GENETIC PROGRAMMING: A NEW PARADIGM IN RAINFALL RUNOFF MODELING1

ABSTRACT: Genetic Programming (GP) is a domain‐independent evolutionary programming technique that evolves computer programs to solve, or approximately solve, problems. To verify GP's capability, a simple example with known relation in the area of symbolic regression, is considered first. GP is then utilized as a flow forecasting tool. A catchment in Singapore with a drainage area of about 6 km² is considered in this study. Six storms of different intensities and durations are used to train GP and then verify the trained GP. Analysis of the GP induced rainfall and runoff relationship shows that the cause and effect relationship between rainfall and runoff is consistent with the hydrologic process. The result shows that the runoff prediction accuracy of symbolic regression based models, measured in terms of root mean square error and correlation coefficient, is reasonably high. Thus, GP induced rainfall runoff relationships can be a viable alternative to traditional rainfall runoff models.     

APPLICATION OF GREY MODEL TOWARD RUNOFF FORECASTING1

ABSTRACT: A reliable forecasting model is essential in real‐time flood forecasting for reducing natural damage. Efforts to develop a real‐time forecasting model over the past two decades have been numerous. This work applies the Grey model to forecast rainfall and runoff owing to the model's relative ability to predict the future using a small amount of historical data. Such a model significantly differs from the stochastic and deterministic models developed previously. Ten historical storm events from two catchment areas in northern Taiwan are selected to calibrate and verify the model. Results in this study demonstrate that the proposed models can reasonably forecast runoff one to four hours ahead, if the Grey error prediction method is further used to update the output of the model.     

ANN OUTPUT UPDATING OF LUMPED CONCEPTUAL RAINFALL/RUNOFF FORECASTING MODELS1

ABSTRACT: Artificial neural networks (ANNs) are tested for the output updating of one‐day‐ahead and three‐day‐ahead streamflow forecasts derived from three lumped conceptual rainfall/runoff (R‐R) models: the GR4J, the IHAC, and the TOPMO. ANN output updating proved superior to a parameter updating scheme and to the ‘simple’ output updating scheme, which always replicates the last observed forecast error. In fact, ANN output updating was able to compensate for large differences in the initial performance of the three tested lumped conceptual R‐R models, which the other tested updating approaches were not able to achieve. This is done mainly by incorporating input vectors usually exploited for ANN R‐R modeling such as previous rainfall and streamflow observations, in addition to the previous observed error. For one‐day‐ahead forecasts, the performance of all three lumped conceptual R‐R models, used in conjunction with ANN output updating, was equivalent to that of the ANN R‐R model. For three‐day‐ahead forecasts, the performance of the ANN‐output‐updated conceptual models was even superior to that of the ANN R‐R model, revealing that the conceptual models are probably performing some tasks that the ANN R‐R model cannot map. However, further testing is needed to substantiate the last statement.     

Mechanistic Simulation of Tree Effects in an Urban Water Balance Model1

Abstract: A semidistributed, physical‐based Urban Forest Effects – Hydrology (UFORE‐Hydro) model was created to simulate and study tree effects on urban hydrology and guide management of urban runoff at the catchment scale. The model simulates hydrological processes of precipitation, interception, evaporation, infiltration, and runoff using data inputs of weather, elevation, and land cover along with nine channel, soil, and vegetation parameters. Weather data are pre‐processed by UFORE using Penman‐Monteith equations to provide potential evaporation terms for open water and vegetation. Canopy interception algorithms modified established routines to better account for variable density urban trees, short vegetation, and seasonal growth phenology. Actual evaporation algorithms allocate potential energy between leaf surface storage and transpiration from soil storage. Infiltration algorithms use a variable rain rate Green‐Ampt formulation and handle both infiltration excess and saturation excess ponding and runoff. Stream discharge is the sum of surface runoff and TOPMODEL‐based subsurface flow equations. Automated calibration routines that use observed discharge has been coupled to the model. Once calibrated, the model can examine how alternative tree management schemes impact urban runoff. UFORE‐Hydro model testing in the urban Dead Run catchment of Baltimore, Maryland, illustrated how trees significantly reduce runoff for low intensity and short duration precipitation events.     

