Importance of spatially distributed hydrologic variables for land use change modeling. (September 2016)

• Record Type: Journal Article
• Authors: Wagner, Paul D.; Waske, Björn
• Is Part Of: Environmental modelling & software. Volume 83(2016:Sep.)
• Page Start: 245
• Page End: 254
• Publication Date: 2016-09
• Subjects: Land use modeling -- Land-Use/Cover Change (LUCC) -- Logistic regression -- Hydrologic modeling -- India; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.06.005
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Land use changes have a pronounced impact on hydrology. Vice versa, hydrologic changes affect land use patterns. The objective of this study is to test whether hydrologic variables can explain land use change. We employ a set of spatially distributed hydrologic variables and compare it against a set of commonly used explanatory variables for land use change. The explanatory power of these variables is assessed by using a logistic regression approach to model the spatial distribution of land use changes in a meso-scale Indian catchment. When hydrologic variables are additionally included, the accuracies of the logistic regression models improve, which is indicated by a change in the relative operating characteristic statistic (ROC) by up to 11%. This is mostly due to the complementarity of the two datasets that is reflected in the use of 44% commonly used variables and 56% hydrologic variables in the best models for land use change. Graphical abstract: Highlights: Hydrologic patterns can contribute towards explaining land use change. Hydrologic variables complement commonly used explanatory variables for land use change. Modeled hydrologic variables improve land use change modeling.