Crop Coefficients for Microsprinkler-Irrigated, Clean-Cultivated, Mature Citrus in an Arid Climate

Crop evapotranspiration (ETc) was measured over a clean-cultivated, mature navel orange orchard with microsprinkler irrigation located near Lindsay, California. Hourly mean latent heat flux density was determined as the residual of the energy balance equation with measured net radiation, soil heat flux density and sensible heat flux density estimated using the surface renewal method. The ETc was compared with ETo calculated using hourly weather data and the ASCE-EWRI Penman-Monteith equation. Following pruning and topping of the trees in the spring of 2001, the Kco values slowly increased as the canopy developed in the following season. An average Kco = 0.82 was observed. In the following year, the mean summertime value increased to about Kco = 0.95, and in 2003 and 2004, the summertime value averaged near Kco = 1.00, which is somewhat higher than observed for drip irrigated trees in southwestern Arizona and considerably higher than reported in the widely used Food and Agricultural Organization of the United Nations publications that were based on infrequent surface irrigation.     

Integrated Agro-Economic Approach to Deficit Irrigation on Lettuce Crops in Sicily (Italy)

The effect of four different irrigation levels on the marketable yield and economic return of summer-growth lettuce was evaluated during 2005 and 2006 in Eastern Sicily, Italy. The viability of deficit irrigation was evaluated by estimating optimum applied water levels. Actual evapotranspiration (ETa) was estimated by combining pan evaporation measures and the Penman–Monteith approach (ET0-PM). The highest marketable yield of lettuce was recorded for plots receiving 100% ET0-PM. For deficit irrigated plots, reductions in crop production were ascribed to a decrease in lettuce weight. Crop coefficients equal to 1 determined maximum crop production values. Crop water use efficiency was maximum at a 100% ET0-PM level of water applied, corresponding to yield of 0.3?t?ha?1?mm?1. Irrigation water use efficiency reached its maximum at a 40% ET0-PM level, with values of 0.54 and 0.44?t?ha?1?mm?1 during 2005 and 2006, respectively. Water applied and marketable yield of lettuce showed a significant quadratic relationship. Cost functions had a quadratic form during 2005 and a linear form during 2006. In the land-limiting condition the optimal economic levels fit the agronomic ones well. In the water-limiting condition, ranges of water deficit of 15–44% and 74–94% were as profitable as full irrigation, thus contributing to appreciable water savings.     

Measuring On-Farm Irrigation Efficiency with Chloride Tracing under Deficit Irrigation

Water is a limited resource in agricultural production in arid climates. Under such conditions, high irrigation efficiency can be obtained either through implementation of efficient irrigation systems such as drip or sprinkler systems or through the age-old practice of deficit irrigation with gravity systems. The method used to increase irrigation efficiency is often dictated by economic and/or social factors. In either case, the effectiveness of water management at the farm level needs to be evaluated by measuring irrigation efficiency. The objective of this study was to evaluate the irrigation efficiencies for three crops in Southern New Mexico using the chloride technique. The chloride technique is a simple method in which the natural chloride in the irrigation water is used as a tracer to estimate the leaching fraction and the irrigation efficiency at the farm level. Soil samples were collected from various fields in 15 cm increments to a depth of 180 cm at the end of the irrigation season. The samples were analyzed for moisture and chloride content. In addition to the chloride technique, on-farm irrigation efficiencies were measured using applied water, yield, and water production functions. Water production functions and yields were used to estimate total evapotranspiration while flow measurements were used to calculate the amount of applied water. The results showed that high irrigation efficiency can be accomplished using deficit irrigation. Irrigation efficiency values ranged from 83 to 98%. Irrigation efficiencies using the chloride technique were compared with efficiencies estimated from direct flow measurements. The differences between the two methods ranged from 2 to 11.4%. The results showed that even though the chloride technique is subject to sampling errors and simplified theoretical assumptions, it can be used to estimate on-farm irrigation efficiency with considerable accuracy.     

Performance-Based Optimization of Land and Water Resources within Irrigation Schemes. I: Method

Optimum land and water allocation to different crops grown in different regions of an irrigation scheme is a complex process, especially when these irrigation schemes are characterized by different soils and environment and by a large network of canals. At the same time if the water supply in the irrigation schemes is limited, there is a need to allocate water both efficiently and equitably. This paper describes the approach to include both productivity (efficiency) and equity in the allocation process and to develop the allocation plans for optimum productivity and/or maximum equity for such irrigation schemes. The approach presented in this paper considers the different dimensions of equity such as water distribution over the season, water distribution during each irrigation, and benefits generated. It also includes distribution and conveyance losses while allocating water equitably to different allocation units. This paper explains the approach with the help of the area and water allocation model which uses the simulation–optimization technique for optimum allocation of land and water resources to different crops grown in different allocation units of the irrigation scheme.     

