Abstract
Groundwater is crucial for economic and agricultural development, particularly in arid areas where surface water resources are extremely scarce. The prediction of groundwater levels is essential for understanding groundwater dynamics and providing scientific guidance for the rational utilization of groundwater resources. A back propagation (BP) neural network based on the artificial bee colony (ABC) optimization algorithm was established in this study to accurately predict groundwater levels in the overexploited arid areas of Northwest China. Recharge, exploitation, rainfall, and evaporation were used as input factors, whereas groundwater level was used as the output factor. Results showed that the fitting accuracy, convergence rate, and stabilization of the ABC-BP model are better than those of the particle swarm optimization (PSO-BP), genetic algorithm (GA-BP), and BP models, thereby proving that the ABC-BP model can be a new method for predicting groundwater levels. The ABC-BP model with double hidden layers and a topology structure of 4-7-3-1, which overcame the overfitting problem, was developed to predict groundwater levels in Yaoba Oasis from 2019 to 2030. The prediction results of different mining regimes showed that the groundwater level in the study area will gradually decrease as exploitation quantity increases and then undergo a decline stage given the existing mining condition of 40 million m3/year. According to the simulation results under different scenarios, the most appropriate amount of groundwater exploitation should be maintained at 31 million m3/year to promote the sustainable development of groundwater resources in Yaoba Oasis.
Highlights
The social development and agricultural production of oases in arid regions rely on valuable groundwater resources
The average annual evaporation ranges from 1400 mm in the east to researchers indicate that the total amount of groundwater recharge is maintained at 31 million m3/year, whereas the amount of groundwater exploitation is maintained at approximately 40 million m3/year in the study area [31]
The initial parameters of the artificial bee colony (ABC) algorithm include the numbers of solutions (NS ), bee colonies (NC ), employed bees (Ne ), and onlooker bees (NO ); the maximum cycle number (MCN); and the limit value
Summary
The social development and agricultural production of oases in arid regions rely on valuable groundwater resources. The long-term overexploitation of groundwater has continuously diminished groundwater levels, in arid oases where surface water is extremely scarce and the ecological environment is fragile [1]. A decline in groundwater levels triggers a series of eco-environmental problems and seriously affects local agricultural production and economic development. These problems have been observed in typical oases, such as Yaoba [2], Minqin [3], and Keriya [4]. The accurate prediction of groundwater level is of great significance for the rational utilization of groundwater resources and the sustainable development of the social economy in arid areas
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