River Discharge Measurements Research Articles

Comparing static and dynamic flood models in estuarine environments: a case study from south-east Australia

Static and dynamic flood models differ substantially in their complexity and their ability to represent environmental processes such as storm tide or riverine flooding. This study analysed spatial differences in flood extent between static (bathtub) and dynamic flood models (Delft3D) in estuarine environments with different morphology and hydrodynamics in order to investigate which approach is most suitable to map flooding due to storm surges and river discharge in estuarine environments. Time series of observed water levels and river discharge measurements were used to force model boundaries. Observational data, such as tidal gauge and water level logger measurements, satellite imagery and aerial photography, were used to validate modelling results. Flood extents were calculated including and excluding river discharge to quantify and investigate its effect on the mapping of flooding. Modelling results indicate that the mature estuarine system, which has largely infilled broad flood plains, requires a consideration of bottom friction and riverine discharge through dynamic modelling techniques, whereas static models may provide an alternative approach to map flooding at low cost and low computational expense in young lake-like estuarine systems that have not been infilled with sediments. Our results suggest that estuarine classifications based on geomorphological characteristics can potentially guide flood risk assessments in estuarine environments.

Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin

Abstract. River discharge measurements have proven invaluable to monitor the global water cycle, assess flood risk, and guide water resource management. However, there is a delay, and ongoing decline, in the availability of gauging data and stations are highly unevenly distributed globally. While not a substitute for river discharge measurement, remote sensing is a cost-effective technology to acquire information on river dynamics in situations where ground-based measurements are unavailable. The general approach has been to relate satellite observation to discharge measured in situ, which prevents its use for ungauged rivers. Alternatively, hydrological models are now available that can be used to estimate river discharge globally. While subject to greater errors and biases than measurements, model estimates of river discharge do expand the options for applying satellite-based discharge monitoring in ungauged rivers. Our aim was to test whether satellite gauging reaches (SGRs), similar to virtual stations in satellite altimetry, can be constructed based on Moderate Resolution Imaging Spectroradiometer (MODIS) optical or Global Flood Detection System (GFDS) passive microwave-derived surface water extent fraction and simulated discharge from the World-Wide Water (W3) model version 2. We designed and tested two methods to develop SGRs across the Amazon Basin and found that the optimal grid cell selection method performed best for relating MODIS and GFDS water extent to simulated discharge. The number of potential river reaches to develop SGRs increases from upstream to downstream reaches as rivers widen. MODIS SGRs are feasible for more river reaches than GFDS SGRs due to its higher spatial resolution. However, where they could be constructed, GFDS SGRs predicted discharge more accurately as observations were less affected by cloud and vegetation. We conclude that SGRs are suitable for automated large-scale application and offer a possibility to predict river discharge variations from satellite observations alone, for both gauged and ungauged rivers.

Saltwater intrusion in a subtropical estuary

River discharge, precipitation, wind, water level and salinity measurements were used to investigate saltwater intrusion in a subtropical estuary. The upstream limit of saltwater intrusion was defined by the position of the 2 g/kg isohaline (X2) as it changed each tidal cycle. Observations were obtained from November 2014 to November 2015 along the Suwannee River, at Florida's Big Bend. Observations provided information to construct a first-order autoregressive Markov-chain model and predict X2. The model predicts X2 from its position in the previous tidal cycle, from river discharge, from water level, from precipitation and from wind velocity. In order to capture the seasonality of the Suwannee River discharge, the analysis was done separately for high and low river discharge regimes. The high discharge regime for the particular year of observations coincided with the cold season and had a mean value of 360 m3/s. The low discharge regime overlapped with the warm season and had a mean of 198 m3/s. As expected, saltwater intrusion was inversely related to river discharge. Values of X2 were 0.4 km for a discharge of 377 m3/s, and 6 km for a discharge of 195 m3/s. The autoregressive model was able to reproduce the observed seasonality of saltwater intrusion in the Suwannee River. The model was then used to project values of X2 for different scenarios of climate change as represented by possible combinations of river discharge and water levels.

