Integrated Reservoir-Based Canal Irrigation Model. II: Application

In a companion paper, development of an integrated reservoir-based canal irrigation model (IRCIM) was described. This developed model combines catchment hydrological modeling, reservoir water balance, command hydrological modeling, and a simple canal hydraulic simulation through a rotational irrigation management system, and simulates the whole system as a single unit to ensure equitable distribution of supply to meet the demand if possible, or, to minimize the gap between the supply and demand. In this paper, the developed model was applied to Kangsabati Irrigation Project, West Bengal, India, as a case study. Results showed that IRCIM successfully simulated the operation of the test reservoir after proper calibration and was able to determine better delivery schedules than that actually practiced. The best delivery schedule determined by IRCIM improved the performance of the test irrigation project considerably over the actual delivery schedule for most of the simulation years. Based on these yearly results, a year-independent alternative delivery schedule was also proposed which could be followed mechanically without a manager’s expertise or experience on the particular irrigation project. It was also shown that IRCIM could be used successfully both modulewise or in an integrated way depending on the requirement of the irrigation manager for efficient operation of any reservoir-based canal irrigation systems either for preseason planning of allocation schedules based on hydrologic and hydraulic simulations or for postseason evaluation of the system performance.     

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.     

Root Zone Moisture Routing and Water Demand Calculations in the Context of Integrated Hydrology

An important issue that integrated hydrologic models (IHMs) for river basins can address is the management of water resources in heavily inhabited and cultivated basins. To address this issue, these models need to simulate water demands and root zone flows in a basin. Irrigation scheduling models (ISMs) have been widely used by professionals to compute farm level water demands and root zone flows. Available ISMs are neither suitable for use at basin scale nor can they be easily linked to IHMs. This paper describes a new model that utilizes methods used by ISMs to compute root zone flows and water demands in river basins and can be linked to IHMs. The model was applied to a basin in California, and the simulated water demands were compared with data compiled for the basin. The differences in the results were attributed to differences in input potential evapotranspiration rates. The paper demonstrates that simulated water demands for rice are very sensitive to saturated soil hydraulic conductivity, whereas demands for other crops are sensitive to the pore size distribution index.     

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.     

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.     

Demand Forecasting for Irrigation Water Distribution Systems

One of the main problems in the management of large water supply and distribution systems is the forecasting of daily demand in order to schedule pumping effort and minimize costs. This paper examines methodologies for consumer demand modeling and prediction in a real-time environment for an on-demand irrigation water distribution system. Approaches based on linear multiple regression, univariate time series models (exponential smoothing and ARIMA models), and computational neural networks (CNNs) are developed to predict the total daily volume demand. A set of templates is then applied to the daily demand to produce the diurnal demand profile. The models are established using actual data from an irrigation water distribution system in southern Spain. The input variables used in various CNN and multiple regression models are (1) water demands from previous days; (2) climatic data from previous days (maximum temperature, minimum temperature, average temperature, precipitation, relative humidity, wind speed, and sunshine duration); (3) crop data (surfaces and crop coefficients); and (4) water demands and climatic and crop data. In CNN models, the training method used is a standard back-propagation variation known as extended-delta-bar-delta. Different neural architectures are compared whose learning is carried out by controlling several threshold determination coefficients. The nonlinear CNN model approach is shown to provide a better prediction of daily water demand than linear multiple regression and univariate time series analysis. The best results were obtained when water demand and maximum temperature variables from the two previous days were used as input data.     

Testing and Application of a Transport Model for Runoff Event Inputs for a Water Supply Reservoir

Effective simulation of the fate and transport of runoff event inflows is an important goal of many water quality modeling initiatives. The set-up and testing of a two-dimensional hydrodynamic transport model is documented for a water supply reservoir, Schoharie Reservoir, New York, that uses specific conductance (SC) as a conservative tracer and focuses on fate and transport of runoff event inputs, particularly the plunging of density currents in summer and fall. Model testing is supported by temporally detailed measurements of meteorological, operational, and tributary (temperature and SC) model drivers, and temporally and spatially replete in-reservoir patterns of SC following multiple runoff events, obtained with a combination of robotic monitoring platforms and gridding with rapid profiling instrumentation. Specific conductance is demonstrated to be an ideal tracer because of the distinct tributary signals and subsequent in-reservoir signatures imparted from runoff events and its close coupling to turbidity patterns that are primary water quality concerns for managers. The model is demonstrated to perform well in simulating in-reservoir signatures of SC following multiple runoff events over the spring to fall interval of 2003, including vertical, longitudinal, and temporal patterns, and features of the thermal stratification regime for the same interval. The validated model is applied in a probabilistic manner on the basis of a 61-year record (239 runoff events) of model drivers to provide a robust representation of the transport of runoff event inputs relative to the location of the water supply intake. This application demonstrates the entry of runoff event inflows as plunging density currents in summer and fall is a recurring phenomenon for this reservoir.     

