Reconciling theory with observations: elements of a diagnostic approach to model evaluation

被引:470
作者
Gupta, Hoshin V. [1 ]
Wagener, Thorsten [2 ]
Liu, Yuqiong [1 ]
机构
[1] Univ Arizona, Dept Hydrol & Water Resources, SAHRA, Tucson, AZ 85721 USA
[2] Penn State Univ, Dept Civil & Environm Engn, University Pk, PA 16802 USA
关键词
model identification; information; evaluation; diagnosis; signatures; uncertainty;
D O I
10.1002/hyp.6989
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
This paper discusses the need for a well-considered approach to reconciling environmental theory with observations that has clear and compelling diagnostic power. This need is well recognized by the scientific community in the context of the 'Predictions in Ungaged Basins' initiative and the National Science Foundation sponsored 'Environmental Observatories' initiative, among others. It is suggested that many current strategies for confronting environmental process models with observational data tire inadequate in the face of the highly complex and high order models becoming central to modern environmental science. and steps are proposed towards the development of a robust and powerful 'Theory of Evaluation'. This paper presents the concept of a diagnostic evaluation approach rooted in information theory and employing the notion of signature indices that measure theoretically relevant system process behaviours. The signature-based approach addresses the issue of degree of system complexity resolvable by a model. Further, it can be placed in the context of Bayesian inference to facilitate uncertainty analysis. and can be readily applied to the problem of process evaluation leading to improved predictions in ungaged basins. Copyright (C) 2008 John Wiley & Sons, Ltd.
引用
收藏
页码:3802 / 3813
页数:12
相关论文
共 65 条
[11]  
Edwards A., 1972, LIKELIHOOD
[13]   Climate, soil, and vegetation controls upon the variability of water balance in temperate and semiarid landscapes: Downward approach to water balance analysis [J].
Farmer, D ;
Sivapalan, M ;
Jothityangkoon, C .
WATER RESOURCES RESEARCH, 2003, 39 (02)
[14]   Model-based diagnosis of hardware designs [J].
Friedrich, G ;
Stumptner, M ;
Wotawa, F .
ARTIFICIAL INTELLIGENCE, 1999, 111 (1-2) :3-39
[15]  
GALL J, 1986, SYSTEMANTICS UNDERGR
[16]   NOVEL-APPROACH TO NONLINEAR NON-GAUSSIAN BAYESIAN STATE ESTIMATION [J].
GORDON, NJ ;
SALMOND, DJ ;
SMITH, AFM .
IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING, 1993, 140 (02) :107-113
[17]  
Grayson R., 2000, SPATIAL PATTERNS CAT
[18]   Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information [J].
Gupta, HV ;
Sorooshian, S ;
Yapo, PO .
WATER RESOURCES RESEARCH, 1998, 34 (04) :751-763
[19]  
GUPTA HV, 2005, ENCY HYDROLOGICAL SC, P1, DOI DOI 10.1002/0470848944.HSA138
[20]  
GUPTA HV, 2007, P INT C WAT ENV EN S, P18