Performance-Based Optimization of Land and Water Resources within Irrigation Schemes. II: Application

The area and water allocation model which uses simulation–optimization technique for optimum allocation of land and water resources to different crops cultivated in different allocation units of the irrigation scheme was modified to include both productivity and equity in the process of developing the allocation plans for optimum productivity and/or maximum equity. This paper illustrates the potential of this approach with the help of a case study on Nazare medium irrigation scheme in India. The allocation plans were developed for optimization of different performance parameters (productivity and equity) for different management strategies based on irrigation amount and irrigation interval and cropping distribution strategies of free and fixed cropping. The results indicated that the two performance objectives productivity and equity conflict with each other and in this case, equitable water distribution may be preferred over free water distribution at the cost of a small loss in productivity. Though these results relate to one case study, they show the value of the approach of incorporating productivity and equity in the allocation process with the help of the simulation-optimization model described in the companion paper.     

Allocation of Scarce Water Resources Using Deficit Irrigation in Rotational Systems

On irrigation schemes with rotational irrigation systems in semiarid tropics, the existing rules for water allocation are based on applying a fixed depth of water with every irrigation irrespective of the crops, their growth stages, and soils on which these crops are grown. However, when water resources are scarce, it is necessary to allocate water optimally to different crops grown in the irrigation scheme taking account of different soils in the command area. Allocating water optimally may lead to applying less water to crops than is needed to obtain the maximum yield. In this paper, a three stage approach is proposed for allocating water from a reservoir optimally based on a deficit irrigation approach, using a simulation-optimization model. The allocation results with a deficit irrigation approach are compared for a single crop (wheat) in an irrigation scheme in India, first with full irrigation (irrigation to fill the root zone to field capacity) and second with the existing rule. The full irrigation with a small irrigation interval was equivalent to adequate irrigation (no stress to the crop). It is found that practicing deficit irrigation enables the irrigated area and the total crop production in the irrigation scheme used for the case study to be increased by about 30–45% and 20–40%, respectively, over the existing rule and by 50 and 45%, respectively, over the adequate irrigation. Allocation of resources also varied with soil types.     

OCCASION: New Planning Tool for Optimal Climate Change Adaption Strategies in Irrigation

To sustain productive irrigated agriculture with limited water resources requires a high water use efficiency. This can be achieved by the precise scheduling of deficit irrigation systems taking into account the crops’ response to water stress at different stages of plant growth. Particularly in the light of climate change with rising population numbers and increasing water scarcity, an optimal solution for this task is of paramount importance. We solve the corresponding complex multidimensional and nonlinear optimization problem, i.e., finding the ideal schedule for maximum crop yield with a given water volume by a well tailored approach which offers straightforward application facilities. A global optimization technique allows, together with physically based modeling, for the risk assessment in yield reduction considering different sources of uncertainty (e.g., climate, soil conditions, and management). A new stochastic framework for decision support is developed which aims at optimal climate change adaption strategies in irrigation. It consists of: (1) a weather generator for simulating regional impacts of climate change; (2) a tailor-made evolutionary optimization algorithm for optimal irrigation scheduling with limited water supply; and (3) mechanistic models for rigorously simulating water transport and crop growth. The result, namely, stochastic crop-water production functions, allows to assess the impact of climate variability on potential yield and thus provides a valuable tool for estimating minimum water demands for irrigation in water resources planning and management, assisting furthermore in generating maps of yield uncertainty for specific crops and specific agricultural areas. The tool is successfully applied at an experimental site in southern France. The impacts of predicted climate variability on maize are discussed.     

Operational Monitoring of Daily Crop Water Requirements at the Regional Scale with Time Series of Satellite Data

