Multilevel Approach for Optimizing Land and Water Resources and Irrigation Deliveries for Tertiary Units in Large Irrigation Schemes. II: Application

The resource allocation model, area and water allocation model, incorporates the concept of deficit irrigation through a variable depth irrigation approach, VDI. It uses this to allocate land and water resources optimally to different crops in a heterogeneous irrigation scheme with limited water under rotational water supply. This model was applied to a medium irrigation scheme in India as a case study, to obtain the land and water allocation plans. These optimal allocation plans were compared to those obtained by using the model with the existing approach (full irrigation with a fixed irrigation interval of 21 days in Rabi and 14 days in the summer season). The allocation plans were obtained taking into account the different parameters that were included in the model, such as crops and cropping pattern, soils, irrigation interval, initial reservoir storage volumes, efficiencies, and the outlet and canal capacities. The total net benefits were compared for the two cases of fixed cropping distribution and free cropping distribution and a sensitivity analysis was conducted on other parameters. Summaries of the allocation plans with the VDI approach are presented for the two cases. The total net benefits obtained with the VDI approach introduced in the model were found to be 22% higher than those obtained with the existing approach. The results of this study are thus indicative of the benefits of deficit irrigation and its application within irrigation schemes that have limited water supply.     

Multilevel Approach for Optimizing Land and Water Resources and Irrigation Deliveries for Tertiary Units in Large Irrigation Schemes. I: Method

This paper presents the area and water allocation model (AWAM), which incorporates deficit irrigation for optimizing the use of water for irrigation. This model was developed for surface irrigation schemes in semiarid regions under rotational water supply. It allocates the land area and water optimally to the different crops grown in different types of soils up to the tertiary level or allocation unit. The model has four phases. In the first phase, all the possible irrigation strategies are generated for each crop-soil-region combination. The second phase prepares the irrigation program for each strategy, taking into account the response of the crop to the water deficit. The third phase selects the optimal and efficient irrigation programs. In the fourth phase of the model, irrigation programs are modified by incorporating the conveyance and the distribution efficiencies. These irrigation programs are then used for allocating the land and water resources and preparing the water release schedule for the canal network.     

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.     

Optimal Irrigation Planning under Water Scarcity

In this study optimal irrigation planning strategies are developed for the Nagarjuna Sagar Right Canal command in the semiarid region of South India. The specific objective of the study is to allocate the available land and water resources in a multicrop and multiseason environment and to obtain irrigation weeks requiring irrigation of a fixed depth of 40 mm. The problem is solved in four stages. First, weekly crop water requirements are calculated from the evapotranspiration model by the Penman-Monteith method. Second, seasonal crop water production functions are developed using the single-crop intraseasonal allocation model for each crop in all seasons. Third, allocations of area and water are made at seasonal and interseasonal levels by deterministic dynamic programming, maximizing the net annual benefit from the project. And fourth, once optimal seasonal allocations have been attained, irrigation scheduling is performed by running a single-crop intraseasonal allocation model. Optimal cropping pattern and irrigation water allocations are then made with full and deficit irrigation strategies for various levels of probability of exceedance of the expected annual water available. The results reveal that the optimization approach can significantly improve the annual net benefit with a deficit irrigation strategy under water scarcity.     

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.     

Productivity and Equity of Different Irrigation Schedules under Limited Water Supply

Some irrigation schemes with limited water supply in Central and Southern India follow the area proportionate water distribution based on assumed uniform characteristics of the command area (planned schedule). However in most cases, this planned schedule is overridden by the practice in which users at head draw more than their share of water (actual schedule) due to human factors and technical limitations of the planned schedule. This practice is highly inequitable as users at tail end do not get any water. This paper considers alternative schedules based on full irrigation or deficit irrigation within the framework of area proportionate water distribution in such irrigation schemes and presents the simulation–optimization technique to develop the corresponding land area and water allocation plan for different allocation units by considering the heterogeneity of the irrigation scheme. This paper further demonstrates the utility of proposed alternative schedules by comparing the productivity and equity of these schedules with planned and actual schedules for one irrigation scheme in Central India. The results show that the actual schedule reduces both productivity and equity greatly and the productivity and equity with the alternative schedules are higher than with the planned schedule. The results also show that deficit irrigation has great potential to increase both productivity and equity of irrigation schemes.     

