Continuous Rainfall-runoff Model Research Articles

Application of SWMM for Water Resources Management by Continuous Rainfall-Runoff Modelling in the Rural Watershed of Kalu River Basin of Sri Lanka

"ENGINEER", established in 1973 by The Institution of Engineers, is a Journal for dissemination of Engineering knowledge, published quarterly.If you are interested in contributing an Original Technical Paper based on research by the author(s) (intended for Section I) or an Original Article of Professional or Technical interest related to Engineering. (Section II) to this journal please go through the publication checklist which can be downloaded from here.Cover DescriptionCover images show a few views of the Maduru Oya reservoir and construction of right bank canal. The Institution of Engineers, Sri Lanka, acknowledges Eng. L.D. Amila Sanjeewa of the Department of Irrigation for providing images and related information of the project.

An evidence for enhancing the design hydrograph estimation for small and ungauged basins in Ethiopia

Study regionEthiopia and Upper Blue Nile Basin. Study focusEstimating design hydrograph characteristics (e.g. flood peak discharge, volume and duration) is a crucial topic in hydrology and this is particularly challenging in data scarce regions. In recent years, significant innovations in hydrological modeling were introduced, allowing for more advanced analyses also in ungauged areas, in doing so limiting the application of empirical approaches (e.g. the rational formula). In the present work we summarize the current practice in Ethiopia and explore the possibility to apply a simplified continuous modeling for estimating design hydrographs. New hydrological insights for the regionThis study supports the conclusion that COSMO4SUB (Continuous Simulation Model for Small and Ungauged Basins) framework, a simplified continuous rainfall-runoff model specifically tailored for small and ungauged basins, can be applied in Ethiopia. Indeed, the minimal information available in the country are sufficient for applying such modeling approach, that can provide useful outputs for a variety of practical hydrological studies.

Continuous hydrologic modelling for small and ungauged basins: A comparison of eight rainfall models for sub-daily runoff simulations

Continuous hydrologic modelling is a natural evolution of the event-based design approach in modern hydrology. It improves the rainfall-runoff transformation and provides the practitioner with more effective hydrological output information for risk assessment. However, this approach is still not widely adopted, mainly because the choice of the most appropriate rainfall simulation model (which is the core of continuous frameworks) for the specific aim of risk analysis has not been sufficiently investigated. In this paper, we test eight rainfall models by evaluating the performances of the simulated rainfall time series when used as input for a simplified continuous rainfall-runoff model, the COSMO4SUB, which is particularly designed for small and ungauged basins. The comparison confirms the capability of all models to provide realistic flood events and allows identifying the models to be further improved and tailored for data-scarce hydrological risk applications. The suggested framework is transferable to any catchment while different hydrologic and rainfall models can be used.

Reducing Predictive Uncertainty in Real-Time Reservoir Operations by Coupling LARS-WG with ARNO Continuous Rainfall–Runoff Model

AbstractIn reservoirs with relatively low capacity-inflow (C/I) ratios, real-time daily operations provide the possibility of minimizing the risk of failure and meeting downstream demands sustainab...

Drought occurrence under future climate change scenarios in the Zard River basin, Iran

Abstract Global warming affected by human activities causes changes in the regime of rivers. Rivers are one of the most vital sources that supply fresh water. Therefore, management, planning, and proper use of rivers will be crucial for future climate change conditions. This study investigated the monitoring of hydrological drought in a future period to examine the impact of climate change on the discharging flow of the Zard River basin in Iran. Zard River is an important supplier of fresh and agricultural water in a vast area of Khuzestan province in Iran. A continuous rainfall-runoff model based on Soil Moisture Accounting (SMA) algorithm was applied to simulate the discharge flow under 10 scenarios (obtained from LARS-WG.6 software) of future climate change. Then, the Stream-flow Drought Index (SDI) and the Standard Precipitation Index (SPI) were calculated for each climate change scenario for the future period (2041–2060). The results of the meteorological drought assessment showed that near normal and moderate droughts had higher proportions among other drought conditions. Moreover, the hydrological drought assessment showed the occurrence of two new droughts (severe and extreme) conditions for the future period (2041–2060) that has never happened in the past (1997–2016).

