An inversed Bayesian modeling approach for estimating nitrogen export coefficients and uncertainty assessment in an agricultural watershed in eastern China
An inversed Bayesian modeling approach for estimating nitrogen export coefficients and uncertainty assessment in an agricultural watershed in eastern China
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中国东部农业流域氮输出系数和不确定性评估的反贝叶斯建模方法
DOI：
10.1016/j.agwat.2012.10.015
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发表时间：
2013
影响因子：
6.7
通讯作者：
Chen, Dingjiang
中科院分区：
文献类型：
--
作者：
Lu, Jun;Gong, Dongqin;Shen, Yena;Liu, Mei;Chen, Dingjiang
需要非点源污染的量化信息来制定流域尺度的最大日负荷总量(TMDL)。所有的输出系数模型和一些复杂的机理模型都依赖于污染物输出系数来量化和识别非点源污染。通常，污染物输出系数是通过监测单一土地利用的田间地块或小流域或通过监测和统计分析混合土地利用的流域来估计的。然而，这些方法忽视了河流中污染物的滞留，低估了出口系数，也忽视了流域内出口系数的时空变异性。此外，这些方法没有解决与估计相关的不确定性。本研究将输出系数模型、河流污染物负荷模型和贝叶斯统计方法相结合，从常用的河流监测数据中反推多种土地利用类型的污染物输出系数。通过对中国东部长乐流域6个小流域2004-2009年72个野外观测数据的农田、居民点和林地总氮输出系数的测定，验证了该逆贝叶斯模型的有效性。在估算总氮输出系数时，考虑了流中保留过程。讨论了流域内每种土地利用类型TN输出系数的时间变化(72个野外观测数据)和空间变化(6个流域)，以及与TN输出系数估计相关的不确定性。这种逆贝叶斯建模方法克服了目前广泛使用的污染物输出系数估计方法的缺点，因此可以更有效地支持TMDL程序的开发，特别是在数据有限的情况下。
Quantification information for nonpoint source pollution is required to develop a Total Maximum Daily Load (TMDL) at the watershed scale. All export coefficient models and some complex mechanistic models rely on the pollutant export coefficients to quantify and identify nonpoint source pollution. Typically, pollutant export coefficients are estimated by monitoring field plots or small catchments with a single land-use or by monitoring and statistically analyzing mixed land-use watersheds. However, these approaches underestimate export coefficients by neglecting in-stream pollutant retention and they also neglect spatio-temporal variability for export coefficients within a watershed. In addition, these methods do not address the uncertainty associated with estimations. This study combined the export coefficient model, a stream pollutant load model and a Bayesian statistical method to inversely estimate pollutant export coefficients for multiple land-use types from commonly available stream monitoring data. The efficacy of this inversed Bayesian modeling approach was confirmed by determining total nitrogen (TN) export coefficients for farmland, residential land and woodland for six catchments of the ChangLe River watershed in eastern China covering 72 field observation dates in 2004–2009. In-stream retention processes were considered in estimating TN export coefficients. The temporal (across 72 field observation dates) and spatial (across 6 catchments) variability of TN export coefficients for each land-use type within the watershed are discussed, as well as the uncertainties associated with TN export coefficient estimation. This inversed Bayesian modeling approach overcomes the shortcomings involved in current widely used approaches for estimating pollutant export coefficients; thus it can more efficiently support development of TMDL programs, particularly in circumstance where limited data are available.
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DOI：
10.1016/s0048-9697(00)00820-2
发表时间：
2001-03
期刊：
The Science of the total environment
影响因子：
--
作者：
Linda May;W. House;M. Bowes;Jim McEvoy
通讯作者：
Linda May;W. House;M. Bowes;Jim McEvoy
影响因子：
6.4
作者：
Johnes, P. J.
通讯作者：
Johnes, P. J.
农业水质管理的交互式不精确模糊有界规划方法
影响因子：
6.7
作者：
Lu, H. W.;Nie, X. H.;He, L.;Du, P.
通讯作者：
Du, P.
影响因子：
9.9
作者：
A. Vassiljev;I. Blinova;P. Ennet
通讯作者：
A. Vassiljev;I. Blinova;P. Ennet
影响因子：
5.8
作者：
Dingjiang Chen;Jun Lu;Hailong Wang;Ye-na Shen;Dongqin Gong
通讯作者：
Dingjiang Chen;Jun Lu;Hailong Wang;Ye-na Shen;Dongqin Gong