Geostatistical interpolation of space–time rainfall on Tamshui River basin,Taiwan

Taiwan suffers from heavy storm rainfall during the typhoon season. This usually causes large river runoff, overland flow, erosion, landslides, debris flows, loss of power, etc. In order to evaluate storm impacts on the downstream basin, a real‐time hydrological modelling is used to estimate potential hazard areas. This can be used as a decision‐support system for the Emergency Response Center, National Fire Agency Ministry, to make ‘real‐time’ responses and minimize possible damage to human life and property. This study used 34 observed events from 14 telemetered rain‐gauges in the Tamshui River basin, Taiwan, to study the spatial–temporal characteristics of typhoon rainfall. In the study, regionalized theory and cross‐semi‐variograms were used to identify the spatial‐temporal structure of typhoon rainfall. The power form and parameters of the cross‐semi‐variogram were derived through analysis of the observed data. In the end, cross‐validation was used to evaluate the performance of the interpolated rainfall on the river basin. The results show the derived rainfall interpolator represents the observed events well, which indicates the rainfall interpolator can be used as a spatial‐temporal rainfall input for real‐time hydrological modelling. Copyright © 2007 John Wiley & Sons, Ltd.     

Improvement of the solute transfer in a conceptual unsaturated zone scheme: a case study of the Seine River basin

For predicting the evolution of solute concentrations in groundwater and testing the impact of remediation policies, a coupling between the agronomical model STICS and the hydrogeological model MODCOU was implemented. When applied to the Seine River basin, this model accurately represents the temporal evolution of average nitrate concentrations in the aquifer, but with large local errors. We propose an improvement to the simple unsaturated zone (UZ) scheme NonsatSW used in STICS–MODCOU. The modifications are based on a comparison with the mechanistic model Metis considered as a reference as it solves Richards' equation. A more realistic saturation profile and a varying percolation rate are integrated in NonsatSW. This new model, named NonsatVG, is assessed by comparing it with NonsatSW and Metis. In an ideal case, NonsatVG generates a solute transfer and a dispersion closer to that of Metis than of NonsatSW. In real cases, without additional calibration, NonsatVG and Metis simulate better the average transfer velocities of the observed nitrate profiles. Furthermore, modifications in NonsatVG give a direct relationship between the depth of the water table and the saturation profile. We obtain, therefore, as in Metis, an evolution of the solute transfer velocity depending on the piezometric level. These dynamics are not simulated in NonsatSW. Despite a modified water transfer through the UZ, NonsatVG is also as valid as NonsatSW in the modelling of water transfer to the saturated zone. Finally, an application to the Seine basin shows that solute transfer velocities are lower with NonsatVG than with NonsatSW, but are in better agreement with literature. Copyright © 2010 John Wiley & Sons, Ltd.     

Assessing the influence of the Merzbacher Lake outburst floods on discharge using the hydrological model SWIM in the Aksu headwaters,Kyrgyzstan/NW China

Glacial lake outburst floods (GLOF) often have a significant impact on downstream users. Including their effects in hydrological models, identifying past occurrences and assessing their potential impacts are challenges for hydrologists working in mountainous catchments. The regularly outbursting Merzbacher Lake is located in the headwaters of the Aksu River, the most important source of water discharge to the Tarim River, northwest China. Modelling its water resources and the evaluation of potential climate change impacts on river discharge are indispensable for projecting future water availability for the intensively cultivated river oases downstream of the Merzbacher Lake and along the Tarim River. The semi‐distributed hydrological model SWIM was calibrated to the outlet station Xiehela on the Kumarik River, by discharge the largest tributary to the Aksu River. The glacial lake outburst floods add to the difficulties of modelling this high‐mountain, heavily glaciated catchment with poor data coverage and quality. The aims of the study are to investigate the glacier lake outburst floods using a modelling tool. Results include a two‐step model calibration of the Kumarik catchment, an approach for the identification of the outburst floods using the measured gauge data and the modelling results and estimations of the outburst flood volumes. Results show that a catchment model can inform GLOF investigations by providing ‘normal’ (i.e. without the outburst floods) catchment discharge. The comparison of the simulated and observed discharge proves the occurrence of GLOFs and highlights the influences of the GLOFs on the downstream water balance. © 2013 The Authors. Hydrological Processes Published by John Wiley & Sons Ltd.     

