Method for estimating trunk and branch canal leakage in irrigation districts and its application in optimal allocation of water resources

Abstract: The water shortage crisis caused by population increase and climate change threatens China's food security and ecological health. How to improve the utilization efficiency of water resources in agricultural production and promote regional sustainable development are main problems faced by agricultural water managers. In agricultural water distribution process, canal leakage is one of the important water consumption sources. Traditional methods usually use a fixed canal leakage coefficient in planning water resources, which affected the estimation accuracy of canal leakage. Therefore, it is of great significance to accurately estimate the leakage of main and branch canals for guiding the construction of canal engineering and formulating effective optimal allocation scheme of agricultural water resources. In order to improve canal leakage estimation accuracy for large-scale agricultural water resources planning, this study proposed a method for estimating the canal leakage based on analyzing the previous researches and the key elements affecting canal leakage. According to the method proposed in this study, the canal leakage coefficient had the dynamic relationships with water amount of canal diversion. The method proposed by this study was compared with the traditional fixed canal leakage factor method to further verify the impact of different canal leakage estimation methods on the optimal allocation of agricultural water resources. Both methods were applied to the middle reaches of the Heihe River. In the study area, the water managers had to optimally allocate limited water resources among 17 large and medium-sized irrigation districts. A multi-objective stochastic programming model with three objectives (including maximum economic benefit, irrigation water use efficiency, and irrigation water productivity) was established for optimizing limited water resources allocation. Available water resources, crop water demand, and food security were considered as constraints of the optimization model. After collecting the necessary data and solving the optimization model by minimum deviation method, optimization results were obtained. The results showed that the optimization results obtained by the traditional method with fixed leakage factor may underestimate the canal leakage loss in the middle reaches of the Heihe River, leading to more than 10% deviation in estimating the leakage. The underestimation may further affect the field water availability, the expected output, and the estimation of the expected profit, making the optimization goal impossible to achieve. When the available surface water changed, the canal leakage estimation method proposed in this study better reflected the dynamics of canal leakage rates, providing more accurate water quantity information for agricultural water resources planning as well as increasing the effectiveness and feasibility of water resources planning schemes. The method proposed in this study can provide an effective tool for the fine management of agricultural water resources and help the development of agricultural water saving.