop water requirements of both crops in all stages of development are similar. Irrigating an area more than once a year affects the water balance of the area as more water is used. Double cropping with irrigation needs much more water than single cropping. This scenario assesses the fate of the water table level if the current pumping rate is used for irrigating farm land. Ground water table and recharge was analysed for two cropping seasons and single cropping season scenarios. A water balance using T-M equation (Equation 12-18) gave that, if the irrigation period is increased from one cropping season to double cropping, the water table level will decline at a faster rate. For the two scenarios, irrigation will start from March to mid July for the single irrigation season and from November to mid March and from April to mid July for double irrigation season. The modelled cropping pattern is based on the assumption that short growing crop varieties could be cultivated three times a year. It is also assumed that the area could be cultivated twice a year starting from 2008 onwards during dry months of the year. Hence, the water table level after 11 years will be 31.2 m below the surface for double cropping irrigation and 25.2 m below the surface for single cropping irrigation. This implies that water table level will decline by 6 m more for two cropping season irrigation than single cropping season irrigation in 11 years of irrigation.

52 Figure 12 shows the water table depth for single and double season irrigation. The water table will decline by 52 cm per year for a single cropping season and 94 cm per year for a double cropping system if the pumping rate continues as is for the future 11 years. Here, the cropping period for a single cropping season is from March to the first week of July, and, for a double cropping system, it starts from mid November to mid February and from mid March to the end of June. For the double cropping season irrigation duration during each season, the overall time is reduced so as to have enough time for cereal cultivation in the rain period. Here, short growing varieties are recommended in order to produce three times a year.

Figure 12: Ground water table elevation from the well surface. GWTE Twice Pumping, is water table elevation if irrigate for two cropping seasons in a year from 2008 to 2018 and GWTE single Pumping is water table elevation if irrigate for one cropping season in a year from 2008 to 2018

As it can be seen from Table 9 and Figure 12, the total rainfall for single and double cropping season systems is almost equal, but the PET during the seven months irrigation period is higher than the four months irrigation period. The water table level declines more for the double cropping irrigation system because the PET during these months is higher than the PET during the months of the single cropping season,

53 although the value of rainfall is similar. This indicates that ground water table status is not only the function of available water; rather, it is a complex function of PET, rainfall and other parameters.

Table 9: Ground water recharge, change in storage and water table height for single and double irrigation scenarios. Single denote for irrigation period from March to mid July and for double irrigation duration the first irrigation is from mid November to mid February and the second irrigation is from mid March to end of June.

PET RF Pumping Recharge Change in Change 2018 water Irrigation (cm/ (cm/ (cm/ (cm/ storage in height table height duration season) season) season) season) (m/year) (m/year) (m) Single 71.6 19 65 39 0.15 0.52 -25.2 1st 37.1 6.4 45 Double 46 0.28 0.94 -31.2 2nd 54.2 12.8 62

Water table status under single and double cropping irrigation for different area of irrigated field As is seen in the previous section, water table depth for different irrigated areas affects the ground and subsurface water balance and hence, the depth and annual recharge of ground water from irrigated fields. Future scenarios for the coming 11 years have been developed for different irrigation areas and cropping patterns associated with irrigation.

Table 10 shows ground water table depth for different irrigated areas under single and double cropping season irrigation if irrigation was started in 2005 with single cropping and 2008 for double cropping season irrigation. Change in storage and water table level will not be affected in the future for irrigation areas with a ratio of irrigated to total irrigable land of up to 0.5. Analysis of the recharge and water table level using the T-M equation and ground water balance for the current and future gave that the water table level will decline at a higher rate for a double cropping season irrigation

54 system if all the available area is irrigated. As seen from Figure 13 and Table 10, the ground water table level during a single cropping season will drop to 25.2 m and 31.1 m below the surface for 75% and 100% irrigated area, respectively. This shows that the maximum ground water depth reduction for a single cropping irrigation system is 12 m in 14 years of irrigation period starting from 2005 and running to 2018.

Table 10: Average annual change in storage and water table depth after 11 years in the future (2018) for different irrigation area under single and double cropping season irrigation. Double irrigation starts in 2008 to 2018

Average annual Change in 2018 water Cropping change in storage ground water table depth type/pattern A irr/A total (m/year) table (m/year) (m) 0.25 0 0 -18.0 Single cropping 0.5 -0.03 0.1 -19.5 season irrigation 0.75 -0.16 0.5 -25.2 1 -0.29 0.9 -31.1 0.25 0.00 0.01 -18.2 Double 0.5 0.12 0.39 -23.4 cropping season irrigation 0.75 0.28 0.94 -31.2 1 0.45 1.50 -39.1

Figure 13: Ground water table depth from the well surface for one irrigation period in a year under different irrigated to irrigable land area ratios.

55 Figure 14 shows the water table depth for different irrigated area proportions for a single cropping season irrigation system from 2005 to 2007 and a double cropping season irrigation system from 2008 to 2018. Irrigation area under the double cropping season system will result in a greater reduction of the ground water table level. From Figure 14 and Table 10, it can be observed that the water table level will drop below the surface by 23.4 m for 50%, 31.2 m for 75% and 39.1 m for 100% of irrigated field usage for a double cropping season irrigation system.

Sensitivity to the ratio irrigation area is greater for the double cropping irrigation system than for the single cropping season system as seen from Table 10 and Figures 13 and 14. The water table level will decline by 6 m more if the irrigation area ratio is increased from 75% to 100% for the single cropping season irrigation system and by 8 m for the double cropping season irrigation system. If the whole plain area could be irrigated twice a year from 2008 on, the water table level at the end of 2018 will be 39.1 m below the surface of the well, i.e. the water table will drop by 21 m in11years rate of 2 m/year.

Figure 14: Ground water table depth from the well surface for two irrigation period in a year from 2008 to 2018 under different irrigated to irrigable land area ratios

56

Water table status under single and double cropping irrigation for different CWR pumping As irrigation depth and ground water pumping has an effect on ground water recharge and water table depth (Kendy et al 2004), irrigation with the crop water requirements of vegetables will have different effects on the water table depth for the future. Figure 15 shows the response of the water table depth to different depths of irrigation if irrigation had been started in 2005 for single cropping season irrigation up to 2018. As the current scenario, a single cropping irrigation system for the onion crop has less of an effect on the water table level. A one season cultivation of onion will result in a final water table depth of 21.9 m below the surface of the well where as tomato and pepper will have 22.2m and 22.3 m level, respectively. But if the current actual pumping continues, the water table level will decline to 25.2 m below the surface, as can be seen in Table 11.

Figure 15: Ground water table depth from 1997 to 2018 if irrigation started in 2005 to 2007 single and continue similarly up to 2018

57 This implies that the difference in the effect of the three vegetable crops if irrigated with their CWR is insignificant as compared with the current pumping rate. Although every pumping rate has resulted in the decline of water table level, irrigating with the crop water requirement of crops being grown will protect the water table from further reduction.

Assessment of the water table depth for the future scenario calculation if the three vegetable crops are to be cultivated two times a year from 2008 to 2018 is shown in Table 11 and Figure 16. Results of the ground water and soil-water balance using the T-M model and a simple water balance that balances inflow and outflow in the ground water system indicate that there is insignificant difference between the three vegetable crops. The changes in storage for the four irrigation scenarios are almost similar, as can be seen in Table 11.

Table 11: Average annual change in storage and water table depth after 11 years in the future (2018) if the area is irrigated by the current pumping rate, onion crop water requirement, tomato crop water requirement and pepper crop water requirement under single and double cropping season irrigation. Double irrigation starts in 2008 to 2018.

Average annual Change in 2018 water change in storage ground water table depth Cropping type/pattern Pumping (m/year) table (m/year) (m) Actual -0.16 0.52 -25.2 -21.9 Single cropping Onion CWR -0.085 0.28 season irrigation Tomato -22.2 CWR -0.090 0.3 Pepper CWR -0.093 0.3 -22.3 Actual -0.306 0.94 -31.2 -30.6 Double cropping Onion CWR -0.312 0.84 season irrigation Tomato -31.5 CWR -0.334 0.95 Pepper CWR -0.317 0.92 -30.8

58

Figure 16: GWTE from 1997 to 2018 if irrigation started in 2005 to 2007 single and twice a year from 2008 to 2018

The comparison of annual change in ground water storage between single cropping and double cropping irrigation systems show that the negative change storage will increase by almost a factor of two in the double cropping season system. If the cropping pattern of the area continues as the current practice, the maximum water table depth will be 25.2 m below the surface of the well at the end 2018. Therefore, water table depth will decrease by 7.2 m from the beginning of the irrigation period as seen from Table 11 and Figure 15. However, if the cropping pattern is changed to two irrigated cropping seasons from 2008, the water table level will decrease to 31.5 m below the surface.

As shown in Table 11 and Figure 16, the water table depth will decline by 13.5 m during a three year single irrigation cropping season system plus a 14 year double irrigation cropping seasons system scenario. This implies that rate of water table depth reduction and cropping seasons are linearly related. If irrigation duration doubles following cropping pattern, the water table level will decline by factor of two.

59 The effect of irrigation scheduling on the ground water recharge and water table decline is different for different irrigation duration than the depth of irrigation. As can be seen from Figure 15 and Table 11, water table declines at different rate following the depth of irrigation, if we irrigate the area for fewer months in a year. But Figure 16 and Table 11 shows that the rate of water table decline does not vary significantly if we irrigate for more months in a year.

60 CHAPTER SIX 6. Conclusions and Recommendations Conclusions In areas where ground water is used for irrigation, as the Kobo valley, groundwater modeling is an important tool for quantifying the groundwater balance which is an essential prerequisite for sound, scientific groundwater management. The Thornthwaite Mather equation and a simple soil water balance formula could be used to quantify the areal recharge due to irrigation and rainfall. By generating an independent estimate of areal recharge, the soil-water balance model presented in this paper also provides an important constraint on estimates of lateral recharge needed for groundwater modeling.

Sustainable use of ground water in arid and semi arid areas could be achieved if farmers are irrigating their farm lands with the CWR of the crops to be grown. Ground water table levels will continue to decline if pumping continues; however, the rate of decline could be decreased to the allowable level by following different agronomic practices, which could increase recharge to the water table and decrease the rate of evaporation. As the livelihood of the farmers in the area is in the worst condition, pumping, regardless of recharge and water table depth is allowable for the coming two decades. The maximum water table reduction rate is about 2 m per year for the coming 10 years.

Recommendations

The results obtained from in this are similar to the study by Kendy et al. (2004) for the North China Plain. Increased acreage of irrigation decreased the ground water table. This resulted in increased pumping costs over time and at the same time a decrease in

61 base flow. If the entire Kobo Valley was irrigated, the ground water could decrease by as much as 2 m per year. Estimates of ground water decline should be refined by by a more realistic simulation of the water recharged from the river into aquifers once the ground water has declined below the river channel.

In order to assess the decline of ground water, monitoring wells should be installed and ground water table monitored monthly. Stream gauging stations should be established as well. This will allow validation of the simulation model and the assessment of the interaction of the surface ground water system.

62 REFERENCES

Al-Kaisi M.M. and I. Broner I. 1991. Scheduling Irrigations: A Guide for Improved Irrigation Water Management Through Proper Timing and Amount of Water Application, USDA, Natural Resources Conservation Service, Agricultural Research Service and Colorado State University Extension, 1991, page 32. Anderson, J., Britten R., and Francis J (1993), Dry land Salinity. 1: The Causes, Dept. Conservation and Land Management, NSW, and Dept. of Water Resour., NSW. Benjamin N.N, Jacques M. and Jean S.R. 2007 Groundwater Recharge from Rainfall in the Southern Border of Lake Chad in Cameroon. World Applied Sciences Journal 2 (2): 125-131. Bowman J. A. and Collins M .A, 1987 Impacts of Irrigation and Drought on Illinois Ground-Water Resources. Report of Investigation 109, State Of Illinois, Department Of Energy and Natural Resources. Cakmak B., Yusuf Ucar Y., Akuzum T. 2006. Water Resource Management, Problems and Solutions for Turkey, International Congress on River Basin Management, 2006. Contor B. A, 2002. Ground Water Irrigation Polygons for Recharge Calculation, Idaho Water Resources Research Institute University of Idaho. Eastern Snake Plain Aquifer Model Enhancement Project Water Budget Design Document Number DDW-009 99–412. English, M., 1990. Deficit irrigation. I. Analytical framework. J. Irrig. Drainage ASCE 116. English, M., Raja, S.N., 1996. Perspectives on deficit irrigation. Agric. Water Manage. 32, 1–14.

63 Fu, B. J., Wang, J., Chen, L., Qiu, Y., 2003. The effect of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China. Catena in press. Gajri, P.R., Gill, K.S., Chaudhary, M.R., 1997. Irrigation of sunflower (Helianthus annuus) in relation to tillage and mulching. Agric. Water Manage. 34, 149– 160. Hagan, R.M., Howard, R.H., Talcoh, W.E., 1967. Irrigation of agricultural lands. Am. Soc. Agron. U.S.A. 680–681. Huang, Y., Chen, L., Fu, B., Huang, Z., Gong, J., 2004. The wheat yields and water- use efficiency in the Loess Plateau: straw mulch and irrigation effects. Agric. Water Manage. Jin, M.G., Zhang, R.Q., Gao, Y.F., 1999. Temporal and spatial soil water management: a case study in the Heiloonggang region, PR China. Agric. Water Manage. 42, 173–187. Kang, S.Z., Zhang, L., Liang, Y.L., Hu, X.T., Cai, H.J., Gu, B.J., 2002. Effects of limited irrigation on yield and water use efficiency of winter wheat in the Loess Plateau of China. Agric. Water Manage. 55, 203–216. Kendy E, G´erard-Marchant P, Walter M.T,1 Zhang Y, Liu C2 and Steenhuis1 T.S, 2003. A soil-water-balance approach to quantify groundwater recharge from irrigated cropland in the North China Plain, Hydrological processes 17, page 2011–2031.

Kendy E, Zhang Y., Liu C, Wang J and Tammo Steenhuis T.S, 2004. Groundwater recharge from irrigated cropland in the North China Plain: case study of Luancheng County, Hebei Province, 1949–2000 Hydrological processes 18, 2289–2302.

64 Khan S., Rana T., Carroll J., Wang B. and Best L. 2004, Managing Climate, Irrigation and Ground Water Interactions using a Numerical Model: A Case Study of the Murrumbidgee Irrigation Area. CSIRO Land and Water Technical Report No. 13/04. Krysanova, V., Müller-Wohlfeil, D., Cramer, W., Becker, A., 2000. Spatial analysis of soil moisture deficit and potential soil loss in the Elbe drainage basin: In: Wilson, J. P. and Galant, J. C. (Eds), Terrain Analysis, Principles and applications. Wiley & Sons, New York. Pp 163-181. Kumar, C. P. 1993, Estimation of Ground Water Recharge due to Rainfall by Modeling of Soil Moisture Movement, National Institute of Hydrology, Technical Report No. TR-142, 1992- 93, 66 pp. Kuo S.F, Lin B.J and Shieh H.J. 2001. CROPWAT model to evaluate crop water requirements in Taiwan, International Commission on A25 Irrigation and Drainage 1st Asian Regional Conference Seoul, 2001. Leathers D.J, Grundstein A.D., and Ellis A. W. 2000. Growing season moisture

deficits across the Nnortheastern United States. Climate Research 14: 43–55

Meyer W.S., Tan C. S., Burrs H. D. and Smith R. C. G. 1990. Root Growth and Water Uptake by Wheat during Drying of Undisturbed and Repacked Soil in Drainage Lysimeters, Aust. J. Agric. Res., 1990, 41, 253-65.

Natural Resources Management and Environment Department. 2000. Crop evapotranspiration - Guidelines for computing crop water requirements, Food and Agriculture Organization (FAO) Corporate Document Repository.

Natural Resources Management and Environment Department. 1975. FAO Irrigation and Drainage Paper 24, Food and Agriculture Organization (FAO) Corporate Document Repository.

65 Schofield, N.J., I.C. Loh, P.R. Scott, J.R. Bartle, P. Ritson, R.W. Bell, H. Borg, B. Anson and, R. Moore, (1989), Vegetation strategies to reduce stream salinity of water resource catchments in south-west Western Australia, Water Authority of Western Australia, Report No. WS33, 81 pp.