WetSpa-Urban: An Adapted Version of WetSpa-Python, A Suitable Tool for Detailed Runoff Calculation in Urban Areas

A tool called WetSpa-Urban was developed to respond to the need for precise runoff estimations in an increasingly urbanized world. WetSpa-Urban links the catchment model WetSpa-Python to the urban drainage model Storm Water Management Model (SWMM). WetSpa-Python is an open-source, fully distributed, process-based model that accurately represents surface hydrological processes but does not simulate hydraulic structures. SWMM is a well-known open-source hydrodynamic tool that calculates pipe flow processes in an accurate manner while runoff is calculated conceptually. Merging these tools along with certain modifications, such as improving the efficiency of surface runoff calculation and simulating flow at the sub-catchment level, makes WetSpa-Urban suitable for event-based and continuous rainfall–runoff modeling for urban areas. WetSpa-Urban was applied to the Watermaelbeek catchment in Brussels, Belgium, which recently experienced rapid urbanization. The model efficiency was evaluated using different statistical methods, such as Nash–Sutcliffe efficiency and model bias. In addition, a statistical investigation, independent of time, was performed by applying the box-cox transformation to the observed and simulated values of the flow peaks. By speeding up the simulation of the hydrological processes, the performance of the surface runoff calculation increased by almost 130%. The evaluation of the simulated 10 minute flow versus the observed flow at the outlet of the catchment for 2015 reached a Nash–Sutcliffe efficiency of 0.86 and a bias equal to 0.06.

Automatic calibration of SWMM using NSGA-III and the effects of delineation scale on an urban catchment

Abstract The study aims at calibration of the storm water management model (SWMM) with non-dominated sorting genetic algorithm-III (NSGA-III) for urban catchment in Hyderabad, India. The SWMM parameters calibrated were Manning's roughness coefficient (N), depression storage for pervious and impervious areas (DP and Di), sub-catchment width (W), curve number (CN), drying time (dry) of soil and percentage of imperviousness (I). The efficacy of calibration was evaluated by comparing the observed and simulated peak flows and runoff using goodness-of-fit indices. The calibration takes into consideration eight event rainfalls resulting in eight calibrated sets. Weights of goodness-of-fit indices were estimated and the best calibrated set was further validated for five continuous rainfalls/runoffs. Simulated runoff volume and peak runoff over the five continuous rainfalls deviated by 7–22% and 2–20% with respect to observed data. Results indicated that parameters calibrated for an event rainfall could be used for continuous rainfall-runoff modelling. The effect of catchment delineation scale on runoff was also studied. The study indicated that output of the model was sensitive to variation in parameter values of infiltration and imperviousness.

Assessment of modern recharge to arid region aquifers using an integrated geophysical, geochemical, and remote sensing approach

The arid and semi-arid regions of the world are facing limited freshwater resources, minimal amounts of rainfall, and increasing population pressure and water demands. These resources, often groundwater, are vulnerable to both natural variability and anthropogenic interventions. Here, we develop and apply an integrated approach using geophysical, geochemical, and remote sensing observations to quantify the recharge rates of arid region aquifers that are witnessing rapid groundwater depletion. Focusing on the Saq aquifer system in the Arabian Peninsula, our study was three-fold: (1) to examine the areal extent of aquifer recharge domains using geologic, climatic, and remote sensing data; (2) to investigate the origin of, and modern contributions to, the aquifer system by examining the isotopic composition of groundwater samples; and (3) to estimate the magnitude of modern recharge to the aquifer utilizing estimates from the Gravity Recovery and Climate Experiment (GRACE) data and a continuous rainfall-runoff model, the Soil and Water Assessment Tool (SWAT) model. Isotopic examination of the groundwater from Saq revealed that deeper aquifers (fossil water) are more depleted compared to shallow reserves (alluvial aquifer; mixed waters). Analysis of GRACE-derived terrestrial and groundwater storage estimates indicates that the aquifer system received an annual recharge rate of 5.21 ± 0.10 km3/yr (11.85 ± 0.22 mm/yr), equal to about half of the withdrawal rate from wells during the investigation period (2002–2016). Analysis of SWAT results indicates that, from 1998 to 2014, the investigated watersheds received an average annual precipitation of 19.20 km3, of which approximately 51% is partitioned as potential recharge. The temporal variations in storage, depletion and recharge are related to the changes in regional groundwater extraction, rainfall, and extent of irrigated areas.

