Impacts of land-use changes on watershed discharge and water quality in a large intensive agricultural area in Thailand

The objectives of this research were to evaluate the effect of land-use change on streamflow, sediment and water quality data along the Lower Yom River, Thailand, covering an intensively agricultural area of 14 613.6 km², and to assess the relative impact of point and non-point sources of pollution from multiple-land-use watersheds. Long-term calibration and validation of the SWAT (Soil and Water Assessment Tool) model was performed on data for 2000–2013. Land-use change led to a 13–49% increase in runoff in the basin and resulted in 37–427% increased sediment yield. The amount of NO₃-N load doubled in the upper and middle parts of the study area, while the increase in PO₄^3– ranged from 37 to 377%, reflecting the increase in agricultural lands and urban areas. It is concluded that the changed land use is closely associated with the quantity of runoff, sediment yield and the NO₃-N and PO₄^3– concentrations.     

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

Soils affect the distribution of hydrological processes by partitioning precipitation into different components of the water balance. Therefore, understanding soil-water dynamics at a catchment scale remains imperative to future water resource management. In this study, the value of hydropedological insights was examined to calibrate a processes-based model. Soil morphology was used as soft data to assist in the calibration of the Soil Water Assessment Tool (SWAT+) model at five different catchment scales (48, 56, 174, 674, and 2421 km²) in the Sabie River catchment, South Africa. The aim of this study was to calibrate the SWAT+ model to accurately simulate long-term monthly streamflow predictions as well as to reflect internal soil hydrological processes using a procedure focusing on hydropedology as a calibration tool in a multigauge system. Results indicated that calibration improved streamflow predictions where R² improved by 2%–8%. Nash-Sutcliffe Efficiency (NSE) improved from negative correlations to values exceeding 0.5 at four of the five catchment scales compared to the uncalibrated model. Results confirm that soil mapping units can be calibrated individually within SWAT+ to improve the representation of hydrological processes. Particularly, the spatial linkage between hydropedology and hydrological processes, which is captured within the soil map of the catchment, can be adequately reflected within the model simulations after calibration. This research will lead to an improved understanding of hydropedology as soft data to improve hydrological modelling accuracy.     

Non‐point source pollution estimation using a modified approach

Non‐point source (NPS) pollution from agricultural land is increasing exponentially in many countries of the world, including India. A modified approach based on the conservation of mass and reaction kinetics has been derived to estimate the inflow of non‐point source pollutants from a river reach. Two water quality variables, namely, nitrate (NO₃) and ortho‐phosphate (o‐PO₄), which are main contributors as non‐point source pollution, were monitored at four locations of River Kali, western Uttar Pradesh, India, and used for calibration and validation of the model. Extensive water quality sampling was done with a total of 576 field data sets collected during the period from March 1999 to February 2000. Remote sensing and geographical information system (GIS) techniques were used to obtain land use/land cover of the region, digital elevation model (DEM), delineation of basin area contributing to non‐point source pollution at each sampling location and drainage map. The results obtained from a modified approach were compared with the existing mass‐balance equations and distributed modelling, and the performances of different equations were evaluated using error estimation viz. standard error, normal mean error, mean multiplicative error and correlation statistics. The developed model for the River Kali minimizes error estimates and improves correlation between observed and computed NPS loads. Copyright © 2007 John Wiley & Sons, Ltd.     

Investigating snowpack across scale in the northern Great Lakes–St. Lawrence forest region of Central Ontario,Canada

This study investigates scaling issues by evaluating snow processes and quantifying bias in snowpack properties across scale in a northern Great Lakes–St. Lawrence forest. Snow depth and density were measured along transects stratified by land cover over the 2015/2016 and 2016/2017 winters. Daily snow depth was measured using a time‐lapse (TL) camera at each transect. Semivariogram analysis of the transect data was conducted, and no autocorrelation was found, indicating little spatial structure along the transects. Pairwise differences in snow depth and snow water equivalent (SWE) between land covers were calculated and compared across scales. Differences in snowpack between forested sites at the TL points corresponded to differences in canopy cover, but this relationship was not evident at the transect scale, indicating a difference in observed process across scale. TL and transect estimates had substantial bias, but consistency in error was observed, which indicates that scaling coefficients may be derived to improve point scale estimates. TL and transect measurements were upscaled to estimate grid scale means. Upscaled estimates were compared and found to be consistent, indicating that appropriately stratified point scale measurements can be used to approximate a grid scale mean when transect data are not available. These findings are important in remote regions such as the study area, where frequent transect data may be difficult to obtain. TL, transect, and upscaled means were compared with modelled depth and SWE. Model comparisons with TL and transect data indicated that bias was dependent on land cover, measurement scale, and seasonality. Modelled means compared well with upscaled estimates, but model SWE was underestimated during spring melt. These findings highlight the importance of understanding the spatial representativeness of in situ measurements and the processes those measurements represent when validating gridded snow products or assimilating data into models.     

