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.     

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.     

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.     

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.     

Modeling Reservoir Irrigation in Uncertain Hydrologic Environment

In a detailed model for reservoir irrigation taking into account the soil moisture dynamics in the root zone of the crops, the data set for reservoir inflow and rainfall in the command will usually be of sufficient length to enable their variations to be described by probability distributions. However, the potential evapotranspiration of the crop itself depends on the characteristics of the crop and the reference evaporation, the quantification of both being associated with a high degree of uncertainty. The main purpose of this paper is to propose a mathematical programming model to determine the annual relative yield of crops and to determine its reliability, for a single reservoir meant for irrigation of multiple crops, incorporating variations in inflow, rainfall in the command area, and crop consumptive use. The inflow to the reservoir and rainfall in the reservoir command area are treated as random variables, whereas potential evapotranspiration is modeled as a fuzzy set. The model’s application is illustrated with reference to an existing single-reservoir system in Southern India.     

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.     

Optimal Reservoir Operations for Irrigation Using a Three Spatial Scales Approach

A three-step computational model for the optimal weekly interseasonal operation of a multipurpose (irrigation, environmental, domestic/industrial) reservoir is developed. Environmental and domestic/industrial uses are evaluated and considered as priority uses that induce deficit irrigation conditions. The spatiotemporal variability of the irrigation water demand at the basin level is accounted for. The objective is the maximization of the interseasonal agricultural profitability at the basin level. The optimal allocation process solves the competition for water on different temporal scales (weekly, seasonal, and interseasonal) and on different spatial scales (in basins among irrigation areas and in irrigation areas among crops). The three steps are simulation model operating at the soil-crop unit level, optimization model operating at the multicrop area level, and optimization model operating at the basin level. This consists of parametric dynamic programming for which an analytical objective function was defined and an analytical solution was determined. This solution replaces the iterative procedure, so that it is possible to account for all the variables without running into the “curse of dimensionality” problem. The environmental use allocation is expressed as a function of a parameter, the variations of which give different environmental protection levels. The validation case study emphasizes the importance of considering the spatiotemporal variability of the demand. This is consistent with the “computationally tractable” model algorithm.     

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.     

Integrated Reservoir-Based Canal Irrigation Model. I: Description

The success of irrigation system operation and planning depends on the quantification of supply and demand and equitable distribution of supply to meet the demand if possible, or to minimize the gap between the supply and demand. Most of the irrigation literature mainly focuses on the demand and distribution aspects only. In addition, irrigation projects that receive water from a reservoir can be challenging to manage as annual fluctuations in runoff from the reservoir’s catchment can have considerable impact on the irrigation management strategy. This study focuses on the development of an integrated reservoir-based canal irrigation model (IRCIM) that includes catchment hydrologic modeling, reservoir water balance, command hydrologic modeling, and a rotational canal irrigation management system. The front end of the IRCIM is developed in Visual Basic 6.0, whereas the back-end coding is done in C language. The graphical user interface is the most important feature of the model, as it provides a better interaction between the model and its user. The IRCIM has a modular structure that consists of three modules, viz., catchment module, reservoir module, and crop water demand module. The catchment module predicts daily runoff from the catchment that inflows to the reservoir. Depending on the data availability, this module is provided with the flexibility of choosing between the Soil Conservation Service’s curve number method combined with the Muskingum routing technique, and an artificial neural network technique using the Levenberg–Marquardt algorithm. The reservoir module is based on conservation of mass approach, and results in daily reservoir storage. The crop water demand module is comprised of water-balance models for both paddy and field crops. The irrigation management system serves as the program flow controller for the model and runs the required module when needed. For postseason evaluation of the irrigation system, performance indicators such as adequacy, efficiency, equity, and dependability are used. In a companion paper, the model is applied for Kangsabati Irrigation Project, West Bengal, India.     

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.     

Long-Term Effects of Irrigation Water Conservation on Crop Production and Environment in Semiarid Areas

As water is becoming a scarcer commodity, savings in the irrigation sector could enhance water development in areas currently not being irrigated, and arrest the rapid environmental degradation due to waterlogging in arid areas. The agro-hydrological model SWAP is used to investigate possible water reductions for wheat and cotton crops under shallow water table conditions prevailing in the Fourth Drainage Project in Punjab, Pakistan. The simulations are performed for both drained and undrained conditions considering three different irrigation water qualities. The overall objective is to save good-quality irrigation water. The results indicate that when good-quality canal water is available, a reduced application to wheat (195 mm) and cotton (260 mm) will keep the soil healthier under both drained and undrained conditions. For poor-quality irrigation waters (mixed canal and tubewell or tubewell alone), this water conservation strategy will be insufficient. Therefore, more water (325 mm for wheat and 325 mm for cotton) should be applied to keep crop production and soil salinity within desirable limits. However, this will only be applicable to the areas where proper subsurface drainage systems are present. For undrained areas, this strategy will not be feasible due to rising water tables; other options like growing more salt-tolerant crops should be considered. Drainage cannot solve salinity buildup problems under all circumstances because relatively dry monsoons provide insufficient leaching water, and salts added by tubewell irrigation can only be evacuated from the soil profile if the drainage system is very intense. Reduced irrigation inputs is a proper short-term solution, although wheat production tends to decline in all areas without drainage, even when irrigated with canal water. Large-scale drainage investments associated with adjusted irrigation planning seem unavoidable in the long run.     