Optimal Irrigation Allocation: A Multilevel Approach

Optimal resources allocation strategies for a canal command in the semiarid region of Indian Punjab are developed in a stochastic regime, considering the competition of the crops in a season, both for irrigation water and area of cultivation. The proposed strategies are divided into two modules using a multilevel approach. The first module determines the optimal seasonal allocation of water as well as optimal cropping pattern. This module is subdivided into two stages. The first stage is a single crop intraseasonal model that employs a stochastic dynamic programming algorithm. The stochastic variables are weekly canal releases and evapotranspiration of the crop that are fitted to different probability distribution functions to determine the expected values at various risk levels. The second stage is a deterministic dynamic programming model that takes into account the multicrop situation. An exponential seasonal crop-water production function is used in this stage. The second module is a single crop stochastic dynamic programming intraseasonal model that takes the output of the first module and gives the optimal weekly irrigation allocations for each crop by considering the stress sensitivity factors of 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.     

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.     

Effect of Preharvest Deficit Irrigation on Second Crop Watermelon Grown in an Extremely Hot Climate

As a second crop, watermelons (Citrullus vulgaris, Crimson sweet) were grown in 2003 and 2004 in the Sanliurfa-Harran Plain in southeastern Turkey to determine the effect of preharvest water stress on fruit yield, quality (i.e., soluble solids contents and fruit size), leaf temperature, and some other physiological parameters. Preharvest drip irrigation treatments included (1) complete irrigation cutoff, dry (D); (2) full irrigation based on replenishment of soil water depleted from 0 to 90?cm soil profile (C); (3) 75% full irrigation (IR1); (4) 50% full irrigation (IR2); and (5) 25% full irrigation (IR3) with 3-day irrigation interval. Treatment plots received the same level of irrigation water until the fruit formation stage, except for Treatment D. Then, different water stress levels were imposed on treatment plots. Irrigation water applied to the five respective treatments were 636, 511, 395, 245, and 120?mm in 2003 and 648, 516, 403, 252, and 127?mm in 2004. Results indicated that fruit yield was significantly lowered by reduced water rates. The seasonal average yield response factor (ky) for both years was 1.0, but it was 0.97 for 2003 and 0.98 for 2004. The highest marketable fruit yield, obtained from treatment C, was 32.4?Mg?ha?1 in 2003 and 37.1?Mg?ha?1 in 2004. D, IR2, and IR3 treatments reduced most measured parameters, except for soluble solids contents (SSC). Both the fruit size and SSC were significantly affected by late-season irrigation management; individual fruit weights were significantly reduced, whereas SSC increased in the IR2 and IR3 treatments compared to the control values. The writers’ results clearly indicated that reduced preharvest irrigation was detrimental. Water use efficiency (WUE) was significantly affected by irrigation treatments. Even a 25% reduction in the irrigation amount caused a 15% reduction in marketable yield. This indicates that deficit irrigation in the ripening stage significantly increased water use efficiency. The study demonstrated that a moderate deficit irrigation, which is replenishment up to 50% of soil water depleted in the root zone, can be successfully used to improve WUE under semiarid climatic conditions.     

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.     

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.     

Optimal Allocation of Irrigation Water Supplies in Real Time

This paper presents an evaluation of the potential of an optimization approach in improving real-time irrigation water management in systems with complex distribution networks. The optimization approach is based on quadratic programming. The operational objective is to maximize crop production through appropriate water allocation, while maintaining equity between different irrigation schemes and units within schemes. The approach has been evaluated through application to the irrigation system in the Lower Ayung River Basin in Bali, Indonesia. A simulation model of this irrigation system was available, and it has been possible to measure the effectiveness of the optimization approach by comparing the results of simulation runs incorporating optimization with the results of runs representing existing water allocation practice. The results indicate that the optimization approach does have potential and can significantly improve crop production at the basin scale. This paper presents a preliminary assessment of the potential of the approach and describes the development of a more sophisticated optimization approach based on real-time evaluations of crop water requirements. Considerations for practical implementation are discussed.     

Optimal Reservoir Operation for Irrigation of Multiple Crops Using Genetic Algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils, and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.     