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.     

Volume Compensation Method for Routing Irrigation Canal Demand Changes

This paper examines the problem of routing known water demands through gate-controlled, open-channel irrigation delivery systems. Volume-compensation principles were used to route multiple demands in multiple-pool canal systems. The volume-compensation method schedules each demand change individually under the assumption of a series of steady states and superimposes the individual results. Volume-compensation routing schedules were computed for two of the test cases proposed by the ASCE Task Committee on Canal Automation. Alternative routing schedules were computed with the gate-stroking method, which is an inverse solution of the unsteady-flow equations. Both solutions were tested through unsteady-flow simulation. While not as effective as gate-stroking solutions, volume-compensation solutions performed satisfactorily under ideal flow control conditions. When subjected to realistic operational constraints, specifically constraints on the flow regulation interval, and also to incorrect canal hydraulic roughness information, both methods performed similarly.     

Modeling Evapotranspiration of Two Land Covers Using Integrated Hydrologic Model

Modeling evapotranspiration (ET) distribution in shallow water table environments is of great importance for understanding and reproducing other hydrologic fluxes such as runoff and recharge. Unfortunately, ET distribution can be the most difficult hydrologic process to analyze. The partitioning of ET into upper zone ET, lower zone ET, and groundwater ET is complex because it depends on land cover and subsurface characteristics. One comprehensive distributed parameter model, integrated hydrologic model (IHM), builds on an improved understanding and characterization of ET partitioning between surface storages, vadose zone storage, and saturated groundwater storage. It provides a smooth transition to satisfy ET demand between the vadose zone and the deeper saturated groundwater. In this paper, the IHM was used to analyze ET contribution from different regions of the vadose zone and saturated zone. Rigorous testing was done on two distinct land covers, grass land and forest land, at a study site in West-Central Florida. Sensitivity analysis on the key parameters was investigated and influence of parameters on ET behavior was also discussed. Statistics with the root mean square error and mean bias error for forest total ET were about 1.46 and 0.04 mm/day, respectively, and 1.61 and 1.07 mm/day for grass total ET. Modeling results further proved that ET distributions from the upper and lower soil and water table, while incorporating field-scale variability of soil and land cover properties, can be predicted reasonably well using IHM model.     

Flexible Irrigation Systems: Concept, Design, and Application

This paper presents the need, value, and concept of flexible irrigation water supply systems that can deliver water with flexibility in frequency, rate, and duration under the control of the farmer at the point of application using a limited rate arranged-demand or other schedule. It introduces the needed terminology including “congestion”—how much reserve time and capacity is required to assure water delivery at the frequency and rate desired. An illustrative design procedure for the necessary pipeline and reservoir capacities is illustrated. The techniques discussed emphasize the conversion of the economical steady supply canal flows to flexible on-farm usage through the use of service area reservoirs located between the secondary and tertiary systems, and of semiclosed pipelines and/or level-top canals as automated distribution systems which facilitates the farmers’ need for daytime only variable on-farm deliveries to permit optimization of on-farm water management. This improved management is the ultimate source of increased food production after improved crop, land, and water resources have reached their maximum. The coordinated use of return flow systems is described.     

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

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

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.     

Irrigation Performance using Hydrological and Remote Sensing Modeling

Development of water saving measures requires a thorough understanding of the water balance. Irrigation performance and water accounting are useful tools to assess water use and related productivity. Remote sensing and a hydrological model were applied to an irrigation project in western Turkey to estimate the water balance to support water use and productivity analyses. Remote sensing techniques can produce high spatial coverage of important terms in the water balance for large areas, but at the cost of a rather sparse temporal resolution. Hydrological models can produce all the terms of the water balance at a high temporal, but low spatial resolution. Actual evapotranspiration for an irrigated area in western Turkey was calculated using the surface energy balance algorithm for land (SEBAL) remote sensing land algorithm for two Landsat images. The hydrological model soil-water-atmosphere-plant (SWAP) was setup to simulate the water balance for the same area, assuming a certain distribution in soil properties, planting dates and irrigation practices. A comparison between evapotranspiration determined from SEBAL and from SWAP was made and differences were minimized by adapting the distribution in planting date and irrigation practice. The optimized input data for SWAP were used to simulate all terms of the accumulated water balance for the entire irrigation project, and subsequently used to derive the irrigation performance indicators. The innovative methodology presented is attractive as it diminishes the need of field data and combines the strong points of remotely sensed techniques and hydrological models.     