Knowledge-Based Model for Supplementary Irrigation Assessment in Agricultural Watersheds

In this paper a knowledge-based model for supplementary irrigation assessment in rainfed agricultural watersheds is presented. The supplementary irrigation assessment problem is divided into different components and is modeled separately. Geographic Information System (GIS) is used to aggregate spatially varying attributes required for the modeling. A graphical user interface is developed in a GIS platform by using the ERDAS macro language tools. The model was applied to two case study areas in India: a subwatershed of Gandheshwari area (West Bengal), and Harsul watershed (Maharashtra). In the Gandheshwari subwatershed, the water availability was found to be inadequate to meet the irrigation requirement and hence the model identified the areas that can be irrigated with different outsource water supply. On the other hand, surface runoff generated in the Harsul watershed was found to be sufficient to meet the supplementary irrigation requirement, thereby showing the feasibility for supplementary irrigation in the area. Using the model, the effect of any rainfall condition can be simulated and hence appropriate measures can be taken in advance to reduce the risk of crop failure.     

Maximum Area That Can Be Economically Irrigated by Solar Photovoltaic Pumping System

This work describes the cost efficiency of a solar photovoltaic (PV) pumping system for irrigation system in relation to the most effective traditional power system, a diesel engine. A mathematical model for optimal sizing of a solar PV pumping system is used to estimate the maximum area that can be economically irrigated by the solar PV pumping system. The proposed methodology and model have been applied in two different areas in Croatia Osijek and Split, as paradigms of continental and coastal Croatia as well as European Union. The obtained results show that maximum areas which can be economically irrigated in the Osijek region are greater than in the Split region. Such result indicates that PV irrigation systems can be equally economically applied in relatively cooler climates and with less solar radiation, as well as in a warmer Mediterranean climate.     

Reservoir Release Policy for Large Irrigation System

This paper describes the formulation of a model for optimized crop and water planning decisions in an irrigation system in Thailand. It facilitates consultation in which representatives of stakeholders, officials, farmers, and researchers can contribute to the decision making. Linear programming and the analytical hierarchy process are the principal modeling tools to optimize the collective system objectives: productivity, equity, and security. The results of the model are compared with observed events of one dry season. The optimized policy generated by the model suggested a diversified cropping pattern, which would decrease the water requirement by 16.4% and enhance net benefit per cubic meter of water used by 39.9%. The erratic water availability from the reservoir and the operational procedures inside the system are reviewed, analyzing historical data in terms of reliability, resiliency, and vulnerability. These include lack of proper assessment of available water, effective farmer organization, and prompt data processing and communication. Furthermore, for the effective implementation of an optimized irrigation policy, a water release pattern of the storage reservoir has been suggested.     

Estimation of the water requirement for beef production in the United States

A static model of developed water use for U.S. cattle production was constructed on a spreadsheet. Water use included that consumed directly by various classes of animals, water applied for irrigation of crops that are consumed by the cattle, water applied to irrigated pasture, and water used to process animals at marketing. Government statistics were consulted for numbers of cattle and crop production. The most recent statistics available for numbers of cattle and crops in individual states were used. On January 1, 1992, a total of 33.8 million beef cows and 5.7 million replacement heifers were in U.S. breeding herds, 12 million animals were on feed, and approximately 28 million animals were fed annually. Thus, the U.S. beef cattle herd produced 6.9 billion kg of boneless beef. Beef cattle directly consumed 760 billion L of water per year. Feedlot cattle were fed various grain and roughage sources corresponding to the regions in which they were fed. Feeds produced in a state were preferentially used by cattle in that state with that state's efficiency; any additional feedstuffs required used water at the national efficiency. Irrigation of crop feedstuffs for beef cattle required 12,991 billion L of water. Irrigated pasture for beef cattle production required an additional 11,243 billion L of water. Carcass processing required 79 billion L of water. The model estimates 3,682 L of developed water per kilogram of boneless meat for beef cattle production in the United States. The model was most sensitive to the dressing percentage and percentage of boneless yield in carcasses of feedlot cattle (62 and 66.7, respectively).(ABSTRACT TRUNCATED AT 250 WORDS)     