Sheng-Feng Kuo, Bor-Jang Lin and Horng-Je Shieh,2001 Cropwat Model to Evaluate Crop Water Requirements in Taiwan. International Commission on Irrigation

and Drainage 1st Asian Regional Conference Seoul, 2001. Singh, P.K., Mishra, A.K., Imtiyaz, M., 1991. Moisture stress and the water use efficiency of mustard. Agric. Water Manage. 20, 245–253. Sun H.Y, Liu C.M, Zhang X.Y, Shen Y.J and Zhang Y.Q. 2006. Effects of irrigation on water balance, yield and WUE of winter wheat in the North China Plain. Agricultural water management 85: 211 – 218.

The Federal Democratic Republic of Ethiopia (FDRE), Amhara National Regional state, 1999. Feasibility study report for Kobo-Girana Valley Development Program. Volume III: Agriculture, Annex I: Agronomy.

The Federal Democratic Republic of Ethiopia (FDRE), Amhara National Regional state, Jan 1999. Feasibility study report for Kobo-Girana Valley Development Program. Volume II: water resource, Annex F: Irrigation.

The Federal Democratic Republic of Ethiopia (FDRE), Amhara National Regional state, commission for sustainable agricultural and environmental rehabilitation in Amhara region, Aug 1997. Feasibility study report for Kobo-Girana Valley Development Program. IV Agriculture, Annex-M soil and water conservation.

The Federal Democratic Republic of Ethiopia (FDRE), Amhara National Regional state, commission for sustainable agricultural and environmental rehabilitation in Amhara region, March 1996. Feasibility study report for Kobo-Girana Valley

66 Development Program. Volume III water resource, Annex A: Hydrology Annex B: Regional geology Annex C: Hydrogeology. Toda O, Yoshida K , Hiroaki S, Katsuhiro H and Tanji H, 2005. Estimation of irrigation water using CROPWAT model at KM35 project site in Savannakhet, Lao PDR, Role of Water Sciences in Transboundary River Basin Management, Thailand, 2005. Toda O., Yoshida K , Hiroaki S. , Katsuhiro H and Tanji H, 2005. Estimation of irrigation water using CROPWAT model at KM35 project site in Transboundary LAO PDR, Role of Water Sciences in Transboundary River Basin Management, Thailand, 2005. Tsai S.M., Chen S., and Wang H.Y. 2005. A Study on the Practical Model of Planned Effective Rainfall for Paddy Fields in Taiwan. Journal of Marine Science and Technology, Vol. 13, No. 2, pp. 73-82. Verstraeten W. W., Veroustraete F. and Feyen J., 2008, Review on Assessment of Evapo-transpiration and Soil Moisture Content Across Different Scales of Observation, Sensors 2008, 8, 70-117. Yaron, D., Bresler, E., 1983. Economic analysis of on-farm irrigation using response function of crops. In: Hillel, D. (Ed.), Advance in Irrigation, vol. 2. pp. 223– 255. Ziemer R. R., 1979. Evaporation and Transpiration. Reviews of Geophysics and Space Physics, Vol. 17, N0. 6.

67 APPENDICES

8.1 Crop water requirements of different vegetables during one day interval irrigation scheduling as recommended by the CropWat soft ware.

8.1.1 Onion

CropWat 4 Windows Ver 4.3 Crop Water Requirements Report - Crop # 1: Onion - Block # : [All blocks] - Planting date :5-Mar - Calculation time step =1 Day(s) - Irrigation Efficiency =90% Date ETo Planted Crop CWR Total Effect. Irr. FWS Area Kc (ETm) Rain Rain Req. (mm/period) (%) ------(mm/period) ---- (l/s/ha) 5-Mar 4.93 100 0.4 1.97 0.5 0.5 1.47 0.19 6-Mar 4.95 100 0.4 1.98 0.54 0.54 1.44 0.18 7-Mar 4.97 100 0.4 1.99 0.58 0.58 1.41 0.18 8-Mar 4.98 100 0.4 1.99 0.63 0.62 1.37 0.18 9-Mar 5 100 0.4 2 0.67 0.66 1.34 0.17 10-Mar 5.01 100 0.4 2.01 0.72 0.7 1.31 0.17 11-Mar 5.03 100 0.4 2.01 0.76 0.74 1.27 0.16 12-Mar 5.05 100 0.4 2.02 0.81 0.79 1.23 0.16 13-Mar 5.06 100 0.4 2.02 0.86 0.83 1.19 0.15 14-Mar 5.08 100 0.4 2.03 0.91 0.87 1.16 0.15 15-Mar 5.09 100 0.4 2.04 0.96 0.92 1.12 0.14 16-Mar 5.11 100 0.4 2.04 1.02 0.96 1.08 0.14 17-Mar 5.12 100 0.4 2.05 1.07 1.01 1.04 0.13 18-Mar 5.14 100 0.4 2.06 1.12 1.06 1 0.13 19-Mar 5.15 100 0.4 2.06 1.17 1.1 0.96 0.12 20-Mar 5.17 100 0.4 2.07 1.23 1.15 0.92 0.12 21-Mar 5.18 100 0.4 2.07 1.28 1.19 0.88 0.11 22-Mar 5.2 100 0.4 2.08 1.33 1.24 0.84 0.11 23-Mar 5.21 100 0.4 2.08 1.38 1.28 0.8 0.1 24-Mar 5.23 100 0.4 2.09 1.43 1.32 0.77 0.1 25-Mar 5.24 100 0.4 2.1 1.48 1.37 0.73 0.09 26-Mar 5.25 100 0.4 2.1 1.53 1.41 0.69 0.09 27-Mar 5.27 100 0.4 2.11 1.58 1.45 0.66 0.08 28-Mar 5.28 100 0.4 2.11 1.63 1.49 0.62 0.08

68 29-Mar 5.29 100 0.4 2.12 1.67 1.53 0.59 0.08 30-Mar 5.31 100 0.4 2.12 1.72 1.57 0.56 0.07 31-Mar 5.32 100 0.4 2.13 1.76 1.6 0.53 0.07 1-Apr 5.33 100 0.4 2.13 1.8 1.64 0.5 0.06 2-Apr 5.35 100 0.4 2.14 1.84 1.67 0.47 0.06 3-Apr 5.36 100 0.4 2.14 1.88 1.7 0.44 0.06 4-Apr 5.37 100 0.42 2.25 1.91 1.73 0.51 0.07 5-Apr 5.38 100 0.44 2.35 1.95 1.76 0.59 0.08 6-Apr 5.4 100 0.46 2.46 1.98 1.79 0.67 0.09 7-Apr 5.41 100 0.47 2.56 2.01 1.81 0.75 0.1 8-Apr 5.42 100 0.49 2.66 2.03 1.83 0.83 0.11 9-Apr 5.43 100 0.51 2.77 2.06 1.85 0.92 0.12 10-Apr 5.44 100 0.53 2.88 2.08 1.87 1 0.13 11-Apr 5.45 100 0.55 2.98 2.1 1.89 1.09 0.14 12-Apr 5.46 100 0.56 3.09 2.11 1.9 1.19 0.15 13-Apr 5.47 100 0.58 3.19 2.13 1.91 1.28 0.16 14-Apr 5.48 100 0.6 3.3 2.14 1.92 1.38 0.18 15-Apr 5.49 100 0.62 3.41 2.15 1.93 1.48 0.19 16-Apr 5.5 100 0.64 3.51 2.15 1.93 1.58 0.2 17-Apr 5.51 100 0.66 3.62 2.15 1.93 1.69 0.22 18-Apr 5.52 100 0.68 3.73 2.15 1.93 1.8 0.23 19-Apr 5.53 100 0.69 3.84 2.15 1.93 1.91 0.25 20-Apr 5.54 100 0.71 3.94 2.14 1.92 2.02 0.26 21-Apr 5.55 100 0.73 4.05 2.13 1.91 2.14 0.27 22-Apr 5.56 100 0.75 4.16 2.12 1.9 2.26 0.29 23-Apr 5.57 100 0.77 4.27 2.1 1.89 2.38 0.31 24-Apr 5.58 100 0.78 4.38 2.09 1.87 2.5 0.32 25-Apr 5.58 100 0.8 4.49 2.06 1.86 2.63 0.34 26-Apr 5.59 100 0.82 4.59 2.04 1.84 2.76 0.35 27-Apr 5.6 100 0.84 4.7 2.01 1.81 2.89 0.37 28-Apr 5.61 100 0.86 4.81 1.98 1.79 3.02 0.39 29-Apr 5.61 100 0.88 4.92 1.95 1.76 3.16 0.41 30-Apr 5.62 100 0.89 5.03 1.92 1.73 3.3 0.42 1-May 5.63 100 0.91 5.14 1.88 1.7 3.44 0.44 2-May 5.63 100 0.93 5.25 1.84 1.67 3.58 0.46 3-May 5.64 100 0.95 5.36 1.79 1.63 3.73 0.48 4-May 5.65 100 0.95 5.36 1.75 1.59 3.77 0.49 5-May 5.65 100 0.95 5.37 1.7 1.55 3.82 0.49 6-May 5.66 100 0.95 5.37 1.65 1.51 3.86 0.5 7-May 5.66 100 0.95 5.38 1.6 1.47 3.91 0.5

69 8-May 5.67 100 0.95 5.38 1.55 1.42 3.96 0.51 9-May 5.67 100 0.95 5.39 1.5 1.38 4.01 0.52 10-May 5.68 100 0.95 5.39 1.44 1.33 4.06 0.52 11-May 5.68 100 0.95 5.4 1.38 1.28 4.11 0.53 12-May 5.68 100 0.95 5.4 1.33 1.24 4.16 0.54 13-May 5.69 100 0.95 5.4 1.27 1.19 4.22 0.54 14-May 5.69 100 0.95 5.41 1.21 1.14 4.27 0.55 15-May 5.7 100 0.95 5.41 1.15 1.09 4.32 0.56 16-May 5.7 100 0.95 5.41 1.09 1.04 4.38 0.56 17-May 5.7 100 0.95 5.42 1.03 0.99 4.43 0.57 18-May 5.7 100 0.95 5.42 0.98 0.94 4.48 0.58 19-May 5.71 100 0.95 5.42 0.92 0.89 4.53 0.58 20-May 5.71 100 0.95 5.42 0.86 0.84 4.58 0.59 21-May 5.71 100 0.95 5.42 0.81 0.79 4.63 0.6 22-May 5.71 100 0.95 5.43 0.76 0.75 4.68 0.6 23-May 5.71 100 0.95 5.43 0.71 0.7 4.72 0.61 24-May 5.71 100 0.95 5.43 0.66 0.66 4.77 0.61 25-May 5.71 100 0.95 5.43 0.61 0.61 4.82 0.62 26-May 5.71 100 0.95 5.43 0.57 0.57 4.86 0.62 27-May 5.72 100 0.95 5.43 0.53 0.53 4.9 0.63 28-May 5.72 100 0.95 5.43 0.5 0.5 4.93 0.63 29-May 5.71 100 0.95 5.43 0.47 0.47 4.96 0.64 30-May 5.71 100 0.95 5.43 0.45 0.45 4.98 0.64 31-May 5.71 100 0.95 5.43 0.43 0.43 5 0.64 1-Jun 5.71 100 0.95 5.43 0.42 0.42 5.01 0.64 2-Jun 5.71 100 0.95 5.43 0.41 0.41 5.02 0.64 3-Jun 5.71 100 0.95 5.42 0.41 0.41 5.01 0.64 4-Jun 5.71 100 0.95 5.42 0.42 0.42 5 0.64 5-Jun 5.71 100 0.95 5.42 0.44 0.43 4.99 0.64 6-Jun 5.7 100 0.95 5.42 0 0 5.42 0.7 7-Jun 5.7 100 0.95 5.42 0 0 5.42 0.7 8-Jun 5.7 100 0.95 5.42 0 0 5.42 0.7 9-Jun 5.7 100 0.95 5.41 0 0 5.41 0.7 10-Jun 5.69 100 0.95 5.41 0 0 5.41 0.7 11-Jun 5.69 100 0.95 5.41 0 0 5.41 0.7 12-Jun 5.69 100 0.95 5.4 0 0 5.4 0.69 13-Jun 5.68 100 0.95 5.4 0 0 5.4 0.69 14-Jun 5.68 100 0.95 5.4 0 0 5.4 0.69 15-Jun 5.68 100 0.95 5.39 0 0 5.39 0.69 16-Jun 5.67 100 0.95 5.39 0 0 5.39 0.69

70 17-Jun 5.67 100 0.95 5.38 0 0 5.38 0.69 18-Jun 5.66 100 0.94 5.33 0 0 5.33 0.69 19-Jun 5.66 100 0.93 5.28 0 0 5.28 0.68 20-Jun 5.65 100 0.93 5.23 0 0 5.23 0.67 21-Jun 5.65 100 0.92 5.18 0 0 5.18 0.67 22-Jun 5.64 100 0.91 5.13 0 0 5.13 0.66 23-Jun 5.63 100 0.9 5.08 0 0 5.08 0.65 24-Jun 5.63 100 0.89 5.03 0 0 5.03 0.65 25-Jun 5.62 100 0.89 4.98 0.23 0.23 4.75 0.61 26-Jun 5.62 100 0.88 4.93 0.73 0.68 4.25 0.55 27-Jun 5.61 100 0.87 4.88 1.2 1 3.88 0.5 28-Jun 5.6 100 0.86 4.83 1.65 1.3 3.53 0.45 29-Jun 5.59 100 0.85 4.78 2.08 1.59 3.19 0.41 30-Jun 5.59 100 0.85 4.73 2.48 1.86 2.87 0.37 1-Jul 5.58 100 0.84 4.68 2.86 2.12 2.56 0.33 2-Jul 5.57 100 0.83 4.62 3.23 2.36 2.27 0.29 3-Jul 5.56 100 0.82 4.57 3.57 2.58 1.99 0.26 4-Jul 5.56 100 0.81 4.52 3.89 2.79 1.73 0.22 5-Jul 5.55 100 0.81 4.47 4.19 2.99 1.48 0.19 6-Jul 5.54 100 0.8 4.42 4.47 3.18 1.24 0.16 7-Jul 5.53 100 0.79 4.37 4.74 3.35 1.02 0.13 8-Jul 5.52 100 0.78 4.32 4.99 3.51 0.81 0.1 9-Jul 5.51 100 0.77 4.27 5.22 3.66 0.6 0.08 10-Jul 5.5 100 0.77 4.21 5.43 3.8 0.42 0.05 11-Jul 5.49 100 0.76 4.16 5.63 3.93 0.24 0.03 12-Jul 5.48 100 0.75 4.11 5.81 4.04 0.07 0.01 Total 716.06 537.12 190.6 163.1 374.02 [0.37]

* ETo data is distributed using polynomial curve fitting. * Rainfall data is distributed using polynomial curve fitting.

71 8.1.2 Tomato

Crop Water Requirements Report Crop Name #: Tomato Block #: [All blocks] Planting date :5-Mar Calculation time step =1 Day(s) Irrigation Efficiency =90%

* ETo data is distributed using polynomial curve fitting. * Rainfall data is distributed using polynomial curve fitting.

