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利用 AnnAGNPS 模型评估中国三峡流域的径流量和泥沙产量。

Assessment of runoff and sediment yields using the AnnAGNPS model in a Three-Gorge watershed of China.

机构信息

Department of Spatial Information Science and Engineering, Xiamen University of Technology, Xiamen 361024, China.

出版信息

Int J Environ Res Public Health. 2012 May;9(5):1887-907. doi: 10.3390/ijerph9051887. Epub 2012 May 16.

DOI:10.3390/ijerph9051887
PMID:22754480
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3386594/
Abstract

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km(2) Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R(2) of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R(2) of 0.93). Additionally, the model was validated using annual average sediment of 2000-2002 (relative error of -0.34) and 2003-2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km(-2)·y(-1)). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km(-2)·y(-1). Sloping areas and low coverage areas are the main source of soil loss in the watershed.

摘要

土壤侵蚀已被公认为全球环境和水质的主要威胁之一,尤其是在中国。为了减轻土壤侵蚀造成的非点源水质问题,已采用最佳管理措施 (BMP) 和/或保护计划。流域模型,如年度农业非点源污染物负荷模型 (AnnAGNPS),已被开发用于帮助评估流域对流域管理措施的响应。该模型已在全球范围内得到应用,并已被证明是一种非常有效的工具,可用于确定严重侵蚀的关键区域,并有助于决策过程,以采用 BMP 和/或保护计划,从而实现成本/效益最大化,并以最有效的方式控制非点源污染。本研究的主要目标是评估流域的土壤侵蚀、泥沙和泥沙输送特征,以便实施有效的保护措施。为了实现本研究的总体目标,收集了中国长江三峡地区 4184 平方公里的大宁河流域的所有必要数据。该模型使用 1998 年至 1999 年的观测月径流量进行校准(纳什-苏特克里夫效率系数为 0.94,R²为 0.94),并使用 2003 年至 2005 年的观测月径流量进行验证(纳什-苏特克里夫效率系数为 0.93,R²为 0.93)。此外,还使用 2000 年至 2002 年(相对误差为-0.34)和 2003 年至 2004 年(相对误差为 0.18)的无锡站年平均泥沙量对模型进行了验证。验证后的模拟结果表明,约有 48%的流域处于中国水利部发布的土壤流失容许值(500 t·km(-2)·y(-1))以下。然而,流域的 8%有超过 5000 t·km(-2)·y(-1)的土壤侵蚀。坡地和低覆盖区是流域水土流失的主要来源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/4ed222f97a08/ijerph-09-01887-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/72c201eaa1b8/ijerph-09-01887-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/c770a660f9a8/ijerph-09-01887-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/d3902f6c9d9f/ijerph-09-01887-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/7435af3b90e2/ijerph-09-01887-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/cd3805316ae5/ijerph-09-01887-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/4ed222f97a08/ijerph-09-01887-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/72c201eaa1b8/ijerph-09-01887-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/c770a660f9a8/ijerph-09-01887-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/d3902f6c9d9f/ijerph-09-01887-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/7435af3b90e2/ijerph-09-01887-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/cd3805316ae5/ijerph-09-01887-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/3386594/4ed222f97a08/ijerph-09-01887-g008.jpg

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