Physically Based Coupled Model for Simulating 1D Surface–2D Subsurface Flow and Plant Water Uptake in Irrigation Furrows. I: Model Development

Physically based modeling of the interacting water flow during a furrow irrigation season can contribute to both a sustainable irrigation management and an improvement of the furrow irrigation efficiency. This paper presents a process based seasonal furrow irrigation model which describes the interacting one-dimensional surface–two-dimensional subsurface flow and crop growth during a whole growing period. The irrigation advance model presented in a previous study is extended to all hydraulic phases of an irrigation event. It is based on an analytical solution of the zero-inertia surface flow equations and is iteratively coupled with the two-dimensional subsurface flow model HYDRUS-2. A conceptual crop growth model calculates daily evaporation, transpiration and leaf area index. The crop model and HYDRUS-2 are coupled via its common boundaries, namely (1) by the flux across the soil-atmosphere interface; and (2) by the flux from the root zone, which is associated with the plant water uptake. We assume the water stress is the only environmental factor reducing crop development and hence final crop yield. The model performance is evaluated with field experimental data in the companion paper, Part II: Model Test and Evaluation (W?hling and Mailhol 2007).     

Irrigation Scheduling. I: Integer Programming Approach

This paper shows how a sequential irrigation schedule for a tertiary unit can be interpreted as a single machine scheduling problem with earliness, tardiness, and a common deadline. An integer program solution is presented for this irrigation scheduling problem. Two different models are presented to reflect different management options at the tertiary level. The first model allows jobs to be scheduled noncontiguously. In the second model only contiguous jobs are allowed. The second model has three submodels reflecting the various ways in which contiguous jobs can be scheduled over a fixed interval. Earlier work in determining unit costs of earliness/tardiness is reviewed and an alternative improved method is suggested. The models presented in this paper are applied to a tertiary unit with 16 users, both as a single interval and multi-interval irrigation scheduling problem. An alternative integer program is also presented which although computationally more efficient can only be used for single period scheduling problems. The models developed in this paper can be used to solve small scheduling problems and also to calibrate the heuristics as presented in the companion paper.     

Tuning of Robust Distant Downstream PI Controllers for an Irrigation Canal Pool. I: Theory

The paper proposes a new method to tune robust distant downstream proportional integral (PI) controllers for an irrigation canal pool. The method emphasizes the role of gain and phase margins in the controller design, by linking the selection of these robustness indicators to the time domain specifications. This leads to link the frequency domain approach used by automatic control engineers to the time domain approach used by hydraulic engineers. The maximum error corresponding to an unpredicted perturbation is shown to be directly linked to the gain margin and the settling time to the phase margin of the controlled system. The tuning method gives analytical expressions for the controller parameters as function of physical parameters of the canal pool in order to satisfy desired performance requirements. The model is first expressed in terms of dimensionless variables, in order to get generic tuning formulas. The dimensionless PI coefficients are then expressed as functions of time-domain performance requirements. The PI tuning method is evaluated by simulation on a full nonlinear model for a canal pool taken from the ASCE test cases.     

Extended-Period Analysis with a Transient Model

To design and operate a distribution system, one must understand how it will perform when subjected to external hydraulic loads and demands. This paper presents a hybrid model that efficiently tracks the full range of hydraulic conditions, from steady state to waterhammer, in a system over an extended period by coupling a transient simulator with a reservoir routing scheme. The model’s procedure consists of running waterhammer simulations at the start and end of an extended time step to track the rate of filling of a system’s reservoirs and then using this information to update reservoir levels at the end of the time step. Beyond conventional level-of-service and capacity-assessment applications, the hybrid model can help the engineer link system unsteadiness to its associated costs in terms of design and operation. Extended period and worst-case simulations presented in a case study suggest that the hybrid model has a high routing accuracy and can be used effectively to identify the critical state which will produce the most severe transients in a system.     

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.     

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.