Date ETo Planted Crop CWR Total Effect. Irr. FWS Area Kc (ETm) Rain Rain Req. (mm/period) (%) ------(mm/period) ------(l/s/ha)

5-Mar 4.93 100 0.4 1.97 0.5 0.5 1.47 0.19 6-Mar 4.95 100 0.4 1.98 0.54 0.54 1.44 0.18 7-Mar 4.97 100 0.4 1.99 0.58 0.58 1.41 0.18 8-Mar 4.98 100 0.4 1.99 0.63 0.62 1.37 0.18 9-Mar 5 100 0.4 2 0.67 0.66 1.34 0.17 10-Mar 5.01 100 0.4 2.01 0.72 0.7 1.31 0.17 11-Mar 5.03 100 0.4 2.01 0.76 0.74 1.27 0.16 12-Mar 5.05 100 0.4 2.02 0.81 0.79 1.23 0.16 13-Mar 5.06 100 0.4 2.02 0.86 0.83 1.19 0.15 14-Mar 5.08 100 0.4 2.03 0.91 0.87 1.16 0.15 15-Mar 5.09 100 0.4 2.04 0.96 0.92 1.12 0.14 16-Mar 5.11 100 0.4 2.04 1.02 0.96 1.08 0.14 17-Mar 5.12 100 0.4 2.05 1.07 1.01 1.04 0.13 18-Mar 5.14 100 0.4 2.06 1.12 1.06 1 0.13 19-Mar 5.15 100 0.4 2.06 1.17 1.1 0.96 0.12 20-Mar 5.17 100 0.4 2.07 1.23 1.15 0.92 0.12 21-Mar 5.18 100 0.4 2.07 1.28 1.19 0.88 0.11 22-Mar 5.2 100 0.4 2.08 1.33 1.24 0.84 0.11 23-Mar 5.21 100 0.4 2.08 1.38 1.28 0.8 0.1 24-Mar 5.23 100 0.4 2.09 1.43 1.32 0.77 0.1 25-Mar 5.24 100 0.4 2.1 1.48 1.37 0.73 0.09 26-Mar 5.25 100 0.4 2.1 1.53 1.41 0.69 0.09 27-Mar 5.27 100 0.4 2.11 1.58 1.45 0.66 0.08 28-Mar 5.28 100 0.4 2.11 1.63 1.49 0.62 0.08 29-Mar 5.29 100 0.4 2.12 1.67 1.53 0.59 0.08 30-Mar 5.31 100 0.4 2.12 1.72 1.57 0.56 0.07

72 31-Mar 5.32 100 0.4 2.13 1.76 1.6 0.53 0.07 1-Apr 5.33 100 0.4 2.13 1.8 1.64 0.5 0.06 2-Apr 5.35 100 0.4 2.14 1.84 1.67 0.47 0.06 3-Apr 5.36 100 0.4 2.14 1.88 1.7 0.44 0.06 4-Apr 5.37 100 0.42 2.26 1.91 1.73 0.53 0.07 5-Apr 5.38 100 0.44 2.39 1.95 1.76 0.63 0.08 6-Apr 5.4 100 0.47 2.51 1.98 1.79 0.72 0.09 7-Apr 5.41 100 0.49 2.63 2.01 1.81 0.82 0.11 8-Apr 5.42 100 0.51 2.75 2.03 1.83 0.92 0.12 9-Apr 5.43 100 0.53 2.88 2.06 1.85 1.03 0.13 10-Apr 5.44 100 0.55 3 2.08 1.87 1.13 0.15 11-Apr 5.45 100 0.57 3.13 2.1 1.89 1.24 0.16 12-Apr 5.46 100 0.59 3.25 2.11 1.9 1.35 0.17 13-Apr 5.47 100 0.62 3.38 2.13 1.91 1.46 0.19 14-Apr 5.48 100 0.64 3.5 2.14 1.92 1.58 0.2 15-Apr 5.49 100 0.66 3.63 2.15 1.93 1.7 0.22 16-Apr 5.5 100 0.68 3.75 2.15 1.93 1.82 0.23 17-Apr 5.51 100 0.7 3.88 2.15 1.93 1.95 0.25 18-Apr 5.52 100 0.72 4 2.15 1.93 2.07 0.27 19-Apr 5.53 100 0.75 4.13 2.15 1.93 2.2 0.28 20-Apr 5.54 100 0.77 4.26 2.14 1.92 2.34 0.3 21-Apr 5.55 100 0.79 4.39 2.13 1.91 2.47 0.32 22-Apr 5.56 100 0.81 4.51 2.12 1.9 2.61 0.34 23-Apr 5.57 100 0.83 4.64 2.1 1.89 2.75 0.35 24-Apr 5.58 100 0.85 4.77 2.09 1.87 2.89 0.37 25-Apr 5.58 100 0.88 4.9 2.06 1.86 3.04 0.39 26-Apr 5.59 100 0.9 5.02 2.04 1.84 3.19 0.41 27-Apr 5.6 100 0.92 5.15 2.01 1.81 3.34 0.43 28-Apr 5.61 100 0.94 5.28 1.98 1.79 3.49 0.45 29-Apr 5.61 100 0.96 5.41 1.95 1.76 3.65 0.47 30-Apr 5.62 100 0.98 5.54 1.92 1.73 3.81 0.49 1-May 5.63 100 1.01 5.67 1.88 1.7 3.97 0.51 2-May 5.63 100 1.03 5.79 1.84 1.67 4.13 0.53 3-May 5.64 100 1.05 5.92 1.79 1.63 4.29 0.55 4-May 5.65 100 1.05 5.93 1.75 1.59 4.34 0.56 5-May 5.65 100 1.05 5.93 1.7 1.55 4.38 0.56 6-May 5.66 100 1.05 5.94 1.65 1.51 4.43 0.57 7-May 5.66 100 1.05 5.95 1.6 1.47 4.48 0.58 8-May 5.67 100 1.05 5.95 1.55 1.42 4.53 0.58 9-May 5.67 100 1.05 5.96 1.5 1.38 4.58 0.59

73 10-May 5.68 100 1.05 5.96 1.44 1.33 4.63 0.6 11-May 5.68 100 1.05 5.96 1.38 1.28 4.68 0.6 12-May 5.68 100 1.05 5.97 1.33 1.24 4.73 0.61 13-May 5.69 100 1.05 5.97 1.27 1.19 4.79 0.62 14-May 5.69 100 1.05 5.98 1.21 1.14 4.84 0.62 15-May 5.7 100 1.05 5.98 1.15 1.09 4.89 0.63 16-May 5.7 100 1.05 5.98 1.09 1.04 4.95 0.64 17-May 5.7 100 1.05 5.99 1.03 0.99 5 0.64 18-May 5.7 100 1.05 5.99 0.98 0.94 5.05 0.65 19-May 5.71 100 1.05 5.99 0.92 0.89 5.1 0.66 20-May 5.71 100 1.05 5.99 0.86 0.84 5.15 0.66 21-May 5.71 100 1.05 5.99 0.81 0.79 5.2 0.67 22-May 5.71 100 1.05 6 0.76 0.75 5.25 0.68 23-May 5.71 100 1.05 6 0.71 0.7 5.3 0.68 24-May 5.71 100 1.05 6 0.66 0.66 5.34 0.69 25-May 5.71 100 1.05 6 0.61 0.61 5.39 0.69 26-May 5.71 100 1.05 6 0.57 0.57 5.43 0.7 27-May 5.72 100 1.05 6 0.53 0.53 5.47 0.7 28-May 5.72 100 1.05 6 0.5 0.5 5.5 0.71 29-May 5.71 100 1.05 6 0.47 0.47 5.53 0.71 30-May 5.71 100 1.05 6 0.45 0.45 5.55 0.71 31-May 5.71 100 1.05 6 0.43 0.43 5.57 0.72 1-Jun 5.71 100 1.05 6 0.42 0.42 5.58 0.72 2-Jun 5.71 100 1.05 6 0.41 0.41 5.59 0.72 3-Jun 5.71 100 1.05 6 0.41 0.41 5.58 0.72 4-Jun 5.71 100 1.05 5.99 0.42 0.42 5.57 0.72 5-Jun 5.71 100 1.05 5.99 0.44 0.43 5.56 0.72 6-Jun 5.7 100 1.05 5.99 0 0 5.99 0.77 7-Jun 5.7 100 1.05 5.99 0 0 5.99 0.77 8-Jun 5.7 100 1.05 5.99 0 0 5.99 0.77 9-Jun 5.7 100 1.05 5.98 0 0 5.98 0.77 10-Jun 5.69 100 1.05 5.98 0 0 5.98 0.77 11-Jun 5.69 100 1.05 5.98 0 0 5.98 0.77 12-Jun 5.69 100 1.05 5.97 0 0 5.97 0.77 13-Jun 5.68 100 1.05 5.97 0 0 5.97 0.77 14-Jun 5.68 100 1.05 5.96 0 0 5.96 0.77 15-Jun 5.68 100 1.05 5.96 0 0 5.96 0.77 16-Jun 5.67 100 1.05 5.95 0 0 5.95 0.77 17-Jun 5.67 100 1.05 5.95 0 0 5.95 0.77 18-Jun 5.66 100 1.04 5.87 0 0 5.87 0.75

74 19-Jun 5.66 100 1.02 5.79 0 0 5.79 0.74 20-Jun 5.65 100 1.01 5.71 0 0 5.71 0.73 21-Jun 5.65 100 1 5.63 0 0 5.63 0.72 22-Jun 5.64 100 0.98 5.55 0 0 5.55 0.71 23-Jun 5.63 100 0.97 5.47 0 0 5.47 0.7 24-Jun 5.63 100 0.96 5.38 0 0 5.38 0.69 25-Jun 5.62 100 0.94 5.3 0.23 0.23 5.08 0.65 26-Jun 5.62 100 0.93 5.22 0.73 0.68 4.54 0.58 27-Jun 5.61 100 0.92 5.14 1.2 1 4.14 0.53 28-Jun 5.6 100 0.9 5.06 1.65 1.3 3.76 0.48 29-Jun 5.59 100 0.89 4.98 2.08 1.59 3.39 0.44 30-Jun 5.59 100 0.88 4.9 2.48 1.86 3.04 0.39 1-Jul 5.58 100 0.86 4.82 2.86 2.12 2.7 0.35 2-Jul 5.57 100 0.85 4.74 3.23 2.36 2.38 0.31 3-Jul 5.56 100 0.84 4.65 3.57 2.58 2.07 0.27 4-Jul 5.56 100 0.82 4.57 3.89 2.79 1.78 0.23 5-Jul 5.55 100 0.81 4.49 4.19 2.99 1.5 0.19 6-Jul 5.54 100 0.8 4.41 4.47 3.18 1.23 0.16 7-Jul 5.53 100 0.78 4.33 4.74 3.35 0.98 0.13 8-Jul 5.52 100 0.77 4.25 4.99 3.51 0.74 0.1 9-Jul 5.51 100 0.76 4.17 5.22 3.66 0.51 0.07 10-Jul 5.5 100 0.74 4.09 5.43 3.8 0.29 0.04 11-Jul 5.49 100 0.73 4.01 5.63 3.93 0.08 0.01 12-Jul 5.48 100 0.72 3.93 5.81 4.04 0 0 13-Jul 5.47 100 0.7 3.85 5.98 4.15 0 0 14-Jul 5.46 100 0.69 3.77 6.13 4.25 0 0 15-Jul 5.45 100 0.68 3.69 6.28 4.33 0 0 16-Jul 5.44 100 0.66 3.61 6.4 4.41 0 0 17-Jul 5.43 100 0.65 3.53 6.52 4.48 0 0 Total 743.33 594.2 221.9 184.7 412.7 [0.39]

75 8.1.3 Pepper

CropWat 4 Windows Ver 4.3 Crop Water Requirements Report -Crop #Sweet Peppers -Block#:[All blocks] -Planting date:1-Mar - Irrigation Efficiency =90% Date ETo Planted Crop CWR Total Effect Irr. FWS Area Kc (ETm) Rain Rain Req. (mm/period) (%) ------(mm/period)------(l/s/ha) 1-Mar 4.87 100 0.4 1.95 0.37 0.37 1.58 0.2 2-Mar 4.88 100 0.4 1.95 0.4 0.4 1.55 0.2 3-Mar 4.9 100 0.4 1.96 0.43 0.43 1.53 0.2 4-Mar 4.92 100 0.4 1.97 0.47 0.47 1.5 0.19 5-Mar 4.93 100 0.4 1.97 0.5 0.5 1.47 0.19 6-Mar 4.95 100 0.4 1.98 0.54 0.54 1.44 0.18 7-Mar 4.97 100 0.4 1.99 0.58 0.58 1.41 0.18 8-Mar 4.98 100 0.4 1.99 0.63 0.62 1.37 0.18 9-Mar 5 100 0.4 2 0.67 0.66 1.34 0.17 10-Mar 5.01 100 0.4 2.01 0.72 0.7 1.31 0.17 11-Mar 5.03 100 0.4 2.01 0.76 0.74 1.27 0.16 12-Mar 5.05 100 0.4 2.02 0.81 0.79 1.23 0.16 13-Mar 5.06 100 0.4 2.02 0.86 0.83 1.19 0.15 14-Mar 5.08 100 0.4 2.03 0.91 0.87 1.16 0.15 15-Mar 5.09 100 0.4 2.04 0.96 0.92 1.12 0.14 16-Mar 5.11 100 0.4 2.04 1.02 0.96 1.08 0.14 17-Mar 5.12 100 0.4 2.05 1.07 1.01 1.04 0.13 18-Mar 5.14 100 0.4 2.06 1.12 1.06 1 0.13 19-Mar 5.15 100 0.4 2.06 1.17 1.1 0.96 0.12 20-Mar 5.17 100 0.4 2.07 1.23 1.15 0.92 0.12 21-Mar 5.18 100 0.4 2.07 1.28 1.19 0.88 0.11 22-Mar 5.2 100 0.4 2.08 1.33 1.24 0.84 0.11 23-Mar 5.21 100 0.4 2.08 1.38 1.28 0.8 0.1 24-Mar 5.23 100 0.4 2.09 1.43 1.32 0.77 0.1 25-Mar 5.24 100 0.4 2.1 1.48 1.37 0.73 0.09 26-Mar 5.25 100 0.4 2.1 1.53 1.41 0.69 0.09 27-Mar 5.27 100 0.4 2.11 1.58 1.45 0.66 0.08 28-Mar 5.28 100 0.4 2.11 1.63 1.49 0.62 0.08 29-Mar 5.29 100 0.4 2.12 1.67 1.53 0.59 0.08

76 30-Mar 5.31 100 0.4 2.12 1.72 1.57 0.56 0.07 31-Mar 5.32 100 0.41 2.2 1.76 1.6 0.6 0.08 1-Apr 5.33 100 0.43 2.28 1.8 1.64 0.64 0.08 2-Apr 5.35 100 0.44 2.36 1.84 1.67 0.69 0.09 3-Apr 5.36 100 0.46 2.44 1.88 1.7 0.74 0.09 4-Apr 5.37 100 0.47 2.52 1.91 1.73 0.79 0.1 5-Apr 5.38 100 0.48 2.6 1.95 1.76 0.84 0.11 6-Apr 5.4 100 0.5 2.68 1.98 1.79 0.89 0.11 7-Apr 5.41 100 0.51 2.76 2.01 1.81 0.95 0.12 8-Apr 5.42 100 0.52 2.84 2.03 1.83 1.01 0.13 9-Apr 5.43 100 0.54 2.92 2.06 1.85 1.07 0.14 10-Apr 5.44 100 0.55 3 2.08 1.87 1.13 0.15 11-Apr 5.45 100 0.56 3.08 2.1 1.89 1.19 0.15 12-Apr 5.46 100 0.58 3.16 2.11 1.9 1.26 0.16 13-Apr 5.47 100 0.59 3.24 2.13 1.91 1.33 0.17 14-Apr 5.48 100 0.61 3.32 2.14 1.92 1.4 0.18 15-Apr 5.49 100 0.62 3.41 2.15 1.93 1.48 0.19 16-Apr 5.5 100 0.63 3.49 2.15 1.93 1.56 0.2 17-Apr 5.51 100 0.65 3.57 2.15 1.93 1.64 0.21 18-Apr 5.52 100 0.66 3.65 2.15 1.93 1.72 0.22 19-Apr 5.53 100 0.68 3.73 2.15 1.93 1.81 0.23 20-Apr 5.54 100 0.69 3.82 2.14 1.92 1.89 0.24 21-Apr 5.55 100 0.7 3.9 2.13 1.91 1.99 0.26 22-Apr 5.56 100 0.72 3.98 2.12 1.9 2.08 0.27 23-Apr 5.57 100 0.73 4.06 2.1 1.89 2.17 0.28 24-Apr 5.58 100 0.74 4.15 2.09 1.87 2.27 0.29 25-Apr 5.58 100 0.76 4.23 2.06 1.86 2.37 0.31 26-Apr 5.59 100 0.77 4.31 2.04 1.84 2.48 0.32 27-Apr 5.6 100 0.78 4.4 2.01 1.81 2.58 0.33 28-Apr 5.61 100 0.8 4.48 1.98 1.79 2.69 0.35 29-Apr 5.61 100 0.81 4.56 1.95 1.76 2.8 0.36 30-Apr 5.62 100 0.83 4.64 1.92 1.73 2.91 0.37 1-May 5.63 100 0.84 4.73 1.88 1.7 3.03 0.39 2-May 5.63 100 0.85 4.81 1.84 1.67 3.14 0.4 3-May 5.64 100 0.87 4.89 1.79 1.63 3.26 0.42 4-May 5.65 100 0.88 4.98 1.75 1.59 3.38 0.44 5-May 5.65 100 0.89 5.06 1.7 1.55 3.51 0.45 6-May 5.66 100 0.91 5.14 1.65 1.51 3.63 0.47 7-May 5.66 100 0.92 5.22 1.6 1.47 3.75 0.48 8-May 5.67 100 0.94 5.31 1.55 1.42 3.88 0.5

