Analyzing and modelling solute and sediment transport at different spatial and temporal scales : a case study of the catchment of the Wahnbach River, Germany

Solute and sediment transport processes occur on a wide range of temporal and spatial scales. Differentiate between the observation and process scale which are defined by the extent, spacing and support of the samples and the modelling scale. Typical modelling scales are the local scale (1m), the hillslope scale (100 m), the catchment scale (10 km) and the regional scale (1000 km) and in time the event scale (1 day), the seasonal scale (1 yr) and the long-term scale (100 yrs). The modelling scale often differs from the process scale which necessitate an upscaling, downscaling or regionalization scheme. In this study process investigations at different scales are used for the temporal and spatial upscaling of a physically-based erosion model (OPUS) and its validation at different temporal and spatial scales. Numerous models for simulating erosion, transport and sedimentation are available. While the USLE model is able to simulate long-term erosion at single slopes without considering sedimentation, other approaches are calculating all processes. In this study a concept for continuously modelling of solute and sediment transport at the catchment scale for a period of 50 years is presented. The simulation is based on the application of the model system OPUS designed for long-term simulations of agricultural processes. As OPUS is a hillslope model the catchment is discretized into numerous slopes. These slopes are linked via a channel model (HEC6-model) which allows the simulation of erosion, transport and sedimentation in a catchment. After introducing some modifications and enhancements of the model it was possible to simulate interflow induced by macropores with OPUS. The simulation results are compared with measurements at different spatial and temporal scales of a meso-scale catchment used for drinking water supply. Three small sub-catchments of 22 to 29 ha are used to validate the model at the local scale. The modified and validated model is then applied to the Wahnbach catchment with an area of about 54 km². Simulations at the local and the catchment scales are presented and compared with measurements. To model the long-term behaviour of solute and sediment transport with a deterministic model a complete set of climate and landuse data is necessary. In this case study a method was developed to overcome the lack of data by using a weather generator. The long-term catchment simulations are validated by determining the mass of sediments trapped in the drinking water reservoir. In general, the obtained simulation results at different scales (from the sub-catchment scale to the catchment scale and from single events to long-term scales) are encouraging. It could be shown that process-based models can be applied at several scales in order to calculate the fluxes of matter. Furthermore, the results show that the considered flux types (water, solutes, sediment) are simulated with different success. The best results are obtained by simulating daily runoff at the sub-catchment scale and at the catchment scale. The solute concentration at the sub-catchment scale and the monthly nitrate discharge at the catchment scale is reproduced satisfactory, but the measures of model accuracy are less high. The sediment transport is simulated with the lowest accuracy

An empirical vegetation correction for soil water content quantification using cosmic ray probes

Cosmic ray probes are an emerging technology to continuously monitor soil water content at a scale significant to land surface processes. However, the application of this method is hampered by its susceptibility to the presence of aboveground biomass. Here we present a simple empirical framework to account for moderation of fast neutrons by aboveground biomass in the calibration. The method extends the N0-calibration function and was developed using an extensive data set from a network of 10 cosmic ray probes located in the Rur catchment, Germany. The results suggest a 0.9% reduction in fast neutron intensity per 1 kg of dry aboveground biomass per m2 or per 2 kg of biomass water equivalent per m2. We successfully tested the novel vegetation correction using temporary cosmic ray probe measurements along a strong gradient in biomass due to deforestation, and using the COSMIC, and the hmf method as independent soil water content retrieval algorithms. The extended N0-calibration function was able to explain 95% of the overall variability in fast neutron intensity

Validation of spaceborne and modelled surface soil moisture products with cosmic-ray neutron probes

The scale difference between point in situ soil moisture measurements and low resolution satellite products limits the quality of any validation efforts in heterogeneous regions. Cosmic Ray Neutron Probes (CRNP) could be an option to fill the scale gap between both systems, as they provide area-average soil moisture within a 150–250 m radius footprint. In this study, we evaluate differences and similarities between CRNP observations, and surface soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2), the METOP-A/B Advanced Scatterometer (ASCAT), the Soil Moisture Active and Passive (SMAP), the Soil Moisture and Ocean Salinity (SMOS), as well as simulations from the Global Land Data Assimilation System Version 2 (GLDAS2). Six CRNPs located on five continents have been selected as test sites: the Rur catchment in Germany, the COSMOS sites in Arizona and California (USA), and Kenya, one CosmOz site in New South Wales (Australia), and a site in Karnataka (India). Standard validation scores as well as the Triple Collocation (TC) method identified SMAP to provide a high accuracy soil moisture product with low noise or uncertainties as compared to CRNPs. The potential of CRNPs for satellite soil moisture validation has been proven; however, biomass correction methods should be implemented to improve its application in regions with large vegetation dynamics

Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach

Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and temporal resolutions of available forecast products have hindered their widespread use in such modelling applications, which usually require high-resolution input data. In this study, we applied sub-seasonal (up to 4 months) and seasonal (7 months) weather forecasts from the latest European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5) in a land surface modelling approach using the Community Land Model version 5.0 (CLM5). Simulations were conducted for 2017–2020 forced with sub-seasonal and seasonal weather forecasts over two different domains with contrasting climate and cropping conditions: the German state of North Rhine-Westphalia (DE-NRW) and the Australian state of Victoria (AUS-VIC). We found that, after pre-processing of the forecast products (i.e. temporal downscaling of precipitation and incoming short-wave radiation), the simulations forced with seasonal and sub-seasonal forecasts were able to provide a model output that was very close to the reference simulation results forced by reanalysis data (the mean annual crop yield showed maximum differences of 0.28 and 0.36 t ha−1 for AUS-VIC and DE-NRW respectively). Differences between seasonal and sub-seasonal experiments were insignificant. The forecast experiments were able to satisfactorily capture recorded inter-annual variations of crop yield. In addition, they also reproduced the generally higher inter-annual differences in crop yield across the AUS-VIC domain (approximately 50 % inter-annual differences in recorded yields and up to 17 % inter-annual differences in simulated yields) compared to the DE-NRW domain (approximately 15 % inter-annual differences in recorded yields and up to 5 % in simulated yields). The high- and low-yield seasons (2020 and 2018) among the 4 simulated years were clearly reproduced in the forecast simulation results. Furthermore, sub-seasonal and seasonal simulations reflected the early harvest in the drought year of 2018 in the DE-NRW domain. However, simulated inter-annual yield variability was lower in all simulations compared to the official statistics. While general soil moisture trends, such as the European drought in 2018, were captured by the seasonal experiments, we found systematic overestimations and underestimations in both the forecast and reference simulations compared to the Soil Moisture Active Passive Level-3 soil moisture product (SMAP L3) and the Soil Moisture Climate Change Initiative Combined dataset from the European Space Agency (ESA CCI). These observed biases of soil moisture and the low inter-annual differences in simulated crop yield indicate the need to improve the representation of these variables in CLM5 to increase the model sensitivity to drought stress and other crop stressors.</p

Evaluating the value of a network of cosmic-ray probes for improving land surface modelling

Land surface models can model matter and energy fluxes between the land surface and atmosphere, and provide a lower boundary condition to atmospheric circulation models. For these applications, accurate soil moisture quantification is highly desirable but not always possible given limited observations and limited subsurface data accuracy. Cosmic-ray probes (CRPs) offer an interesting alternative to indirectly measure soil moisture and provide an observation that can be assimilated into land surface models for improved soil moisture prediction. Synthetic studies have shown the potential to estimate subsurface parameters of land surface models with the assimilation of CRP observations. In this study, the potential of a network of CRPs for estimating subsurface parameters and improved soil moisture states is tested in a real-world case scenario using the local ensemble transform Kalman filter with the Community Land Model. The potential of the CRP network was tested by assimilating CRP-data for the years 2011 and 2012 (with or without soil hydraulic parameter estimation), followed by the verification year 2013. This was done using (i) the regional soil map as input information for the simulations, and (ii) an erroneous, biased soil map. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the biased soil map, soil moisture characterization improved in both periods strongly from a ERMS of 0.11 cm3/cm3 to 0.03 cm3/cm3 (assimilation period) and from 0.12 cm3/cm3 to 0.05 cm3/cm3 (verification period) and the estimated soil hydraulic parameters were after assimilation closer to the ones of the regional soil map. Finally, the value of the CRP network was also evaluated with jackknifing data assimilation experiments. It was found that the CRP network is able to improve soil moisture estimates at locations between the assimilation sites from a ERMS of 0.12 cm3/cm3 to 0.06 cm3/cm3 (verification period), but again only if the initial soil map was biased

Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site Wüstebach

Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms

High-resolution drought simulations and comparison to soil moisture observations in Germany

Germany\u27s 2018–2020 consecutive drought events resulted in multiple sectors – including agriculture, forestry, water management, energy production, and transport – being impacted. High-resolution information systems are key to preparedness for such extreme drought events. This study evaluates the new setup of the one-kilometer German drought monitor (GDM), which is based on daily soil moisture (SM) simulations from the mesoscale hydrological model (mHM). The simulated SM is compared against a set of diverse observations from single profile measurements, spatially distributed sensor networks, cosmic-ray neutron stations, and lysimeters at 40 sites in Germany. Our results show that the agreement of simulated and observed SM dynamics in the upper soil (0–25 cm) are especially high in the vegetative active period (0.84 median correlation R) and lower in winter (0.59 median R). The lower agreement in winter results from methodological uncertainties in both simulations and observations. Moderate but significant improvements between the coarser 4 km resolution setup and the ≈ 1.2 km resolution GDM in the agreement to observed SM dynamics is observed in autumn (+0.07 median R) and winter (+0.12 median R). Both model setups display similar correlations to observations in the dry anomaly spectrum, with higher overall agreement of simulations to observations with a larger spatial footprint. The higher resolution of the second GDM version allows for a more detailed representation of the spatial variability of SM, which is particularly beneficial for local risk assessments. Furthermore, the results underline that nationwide drought information systems depend both on appropriate simulations of the water cycle and a broad, high-quality, observational soil moisture database

Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site Wüstebach

Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms

Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site Wüstebach

Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms

TERENO: German network of terrestrial environmental observatories

Central elements of the TERENO network are “terrestrial observatories” at the catchment scale which were selected in climate sensitive regions of Germany for the regional analyses of climate change impacts. Within these observatories small scale research facilities and test areas are placed in order to accomplish energy, water, carbon and nutrient process studies across the different compartments of the terrestrial environment. Following a hierarchical scaling approach (point-plot-field) these detailed information and the gained knowledge will be transferred to the regional scale using integrated modelling approaches. Furthermore, existing research stations are enhanced and embedded within the observatories. In addition, mobile measurement platforms enable monitoring of dynamic processes at the local scale up to the determination of spatial pattern at the regional scale are applied within TERENO