Watershed modelling of hydrology and water quality in the Sacramento River watershed,California

Agricultural pollutant runoff is a major source of water contamination in California's Sacramento River watershed where 8500 km² of agricultural land influences water quality. The Soil and Water Assessment Tool (SWAT) hydrology, sediment, nitrate and pesticide transport components were assessed for the Sacramento River watershed. To represent flood conveyance in the area, the model was improved by implementing a flood routing algorithm. Sensitivity/uncertainty analyses and multi‐objective calibration were incorporated into the model application for predicting streamflow, sediment, nitrate and pesticides (chlorpyrifos and diazinon) at multiple watershed sites from 1992 to 2008. Most of the observed data were within the 95% uncertainty interval, indicating that the SWAT simulations were capturing the uncertainties that existed, such as model simplification, observed data errors and lack of agricultural management data. The monthly Nash–Sutcliffe coefficients at the watershed outlet ranged from 0.48 to 0.82, indicating that the model was able to successfully predict streamflow and agricultural pollutant transport after calibration. Predicted sediment loads were highly correlated to streamflow, whereas nitrate, chlorpyrifos and diazinon were moderately correlated to streamflow. This indicates that timing of agricultural management operations plays a role in agricultural pollutant runoff. Best management practices, such as pesticide use limits during wet seasons, could improve water quality in the Sacramento River watershed. The calibrated model establishes a modelling framework for further studies of hydrology, water quality and ecosystem protection in the study area. Copyright © 2012 John Wiley & Sons, Ltd.     

Multivariate adaptive regression splines for estimating riverine constituent concentrations

Regression-based methods are commonly used for riverine constituent concentration/flux estimation, which is essential for guiding water quality protection practices and environmental decision making. This paper developed a multivariate adaptive regression splines model for estimating riverine constituent concentrations (MARS-EC). The process, interpretability and flexibility of the MARS-EC modelling approach, was demonstrated for total nitrogen in the Patuxent River, a major river input to Chesapeake Bay. Model accuracy and uncertainty of the MARS-EC approach was further analysed using nitrate plus nitrite datasets from eight tributary rivers to Chesapeake Bay. Results showed that the MARS-EC approach integrated the advantages of both parametric and nonparametric regression methods, and model accuracy was demonstrated to be superior to the traditionally used ESTIMATOR model. MARS-EC is flexible and allows consideration of auxiliary variables; the variables and interactions can be selected automatically. MARS-EC does not constrain concentration-predictor curves to be constant but rather is able to identify shifts in these curves from mathematical expressions and visual graphics. The MARS-EC approach provides an effective and complementary tool along with existing approaches for estimating riverine constituent concentrations.     

Evaluation of floodplain variability considering impacts of climate change

In this study, an approach is presented for handling hydraulic uncertainties in the prediction of floodplain. Different factors affect river flood characteristics. Furthermore, the high changeability of flooding conditions leads to high variability of the inundation. River morphology is one of the most effective factors in river flood characteristics. This factor is influenced by sedimentation and erosion in the river cross sections, which affects the discharge variation. The depth and the width of the river cross section lead to an increase or decrease in the river flow path. This results in changes in the extent of the floodplain based on the generated rainfall. The inundated region boundaries are determined by utilizing the mean first‐order second‐moment analysis. The proposed method is applied to the Kajoo River in the south‐eastern part of Iran. Determination of floodplain uncertainty is a damage‐reduction policy in this region. Also, it is useful to prepare the necessary activities for overcoming the flood hazards. Climate change is the second effective factor on the floodplain uncertainties. Climate change affects the magnitude, extent and depth of inundation and it may intensify the flood problem. Therefore, the future rainfall pattern of the study area under climate change is simulated to evaluate its impacts on the river flow characteristic. Subsequently, a hydraulic routing model is used to determine floodplain. Finally, the copula function is used to estimate the joint probability of the changes in the inundation area due to changes in river morphology and the rainfall changes due to impacts of climate change. Results show that the uncertainties of the extent of floodplain are affected by climate change and river morphology, leading to noticeable changes in the magnitude and frequency of floods. Evaluating these impacts and estimating corresponding river discharges will help in the study of river dynamics, and will also contribute towards devising effective mitigation and management strategies. Copyright © 2010 John Wiley & Sons, Ltd.     

