Decision Support System for Crop Planning during Droughts
01 Mar 1992-Journal of Irrigation and Drainage Engineering-asce (American Society of Civil Engineers)-Vol. 118, Iss: 2, pp 229-241
TL;DR: In this article, a linear programming model was used to generate optimal cropping patterns from past drought experiences as also from synthetic drought occurrences in a tropical region such as India, where one third of the cropped area is affected by frequent droughts.
Abstract: Demand for water is increasing continually, whereas available supplies are more or less constant. Under these circumstances there is an urgent need to introduce efficient techniques in water resources management for optimal utilization of available water. Water management under drought conditions assumes great importance in a tropical region such as India, where one‐third of the cropped area is affected by frequent droughts. This paper deals with the development and application of an expert system for drought management. A linear programming model was used to generate optimal cropping patterns from past drought experiences as also from synthetic drought occurrences. These policies together with the knowledge of the experts were incorporated in an expert system. Using this, one can identify the degree of drought in the current situation and its similarity to the identified drought events and be able to get the corresponding management strategy.
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TL;DR: In this article, a decision support system (DSS) for optimum cropping and water resources management has been developed considering different soil (saline and non-saline), agriculture (rainfed and irrigated), season (monsoon and winter), and crop types in a coastal river basin in India.
Abstract: A Decision Support System (DSS) for optimum cropping and water resources management has been developed considering different soil (saline and non-saline), agriculture (rainfed and irrigated), season (monsoon and winter), and crop types in a coastal river basin in India. The DSS includes data base subsystem, model base subsystem, knowledge base, and user interface. The data base subsystem includes the meteorological, crop, and water resources data of the study area whereas the model base includes the optimization (Linear Program), and forecasting (groundwater balance and evapotranspiration) models. The knowledge base subsystem was developed to generate optimal cropping and water resources allocation for different soil, agriculture, season, and crop types. Forecasting models and user-interface components were incorporated to make the DSS useful to farmer/user in getting decisions for crop planning during growing seasons in different soils, and agricultures to maximize the economic returns.
1 citations
01 Jan 2003
TL;DR: The Decision Support System developed within the EC INCO-DC project “A DSS for drought mitigation in Mediterranean regions” is presented, to aid decision makers in managing water systems devoted to irrigation use under drought conditions.
Abstract: Successful management of water supply system under drought conditions requires the effective use of advanced tools able to support water managers in the decision process. This paper presents the Decision Support System (DSS) developed within the EC INCO-DC project “A DSS for drought mitigation in Mediterranean regions”. The objective of the DSS is to aid decision makers in managing water systems devoted to irrigation use under drought conditions. This is accomplished through six main computational modules, namely a drought identification model, an irrigation scheduling model, reservoir optimisation and simulation models, a model that allows to derive reservoir operating rules by multiple regressions and/or neural network approach and a multicriteria analysis model, with all modules integrated in an user friendly environment in order to effectively assist in making decision in water supply systems management.
1 citations
01 Jan 2021
TL;DR: In this paper, a simulation and linear programming (LP) model was proposed to find the best possible cropping arrangement in order to maximize the net benefit of the crops in the Kulsi Basin.
Abstract: Irrigation potential of an area can be benefitted if we thrust on maximizing crop production by suitable allocation of limited resources to get optimal productivity. The Kulsi River Basin, located in the Southern bank of the Brahmaputra River, is the area of study. The gross command area and net irrigated area in the basin are 37,908 Ha and 23,882 Ha, respectively. The river basin is deficit of regular irrigation facilities, and only traditional cropping pattern (rain-fed conditions only) has been followed by the cultivators of the area. Hence, to promote the areas potential, the Kulsi Multipurpose Project Authority of Brahmaputra Board has proposed a multipurpose reservoir for the generation of hydropower, flood control, and irrigation. The capacity of the reservoir is 525.64 MCM, plant capacity is 55 MW, tail water level is 63 m, and dead storage of the reservoir is 85.86 MCM. Keeping in mind the benefits to be received by the proposed reservoir, the objective of the paper is mainly emphasized to compute the crop water requirement of the Kulsi Basin and to formulate a simulation and linear programming (LP) model to find the best possible cropping arrangement in order to maximize the net benefit of the crops.
01 Jan 2011
TL;DR: In this paper, a linear programming (LP) model has been developed for optimum water resources allocation and cropping pattern for effective management of land and water resources in the Hirakud Canal Command, a multi-purpose water resources project in India.