77 9-May 5.67 100 0.95 5.39 1.5 1.38 4.01 0.52 10-May 5.68 100 0.95 5.39 1.44 1.33 4.06 0.52 11-May 5.68 100 0.95 5.4 1.38 1.28 4.11 0.53 12-May 5.68 100 0.95 5.4 1.33 1.24 4.16 0.54 13-May 5.69 100 0.95 5.4 1.27 1.19 4.22 0.54 14-May 5.69 100 0.95 5.41 1.21 1.14 4.27 0.55 15-May 5.7 100 0.95 5.41 1.15 1.09 4.32 0.56 16-May 5.7 100 0.95 5.41 1.09 1.04 4.38 0.56 17-May 5.7 100 0.95 5.42 1.03 0.99 4.43 0.57 18-May 5.7 100 0.95 5.42 0.98 0.94 4.48 0.58 19-May 5.71 100 0.95 5.42 0.92 0.89 4.53 0.58 20-May 5.71 100 0.95 5.42 0.86 0.84 4.58 0.59 21-May 5.71 100 0.95 5.42 0.81 0.79 4.63 0.6 22-May 5.71 100 0.95 5.43 0.76 0.75 4.68 0.6 23-May 5.71 100 0.95 5.43 0.71 0.7 4.72 0.61 24-May 5.71 100 0.95 5.43 0.66 0.66 4.77 0.61 25-May 5.71 100 0.95 5.43 0.61 0.61 4.82 0.62 26-May 5.71 100 0.95 5.43 0.57 0.57 4.86 0.62 27-May 5.72 100 0.95 5.43 0.53 0.53 4.9 0.63 28-May 5.72 100 0.95 5.43 0.5 0.5 4.93 0.63 29-May 5.71 100 0.95 5.43 0.47 0.47 4.96 0.64 30-May 5.71 100 0.95 5.43 0.45 0.45 4.98 0.64 31-May 5.71 100 0.95 5.43 0.43 0.43 5 0.64 1-Jun 5.71 100 0.95 5.43 0.42 0.42 5.01 0.64 2-Jun 5.71 100 0.95 5.43 0.41 0.41 5.02 0.64 3-Jun 5.71 100 0.95 5.42 0.41 0.41 5.01 0.64 4-Jun 5.71 100 0.95 5.42 0.42 0.42 5 0.64 5-Jun 5.71 100 0.95 5.42 0.44 0.43 4.99 0.64 6-Jun 5.7 100 0.95 5.42 0 0 5.42 0.7 7-Jun 5.7 100 0.95 5.42 0 0 5.42 0.7 8-Jun 5.7 100 0.95 5.42 0 0 5.42 0.7 9-Jun 5.7 100 0.95 5.41 0 0 5.41 0.7 10-Jun 5.69 100 0.95 5.41 0 0 5.41 0.7 11-Jun 5.69 100 0.95 5.41 0 0 5.41 0.7 12-Jun 5.69 100 0.95 5.4 0 0 5.4 0.69 13-Jun 5.68 100 0.95 5.4 0 0 5.4 0.69 14-Jun 5.68 100 0.95 5.4 0 0 5.4 0.69 15-Jun 5.68 100 0.95 5.39 0 0 5.39 0.69 16-Jun 5.67 100 0.95 5.39 0 0 5.39 0.69 17-Jun 5.67 100 0.95 5.38 0 0 5.38 0.69

78 18-Jun 5.66 100 0.95 5.38 0 0 5.38 0.69 19-Jun 5.66 100 0.94 5.34 0 0 5.34 0.69 20-Jun 5.65 100 0.94 5.3 0 0 5.3 0.68 21-Jun 5.65 100 0.93 5.26 0 0 5.26 0.68 22-Jun 5.64 100 0.93 5.22 0 0 5.22 0.67 23-Jun 5.63 100 0.92 5.18 0 0 5.18 0.67 24-Jun 5.63 100 0.91 5.14 0 0 5.14 0.66 25-Jun 5.62 100 0.91 5.1 0.23 0.23 4.88 0.63 26-Jun 5.62 100 0.9 5.06 0.73 0.68 4.39 0.56 27-Jun 5.61 100 0.9 5.03 1.2 1 4.03 0.52 28-Jun 5.6 100 0.89 4.99 1.65 1.3 3.68 0.47 29-Jun 5.59 100 0.88 4.95 2.08 1.59 3.36 0.43 30-Jun 5.59 100 0.88 4.91 2.48 1.86 3.05 0.39 1-Jul 5.58 100 0.87 4.87 2.86 2.12 2.75 0.35 2-Jul 5.57 100 0.87 4.82 3.23 2.36 2.47 0.32 3-Jul 5.56 100 0.86 4.78 3.57 2.58 2.2 0.28 4-Jul 5.56 100 0.85 4.74 3.89 2.79 1.95 0.25 5-Jul 5.55 100 0.85 4.7 4.19 2.99 1.71 0.22 6-Jul 5.54 100 0.84 4.66 4.47 3.18 1.49 0.19 7-Jul 5.53 100 0.84 4.62 4.74 3.35 1.27 0.16 8-Jul 5.52 100 0.83 4.58 4.99 3.51 1.07 0.14 9-Jul 5.51 100 0.82 4.54 5.22 3.66 0.88 0.11 10-Jul 5.5 100 0.82 4.5 5.43 3.8 0.7 0.09 11-Jul 5.49 100 0.81 4.46 5.63 3.93 0.53 0.07 12-Jul 5.48 100 0.81 4.42 5.81 4.04 0.38 0.05 13-Jul 5.47 100 0.8 4.38 5.98 4.15 0.23 0.03 Total 741.1 550.58 198.25 168.9 381.6 [0.36] * ETo data is distributed using polynomial curve fitting. * Rainfall data is distributed using polynomial curve fitting.

79 8.2 Irrigation scheduling of different vegetables during one day interval irrigation scheduling as recommended by the CropWat soft ware.

8.2.1 Onion

CropWat4 Windows Ver 4.3 Irrigation Scheduling Report * Crop Data: - Crop # 1: Onion - Block # : [All blocks] - Planting date :5-Mar * Soil Data: Soil description: Sandy clay loam Initial soil moisture depletion: 0% * Irrigation Scheduling Criteria: Application Timing: Irrigate each1days. Applications Depths: Refill to 100% of readily available soil moisture. Start of Scheduling: 5/3 Date TAM RAM Total Efct. ETc ETc/ETm SMD Interv. Net Lost User Rain Rain Irr. Irr. Adj. (mm) (mm) (mm) (mm) (mm) (%) (mm) (Days) (mm) (mm) (mm) 5-Mar 51 12.8 0.5 0 2 100.00% 2 6-Mar 51.9 13 0.5 0.5 2 100.00% 3.4 1 3.4 0 7-Mar 52.7 13.3 0.6 0 2 100.00% 2 1 2 0 8-Mar 53.5 13.5 0.6 0 2 100.00% 2 1 2 0 9-Mar 54.4 13.8 0.7 0 2 100.00% 2 1 2 0 10-Mar 55.3 14 0.7 0 2 100.00% 2 1 2 0 11-Mar 56.1 14.3 0.8 0 2 100.00% 2 1 2 0 12-Mar 57 14.6 0.8 0 2 100.00% 2 1 2 0 13-Mar 57.8 14.8 0.9 0 2 100.00% 2 1 2 0 14-Mar 58.7 15.1 0.9 0 2 100.00% 2 1 2 0 15-Mar 59.5 15.4 1 0 2 100.00% 2 1 2 0 16-Mar 60.4 15.6 1 0 2 100.00% 2 1 2 0 17-Mar 61.2 15.9 1.1 0 2 100.00% 2 1 2 0 18-Mar 62.1 16.2 1.1 0 2.1 100.00% 2.1 1 2.1 0 19-Mar 62.9 16.5 1.2 0 2.1 100.00% 2.1 1 2.1 0 20-Mar 63.8 16.7 1.2 0 2.1 100.00% 2.1 1 2.1 0 21-Mar 64.6 17 1.3 0 2.1 100.00% 2.1 1 2.1 0 22-Mar 65.5 17.3 1.3 0 2.1 100.00% 2.1 1 2.1 0 23-Mar 66.3 17.6 1.4 0 2.1 100.00% 2.1 1 2.1 0 24-Mar 67.2 17.9 1.4 0 2.1 100.00% 2.1 1 2.1 0 25-Mar 68 18.1 1.5 0 2.1 100.00% 2.1 1 2.1 0 26-Mar 68.9 18.4 1.5 0 2.1 100.00% 2.1 1 2.1 0

80 27-Mar 69.7 18.7 1.6 0 2.1 100.00% 2.1 1 2.1 0 28-Mar 70.6 19 1.6 0 2.1 100.00% 2.1 1 2.1 0 29-Mar 71.4 19.3 1.7 0 2.1 100.00% 2.1 1 2.1 0 30-Mar 72.3 19.6 1.7 0 2.1 100.00% 2.1 1 2.1 0 31-Mar 73.1 19.9 1.8 0 2.1 100.00% 2.1 1 2.1 0 1-Apr 73.9 20.2 1.8 0 2.1 100.00% 2.1 1 2.1 0 2-Apr 74.8 20.4 1.8 0 2.1 100.00% 2.1 1 2.1 0 3-Apr 75.7 20.7 1.9 0 2.1 100.00% 2.1 1 2.1 0 4-Apr 76.5 21 1.9 0 2.2 100.00% 2.2 1 2.2 0 5-Apr 77.3 21.3 1.9 0 2.4 100.00% 2.4 1 2.4 0 6-Apr 78.2 21.6 2 0 2.5 100.00% 2.5 1 2.5 0 7-Apr 79.1 21.9 2 0 2.6 100.00% 2.6 1 2.6 0 8-Apr 79.9 22.2 2 0 2.7 100.00% 2.7 1 2.7 0 9-Apr 80.8 22.5 2.1 0 2.8 100.00% 2.8 1 2.8 0 10-Apr 81.6 22.8 2.1 0 2.9 100.00% 2.9 1 2.9 0 11-Apr 82.5 23.2 2.1 0 3 100.00% 3 1 3 0 12-Apr 83.3 23.5 2.1 0 3.1 100.00% 3.1 1 3.1 0 13-Apr 84.2 23.8 2.1 0 3.2 100.00% 3.2 1 3.2 0 14-Apr 85 24.1 2.1 0 3.3 100.00% 3.3 1 3.3 0 15-Apr 85.8 24.4 2.1 0 3.4 100.00% 3.4 1 3.4 0 16-Apr 86.7 24.7 2.2 0 3.5 100.00% 3.5 1 3.5 0 17-Apr 87.6 25 2.2 0 3.6 100.00% 3.6 1 3.6 0 18-Apr 88.4 25.3 2.2 0 3.7 100.00% 3.7 1 3.7 0 19-Apr 89.3 25.7 2.1 0 3.8 100.00% 3.8 1 3.8 0 20-Apr 90.1 26 2.1 0 3.9 100.00% 3.9 1 3.9 0 21-Apr 91 26.3 2.1 0 4.1 100.00% 4.1 1 4.1 0 22-Apr 91.8 26.6 2.1 0 4.2 100.00% 4.2 1 4.2 0 23-Apr 92.7 26.9 2.1 0 4.3 100.00% 4.3 1 4.3 0 24-Apr 93.5 27.3 2.1 0 4.4 100.00% 4.4 1 4.4 0 25-Apr 94.3 27.6 2.1 0 4.5 100.00% 4.5 1 4.5 0 26-Apr 95.2 27.9 2 0 4.6 100.00% 4.6 1 4.6 0 27-Apr 96.1 28.3 2 0 4.7 100.00% 4.7 1 4.7 0 28-Apr 96.9 28.6 2 0 4.8 100.00% 4.8 1 4.8 0 29-Apr 97.8 28.9 2 0 4.9 100.00% 4.9 1 4.9 0 30-Apr 98.6 29.3 1.9 0 5 100.00% 5 1 5 0 1-May 99.5 29.6 1.9 0 5.1 100.00% 5.1 1 5.1 0 2-May 100.3 29.9 1.8 0 5.2 100.00% 5.2 1 5.2 0 3-May 101.2 30.3 1.8 0 5.4 100.00% 5.4 1 5.4 0 4-May 102 30.6 1.7 0 5.4 100.00% 5.4 1 5.4 0 5-May 102 30.6 1.7 0 5.4 100.00% 5.4 1 5.4 0

81 6-May 102 30.6 1.7 0 5.4 100.00% 5.4 1 5.4 0 7-May 102 30.6 1.6 0 5.4 100.00% 5.4 1 5.4 0 8-May 102 30.6 1.6 0 5.4 100.00% 5.4 1 5.4 0 9-May 102 30.6 1.5 0 5.4 100.00% 5.4 1 5.4 0 10-May 102 30.6 1.4 0 5.4 100.00% 5.4 1 5.4 0 11-May 102 30.6 1.4 0 5.4 100.00% 5.4 1 5.4 0 12-May 102 30.6 1.3 0 5.4 100.00% 5.4 1 5.4 0 13-May 102 30.6 1.3 0 5.4 100.00% 5.4 1 5.4 0 14-May 102 30.6 1.2 0 5.4 100.00% 5.4 1 5.4 0 15-May 102 30.6 1.2 0 5.4 100.00% 5.4 1 5.4 0 16-May 102 30.6 1.1 0 5.4 100.00% 5.4 1 5.4 0 17-May 102 30.6 1 0 5.4 100.00% 5.4 1 5.4 0 18-May 102 30.6 1 0 5.4 100.00% 5.4 1 5.4 0 19-May 102 30.6 0.9 0 5.4 100.00% 5.4 1 5.4 0 20-May 102 30.6 0.9 0 5.4 100.00% 5.4 1 5.4 0 21-May 102 30.6 0.8 0 5.4 100.00% 5.4 1 5.4 0 22-May 102 30.6 0.8 0 5.4 100.00% 5.4 1 5.4 0 23-May 102 30.6 0.7 0 5.4 100.00% 5.4 1 5.4 0 24-May 102 30.6 0.7 0 5.4 100.00% 5.4 1 5.4 0 25-May 102 30.6 0.6 0 5.4 100.00% 5.4 1 5.4 0 26-May 102 30.6 0.6 0 5.4 100.00% 5.4 1 5.4 0 27-May 102 30.6 0.5 0 5.4 100.00% 5.4 1 5.4 0 28-May 102 30.6 0.5 0 5.4 100.00% 5.4 1 5.4 0 29-May 102 30.6 0.5 0 5.4 100.00% 5.4 1 5.4 0 30-May 102 30.6 0.4 0 5.4 100.00% 5.4 1 5.4 0 31-May 102 30.6 0.4 0 5.4 100.00% 5.4 1 5.4 0 1-Jun 102 30.6 0.4 0 5.4 100.00% 5.4 1 5.4 0 2-Jun 102 30.6 0.4 0 5.4 100.00% 5.4 1 5.4 0 3-Jun 102 30.6 0.4 0 5.4 100.00% 5.4 1 5.4 0 4-Jun 102 30.6 0.4 0 5.4 100.00% 5.4 1 5.4 0 5-Jun 102 30.6 0.4 0 5.4 100.00% 5.4 1 5.4 0 6-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 7-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 8-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 9-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 10-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 11-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 12-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 13-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 14-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0

