Effects of Different Levels of Irrigation Water Salinity and Leaching on Yield and Yield Components of Wheat in an Arid Region

Soil salinity is a major environmental factor limiting the productivity of agricultural lands. To determine the effects of irrigation water salinity and leaching on soil salinity and consequently wheat yield, a field experiment was conducted on a silty clay soil, a typical soil of Rudasht region, Isfahan province, Iran, with three irrigation water salinity levels of 2, 8, and 12?dS/m with/without leaching levels of 4, 19, and 32% with two different irrigation water managements, using factorial design with four replications for each treatment. The results showed that as the irrigation water salinity and consequently soil salinity increases, the yield components such as grain yield, straw yield, 1,000-grain weight, crop height, spike length, and leaf area index decreases significantly. Leaching caused the yield components to increase significantly. An increase in seed protein percentage was noted as the salinity of irrigation water increased. The interaction effects of irrigation management and leaching on yield and yield components was significant. The results of best fit line to relative yield data versus soil ECe showed that the parameters of the above linear relation are site specific, and there is no significant difference between the parameters obtained in this study as compared to the other researchers’ results and the study validates the established relationships between wheat yield and salinity obtained by other researchers. The recycled drainage water could be used in combination with less saline river water as an alternative and less expensive irrigation water to grow salt-tolerant crops such as wheat, to produce profitable yield and to improve the agricultural economy of arid land regions.     

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 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.     

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.     

Predicting Soil Salinity under Various Strategies in Irrigation Systems

This paper presents a model to estimate the soil salinity for different on-farm management strategies under irrigated conditions. It is based on research in the Mani?oba irrigation scheme in northeast Brazil, where upward flow from the shallow water table is the main cause of soil salinization. The model calculates soil water and salt balances for the topsoil. It is calibrated for the topsoil of abandoned plots and for the root zone (0.9?m) of mango trees. Simulating the effect of different management scenarios on soil salinity may help to organize the switch from intensive surface irrigation to more efficient irrigation practices.     

Coupled Surface-Subsurface Flow Model for Improved Basin Irrigation Management

The availability of a process-based coupled surface-subsurface model can lead to improved surface irrigation/fertigation management practices. In this study, a one-dimensional zero-inertia model is coupled with a one-dimensional unsaturated zone water-flow model: HYDRUS-1D. A driver program is used to effect internal iterative coupling of the surface and subsurface flow models. Flow depths calculated using the surface-flow model are used as Dirichlet boundary conditions for the subsurface-flow model, and infiltration amounts calculated by the subsurface model are in turn used in surface-flow mass balance calculations. The model was tested by using field data collected at the University of Arizona, Yuma Mesa, research farm. The maximum mean absolute difference between field-observed and model-predicted advance is 2?min. Applications of the coupled model in improved irrigation management are highlighted. In addition, the significance of the effects of soil moisture redistribution on irrigation water availability to crops and the capability of the coupled model in tracking those changes in soil water status over time are discussed using examples.     

Evaluating Regional Solutions to Salinization and Waterlogging in an Irrigated River Valley

Potential solutions to high soil salinity levels and waterlogging problems are investigated on a regional scale using calibrated finite-difference flow and mass transport modeling for a portion of the Lower Arkansas River Valley in Colorado. A total of 38 alternatives incorporating varying degrees of recharge reduction, canal seepage reduction, subsurface drainage installation, and pumping volume increases are modeled over three irrigation seasons (1999–2001). Six performance indicators are used to evaluate the effectiveness of these alternatives in improving agroecological conditions, compared to existing conditions. Predicted average regional decrease in water table elevation (as great as 1.93 m over the irrigation season) is presented for selected alternatives, as well as the spatial mapping of results. Decrease in soil salinity concentration (with regional and seasonal average reduction as high as 950 mg/L) is also predicted and mapped. Estimated groundwater salinity changes, reduction in total salt loading to the river, increase in average regional crop yield, and changes in net water consumption indicate the potential for marked regional-scale enhancements to the irrigation-stream-aquifer system.     

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.     

Soil Salinity Modeling over Shallow Water Tables. II: Application of LEACHC

Root zone salinity is one of the major factors adversely affecting crop production. A saline shallow water table can contribute significantly to salinity increases in the root zone. A soil salinity model (LEACHC) was used to simulate the effects of various management alternatives and initial conditions on root zone salinity, given a consistently high water table. The impact of water table salinity levels, irrigation management strategies, soil types, and crop types on the accumulation of salts in the root zone and on crop yields was evaluated. There were clear differences in soil salinity accumulations depending upon the depth and salinity of the water table. In general, increasing water table depth reduced average soil profile salinity, as did having lower salinity in the water table. Among the four irrigation strategies that were compared, the 14-day irrigation interval with replenishment of 75% of evapotranspiration (ET) resulted in the lowest soil salinity. With a 4-day interval and 50% ET replenishment, a wheat yield reduction of nearly 40% was predicted after three years of salt accumulation. Soil type and crop type had minimal or no impact on soil salinity accumulation. Under all conditions, soil water average electrical conductivity increased during the 3-year simulation period. This trend continued when the simulation period was extended to 6 years. Under the conditions shown to develop the highest average soil salinity (high water table, low irrigation), an annual presowing irrigation of 125 mm caused a nearly 50% reduction in soil salinity at the end of the 6-year simulation period, as compared with the soil salinity given no presowing irrigation.     

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.     