Uptake of 137Cs in vegetable crops grown on a contaminated lakebed

Mean concentrations and plant:soil concentration ratios of 137Cs were determined for six vegetable crops grown on an exposed, contaminated lakebed of a former reactor cooling reservoir in South Carolina. Each crop species was grown with or without potassium fertilizer. Selected crops were also irrigated with either reservoir water or groundwater. Subsamples of crops were prepared for human consumption before analysis to determine the extent of any loss. Plant:soil concentration ratios (dry basis) ranged from 0.22 to 6.82, values which were substantially higher than those used in generic assessment models. While there was no statistically significant effect of irrigation source or culinary preparation, the effect of potassium-fertilizer was dramatic. In many cases, concentrations of 137Cs in those plants receiving potassium were less than half of the concentrations in plants that did not receive potassium. Significant differences among species and plant parts for 137Cs concentrations were observed. Dose/risk calculations for the ingestion of these vegetables by a hypothetical 30-y resident indicates the possibility of a lifetime fatal cancer risk well-above the U.S. Environmental Protection Agency's regulatory guideline of 10(-4).     

Coupled Reservoir Operation-Irrigation Scheduling by Dynamic Programming

This paper develops a forward dynamic programming (FDP) model to solve the problem of reservoir operation and irrigation scheduling. The typical scenario for application of the model is composed of a system of two reservoirs in parallel supplying water to as many as three irrigation districts. Two models are coupled. The interseasonal model defines seasonal deliveries from the reservoir system. The intraseasonal model uses area and water allocations generated from the interseasonal model to produce an irrigation scheduling for the individual farms in one of the irrigation districts in the reservoir system. Crop evapotranspiration, reservoir evaporation, and inflows are forecasted. Upon availability of the current values, the forecast is updated and the model runs to generate a more precise irrigation schedule. This feature permits the application of the model for real-time operation of the irrigation district. At the end of the season, the intraseasonal model is updated. The FDP model is applied to a real watershed with a 2 year planning horizon for the interseasonal and 6 months for the intraseasonal model.     

A Paradigm Shift in Irrigation Management

In coming decades, irrigated agriculture will be called upon to produce up to two thirds of the increased food supply needed by an expanding world population. But the increasing dependence on irrigation will coincide with accelerating competition for water and rising concern about the environmental effects of irrigation. These converging pressures will force irrigators to reconsider what is perhaps the most fundamental precept of conventional irrigation practice; that crop water demands should be satisfied in order to achieve maximum crop yields per unit of land. Ultimately, irrigated agriculture will need to adopt a new management paradigm based on an economic objective—the maximization of net benefits—rather than the biological objective of maximizing yields. Irrigation to meet crop water demand is a relatively simple and clearly defined problem with a singular objective. Irrigation to maximize benefits is a substantially more complex and challenging problem. Identifying optimum irrigation strategies will require more detailed models of the relationships between applied water, crop production, and irrigation efficiency. Economic factors, particularly the opportunity costs of water, will need to be explicitly incorporated into the analysis. In some cases the analysis may involve multi-objective optimization. The increased complexity of the analysis will necessitate the use of more sophisticated analytical tools. This paper examines the underlying logic of this alternative approach to irrigation management, explores the factors that will compel its adoption, and examines its economic and environmental implications. Two important concerns, sustainability and risk, are discussed in some depth. Operational practices for implementing the new approach are contrasted with current, conventional irrigation practices. Some of the analytical tools that might be employed in the search for optimum irrigation strategies are reviewed. Finally, the limited and largely intuitive efforts that have already been made to implement this new paradigm are discussed.     

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.     

Model for the Simulation of Water Flows in Irrigation Districts. I: Description

Significant improvements in the profitability and sustainability of irrigated areas can be obtained by the application of new technologies. In this work, a model for the simulation of water flows in irrigation districts is presented. The model is based on the combination of a number of modules specialized on surface irrigation, open channel distribution networks, crop growth modeling, irrigation decision making, and hydrosaline balances. These modules are executed in parallel, and are connected by a series of variables. The surface irrigation module is based on a numerical hydrodynamic routine solving the Saint Venant equations, including the heterogeneity of soil physical properties. The simulation of water conveyance is performed on the basis of the capacity of the elements of the conveyance network. Crop growth is simulated using a scheme derived from the well-known model CropWat. The irrigation decision making module satisfies water orders considering water stress, yield sensitivity to stress, multiple water sources, and the network capacity. Finally, the hydrosaline module is based on a steady state approach, and provides estimations of the volume and salinity of the irrigation return flows for the whole irrigation season. The application of the model to district irrigation management and modernization studies may be limited by the volume of data required. In a companion paper, the model is calibrated, validated, and applied to a real irrigation district.