Retrieving river baseflow from SWOT spaceborne mission

The quantification of aquifer contribution to river discharge is of primary importance to evaluate the impact of climatic and anthropogenic stresses on the availability of water resources. Several baseflow estimation methods require river discharge measurements, which can be difficult to obtain at high spatio-temporal resolution for large basins. The future Surface Water and Ocean Topography (SWOT) satellite mission will provide discharge estimations for large rivers (>50–100 m wide) even in ungauged basins. The frequency of these estimations depends mainly on latitude and ranges from zero to more than ten values in the 21-day satellite cycle. This work aims at answering the following question: can baseflow be estimated from SWOT observations during the mission lifetime? An algorithm based on hydrograph separation by Chapman's filter was developed to automatically estimate the baseflow in a river network at regional scale (>10 000 km2). The algorithm was applied to the Seine river basin (75 000 km2, France) using the discharge time series simulated at daily time step by a coupled hydrological-hydrogeological model to obtain the reference baseflow estimations. The same algorithm is then forced with discharge time series sampled at SWOT observation frequency. The average baseflow is estimated with good accuracy for all the reaches which are observed at least once per cycle (relative bias less than 8%). The time evolution of baseflow is also rather well retrieved, with a Nash-Sutcliffe coefficient above 0.7 for 96% of the network length. An analysis of the effect of SWOT discharge uncertainties on baseflow estimation shows that bias is the component of discharge error that most contributes to the error on baseflow. Anyway, when the combined effect of SWOT discharge sampling and SWOT discharge uncertainties is considered, the error on baseflow estimates is slightly smaller than that on discharge. This work provides new potential for the SWOT mission in terms of global hydrological analysis and water cycle closure.

Analisis Awal Potensi Renewable Energy di Bawah Jembatan Aur Duri II Jambi

The city of Jambi is dibentangi River batanghari, study on utilization of renewable electricity in particular an against water power through Streams need to be consider for perencanan Micro Hydro power plant (PLTMH). Water conditions that can be utilized as a resource (resources) electric generator has a capacity of flow and elevation of water channel system. The main problems in hydropower generation is the availability of water of the river discharge as energy for propulsion power plant. Therefore it takes a specific technique to predict the potential flow of river water on all the time or signature debit River that can be used for energy micro hydro power plant, not the onset of rain with a long time as well as the condition of watersheds (DAS) that can cause critical flow of river water into small even dried up. River discharge measurements manually at any given time can only represent the volume of discharge of the River at the time of measurement is performed. Changes that occur due to the onset of rain in the next time, or decrease in discharge of the River because the groundwater deposits shrink, can not be observed with either it needs to be planned debit kontiniu for turbine generator round capacity taking into account the capacity of electricity from generators that can be optimally raised

Non-uniform grid based LBM for the Saint-Venant equations

A novel form of the lattice Boltzmann method for the Saint-Venant equations (LABSVE) is formulated and implemented. To eliminate equidistant property of the lattice structure being the major drawback of the LBM, and thus establish the LB model as tool for practical application (natural water bodies) fully competitive compared to the presently available computational models, new form of equilibrium distribution function (EDF) based on geometrically transformed Saint-Venant equations (SVE) is derived. Introducing the metric relation function between the physical and computational system, the non-uniform spatial discretization is managed by solving the transformed SVE rather than altering the symmetrical properties of lattice structure. Since the geometrical correlation between the two corresponding systems is introduced into the transformed SVE, the very basic structure of the LBM in terms of simplicity in implementing the boundary conditions and computational efficiency (owing to the parallel structure) is maintained and further improved by removing the limitations imposed by the equidistant lattice condition. Furthermore, the discharge-water level definition of the SVE as more applicable form when natural watercourses are considered, is applied. In this way the bed slope term is completely eliminated from the equations, establishing therefore a model more suitable for natural systems characterized by arbitrary cross sectional geometry. In order to test the proposed non-equidistant LABSVE model, steady flow in prismatic channel, unsteady flow in non-prismatic channel of simple cross section geometry, and unsteady flow along a Danube section is modelled. Additional simulations by using the HEC-RAS modelling tool are conducted in order to produce comparison basis for both unsteady simulations, while in case of the Danube River section actual water level and discharge measurements are additionally used for calibration and verification of the model. Very good agreement between compared results is obtained showing that the proposed non-equidistant form of the LABSVE is capable of solving complex environmental problems, maintaining the order of accuracy, simplicity and efficiency of the basic LBM.

Using a Helicopter to Measure River Discharge under Extreme Environmental Conditions: A Methodological Approach on the Sagavanirktok River, Alaska

River discharge is a critical variable in many aspects of hydrology, particularly river mechanics. Due to the importance of river discharge, the standards for performing measurements are already established. In the extreme environmental conditions of breakup in Arctic regions, field crews face significant challenges in carrying out measurements, including risks to personnel, equipment safety, and river access difficulties. The use of a helicopter in performing river discharge measurements with these challenges provides an alternative to using a boat. We present the details of measuring river discharge with the help of a helicopter along the braided Sagavanirktok River on the Alaska North Slope.