Effects of Soil Water Salinity on Field Soil Hydraulic Functions

Unsaturated soil hydraulic parameters and functions used in numerical models to simulate water flow and solute transport in the unsaturated zone are generally considered invariant of soil water salinity levels. This study uses 5 years of field soil water salinity levels at three observation sites from the Land Retirement Demonstration Project (LRDP) (20069) located in western Fresno County, California, to test the hypothesis that field unsaturated soil hydraulic properties are also a function of soil water salinity level. The HYDRUS-1D software package for simulating one-dimensional (1D) movement of water, heat, and multiple solutes in variably saturated media, and Parameter Estimation (PEST), a model-independent parameter optimizer, is used to optimize the soil hydraulic parameters and downward bottom flux corresponding to three different average soil salinity levels at each site. The results show that at the same pressure head, soil water content is less with higher soil water salinity as compared with lower soil water salinity. It is thus concluded that the use of soil water salinity invariant soil water hydraulic parameters in numerical modeling can seriously compromise predictions, especially for a variable soil water salinity environment.     

Regional Water Management Modeling for Decision Support in Irrigated Agriculture

Efficient water management is one of the key elements in successful operation of irrigation schemes in arid and semiarid regions. An integrated water management model was developed by combining an unsaturated flow model and a groundwater simulation model. These combined models serve as a tool for decision making in irrigation water management to maintain the water tables at a safe depth. The integrated model was applied on a regional scale in Sirsa Irrigation Circle, covering about a 0.42 million ha area in the northwestern part of Haryana, India, which is faced with serious waterlogging and salinity problems in areas underlain with saline ground irrigated by the canal network. The model was calibrated using the agrohydrologic data for the period 1977–1981 and validated for the period 1982–1990 by keeping the calibrating parameters unchanged. The model was used to study the long-term impact of two water management interventions related to the canal irrigation system—change in pricing system of irrigation water, and water supply according to demand—on the extent of waterlogging risk. Both of these strategies, if implemented, would considerably reduce aquifer recharge and consequently waterlogging risk, compared to the existing practice. The water supply according to demand strategy was slightly more effective in reducing aquifer recharge than the water pricing intervention. The implementation of the proposed water pricing policy would pose no problem in fitting into the existing irrigation system, and thus it would be easier to implement, compared to the water supply according to demand strategy, when taking technical, financial, and social considerations into account.     

Growth and Evapotranspiration of Okra (Abelmoschus Esculentus L.) as Influenced by Salinity of Irrigation Water

The effects of irrigation water salinity on growth, yield, and water consumption of okra was investigated with a pot experiment. For this purpose, five irrigation water salinity levels with electrical conductivities of 1.5, 2.5, 3.5, 5.0, and 7.0?dS/m and tap water as a control treatment were used in a randomized design with five replications. Irrigation practices were realized by considering the weight of each pot. Threshold soil salinity and slope values of the yield response to soil salinity level were determined to be 3.48?dS/m and 4.2%, respectively, for fruit yield, 4.24?dS/m and 7.0% for vegetative dry weight, and 6.0?dS/m and 7.9% for root dry weight. The results revealed that okra was moderately tolerant to salinity. Increasing soil salinity levels caused significant decreases in plant water consumption. Plant water consumption decreased by 2.43% per unit increase in soil salinity. Plant coefficient (Ky) was 1.26. Saline irrigation water treatments altered Cl, Mg, Ca, and Na accumulations in leaves, whereas only Na accumulation in fruits was observed.     

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.     

Monitoring and Modeling Flow and Salt Transport in a Salinity-Threatened Irrigated Valley

Saline high water tables pose a growing threat to the world’s productive irrigated land. Much of this land lies along arid alluvial plains, where solutions must now be developed in the context of changing constraints on river management. Findings are presented from the preliminary phase of a project aimed at developing, through well-conceived data collection and modeling, strategies to sustain irrigated agriculture in the salinity-threatened lower Arkansas River Basin of Colorado. Extensive field data from a representative subregion of the valley reveal the nature and variability of water table depth and salinity, irrigation efficiency and salt loading, and soil salinity. The shallow water table had an average salinity concentration of 3,100 mg/L and an average depth of 2.1 m, and was less than 1.5 m deep under about 25% of the area. Evidence reveals low irrigation efficiencies and high salt loading under each of six canals serving the subregion. Water table depths less than 2.5–3 m contributed to soil salinity levels that exceed threshold tolerances for crops under about 70% of the area. Preliminary steady-state modeling indicates that only limited improvement can be expected from vertical drainage derived from increased pumping, or from decreased recharge brought about by reduced overirrigation. Investments in canal lining, horizontal subsurface drainage, and improved river conditions also will need consideration.     

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.     

Reduced-Runoff Irrigation of Sudan Grass Hay, Imperial Valley, California

Sudan grass is a moderately salt-tolerant annual that is capable of substantial osmotic adjustment under high soil salinity conditions, but little is documented about its actual water use and yield under saline conditions. We estimate water use and evaluate the effects of “reduced-runoff” irrigation on soil salinity associated with Sudan grass hay production during a three-year field study (1996–98) in the Imperial Valley, California. The reduced-runoff irrigation method relies on the application of a simplified volume-balance surface irrigation model, and can result in negligible surface runoff; however, its use may have adverse impacts on soil salinity. Despite an anticipated salinity-induced yield reduction of about 15% associated with an average soil salinity of 6 dS∕m (0–0.6 m depth), use of the reduced-runoff method resulted in satisfactory crop yields, practically no tailwater runoff, and a slight decrease from the initial average profile soil salinity. The average applied water depth and estimated consumptive use (ETc) during the project were 1,019 and 935 mm, respectively, resulting in an average hay yield of 14.4 Mg∕ha versus the 1996–98 county average of 12.6 Mg∕ha. The project average ETc/ET0 and yield∕ETc ratios of 0.73 and 15.5 kg∕ha?mm, respectively, were approximately 15% less than those estimated from water-use-efficiency studies, probably as a result of salinity-induced hay yield reduction.     

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.     

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.     

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.