Water and nutrient predictions in ungauged basins: set-up and evaluation of a model at the national scale

Abstract

A dynamic water quality model, HYPE, was applied to a large, data-sparse region to study whether reliable information on water quantity and water quality could be obtained for both gauged and ungauged waterbodies. The model (called S-HYPE) was set up for all of Sweden (～450 000 km²), divided into sub-basins with an average area of 28 km². Readily available national databases were used for physiographic data, emissions and agricultural practices, fixed values for representative years were used. Daily precipitation and temperature were used as the dynamic forcing of the model. Model evaluation was based on data from several hundred monitoring sites, of which approximately 90% had not been used in calibration on a daily scale. Results were evaluated using the Nash-Sutcliffe efficiency (NSE), correlation and relative errors: 92% of the spatial variation was explained for specific water discharge, and 88% and 59% for total nitrogen and total phosphorus concentrations, respectively. Day-to-day variations were modelled with satisfactory results for water discharge and the seasonal variation of nitrogen concentrations was also generally well captured. In 20 large, unregulated rivers the median NSE for water discharge was 0.84, and the corresponding number for 76 partly-regulated river basins was 0.52. In small basins, the NSE was typically above 0.6. These major achievements relative to previous similar experiments were ascribed to the step-wise calibration process using representative gauged basins and the use of a modelling concept, whereby coefficients are linked to physiographic variables rather than to specific sites.

Editor D. Koutsoyiannis

Citation Strömqvist, J., Arheimer, B., Dahné, J., Donnelly, C. and Lindström, G., 2012. Water and nutrient predictions in ungauged basins: set-up and evaluation of a model at the national scale. Hydrological Sciences Journal, 57 (2), 229–247.     

Calibration of the Wetland Hydrodynamic Model to the Everglades Nutrient Removal Project

The objective of this study was to calibrate the Everglades Wetland Hydrodynamic Model (EWHM) to the Everglades Nutrient Removal (ENR) Project, from April 1995 through July of 1996. Model predictions were evaluated graphically and statistically against field observations to quantify the accuracy of model predictions and evaluate the success of model calibration. Comparisons between model predictions and field observations of water surface elevations at interior stations indicated that the model was successfully calibrated and model predictions were highly correlated with observed water surface elevations (r² ranged from 0.79 to 0.84). Model-predicted chloride (Cl) concentrations fell within the observed range of field observations, further confirming the success of model calibration. Good agreement found in these comparisons between observed and predicted results warrants the use of the model in a predictive mode. This is further supported by noting that the model contains no adjustable constants and requires no computational fitting of parameters to experimental data as is necessary in many previous obstructed flow studies.     

Hydrochemical behaviour of dissolved nitrogen and carbon in a headwater stream of the Canadian Shield: relevance of antecedent soil moisture conditions

