Deriving the Main Cultivation Direction from Open Remote Sensing Data to Determine the Support Practice Measure Contouring

The P-factor for support practice of the Universal Soil Loss Equation (USLE) accounts for soil conservation measures and leads to a significant reduction in the modelled soil loss. However, in the practical application, the P-factor is the most neglected factor overall due to high effort for determining or lack of input data. This study provides a new method for automatic derivation of the main cultivation direction from seed rows and tramlines on agricultural land parcels using the Fast Line Detector (FLD) of the Open Computer Vision (OpenCV) package and open remote sensing data from Google Earth™. Comparison of the cultivation direction with the mean aspect for each land parcel allows the determination of a site-specific P-factor for the soil conservation measure contouring. After calibration of the FLD parameters, the success rate in a first application in the low mountain range Fischbach catchment, Germany, was 77.7% for 278 agricultural land parcels. The main reasons for unsuccessful detection were problems with headland detection, existing soil erosion, and widely varying albedo within the plots as well as individual outliers. The use of a corrected mask and enhanced parameterization offers promising improvements for a higher success rate of the FLD

A Systematic Analysis of the Interaction between Rain-on-Grid-Simulations and Spatial Resolution in 2D Hydrodynamic Modeling

A large number of 2D models were originally developed as 1D models for the calculation of water levels along the main course of a river. Due to their development as 2D distributed models, the majority have added precipitation as a source term. The models can now be used as quasi-2D hydrodynamic rainfall–runoff models (‘HDRRM’). Within the direct rainfall method (‘DRM’), there is an approach, referred to as ‘rain-on-grid’, in which input precipitation is applied to the entire catchment area. The study contains a systematic analysis of the model behavior of HEC-RAS (‘Hydrologic Engineering Center—River Analysis System’) with a special focus on spatial resolution. The rain-on-grid approach is applied in a small, ungauged, low-mountainrange study area (Messbach catchment, 2.13 km2 ) in Central Germany. Suitable model settings and recommendations on model discretization and parametrization are derived therefrom. The sensitivity analysis focuses on the influence of the mesh resolution’s interaction with the spatial resolution of the underlying terrain model (‘subgrid’). Furthermore, the sensitivity of the parameters interplaying with spatial resolution, like the height of the laminar depth, surface roughness, model specific filter-settings and the precipitation input-data temporal distribution, is analyzed. The results are evaluated against a high-resolution benchmark run, and further criteria, such as 1. Nash–Sutcliffe efficiency, 2. water-surface elevation, 3. flooded area, 4. volume deficit, 5. volume balance and 6. computational time. The investigation showed that, based on the chosen criteria for this size and type of catchment, a mesh resolution between 3 m to 5 m, in combination with a DEM resolution from 0.25 m to 1 m, are recommendable. Furthermore, we show considerable scale effects on flooded areas for coarser meshing, due to low water levels in relation to topographic height

Evaluation of Baseflow Modeling with BlueM.Sim for Long-Term Hydrological Studies in the German Low Mountain Range of Hesse, Germany

So far, research with the hydrological model BlueM.Sim has been focused on reservoir management and integrated river basin modeling. BlueM.Sim is part of the official toolset for estimating immissions into rivers in Hesse (Germany) via long-term continuous modeling. Dynamic runoff modeling from rural catchments is permitted within the Hessian guidelines, but in practice, a constant flow or low flow is used. However, due to increasing water stress in the region caused by climate change, the dynamic modeling of runoff from rural catchments will become necessary. Therefore, dynamic baseflow modeling with BlueM.Sim is of the greatest importance. This study evaluated baseflow modeling with BlueM.Sim in a representative hard-rock aquifer in the German Low Mountain range. Two model setups (Factor Approach (FA): CN method + monthly baseflow; Soil Moisture Approach (SMA): physical soil moisture simulation) were calibrated (validated) for a 9-year (5-year) period. The FA achieved an NSE of 0.62 (0.44) and an LnNSE of 0.64 (0.60) for the calibration and validation periods. The selection of a solution for the successful validation of the FA was challenging and required a selection that overestimated baseflow in the calibration period. This is due to the major disadvantage of the FA, namely, that baseflow can only vary according to an estimated yearly pattern of monthly baseflow factors. However, the data requirements are low, and the estimation of monthly baseflow factors is simple and could potentially be regionalized for Hesse, leading to a better representation of baseflow than in current practice. The SMA achieved better results with an NSE of 0.78 (0.75) and an LnNSE of 0.72 (0.78). The data requirements and model setup are extensive and require the estimation of many parameters, which are limitations to its application in practice. Furthermore, a literature review has shown that a single linear reservoir, as in BlueM.Sim, is not optimal for modeling baseflow in hard-rock aquifers. However, for detailed climate change impact studies in the region with BlueM.Sim, the SMA should be preferred over the FA. It is expected that BlueM.Sim would benefit from implementing a more suitable model structure for baseflow in hard-rock aquifers, resulting in improved water balance and water quality outcomes

