Abstract
Allocation and management of agricultural water resources is an emerging concern due to diminishing water supplies and increasing water demands. To achieve economic, social, and environmental goals in a specific irrigation district, decisions should be made subject to the changing water supply and water demand—the two critical random parameters in agricultural water resources management. This paper presents the foundations of a systematic framework for agricultural water resources management, including determination of distribution functions, joint probability of water supply and water demand, optimal allocation of agricultural water resources, and evaluation of various schemes according to agricultural water resources carrying capacity. The maximum entropy method is used to estimate parameters of probability distributions of water supply and demand, which is the basic for the other parts of the framework. The entropy-weight-based TOPSIS method is applied to evaluate agricultural water resources allocation schemes, because it avoids the subjectivity of weight determination and reflects the dynamic changing trend of agricultural water resources carrying capacity. A case study using an irrigation district in Northeast China is used to demonstrate the feasibility and applicability of the framework. It is found that the framework works effectively to balance multiple objectives and provides alternative schemes, considering the combinatorial variety of water supply and water demand, which are conducive to agricultural water resources planning.
Highlights
The conflict between limited water supplies and increased water demands underscores the necessity of efficient and sustainable water resources management
How to evaluate the performance of system objectives and the corresponding water resources allocation strategies under different combination scenarios of water supply and demand is conducive to making judicious decisions
The objective of this study is to develop a framework that integrates the following components: (1) Determining probability distribution functions of water supply and water demand with parameter estimation using the maximum entropy principle; (2) establishing a joint distribution function of water supply and water demand using a copula function and obtaining their joint occurrence probabilities; (3) modeling agricultural water resources allocation using a multi-objective programming technique; and (4) evaluating system performance under different scenarios based on agricultural water resources carrying capacity using entropy-weight-based TOPSIS method
Summary
The conflict between limited water supplies and increased water demands underscores the necessity of efficient and sustainable water resources management. How to evaluate the performance of system objectives and the corresponding water resources allocation strategies under different combination scenarios of water supply and demand is conducive to making judicious decisions. The objective of this study is to develop a framework that integrates the following components: (1) Determining probability distribution functions of water supply and water demand with parameter estimation using the maximum entropy principle; (2) establishing a joint distribution function of water supply and water demand using a copula function and obtaining their joint occurrence probabilities; (3) modeling agricultural water resources allocation using a multi-objective programming technique; and (4) evaluating system performance under different scenarios based on agricultural water resources carrying capacity using entropy-weight-based TOPSIS method.
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