Optimizing groundwater development strategies by genetic algorithm: a case study for balancing the needs for agricultural irrigation and environmental protection in northern China

Gaoqing Plain is a major agriculture center of Shandong Province in northern China. Over the last 30 years, the diversion of Yellow River water for intensive irrigation in Gaoqing Plain has led to elevation of the water table and increased evaporation, and subsequently, a dramatic increase in salt c...

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Veröffentlicht in:Hydrogeology journal Jg. 15; H. 7; S. 1265 - 1278
Hauptverfasser: Wu, Jianfeng, Zheng, Li, Liu, Depeng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Heidelberg Berlin/Heidelberg : Springer-Verlag 01.11.2007
Springer Nature B.V
Schlagworte:
Algorithms
case studies
China
Crop production
Development strategies
Economic development
Engineering drawings
Environment models
Environmental impact
Environmental protection
Environmental quality
Error analysis
Evaporation
Genetic algorithms
Groundwater
groundwater extraction
Groundwater irrigation
Groundwater potential
Groundwater quality
Groundwater recharge/water budget
Groundwater table
irrigated farming
Irrigation
Irrigation water
Optimization models
Over-abstraction
River water
Rivers
Simulation-optimization model
soil degradation
soil salts
Soil water
Studies
Water table
Yellow River
Yellow River
China
China, People's Rep., Shandong Prov
China, People's Rep., Huang He R
ISSN:1431-2174, 1435-0157
Online-Zugang:Volltext
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Zusammenfassung:Gaoqing Plain is a major agriculture center of Shandong Province in northern China. Over the last 30 years, the diversion of Yellow River water for intensive irrigation in Gaoqing Plain has led to elevation of the water table and increased evaporation, and subsequently, a dramatic increase in salt content in soil and rapid degradation of crop productivity. Optimal strategies have been explored, that will balance the need to extract sufficient groundwater for irrigation (to ease the pressure on diverting Yellow River water) with the need to improve the local environment by appropriately lowering the water table. Two simulation-optimization models have been formulated and a genetic algorithm (GA) is applied to search for the optimal groundwater development strategies in Gaoqing Plain, while keeping the adverse environmental impacts in check. Compared with the trial-and-error approach of previous studies, the optimization results demonstrate that using an optimization model coupled with a GA search is both effective and efficient. The optimal solutions identified by the GA will provide Gaoqing Plain with the blueprints for developing sustainable groundwater abstraction plans to support local economic development and improve its environmental quality.
Bibliographie:http://dx.doi.org/10.1007/s10040-007-0200-2
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ISSN:1431-2174
1435-0157
DOI:10.1007/s10040-007-0200-2