Importance of spatially distributed hydrologic variables for land use change modeling. (September 2016) - Wagner, Paul D.; Waske, Björn
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.