Modeling hydrologic controls on denitrification: sensitivity to parameter uncertainty and landscape representation

被引:0
|
作者
Christina Tague
机构
[1] University of California,Bren School of Environmental Science and Management
来源
Biogeochemistry | 2009年 / 93卷
关键词
Calibration; Denitrification; Eco-hydrology; RHESSys;
D O I
暂无
中图分类号
学科分类号
摘要
This paper presents a general discussion of the interplay between model structure and hydrologic parameters in the context of denitrification estimation using coupled hydro-ecosystem models at a watershed scale. Given the key role played by hydrology in denitrification models, sensitivity analysis of hydrologic parameters is needed to determine both uncertainty in denitrification estimates and to suggest how measured data, such as streamflow, can be effectively used to reduce this uncertainty. This paper contributes to the broad goal of sensitivity analysis by examining the linkage between landscape tessellation, calibration, and the ability of models to capture hot-spot contributions to watershed scale denitrification across a range of N-loading. For a small mid-Atlantic forested watershed, denitrification estimates using RHESSys (regional hydro-ecologic simulation system) are compared across different strategies for calibration and landscape tessellation. Results demonstrate the utility of several potential approaches to account for hydrologically mediated hot-spots within landscapes.
引用
收藏
页码:79 / 90
页数:11
相关论文
共 50 条
  • [1] Modeling hydrologic controls on denitrification: sensitivity to parameter uncertainty and landscape representation
    Tague, Christina
    BIOGEOCHEMISTRY, 2009, 93 (1-2) : 79 - 90
  • [2] Uncertainty and sensitivity analysis techniques for hydrologic modeling
    Mishra, Srikanta
    JOURNAL OF HYDROINFORMATICS, 2009, 11 (3-4) : 282 - 296
  • [3] A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT
    Abbas, Salam A.
    Bailey, Ryan T.
    White, Jeremy T.
    Arnold, Jeffrey G.
    White, Michael J.
    Cerkasova, Natalja
    Gao, Jungang
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2024, 28 (01) : 21 - 48
  • [4] REDUCING HYDROLOGIC PARAMETER UNCERTAINTY
    Tung, Yeou-Koung
    Mays, Larry W.
    Journal of the Water Resources Planning and Management Division, American Society of Civil Engineers, 1981, 107 (01): : 245 - 262
  • [5] Global sensitivity analysis of parameter uncertainty in landscape evolution models
    Skinner, Christopher J.
    Coulthard, Tom J.
    Schwanghart, Wolfgang
    Van De Wiel, Marco J.
    Hancock, Greg
    GEOSCIENTIFIC MODEL DEVELOPMENT, 2018, 11 (12) : 4873 - 4888
  • [6] Hydrologic Modeling, Uncertainty, and Sensitivity in the Okavango Basin: Insights for Scenario Assessment
    Linhoss, Anna
    Munoz-Carpena, Rafael
    Kiker, Gregory
    Hughes, Denis
    JOURNAL OF HYDROLOGIC ENGINEERING, 2013, 18 (12) : 1767 - 1778
  • [7] Evaluating the parameter sensitivity and impact of hydrologic modeling decisions on flood simulations
    Alexander, Ashlin Ann
    Kumar, D. Nagesh
    Knoben, Wouter J. M.
    Clark, Martyn P.
    ADVANCES IN WATER RESOURCES, 2023, 181
  • [8] Towards reducing the high cost of parameter sensitivity analysis in hydrologic modeling: a regional parameter sensitivity analysis approach
    Larabi, Samah
    Mai, Juliane
    Schnorbus, Markus
    Tolson, Bryan A.
    Zwiers, Francis
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2023, 27 (17) : 3241 - 3263
  • [9] PARAMETRIC UNCERTAINTY IN HYDROLOGIC MODELING
    HAAN, CT
    TRANSACTIONS OF THE ASAE, 1989, 32 (01): : 137 - 146
  • [10] MOESHA: A GENETIC ALGORITHM FOR AUTOMATIC CALIBRATION AND ESTIMATION OF PARAMETER UNCERTAINTY AND SENSITIVITY OF HYDROLOGIC MODELS
    Barnhart, B. L.
    Sawicz, K. A.
    Ficklin, D. L.
    Whittaker, G. W.
    TRANSACTIONS OF THE ASABE, 2017, 60 (04) : 1259 - 1269