Dynamic feedback between land-use and hydrology for ecosystem services assessment
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Yalew, S.; Pilz, T.; Schweitzer, C.; Liersch, S.; van der Kwast, J.; Mul, Marloes L.; van Griensven, A.; van der Zaag, P. 2014. Dynamic feedback between land-use and hydrology for ecosystem services assessment. In Ames, D.P., Quinn, N.W.T., Rizzoli, A.E. (Eds.). Proceedings of the 7th International Congress on Environmental Modelling and Software, San Diego, California, USA, 15-19 June 2014. Manno, Switzerland: International Environmental Modelling and Software Society (iEMSs). 8p.
Permanent link to cite or share this item: http://hdl.handle.net/10568/67596
External link to download this item: http://www.iemss.org/sites/iemss2014/papers/iemss2014_submission_255.pdf
Ecosystem services assessment requires an integrated approach, as it is influenced by elements such as climate, hydrology and socio-economics, which in turn influence each other. However, there are few studies that integrate these elements in order to assess ecosystem services. Absence of integrated approach to modelling hydrological and land-use changes, for instance, often oversights the dynamic feedback between the two processes. Dynamic changes in land-use should be fed into hydrological models and vice-versa at each time-step for a more realistic representation. In this study, this approach is demonstrated with a case study of the uThukela catchment, South Africa. There is an increasing pressure on grasslands in the catchment. The grassland supports livestock grazing, one of the main economic and social service for the communal farmers. High livestock population causes degradation of the grasslands, and increasing demand for agricultural lands decreases the extent of the grazing lands. In addition, this is further influenced by changes in climate, and has multiple impacts, such as increased erosion and changing flow regime. The SITE (SImulation of Terrestrial Environments) land-use change model and the SWIM (Soil and Water Integrated Model) hydrological model were coupled at code level to account for these processes. The two models exchange land-use maps (from SITE) and biomass production (from SWIM). SWIM was modified to produce biomass output. Grassland capacity for grazing service is determined through biomass coming from SWIM. Likewise, the simulated land-use change is passed back to the hydrological model to determine effects of land-use change on hydrological components. Preliminary result of the interactions between the two models and its use for estimating grazing capacity show that through the coupled models, sustainable level of grassland grazing locations were easily identifiable.