Input data resolution‐induced uncertainty in watershed modelling

The temporal‐spatial resolution of input data‐induced uncertainty in a watershed‐based water quality model, Hydrologic Simulation Program‐FORTRAN (HSPF), is investigated in this study. The temporal resolution‐induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log‐normal relation with time interval for temperature data while it exhibits a power‐law relation for rainfall data. The temporal‐scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash‐Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate‐nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log‐normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal‐scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non‐symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.     

Which catchment characteristics control the temporal dependence structure of daily river flows?

Hydrological classification systems seek to provide information about the dominant processes in the catchment to enable information to be transferred between catchments. Currently, there is no widely agreed‐upon system for classifying river catchments. This paper develops a novel approach to classifying catchments based on the temporal dependence structure of daily mean river flow time series, applied to 116 near‐natural ‘benchmark’ catchments in the UK. The classification system is validated using 49 independent catchments. Temporal dependence in river flow data is driven by the flow pathways, connectivity and storage within the catchment and can thus be used to assess the influence catchment characteristics have on moderating the precipitation‐to‐flow relationship. Semi‐variograms were computed for the 116 benchmark catchments to provide a robust and efficient way of characterising temporal dependence. Cluster analysis was performed on the semi‐variograms, resulting in four distinct clusters. The influence of a wide range of catchment characteristics on the semi‐variogram shape was investigated, including: elevation, land cover, physiographic characteristics, soil type and geology. Geology, depth to gleyed layer in soils, slope of the catchment and the percentage of arable land were significantly different between the clusters. These characteristics drive the temporal dependence structure by influencing the rate at which water moves through the catchment and/or the storage in the catchment. Quadratic discriminant analysis was used to show that a model with five catchment characteristics is able to predict the temporal dependence structure for un‐gauged catchments. This method could form the basis for future regionalisation strategies, as a way of transferring information on the precipitation‐to‐flow relationship between gauged and un‐gauged catchments. © 2014 The Authors. Hydrological Processes by published by John Wiley & Sons, Ltd.     

Simulating the surface waters of the Amazon River basin: impacts of new river geomorphic and flow parameterizations

This paper describes the impacts of new river geomorphic and flow parameterizations on the simulated surface waters dynamics of the Amazon River basin. Three major improvements to a hydrologic model are presented: (1) the river flow velocity equation is expanded to be dependent on river sinuosity and friction in addition to gradient forces; (2) equations defining the morphological characteristics of the river, such as river height, width and bankfull volume, are derived from 31 622 measurements of river morphology and applied within the model; (3) 1 km resolution topographic data from the Shuttle Radar Topography Mission (SRTM) are used to provide physically based fractional flooding of grid cells from a statistical representation of sub‐grid‐scale floodplain morphology. The discharge and floodplain inundation of the Amazon River is simulated for the period 1968–1998, validated against observations, and compared with results from a previous version of the model. These modifications result in considerable improvement in the simulations of the hydrological features of the Amazon River system. The major impact is that the average wet‐season flooded area on the Amazon mainstem for the period 1983–1988 is now within 5% of satellite‐derived estimates of flooded area, whereas the previous model overestimates the flooded area by about 80%. The improvements are a consequence of the new empirical river geomorphologic functions and the SRTM topography. The new formulation of the flow velocity equation results in increased river velocity on the mainstem and major tributaries and a better correlation between the mean monthly simulated and observed discharge. Copyright © 2007 John Wiley & Sons, Ltd.     