Hhaynu micro hydropower scheme: Mbulu – Tanzania comparative river flow velocity and discharge measurement methods

The objective of the study has been to determine the river discharge by measuring the river flow velocity using two different measurement methods together with the area method and compare the accuracy of the results.Two river flow velocity measurement methods were used, the floating method and the use of current meter. In floating method a floating object was used to determine the water flow velocity on the surface by allow a float to move a distance of 1 m along the river and record the time it takes to travel that distance in seconds. Ten readings were taken and manually recorded and the flow velocity was determined by taking the distance travel by the float (1 m) divide by the time taken by the float (in seconds). On the other hand, the current meter method measure directly the average flow velocity across the river depth, twenty readings were taken and recorded manually and the average velocity were calculated. The use of current meter display flow velocity directly without the need of calculations.The result shows that both methods produce very close value, but the floating method have displayed higher value of around + 2% than current meter method which is a good value, despite the fact that floating method measures the surface velocity and the use of calculation. Many literature highlighted the accuracy of flow velocity measurement using current meter due to the fact that it measures the average velocity across the river, but from the findings when the floating method flow velocity measurement is properly applied it will produce as accurate results as the current meter with a fraction of cost in terms of instrument cost and expertise requirement in measurements.The floating method flow velocity measurement method could be applicable as alternative to current meter in micro hydropower projects river flow measurements in rural areas of developing countries with limited funding and local expertise.

Stream Flow Modeling In Gin River Basin Using Swat Cup

Around the world, human activity and natural forces are reducing available water resources. Rivers play a vital role to provide the water requirements of humans and nature. The stream flow of a river is affected by both natural and human factors. River (stream) flow is generally simulated by using mathematical models, and they can be used to evaluate the response of rivers to changes in flow parameters. River Gin Ganga in the south of Sri Lanka, draining an area of 865.5 km2, is subject to rapid changes in land use apart from climate variability. In order to simulate the stream flow of Gin Ganga a SWAT (Soil and Water Assessment Tool) model (consisting of 43 sub-basins) was set-up, calibrated and validated. The model is calibrated (1983-1989) and validated (1990-1994) against monthly measured discharge at one location by using Sequential Uncertainty Fitting version 2 (SUFI-2) techniques. The performance of the calibration was evaluated using five objective functions including the coefficient of determination (R2), Nash-Sutcliff (NS) efficiency P-factor, R-factor and coefficient of determination divided by coefficient of regression (bR2). The model simulates the stream flow for 22 years. The Curve Number (CN2) parameter of the model was identified as the most sensitive and critical parameter (which had a positive correlation with runoff) for model calibration. The calibrated model may be further improved with measured river discharge data at other locations (if and when available). The model can be further used for analyzing: impacts of climatic and land use changes, sediment yields, water quality and flood risk. Keywords: Gin Ganga, Modelling, Stream flow, SUFI-2, SWAT

Direct measurements of meltwater runoff on the Greenland ice sheet surface

Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2 moulin-terminating internally drained catchment (IDC) on Greenland's midelevation (1,207-1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems.

Rectification of Image Velocity Results (RIVeR): A simple and user-friendly toolbox for large scale water surface Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV)

LSPIV (Large Scale Particle Image Velocimetry) and LSPTV (Large Scale Particle Tracking Velocimetry) are used as relatively low-cost and non-intrusive techniques for water-surface velocity analysis and flow discharge measurements in rivers or large-scale hydraulic models. This paper describes a methodology based on state-of-the-art tools (for example, that apply classical PIV/PTV analysis) resulting in large-scale surface-flow characterization according to the first operational version of the RIVeR (Rectification of Image Velocity Results). RIVeR is developed in Matlab and is designed to be user-friendly. RIVeR processes large-scale water-surface characterization such as velocity fields or individual trajectories of floating tracers. This work describes the wide range of application of the techniques for comparing measured surface flows in hydraulic physical models to flow discharge estimates for a wide range of flow events in rivers (for example, low and high flows).