Exploiting Satellite-Based Surface Soil Moisture for Flood Forecasting in the Mediterranean Area: State Update Versus Rainfall Correction

Many satellite soil moisture products are today globally available in near real-time. These observations are of paramount importance for enhancing the understanding of the hydrological cycle and particularly useful for flood forecasting purposes. In recent decades, several studies assimilated satellite soil moisture observations into rainfall-runoff models to improve their flood forecasting skills. The rationale is that a better representation of the catchment states leads to a better stream flow estimation. By exploiting the strong physical connection between the soil moisture dynamic and rainfall, some recent studies demonstrated that satellite soil moisture observations can be also used for enhancing the quality of rainfall observations. Given that the quality of the rainfall is one of the main drivers of the hydrological model uncertainty, this begs the question—to what extent updating soil moisture states leads to better flood forecasting skills than correcting rainfall forcing? In this study, we try to answer this question by using rainfall-runoff observations from 10 catchments throughout the Mediterranean area and a continuous rainfall-runoff model—MISDc—forced with reanalysis- and satellite-based rainfall observations. Satellite soil moisture retrievals from the Advanced SCATterometer (ASCAT) are either assimilated into MISDc model via the Ensemble Kalman filter to update model states or, alternatively, used to correct rainfall observations derived from a reanalysis and a satellite-based product through the integration with soil moisture-based rainfall estimates. 4–9 years (depending on the catchment) of stream flow observations are organized into calibration and validation periods to test the two different schemes. Results show that the rainfall correction is favourable if the target is the predictions of high flows while for low flows there is a small advantage of the state correction scheme with respect to the rainfall correction. The improvements for high flows are particularly large when the quality of the rainfall is relatively poor with important implications for large-scale flood forecasting in the Mediterranean area.

Real-Time Flood Forecasting and Information System for the State of Iowa

Abstract The Iowa Flood Center (IFC), established following the 2008 record floods, has developed a real-time flood forecasting and information dissemination system for use by all Iowans. The system complements the operational forecasting issued by the National Weather Service, is based on sound scientific principles of flood genesis and spatial organization, and includes many technological advances. At its core is a continuous rainfall–runoff model based on landscape decomposition into hillslopes and channel links. Rainfall conversion to runoff is modeled through soil moisture accounting at hillslopes. Channel routing is based on a nonlinear representation of water velocity that considers the discharge amount as well as the upstream drainage area. Mathematically, the model represents a large system of ordinary differential equations organized to follow river network topology. The IFC also developed an efficient numerical solver suitable for high-performance computing architecture. The solver allows the IFC to update forecasts every 15 min for over 1,000 Iowa communities. The input to the system comes from a radar-rainfall algorithm, developed in-house, that maps rainfall every 5 min with high spatial resolution. The algorithm uses Level II radar reflectivity and other polarimetric data from the Weather Surveillance Radar-1988 Dual-Polarimetric (WSR-88DP) radar network. A large library of flood inundation maps and real-time river stage data from over 200 IFC “stream-stage sensors” complement the IFC information system. The system communicates all this information to the general public through a comprehensive browser-based and interactive platform. Streamflow forecasts and observations from Iowa can provide support for a similar system being developed at the National Water Center through model intercomparisons, diagnostic analyses, and product evaluations.

Accuracy versus variability of climate projections for flood assessment in central Italy

Climatic extremes are changing and decision-makers express a strong need for reliable information on future changes over the coming decades as a basis for adaption strategies. In the hydrological-hydraulic context, to estimate changes on floods, a modeling chain composed by general circulation models (GCMs), bias correction (BC) methods, and hydrological modeling is generally applied. It is well-known that each step of the modeling chain introduces uncertainties, resulting in a reduction of the reliability of future climate projections. The main goal of this study is the assessment of the accuracy and variability (i.e., model accuracy, climate intermodel variability, and natural variability) on climate projections related to the present period. By using six different GCMs and two BC methods, the “climate intermodel variability” is evaluated. “Natural variability” is estimated through random realizations of stochastic weather generators. By comparing observed and simulated extreme discharge values, obtained through a continuous rainfall-runoff model, “model accuracy” is computed. The Tiber River basin in central Italy is used as a case study. Results show that in climate projections, model accuracy and climate intermodel variability components have to be clearly distinguished. For accuracy, the hydrological model is found to be the largest source of error; for variability, natural variability contributes for more than 75% to the total variability while GCM and BC have a much lower influence. Moreover, accuracy and variability components vary significantly, and not consistently, between catchments with different permeability characteristics.