Comparative Analysis of Inundation Mapping Approaches for the 2016 Flood in the Brazos River,Texas

Accurate and timely flood inundation maps serve as crucial information for hydrologists, first‐responders, and decision makers of natural disaster management agencies. In this study, two modeling approaches are applied to estimate the inundation area for a large flooding event that occurred in May 2016 in the Brazos River: (1) Height Above the Nearest Drainage combined with National Hydrograph Dataset Plus (NHDPlus‐HAND) and (2) International River Interface Cooperative — Flow and Sediment Transport with Morphological Evolution of Channels (iRIC‐FaSTMECH). The inundation extents simulated from these two modeling approaches are then compared against the observed inundation extents derived from a Landsat 8 satellite image. The simulated results from NHDPlus‐HAND and iRIC‐FaSTMECH show 56% and 70% of overlaps with the observed flood extents, respectively. A modified version of the NHDPlus‐HAND model, considering networked catchment behaviors, is also tested with an improved fitness of 67%. This study suggests that NHDPlus‐HAND has the potential for real‐time continental inundation forecast due to its low computational cost and ease to couple with the National Water Model. Better performance of NHDPlus‐HAND can be achieved by considering the inter‐catchment flows during extreme riverine flood events. Overall, this study presents a comprehensive examination made of remote sensing compared with HAND‐based inundation mapping in a region of complex topography.     

RUNOFF MODELING OF A MOUNTAINOUS CATCHMENT USING TOPMODEL: A CASE STUDY1

ABSTRACT: The rainfall‐runoff response of the Tygarts Creek Catchment in eastern Kentucky is studied using TOPMODEL, a hydrologic model that simulates runoff at the catchment outlet based on the concepts of saturation excess overland flow and subsurface flow. Unlike the traditional application of this model to continuous rainfall‐runoff data, the use of TOPMOEL in single event runoff modeling, specifically floods, is explored here. TOPMODEL utilizes a topographic index as an indicator of the likely spatial distribution of rainfall excess generation in the catchment. The topographic index values within the catchment are determined using the digital terrain analysis procedures in conjunction with digital elevation model (DEM) data. Select parameters in TOPMODEL are calibrated using an iterative procedure to obtain the best‐fit runoff hydrograph. The calibrated parameters are the surface transmissivity, T_O, the transmissivity decay parameter, m, and the initial moisture deficit in the root zone, S_r0. These parameters are calibrated using three storm events and verified using three additional storm events. Overall, the calibration results obtained in this study are in general agreement with the results documented from previous studies using TOPMODEL. However, the parameter values did not perform well during the verification phase of this study.     

Does the Temporal Resolution of Precipitation Input Influence the Simulated Hydrological Components Employing the SWAT Model?

This study aimed to evaluate the influence of sub‐daily precipitation time steps on model performance and hydrological components by applying the Green and Ampt infiltration method using the Soil and Water Assessment Tool (SWAT). Precipitation was measured at a resolution of 0.1 mm and aggregated to 5‐, 15‐, 30‐, and 60‐min time steps. Daily discharge data over a 10‐year period were used to calibrate and validate the model. Following a global sensitivity analysis, relevant parameters were optimized through an automatic calibration procedure using SWAT‐CUP for each time step. Daily performance statistics were almost equal among all four time steps (NSE ≈ 0.47). Discharge mainly consisted of groundwater flow (55%) and tile flow (42%), in reasonable proportions for the investigated catchment. In conclusion, model outputs were almost identical, showing simulations responded nearly independently of the chosen precipitation time step. This held true for (1) the selection of sensitive parameters, (2) performance statistics, (3) the shape of the hydrographs, and (4) flow components. However, a scenario analysis revealed that the precipitation time step becomes important when saturated hydraulic conductivities are low and curve numbers are high. The study suggests that there is no need in using precipitation time steps <1 h for lowland catchments dominated by soils with a low surface runoff potential if daily flow values are being considered. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.     

