首页|Identifying the impact of crop distribution on groundwater resources carrying capacity in groundwater-depended agricultural regions
Identifying the impact of crop distribution on groundwater resources carrying capacity in groundwater-depended agricultural regions
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NSTL
Elsevier
? 2022 Elsevier B.V.Groundwater resources carrying capacity (GRCC) is defined as the capacity of groundwater resources for supporting social-economic development, which has been incredibly reduced in groundwater-depended agricultural regions due to unreasonable use of groundwater resources. Identifying the key factors influencing GRCC and providing the optimal strategy is critical for sustainable use of groundwater resources. The present study used the improved GRCC index, regression functions, and random forest to identify the key factors influencing the GRCC in a groundwater over-exploited area [Zhangjiakou, Hebei province, China (ZJK)]. And the particle swarm optimization and optimal water allocation model were used to select the best crop distribution scenarios for improving the GRCC. The results showed that IncMSE index (random forest) for each influencing factors ranging from ? 3.4–8.9, indicating that crop distribution is the most important factor affecting the GRCC. Therefore, changing the crop distribution is the key factor to improve the GRCC in ZJK. The results of optimizing crop distribution scenarios showed the total water use for optimized crop distribution O26 (potato and cabbage planting area were 36,885 and 362,936 ha) was 713,701,500 m3, which was reduced by 14% compared to base scenarios in 2016. Furthermore, the GRCC index (D) has decreased by 53%～83%, which means the groundwater resources would be sustainable by using this crop distribution with irrigation quotas are 900 and 1875 m3/ha respectively. The results can provide decision-making references for sustainable use of groundwater resources in groundwater over-exploitation regions.
Agriculture water useCrop distributionGroundwater resources managementRandom forest
Yang H.、Cheng B.、Gao F.、Sun S.、Yao N.、Luan X.、Wang K.
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School of Land Science and Space Planning Digital Territory Experiment Center Heibei GEO University
College of Emergency Technology and Management North China Institute of Science & Technology
Key Laboratory for Agricultural Soil and Water Engineering in Arid Area of Ministry of Education Northwest A&F University
NSTL
Elsevier