Remote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information

Although river discharge is a fundamental hydrologic quantity, conventional methods of streamgaging are impractical, expensive, and potentially dangerous in remote locations. This study evaluated the potential for measuring discharge via various forms of remote sensing, primarily thermal imaging of flow velocities but also spectrally-based depth retrieval from passive optical image data. We acquired thermal image time series from bridges spanning five streams in Alaska and observed strong agreement between velocities measured in situ and those inferred by Particle Image Velocimetry (PIV), which quantified advection of thermal features by the flow. The resulting surface velocities were converted to depth-averaged velocities by applying site-specific, calibrated velocity indices. Field spectra from three clear-flowing streams provided strong relationships between depth and reflectance, suggesting that, under favorable conditions, spectrally-based bathymetric mapping could complement thermal PIV in a hybrid approach to remote sensing of river discharge; this strategy would not be applicable to larger, more turbid rivers, however. A more flexible and efficient alternative might involve inferring depth from thermal data based on relationships between depth and integral length scales of turbulent fluctuations in temperature, captured as variations in image brightness. We observed moderately strong correlations for a site-aggregated data set that reduced station-to-station variability but encompassed a broad range of depths. Discharges calculated using thermal PIV-derived velocities were within 15% of in situ measurements when combined with depths measured directly in the field or estimated from field spectra and within 40% when the depth information also was derived from thermal images. The results of this initial, proof-of-concept investigation suggest that remote sensing techniques could facilitate measurement of river discharge.

Estimation of Suspended Sediment Loads Using Copula Functions

Suspended sediment load (SSL) observations are usually less frequent than precipitation and river discharge measurements; therefore a reliable procedure is needed for the estimation of SSL. One year of precipitation, SSL, and discharge measurements at 20-min intervals were performed at the Kuzlovec torrent in Slovenia. The Frank copula was selected to construct an event-based model using the following variables: precipitation sum (P), peak discharge (Q), and SSL. The idea was to estimate the SSL based on the measured P and Q. The proposed model was additionally tested using the daily data from the Gornja Radgona station on the Mura River, for which 29 years of data were available and where Khoudraji-Liebscher copulas were used. The estimated SSL values using the copula were compared with different regression models. The proposed copula model yielded meaningful SSL estimates. Some performance criteria and tests indicated that the copula model gives a better fit to the measured data than other tested methods.

Purus River suspended sediment variability and contributions to the Amazon River from satellite data (2000–2015)

The Purus River is one of the major tributaries of Solimões River in Brazil, draining an area of 370,091km2 and stretching over 2765km. Unlike those of the other main tributaries of the Amazon River, the Purus River's sediment discharge is poorly characterized. In this study, as an alternative to the logistic difficulties and considering high monitoring costs, we report an experiment where field measurement data and 2700 satellite (MODIS) images are combined to retrieve both seasonal and interannual dynamics in terms of the Purus river sediment discharge near its confluence with the Solimões River. Field radiometric and hydrologic measurements were acquired during 18 sampling trips, including 115 surface water samples and 61 river discharge measurements. Remote sensing reflectance gave important results in the red and infrared levels. They were very well correlated with suspended sediment concentration. The values of R2 are greater than 0.8 (red band) and 0.9 (NIR band). A retrieval algorithm based on the reflectance in both the red and the infrared was calibrated using the water samples collected for the determination of the surface-suspended sediment concentration (SSS). The algorithm was used to calculate 16 years of SSS time series with MODIS images at the Purus River near its confluence with the Solimões River. Results from satellite data correlated with in situ SSS values validate the use of satellite data to be used as a tool to monitor SSS in the Purus River. We evidenced a very short and intense sediment discharge pulse with 55% of the annual sediment budget discharged during the months of January and February. Using river discharge records, we calculated the mean annual sediment discharge of the Purus River at about of 17 Mt·yr−1.

Evapotranspiration seasonality across the Amazon Basin

Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon Basin. We used in situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (∼ 1497 mm year−1) and the lowest values in the Solimões River basin (∼ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.

Modeling daily dissolved oxygen concentration using modified response surface method and artificial neural network: a comparative study

In the present study, two nonlinear mathematical modeling approaches, namely modified response surface method (MRSM) and multilayer perceptron neural network (MLPNN) were developed and compared for modeling daily dissolved oxygen (DO) concentration. The DO concentration and water quality variables data for several years, available from four stations operated by the United States Geological Survey, were used for developing the two models. The water quality data selected consisted of daily measured river discharge, water pH, specific conductance, water turbidity, and DO. The response surface methodology is modified based on the two steps for calibrating process. In the first regression step, the normalized input data were calibrated based on a linear function and then transferred by an inverse power function. In the second regression step, the input data from first step were used to calibrate a highly nonlinear third-order polynomial function. The accuracy of the proposed nonlinear MRSM is compared with the standard MLPNN using several error statistics such as root-mean-square error, mean absolute error, mean bias error, the coefficient of correlation, the Nash–Sutcliffe efficiency, and the Willmott index of agreement. The results obtained indicate that MRSM model performed best in comparison with the MLPNN for the all four stations.