The Watershed Flow and Allocation Model: An NHDPlus‐Based Watershed Modeling Approach for Multiple Scales and Conditions

The Watershed Flow and Allocation model (WaterFALL^®) provides segment‐specific, daily streamflow at both gaged and ungaged locations to generate the hydrologic foundation for a variety of water resources management applications. The model is designed to apply across the spatially explicit and enhanced National Hydrography Dataset (NHDPlus) stream and catchment network. To facilitate modeling at the NHDPlus catchment scale, we use an intermediate‐level rainfall‐runoff model rather than a complex process‐based model. The hydrologic model within WaterFALL simulates rainfall‐runoff processes for each catchment within a watershed and routes streamflow between catchments, while accounting for withdrawals, discharges, and onstream reservoirs within the network. The model is therefore distributed among each NHDPlus catchment within the larger selected watershed. Input parameters including climate, land use, soils, and water withdrawals and discharges are georeferenced to each catchment. The WaterFALL system includes a centralized database and server‐based environment for storing all model code, input parameters, and results in a single instance for all simulations allowing for rapid comparison between multiple scenarios. We demonstrate and validate WaterFALL within North Carolina at a variety of scales using observed streamflows to inform quantitative and qualitative measures, including hydrologic flow metrics relevant to the study of ecological flow management decisions.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

Runoff Storage Potential of Drained Upland Depressions on the Des Moines Lobe of Iowa

We present estimates of the volumetric storage capacities of currently drained upland depressions and catchment depressional specific storage and runoff storage indices for the Des Moines Lobe of Iowa (DML‐IA) subregion of the Prairie Pothole Region of North America. Storage capacities were determined using hydrologically enforced Light Detection and Ranging‐derived digital elevation models, and a unique geoprocessing algorithm. Depressional specific storage was estimated for each 12‐digit Hydrologic Unit Code (HUC12) watershed in the region from total catchment‐specific depressional storage volume and catchment area. Runoff storage indices were calculated using catchment depressional specific storage values and estimates of the amount of rainfall likely to fall within each watershed during sub‐annual and 1‐, 2‐, 5‐, and 10‐year 24‐h events. The 173,171 identified drained depressions in the DML‐IA can store up to 903.5 Mm³ of runoff. Most of this capacity is in depressions located in the north of the region. Specific storage varies from nearly 109 mm in the younger landscapes to <10 mm in older more eroded areas. For 95% of the HUC12 watersheds comprising the region, depressional storage will likely be exhausted by rainfall‐derived runoff in excess of a 1‐year 24‐h event. Rainfall amounts greater than a 5‐year 24‐h event will exceed all available depressional storage. Therefore, the capacity of drained depressions in the DML‐IA to mitigate flooding resulting from infrequent, but large, storm events is limited.     

Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering1

Caballero, Luis A., Alon Rimmer, Zachary M. Easton, and Tammo S. Steenhuis, 2012. Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering. Journal of the American Water Resources Association (JAWRA) 48(5): 1022‐1031. DOI: 10.1111/j.1752‐1688.2012.00668.x Abstract: Understanding the basic relationships between rainfall and runoff is vital for effective management and utilization of scarce water resources. Especially, this is important in Central America with widespread potable water shortage during the dry months of the monsoon. Potential good water sources are cloud forests, but little information concerning its potential is available to water supply engineers. Our objective is to define rainfall‐runoff‐base flow relationships for a cloud forest catchment. Flumes were installed for measuring river flow in four subwatersheds in La Tigra National Park, Honduras. One of the four watersheds was a 636‐ha subwatershed (WS1) with 60% cloud forest coverage. Precipitation averaged 1,130 mm/yr over the entire basin. About half of the total rainfall became runoff for the cloud forest watershed whereas, for the adjacent undisturbed forested watershed, the total discharge was <20% of the amount of precipitation. Infiltration rates were generally greater than rainfall rates. Therefore, most rainfall infiltrated into the soil, especially in the upper, steep, and well‐drained portions of the watershed. Direct runoff was generated from saturated areas near the river and exposed bedrock. This research provides compelling evidence that base flow is the primary contributor to streamflow during both wet and dry seasons in cloud forest catchments. Protecting these flow processes over time is critical for the sustained provision of potable water.     