A Study on Regionalization of Parameters for Sacramento Continuous Rainfall-Runoff Model Using Watershed Characteristics

The simulation of natural streamflow at ungauged basins is one of the fundamental challenges in hydrology community. The key to runoff simulation in ungauged basins is generally involved with a reliable parameter estimation in a rainfall-runoff model. However, the parameter estimation of the rainfall-runoff model is a complex issue due to an insufficient hydrologic data. This study aims to regionalize the parameters of a continuous rainfall-runoff model in conjunction with a Bayesian statistical technique to consider uncertainty more precisely associated with the parameters. First, this study employed Bayesian Markov Chain Monte Carlo scheme for the estimation of the Sacramento rainfall-runoff model. The Sacramento model is calibrated against observed daily runoff data, and finally, the posterior density function of the parameters is derived. Second, we applied a multiple linear regression model to the set of the parameters with watershed characteristics, to obtain a functional relationship between pairs of variables. The proposed model was also validated with gauged watersheds in accordance with the efficiency criteria such as the Nash-Sutcliffe efficiency, index of agreement and the coefficient of correlation.

HEC-HMS model for runoff simulation in a tropical catchment with intra-basin diversions – case study of the Deduru Oya river basin, Sri Lanka

Hydrological modeling is a commonly used tool by water resource planners to simulate the hydrological response in a basin due to precipitation for the purpose of management of basin water. With the increasing demand for limited water resources in every basin, careful management of water resources becomes more important. The Deduru Oya river in Sri Lanka supplies water to number of new and ancient irrigation systems and the management of water resources in the Deduru Oya river basin, which has an area of 2620 km2, is important for optimum utilization of water for these irrigation systems. This paper describes a case study of continuous rainfall-runoff modeling in part of the Deduru Oya basin with intra-basin diversions and storage irrigation systems using the Hydrologic Engineering Center – Hydrologic Modeling System (HEC–HMS) version 3.0.1 to estimate runoff in the Deduru Oya river. Long term daily rainfall data at several rain gauging stations, evaporation, land use and soil data in the river basin, daily river runoff at a stream gauging station, intra-basin diversions from the river into a storage reservoir, irrigation releases from the reservoir and drainage flow returned to the river from irrigation systems were used to set up the HEC-HMS model. Five-layer soil moisture accounting loss method, Clark unit hydrograph transformation method, and recession base flow method of the HEC-HMS model were used. Temporally varying irrigation water uses, storages and losses in the basin were taken into account in the analysis. The results depict the capability of HEC–HMS to reproduce stream flows in the basin to a high accuracy with averaged computed Nash Sutcliffe efficiencies of 0.80. The study demonstrates potential HEC–HMS application in flow estimation from tropical catchments with intra-basin diversions and irrigation storages. The model developed is a tool for water management in the Deduru Oya river basin. ENGINEER, Vol. 48, No.01, pp. 1-9, 2015

The Use of H-SAF Soil Moisture Products for Operational Hydrology: Flood Modelling over Italy

The ever-increasing availability of new remote sensing and land surface model datasets opens new opportunities for hydrologists to improve flood forecasting systems. The current study investigates the performance of two operational soil moisture (SM) products provided by the “EUMETSATSatellite Application Facility in Support of Operational Hydrology and Water Management” (H-SAF, http://hsaf.meteoam.it/) within a recently-developed hydrological model called the “simplified continuous rainfall-runoff model” (SCRRM) and the possibility of using such a model at an operational level. The model uses SM datasets derived from external sources (i.e., remote sensing and land surface models) as input for calculating the initial wetness conditions of the catchment prior to the flood event. Hydro-meteorological data from 35 Italian catchments ranging from 800 to 7400 km2 were used for the analysis for a total of 593 flood events. The results show that H-SAF operational products used within SCRRM satisfactorily reproduce the selected flood events, providing a median Nash–Sutcliffe efficiency index equal to 0.64 (SM-OBS-1) and 0.60 (SM-DAS-2), respectively. Given the results obtained along with the parsimony, the simplicity and independence of the model from continuously-recorded rainfall and evapotranspiration data, the study suggests that: (i) SM-OBS-1 and SM-DAS-2 contain useful information for flood modelling, which can be exploited in flood forecasting; and (ii) SCRRM is expected to be beneficial as a component of real-time flood forecasting systems in regions characterized by low data availability, where a continuous modelling approach can be problematic.