This paper examines the impact of contrasting antecedent soil moisture conditions on the hydrochemical response, here the changes in dissolved nitrogen (NO₃^?, NH₄⁺ and dissolved organic nitrogen (DON)) and dissolved organic carbon (DOC) concentrations, of a first‐order stream during hydrological events. The study was performed in the Hermine, a 5 ha forested watershed of the Canadian Shield. It focused on a series of eight precipitation events (spring, summer and fall) sampled every 2 or 3 h and showing contrasted antecedent moisture conditions. The partition of the eight events between two groups (dry or wet) of antecedent moisture conditions was conducted using a principal component analysis (PCA). The partition was controlled (first axis explained 86% of the variability) by the antecedent streamflow, the streamflow to precipitation ratio Q/P and by the antecedent groundwater depth. The mean H⁺, NO₃^?, NH₄⁺, total dissolved nitrogen and DOC concentrations and electrical conductivity values in the stream were significantly higher following dry antecedent conditions than after wetter conditions had prevailed in the Hermine, although the temporal variability was high (17 to 138%). At the event scale, a significantly higher proportion of the changes in DON, NO₃^?, and DOC concentrations in the stream was explained by temporal variations in discharge compared with the seasonal and annual scales. Two of the key hydrochemical features of the dry events were the synchronous changes in DOC and flow and the frequent negative relationships between discharge and NO₃^?. The DON concentrations were much less responsive than DOC to changes in discharge, whereas NH was not in phase with streamflow. During wet events, the synchronicity between streamflow and DON or NO₃^? was higher than during dry events and discharge and NO₃^? were generally positively linked. Based on these observations, the hydrological behaviour of the Hermine is conceptually compatible with a two‐component model of shallow (DON and DOC rich; variable NO₃^?) and deep (DON and DOC poor; variable NO₃^?) subsurface flow. The high NO₃^? and DOC levels measured at the early stages of dry events reflected the contribution from NO₃^?‐rich groundwaters. The contribution of rapid surface flow on water‐repellent soil materials located close to the stream channel is hypothesized to explain the DOC levels. An understanding of the complex interactions between antecedent soil moisture conditions, the presence of soil nutrients available for leaching and the dynamics of soil water flow paths during storms is essential to explain the fluxes of dissolved nitrogen and carbon in streams of forested watersheds. Copyright © 2007 John Wiley & Sons, Ltd.     

Subgrid variability of snow water equivalent at operational snow stations in the western USA

The spatial distribution of snow water equivalent (SWE) is a key variable in many regional‐scale land surface models. Currently, the assimilation of point‐scale snow sensor data into these models is commonly performed without consideration of the spatial representativeness of the point data with respect to the model grid‐scale SWE. To improve the understanding of the relationship between point‐scale snow measurements and surrounding areas, we characterized the spatial distribution of snow depth and SWE within 1‐, 4‐ and 16‐km² grids surrounding 15 snow stations (snowpack telemetry and California snow sensors) in California, Colorado, Wyoming, Idaho and Oregon during the 2008 and 2009 snow seasons. More than 30 000 field observations of snowpack properties were used with binary regression tree models to relate SWE at the sensor site to the surrounding area SWE to evaluate the sensor representativeness of larger‐scale conditions. Unlike previous research, we did not find consistent high biases in snow sensor depth values as biases over all sites ranged from 74% overestimates to 77% underestimates. Of the 53 assessments, 27 surveys indicated snow station biases of less than 10% of the surrounding mean observed snow depth. Depth biases were largely dictated by the physiographic relationship between the snow sensor locations and the mean characteristics of the surrounding grid, in particular, elevation, solar radiation index and vegetation density. These scaling relationships may improve snow sensor data assimilation; an example application is illustrated for the National Operational Hydrologic Remote Sensing Center National Snow Analysis SWE product. The snow sensor bias information indicated that the assimilation of point data into the National Operational Hydrologic Remote Sensing Center model was often unnecessary and reduced model accuracy. Copyright © 2012 John Wiley & Sons, Ltd.     

Grid‐resolution effects on a model for integrating urban and rural areas

The impact of grid‐cell size on calibrated parameters and on the performance of a variable source area model intended for urbanizing catchments is studied in this research. The model uses TOPMODEL concepts that were modified to consider urban areas in both the topographic index and the mechanism of surface runoff generation. The revised model known as TOPURBAN, was applied to a small catchment of roughly 8 km² in southern Ontario. Ten different grid‐cell sizes ranging from 10 m to 100 m were selected to study scale effects in this catchment with mild to moderate relief, on three separate time periods. The model performed adequately with calibration efficiencies for all three time periods in the range of 0\65 to 0\85. The verification efficiencies were not as high and ranged from 0\4 to 0\6. Larger cell sizes produced higher averages of topographic index, and this resulted in larger calibrated transmissivities. The most important parameter in determining the quantity of urban runoff was slightly affected by grid resolution. During the calibration process, this parameter was also found to interact with important parameters that dealt primarily with rural runoff generation. As cell size increased, contributions from urban areas increased and overland flow contributions from rural areas decreased. Results showed that in this integrated model of urban and rural areas, predicted processes based on calibrated parameters were dependent on grid resolution. Calibration of internal state variables is recommended to draw conclusions on the influences between urban and rural areas on the overall flow. Copyright © 2000 John Wiley & Sons, Ltd.     

