Gaining prediction accuracy in land use modeling by integrating modeled hydrologic variables. (May 2019)

• Record Type: Journal Article
• Authors: Wagner, Paul D.; Fohrer, Nicola
• Is Part Of: Environmental modelling & software. Volume 115(2019)
• Page Start: 155
• Page End: 163
• Publication Date: 2019-05
• Subjects: Land use modeling -- Hydrologic modeling -- Land-Use/Cover Change (LUCC) -- CLUE-s -- 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.2019.02.011
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Land use and hydrology are interdependent, so that land use modeling could benefit from hydrologic modeling. This study aims to integrate spatial predictions of hydrologic variables as provided by a hydrologic model into a land use model for a rapidly urbanizing catchment in India. The benefits of this integration are quantified by comparing predictions of a land use model that uses a basic set of explanatory variables to a land use model that additionally uses the modeled hydrologic variables. Our results indicate that the integration of the hydrologic variables improved the model accuracy indicated by overall accuracy (+3 and + 4 percentage points (pp)), class specific user and producer accuracies (up to +8 pp) and figure of merit (+4 and + 5.3 pp) when compared with land use classifications at two points in time. Moreover, the land use patterns show that the integration of the hydrologic variables helped to avoid allocation errors. Highlights: Hydrologic variables modeled with SWAT improved CLUE-s model simulations. A more reasonable allocation was achieved for a future scenario. We recommend to integrate land use models and hydrologic models.