The identifiability of parameters in a water quality model of the Biebrza River, Poland

The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The water quality model simulates the steady state concentration profiles of chloride, phosphate, ammonium, and nitrate as a function of distance along a river. The water quality model with the best combination of parameter values simulates the observed concentrations very well. However, the range of possible modelled concentrations obtained for other more or less equally eligible combinations of parameter values is rather wide. This range in model outcomes reflects possible errors in the model parameters. Discrepancies between the range in model outcomes and the validation data set are only caused by errors in model structure, or (measurement) errors in boundary conditions or input variables. In this sense the validation procedure is a test of model capability, where the effects of calibration errors are filtered out. It is concluded that, despite some slight deviations between model outcome and observations, the model is successful in simulating the spatial pattern of nutrient concentrations in the Biebrza River.     

A hydro‐economic modelling framework for flood damage estimation and the role of riparian vegetation

A modelling framework for the quick estimate of flood inundation and the resultant damages is developed in this paper. The model, called the flood economic impact analysis system (FEIAS), can be applied to a river reach of any hydrogeological river basin. For the development of the integrated modelling framework, three models were employed: (1) a modelling scheme based on the Hydrological Simulation Program FORTRAN model that was developed for any geomorphological river basin, (2) a river flow/floodplain model, and (3) a flood loss estimation model. The first sub‐model of the flood economic impact analysis system simulates the hydrological processes for extended periods of time, and its output is used as input to a second component, the river/floodplain model. The hydraulic model MIKE 11 (quasi‐2D) is the river/floodplain model employed in this study. The simulated flood parameters from the hydraulic model MIKE 11 (quasi‐2D) are passed, at the end of each time step, to a third component, the flood loss model for the estimation of flood damage. In the present work, emphasis was given to the seasonal variation of Manning's coefficient (n), which is an important parameter for the determination of the flood inundation in hydraulic modelling. High values of Manning's coefficient for a channel indicate high flow resistance. The riparian vegetation can have a large impact on channel resistance. The modelling framework developed in this paper was used to investigate the role of riparian vegetation in reducing flood damage. Moreover, it was used to investigate the influence of cutting riparian vegetation scenarios on the flow characteristics. The proposed framework was applied to the downstream part of the Koiliaris River basin in Crete, Greece, and was tested and validated with historical data. Copyright © 2012 John Wiley & Sons, Ltd.     

The comparative study of multi‐site uncertainty evaluation method based on SWAT model

With the recent development of distributed hydrological models, the use of multi‐site observed data to evaluate model performance is becoming more common. Distributed hydrological model have many advantages, and at the same time, it also faces the challenge to calibrate over‐do parameters. As a typical distributed hydrological model, problems also exist in Soil and Water Assessment Tool (SWAT) parameter calibration. In the paper, four different uncertainty approaches – Particle Swarm Optimization (PSO) techniques, Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting algorithm (SUFI‐2) and Parameter Solution (PARASOL) – are taken to a comparative study with the SWAT model applied in Peace River Basin, central Florida. In our study, the observed river discharge data used in SWAT model calibration were collected from the three gauging stations at the main tributary of the Peace River. Behind these approaches, there is a shared philosophy; all methods seek out many parameter set to fit the uncertainties due to the non‐uniqueness in model parameter evaluation. On the basis of the statistical results of four uncertainty methods, difficulty level of each method, the number of runs and theoretical basis, the reasons that affected the accuracy of simulation were analysed and compared. Furthermore, for the four uncertainty method with SWAT model in the study area, the pairwise correlation between parameters and the distributions of model fit summary statistics computed from the sampling over the behavioural parameter and the entire model calibration parameter feasible spaces were identified and examined. It provided additional insight into the relative identifiability of the four uncertainty methods Copyright © 2014 John Wiley & Sons, Ltd.     