Using globally available soil moisture indicators for flood modelling in Mediterranean catchments

Abstract. Floods are one of the most dangerous natural hazards in Mediterranean regions. Flood forecasting tools and early warning systems can be very beneficial to reducing flood risk. Event-based rainfall–runoff models are frequently employed for operational flood forecasting purposes because of their simplicity and the reduced number of parameters involved with respect to continuous models. However, the advantages related to the reduced parameterization oppose to the need of a correct initialization of the model, especially in areas characterized by strong climate seasonality. In this case, the use of continuous models could be desirable but it is very problematic in poorly gauged areas where continuous rainfall and temperature data are not available. This paper introduces a Simplified Continuous Rainfall–Runoff model (SCRRM), which uses globally available soil moisture retrievals to identify the initial wetness condition of the catchment, and, only event rainfall data to simulate discharge hydrographs. The model calibration involves only three parameters. For soil moisture, besides in situ data, satellite products from the Advanced SCATterometer (ASCAT) and the Advanced Microwave Scanning Radiometer for Earth observation (AMSR-E) sensors were employed. Additionally, the ERA-Land reanalysis soil moisture product of the European Centre for Medium-Range Weather Forecasting (ECMWF) was used. SCRRM was tested in the small catchment of the Rafina River, 109 km2, located in the eastern Attica region, Greece. Specifically, sixteen recorded rainfall–runoff events were simulated by considering the different indicators for the estimation of the initial soil moisture conditions from in situ, satellite and reanalysis data. By comparing the performance of the different soil moisture products, we conclude that: (i) all global indicators allow for a fairly good reproduction of the selected flood events, providing much better results than those obtained from setting constant initial conditions; (ii) the use of all the indicators yields similar results when compared with a standard continuous simulation approach that, however, is more data demanding; (iii) SCRRM is robust since it shows good performances in validation for a significant flood event that occurred on February 2013 (after calibrating the model for small to medium flood events). Due to the wide diffusion of globally available soil moisture retrievals and the limited number of parameters used, the proposed modelling approach is very suitable for runoff prediction in poorly gauged areas.

Application of a continuous Rainfall-Runoff model to the basin of Kosynthos river using the hydrological software HEC-HMS

<div>
 <h1 style="text-align: justify;"><span style="font-size:11px;"><span style="font-family:arial,helvetica,sans-serif;">In this paper, the application of a continuous rainfall-runoff model to the basin of Kosynthos River (district of Xanthi, Thrace, northeastern Greece), as well as the comparison of the computational runoff results with field discharge measurements are presented. The rainfall losses are estimated by the widely known Soil Conservation Service-Curve Number model, while the transformation of rainfall excess into direct runoff hydrograph is made by using the dimensionless unit hydrograph of Soil Conservation Service. The baseflow is computed by applying an exponential recession model. The routing of the total runoff hydrograph from the outlet of a sub-basin to the outlet of the whole basin is achieved by the Muskingum-Cunge model. The application of this complex hydrologic model was elaborated with the HEC-HMS 3.5 Hydrologic Modeling System of the U.S. Army Corps of Engineers. The results of the comparison between computed and measured discharge values are very satisfactory.</span></span></h1>
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Impact of Climate Change on Flood Frequency Using Different Climate Models and Downscaling Approaches

AbstractThe analysis of the climate change impact on flood frequency represents an important issue for water resources management and flood risk mitigation. However, for small/medium catchments ( 40,000 km2) and downscaling procedures are required. In this paper, two different GCMs selected among the Coupled Model Intercomparison Project 3 models, the Hadley Center Coupled Model, the Parallel Climate Model, and two statistical downscaling approaches, (1) delta change, and (2) quantile mapping, are compared. For the generation of long hourly time series of rainfall, temperature, and discharge, stochastic weather generators coupled with a continuous rainfall-runoff model are employed. Therefore, the frequency of annual maxima rainfall and discharge is projected for the future period 2070–2099 over three small subcatchments in the Upper Tiber River Basin, central Italy. Results reveal that both the GCMs...

