SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Spatiotemporal dynamics of nitrogen transport in the Qiandao Lake Basin, a large hilly monsoon basin of southeastern China 
Authors:Cheng, D., H. Li, W. Zhang, S.G. Pueppke, J. Pang and Y. Diao 
Volume (Issue):12(4) 
Article ID:1075 
URL (non-DOI journals): 
Broad Application Category:hydrologic & pollutant 
Primary Application Category:nitrogen cycling/loss and transport 
Secondary Application Category:hydrologic and/or pollutant indices 
Watershed Description:10,369 km^2 Qiandao Lake drainage area, which drains parts of Zhejiang Province (4,341 km^2) and Anhui Province (6,028 km^2) in southeast China 
Calibration Summary: 
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Abstract:The Qiandao Lake Basin (QLB), which occupies low hilly terrain in the monsoon region of southeastern China, is facing serious environmental challenges due to human activities and climate change. Here, we investigated source attribution, transport processes, and the spatiotemporal dynamics of nitrogen (N) movement in the QLB using the Soil and Water Assessment Tool (SWAT), a physical-based model. The goal was to generate key localized vegetative parameters and agronomic variables to serve as credible information on N sources and as a reference for basin management. The simulation indicated that the basin’s annual average total nitrogen (TN) load between 2007 and 2016 was 11,474 tons. Steep slopes with low vegetation coverage significantly influenced the spatiotemporal distribution of N and its transport process. Monthly average TN loads peaked in June due to intensive fertilization of tea plantations and other agricultural areas and then dropped rapidly in July. Subsurface flow is the key transport pathway, with approximately 70% of N loads originating within Anhui Province, which occupies just 58% of the basin area. The TN yields of sub-basins vary considerably and have strong spatial effects on incremental loads entering the basin’ major stream, the Xin’anjiang River. The largest contributor to N loads was domestic sewage (21.8%), followed by livestock production (20.8%), cropland (18.6%), tea land (15.5%), forest land (10.9%), atmospheric deposition (5.6%), orchards (4.6%), industry (1.4%), and other land (0.8%). Our simulation underscores the urgency of increasing the efficiency of the wastewater treatment, conserving slope land, and optimizing agricultural management as components of a comprehensive policy to control N pollution in the basin. 
Keywords:N sources; spatiotemporal patterns of pollution; N transport processes; Qiandao Lake Basin; fertilization