SWAT Literature Database for Peer-Reviewed Journal Articles

Title:How to optimize ecosystem services based on a Bayesian model: A case study of Jinghe River Basin 
Authors:Tang C., J. Li, Z. Zhou, L. Zeng, C. Zhang and H. Ran 
Year:2019 
Journal:Sustainability 
Volume (Issue):11(15) 
Pages: 
Article ID:4149 
DOI:10.3390/su11154149 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:hydrologic & pollutant 
Primary Application Category:ecosystem services 
Secondary Application Category:land use change 
Watershed Description:45,421 kmĀ² Jinghe River, a tributary of the Weihe River (and larger Yellow River system) located in north central China. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Based on a Bayesian Network Model (BBN), we established an ecological service network system of the Jinghe River Basin in 2015. Our method consisted of using the distributed eco-hydrological model (Soil and Water Assessment Tool (SWAT) model) to simulate water yield, the Carnegie-Ames-Stanford Approach (CASA) model to estimate Net Primary Productivity (NPP), the Universal Soil Loss Equation (USLE) model to calculate soil erosion and the Crop Productivity (CP) model to simulate agricultural productivity to quantify the four ecosystem services. Based on the network established, the key variable subset and the visual optimal state subset, which we visualized, were analyzed and used to provide spatial optimization suggestions for the four kinds of ecosystem services studied. Our results indicate that water yield, concentrated in the middle and lower reaches of the mountain and river areas, is increasing in the Jinghe River Basin. NPP is continuously increasing and is distributed in the middle and lower reaches of the mountain areas on both sides of the river. Agricultural productivity also shows an upward trend, with areas of high productivity concentrated in the southern downstream mountain areas. On the contrary, the amount of soil erosion is declining, and the high erosion value is also declining, mainly in the upper reaches of the basin (in the Loess Hilly Area). Additionally, we found that a synergistic relationship exists between water yield, NPP and agricultural productivity, which can increase vegetation cover, leading to enhanced agricultural productivity. However, water yield can be reduced as required in order to balance the tradeoff between water yield and soil erosion. Clear regional differences exist in ecosystem services in the river basin. In the future, the two wings of the middle and lower reaches of the river basin will be the main areas of optimization, and it is likely that an optimal ecosystem services pattern can be reached. 
Language:English 
Keywords:Bayesian network; optimization; interaction; spatial modeling; joint probability distribution