LEPA and Spray Irrigation for Grain Crops

Two low energy precision application (LEPA) sprinkler methods (double-ended socks and bubblers) and two spray sprinkler methods (low-elevation spray application and overhead spray) were used to irrigate corn, grain sorghum, and winter wheat in the Southern High Plains. For full or 100% irrigation, sufficient 25-mm applications were applied to maintain soil water at non-yield-limiting levels determined in earlier research with the three crops. Deficit-irrigated treatments were irrigated on the same days as the control treatment in 25 or 33% increments of the fully irrigated amount. Irrigation water was applied to or above alternate furrows with a three-span lateral move irrigation system. Corn and sorghum were grown on beds and furrows with all furrows diked, and wheat was flat-planted without basin tillage. Grain yields increased significantly with irrigation amount (p ≤ 0.05) for all crops during all years. With full irrigation, grain yields varied little among the sprinkler methods, and yields averaged 13.5, 8.9, and 4.6 Mg∕ha for corn, sorghum, and wheat, respectively. With the 25 and 50% deficit irrigation amounts, sorghum yields with LEPA irrigation were 1.1 Mg∕ha larger than with the two spray methods. For 75% irrigation of sorghum and for deficit irrigation of the other two crops, there was little yield difference between the LEPA and spray sprinkler methods. Grain yields were significantly correlated with seasonal water use with regression coefficients of 2.89, 1.84, and 0.915 kg∕m3 for corn, sorghum, and wheat, respectively.     

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.     

Farmers’ Adaptation and Regional Land-Use Changes in Irrigation Systems under Fluctuating Water Supply, South India

In closing river basins where nearly all available water is committed to existing uses, downstream irrigation projects are expected to experience water shortages more frequently. Understanding the scope for resilience and adaptation of large surface irrigation systems is vital to the development of management strategies designed to mitigate the impact of river basin closure on food production and the livelihoods of farmers. A multilevel analysis (farm-level surveys and regional assessment through remote-sensing techniques and statistics) of the dynamics of irrigation and land use in the Nagarjuna Sagar project (South India) in times of changing water availability (2000–2006) highlights that during low-flow years, there is large-scale adoption of rainfed or supplementary irrigated crops that have lower land productivity but higher water productivity, and that a large fraction of land is fallowed. Cropping pattern changes during the drought reveal short-term coping strategies rather than long-term evolutions: after the shock, farmers reverted to their usual cropping patterns during years with adequate canal supplies. For the sequence of water supply fluctuations observed from 2000 to 2006, the Nagarjuna Sagar irrigation system shows a high level of sensitivity to short-term perturbations, but long-term resilience if flows recover. Management strategies accounting for local-level adaptability will be necessary to mitigate the impacts of low-flow years but there is scope for improvement of the performance of the system.     

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.     

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.     

Prediction Accuracy for Projectwide Evapotranspiration Using Crop Coefficients and Reference Evapotranspiration

The Imperial Irrigation District is a large irrigation project in the western United States having a unique hydrogeologic structure such that only small amounts of deep percolation leave the project directly as subsurface flows. This structure is conducive to relatively accurate application of a surface water balance to the district, enabling the determination of crop evapotranspiration (ETc) as a residual of inflows and outflows. The ability to calculate ETc from discharge measurements provides the opportunity to assess the accuracy and consistency of an independently applied crop coefficient—reference evapotranspiration (Kc?ET0) procedure integrated over the project. The accuracy of the annual crop evapotranspiration via water balance estimates was ±6% at the 95% confidence level. Calculations using Kc and ET0 were based on the FAO-56 dual crop coefficient approach and included separate calculation of evaporation from precipitation and irrigation events. Grass reference ET0 was computed using the CIMIS Penman equation and ETc was computed for over 30 crop types. On average, Kc-based ET computations exceeded ETc determined by water balance (referred to as ETc?WB) by 8% on an annual basis over a 7 year period. The 8% overprediction was concluded to stem primarily from use of Kc that represents potential and ideal growing conditions, whereas crops in the study area were not always in full pristine condition due to various water and agronomic stresses. A 6% reduction to calculated Kc-based ET was applied to all crops, and a further 2% reduction was applied to lower value crops to bring the project-wide ET predicted by Kc-based ET into agreement with ETc?WB. The standard error of estimate (SEE) for annual ETc for the entire project based on Kc, following the reduction adjustment, was 3.4% of total annual ETc, which is considered to be quite good. The SEE for the average monthly ETc was 15% of average monthly ETc. A sensitivity analysis of the computational procedure for Kc showed that relaxation from using the FAO-56 dual Kc method to the more simple mean (i.e., single) Kc curve and relaxation of specificity of planting and harvest dates did not substantially increase the projectwide prediction error The use of the mean Kc curves, where effects of evaporation from wet soil are included as general averages, predicted 5% lower than the dual method for monthly estimates and 8% lower on an annual basis, so that no adjustment was required to match annual ET derived from water balance. About one half of the reduction in estimates when applying the single (or mean) Kc method rather than the dual Kc method was caused by the lack of accounting for evaporation from special irrigations during the off season (i.e., in between crops).