EQUIVALENCE BETWEEN TOPMODEL AND THE NRCS CURVE NUMBER METHOD IN PREDICTING VARIABLE RUNOFF SOURCE AREAS1

An equivalence is proposed between two rainfall‐runoff methods with a long history of use in the United States and Europe. In watersheds where variable source areas dominate runoff, the two methods can have comparable probability distribution functions of moisture deficit, and therefore predict similar saturated runoff source areas. A novel approach is introduced to determine the S parameter in the Natural Resources Conservation Service (NRCS) method. This approach constrains S by the physical soil and topography characteristics of the catchment and depth to water table. The NRCS curve number method is at the core of many rainfall‐runoff models in hydrology. As a simple lumped parameter method, it is often scrutinized because it is not obvious how to derive S from catchment hydromorphological characteristics. The novel approach provides a clear physical meaning for S, allowing better estimation of this parameter in humid shallow water table environments where the variable source area can be the dominant runoff mechanism.     

ASSESSING FLOOD MITIGATION ALTERNATIVES IN SHIJR AREA IN METROPOLITAN TAIPEI1

The Keelung River Basin in northern Taiwan lies immediately upstream of the Taipei metropolitan area. The Shijr area is in the lower basin and is subject to frequent flooding. This work applies micromanagement and source control, including widely distributed infiltration and detention/ retention runoff retarding measures, in the Wudu watershed above Shijr. A method is also developed that combines a genetic algorithm and a rainfall runoff model to optimize the spatial distribution of runoff retarding facilities. Downstream of Wudu in the Shijr area, five dredging schemes are considered. If 10‐year flood flows cannot be confined in the channel, then a levee embankment that corresponds to the respective runoff retarding scheme will be required. The minimum total cost is considered in the rule to select from the regional flood mitigation alternatives. The results of this study reveal that runoff retarding facilities installed in the upper and middle parts of the watershed are most effective in reducing the flood peak. Moreover, as the cost of acquiring land for the levee embankment increases, installing runoff retarding measures in the upper portion of the watershed becomes more economical.     

Modeling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchment1

Shrestha, Rajesh R., Yonas B. Dibike, and Terry D. Prowse, 2011. Modeling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchment. Journal of the American Water Resources Association (JAWRA) 48(1): 74‐89. DOI: 10.1111/j.1752‐1688.2011.00592.x Abstract: This paper presents a modeling study on climate‐induced changes in hydrologic and nutrient fluxes in the Upper Assiniboine catchment, located in the Lake Winnipeg watershed. The hydrologic and agricultural chemical yield model, Soil and Water Assessment Tool (SWAT) was employed to model a 21‐year baseline (1980‐2000) and future (2042‐2062) periods with model forcings for future climates derived from three regional climate models (RCMs) and their ensemble means. The modeled future scenarios reveal that potential future changes in the climatic regime are likely to modify considerably hydrologic and nutrient fluxes. The effects of future changes in climatic variables, especially precipitation and temperature, are clearly evident in the resulting snowmelt and runoff regimes. The future hydrologic scenarios consistently show earlier onsets of spring snowmelt and discharge peaks, and higher total runoff volumes. The simulated nutrient loads closely match the dynamics of the future runoff for both nitrogen and phosphorus, in terms of earlier timing of peak loads and higher total loads. However, nutrient concentrations could decrease due to the higher rate of runoff increase. Overall, the effects of these changes on the nutrient transport regime need to be considered together with possible future changes in land use, crop type, fertilizer application, and transformation processes in the receiving water bodies.     

