4.7 Article

An improved method for interpretation of riverine concentration-discharge relationships indicates long-term shifts in reservoir sediment trapping

期刊

GEOPHYSICAL RESEARCH LETTERS
卷 43, 期 19, 页码 10215-10224

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/2016GL069945

关键词

chemostasis; mobilization; dilution; seasonality; stationarity; uncertainty

资金

  1. Maryland Water Resources Research Center [2015MD329B]
  2. Maryland Sea Grant [NA10OAR4170072, NA14OAR1470090]
  3. National Science Foundation [CBET-1360415]
  4. Directorate For Engineering
  5. Div Of Chem, Bioeng, Env, & Transp Sys [1360345] Funding Source: National Science Foundation
  6. Div Of Chem, Bioeng, Env, & Transp Sys
  7. Directorate For Engineering [1360424, 1360395, 1360415] Funding Source: National Science Foundation

向作者/读者索取更多资源

Derived from river monitoring data, concentration-discharge (C-Q) relationships are powerful indicators of export dynamics. Proper interpretation of such relationships can be made complex, however, if the ln(C)-ln(Q) relationships are nonlinear or if the relationships change over time, season, or discharge. Methods of addressing these issues by binning data can introduce artifacts that obscure underlying interactions among time, discharge, and season. Here we illustrate these issues and propose an alternative method that uses the regression coefficients of the recently developed Weighted Regressions on Time, Discharge, and Season model for examining C-Q relationships in long-term, discretely sampled data for various water-quality constituents, including their uncertainties. The method is applied to sediment concentration data from Susquehanna River at Conowingo Dam, Maryland, to illustrate how the coefficients can be accessed and presented in ways that provide additional insights toward the interpretation of river water-quality data, which reaffirms the recently documented decadal-scale decline in reservoir trapping performance.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据