T‐NET,a dynamic model for simulating daily stream temperature at the regional scale based on a network topology

Currently, the distribution areas of aquatic species are studied by using air temperature as a proxy of water temperature, which is not available at a regional scale. To simulate water temperature at a regional scale, a physically based model using the equilibrium temperature concept and including upstream‐downstream propagation of the thermal signal is proposed. This model, called Temperature‐NETwork (T‐NET), is based on a hydrographical network topology and was tested at the Loire basin scale (10⁵ km²). The T‐NET model obtained a mean root mean square error of 1.6 °C at a daily time step on the basis of 128 water temperature stations (2008–2012). The model obtained excellent performance at stations located on small and medium rivers (distance from headwater <100 km) that are strongly influenced by headwater conditions (median root mean square error of 1.8 °C). The shading factor and the headwater temperature were the most important variables on the mean simulated temperature, while the river discharge influenced the daily temperature variation and diurnal amplitude. The T‐NET model simulates specific events, such as temperature of the Loire during the floods of June 1992 and the thermal regime response of streams during the heatwave of August 2003, much more efficiently than a simple point‐scale heat balance model. The T‐NET model is very consistent at a regional scale and could easily be transposed to changing forcing conditions and to other catchments. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatial and temporal variations in surface water nitrate concentrations in a mixed land use catchment under humid temperate climatic conditions

Streamwater nitrate (NO^―₃) concentrations along the main stream and at the outlet of several subcatchments within the 114\3 km² Zwalm watershed in Flanders, Belgium, have been monitored regularly since 1991. Land use within the Zwalm catchment is predominantly agricultural, with forested regions in the south and urban concentrations in the north‐east of the catchment. Streamwater NO^―₃ concentrations increased with increases in stream discharge rates, but in general, discharge rate explained only about 30% of the variation in NO^―₃ concentrations. The low R² values were attributed to the observed anticlockwise hysteresis in the NO^―₃ concentration – discharge relationship and to differences in NO^―₃ concentrations between both seasonal flow and various flow regimes, with winter flow explaining 51% of the variation in NO^―₃ concentrations, whereas summer flow explained only 28% of the variation. A hypothesis was formulated in which flow regime accounts for the seasonal variation in NO^―₃ export, postulating that the catchment seasonally alternates between two hydrological stages. The first stage occurs during wet winter periods, when the catchment drains as a single source area, whereas the second stage occurs during dry summer periods, when the groundwater store disconnects into separate subcatchments. This causes NO^―₃ concentration peaks to be more delayed during summer storm events compared with winter storm events. Regarding flow regimes, differences between high and low flow conditions and between increasing and stable/decreasing flow were not as pronounced a differences between seasons. In contrast to the estimation of NO^―₃ concentrations, discharge was a strong predictor (R²= 0\71) of the NO^―₃ flux within the tributaries of the Zwalm catchment. The NO^―₃ concentrations in the main stream increased with decreasing elevation, whereas the seasonal concentration patterns along the main channel were similar to those observed at the outlet. NO^―₃ concentrations varied considerably among catchments and showed a high variability over time, although in general, the variation in NO^―₃ concentration was higher between catchments than within catchments. The impact of land use is clearly reflected in the streamwater NO^―₃ concentrations, although NO^―₃ concentration patterns were also affected by topography and, to a lesser extent, by soil type. A gradual increase in NO^―₃ concentrations at the outlet of the Zwalm catchment could be observed throughout the 1991 – 1998 study period, providing evidence for the general trends of increase in Flanders, which are attributed to the intensification of agricultural activities. Copyright © 2000 John Wiley & Sons, Ltd.     

Nitrate dynamics in a rural headwater catchment: measurements and modelling

This study was designed to improve our understanding of, and mechanistically simulate, nitrate (NO₃) dynamics in a steep 9.8 ha rural headwater catchment, including its production in soil and delivery to a stream via surface and subsurface processes. A two‐dimensional modelling approach was evaluated for (1) integrating these processes at a hillslope scale annually and within storms, (2) estimating denitrification, and (3) running virtual experiments to generate insights and hypotheses about using trees in streamside management zones (SMZs) to mitigate NO₃ delivery to streams. Total flow was mathematically separated into quick‐ and slow‐flow components; the latter was routed through the HYDRUS software with a nitrogen module designed for constructed wetlands. Flow was monitored for two years. High surface‐soil NO₃ concentrations started to be delivered to the stream via preferential subsurface flow within two days of the storm commencing. Groundwater NO₃‐N concentrations decreased from 1.0 to less than 0.1 mg l^?1 from up‐slope to down‐slope water tables, respectively, which was attributed to denitrification. Measurements were consistent with the flushing of NO₃ mainly laterally from surface soil during and following each storm. The model accurately accounted for NO₃ turnover, leading to the hypotheses that denitrification was a minor flux (<3 kg N ha^?1) compared to uptake (98^?127 kg N ha^?1), and that SMZ trees would reduce denitrification if they lowered the water table. This research provides an example of the measurement and modelling of NO₃ dynamics at a small‐catchment scale with high spatial and temporal resolution. Copyright © 2013 John Wiley & Sons, Ltd.     

