thumbnail

Entropy and generalized least square methods in assessment of the regional value of streamgages

Journal of Hydrology

By:
, , and
DOI: 10.1016/S0022-1694(03)00244-0

Links

Abstract

The Illinois State Water Survey performed a study to assess the streamgaging network in the State of Illinois. One of the important aspects of the study was to assess the regional value of each station through an assessment of the information transfer among gaging records for low, average, and high flow conditions. This analysis was performed for the main hydrologic regions in the State, and the stations were initially evaluated using a new approach based on entropy analysis. To determine the regional value of each station within a region, several information parameters, including total net information, were defined based on entropy. Stations were ranked based on the total net information. For comparison, the regional value of the same stations was assessed using the generalized least square regression (GLS) method, developed by the US Geological Survey. Finally, a hybrid combination of GLS and entropy was created by including a function of the negative net information as a penalty function in the GLS. The weights of the combined model were determined to maximize the average correlation with the results of GLS and entropy. The entropy and GLS methods were evaluated using the high-flow data from southern Illinois stations. The combined method was compared with the entropy and GLS approaches using the high-flow data from eastern Illinois stations. ?? 2003 Elsevier B.V. All rights reserved.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Entropy and generalized least square methods in assessment of the regional value of streamgages
Series title:
Journal of Hydrology
DOI:
10.1016/S0022-1694(03)00244-0
Volume
283
Issue:
1-4
Year Published:
2003
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Journal of Hydrology
First page:
107
Last page:
121