A Hydrologic Data Screening Procedure for Exploring Monotonic Trends and Shifts in Rainfall and Runoff Patterns

A thorough understanding of past and present hydrologic responses to changes in precipitation patterns is crucial for predicting future conditions. The main objectives of this study were to determine temporal changes in rainfall‐runoff relationship and to identify significant trends and abrupt shifts in rainfall and runoff time series. Ninety‐year rainfall and runoff time series datasets from the Gasconade and Meramec watersheds in east‐central Missouri were used to develop data screening procedure to assess changes in the rainfall and runoff temporal patterns. A statistically significant change in mean and variance was detected in 1980 in the rainfall and runoff time series within both watersheds. In addition, both the rainfall and runoff time series indicated the presence of nonstationary attributes such as statistically significant monotonic trends and/or change in mean and variance, which should be taken into consideration when using the time series to predict future scenarios. The annual peak runoff and the annual low flow in the Meramec watershed showed significant temporal changes compared to that in the Gasconade watershed. Water loss in both watersheds was found to be significantly increasing which is potentially due to the increase in groundwater pumping for water supply purposes.     

Impacts of Climate Change on Extreme Precipitation Events Over Flamingo Tropicana Watershed1

Abstract: Climate change, particularly the projected changes to precipitation patterns, is likely to affect runoff both regionally and temporally. Extreme rainfall events are expected to become more intense in the future in arid urban areas and this will likely lead to higher streamflow. Through hydrological modeling, this article simulates an urban basin response to the most intense storm under anthropogenic climate change conditions. This study performs an event‐based simulation for shorter duration storms in the Flamingo Tropicana (FT) watershed in Las Vegas, Nevada. An extreme storm, defined as a 100‐year return period storm, is selected from historical records and perturbed to future climatic conditions with respect to multimodel multiscenario (A1B, A2, B1) bias corrected and spatially disaggregated data from the World Climate Research Programme's (WCRP's) database. The cumulative annual precipitation for each 30‐year period shows a continuous decrease from 2011 to 2099; however, the summer convective storms, which are considered as extreme storms for the study area, are expected to be more intense in future. Extreme storm events show larger changes in streamflow under different climate scenarios and time periods. The simulated peak streamflow and total runoff volume shows an increase from 40% to more than 150% (during 2041‐2099) for different climate scenarios. This type of analysis can help evaluate the vulnerability of existing flood control system and flood control policies.     

Temporal Changes in Streamflow and Attribution of Changes to Climate and Landuse in Wisconsin Watersheds

Previous historic trends analyses on 21st Century hydrologic data in the United States generally focus on annual flow statistics and have continued to use USGS hydro‐climatic data network (HCDN) stations, although post‐1988 diversions and runoff regulations are not reflected in the HCDN. Using a more recent dataset, Geospatial Attributes of Gages for Evaluating Streamflow, version II (GAGES II), compiled by Falcone (2012), which includes more watersheds with reference conditions, a comprehensive analysis of changes in seasonal, and annual streamflow in Wisconsin watersheds is demonstrated. Given the pronounced influence of seasonal hydrology in Wisconsin watersheds, the objective of this study is to elucidate the nature of temporal (annual, seasonal, and monthly) changes in runoff. Considerable temporal and regional variability was found in annual and seasonal streamflow changes between the two historic periods 1951‐1980 and 1981‐2010 considered in the study. For example, the northern watersheds show relatively small changes in streamflow discharge ranging from ?6.0 to 4.2%, while the southern watersheds show relatively large increases in streamflow discharge ranging from 13.1 to 18.2%. To apportion streamflow changes to climate and nonclimatic factors, a method based on potential evapotranspiration changes is demonstrated. Results show that nonclimatic factors account for more than 60% of changes in annual runoff in Wisconsin watersheds considered in the study.     

