Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.     

THE APPLICATION OF HYDROLOGIC MODELS TO SMALL WATERSHEDS HAVING MILD TOPOGRAPHY1

ABSTRACT: The application of hydrologic models to small watersheds of mild topography is not well documented. This study evaluates the applicability of hydrologic models described by Huggins and the Soil Conservation Service to small watersheds by comparing the simulated and actual hydrograph for both gaged and ungaged situations. The annual maximum rainfall events plus storms exceeding 2.5 inches from 25 years of rainfall and runoff data for two small watersheds were selected for the model evaluations. These storms had a variety of patterns and occurred on many different watershed conditions. Simulated and actual hydrographs were compared using a parameter which contained volume, peak, and shape factors. One-half of the selected storms were used to calibrate the models. For both models, there were no significant differences between the simulated and actual runoff volumes and peak runoff rates. Parameters obtained during the calibration process and relationships developed to estimate antecedent moisture and to modify tabulated runoff curve numbers were used to simulate the runoff hydrograph from the remaining storms. These remaining storms or test storms were simulated only once in order to imitate an ungaged situation. In general, both the Huggins and SCS model performed similarly on the test storms, but the level of model performance was lower than that for the calibration storms. For both models, the two-day antecedent rainfall was more important than the five-day in determining antecedent moisture and modifying tabulated curve numbers. The time of concentration which resulted in good hydrograph simulations was about three times larger than that estimated using published empirical relationships.     

APPLICATION OF RORB MODEL TO A CATCHMENT IN SINGAPORE1

ABSTRACT: Runoff Routing model (RORB) is a general model applicable to both rural and urban catchments. The performance of the model is illustrated through its simulation of flood runoff hydrographs in an urban catchment in Singapore. The essential feature of the model is the routing of rainfall excesses on subareas through some arrangement of concentrated storage elements, which represent the distribution of temporary storage of flood runoff on the watershed. This nonlinear routing procedure of the storage elements has two common parameters, k_c and m. With the limited data available, these two parameter values were determined through calibration runs. The same set of values of k_c and m were then used in the model to determine the runoff hydrographs of five other storms selected from the rainfall events between 1979 and 1981. It was found that the simulated runoff hydrographs matched reasonably well with the recorded hydrographs.     

APPLICATION OF SCS INFILTRATION MODEL1

ABSTRACT: The SCS infiltration model was applied to the Ralston Creek watershed in eastern Iowa. The criteria to determine the various model parameters were revised to obtain a better agreement between the observed and computed total runoffs. A procedure to calibrate the infiltration model is presented. The infiltration model was used in conjunction with an overland flow model to develop flood hydrographs. The results indicate that SCS infiltration model adequately describe the distribution of losses.     

Uncertainty assessment of the model RICEWQ in northern Italy

Model predictions are often seriously affected by uncertainties arising from many sources. Ignoring the uncertainty associated with model predictions may result in misleading interpretations when the model is used by a decision-maker for risk assessment. In this paper, an analysis of uncertainty was performed to estimate the uncertainty of model predictions and to screen out crucial variables using a Monte Carlo stochastic approach and a number of statistical methods, including ANOVA and stepwise multiple regression. The model studied was RICEWQ (Version 1.6.1), which was used to forecast pesticide fate in paddy fields. The results demonstrated that the paddy runoff concentration predicted by RICEWQ was in agreement with field measurements and the model can be applied to simulate pesticide fate at field scale. Model uncertainty was acceptable, runoff predictions conformed to a log-normal distribution with a short right tail, and predictions were reliable at field scale due to the narrow spread of uncertainty distribution. The main contribution of input variables to model uncertainty resulted from spatial (sediment-water partition coefficient and mixing depth to allow direct partitioning to bed) and management (time and rate of application) parameters, and weather conditions. Therefore, these crucial parameters should be carefully parameterized or precisely determined in each site-specific paddy field before the application of the model, since small errors of these parameters may induce large uncertainty of model outputs.     

ESTIMATING THE PROBABILITY OF EXCEEDING GROUNDWATER QUALITY STANDARDS1

ABSTRACT: A model for estimating the probability of exceeding groundwater quality standards at environmental receptors based on a simple contaminant transport model is described. The model is intended for locations where knowledge about site-specific hydrogeologic conditions is limited. An efficient implementation methodology using numerical Monte Carlo simulation is presented. The uncertainty in the contaminant transport system due to uncertainty in the hydraulic conductivity is directly calculated in the Monte Carlo simulations. Numerous variations of the deterministic parameters of the model provide an indication of the change in exceedance probability with change in parameter value. The results of these variations for a generic example are presented in a concise graphical form which provides insight into the topology of the exceedance probability surface. This surface can be used to assess the impact of the various parameters on exceedance probability.     

Hydrologic Modeling Uncertainty Resulting From Land Cover Misclassification1

Abstract: A stochastic, spatially explicit method for assessing the impact of land cover classification error on distributed hydrologic modeling is presented. One‐hundred land cover realizations were created by systematically altering the North American Landscape Characterization land cover data according to the dataset’s misclassification matrix. The matrix indicates the probability of errors of omission in land cover classes and is used to assess the uncertainty in hydrologic runoff simulation resulting from parameter estimation based on land cover. These land cover realizations were used in the GIS‐based Automated Geospatial Watershed Assessment tool in conjunction with topography and soils data to generate input to the physically‐based Kinematic Runoff and Erosion model. Uncertainties in modeled runoff volumes resulting from these land cover realizations were evaluated in the Upper San Pedro River basin for 40 watersheds ranging in size from 10 to 100 km² under two rainfall events of differing magnitudes and intensities. Simulation results show that model sensitivity to classification error varies directly with respect to watershed scale, inversely to rainfall magnitude and are mitigated or magnified by landscape variability depending on landscape composition.     

