Search

The USLE is used world-wide to predict soil loss on the field scale from sheet and rill erosion. The slope length (L) factor is derived as its topographical factor. The accuracy of L factor determines the precision of soil loss estimation with USLE. Uncertainties on L factor are caused by DEM resolution and the choice of the processing algorithm. In the present study we made two comparisons to evaluate the effects of DEM horizontal resolution and processing algorithm on the accuracy of the L factor in gently sloped landscapes: one is between the grid cumulating method (GC) and the contributing area method (CA) using D8 flow-routing algorithm, the other is among single (D8, Rho8) and multiple (FD8, FRho8 and DEMON) flow-routing algorithms for processing the contributing area method. In two comparisons, 5 m, 10 m, 25 m, 50 m and 100 m DEM of a 0.88 km2 catchment in the lowland of Northern Germany were applied. The results indicate that L factor calculated with any of the six methods is sensitive to horizontal resolution, which strongly affects the accuracy. With decreasing resolution, correlations of LCA_Rho8 and LCA_D8, LCA_FD8 and LCA_D8, LCA_FD8 and LCA_Rho8 increase while those between DEMON and the other flow-routing algorithms do not change significantly. With decreasing resolution, the difference between LGC_D8 and LCA_D8 is enlarged, while differences between any two flow algorithms using CA did not change significantly. The L factor variation between any two methods is larger on the upslope than the flat valley for the 5 m and 10 m DEM while terrain characteristics are not visible on the 25 m, 50 m and 100 m DEM. The L factor also depends on the computation method. LGC_D8 is approximately half of LCA. It is concluded that DEM horizontal resolution is very important for L factor calculation. The most suitable calculation method is LGC_D8 for gently rolling landscapes. This study can be used for selecting a suitable method and DEM resolution for accurate calculation of L factor and soil loss in gently rolling landscapes.

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-km2 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 r2, 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. Copyright © 2010 John Wiley & Sons, Ltd.

The reliability and the estimation technique of the S factor limit the use of the Universal Soil Loss Equation (USLE) at a regional scale. The accuracy of the S factor principally depends on the digital elevation model (DEM) accuracy and the precision of algorithms. Few studies were conducted on the accuracy of the S factor for a gently rolling landscape at a regional scale. We select a rectangular study site of 1.3 km2 in northern Germany as a case study to explore the effects of algorithm, horizontal resolution and vertical precision of DEM as well as terrain on the S factor. Horizontal resolution includes 1 m, 5 m, 10 m, 25 m, 50 m and 100 m. We use the following eight algorithms: maximum slope gradient, maximum downhill slope gradient, second-order finite difference, third-order finite difference, third-order finite difference weighted by reciprocal of squared distance, third-order finite difference weighted by reciprocal of distance, frame finite difference and simple difference. The results are as follows: (1) the algorithms affect the accuracy of the S factor at any given resolution of DEM, in particular more obvious for the lower DEM resolutions; (2) the accuracy of the S factor decreases as horizontal resolution decreases; (3) the most suitable algorithm is maximum downhill slope gradient for 1 m, and maximum slope gradient for the 5 m to 100 m resolution; (4) vertical precision also affects the accuracy of the S factor. However, vertical precision almost does not change the order of rank of the S factor with eight different algorithms at any given resolution of DEM; (5) the more complex the terrain is, the worse the accuracy of the S factor is represented. Among all the affective factors, horizontal resolution is the most important for the accuracy of the S factor. Selecting the most suitable algorithm is the best way for reducing the errors of the S factor when applying the USLE.

To date, no examples of small- to meso-scale hydrological simulations exist in the southern part of the Western Siberian lowlands, despite intensive agriculture and high vulnerability to climate change. We propose a first simulation approach in which we assess the importance of surface and groundwater processes on hydrological model performance. Therefore, we simulated three catchments, using four different model setups incorporating different landscape characteristics and processes. An objective calibration and comparison framework was applied to assess the different setups which reached very diverse performance: the setups where physically-based surface retention is considered, showed slightly more realistic surface runoff driven peak flows and the setups with a more complex groundwater concept improved the depiction of surface runoff, the recession phase and the contributing baseflow significantly. The best performing, most complex setup was used to assess the prevailing hydrological processes of the lowland with its cold, continental climate in more detail.

Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on river ecosystems.

This study shows a comprehensive simulation of water and sediment fluxes from the catchment to the reach scale. We describe the application of a modelling cascade in a well researched study catchment through connecting stateof- the-art public domain models in ArcGIS. Three models are used consecutively: (1) the hydrological model SWAT to evaluate water balances, sediment input from fields and tile drains as a function of catchment characteristics; (2) the onedimensional hydraulic model HEC-RAS to depict channel erosion and sedimentation along a 9 km channel onedimensionally; and (3) the two-dimensional hydraulic model AdH for simulating detailed substrate changes in a 230 m long reach section over the course of one year. Model performance for the water fluxes is very good, sediment fluxes and substrate changes are simulated with good agreement to observed data. Improvement of tile drain sediment load, simulation of different substrate deposition events and carrying out data sensitivity tests are suggested as future work. Main advantages that can be deduced from this study are separate representation of field, drain and bank erosion processes; shown adaptability to lowland catchments and transferability to other catchments; usability of the model’s output for habitat assessments.

The area where soil loss is occurring within the Yangtze River Basin is the largest in China's seven big river basins. Severe soil loss, in particular in the middle and upper reaches of Yangtze River, has damaged land resources, endangered food security and induced a high sediment input into the river and the three gorges reservoir. Thus, government and local farmers adopted soil and water conservation measures to control soil loss. This paper summarizes the characteristics of soil erosion and all soil and water conservation measures, and illustrates their roles on controlling soil loss and combating land degradation. It is indicated that soil loss in the whole Yangtze River Basin is increasingly severe due to higher rainfall intensities. Soil and water conservation measures, such as living hedgerow on sloping lands are practical. Some others are also effective, but very expensive so that they can not be adopted in the whole Yangtze River Basin. Most importantly, neither are suitable assessment methodologies and criteria applied to evaluate soil and water conservation measures, nor are measures selected to control soil loss and prevent land degradation.

Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species’ response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower-mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present-day gauging data. Species’ abundances were predicted for three periods: (1) baseline (1998–2017), (2) horizon 2050 (2046–2065) and (3) horizon 2090 (2080–2099) based on these empirical relationships and using high-resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low-flow conditions, leading to decreased abundances of species up to −42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower-mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate-change impacts on species abundances and can be applied to any stressor, species, or region.