Determining phosphorus release rates to runoff from selected Alberta soils using laboratory rainfall simulation

Phosphorus losses from agricultural land can cause accelerated eutrophication of surface water bodies. This study evaluated the use of soil test phosphorus (STP) levels to predict dissolved inorganic phosphorus (DIP) concentrations in runoff water from agricultural soils using laboratory rainfall simulation. The objectives of this study were to determine (i) to what extent STP concentrations can be used as a basis to predict P losses from Alberta soils and (ii) how extended rainfall simulation run times affected DIP losses. Soil samples collected from a total of 38 field sites, widely scattered throughout the southern half of Alberta, were subjected to rainfall simulation in the laboratory. The STP concentrations were determined using Miller-Axley, Norwest, Kelowna, Modified Kelowna Mehlich-III, and distilled water extraction methods. Each rainfall simulation event lasted for at least 90 min. Runoff samples were collected in time series for the duration of each simulation, during two distinct runoff intervals: (i) for the first 30 min of continuous runoff (T30) and (ii) for 40 min during runoff equilibrium (Teq). For all the STP extractants and both runoff intervals, the relationship with DIP-flow-weighted mean concentration (FWMC) was linear and highly significant with r2 values ranging from 0.74 to 0.96. However, the slopes of the resulting regression lines were, on average, 1.85 times greater for the T30 runoff interval over those computed for the Teq interval. Thus experimental methodology greatly influenced regression parameters, suggesting that more work was needed to verify these relationships under natural conditions. In addition, with many of the r2 values greater than 0.90 there would be little, if any, benefit derived by including soil properties in regression analysis.     

Temporal variability of surface runoff due to cropping systems in cultivated catchment areas: Use of the DIAR model for the assessment of environmental public policies in the Pays de Caux (France)

This article proposes the use of a new model, DIAR (Diagnostic Agronomique du Ruissellement, or Agronomic Assessment of Runoff), for the prediction of the timing of the risk of runoff. DIAR is dedicated to loamy soils which are very sensitive to surface crusting, leading to runoff, soil erosion and muddy flows. The approach is proposed for the north-western European loess belt regions where muddy flows severely impact human activities. The likelihood of runoff is assessed from the sequence of soil surface states generated by cultivation practices. DIAR is based on the calculation of curve number values, for each stage of the soil-surface-state sequence, for calculating runoff for each of these stages. In this study, DIAR is applied to a catchment of 912 ha, cultivated by 26 farmers in the Pays de Caux (Normandy, France) where infrastructures located at the outlet have been damaged several times by muddy flows. Local public authorities involved in reducing muddy flows are eager to limit the agricultural upstream runoff by extending the planting of mustard as a winter cover crop. We tested the efficiency of such a policy on the reduction of the mean runoff. We also tested the year-to-year variability of this efficiency using the acreages of four successive years (1999–2000 to 2002–2003). Finally, the cost-efficiency of the policy was also considered. Though we used the same weather scenario, the initial situation (without much mustard cover) showed a wide year-to-year variation in the total runoff. This variation can be associated with the structure of the farms that cultivate the catchment (Utilised Agricultural Area (UAA) of each farm and percentage of this UAA inside the catchment). Our results showed that the widespread planting of winter cover crops could reduce the runoff by 10–20% compared with the initial situation (depending on the year), and also reduce the year-to-year variability of runoff. For each of the 4 tested years, the cost of the infiltrated m³, due to each ha of mustard cover, decreases with the increase in mustard cover. It indicates that the present siting of the mustard cover is not as efficient as it could be. We should ask why farmers do not sow it elsewhere.