Artificial neural network modelling of concentrations of nitrogen,phosphorus and dissolved oxygen in a non‐point source polluted river in Zhejiang Province,southeast China

A back‐propagation algorithm neural network (BPNN) was developed to synchronously simulate concentrations of total nitrogen (TN), total phosphorus (TP) and dissolved oxygen (DO) in response to agricultural non‐point source pollution (AGNPS) for any month and location in the Changle River, southeast China. Monthly river flow, water temperature, flow travel time, rainfall and upstream TN, TP and DO concentrations were selected as initial inputs of the BPNN through coupling correlation analysis and quadratic polynomial stepwise regression analysis for the outputs, i.e. downstream TN, TP and DO concentrations. The input variables and number of hidden nodes of the BPNN were then optimized using a combination of growing and pruning methods. The final structure of the BPNN was determined from simulated data based on experimental data for both the training and validation phases. The predicted values obtained using a BPNN consisting of the seven initial input variables (described above), one hidden layer with four nodes and three output variables matched well with observed values. The model indicated that decreasing upstream input concentrations during the dry season and control of NPS along the reach during average and flood seasons may be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data are available, the methodology developed here can easily be applied to other case studies. The BPNN model is an easy‐to‐use modelling tool for managers to obtain rapid preliminary identification of spatiotemporal water quality variations in response to natural and artificial modifications of an agricultural drainage river. Copyright © 2009 John Wiley & Sons, Ltd.     

Validation of a full hydrodynamic model for large‐scale hydrologic modelling in the Amazon

A key aspect of large river basins partially neglected in large‐scale hydrological models is river hydrodynamics. Large‐scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large‐scale hydrodynamic approach resultant from an improvement of the MGB‐IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS‐based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river‐floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd.     

Temporal and spatial rainfall analysis across a humid tropical catchment

Temporal and spatial rainfall patterns were analysed to describe the distribution of daily rainfall across a medium‐sized (379km²) tropical catchment. Investigations were carried out to assess whether a climatological variogram model was appropriate for mapping rainfall taking into consideration the changing rainfall characteristics through the wet season. Exploratory, frequency and moving average analyses of 30 years' daily precipitation data were used to describe the reliability and structure of the rainfall regime. Four phases in the wet season were distinguished, with the peak period (mid‐August to mid‐September) representing the wettest period. A low‐cost rain gauge network of 36 plastic gauges with overflow reservoirs was installed and monitored to obtain spatially distributed rainfall data. Geostatistical techniques were used to develop global and wet season phase climatological variograms. The unscaled climatological variograms were cross‐validated and compared using a range of rainfall events. Ordinary Kriging was used as the interpolation method. The global climatological variogram performed better, and was used to optimize the number and location of rain gauges in the network. The research showed that although distinct wet season phases could be established based on the temporal analysis of daily rainfall characteristics, the interpolation of daily rainfall across a medium‐sized catchment based on spatial analysis was better served by using the global rather than the wet season phase climatological variogram model. Copyright © 2001 John Wiley & Sons, Ltd.     

Measuring and modeling vertical gradients in suspended sediments in the Solimões/Amazon River

Accurately measuring sediment flux in large rivers remains a challenge due to the spatial and temporal cross‐sectional variability of suspended sediment concentrations in conjunction with sampling procedures that fail to accurately quantify these differences. This study presents a field campaign methodology that can be used to improve the measurement of suspended sediment concentrations in the Amazon River or similarly large rivers. The turbidity signal and Rouse model are together used in this study to define the spatial distribution of suspended sediment concentrations in a river cross‐section, taking into account the different size fractions of the sediment. With this methodology, suspended sediment fluxes corresponding to each sediment class are defined with less uncertainty than with manual samples. This paper presents an application of this methodology during a field campaign at different gauging stations along a 3,000‐km stretch of the Solimões/Amazon River during low water and flood periods. Vertical concentration profiles and Rouse model applications for distinctive sediment sizes are explored to determine concentration gradients throughout a cross‐section of the river. The results show that coupling both turbidity technology and the Rouse model may improve our understanding of the spatial distribution of different sediments fractions sizes in the Solimões/Amazon River. These data are very useful in defining a pertinent monitoring strategy for suspended sediment concentrations in the challenging context of large rivers.     

