Keywords
Model coupling, SWAT, CLUE-s, feedbacks
Start Date
17-9-2020 11:40 AM
End Date
17-9-2020 12:00 PM
Abstract
Even though land use and hydrology are closely related, the modelling communities of both disciplines are widely separated. Whereas hydrologic models sometimes use land use model predictions, land use models rarely incorporated modelled hydrologic variables. However, we were able to show that the integration of modelled dynamic land use change in a hydrologic model and of modelled spatially distributed hydrologic variables in a land use model, improved model predictions for a rapidly urbanizing meso-scale catchment in India. By establishing a bi-directional link between the two models on an annual basis, we aim at taking feedback effects between land use and hydrology into account as well as at making more consistent predictions. The coupling of the two models allows for a better representation of spatial dynamics and management decisions during a model run. If, for example, agricultural areas repeatedly suffer from water stress that leads to crop failure, they may be abandoned, particularly, if there is competition for land due to rapid urbanization. By implementing a water stress based abandonment of agricultural areas, we are able to analyse spatial effects of possible future scenarios, e.g. the future use of these areas or a shift of agriculture to more suitable locations. In particular, we are testing the sensitivity of the coupled model with regard to different climate and land use change scenarios as well as with regard to management decisions (e.g. the water stress threshold for abandonment). Our results shed light on the importance of feedback effects between land use and hydrology to accurately and consistently assess impacts of global change on land and water resources.
Bi-directional coupling of the hydrologic model SWAT and the land use model CLUE-s
Even though land use and hydrology are closely related, the modelling communities of both disciplines are widely separated. Whereas hydrologic models sometimes use land use model predictions, land use models rarely incorporated modelled hydrologic variables. However, we were able to show that the integration of modelled dynamic land use change in a hydrologic model and of modelled spatially distributed hydrologic variables in a land use model, improved model predictions for a rapidly urbanizing meso-scale catchment in India. By establishing a bi-directional link between the two models on an annual basis, we aim at taking feedback effects between land use and hydrology into account as well as at making more consistent predictions. The coupling of the two models allows for a better representation of spatial dynamics and management decisions during a model run. If, for example, agricultural areas repeatedly suffer from water stress that leads to crop failure, they may be abandoned, particularly, if there is competition for land due to rapid urbanization. By implementing a water stress based abandonment of agricultural areas, we are able to analyse spatial effects of possible future scenarios, e.g. the future use of these areas or a shift of agriculture to more suitable locations. In particular, we are testing the sensitivity of the coupled model with regard to different climate and land use change scenarios as well as with regard to management decisions (e.g. the water stress threshold for abandonment). Our results shed light on the importance of feedback effects between land use and hydrology to accurately and consistently assess impacts of global change on land and water resources.
Stream and Session
false