Abstract: Conjunctive use of surface and groundwater is pursued in many regions to maximize water availability at the time of its need. Successful regional water management policies will identify the physical and legal constraints on these integrated supplies. To cope up with all the aforesaid constraints, a linear programming (LP) model has been developed for optimum water resources allocation and cropping pattern for effective management of land and water resources in the Hirakud Canal Command, a multi-purpose water resources project in India. The Decision Support System (DSS) incorporates the linear programming model in model base, data base, and knowledge base subsystems along with user interface. The model base subsystem includes the LP, groundwater balance and evapotranspiration models. The data base subsystem includes the meteorological, crop, and water resources data of the study area. The knowledge base subsystem was developed with the knowledge derived from the results of the aforementioned models. Sensitivity analysis of LP model parameters is carried out by varying the parameters that affect the optimal cropping pattern and groundwater allocation. The result indicates that conjunctive use of 87% surface water along with13% ground water appears to be the most viable water allocation level and 20% deviation in existing cropping pattern is selected as the best alternative as it considered socio-economic value and meets the entire food demand of the study area.
References
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TL;DR: A decision support system used to aid in drought decisions is described, which incorporates operator experience and intuition using a rule base developed through interviews with management personnel from the Seattle Water Department.
Abstract: Seattle, Washington, suffered its most extreme drought on record during the summer and fall of 1987. Severe and continuing water use restrictions were required to limit the drought's impact on municipal water supplies, fish populations, and navigation. This paper describes a decision support system used to aid in drought decisions. Its components include an expert system, a linear programming model, database management tools, and computer graphics. The expert system incorporates operator experience and intuition using a rule base developed through interviews with management personnel from the Seattle Water Department. The expert system also integrates the other programming techniques into a single system. A linear programming model determines system yield and optimal operating policies for past hydrologic regimes. Database management and graphics software store and allow the display of over two thousand operating policies to decision‐makers. The system provides user‐friendly support to help decision‐maker...
53 citations
TL;DR: The presentation is illustrated with an example of an engineering expert system for reservoir analysis that is currently in development, and the potential benefits of this technology in the area of reservoir management and operations are presented.
Abstract: Reservoir management and operations are very complex activities in the field of water resources engineering. During the last two decades, a number of systems analysis techniques, particularly optimization and simulation, have been adopted for reservoir planning, design, and operations. Recently, the area of knowledge-based engineering (expert systems) has emerged as a potential technique for incorporationg human expertise and some degree of intelligent judgment into decision-supporting software. This paper presents the potential benefits of this technology in the area of reservoir management and operations. The presentation is illustrated with an example of an engineering expert system for reservoir analysis that is currently in development.
50 citations
TL;DR: An interactive user‐support framework has been developed to automate the calibration of the runoff block and acts as a front end to assist the user in the initial estimation of the parameter values and in building the SWMM input files.
Abstract: EPA'S Storm Water Management Model (SWMM) simulates all aspects of the hydrologic and quality cycles. Using expert system technology, an interactive user‐support framework has been developed to automate the calibration of the runoff block. It acts as a front end to assist the user in the initial estimation of the parameter values and in building the SWMM input files. It interprets the simulation results and suggests some useful adjustments in the value of significant parameters thus reducing the user's time and effort. For the interpretation of simulation results, production rules are employed to help the user decide what parameters need to be adjusted. Some heuristics have been developed to evaluate the new parameter values. The combination of simulation techniques and expert system methodologies facilitates the use of sophisticated models such as SWMM.
49 citations
TL;DR: A methodology in which an expert system shell (INSIGHT 2+) is used to evaluate and display information on drought management planning and a linear programming model is usedto generate optimal operating policies as a function of numerous past drought experiences is presented.
Abstract: Expert systems have been proposed for a wide range of civil engineering applications. They have been applied most successfully in situations governed by simple rules. Many civil engineering decisions, however, must be made in environments in which simple rules are not possible, but rather large amounts of data must be analyzed and evaluated. This paper presents a methodology in which an expert system shell (INSIGHT 2+) is used to evaluate and display information on drought management planning. A linear programming model is used to generate optimal operating policies as a function of numerous past drought experiences. These policies are incorporated into an expert system where the user is required to identify the degree to which the current drought situation is similar to past events. The expert system then aids the user in developing appropriate management policies based on time of year, descriptions of drought intensity, and other system characteristics.
29 citations
01 Mar 1987
TL;DR: In this paper, the basic features of expert systems are outlined and illustrated, and the potential of such an approach as an aid to decision-making in the field of river basin management is explored.
Abstract: The basic features of expert systems are outlined and illustrated, and the potential of such an approach as an aid to decision-making in the field of river basin management is explored. Work undertaken towards the development of an expert system for the operational control of a wastewater treatment plant is described. Further areas of potential application are discussed, including data utilization.
6 citations