scispace - formally typeset
Open AccessJournal ArticleDOI

Evaluating the use of “goodness-of-fit” Measures in hydrologic and hydroclimatic model validation

David R. Legates, +1 more
- 01 Jan 1999 - 
- Vol. 35, Iss: 1, pp 233-241
Reads0
Chats0
TLDR
In this paper, the goodness-of-fit or relative error measures (including the coefficient of efficiency and the index of agreement) that overcome many of the limitations of correlation-based measures are discussed.
Abstract
Correlation and correlation-based measures (e.g., the coefficient of determination) have been widely used to evaluate the “goodness-of-fit” of hydrologic and hydroclimatic models. These measures are oversensitive to extreme values (outliers) and are insensitive to additive and proportional differences between model predictions and observations. Because of these limitations, correlation-based measures can indicate that a model is a good predictor, even when it is not. In this paper, useful alternative goodness-of-fit or relative error measures (including the coefficient of efficiency and the index of agreement) that overcome many of the limitations of correlation-based measures are discussed. Modifications to these statistics to aid in interpretation are presented. It is concluded that correlation and correlation-based measures should not be used to assess the goodness-of-fit of a hydrologic or hydroclimatic model and that additional evaluation measures (such as summary statistics and absolute error measures) should supplement model evaluation tools.

read more

Citations
More filters
Journal ArticleDOI

Modeling evapotranspiration in Arctic coastal plain ecosystems using a modified BIOME-BGC model

TL;DR: In this paper, the authors adapted the BIOME-BGC model to represent the unique conditions in Arctic ecosystems by including a new water storage and evaporation routine that accounts for nonvascular vegetation and the effects of permafrost, adding ground heat flux as an input, and representing ground shading by dead vegetation.
Journal ArticleDOI

Simulating the fate of water in field soil–crop environment

TL;DR: In this article, the root zone water quality model (RZWQM) is used for assessing the fate of water in the soil-crop environment at the field scale under the particular conditions of a Mediterranean region.
Journal ArticleDOI

Time series modeling and prediction of salinity in the Caloosahatchee River Estuary

TL;DR: In this paper, the authors present an approach for the development of an alternative salinity model based on time series analyses of salinity data, which consists of an autoregressive term representing the system persistence and an exogenous term accounting for physical drivers including freshwater inflow, rainfall and tidal water surface elevation that cause salinity to vary.
Journal ArticleDOI

A novel hybrid neural network based on continuity equation and fuzzy pattern-recognition for downstream daily river discharge forecasting

TL;DR: A novel hybrid model which combines continuity equation and fuzzy pattern-recognition concept with artificial neural network (ANN) is presented for downstream river discharge forecasting in a river network and results indicate that the proposed hybrid model delivers better performance, which can effectively improve forecasting capability at the studied station.
Journal ArticleDOI

Evaluation of linear, nonlinear, and hybrid models for predicting PM2.5 based on a GTWR model and MODIS AOD data

TL;DR: In this article, a geographically and temporally weighted regression (GTWR) model was utilized to investigate the spatial and temporal variability relationship between PM2.5 concentrations measured at ground monitoring stations and satellite aerosol optical depth (AOD) data.
References
More filters
Journal ArticleDOI

River flow forecasting through conceptual models part I — A discussion of principles☆

TL;DR: In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.
Journal ArticleDOI

On the validation of models

TL;DR: In this paper, it is suggested that the correlation coefficieness between observed and simulated variates is not as good as observed variates, and that correlation can be improved.
Journal ArticleDOI

A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation

TL;DR: This paper reviewed the nonparametric estimation of statistical error, mainly the bias and standard error of an estimator, or the error rate of a prediction rule, at a relaxed mathematical level, omitting most proofs, regularity conditions and technical details.
Related Papers (5)