Agent-based modeling of land use change and simulation of response on nonpoint source pollution for Erhai Lake watershed

Quan Li Xu, Kun Yang*, Jian Li, Yu Lian Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

There is a significant chain-driven effect on water environmental pollution for the Erhai Lake Watershed, which is nonpoint source pollution due to land use and cover change (LUCC) caused by human activities. Therefore, it is necessary to analyze this chain-driven, simulate and predict land use changes as well as response of nonpoint source pollution of the Erhai Lake watershed. An agent-based modeling (ABM) was used to simulate the interaction mechanism between human and land and to predict the results of LUCC; and then, based on the LUCC forecasting and SWAT model, the outputs and spatial-temporal distribution of major nonpoint source pollution loads were computed, such as nitrogen and phosphorus under different land use scenarios. Finally, combined with statistics methods and GIS technologies of spatial analysis and visualization, the processing of validation and sensibility verification of model are discussed, and comprehensive simulated results are analyzed. The results show that: (1) the major interaction between humans and the land over the next ten years will force a persistent reduction in farmland (-19.28%) and a continuous increase in urban land (35.27%); (2) the relative consistency of nitrogen and phosphorus in time and space shows that LUCC has a closer water environmental effect on nitrogen and phosphorus in the study area; (3) the nonpoint source pollution of watershed in the next 10 years will mainly come from the agricultural area, the agricultural planting structure and pattern of production areas should be optimized to reduce nonpoint source pollution contribution rate of agricultural production while taking measures to protect farmland; (4) in the next 10 years the farmland areas will reduce continually and agricultural nonpoint source pollution will appear to reduction trend year by year; meanwhile, as increasing land of construction, a possible rapid increase in urban nonpoint source pollution caused by impervious surfaces needs to attract enough attention.

Original languageEnglish
Pages (from-to)1272-1283
Number of pages12
JournalShuili Xuebao/Journal of Hydraulic Engineering
Volume45
Issue number11
DOIs
Publication statusPublished - 1 Nov 2014
Externally publishedYes

Keywords

  • Agent-based modeling
  • Artificial neural network
  • LUCC
  • Nonpoint source pollution response
  • Watershed water environmental effect

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