Groundwater and surface-water interactions and impacts of human activities in the Hailiutu catchment, northwest China

The interactions between groundwater and surface water have been significantly affected by human activities in the semi-arid Hailiutu catchment, northwest China. Several methods were used to investigate the spatial and temporal interactions between groundwater and surface water. Isotopic and chemical analyses of water samples determined that groundwater discharges to the Hailiutu River, and mass balance equations were employed to estimate groundwater seepage rates along the river using chemical profiles. The hydrograph separation method was used to estimate temporal variations of groundwater discharges to the river. A numerical groundwater model was constructed to simulate groundwater discharges along the river and to analyze effects of water use in the catchment. The simulated seepage rates along the river compare reasonably well with the seepage estimates derived from a chemical profile in 2012. The impacts of human activities (river-water diversion and groundwater abstraction) on the river discharge were analyzed by calculating the differences between the simulated natural groundwater discharge and the measured river discharge. Water use associated with the Hailiutu River increased from 1986 to 1991, reached its highest level from 1992 to 2000, and decreased from 2001 onwards. The reduction of river discharge might have negative impacts on the riparian ecosystem and the water availability for downstream users. The interactions between groundwater and surface water as well as the consequences of human activities should be taken into account when implementing sustainable water resources management in the Hailiutu catchment.

Generation of 3‐D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

AbstractWe present a new methodology to combine spatially dense high‐resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3‐D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

Estimation of Amazon River discharge based on EOF analysis of GRACE gravity data

River discharge is a critical component for understanding hydrological processes and sustainable management of water resources. The importance of discharge observation has increased due to its potential extreme variation resulting from the projected climate change and stronger variability of precipitation and temperature in some large basins. However, inherent difficulties in ground-based observations and decreasing number of gauge stations hinder accurate measurement of global river discharge and its spatio-temporal variations. Various remote sensing methods have been examined as alternatives, however, they require ground measurements to convert their proxy measurements into the actual river discharge. In this study, we estimate the discharge at the Óbidos station and the mouth of the Amazon basin using the water storage variations derived from GRACE gravity data without relying on any auxiliary ground observations. We extract the water mass signal along the main stem of the river by applying the Empirical Orthogonal Function (EOF) for water storage variations over the basin. The relative water storage variations along the main stem derived from the EOF decomposition are highly correlated with in-situ discharge at the Óbidos. However, in high water season, the GRACE-based discharge is estimated larger than the in-situ observations, and the difference is particularly significant during the 2009 extreme flood season. We argue that the in-situ river discharge in 2009 was underestimated due to the missed water volume for the flow detouring around the Óbidos gauge station during the high-flow event. Net river discharge of the Amazon Basin to Atlantic Ocean is also estimated, and its annual discharge is about 23% larger than that of the Óbidos. In particular, 2009 river discharge to Atlantic Oceans is estimated as 1050Gton.

POINT AND NON-POINT-SOURCE NUTRIENT CIRCULATION MODELLING FOR THE TAKASAKI RIVER BASIN, CHIBA JAPAN

Nutrient discharge to the Takasaki River from different Point-Sources (PS) and Non-Point-Sources (NPS) are considered in this study. Land use types: agricultural areas, forests and urban areas are considered as NPS in the study. Nitrogen (N) and phosphorous (P) based nutrient discharges from different land use types have a significant contribution to the river water quality. Limitations in technical, human and financial resources impede efficient monitoring of those nutrients at watershed scale. At this end, numerical model would be a beneficial tool to understand and predict the water quality variations under different climatic and anthropological conditions. The Water and Energy transfer Processes (WEP) model coupled with nutrient transport processes is applied to understand the impact of NPS considering the land use distribution in the Takasaki River. Mainly six land use types are prevailing in the Takasaki River basin, namely forests, crops, bare lands, paddy fields, urban areas and water bodies. Initially two rainfall events were selected to check the performances of the model. During the first event, average measured river discharge, TN loading and TP loading were 21.51 m3/s, 108.04 g/s and 11.73 g/s, while the simulated averages were 17.67 m3/s, 86.24 g/s and 7.52 g/s respectively. In the case of second event, average measured river discharge, TN loading and TP loading were 22.52 m3/s, 88.74 g/s and 8.73 g/s while the simulated averages were 17.72 m3/s, 80.84 g/s and 7.65 g/s respectively. As the next step two sub basins within the Takasaki basin which are agriculture dominant and urban area dominant were also analyzed to understand the impacts in difference land use types and their loadings to the river.