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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #252437

Title: Incorporating landscape depressions and tile drainages of a northern German lowland catchment into a semi-distributed model

item KIESEL, JENS - University Of Kiel
item FOHRER, NICOLA - University Of Kiel
item SCHMALZ, BRITTA - University Of Kiel
item White, Michael

Submitted to: Hydrological Processes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/21/2009
Publication Date: 5/30/2010
Citation: Kiesel, J., Fohrer, N., Schmalz, B., White, M.J. 2010. Incorporating landscape depressions and tile drainages of a northern German lowland catchment into a semi-distributed model. Hydrological Processes. 24(11):1472-1486.

Interpretive Summary: The Soil and Water Assessment Tool (SWAT) is commonly used to evaluate water yield from many different types of landscapes. The model has components to simulate landscape depressions and artificial drainage, but these routines have not been widely used. This research evaluated model performance in 50 km2 watershed dominated by these features. The activation of these routines in SWAT significantly improved model performance, allowing more accurate streamflow predictions in all seasons.

Technical Abstract: Hydrological models need to be adapted to specific hydrological characteristics of the catchment in which they are applied. In the lowland region of northern Germany, tile drains and depressions are prominent features of the landscape though are often neglected in hydrological modelling on the catchment scale. It is shown how these lowland features can be implemented into the Soil and Water Assessment Tool (SWAT). For obtaining the necessary input data, results from a GIS method to derive the location of artificial drainage areas have been used. Another GIS method has been developed to evaluate the spatial distribution and characteristics of landscape depressions. In the study catchment, 31 percent of the watershed area is artificially drained, which heavily influences groundwater processes. Landscape depressions are common over the 50-km**2 study area and have considerable retention potential with an estimated surface area of 582 ha. It was the scope of this work to evaluate the extent by which these two processes affect model performance. Accordingly, three hypotheses have been formulated and tested through a stepwise incorporation of drainage and depression processes into an auto calibrated default setup: (1) integration of artificial drainage alone; (2) integration of depressions alone and (3) integration of both processes combined. The results show a strong improvement of model performance for including artificial drainage while the depression setup only induces a slight improvement. The incorporation of the two landscape characteristics combined led to an overall enhancement of model performance and the strongest improvement in r**2, root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) of all setups. In particular, summer rainfall events with high intensity, winter flows and the hydrograph's recession limbs are depicted more realistically.