This work presents a simple, cost-effective, and operational approach to monitor crop water requirements at the regional scale for water management and monitoring purposes. The recommended Food and Agricultural Organization of the United Nations methodology (FAO-56) calculates crop evapotranspiration using crop-specific coefficients (Kc), which vary according to the crop type, health, and phenological stage. This approach, though widely applied for irrigation planning, cannot always match the appropriate crop coefficient with the actual crop phenological stage and health condition, especially in anomalous situations. Previous research demonstrated that crop coefficients and spectral vegetation indexes are correlated. Recent studies have used this relationship with high-resolution satellite data from different sensors to provide information to irrigation advisory services. However, high-resolution data are not feasible for an operational and routine monitoring of water consumption and needs. This paper tests the usefulness of time series of coarse resolution satellite data such as those collected by the moderate-resolution imaging spectroradiometer (MODIS) sensor, to monitor crop coefficients temporal and spatial variability and therefore crop water needs at the regional scale taking advantage of the peculiar characteristics offered by MODIS in terms of high temporal resolution and preprocessed products availability. The outlined methodology takes into account the actual growing stage of the crops and nearly real-time vegetation variations, overcoming some limitations of the traditional FAO approach while preserving the maximum operability. The analysis was carried out in the South Milan agricultural area on data referring to 2003 and 2004. The results agreed with those of other studies and proved to be able to account for the anomalous conditions of the summer in 2003. These results were then compared with those obtained using the traditional FAO crop coefficient curves built with data collected during field campaigns in the same years in rice fields. Constraints, limitations, and possible uses are discussed.     

Estimation of Crop Coefficients Using Satellite Remote Sensing

Crop coefficient (Kc) based estimation of crop evapotranspiration (ETc) is one of the most commonly used methods for irrigation water management. The standardized FAO56 Penman-Monteith approach for estimating ETc from reference evapotranspiration and tabulated generalized Kc values has been widely adopted worldwide to estimate ETc. In this study, we presented a modified approach toward estimating Kc values from remotely sensed data. The surface energy balance algorithm for land model was used for estimating the spatial distribution of ETc for major agronomic crops during the 2005 growing season in southcentral Nebraska. The alfalfa-based reference evapotranspiration (ETr) was calculated using data from multiple automatic weather stations with geostatistical analysis. The Kc values were estimated based on ETc and ETr (i.e., Kc = ETc/ETr). A land use map was used for sampling and profiling the Kc values from the satellite overpass for the major crops grown in southcentral Nebraska. Finally, a regression model was developed to establish the relationship between the normalized difference vegetation index (NDVI) and the ETr-based crop coefficients (Kcr) for corn, soybeans, sorghum, and alfalfa. We found that the coefficients of variation (CV) for NDVI, as well as for Kcr of crops were lower during the midseason as compared to the early and late growing seasons. High CV values during the early growing season can be attributed to differences in planting dates between the fields, whereas high CVs during the late season can be attributed to differences in maturity dates of the crops, variety, and management practices. There was a good relationship between Kcr and NDVI for all the crops except alfalfa. Validation of the developed model for irrigated corn showed very promising results. There was a good correlation between the NDVI-estimated Kcr and the Bowen ratio energy balance system based Kcr with a R2 of 0.74 and a low root mean square difference of 0.21. This approach can be a very useful tool for a large (watershed or regional) scale estimation of evapotranspiration using the crop coefficient and reference evapotranspiration approach.     

Operational Cost Benefits Study of Flexible On-Farm Irrigation Supply Systems

Efficient on-farm use of water and labor for all methods requires a water supply flexible in frequency, rate, and duration and under the control of the irrigator at the point of application. For surface irrigation, the use of large capacity systems for supply and distribution are essential and economical, especially when considering the reduced labor needs, increased irrigation efficiency, and reduced potential high water table problems resulting from having a large, flexible supply associated with a flexible arranged-demand schedule. Automation and stability of flow at the farm turnout, comparable to a domestic system with variable flow delivery conditions, are typically accomplished by use of large capacity semiclosed pipeline systems. A cost comparison of capital investment for various sized, flexible supply systems with resulting farm water and labor costs is presented which shows the great value from the upgraded management made possible.     

Development of GIS-Based Model to Estimate Relative Reductions in Crop Yield due to Salinity and Waterlogging

A model is introduced that utilizes geographic information systems (GIS) to predict relative reductions in crop yield due to salinity and waterlogging at a field-scale by incorporating spatially and temporally variable crop, climatic, and irrigation data to simulate crop yields. This model utilizes soil and water data commonly collected in field-scale studies. The model’s algorithms are integrated into a GIS (ARCVIEW 3.2) as an extension. The result is a model that does not require extraordinary data collection but will provide practical insight into the spatial effects of salinity and waterlogging on crop yields.     