Modelling of riverine ecosystems by integrating models: conceptual approach, a case study and research agenda

Aim Highly complex interactions between the hydrosphere and biosphere, as well as multifactorial relationships, characterize the interconnecting role of streams and rivers between different elements of a landscape. Applying species distribution models (SDMs) in these ecosystems requires special attention because rivers are linear systems and their abiotic and biotic conditions are structured in a linear fashion with significant influences from upstream/downstream or lateral influences from adjacent areas. Our aim was to develop a modelling framework for benthic invertebrates in riverine ecosystems and to test our approach in a data-rich study catchment. Location We present a case study of a 9-km section of the lowland Kielstau River located in northern Germany. Methods We linked hydrological, hydraulic and species distribution models to predict the habitat suitability for the bivalve Sphaerium corneum in a riverine system. The results generated by the hydrological model served as inputs into the hydraulic model, which was used to simulate the resulting water levels, velocities and sediment discharge within the stream channel. Results The ensemble model obtained good evaluation scores (area under the receiver operating characteristic curve 0.96; kappa 0.86; true skill statistic 0.95; sensitivity 86.14; specificity 85.75). Mean values for variables at the sampling sites were not significantly different from the values at the predicted distribution (MannWhitney U-test P > 0.05). High occurrence probabilities were predicted in the downstream half of the 9-km section of the Kielstau. The most important variable for the model was sediment discharge (contributing 40%), followed by water depth (30%), flow velocity (19%) and stream power (11%). Main conclusions The hydrological and hydraulic models are able to produce predictors, acting at different spatial scales, which are known to influence riverine organisms; which, in turn, are used by the SDMs as input. Our case study yielded good results, which corresponded well with ecological knowledge about our study organism. Although this method is feasible for making projections of habitat suitability on a local scale (here: a reach in a small catchment), we discuss remaining challenges for future modelling approaches and large-scale applications.Aim Highly complex interactions between the hydrosphere and biosphere, as well as multifactorial relationships, characterize the interconnecting role of streams and rivers between different elements of a landscape. Applying species distribution models (SDMs) in these ecosystems requires special attention because rivers are linear systems and their abiotic and biotic conditions are structured in a linear fashion with significant influences from upstream/downstream or lateral influences from adjacent areas. Our aim was to develop a modelling framework for benthic invertebrates in riverine ecosystems and to test our approach in a data-rich study catchment. Location We present a case study of a 9-km section of the lowland Kielstau River located in northern Germany. Methods We linked hydrological, hydraulic and species distribution models to predict the habitat suitability for the bivalve Sphaerium corneum in a riverine system. The results generated by the hydrological model served as inputs into the hydraulic model, which was used to simulate the resulting water levels, velocities and sediment discharge within the stream channel. Results The ensemble model obtained good evaluation scores (area under the receiver operating characteristic curve 0.96; kappa 0.86; true skill statistic 0.95; sensitivity 86.14; specificity 85.75). Mean values for variables at the sampling sites were not significantly different from the values at the predicted distribution (MannWhitney U-test P > 0.05). High occurrence probabilities were predicted in the downstream half of the 9-km section of the Kielstau. The most important variable for the model was sediment discharge (contributing 40%), followed by water depth (30%), flow velocity (19%) and stream power (11%). Main conclusions The hydrological and hydraulic models are able to produce predictors, acting at different spatial scales, which are known to influence riverine organisms; which, in turn, are used by the SDMs as input. Our case study yielded good results, which corresponded well with ecological knowledge about our study organism. Although this method is feasible for making projections of habitat suitability on a local scale (here: a reach in a small catchment), we discuss remaining challenges for future modelling approaches and large-scale applications

Hydrological studies in a small German research basin in the low mountain range

The benefit of many years of operation of small hydrological research basins results from the acquisition of long-term, high-resolution data series, the improvement of hydrological process knowledge and the analysis of changes in climate, land use, land and water management. Furthermore, their importance is emphasized during extreme events, e.g. when springs run dry or very low river water levels occur in dry years or, in contrast, during floods and heavy rainfall. A small river basin with a catchment size of 36 km² is introduced as part of a larger river basin (500 km²) in the German low mountain range together with its characteristics. Monitoring and modelling concepts and results are presented and discussed