82 15-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 16-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 17-Jun 102 30.6 0 0 5.4 100.00% 5.4 1 5.4 0 18-Jun 102 31.4 0 0 5.3 100.00% 5.3 1 5.3 0 19-Jun 102 32.2 0 0 5.3 100.00% 5.3 1 5.3 0 20-Jun 102 33 0 0 5.2 100.00% 5.2 1 5.2 0 21-Jun 102 33.9 0 0 5.2 100.00% 5.2 1 5.2 0 22-Jun 102 34.7 0 0 5.1 100.00% 5.1 1 5.1 0 23-Jun 102 35.5 0 0 5.1 100.00% 5.1 1 5.1 0 24-Jun 102 36.3 0 0 5 100.00% 5 1 5 0 25-Jun 102 37.1 0.2 0 5 100.00% 5 1 5 0 26-Jun 102 37.9 0.7 0 4.9 100.00% 4.9 1 4.9 0 27-Jun 102 38.8 1.2 0 4.9 100.00% 4.9 1 4.9 0 28-Jun 102 39.6 1.7 0 4.8 100.00% 4.8 1 4.8 0 29-Jun 102 40.4 2.1 0 4.8 100.00% 4.8 1 4.8 0 30-Jun 102 41.2 2.5 0 4.7 100.00% 4.7 1 4.7 0 1-Jul 102 42 2.9 0 4.7 100.00% 4.7 1 4.7 0 2-Jul 102 42.8 3.2 0 4.6 100.00% 4.6 1 4.6 0 3-Jul 102 43.7 3.6 0 4.6 100.00% 4.6 1 4.6 0 4-Jul 102 44.5 3.9 0 4.5 100.00% 4.5 1 4.5 0 5-Jul 102 45.3 4.2 0 4.5 100.00% 4.5 1 4.5 0 6-Jul 102 46.1 4.5 0 4.4 100.00% 4.4 1 4.4 0 7-Jul 102 46.9 4.7 0 4.4 100.00% 4.4 1 4.4 0 8-Jul 102 47.7 5 0 4.3 100.00% 4.3 1 4.3 0 9-Jul 102 48.6 5.2 0 4.3 100.00% 4.3 1 4.3 0 10-Jul 102 49.4 5.4 0 4.2 100.00% 4.2 1 4.2 0 11-Jul 102 50.2 5.6 0 4.2 100.00% 4.2 1 4.2 0 12-Jul 102 51 5.8 0 4.1 100.00% 4.1 1 4.1 0 Total 11705.5 3673.3 190.6 0.5 537.1 100.00% 536.6 0 0 * Yield Reduction: Estimated yield reduction in growth stage # 1 = 0 % Estimated yield reduction in growth stage # 2 = 0 % Estimated yield reduction in growth stage # 3 = 0 % Estimated yield reduction in growth stage # 14= 0 % Estimated total yield reduction =0% * These estimates may be used as guidelines and not as actual figures. * Legend: TAM = Total Available Moisture = (FC%- WP %)* Root Depth [mm]. RAM = Readily Available Moisture = TAM* P [mm]. SMD = Soil Moisture Deficit [mm].

83 8.2.2 Tomato

CropWat4 Windows Ver 4.3 Irrigation Scheduling Report Crop Data: - Crop # 1: Onion - Block # : [All blocks] - Planting date :5-Mar * Soil Data: Soil description: Sandy clay loam Initial soil moisture depletion: 0% * Irrigation Scheduling Criteria: Irrigate each1days. Applications Depths: Refill to 100% of readily available soil moisture. Start of Scheduling: 5/3 Date TAM RAM Total Efct. ETc ETc/ETm SMD Interv. Net Lost User Rain Rain Irr. Irr. Adj. (mm) (mm) (mm) (mm) (mm) (%) (mm) (Days) (mm) (mm) (mm) 5-Mar 51 12.8 0.5 0 2 100.00% 2 6-Mar 51.9 13 0.5 0.5 2 100.00% 3.4 1 3.4 0 7-Mar 52.7 13.3 0.6 0 2 100.00% 2 1 2 0 8-Mar 53.5 13.5 0.6 0 2 100.00% 2 1 2 0 9-Mar 54.4 13.8 0.7 0 2 100.00% 2 1 2 0 10-Mar 55.3 14 0.7 0 2 100.00% 2 1 2 0 11-Mar 56.1 14.3 0.8 0 2 100.00% 2 1 2 0 12-Mar 57 14.6 0.8 0 2 100.00% 2 1 2 0 13-Mar 57.8 14.8 0.9 0 2 100.00% 2 1 2 0 14-Mar 58.7 15.1 0.9 0 2 100.00% 2 1 2 0 15-Mar 59.5 15.4 1 0 2 100.00% 2 1 2 0 16-Mar 60.4 15.6 1 0 2 100.00% 2 1 2 0 17-Mar 61.2 15.9 1.1 0 2 100.00% 2 1 2 0 18-Mar 62.1 16.2 1.1 0 2.1 100.00% 2.1 1 2.1 0 19-Mar 62.9 16.5 1.2 0 2.1 100.00% 2.1 1 2.1 0 20-Mar 63.8 16.7 1.2 0 2.1 100.00% 2.1 1 2.1 0 21-Mar 64.6 17 1.3 0 2.1 100.00% 2.1 1 2.1 0 22-Mar 65.5 17.3 1.3 0 2.1 100.00% 2.1 1 2.1 0 23-Mar 66.3 17.6 1.4 0 2.1 100.00% 2.1 1 2.1 0 24-Mar 67.2 17.9 1.4 0 2.1 100.00% 2.1 1 2.1 0 25-Mar 68 18.1 1.5 0 2.1 100.00% 2.1 1 2.1 0 26-Mar 68.9 18.4 1.5 0 2.1 100.00% 2.1 1 2.1 0 27-Mar 69.7 18.7 1.6 0 2.1 100.00% 2.1 1 2.1 0 28-Mar 70.6 19 1.6 0 2.1 100.00% 2.1 1 2.1 0 29-Mar 71.4 19.3 1.7 0 2.1 100.00% 2.1 1 2.1 0 30-Mar 72.3 19.6 1.7 0 2.1 100.00% 2.1 1 2.1 0

84 31-Mar 73.1 19.9 1.8 0 2.1 100.00% 2.1 1 2.1 0 1-Apr 73.9 20.2 1.8 0 2.1 100.00% 2.1 1 2.1 0 2-Apr 74.8 20.4 1.8 0 2.1 100.00% 2.1 1 2.1 0 3-Apr 75.7 20.7 1.9 0 2.1 100.00% 2.1 1 2.1 0 4-Apr 76.5 21 1.9 0 2.3 100.00% 2.3 1 2.3 0 5-Apr 77.3 21.3 1.9 0 2.4 100.00% 2.4 1 2.4 0 6-Apr 78.2 21.6 2 0 2.5 100.00% 2.5 1 2.5 0 7-Apr 79.1 21.9 2 0 2.6 100.00% 2.6 1 2.6 0 8-Apr 79.9 22.2 2 0 2.8 100.00% 2.8 1 2.8 0 9-Apr 80.8 22.5 2.1 0 2.9 100.00% 2.9 1 2.9 0 10-Apr 81.6 22.8 2.1 0 3 100.00% 3 1 3 0 11-Apr 82.5 23.2 2.1 0 3.1 100.00% 3.1 1 3.1 0 12-Apr 83.3 23.5 2.1 0 3.3 100.00% 3.3 1 3.3 0 13-Apr 84.2 23.8 2.1 0 3.4 100.00% 3.4 1 3.4 0 14-Apr 85 24.1 2.1 0 3.5 100.00% 3.5 1 3.5 0 15-Apr 85.8 24.4 2.1 0 3.6 100.00% 3.6 1 3.6 0 16-Apr 86.7 24.7 2.2 0 3.8 100.00% 3.8 1 3.8 0 17-Apr 87.6 25 2.2 0 3.9 100.00% 3.9 1 3.9 0 18-Apr 88.4 25.3 2.2 0 4 100.00% 4 1 4 0 19-Apr 89.3 25.7 2.1 0 4.1 100.00% 4.1 1 4.1 0 20-Apr 90.1 26 2.1 0 4.3 100.00% 4.3 1 4.3 0 21-Apr 91 26.3 2.1 0 4.4 100.00% 4.4 1 4.4 0 22-Apr 91.8 26.6 2.1 0 4.5 100.00% 4.5 1 4.5 0 23-Apr 92.7 26.9 2.1 0 4.6 100.00% 4.6 1 4.6 0 24-Apr 93.5 27.3 2.1 0 4.8 100.00% 4.8 1 4.8 0 25-Apr 94.3 27.6 2.1 0 4.9 100.00% 4.9 1 4.9 0 26-Apr 95.2 27.9 2 0 5 100.00% 5 1 5 0 27-Apr 96.1 28.3 2 0 5.2 100.00% 5.2 1 5.2 0 28-Apr 96.9 28.6 2 0 5.3 100.00% 5.3 1 5.3 0 29-Apr 97.8 28.9 2 0 5.4 100.00% 5.4 1 5.4 0 30-Apr 98.6 29.3 1.9 0 5.5 100.00% 5.5 1 5.5 0 1-May 99.5 29.6 1.9 0 5.7 100.00% 5.7 1 5.7 0 2-May 100.3 29.9 1.8 0 5.8 100.00% 5.8 1 5.8 0 3-May 101.2 30.3 1.8 0 5.9 100.00% 5.9 1 5.9 0 4-May 102 30.6 1.7 0 5.9 100.00% 5.9 1 5.9 0 5-May 102 30.6 1.7 0 5.9 100.00% 5.9 1 5.9 0 6-May 102 30.6 1.7 0 5.9 100.00% 5.9 1 5.9 0 7-May 102 30.6 1.6 0 5.9 100.00% 5.9 1 5.9 0 8-May 102 30.6 1.6 0 6 100.00% 6 1 6 0 9-May 102 30.6 1.5 0 6 100.00% 6 1 6 0

85 10-May 102 30.6 1.4 0 6 100.00% 6 1 6 0 11-May 102 30.6 1.4 0 6 100.00% 6 1 6 0 12-May 102 30.6 1.3 0 6 100.00% 6 1 6 0 13-May 102 30.6 1.3 0 6 100.00% 6 1 6 0 14-May 102 30.6 1.2 0 6 100.00% 6 1 6 0 15-May 102 30.6 1.2 0 6 100.00% 6 1 6 0 16-May 102 30.6 1.1 0 6 100.00% 6 1 6 0 17-May 102 30.6 1 0 6 100.00% 6 1 6 0 18-May 102 30.6 1 0 6 100.00% 6 1 6 0 19-May 102 30.6 0.9 0 6 100.00% 6 1 6 0 20-May 102 30.6 0.9 0 6 100.00% 6 1 6 0 21-May 102 30.6 0.8 0 6 100.00% 6 1 6 0 22-May 102 30.6 0.8 0 6 100.00% 6 1 6 0 23-May 102 30.6 0.7 0 6 100.00% 6 1 6 0 24-May 102 30.6 0.7 0 6 100.00% 6 1 6 0 25-May 102 30.6 0.6 0 6 100.00% 6 1 6 0 26-May 102 30.6 0.6 0 6 100.00% 6 1 6 0 27-May 102 30.6 0.5 0 6 100.00% 6 1 6 0 28-May 102 30.6 0.5 0 6 100.00% 6 1 6 0 29-May 102 30.6 0.5 0 6 100.00% 6 1 6 0 30-May 102 30.6 0.4 0 6 100.00% 6 1 6 0 31-May 102 30.6 0.4 0 6 100.00% 6 1 6 0 1-Jun 102 30.6 0.4 0 6 100.00% 6 1 6 0 2-Jun 102 30.6 0.4 0 6 100.00% 6 1 6 0 3-Jun 102 30.6 0.4 0 6 100.00% 6 1 6 0 4-Jun 102 30.6 0.4 0 6 100.00% 6 1 6 0 5-Jun 102 30.6 0.4 0 6 100.00% 6 1 6 0 6-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 7-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 8-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 9-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 10-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 11-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 12-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 13-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 14-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 15-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 16-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 17-Jun 102 30.6 0 0 6 100.00% 6 1 6 0 18-Jun 102 31.3 0 0 5.9 100.00% 5.9 1 5.9 0

86 19-Jun 102 32 0 0 5.8 100.00% 5.8 1 5.8 0 20-Jun 102 32.6 0 0 5.7 100.00% 5.7 1 5.7 0 21-Jun 102 33.3 0 0 5.6 100.00% 5.6 1 5.6 0 22-Jun 102 34 0 0 5.5 100.00% 5.5 1 5.5 0 23-Jun 102 34.7 0 0 5.5 100.00% 5.5 1 5.5 0 24-Jun 102 35.4 0 0 5.4 100.00% 5.4 1 5.4 0 25-Jun 102 36 0.2 0 5.3 100.00% 5.3 1 5.3 0 26-Jun 102 36.7 0.7 0 5.2 100.00% 5.2 1 5.2 0 27-Jun 102 37.4 1.2 0 5.1 100.00% 5.1 1 5.1 0 28-Jun 102 38.1 1.7 0 5.1 100.00% 5.1 1 5.1 0 29-Jun 102 38.8 2.1 0 5 100.00% 5 1 5 0 30-Jun 102 39.4 2.5 0 4.9 100.00% 4.9 1 4.9 0 1-Jul 102 40.1 2.9 0 4.8 100.00% 4.8 1 4.8 0 2-Jul 102 40.8 3.2 0 4.7 100.00% 4.7 1 4.7 0 3-Jul 102 41.5 3.6 0 4.7 100.00% 4.7 1 4.7 0 4-Jul 102 42.2 3.9 0 4.6 100.00% 4.6 1 4.6 0 5-Jul 102 42.8 4.2 0 4.5 100.00% 4.5 1 4.5 0 6-Jul 102 43.5 4.5 0 4.4 100.00% 4.4 1 4.4 0 7-Jul 102 44.2 4.7 0 4.3 100.00% 4.3 1 4.3 0 8-Jul 102 44.9 5 0 4.3 100.00% 4.3 1 4.3 0 9-Jul 102 45.6 5.2 0 4.2 100.00% 4.2 1 4.2 0 10-Jul 102 46.2 5.4 0 4.1 100.00% 4.1 1 4.1 0 11-Jul 102 46.9 5.6 0 4 100.00% 4 1 4 0 12-Jul 102 47.6 5.8 0 3.9 100.00% 3.9 1 3.9 0 13-Jul 102 48.3 6 0 3.8 100.00% 3.8 1 3.8 0 14-Jul 102 49 6.1 0 3.8 100.00% 3.8 1 3.8 0 15-Jul 102 49.6 6.3 0 3.7 100.00% 3.7 1 3.7 0 16-Jul 102 50.3 6.4 0 3.6 100.00% 3.6 1 3.6 0 17-Jul 102 51 6.5 0 3.5 100.00% 3.5 1 3.5 0 Total 221.9 0.5 594.1 100.00% 593.6 0 0

Estimated yield reduction in growth stage # 1 = 0 % Estimated yield reduction in growth stage # 2 = 0 % Estimated yield reduction in growth stage # 3 = 0 % Estimated yield reduction in growth stage # 14= 0 % Estimated total yield reduction =0% * These estimates may be used as guidelines and not as actual figures. * Legend: TAM = Total Available Moisture = (FC%- WP %)* Root Depth [mm]. RAM = Readily Available Moisture = TAM* P [mm]. SMD = Soil Moisture Deficit [mm].

