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- W2808199130 abstract "In recent years, the large-scale development of land and water resources has led to a conflict between water supply and demand. Especially in arid regions, fragile ecosystems and continuous farmland expansion have threatened the ecological and social security of river basins. Therefore, it is urgent to propose scientific and reasonable water resource management models to alleviate this conflict. Based on the principle of “the strictest water resource management measures” for river basin water resources, this study has taken Heshuo County, Xinjiang as the research object, using a full-cost method to determine agricultural water prices for the irrigation district at 0.35 RMB/m3 and 1.4 RMB/m3. With the participation of stakeholders and experts, current water rights trading and management systems were analyzed by a Bayesian network (BN) model. In addition, the impact of water-pricing policy on farmers’ planting behavior was also quantified. The results indicated that an increase in water prices can effectively reduce agricultural water consumption for irrigation, but it would also induce negative externalities involving groundwater (GW) preservation and farmers’ income. A water resource management model mainly directed by water-pricing policy, and supplemented by GW protection and agricultural subsidy policies, could effectively regulate farmers’ water-use behavior, guarantee farmers’ income, and protect GW. This study provides a successful management approach for coordinating the relationship between agricultural water resources and the ecological environment in an arid basin watershed and promoting the efficient use of agricultural water resources in irrigated areas." @default.
- W2808199130 created "2018-06-21" @default.
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- W2808199130 date "2018-06-12" @default.
- W2808199130 modified "2023-09-30" @default.
- W2808199130 title "Evaluation of Agricultural Water Pricing in an Irrigation District Based on a Bayesian Network" @default.
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- W2808199130 doi "https://doi.org/10.3390/w10060768" @default.
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