Representation of hydrological processes in a rural lowland catchment in Northern Germany usingSWATandSWAT+

Abstract

The latest version of the Soil and Water Assessment Tool (SWAT+) features several improvements compared with previous versions of the model, for example, the definition of landscape units that allow for a better representation of spatio‐temporal dynamics. To evaluate the new model capabilities in lowland catchments characterized by near‐surface groundwater tables and extensive tile drainage, we assess the performance of two SWAT+ model setups in comparison to a setup based on a previous SWAT model version (SWAT3S with a modified three groundwater storage model) in the Kielstau catchment in Northern Germany. The Kielstau catchment has an area of about 50 km2, is dominated by agricultural land use, and has been thoroughly monitored since 2005. In both SWAT+ setups, the catchment is divided into upland areas and floodplains, but in the first SWAT+ model setup, runoff from the hydrologic response units is summed up at landscape unit level and added directly to the stream. In the second SWAT+ model setup, runoff is routed across the landscape before it reaches the streams. Model results are compared with regard to (i) model performance for stream flow at the outlet of the catchment and (ii) aggregated as well as temporally and spatially distributed water balance components. All three model setups show a very good performance at the catchment outlet. In comparison to a previous version of the SWAT model that produced more groundwater flow, the SWAT+ model produced more tile drainage flow and surface runoff. Results from the new SWAT+ model confirm that the representation of routing processes from uplands to floodplains in the model further improved the representation of hydrological processes. Particularly, the stronger spatial heterogeneity that can be related to characteristics of the landscape, is very promising for a better understanding and model representation of hydrological fluxes in lowland areas. The outcomes of this study are expected to further prove the applicability of SWAT+ and provide useful information for future model development.

Setting an ecological flow regime in a Mediterranean basin with limited data availability: The Locone River case study (S-E Italy)

“…To date, since there is not a large number of SWAT+ applications in the Mediterranean environment, it is not possible to make a comparison with other studies in order to understand if the underestimation of the extremely low flow is due to the model structure or if it is due to model inputs. However, Wagner et al (2022) in their work carried out in a lowland catchment in Germany pointed out that low flows were better predicted by SWAT2012, meanwhile, high flows were better represented by SWAT+, since the latter produced more tile drainage flow and surface runoff than SWAT2012. The authors highlighted that the ongoing improvements of the SWAT+ code, such as the introduction of new parameters (i.e., CN3_SWF, soil water factor for curve number condition III; and LATQ_CO, lateral flow coefficient), which were not included in the SWAT+ version used in present work, is very promising to improve predictions of hydrological processes.…”

Model calibration using hydropedological insights to improve the simulation of internal hydrological processes using SWAT+

“…SWAT+ incorporates parameters that allows the calibration of these processes, where PERCO and LATQ_CO parameters are linear coefficients that can be applied to the hillslope storage equation to limit lateral flow and percolation values (Wagner et al, 2022). Therefore, these parameters could potentially be manually calibrated to link soil morphology to dominant hydrological processes and accurately reflect these processes for each mapping unit as the current soil hydraulic properties fail to correctly simulate these processes.…”

“…Different parameters within SWAT have different levels of sensitivity within the model, which allows modellers the opportunity to calibrate different hydrological processes such as surface runoff, lateral flow, return flow, and evapotranspiration rates (Wagner et al, 2022).…”

A guideline for spatio‐temporal consistency in water quality modelling in rural areas

“…In et al, 2013), evaporation (Wagner et al, 2011) and biomass, as well as the timing of harvest and yield (Lautenbach et al, 2013). In addition, model outputs can be validated against spatial patterns (Bieger et al, 2015;Wagner et al, 2022). This requires the spatial representation of the remotely sensed or mapped variables in the model, for example evaporation or soil moisture (Odusanya et al, 2019;Rajib et al, 2016).…”

“…The consistency check for plant‐related characteristics largely depends on the modelling scale and requires to consider the influence of each combination of plant–soil‐climatic conditions on the simulated time series of leaf area index (Strauch et al, 2013), evaporation (Wagner et al, 2011) and biomass, as well as the timing of harvest and yield (Lautenbach et al, 2013). In addition, model outputs can be validated against spatial patterns (Bieger et al, 2015; Wagner et al, 2022). This requires the spatial representation of the remotely sensed or mapped variables in the model, for example evaporation or soil moisture (Odusanya et al, 2019; Rajib et al, 2016).…”