Discussions: Irrigation Land Management Model
01 Jan 1995-Journal of Irrigation and Drainage Engineering-asce (American Society of Civil Engineers)-Vol. 121, Iss: 1, pp 122-127
About: This article is published in Journal of Irrigation and Drainage Engineering-asce.The article was published on 1995-01-01. It has received 1 citations till now. The article focuses on the topics: Irrigation management & Irrigation statistics.
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TL;DR: In this article, a seasonal ARIMA model with one autoregressive and one moving average process and with a seasonality of 52 weeks was found to be an appropriate stochastic model for forecasting weekly reference crop ET.
Abstract: Evapotranspiration (ET) is an important process in the hydrological cycle and needs to be accurately quantified for proper irrigation scheduling and optimal water resources systems operation. The time variant characteristics of ET necessitate the need for forecasting ET. In this paper, two techniques, namely a seasonal ARIMA model and Winter's exponential smoothing model, have been investigated for their applicability for forecasting weekly reference crop ET. A seasonal ARIMA model with one autoregressive and one moving average process and with a seasonality of 52 weeks was found to be an appropriate stochastic model. The ARIMA and Winter's models were compared with a simple ET model to assess their performance in forecasting. The forecast errors produced by these models were very small and the models would be promisingly of great use in real-time irrigation management.
31 citations
References
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TL;DR: In this paper, a procedure is recommended for estimating crop water requirements that only requires the measurement of maximum and minimum temperatures, although calibrated for the Senegal River Basin using climatic data from four representative locations appears to be generally applicable for other areas without calibration.
Abstract: The Senegal River is a major natural resource in West Africa where the principal economic resources are agricultural. A proposed irrigation project will provide a significant increase in crop production and will exert a large influence on the economics of Senegal, Mauritania, and Mali. The magnitude of benefits from the project will depend upon the allocation, scheduling and managing of that portion of the water to be used for irrigating agricultural crops. A procedure is recommended for estimating crop water requirements that only requires the measurement of maximum and minimum temperatures. This procedure although calibrated for the Senegal River Basin using climatic data from four representative locations appears to be generally applicable for other areas without calibration. The importance of rainfall in supplying part of crop water requirements is described. Mean, actual dependable and effective precipitation values are compared for one location. Block farming or the planting of a single crop to mana...
420 citations
TL;DR: In this paper, a model based on stochastic dynamic programing is formulated to maximize net benefits from a crop facing uncertain, correlated evapotranspiration demands, and weekly irrigation decisions are made after observing current soil moisture and available irrigation water, as well as potential evapOTranspiration in the past week.
Abstract: Scheduling and determining of irrigation water applications are important considerations given limited water resources and increasing concern about agricultural productivity. Past literature has repeatedly been concerned with the influence of the variability of actual evapotranspiration on crop irrigation needs. This work investigates the above issue. A model, based on stochastic dynamic programing, is formulated to maximize net benefits from a crop facing uncertain, correlated evapotranspiration demands. Weekly irrigation decisions are made after observing current soil moisture and available irrigation water, as well as potential evapotranspiration in the past week. The model is similar to the traditional reservoir control algorithms popular in the surface water literature. A case study example indicates that although the model formulation is useful and feasible, the effect of uncertain evapotranspiration on irrigation performance measures is apparently minimal. This work should be of interest to researchers of agricultural management and to those studying the applications and use of operation research techniques in water resources. Computer programs utilized in this paper are available from the authors.
67 citations
TL;DR: In this paper, a simulation model is developed which accounts for the major processes governing shallow saline water table behavior in salinity-affected irrigated regions, which can be used to develop economically optimal irrigation and drainage strategies for long-term regional management.
Abstract: A simulation model is developed which accounts for the major processes governing shallow saline water table behavior in salinity‐affected irrigated regions. Designed for feasibility stage project planning, the model may be used to develop economically optimal irrigation and drainage strategies for long‐term regional management. Incorporation of uncertainty due to regional‐scale physical parameter variability places the optimal management problem in a stochastic setting. An application to a system representative of conditions in the Western San Joaquin Valley of California reveals the merits of the model in providing decision makers with a set of alternative strategies for possible implementation in a regional project. This approach, as shown in the example application, allows system responses to be interpreted with notions of stability and risk.
44 citations
TL;DR: In this article, a stochastic quasigradient (SQG) approximation method was used to obtain near-optimal solutions in about 15% of the CPU time required to obtain such solutions using response surface methodology.
Abstract: Parameter uncertainty in modeling complex hydrologic systems has resulted in development of stochastically based water management models. Optimal solutions to such models, particularly those having parameters with large variance, may be difficult, if at all possible, to obtain, due to intensive computational requirements. This paper discusses application of a stochastic quasigradient (SQG) approximation method to a management model. The model describes the effects of regional irrigation and drainage system planning on shallow saline groundwater behavior and net economic returns to farmers. Due to the complexity of the model, Monte Carlo simulation techniques were used. Despite model complexity and large parameter variance originating from spatial variability in soil hydraulic properties, the SQG method obtained near‐optimal solutions in about 15% of the CPU time required to obtain such solutions using response surface methodology.
22 citations
TL;DR: In this article, the first reference crop evapotranspiration was estimated by predicting first reference crops evapOTranspiration, and the FAO-Penman with Penman (1948) wind function for clipped grass was ranked first among the methods selected to predict grass ET.
Abstract: Rapid irrigation development in the Sudan has stretched to the limit its share in the Nile waters. Significant savings on irrigation water can be made by improved water management. Accurate estimation of crops evapotranspiration, ET, is a prerequisite. ET was estimated by predicting first reference crop evapotranspiration. Grass was selected as the reference crop. FAO‐Penman with Penman (1948) wind function for clipped grass was ranked first among the methods selected to predict grass ET. Using the crop coefficients of Doorenbos and Kassam (1979), ET for cotton, groundnuts and wheat grown in the Gezira scheme were then predicted. Predicted and measured ET remained well within ±15%. For air temperature higher and lower than 28.3° C, it was found that warm‐season grass ET was equal to 1.0 and 0.635 ET of cool‐season grass, respectively. Because of this temperature effect, care must be taken not to use these two grass varieties indiscriminately to estimate crop ET.
11 citations