Using geostatistical simulation to disaggregate air quality model results for individual exposure estimation on GPS tracks

In this work, we address the mismatch in spatio-temporal resolution between individual, point-location based exposure and grid cell based air quality model predictions by disaggregating the grid model results. Variability of PM₁₀ point measurements was modelled within each grid cell by the exponential variogram, using point support concentration measurements. Variogram parameters were estimated over the study area globally using constant estimates, and locally by multiple regression models using traffic, weather and land use data. Model predictions of spatio-temporal variability were used for geostatistical unconditional simulation, estimating the deviation of point values from grid cell averages on GPS tracks. The distribution of deviations can be used as an estimate of uncertainty for individual exposure. Results showed a relevant impact of the disaggregation uncertainties compared to other uncertainty sources, dependent of the model used for spatio-temporal variability. Depending on individual behaviour and variability of the pollutant, these uncertainties average out again over time.     

Precise Relative Location of 25-ton Chemical Explosions at Balapan Using IMS Stations

—?We test how well low-magnitude (m _bLg 1.8 to 2.6), 25-ton chemical explosions at Balapan, Kazakhstan, can be located using IMS stations and standard earth models, relying on precisely determined relative arrival times of nearly similar, regional and teleseismic waveforms. Three 1997 Balapan explosions were recorded by a number of currently reporting and surrogate IMS stations. Three regional stations and two teleseismic arrays yielded consistent waveforms appropriate for relative picking. Master-event locations based on the AK135 model and ground-truth information from the first, shallowest and best-recorded explosion, fell under 1 km from known locations, for depths constrained to that of the master event. The resulting 90% confidence ellipses covered 12–13?km² and contained the true locations; however, results for depth constrained to true depth were slightly less satisf actory. From predictions based on ground truth, we found a P _g -coda phase at Makanchi, Kazakhstan to be misidentified and poorly modeled. After accounting for this, 90% ellipses shrank to 2–3?km² and true-depth mislocation vectors became more consistent with confidence-ellipse orientations. These results suggest that a high level of precision could be provided by a tripartite array of calibration shots in cases where models are poorly known. We hope that the successful relocation of these small Balapan shots will support the role of calibration explosions in verification monitoring and special event studies, including on-site inspection.     

In situ and high frequency monitoring of suspended sediment properties using a spectrophotometric sensor

It is well known that sediment properties, including sediment‐associated chemical constituents and sediment physical properties, can exhibit significant variations within and between storm runoff events. However, the number of samples included in suspended sediment studies is often limited by time‐consuming and expensive laboratory procedures after stream water sampling. This restricts high frequency sampling campaigns to a limited number of events and reduces accuracy when aiming to estimate fluxes and loads of sediment‐associated chemical constituents. In this study, we address the potential of a portable ultraviolet–visible spectrophotometer (220–730 nm) to estimate suspended sediment properties in a resource efficient way. Several field deployable spectrophotometers are currently available for in‐stream measurements of environmental variables at high temporal resolution. These instruments have primarily been developed and used to quantify solute concentrations (e.g. dissolved organic carbon and NO₃‐N), total concentrations of dissolved and particulate forms (e.g. total organic carbon) and turbidity. Here we argue that light absorbance values can be calibrated to estimate sediment properties. We present light absorbance data collected at 15‐min intervals in the Weierbach catchment (NW Luxembourg, 0.45 km²) from December 2013 to January 2015. In this proof‐of‐concept study, we performed a local calibration using suspended sediment loss‐on‐ignition (LOI) measurements as an example of suspended sediment property. We assessed the performance of several regression models that relate light absorbance measurements with the percentage weight LOI. The MM‐robust regression method presented the lowest standard error of prediction (0.48%) and was selected for calibration (adjusted r² = 0.76 between observed and predicted values). The model was then used to predict LOI during a storm runoff event in December 2014. This study demonstrates that spectrophotometers can be used to estimate suspended sediment properties at high temporal resolution and for long‐time spans in a simple, non‐destructive and affordable manner. Copyright © 2016 John Wiley & Sons, Ltd.     