Satellite-Based Energy Balance to Assess Within-Population Variance of Crop Coefficient Curves

Quantifying evapotranspiration (ET) from agricultural fields is important for field water management, water resources planning, and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage. Recent development of satellite remote sensing ET models has enabled us to estimate ET and Kc for large populations of fields. This study evaluated the distribution of Kc over space and time for a large number of individual fields by crop type using ET maps created by a satellite based energy balance (EB) model. Variation of Kc curves was found to be substantially larger than that for the normalized difference vegetation index because of the impacts of random wetting events on Kc, especially during initial and development growth stages. Two traditional Kc curves that are widely used in Idaho for crop management and water rights regulation were compared against the satellite-derived Kc curves. Simple adjustment of the traditional Kc curves by shifting dates for emergence, effective full cover, and termination enabled the traditional curves to better fit Kc curves as determined by the EB model. Applicability of the presented techniques in humid regions having higher chances of cloudy dates was discussed.     

Uniformity Distribution and its Economic Effect on Irrigation Management in Semiarid Zones

The management of water resources in irrigation is a fundamental aspect for their sustainability. For correct management, several tools and systems for decision making are necessary. Among the large number of factors that affect the optimization of water use, we must focus on irrigation uniformity and its economic implications. The following methodology, implemented in a computer model, allows us to carry out an economic analysis of the effects of different Christiansen’s uniformity coefficients (CU), which are useful for system design and calculation and also for irrigation management in order to obtain maximize gross margin. In the zone studied (Hydrogeologic System 08.29, Castilla-La Mancha, Spain) working with a solid set system and with four crops (barley, garlic, maize, and onion), there is an economic interest in designing systems with a high CU (90%) that allows us to obtain a high application efficiency (Ea). Regarding the economic optimization of the irrigation depths, the results show that the optimum gross depths are always lower than the irrigation depths for maximum crop yield. The higher the CU, the lower the depths, while the crop yield increases and the gross margin of the crop improves. These general results present significant differences among crops, according to their water requirements and their economic profitability.     

SDI Dripline Spacing Effect on Corn and Soybean Yield in a Piedmont Clay Soil

A subsurface drip irrigation (SDI) system was installed in the Piedmont of North Carolina in a clay soil in the fall of 2001 to test the effect of dripline spacing on corn and soybean yield. The system was zoned into three sections; each section was cropped to either corn (Zea mays L.), full-season soybean [Glycine max (L.) Merr.], or winter wheat (Triticum aestivum) double cropped to soybean representing any year of a typical crop rotation in the region. Each section had four plots; two SDI plots with dripline spacing at either 1.52 or 2.28 m, an overhead sprinkler irrigated plot, and an unirrigated plot. There was no difference in average corn grain yield for 2002–2005 between dripline spacings or between either dripline spacing and sprinkler. Irrigation water use efficiency (IWUE) was greater for sprinkler irrigated corn than for either SDI treatment and there was no difference in IWUE in soybean. Water typically moved laterally from the driplines 0.38 to 0.50 m. SDI yield and IWUE increased relative to sprinkler yields and water use efficiency in the second and third year of the study. This may suggest that initial fracturing of the heavy clay soil during SDI system installation and subsequent settling of the soil affected water distribution.     

Analysis of Clément’s First Formula for Irrigation Distribution Networks

The aim of this article is to determine with real data to what extent the hypotheses on which Clément’s first formula is based are fulfilled, and to compare the results of applying this formula. To this end the flow demand in the peak period was studied in two distribution networks with different irrigation methods and crops located in the Ebro River basin (northeast Spain). The calibration procedure for this formula proposed by the Centre Technique du Génie Rural des Eaux et des Forets (CTGREF) in 1977 was also analyzed. The result was that most of the hypotheses were not fulfilled. Furthermore, the discharge distributions obtained in the period of study did not correspond to a normal distribution. However, comparing the real accumulated probability curve and that calculated by Clément’s formula, it was found that the differences between the two curves for probabilities greater than 90% (a wide range of application of the formula) were lower than 9.4%. The reason for this result was found. It was shown also, that the CTGREF adjustment procedure did not provide substantial improvement in the estimation of flows because the aim of the fit was to achieve a normal distribution rather than an accumulated distribution function.     

Optimal Crop Planning and Conjunctive Use of Surface Water and Groundwater Resources Using Fuzzy Dynamic Programming

Optimal crop planning and the conjunctive use of surface water and groundwater resources are imperative for the sustainable management of water resources, especially in semiarid regions. In recent years, considerable attention has been given to crop planning and water resources management under uncertainties caused by climate changes that affect irrigation planning in terms of decisions to determine the amounts of water that can/must be allocated. In this paper, optimal crop planning and conjunctive use of surface water and groundwater are developed for the Najafabad Plain, a part of the Zayandehrood River basin in west-central Iran. The fuzzy inference system (FIS) is used to account for the experience and expert judgments of decision makers and farmers to obtain optimal crop planning and cultivation with a reliable water demand based on climate conditions. In the present work, fuzzy regression is used for considering uncertainty and ambiguity in the data used in the simulation model as well as the uncertainties in interactions between surface water and groundwater. The objective function of the optimization model is to minimize shortages in supplying irrigation demands. The results are applicable to a wide range of climate conditions.     