Numerical modelling of climate change impacts on Saint‐Lawrence River tributaries

The impacts of climate‐induced changes in discharge and base level in three tributaries of the Saint‐Lawrence River, Québec, Canada, are modelled for the period 2010–2099 using a one‐dimensional morphodynamic model. Changes in channel stability and bed‐material delivery to the Saint‐Lawrence River over this period are simulated for all combinations of seven tributary hydrological regimes (present‐day and those predicted using three global climate models and two greenhouse gas emission scenarios) and three scenarios of how the base level provided by the Saint‐Lawrence River will alter (no change, gradual fall, step fall). Even with no change in base level the projected discharge scenarios lead to an increase in average bed material delivery for most combinations of river and global climate model, although the magnitude of simulated change depends on the choice of global climate model and the trend over time seems related to whether the river is currently aggrading, degrading or in equilibrium. The choice of greenhouse gas emission scenario makes much less difference than the choice of global climate model. As expected, a fall in base level leads to degradation in the rivers currently aggrading or in equilibrium, and amplifies the effects of climate change on sediment delivery to the Saint‐Lawrence River. These differences highlight the importance of investigating several rivers using several climate models in order to determine trends in climate change impacts. Copyright © 2010 John Wiley & Sons, Ltd.     

Reconstructing fluvial incision rates based on palaeo-water tables in chalk karst networks along the Seine valley (Normandy,France)

Quantifying rates of river incision and continental uplift over Quaternary timescales offer the potential for modelling landscape change due to tectonic and climatic forcing. In many areas, river terraces form datable archives that help constrain the timing and rate of valley incision. However, old river terraces, with high-level deposits, are prone to weathering and often lack datable material. Where valleys are incised through karst areas, caves and sediments can be used to reconstruct the landscape evolution because they can record the elevation of palaeo-water tables and contain preserved datable material. In Normandy (N. France), the Seine River is entrenched into an extensive karstic chalk plateau. Previous estimates of valley incision were hampered by the lack of preserved datable fluvial terraces. A stack of abandoned phreatic cave passages preserved in the sides of the Seine valley can be used to reconstruct the landscape evolution of the region. Combining geomorphological observations, palaeomagnetic and U/Th dating of speleothem and sediments in eight caves along the Lower Seine valley, we have constructed a new age model for cave development and valley incision. Six identified cave levels up to ∼100 m a.s.l. were formed during the last ~1 Ma, coeval with the incision of the Seine River. Passage morphologies indicate that the caves formed in a shallow phreatic/epiphreatic setting, modified by sediment influxes. The valley's maximum age is constrained by the occurrence of late Pliocene marine sand. Palaeomagnetic dating of cave infills indicates that the highest-level caves were being infilled prior to 1.1 Ma. The evidence from the studied caves, complemented by fluvial terrace sequences, indicates that rapid river incision occurred during marine isotope stage (MIS) 28 to 20 (0.8–1 Ma), with maximal rates of ~0.30 m ka⁻¹, dropping to ~0.08 m ka⁻¹ between MIS 20–11 (0.8–0.4 Ma) and 0.05 m ka⁻¹ from MIS 5 to the present time. © 2020 John Wiley & Sons, Ltd.     

The Role of Groundwater for Lake‐Water Quality and Quantification of N Seepage

The heterogeneous nature of both groundwater discharge to a lake (inflow) and nitrate concentrations in groundwater can lead to significant errors in calculations of nutrient loading. Therefore, an integrated approach, combining groundwater flow and transport modelling with observed nitrate and ammonium groundwater concentrations, was used to estimate nitrate loading from a catchment via groundwater to an oligotrophic flow‐through lake (Lake Hampen, Denmark). The transport model was calibrated against three vertical nitrate profiles from multi‐level wells and 17 shallow wells bordering a crop field near the lake. Nitrate concentrations in groundwater discharging to the lake from the crop field were on average 70 times higher than in groundwater from forested areas. The crop field was responsible for 96% of the total nitrate loading (16.2 t NO₃/year) to the lake even though the field only covered 4.5% of the catchment area. Consequently, a small change in land use in the catchment will have a large effect on the lake nutrient balance and possible lake restoration. The study is the first known attempt to estimate the decrease of nitrate loading via groundwater to a seepage lake when an identified catchment source (a crop field) is removed.