A geostatistical approach for assessing population exposure to NO2 in a complex urban area (Beirut,Lebanon)

Few studies in the Middle East region estimated the spatial distribution of air pollutants for exposure studies. This paper presents a geostatistical approach to assess background NO₂ spatial distribution and the associated exposed population in a Mediterranean city with a complex topography, Beirut. Such modeling gave an accurate mapping of the 2010 yearly background average value of NO₂: it varies between 35 and 67 μg m^?3 with a mean of 53 μg m^?3. The mean SD of the estimated error was about 3 μg m^?3. The results showed that the spatial distribution of NO₂ follows a nested structuring, with a major structure related to topoclimatic characteristics (interaction topography/atmospheric flow at large scale) and a minor one linked to micro-environment and micro-climatic characteristics (interactions urban morphology/atmospheric flows at fine scale). The probability for the city’s inhabitants to be exposed to NO₂ levels exceeding 40 μg m^?3 threshold limit set by the World Health Organization (WHO) showed that Beirut city has a real sanitary risk to the NO₂ pollution. 93 % of the population (around 358,459 people) is 100 % sure to be exposed to a yearly average exceeding 40 μg m^?3. This knowledge will be certainly useful for developing a tool for decision support in order to implement policies of reducing air pollution in Beirut, which is, given the results, very urgent.     

Coupling the Xinanjiang model to a kinematic flow model based on digital drainage networks for flood forecasting

The Xinanjiang model, which is a conceptual rainfall‐runoff model and has been successfully and widely applied in humid and semi‐humid regions in China, is coupled by the physically based kinematic wave method based on a digital drainage network. The kinematic wave Xinanjiang model (KWXAJ) uses topography and land use data to simulate runoff and overland flow routing. For the modelling, the catchment is subdivided into numerous hillslopes and consists of a raster grid of flow vectors that define the water flow directions. The Xinanjiang model simulates the runoff yield in each grid cell, and the kinematic wave approach is then applied to a ranked raster network. The grid‐based rainfall‐runoff model was applied to simulate basin‐scale water discharge from an 805‐km² catchment of the Huaihe River, China. Rainfall and discharge records were available for the years 1984, 1985, 1987, 1998 and 1999. Eight flood events were used to calibrate the model's parameters and three other flood events were used to validate the grid‐based rainfall‐runoff model. A Manning's roughness via a linear flood depth relationship was suggested in this paper for improving flood forecasting. The calibration and validation results show that this model works well. A sensitivity analysis was further performed to evaluate the variation of topography (hillslopes) and land use parameters on catchment discharge. Copyright © 2009 John Wiley & Sons, Ltd.     

Validation of official erosion modelling based on high‐resolution radar rain data by aerial photo erosion classification

The universal soil loss equation (USLE) is the most frequently applied erosion prediction model and it is also implemented as an official decision‐making instrument for agricultural regulations. The USLE itself has been already validated using different approaches. Additional errors, however, arise from input data and interpolation procedures that become necessary for field‐specific predictions on a national scale for administrative purposes. In this study, predicted event soil loss using the official prediction system in Bavaria (Germany) was validated by comparison with aerial photo erosion classifications of 8100 fields. Values for the USLE factors were mainly taken from the official Bavarian high‐resolution (5 × 5 m²) erosion cadastre. As series of erosion events were examined, the cover and management factor was replaced by the soil loss ratio. The event erosivity factor was calculated from high‐resolution (1 × 1 km², 5 min), rain gauge‐adjusted radar rain data (RADOLAN). Aerial photo erosion interpretation worked sufficiently well and average erosion predictions and visual classifications correlated closely. This was also true for data broken down to individual factors and different crops. There was no reason to assume a general invalidity of the USLE and the official parametrization procedures. Event predictions mainly suffered from errors in the assumed crop stage period and tillage practices, which do not reflect interannual and farm‐specific variation. In addition, the resolution of radar data (1 km²) did not seem to be sufficient to predict short‐term erosion on individual fields given the strong spatial gradients within individual rains. The quality of the input data clearly determined prediction quality. Differences between USLE predictions and observations are most likely caused by parametrization weaknesses but not by a failure of the model itself. Copyright © 2017 John Wiley & Sons, Ltd.