Application of a model-based rainfall-runoff database as efficient tool for flood risk management

Abstract. A framework for a comprehensive synthetic rainfall-runoff database was developed to study catchment response to a variety of rainfall events. The framework supports effective flood risk assessment and management and implements simple approaches. It consists of three flexible components, a rainfall generator, a continuous rainfall-runoff model, and a database management system. The system was developed and tested at two gauged river sections along the upper Tiber River (central Italy). One of the main questions was to investigate how simple such approaches can be applied without impairing the quality of the results. The rainfall-runoff model was used to simulate runoff on the basis of a large number of rainfall events. The resulting rainfall-runoff database stores pre-simulated events classified on the basis of the rainfall amount, initial wetness conditions and initial discharge. The real-time operational forecasts follow an analogue method that does not need new model simulations. However, the forecasts are based on the simulation results available in the rainfall-runoff database (for the specific class to which the forecast belongs). Therefore, the database can be used as an effective tool to assess possible streamflow scenarios assuming different rainfall volumes for the following days. The application to the study site shows that magnitudes of real flood events were appropriately captured by the database. Further work should be dedicated to introduce a component for taking account of the actual temporal distribution of rainfall events into the stochastic rainfall generator and to the use of different rainfall-runoff models to enhance the usability of the proposed procedure.

관측자료 동화기법과 댐운영을 고려한 실시간 댐 수문량 예측모형 개발

본 연구의 목적은 앙상블 칼만필터링 기법과 연속형 강우-유출모형을 연계한 SURF 모형과Auto ROM을 결합한 실시간 댐 수문량 예측모형(DHVPM)을 개발하고 그 적용성을 평가하는데 있다. 대상유역은 충주댐 상류유역을 선정하였으며 2006~2009년 동안 연최대 유입량이 발생한 4개 사례를 선정하였다. 관측유량 자료동화 적용에 따른 선행시간 1시간 유입량에 대한 첨두유량 상대오차, 평균제곱근오차, 모형효율성계수를 산정한 결과, 2007년 첨두유량 상대오차 결과를 제외한 모든 사례에서 자료동화기법을 적용한 결과가 우수한 것으로 나타났다. 현시점으로 가정한 가상시점에서 예측 선행시간 10시간에 대해 유입량을 예측한 결과에서, 유역평균 강우량의 오차가 큰 경우에 대해 자료동화기법을 적용함으로써 예측 유입량의 오차가 줄어드는 것을 확인하였다. 이상의 결과로부터 실시간 예측유입량의 정확도를 향상시키기 위해서는 관측유입량의 실시간 활용이 가능한 환경에서 자료동화기법을 연계한 유입량 예측모형을 이용하는 것이 바람직할 것으로 판단된다. This study developed a real-time dam's hydrologic variables prediction model (DHVPM) and evaluated its performance for simulating historical dam inflow and outflow in the Chungju dam basin. The DHVPM consists of the Sejong University River Forecast (SURF) model for hydrologic modeling and an autoreservoir operation method (Auto ROM) for dam operation. SURF model is continuous rainfall-runoff model with data assimilation using an ensemble Kalman filter technique. The four extreme events including the maximum inflow of each year for 2006~2009 were selected to examine the performance of DHVPM. The statistical criteria, the relative error in peak flow, root mean square error, and model efficiency, demonstrated that DHVPM with data assimilation can simulate more close to observed inflow than those with no data assimilation at both 1-hour lead time, except the relative error in peak flow in 2007. Especially, DHVPM with data assimilation until 10-hour lead time reduced the biases of inflow forecast attributed to observed precipitation error. In conclusion, DHVPM with data assimilation can be useful to improve the accuracy of inflow forecast in the basin where real-time observed inflow are available.

A new river system modelling tool for sustainable operational management of water resources

The eWater Cooperative Research Centre of Australia has developed a river system modelling software called eWater Source that can be used to assist water managers and river operators in planning and operating river systems. It has been designed and developed within Australia to provide a consistent approach to underpin a wide range of water planning and management purposes. The software provides tools for the prediction and quantification of water from catchments to the end of a river system by integrating continuous rainfall-runoff and river system models. It includes three modes (catchment runoff, river management and river operations) for different applications. This paper introduces the operations mode of Source and compares its functionality with the existing tools used for daily river operations in Australia, with the Goulburn River as the case study. A 5-year period is used to compare modelled and observed results. Forecasts from Source and the existing tools are compared to observations over 7-day forecast periods that include an environmental water release. Source provided acceptable or improved results and required less user input than the existing method. Source provides a flexible software tool in which various forecast models can be incorporated. The application has demonstrated the potential of Source to provide an improvement on the existing river operations models in Australia at both the daily and seasonal time steps.