87 8.2.3 Pepper

CropWat4 Windows Ver 4.3 Irrigation Scheduling Report

* Crop Data: - Crop # 1: Pepper - Block # : [All blocks] - Planting date :1-Mar * Soil Data: Soil description: Sandy clay loam Initial soil moisture depletion: 0% * Irrigation Scheduling Criteria: Application Timing: Irrigate each1days. Applications Depths: Refill to 100% of readily available soil moisture. Start of Scheduling: 1/3 Date TAM RAM Total Efct. ETc ETc/ETm SMD Interv. Net Lost User Rain Rain Irr. Irr. Adj. (mm) (mm) (mm) (mm) (mm) (%) (mm) (Days) (mm) (mm) (mm) 1-Mar 42.5 8.5 0.4 0 1.9 100.00% 1.9 2-Mar 43.8 8.8 0.4 0.4 2 100.00% 3.5 1 3.5 0 3-Mar 45.2 9.2 0.4 0 2 100.00% 2 1 2 0 4-Mar 46.5 9.5 0.5 0 2 100.00% 2 1 2 0 5-Mar 47.8 9.8 0.5 0 2 100.00% 2 1 2 0 6-Mar 49.2 10.2 0.5 0 2 100.00% 2 1 2 0 7-Mar 50.5 10.5 0.6 0 2 100.00% 2 1 2 0 8-Mar 51.9 10.9 0.6 0 2 100.00% 2 1 2 0 9-Mar 53.2 11.2 0.7 0 2 100.00% 2 1 2 0 10-Mar 54.5 11.6 0.7 0 2 100.00% 2 1 2 0 11-Mar 55.9 12 0.8 0 2 100.00% 2 1 2 0 12-Mar 57.2 12.3 0.8 0 2 100.00% 2 1 2 0 13-Mar 58.5 12.7 0.9 0 2 100.00% 2 1 2 0 14-Mar 59.9 13.1 0.9 0 2 100.00% 2 1 2 0 15-Mar 61.2 13.5 1 0 2 100.00% 2 1 2 0 16-Mar 62.5 13.8 1 0 2 100.00% 2 1 2 0 17-Mar 63.9 14.2 1.1 0 2 100.00% 2 1 2 0 18-Mar 65.2 14.6 1.1 0 2.1 100.00% 2.1 1 2.1 0 19-Mar 66.5 15 1.2 0 2.1 100.00% 2.1 1 2.1 0 20-Mar 67.9 15.4 1.2 0 2.1 100.00% 2.1 1 2.1 0 21-Mar 69.2 15.8 1.3 0 2.1 100.00% 2.1 1 2.1 0 22-Mar 70.5 16.2 1.3 0 2.1 100.00% 2.1 1 2.1 0 23-Mar 71.9 16.6 1.4 0 2.1 100.00% 2.1 1 2.1 0 24-Mar 73.2 17.1 1.4 0 2.1 100.00% 2.1 1 2.1 0

88 25-Mar 74.6 17.5 1.5 0 2.1 100.00% 2.1 1 2.1 0 26-Mar 75.9 17.9 1.5 0 2.1 100.00% 2.1 1 2.1 0 27-Mar 77.2 18.3 1.6 0 2.1 100.00% 2.1 1 2.1 0 28-Mar 78.6 18.7 1.6 0 2.1 100.00% 2.1 1 2.1 0 29-Mar 79.9 19.2 1.7 0 2.1 100.00% 2.1 1 2.1 0 30-Mar 81.2 19.6 1.7 0 2.1 100.00% 2.1 1 2.1 0 31-Mar 82.6 20.1 1.8 0 2.2 100.00% 2.2 1 2.2 0 1-Apr 83.9 20.5 1.8 0 2.3 100.00% 2.3 1 2.3 0 2-Apr 85.2 20.9 1.8 0 2.4 100.00% 2.4 1 2.4 0 3-Apr 86.6 21.4 1.9 0 2.4 100.00% 2.4 1 2.4 0 4-Apr 87.9 21.9 1.9 0 2.5 100.00% 2.5 1 2.5 0 5-Apr 89.2 22.3 1.9 0 2.6 100.00% 2.6 1 2.6 0 6-Apr 90.6 22.8 2 0 2.7 100.00% 2.7 1 2.7 0 7-Apr 91.9 23.2 2 0 2.8 100.00% 2.8 1 2.8 0 8-Apr 93.3 23.7 2 0 2.8 100.00% 2.8 1 2.8 0 9-Apr 94.6 24.2 2.1 0 2.9 100.00% 2.9 1 2.9 0 10-Apr 95.9 24.7 2.1 0 3 100.00% 3 1 3 0 11-Apr 97.3 25.1 2.1 0 3.1 100.00% 3.1 1 3.1 0 12-Apr 98.6 25.6 2.1 0 3.2 100.00% 3.2 1 3.2 0 13-Apr 99.9 26.1 2.1 0 3.2 100.00% 3.2 1 3.2 0 14-Apr 101.3 26.6 2.1 0 3.3 100.00% 3.3 1 3.3 0 15-Apr 102.6 27.1 2.1 0 3.4 100.00% 3.4 1 3.4 0 16-Apr 103.9 27.6 2.2 0 3.5 100.00% 3.5 1 3.5 0 17-Apr 105.3 28.1 2.2 0 3.6 100.00% 3.6 1 3.6 0 18-Apr 106.6 28.6 2.2 0 3.7 100.00% 3.7 1 3.7 0 19-Apr 107.9 29.1 2.1 0 3.7 100.00% 3.7 1 3.7 0 20-Apr 109.3 29.7 2.1 0 3.8 100.00% 3.8 1 3.8 0 21-Apr 110.6 30.2 2.1 0 3.9 100.00% 3.9 1 3.9 0 22-Apr 112 30.7 2.1 0 4 100.00% 4 1 4 0 23-Apr 113.3 31.2 2.1 0 4.1 100.00% 4.1 1 4.1 0 24-Apr 114.6 31.8 2.1 0 4.1 100.00% 4.1 1 4.1 0 25-Apr 116 32.3 2.1 0 4.2 100.00% 4.2 1 4.2 0 26-Apr 117.3 32.8 2 0 4.3 100.00% 4.3 1 4.3 0 27-Apr 118.6 33.4 2 0 4.4 100.00% 4.4 1 4.4 0 28-Apr 120 33.9 2 0 4.5 100.00% 4.5 1 4.5 0 29-Apr 121.3 34.5 2 0 4.6 100.00% 4.6 1 4.6 0 30-Apr 122.6 35 1.9 0 4.6 100.00% 4.6 1 4.6 0 1-May 124 35.6 1.9 0 4.7 100.00% 4.7 1 4.7 0 2-May 125.3 36.2 1.8 0 4.8 100.00% 4.8 1 4.8 0 3-May 126.7 36.7 1.8 0 4.9 100.00% 4.9 1 4.9 0

89 4-May 128 37.3 1.7 0 5 100.00% 5 1 5 0 5-May 129.3 37.9 1.7 0 5.1 100.00% 5.1 1 5.1 0 6-May 130.7 38.5 1.7 0 5.1 100.00% 5.1 1 5.1 0 7-May 132 39 1.6 0 5.2 100.00% 5.2 1 5.2 0 8-May 133.3 39.6 1.6 0 5.3 100.00% 5.3 1 5.3 0 9-May 134.7 40.2 1.5 0 5.4 100.00% 5.4 1 5.4 0 10-May 136 40.8 1.4 0 5.4 100.00% 5.4 1 5.4 0 11-May 136 40.8 1.4 0 5.4 100.00% 5.4 1 5.4 0 12-May 136 40.8 1.3 0 5.4 100.00% 5.4 1 5.4 0 13-May 136 40.8 1.3 0 5.4 100.00% 5.4 1 5.4 0 14-May 136 40.8 1.2 0 5.4 100.00% 5.4 1 5.4 0 15-May 136 40.8 1.2 0 5.4 100.00% 5.4 1 5.4 0 16-May 136 40.8 1.1 0 5.4 100.00% 5.4 1 5.4 0 17-May 136 40.8 1 0 5.4 100.00% 5.4 1 5.4 0 18-May 136 40.8 1 0 5.4 100.00% 5.4 1 5.4 0 19-May 136 40.8 0.9 0 5.4 100.00% 5.4 1 5.4 0 20-May 136 40.8 0.9 0 5.4 100.00% 5.4 1 5.4 0 21-May 136 40.8 0.8 0 5.4 100.00% 5.4 1 5.4 0 22-May 136 40.8 0.8 0 5.4 100.00% 5.4 1 5.4 0 23-May 136 40.8 0.7 0 5.4 100.00% 5.4 1 5.4 0 24-May 136 40.8 0.7 0 5.4 100.00% 5.4 1 5.4 0 25-May 136 40.8 0.6 0 5.4 100.00% 5.4 1 5.4 0 26-May 136 40.8 0.6 0 5.4 100.00% 5.4 1 5.4 0 27-May 136 40.8 0.5 0 5.4 100.00% 5.4 1 5.4 0 28-May 136 40.8 0.5 0 5.4 100.00% 5.4 1 5.4 0 29-May 136 40.8 0.5 0 5.4 100.00% 5.4 1 5.4 0 30-May 136 40.8 0.4 0 5.4 100.00% 5.4 1 5.4 0 31-May 136 40.8 0.4 0 5.4 100.00% 5.4 1 5.4 0 1-Jun 136 40.8 0.4 0 5.4 100.00% 5.4 1 5.4 0 2-Jun 136 40.8 0.4 0 5.4 100.00% 5.4 1 5.4 0 3-Jun 136 40.8 0.4 0 5.4 100.00% 5.4 1 5.4 0 4-Jun 136 40.8 0.4 0 5.4 100.00% 5.4 1 5.4 0 5-Jun 136 40.8 0.4 0 5.4 100.00% 5.4 1 5.4 0 6-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 7-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 8-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 9-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 10-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 11-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 12-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0

90 13-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 14-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 15-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 16-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 17-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 18-Jun 136 40.8 0 0 5.4 100.00% 5.4 1 5.4 0 19-Jun 136 41.9 0 0 5.3 100.00% 5.3 1 5.3 0 20-Jun 136 43 0 0 5.3 100.00% 5.3 1 5.3 0 21-Jun 136 44.1 0 0 5.3 100.00% 5.3 1 5.3 0 22-Jun 136 45.2 0 0 5.2 100.00% 5.2 1 5.2 0 23-Jun 136 46.2 0 0 5.2 100.00% 5.2 1 5.2 0 24-Jun 136 47.3 0 0 5.1 100.00% 5.1 1 5.1 0 25-Jun 136 48.4 0.2 0 5.1 100.00% 5.1 1 5.1 0 26-Jun 136 49.5 0.7 0 5.1 100.00% 5.1 1 5.1 0 27-Jun 136 50.6 1.2 0 5 100.00% 5 1 5 0 28-Jun 136 51.7 1.7 0 5 100.00% 5 1 5 0 29-Jun 136 52.8 2.1 0 4.9 100.00% 4.9 1 4.9 0 30-Jun 136 53.9 2.5 0 4.9 100.00% 4.9 1 4.9 0 1-Jul 136 54.9 2.9 0 4.9 100.00% 4.9 1 4.9 0 2-Jul 136 56 3.2 0 4.8 100.00% 4.8 1 4.8 0 3-Jul 136 57.1 3.6 0 4.8 100.00% 4.8 1 4.8 0 4-Jul 136 58.2 3.9 0 4.7 100.00% 4.7 1 4.7 0 5-Jul 136 59.3 4.2 0 4.7 100.00% 4.7 1 4.7 0 6-Jul 136 60.4 4.5 0 4.7 100.00% 4.7 1 4.7 0 7-Jul 136 61.5 4.7 0 4.6 100.00% 4.6 1 4.6 0 8-Jul 136 62.6 5 0 4.6 100.00% 4.6 1 4.6 0 9-Jul 136 63.6 5.2 0 4.5 100.00% 4.5 1 4.5 0 10-Jul 136 64.7 5.4 0 4.5 100.00% 4.5 1 4.5 0 11-Jul 136 65.8 5.6 0 4.5 100.00% 4.5 1 4.5 0 12-Jul 136 66.9 5.8 0 4.4 100.00% 4.4 1 4.4 0 13-Jul 136 68 6 0 4.4 100.00% 4.4 1 4.4 0 Total 198.3 0.4 550.6 100.00% 550.2 0 0 * Yield Reduction: Estimated yield reduction in growth stage # 1 = 0 % Estimated yield reduction in growth stage # 2 = 0 % Estimated yield reduction in growth stage # 3 = 0 % Estimated yield reduction in growth stage # 14= 0 % Estimated total yield reduction =0% * These estimates may be used as guidelines and not as actual figures. * Legend: TAM = Total Available Moisture = (FC%- WP %)* Root Depth [mm]. RAM = Readily Available Moisture = TAM* P [mm]. SMD = Soil Moisture Deficit [mm].

91 8.3 Irrigation scheduling of different vegetables during rain-fed schedule

8.3.1 Onion

CropWat4 Windows Ver 4.3 Irrigation Scheduling Report * Crop Data: - Crop # 1: Onion - Block # : [All blocks] - Planting date :5-Mar * Soil Data: Soil description: Sandy clay loam Initial soil moisture depletion: 0% * Irrigation Scheduling Criteria: Rain-fed scheduling Irrigate each1days. Start of Scheduling: 5/3 Date TAM RAM Total Efct. ETc ETc/ETm SMD Interv. Net Lost User Rain Rain Irr. Irr. Adj. (mm) (mm) (mm) (mm) (mm) (%) (mm) (Days) (mm) (mm) (mm) 5-Mar 51 12.8 0.5 0 2 100.00% 2 6-Mar 51.9 13 0.5 0.5 2 100.00% 3.4 7-Mar 52.7 13.3 0.6 0.6 2 100.00% 4.8 8-Mar 53.5 13.5 0.6 0.6 2 100.00% 6.2 9-Mar 54.4 13.8 0.7 0.7 2 100.00% 7.5 10-Mar 55.3 14 0.7 0.7 2 100.00% 8.8 11-Mar 56.1 14.3 0.8 0.8 2 100.00% 10 12-Mar 57 14.6 0.8 0.8 2 100.00% 11.3 13-Mar 57.8 14.8 0.9 0.9 2 100.00% 12.4 14-Mar 58.7 15.1 0.9 0.9 2 100.00% 13.5 15-Mar 59.5 15.4 1 1 2 100.00% 14.6 16-Mar 60.4 15.6 1 1 2 100.00% 15.6 17-Mar 61.2 15.9 1.1 1.1 2 100.00% 16.6 18-Mar 62.1 16.2 1.1 1.1 2.1 100.00% 17.5 19-Mar 62.9 16.5 1.2 1.2 2.1 100.00% 18.4 20-Mar 63.8 16.7 1.2 1.2 2 99.00% 19.3 21-Mar 64.6 17 1.3 1.3 2 98.00% 20 22-Mar 65.5 17.3 1.3 1.3 2 97.10% 20.7 23-Mar 66.3 17.6 1.4 1.4 2 96.40% 21.3 24-Mar 67.2 17.9 1.4 1.4 2 95.90% 21.9 25-Mar 68 18.1 1.5 1.5 2 95.40% 22.4 26-Mar 68.9 18.4 1.5 1.5 2 95.10% 22.9 27-Mar 69.7 18.7 1.6 1.6 2 94.90% 23.3 28-Mar 70.6 19 1.6 1.6 2 94.80% 23.7 29-Mar 71.4 19.3 1.7 1.7 2 94.80% 24