Development and Application of an Integrated Optimization-Simulation Model for Major Irrigation Projects

A nonlinear, constrained multivariable optimization routine is developed for deciding the optimal canal water release and linked to a canal hydraulic module (MIKE 11) and command hydrological module (MIKE SHE). The optimization routine is solved using the sequential quadratic programming (SQP) technique. The hydraulic and the hydrological modules are calibrated and validated independently, and the results are found to be satisfactory. The integrated optimization-simulation model is applied to the Right Bank Main Canal System of Kangsabati Irrigation Project, West Bengal, India. An improved rotational delivery schedule based on long-term field data analysis is also developed. Three simulation scenarios are considered. These are (1) MIKE 11 and MIKE SHE simulation, (3) integrated optimization simulation, and (3) integrated optimization-simulation with improved schedule. Simulations were performed for Kharif (rainy) irrigation periods for 3 different years (1995–1997). The intercomparison of the three simulation scenarios showed that the application of the integrated optimization-simulation model reduced the gap between irrigation water supply and crop water demand and improved the spatial distribution of supply, thereby, minimizing the tail-end deprivation.     

Survey of Irrigation Methods in California in 2001

Reliable information on irrigation methods is important for determining agricultural water demand trends. Therefore, a study was conducted during 2002 to collect information on irrigation methods that were used by growers to irrigate their crops in 2001. The results were compared to earlier surveys to assess trends in cropping and irrigation methods. A one-page questionnaire was developed to collect information on irrigated land by crop and irrigation methods. The questionnaire was mailed to 10,000 growers in California that were randomly selected from a list of 58,000 growers by the California Department of Food and Agriculture, excluding rice, dry-land, and livestock producers. From 1972 to 2002, the area planted has increased from 15 to 31% for orchards and from 6 to 16% for vineyards. The area planted to vegetables has remained relatively static, while that planted to field crops has declined from 67 to 42% of the irrigated area. The land irrigated by low-volume (drip and microsprinkler) irrigation has increased by about 33%, while the amount of land irrigated by surface methods has decreased by about 31%. Sprinkler usage has decreased in orchards and vineyards, but it has increased in vegetable crops.     

Long-Term Operation of Irrigation Dams Considering Variable Demands: Case Study of Zayandeh-rud Reservoir, Iran

Dependency of water demands on the climate variation occurs especially in regions where agricultural demand has a significant share of the total water demands. The variability between demands that are based on annual climate conditions may be larger than the uncertainty associated with other explanatory variables in long-term operation of an irrigation dam. This paper illustrates certain benefits of using variable demands for long-term reservoir operation to help manage water resources system in Zayandeh-rud river basin in Iran. A regional optimal allocation of water among different crops and irrigation units is developed. The optimal allocation model is coupled with a reservoir operating model, which is developed based on the certain hedgings that deals with the available water and the water demands mutually. This coupled model is able to activate restrictions on allocating water to agricultural demands considering variation of inflow to the reservoir, variation of demands, and the economic value of allocating water among different crops and irrigation units. Using this model, long-term operation of Zayandeh-rud dam is evaluated considering different scenarios of inflow to the reservoir as well as agricultural demands. The results indicate that the use of operating rules which consider variable demands could significantly improve the efficiency of a water resources system in long-term operation, as it improves the benefit of Zayandeh-rud reservoir operation in comparison with conventional water supply approaches.     

Analysis of Spatial Scenarios Aiding Decision Making for Regional Irrigation Water-Demand Planning

Regional irrigation water-demand planning is utilized to establish appropriate cropping patterns and estimate irrigation water demand. Although optimization methods have been extensively adopted, uncertainties of meteorological conditions and the complexity of spatial contexts make developing explicit and structured decision making extremely difficult. Rather than generating a single optimal solution, decision makers prefer to generate several possible scenarios and compare results. This study proposes a novel spatial scenario-based planning framework, with a database, model base, and scenario-setting modules, to generate flexible spatial planning scenarios for improving irrigation water-demand planning. Possible demand planning scenarios for irrigation managers are discussed. A prototype of the proposed scenario-based framework is implemented on a geographic information system platform to assist in spatial decision making. Demand planning during a drought period for the Chia-Nan irrigation command area, the largest one in Taiwan, is adopted as a case study to demonstrate the proposed framework for spatial scenario analysis.