Abstract:SWAT (Soil and Water Assessment Tool) is a conceptual, continuous time model that was developed in the early 1990s to assist water resource managers in assessing the impact of management and climate on water supplies and non-point source pollution in watersheds and large river basins. SWAT is the continuation of over 30 years of model development within the US Department of Agriculture's Agricultural Research Service and was developed to 'scale up' past field-scale models to large river basins. Model components include weather, hydrology, erosion/sedimentation, plant growth, nutrients, pesticides, agricultural management, stream routing and pond/reservoir routing. The latest version, SWAT2000, has several significant enhancements that include: bacteria transport routines; urban routines; Green and Ampt infiltration equation; improved weather generator; ability to read in daily solar radiation, relative humidity, wind speed and potential ET; Muskingum channel routing; and modified dormancy calculations for tropical areas. A complete set of model documentation for equations and algorithms, a user manual describing model inputs and outputs, and an ArcView interface manual are now complete for SWAT2000. The model has been recoded into Fortran 90 with a complete data dictionary, dynamic allocation of arrays and modular subroutines. Current research is focusing on bacteria, riparian zones, pothole topography, forest growth, channel downcutting and widening, and input uncertainty analysis.The model SWAT is meanwhile used in many countries all over the world. Recent developments in European Environmental Policy, such as the adoption of the European Water Framework directive in December 2000, demand tools for integrative river basin management. The model SWAT is applicable for this purpose. It is a flexible model that can be used under a wide range of different environmental conditions, as this special issue will show. The papers compiled here are the result of the first International SWAT Conference held in August 2001 in Rauischholzhausen, Germany. More than 50 participants from 14 countries discussed their modelling experiences with the model development team from the USA. Nineteen selected papers with issues reaching from the newest developments, the evaluation of river basin management, interdisciplinary approaches for river basin management, the impact of land use change, methodical aspects and models derived from SWAT are published in this special issue.

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Model diagnostic analyses help to improve the understanding of hydrological processes and their representation in hydrological models. A detailed temporal analysis detects periods of poor model performance and model components with potential for model improvements, which cannot be found by analysing the whole discharge time series. In this study, we aim to improve the understanding of hydrological processes by investigating the temporal dynamics of parameter sensitivity and of model performance for the Soil and Water Assessment Tool model applied to the Treene lowland catchment in Northern Germany. The temporal analysis shows that the parameter sensitivity varies temporally with high sensitivity for three groundwater parameters (groundwater time delay, baseflow recession constant and aquifer fraction coefficient) and one evaporation parameter (soil evaporation compensation factor). Whereas the soil evaporation compensation factor dominates in baseflow and resaturation periods, groundwater time delay, baseflow recession constant and aquifer fraction coefficient are dominant in the peak and recession phases. The temporal analysis of model performance identifies three clusters with different model performances, which can be related to different phases of the hydrograph. The lowest performance, when comparing six performance measures, is detected for the baseflow cluster. A spatially distributed analysis for six hydrological stations within the Treene catchment shows similar results for all stations. The linkage of periods with poor model performance to the dominant model components in these phases and with the related hydrological processes shows that the groundwater module has the highest potential for improvement. This temporal diagnostic analysis enhances the understanding of the Soil and Water Assessment Tool model and of the dominant hydrological processes in the lowland catchment. Copyright © 2013 John Wiley & Sons, Ltd.

Hydrological models are useful tools to analyze present and future conditions of water quantity and quality. The integrated modelling of water and nutrients needs an adequate representation of the different discharge components. In common with many lowlands, groundwater contribution to the discharge in the North German lowlands is a key factor for a reasonable representation of the water balance, especially in low flow periods. Several studies revealed that the widely used Soil and Water Assessment Tool (SWAT) model performs poorly for low flow periods. This paper deals with the extension of the groundwater module of the SWAT model to enhance low flow representation. The current two-storage concept of SWAT was further developed to a three-storage concept. This was realized due to modification of the groundwater module by splitting the active groundwater storage into a fast and a slow contributing aquifer. The results of this study show that the groundwater module with three storages leads to a good prediction of the overall discharge especially for the recession limbs and the low flow periods. The improved performance is reflected in the signature measures for the mid-segment (percent bias À2.4% vs À15.9%) and the low segment (percent bias 14.8% vs 46.8%) of the flow duration curve. The three-storage groundwater module is more process oriented than the original version due to the introduction of a fast and a slow groundwater flow component. The three-storage version includes a modular approach, because groundwater storages can be activated or deactivated independently for subbasin and hydrological response unit level.Model calibration. Both model setups (two-storage/ three-storage concept) were calibrated independently. The 5603 MULTI-STORAGE CONCEPT TO EMPHASIZE NONLINEAR GROUNDWATER DYNAMICS Additional parameters for the three-storage version are marked with * and were not used in the original two-storage version of the Soil and Water Assessment Tool. Calibrated parameter values are shown for the best model run of each model version 5606 M. PFANNERSTILL, B. GUSE AND N. FOHRER

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% 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.