92 30-Mar 72.3 19.6 1.7 1.7 2 94.90% 24.3 31-Mar 73.1 19.9 1.8 1.8 2 95.00% 24.6 1-Apr 73.9 20.2 1.8 1.8 2 95.20% 24.8 2-Apr 74.8 20.4 1.8 1.8 2 95.40% 25 3-Apr 75.7 20.7 1.9 1.9 2.1 95.70% 25.2 4-Apr 76.5 21 1.9 1.9 2.2 96.00% 25.4 5-Apr 77.3 21.3 1.9 1.9 2.3 96.20% 25.7 6-Apr 78.2 21.6 2 2 2.4 96.30% 26.1 7-Apr 79.1 21.9 2 2 2.5 96.20% 26.5 8-Apr 79.9 22.2 2 2 2.6 96.10% 27.1 9-Apr 80.8 22.5 2.1 2.1 2.7 95.70% 27.7 10-Apr 81.6 22.8 2.1 2.1 2.7 95.30% 28.3 11-Apr 82.5 23.2 2.1 2.1 2.8 94.80% 29.1 12-Apr 83.3 23.5 2.1 2.1 2.9 94.20% 29.8 13-Apr 84.2 23.8 2.1 2.1 3 93.50% 30.7 14-Apr 85 24.1 2.1 2.1 3.1 92.60% 31.6 15-Apr 85.8 24.4 2.1 2.1 3.1 91.70% 32.6 16-Apr 86.7 24.7 2.2 2.2 3.2 90.70% 33.6 17-Apr 87.6 25 2.2 2.2 3.2 89.70% 34.7 18-Apr 88.4 25.3 2.2 2.2 3.3 88.50% 35.9 19-Apr 89.3 25.7 2.1 2.1 3.3 87.30% 37.1 20-Apr 90.1 26 2.1 2.1 3.4 86.00% 38.3 21-Apr 91 26.3 2.1 2.1 3.4 84.70% 39.6 22-Apr 91.8 26.6 2.1 2.1 3.5 83.30% 41 23-Apr 92.7 26.9 2.1 2.1 3.5 81.80% 42.4 24-Apr 93.5 27.3 2.1 2.1 3.5 80.40% 43.8 25-Apr 94.3 27.6 2.1 2.1 3.5 78.80% 45.3 26-Apr 95.2 27.9 2 2 3.5 77.30% 46.8 27-Apr 96.1 28.3 2 2 3.6 75.60% 48.3 28-Apr 96.9 28.6 2 2 3.6 74.00% 49.9 29-Apr 97.8 28.9 2 2 3.6 72.30% 51.5 30-Apr 98.6 29.3 1.9 1.9 3.6 70.70% 53.2 1-May 99.5 29.6 1.9 1.9 3.5 69.00% 54.8 2-May 100.3 29.9 1.8 1.8 3.5 67.20% 56.5 3-May 101.2 30.3 1.8 1.8 3.5 65.50% 58.2 4-May 102 30.6 1.7 1.7 3.4 63.80% 59.9 5-May 102 30.6 1.7 1.7 3.3 61.40% 61.5 6-May 102 30.6 1.7 1.7 3.2 59.10% 63 7-May 102 30.6 1.6 1.6 3.1 56.90% 64.5 8-May 102 30.6 1.6 1.6 2.9 54.70% 65.9

93 9-May 102 30.6 1.5 1.5 2.8 52.70% 67.2 10-May 102 30.6 1.4 1.4 2.7 50.80% 68.5 11-May 102 30.6 1.4 1.4 2.6 48.90% 69.8 12-May 102 30.6 1.3 1.3 2.5 47.00% 71 13-May 102 30.6 1.3 1.3 2.4 45.20% 72.1 14-May 102 30.6 1.2 1.2 2.4 43.50% 73.3 15-May 102 30.6 1.2 1.2 2.3 41.80% 74.4 16-May 102 30.6 1.1 1.1 2.2 40.20% 75.5 17-May 102 30.6 1 1 2.1 38.60% 76.5 18-May 102 30.6 1 1 2 37.00% 77.6 19-May 102 30.6 0.9 0.9 1.9 35.50% 78.6 20-May 102 30.6 0.9 0.9 1.8 34.00% 79.6 21-May 102 30.6 0.8 0.8 1.8 32.60% 80.5 22-May 102 30.6 0.8 0.8 1.7 31.20% 81.4 23-May 102 30.6 0.7 0.7 1.6 29.80% 82.4 24-May 102 30.6 0.7 0.7 1.5 28.40% 83.2 25-May 102 30.6 0.6 0.6 1.5 27.10% 84.1 26-May 102 30.6 0.6 0.6 1.4 25.90% 84.9 27-May 102 30.6 0.5 0.5 1.3 24.60% 85.7 28-May 102 30.6 0.5 0.5 1.3 23.50% 86.5 29-May 102 30.6 0.5 0.5 1.2 22.30% 87.3 30-May 102 30.6 0.4 0.4 1.2 21.30% 88 31-May 102 30.6 0.4 0.4 1.1 20.30% 88.6 1-Jun 102 30.6 0.4 0.4 1 19.30% 89.3 2-Jun 102 30.6 0.4 0.4 1 18.40% 89.9 3-Jun 102 30.6 0.4 0.4 1 17.60% 90.4 4-Jun 102 30.6 0.4 0.4 0.9 16.80% 90.9 5-Jun 102 30.6 0.4 0.4 0.9 16.20% 91.3 6-Jun 102 30.6 0 0 0.8 14.90% 92.1 7-Jun 102 30.6 0 0 0.7 13.80% 92.9 8-Jun 102 30.6 0 0 0.7 12.80% 93.6 9-Jun 102 30.6 0 0 0.6 11.80% 94.2 10-Jun 102 30.6 0 0 0.6 10.90% 94.8 11-Jun 102 30.6 0 0 0.5 10.10% 95.3 12-Jun 102 30.6 0 0 0.5 9.30% 95.9 13-Jun 102 30.6 0 0 0.5 8.60% 96.3 14-Jun 102 30.6 0 0 0.4 8.00% 96.7 15-Jun 102 30.6 0 0 0.4 7.40% 97.1 16-Jun 102 30.6 0 0 0.4 6.80% 97.5 17-Jun 102 30.6 0 0 0.3 6.30% 97.8

94 18-Jun 102 31.4 0 0 0.3 5.90% 98.2 19-Jun 102 32.2 0 0 0.3 5.50% 98.5 20-Jun 102 33 0 0 0.3 5.10% 98.7 21-Jun 102 33.9 0 0 0.2 4.80% 99 22-Jun 102 34.7 0 0 0.2 4.50% 99.2 23-Jun 102 35.5 0 0 0.2 4.20% 99.4 24-Jun 102 36.3 0 0 0.2 3.90% 99.6 25-Jun 102 37.1 0.2 0.2 0.2 4.00% 99.6 26-Jun 102 37.9 0.7 0.7 0.2 4.90% 99.1 27-Jun 102 38.8 1.2 1.2 0.3 6.50% 98.2 28-Jun 102 39.6 1.7 1.7 0.4 8.70% 97 29-Jun 102 40.4 2.1 2.1 0.5 11.50% 95.5 30-Jun 102 41.2 2.5 2.5 0.7 14.80% 93.7 7-Jan 102 42 2.9 2.9 0.9 18.60% 91.7 7-Feb 102 42.8 3.2 3.2 1.1 22.90% 89.5 7-Mar 102 43.7 3.6 3.6 1.3 27.50% 87.2 7-Apr 102 44.5 3.9 3.9 1.5 32.50% 84.8 7-May 102 45.3 4.2 4.2 1.7 37.70% 82.3 7-Jun 102 46.1 4.5 4.5 1.9 43.30% 79.7 7-Jul 102 46.9 4.7 4.7 2.1 49.00% 77.1 7-Aug 102 47.7 5 5 2.4 55.00% 74.5 7-Sep 102 48.6 5.2 5.2 2.6 61.20% 71.9 7-Oct 102 49.4 5.4 5.4 2.8 67.50% 69.3 7-Nov 102 50.2 5.6 5.6 3.1 73.90% 66.8 7-Dec 102 51 5.8 5.8 3.3 80.50% 64.3 Total 190.6 190.1 254.4 47.40% 0 0

* Yield Reduction: - Estimated yield reduction in growth stage # 1 =1% - Estimated yield reduction in growth stage # 2 = 13.6% - Estimated yield reductionin growth stage # 3 = 56.8% - Estimated yield reduction in growth stage # 4 = 22.7% - Estimated total yield reduction = 57.9% * These estimates may be used as guidelines and not as actual figures. * Legend: TAM = Total Available Moisture = (FC%- WP %)* Root Depth [mm]. RAM = Readily Available Moisture = TAM* P [mm]. SMD = Soil Moisture Deficit [mm].

95 8.3.2 Tomato

CropWat4 Windows Ver 4.3 Irrigation Scheduling Report * Crop Data: - Crop # 1: Tomato - Block # : [All blocks] - Planting date :5-Mar * Soil Data: Soil description: Sandy clay loam Initial soil moisture depletion: 0% * Irrigation Scheduling Criteria: Rain-fed scheduling Irrigate each1days. Start of Scheduling: 5/3 Date TAM RAM Total Efct. ETc ETc/ETm SMD Interv. Net Lost User Rain Rain Irr. Irr. Adj. (mm) (mm) (mm) (mm) (mm) (%) (mm) (Days) (mm) (mm) (mm) 5-Mar 51 12.8 0.5 0 2 100.00% 2 6-Mar 51.9 13 0.5 0.5 2 100.00% 3.4 7-Mar 52.7 13.3 0.6 0.6 2 100.00% 4.8 8-Mar 53.5 13.5 0.6 0.6 2 100.00% 6.2 9-Mar 54.4 13.8 0.7 0.7 2 100.00% 7.5 10-Mar 55.3 14 0.7 0.7 2 100.00% 8.8 11-Mar 56.1 14.3 0.8 0.8 2 100.00% 10 12-Mar 57 14.6 0.8 0.8 2 100.00% 11.3 13-Mar 57.8 14.8 0.9 0.9 2 100.00% 12.4 14-Mar 58.7 15.1 0.9 0.9 2 100.00% 13.5 15-Mar 59.5 15.4 1 1 2 100.00% 14.6 16-Mar 60.4 15.6 1 1 2 100.00% 15.6 17-Mar 61.2 15.9 1.1 1.1 2 100.00% 16.6 18-Mar 62.1 16.2 1.1 1.1 2.1 100.00% 17.5 19-Mar 62.9 16.5 1.2 1.2 2.1 100.00% 18.4 20-Mar 63.8 16.7 1.2 1.2 2 99.00% 19.3 21-Mar 64.6 17 1.3 1.3 2 98.00% 20 22-Mar 65.5 17.3 1.3 1.3 2 97.10% 20.7 23-Mar 66.3 17.6 1.4 1.4 2 96.40% 21.3 24-Mar 67.2 17.9 1.4 1.4 2 95.90% 21.9 25-Mar 68 18.1 1.5 1.5 2 95.40% 22.4 26-Mar 68.9 18.4 1.5 1.5 2 95.10% 22.9 27-Mar 69.7 18.7 1.6 1.6 2 94.90% 23.3 28-Mar 70.6 19 1.6 1.6 2 94.80% 23.7 29-Mar 71.4 19.3 1.7 1.7 2 94.80% 24 30-Mar 72.3 19.6 1.7 1.7 2 94.90% 24.3 31-Mar 73.1 19.9 1.8 1.8 2 95.00% 24.6

96 1-Apr 73.9 20.2 1.8 1.8 2 95.20% 24.8 2-Apr 74.8 20.4 1.8 1.8 2 95.40% 25 3-Apr 75.7 20.7 1.9 1.9 2.1 95.70% 25.2 4-Apr 76.5 21 1.9 1.9 2.2 96.00% 25.4 5-Apr 77.3 21.3 1.9 1.9 2.3 96.20% 25.8 6-Apr 78.2 21.6 2 2 2.4 96.20% 26.2 7-Apr 79.1 21.9 2 2 2.5 96.10% 26.7 8-Apr 79.9 22.2 2 2 2.6 95.80% 27.3 9-Apr 80.8 22.5 2.1 2.1 2.7 95.30% 28 10-Apr 81.6 22.8 2.1 2.1 2.8 94.80% 28.8 11-Apr 82.5 23.2 2.1 2.1 2.9 94.10% 29.6 12-Apr 83.3 23.5 2.1 2.1 3 93.30% 30.5 13-Apr 84.2 23.8 2.1 2.1 3.1 92.30% 31.5 14-Apr 85 24.1 2.1 2.1 3.2 91.30% 32.6 15-Apr 85.8 24.4 2.1 2.1 3.3 90.20% 33.7 16-Apr 86.7 24.7 2.2 2.2 3.3 89.00% 34.9 17-Apr 87.6 25 2.2 2.2 3.4 87.70% 36.1 18-Apr 88.4 25.3 2.2 2.2 3.5 86.30% 37.4 19-Apr 89.3 25.7 2.1 2.1 3.5 84.90% 38.8 20-Apr 90.1 26 2.1 2.1 3.5 83.40% 40.2 21-Apr 91 26.3 2.1 2.1 3.6 81.80% 41.7 22-Apr 91.8 26.6 2.1 2.1 3.6 80.20% 43.2 23-Apr 92.7 26.9 2.1 2.1 3.6 78.50% 44.7 24-Apr 93.5 27.3 2.1 2.1 3.7 76.80% 46.3 25-Apr 94.3 27.6 2.1 2.1 3.7 75.10% 47.9 26-Apr 95.2 27.9 2 2 3.7 73.40% 49.5 27-Apr 96.1 28.3 2 2 3.7 71.60% 51.2 28-Apr 96.9 28.6 2 2 3.7 69.80% 52.9 29-Apr 97.8 28.9 2 2 3.7 68.00% 54.6 30-Apr 98.6 29.3 1.9 1.9 3.7 66.20% 56.4 1-May 99.5 29.6 1.9 1.9 3.6 64.30% 58.1 2-May 100.3 29.9 1.8 1.8 3.6 62.50% 59.9 3-May 101.2 30.3 1.8 1.8 3.6 60.70% 61.7 4-May 102 30.6 1.7 1.7 3.5 58.80% 63.5 5-May 102 30.6 1.7 1.7 3.3 56.30% 65.1 6-May 102 30.6 1.7 1.7 3.2 54.00% 66.7 7-May 102 30.6 1.6 1.6 3.1 51.70% 68.1 8-May 102 30.6 1.6 1.6 3 49.60% 69.5 9-May 102 30.6 1.5 1.5 2.8 47.60% 70.9 10-May 102 30.6 1.4 1.4 2.7 45.60% 72.2

97 11-May 102 30.6 1.4 1.4 2.6 43.70% 73.4 12-May 102 30.6 1.3 1.3 2.5 41.90% 74.6 13-May 102 30.6 1.3 1.3 2.4 40.20% 75.7 14-May 102 30.6 1.2 1.2 2.3 38.50% 76.8 15-May 102 30.6 1.2 1.2 2.2 36.90% 77.8 16-May 102 30.6 1.1 1.1 2.1 35.40% 78.9 17-May 102 30.6 1 1 2 33.90% 79.9 18-May 102 30.6 1 1 1.9 32.40% 80.8 19-May 102 30.6 0.9 0.9 1.9 31.00% 81.8 20-May 102 30.6 0.9 0.9 1.8 29.60% 82.7 21-May 102 30.6 0.8 0.8 1.7 28.20% 83.5 22-May 102 30.6 0.8 0.8 1.6 26.90% 84.4 23-May 102 30.6 0.7 0.7 1.5 25.60% 85.2 24-May 102 30.6 0.7 0.7 1.5 24.40% 86 25-May 102 30.6 0.6 0.6 1.4 23.20% 86.8 26-May 102 30.6 0.6 0.6 1.3 22.10% 87.6 27-May 102 30.6 0.5 0.5 1.3 21.00% 88.3 28-May 102 30.6 0.5 0.5 1.2 19.90% 89 29-May 102 30.6 0.5 0.5 1.1 18.90% 89.7 30-May 102 30.6 0.4 0.4 1.1 17.90% 90.3 31-May 102 30.6 0.4 0.4 1 17.00% 90.9 1-Jun 102 30.6 0.4 0.4 1 16.20% 91.4 2-Jun 102 30.6 0.4 0.4 0.9 15.40% 91.9 3-Jun 102 30.6 0.4 0.4 0.9 14.70% 92.4 4-Jun 102 30.6 0.4 0.4 0.8 14.00% 92.8 5-Jun 102 30.6 0.4 0.4 0.8 13.50% 93.2 25-Jun 102 36 0.2 0.2 0.2 6.20% 100.2 26-Jun 102 36.7 0.7 0.7 0.2 3.80% 99.7 27-Jun 102 37.4 1.2 1.2 0.3 5.40% 98.8 28-Jun 102 38.1 1.7 1.7 0.4 7.60% 97.5 29-Jun 102 38.8 2.1 2.1 0.5 10.40% 96 30-Jun 102 39.4 2.5 2.5 0.7 13.60% 94.1 1-Jul 102 40.1 2.9 2.9 0.8 17.30% 92.1 2-Jul 102 40.8 3.2 3.2 1 21.40% 89.9 3-Jul 102 41.5 3.6 3.6 1.2 25.90% 87.5 4-Jul 102 42.2 3.9 3.9 1.4 30.70% 85.1 5-Jul 102 42.8 4.2 4.2 1.6 35.70% 82.5 6-Jul 102 43.5 4.5 4.5 1.8 41.00% 79.8 7-Jul 102 44.2 4.7 4.7 2 46.60% 77.1 8-Jul 102 44.9 5 5 2.2 52.30% 74.3

98 9-Jul 102 45.6 5.2 5.2 2.4 58.30% 71.5 10-Jul 102 46.2 5.4 5.4 2.6 64.40% 68.7 11-Jul 102 46.9 5.6 5.6 2.8 70.60% 65.9 12-Jul 102 47.6 5.8 5.8 3 77.00% 63.2 13-Jul 102 48.3 6 6 3.2 83.40% 60.4 14-Jul 102 49 6.1 6.1 3.4 90.00% 57.6 15-Jul 102 49.6 6.3 6.3 3.6 96.70% 54.9 16-Jul 102 50.3 6.4 6.4 3.6 100.00% 52.1 17-Jul 102 51 6.5 6.5 3.5 100.00% 49.2 Total 221.9 221.4 270.6 45.50% 0 0 0 * Yield Reduction: - Estimated yield reduction in growth stage # 1 =1% - Estimated yield reduction in growth stage # 2 = 16% - Estimated yield reductionin growth stage # 3 = 59.7% - Estimated yield reduction in growth stage # 4 = 20.6% - Estimated total yield reduction = 59.9% * These estimates may be used as guidelines and not as actual figures. * Legend: TAM = Total Available Moisture = (FC%- WP %)* Root Depth [mm]. RAM = Readily Available Moisture = TAM* P [mm]. SMD = Soil Moisture Deficit [mm].

99 8.3.3 Pepper

CropWat4 Windows Ver 4.3 Irrigation Scheduling Report * Crop Data: - Crop # 1: Pepper - Block # : [All blocks] - Planting date :1-Mar * Soil Data: Soil description: Sandy clay loam Initial soil moisture depletion: 0% Irrigation Scheduling Criteria: Rain-fed scheduling Irrigate each1days. Start of Scheduling: 1/3 Date TAM RAM Total Efct. ETc ETc/ETm SMD Interv. Net Lost User Rain Rain Irr. Irr. Adj. (mm) (mm) (mm) (mm) (mm) (%) (mm) (Days) (mm) (mm) (mm) 1-Mar 42.5 8.5 0.4 0 1.9 100.00% 1.9 2-Mar 43.8 8.8 0.4 0.4 2 100.00% 3.5 3-Mar 45.2 9.2 0.4 0.4 2 100.00% 5 4-Mar 46.5 9.5 0.5 0.5 2 100.00% 6.5 5-Mar 47.8 9.8 0.5 0.5 2 100.00% 8 6-Mar 49.2 10.2 0.5 0.5 2 100.00% 9.4 7-Mar 50.5 10.5 0.6 0.6 2 100.00% 10.8 8-Mar 51.9 10.9 0.6 0.6 2 100.00% 12.2 9-Mar 53.2 11.2 0.7 0.7 2 99.30% 13.5 10-Mar 54.5 11.6 0.7 0.7 1.9 97.20% 14.8 11-Mar 55.9 12 0.8 0.8 1.9 95.40% 15.9 12-Mar 57.2 12.3 0.8 0.8 1.9 93.80% 17 13-Mar 58.5 12.7 0.9 0.9 1.9 92.50% 18 14-Mar 59.9 13.1 0.9 0.9 1.9 91.40% 18.9 15-Mar 61.2 13.5 1 1 1.8 90.50% 19.8 16-Mar 62.5 13.8 1 1 1.8 89.80% 20.6 17-Mar 63.9 14.2 1.1 1.1 1.8 89.20% 21.4 18-Mar 65.2 14.6 1.1 1.1 1.8 88.80% 22.1 19-Mar 66.5 15 1.2 1.2 1.8 88.50% 22.8 20-Mar 67.9 15.4 1.2 1.2 1.8 88.30% 23.4 21-Mar 69.2 15.8 1.3 1.3 1.8 88.30% 23.9 22-Mar 70.5 16.2 1.3 1.3 1.8 88.30% 24.4 23-Mar 71.9 16.6 1.4 1.4 1.8 88.40% 24.9 24-Mar 73.2 17.1 1.4 1.4 1.9 88.60% 25.3 25-Mar 74.6 17.5 1.5 1.5 1.9 88.90% 25.7 26-Mar 75.9 17.9 1.5 1.5 1.9 89.20% 26

100 27-Mar 77.2 18.3 1.6 1.6 1.9 89.60% 26.3 28-Mar 78.6 18.7 1.6 1.6 1.9 90.10% 26.6 29-Mar 79.9 19.2 1.7 1.7 1.9 90.50% 26.8 30-Mar 81.2 19.6 1.7 1.7 1.9 91.10% 27.1 31-Mar 82.6 20.1 1.8 1.8 2 91.60% 27.3 1-Apr 83.9 20.5 1.8 1.8 2.1 92.10% 27.6 2-Apr 85.2 20.9 1.8 1.8 2.2 92.50% 27.9 3-Apr 86.6 21.4 1.9 1.9 2.3 92.80% 28.3 4-Apr 87.9 21.9 1.9 1.9 2.3 93.10% 28.8 5-Apr 89.2 22.3 1.9 1.9 2.4 93.30% 29.2 6-Apr 90.6 22.8 2 2 2.5 93.40% 29.8 7-Apr 91.9 23.2 2 2 2.6 93.40% 30.3 8-Apr 93.3 23.7 2 2 2.7 93.40% 30.9 9-Apr 94.6 24.2 2.1 2.1 2.7 93.30% 31.6 10-Apr 95.9 24.7 2.1 2.1 2.8 93.20% 32.3 11-Apr 97.3 25.1 2.1 2.1 2.9 93.00% 33.1 12-Apr 98.6 25.6 2.1 2.1 2.9 92.70% 33.9 13-Apr 99.9 26.1 2.1 2.1 3 92.30% 34.8 14-Apr 101.3 26.6 2.1 2.1 3.1 91.90% 35.7 15-Apr 102.6 27.1 2.1 2.1 3.1 91.50% 36.7 16-Apr 103.9 27.6 2.2 2.2 3.2 91.00% 37.7 17-Apr 105.3 28.1 2.2 2.2 3.2 90.40% 38.8 18-Apr 106.6 28.6 2.2 2.2 3.3 89.80% 39.9 19-Apr 107.9 29.1 2.1 2.1 3.3 89.10% 41.1 20-Apr 109.3 29.7 2.1 2.1 3.4 88.40% 42.3 21-Apr 110.6 30.2 2.1 2.1 3.4 87.60% 43.6 22-Apr 112 30.7 2.1 2.1 3.5 86.80% 44.9 23-Apr 113.3 31.2 2.1 2.1 3.5 85.90% 46.3 24-Apr 114.6 31.8 2.1 2.1 3.5 85.00% 47.7 25-Apr 116 32.3 2.1 2.1 3.6 84.00% 49.2 26-Apr 117.3 32.8 2 2 3.6 83.00% 50.8 27-Apr 118.6 33.4 2 2 3.6 82.00% 52.4 28-Apr 120 33.9 2 2 3.6 80.90% 54 29-Apr 121.3 34.5 2 2 3.6 79.80% 55.7 30-Apr 122.6 35 1.9 1.9 3.7 78.60% 57.4 1-May 124 35.6 1.9 1.9 3.7 77.40% 59.2 2-May 125.3 36.2 1.8 1.8 3.7 76.20% 61 3-May 126.7 36.7 1.8 1.8 3.7 75.00% 62.9 4-May 128 37.3 1.7 1.7 3.7 73.70% 64.8 5-May 129.3 37.9 1.7 1.7 3.7 72.40% 66.8

101 6-May 130.7 38.5 1.7 1.7 3.7 71.10% 68.8 7-May 132 39 1.6 1.6 3.6 69.70% 70.8 8-May 133.3 39.6 1.6 1.6 3.6 68.40% 72.9 9-May 134.7 40.2 1.5 1.5 3.6 67.00% 75 10-May 136 40.8 1.4 1.4 3.5 65.60% 77.1 11-May 136 40.8 1.4 1.4 3.4 63.30% 79.1 12-May 136 40.8 1.3 1.3 3.3 61.10% 81.1 13-May 136 40.8 1.3 1.3 3.2 59.00% 83 14-May 136 40.8 1.2 1.2 3.1 56.90% 84.9 15-May 136 40.8 1.2 1.2 3 54.90% 86.7 16-May 136 40.8 1.1 1.1 2.9 52.90% 88.5 17-May 136 40.8 1 1 2.8 51.00% 90.2 18-May 136 40.8 1 1 2.7 49.10% 91.9 19-May 136 40.8 0.9 0.9 2.6 47.30% 93.5 20-May 136 40.8 0.9 0.9 2.5 45.50% 95.1 21-May 136 40.8 0.8 0.8 2.4 43.80% 96.7 22-May 136 40.8 0.8 0.8 2.3 42.10% 98.2 23-May 136 40.8 0.7 0.7 2.2 40.40% 99.7 24-May 136 40.8 0.7 0.7 2.1 38.80% 101.2 25-May 136 40.8 0.6 0.6 2 37.20% 102.6 26-May 136 40.8 0.6 0.6 1.9 35.70% 104 27-May 136 40.8 0.5 0.5 1.9 34.20% 105.3 28-May 136 40.8 0.5 0.5 1.8 32.80% 106.6 29-May 136 40.8 0.5 0.5 1.7 31.40% 107.8 30-May 136 40.8 0.4 0.4 1.6 30.10% 109 31-May 136 40.8 0.4 0.4 1.6 28.80% 110.1 1-Jun 136 40.8 0.4 0.4 1.5 27.60% 111.2 2-Jun 136 40.8 0.4 0.4 1.4 26.50% 112.2 3-Jun 136 40.8 0.4 0.4 1.4 25.40% 113.2 4-Jun 136 40.8 0.4 0.4 1.3 24.40% 114.1 5-Jun 136 40.8 0.4 0.4 1.3 23.50% 114.9 25-Jun 136 48.4 0.2 0.2 0.4 13.60% 129.3 26-Jun 136 49.5 0.7 0.7 0.4 8.60% 129 27-Jun 136 50.6 1.2 1.2 0.5 9.60% 128.3 28-Jun 136 51.7 1.7 1.7 0.6 11.10% 127.2 29-Jun 136 52.8 2.1 2.1 0.6 13.10% 125.7 30-Jun 136 53.9 2.5 2.5 0.8 15.50% 124 1-Jul 136 54.9 2.9 2.9 0.9 18.30% 122 2-Jul 136 56 3.2 3.2 1 21.50% 119.9 3-Jul 136 57.1 3.6 3.6 1.2 25.00% 117.5

102 4-Jul 136 58.2 3.9 3.9 1.4 28.80% 115 5-Jul 136 59.3 4.2 4.2 1.5 32.90% 112.3 6-Jul 136 60.4 4.5 4.5 1.7 37.20% 109.6 7-Jul 136 61.5 4.7 4.7 1.9 41.80% 106.8 8-Jul 136 62.6 5 5 2.1 46.60% 103.9 9-Jul 136 63.6 5.2 5.2 2.3 51.50% 101.1 10-Jul 136 64.7 5.4 5.4 2.5 56.70% 98.2 11-Jul 136 65.8 5.6 5.6 2.8 61.90% 95.3 12-Jul 136 66.9 5.8 5.8 3 67.30% 92.5 13-Jul 136 68 6 6 3.2 72.80% 89.7 Total 198.3 197.9 287.6 52.20% 0 0 0

* Yield Reduction: - Estimated yield reduction in growth stage # 1 =9.6% - Estimated yield reduction in growth stage # 2 = 9.9% - Estimated yield reductionin growth stage # 3 = 79% - Estimated yield reduction in growth stage # 4 = 52.5% Estimated total yield reduction = 57.9% * These estimates may be used as guidelines and not as actual figures. * Legend: TAM = Total Available Moisture = (FC%- WP %)* Root Depth [mm]. RAM = Readily Available Moisture = TAM* P [mm]. SMD = Soil Moisture Deficit [mm].

103 8.4 Potential evapotranspiration of the Kobo area as computed by the CropWat software

Climate and ETo (grass) Data Data Source: C:\CROPWATW\CLIMATE\KOBO.PEM Country : Ethiopia Station: Kobo Altitude:15499 meter(s) above M.S.L Latitude:12.04 Deg (North) Longitude: 39.64 Deg. (East) ------Month MaxTemp MiniTemp Humidity Wind Spd SunShine Solar Rad. ETo (deg.C) (deg.C) (%) (Km/d) (Hours) (MJ/m2/d) (mm/d) ------January 26-Jan 12.9 63 148.9 8.4 19.2 3.91 February 28-Jan 12.5 60 155.5 7.3 19 4.44 March 29-Jan 15.1 57 181.4 7.8 21.1 5.1 April 30-Jan 16.8 53 181.4 7.9 21.7 5.53 May 2-Feb 17 48 181.4 8.3 22 5.99 June 3-Feb 18.5 48 190.1 6.8 19.4 5.86 July 31-Jan 18 49 181.4 6.2 18.6 5.34 August 30-Jan 16.6 56 138.2 6.2 18.9 4.69 September 30-Jan 14.7 54 103.7 6.7 19.5 4.48 October 29-Jan 12.8 54 103.7 8.4 21 4.4 November 28-Jan 11.6 53 121 9.8 21.4 4.27 December 26-Jan 10.7 61 129.6 8.9 19.3 3.82 ------Average 30-Jan 14.8 54.7 151.4 7.7 20.1 4.8 ------a = 0.2 5 b = 0.5

104 8.5 Mean annual, annual, mean monthly and monthly rainfall of Kobo from the NMA of Ethiopia for the Kobo Meteorological station

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Average January 0.00 53.90 20.31 19.10 0.00 0.00 40.40 29.90 0.00 0.00 17.80 16.49 February 0.00 32.61 0.00 0.00 0.00 0.00 32.70 0.00 0.00 10.80 11.80 7.99 March 42.50 24.10 33.52 1.51 70.61 0.00 34.80 28.10 34.00 46.70 36.90 32.07 April 57.60 38.90 40.10 76.11 64.42 0.00 66.30 88.10 148.20 56.60 46.60 62.08 May 47.81 11.70 11.70 42.00 35.69 13.00 30.70 3.00 125.60 16.20 11.70 31.74 June 51.52 3.80 2.20 5.21 13.17 2.90 11.00 25.90 2.80 4.00 29.00 13.77 July 110.60 326.11 231.30 230.72 171.98 99.70 140.00 116.20 125.20 81.20 232.80 169.62

105 August 94.40 311.82 315.91 241.40 230.98 296.00 230.98 162.40 190.90 222.90 276.50 234.02 September 37.42 50.93 47.58 48.12 47.58 116.60 47.58 9.20 23.20 75.40 74.10 52.52 October 169.30 6.11 48.80 87.80 48.80 16.01 0.00 53.70 8.70 12.50 38.80 44.59 November 49.30 0.00 24.82 24.12 24.82 0.00 0.00 35.50 64.80 0.00 7.40 20.98 December 0.00 0.00 29.00 83.41 29.00 66.60 42.80 10.20 0.00 16.00 0.00 25.18 Total (mm) 660.45 860 805.24 859.50 737.03 610.81 677.25 562.20 723.40 542.30 783.40 711.05 Total (cm) 66.045 86.00 80.52 85.95 73.70 61.08 67.73 56.22 72.34 54.23 78.34 71.10516

8.6 Crop Coefficients (Kc), stages of development and growing periods of the vegetables in the Kobo valley

Total Growing Kc Values period Development Mid Season Initial stage stage Stage Late season stage Stage Stage Stage Stage Crop Kc days Kc days Kc days Kc days Onion 0.4 30 0.95 30 0.95 45 0.75 25 130 Pepper 0.4 30 0.95 40 0.95 40 0.8 40 135 Tomato 0.4 30 1.05 30 1.05 45 0.65 30 135

106 8.7 Graphs showing the mean monthly values of different meteorological parameters used in the research

107