Sensitivity of SCS Models to Curve Number Variation1

ABSTRACT: The Soil Conservation Service (SCS) models, including the TR-20 computer program and the simplified methods in TR-55, are widely used in hydrologic design. The runoff curve number (CN), which is an important input parameter to SCS models, is defined in terms of land use tretments, hydrologic, condition, antecedent soil moisture, and soil type. The objective of this study was to evaluate the sensitivity of the SCS models to errors in CN estimates. The results show that the effects of CN variation decrease as the design rainfall depth increases, such as for the larger storm events. The value and use of the sensitivity curves are demonstrated using a comparison of Landsat and conventionally derived curve numbers for three watersheds in Pennsylvania.     

Modeling Watershed‐Scale Impacts of Stormwater Management with Traditional versus Low Impact Development Design

Stormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78 kg more nitrogen, 3 kg more phosphorus, and 1,592 kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.     

NORMALIZED UNIT HYDROGRAPH AGGREGATION1

ABSTRACT: The unit hydrograph is a common tool in hydraulic design. Used correctly, it allows a design engineer to estimate a runoff hydrograph from a drainage basin given a rainfall event. The typical method for estimating a unit hydrograph for a gaged watershed is by deconvolution. However, distinct storms produce different unit hydrographs for a single watershed. Consequently, a design engineer usually develops a composite, or average, unit hydrograph based on several recorded storm events. Common methods for estimating this composite unit hydrograph include curve fitting, simple aggregation, and multistorm optimization techniques. This paper introduces a new method to perform aggregation of unit hydrographs. The method is an extension to the simple averaging technique, in which prior to averaging, the individual unit hydrograph time ordinates are normalized with respect to the average time to peak. The normalization method is compared to a simple averaging technique and two multistorm aggregation techniques at six rural watersheds in Alabama. The results indicate that on average the normalization method predicts runoff nearly as accurately as the multistorm techniques, and displays improvement for 60 percent of the storms tested when compared with the simple averaging technique.     

FLOOD-RUNOFF FORECASTING WITH HEC1F1

HEC1F is a computer program for making short- to medium-term forecasts of uncontrolled flood runoff. The program employs unit hydrographs and hydrologic routing to simulate runoff from a subdivided basin. Estimates of future rainfall can be accommodated. Runoff parameters for gaged headwater subbasins can be estimated (optimized) in real time. Blending of calculated with observed hydrographs can be performed. HEC1F is a component of an on-line software system that includes capability for data acquisition and processing, precipitation analysis, streamflow forecasting, reservoir system analysis, and graphical display of data and simulation results. The conceptual framework for HEC1F is described, and application of the program is illustrated.     

VERIFICATION AND APPLICATION OF REGIONAL EQUATIONS FOR THE STORAGE FUNCTION RUNOFF MODEL1

The storage function model is a nonlinear rainfall-runoff model that has been developed for and applied to flood runoff analysis in Japan. This paper extends the model applicability by developing practical equations for estimating model parameters which are appropriate on a regional basis, i.e., so-called regional equations. Previously, the parameters were computed from historical data for a specific basin or from relationships that do not account for land use and topography. To develop the regionalized equations, model parameters were identified for 91 flood events from 22 watersheds in Japan by applying a mathematical optimization technique. Results from 39 of these events were statistically compared and regional relationships were determined as a function of land use, basin area and rainfall intensity. The utility of the estimated equations were tested by computing runoff hydrographs for lumped basins. The estimated parameters were also applied in a distributed watershed model formulation. Both applications showed acceptable results that validate the use of the regionalized relationships.     

Demonstrating Floodplain Uncertainty Using Flood Probability Maps1

Abstract: The U.S. Federal Emergency Management Agency (FEMA) flood maps depict the 100‐year recurrence interval floodplain boundary as a single line. However, because of natural variability and model uncertainty, no floodplain extents can be accurately defined by a single line. This article presents a new approach to floodplain mapping that takes advantage of accepted methodologies in hydrologic and hydraulic analysis while including the effects of uncertainty. In this approach, the extents of computed floodplain boundaries are defined as a continuous map of flood probabilities, rather than as a single line. Engineers and planners can use these flood probability maps for viewing the uncertainty of a floodplain boundary at any recurrence interval. Such a flood probability map is a useful tool for visualizing the uncertainty of a floodplain boundary and represents greater honesty in engineering technologies that are used for flood mapping. While institutional barriers may prevent adoption of such definitions for use in graduated flood insurance rates (as most other insurance industries use to account for relative risks), the methods open the door technically to such a reality.     

PLANNING OF URBAN BEST MANAGEMENT PRACTICES1

ABSTRACT: A “user-friendly” computer program has been developed for application in personal computers for preliminary design, evaluation, and cost effectiveness analysis of various best management practice (BMP) measures to control stormwater quantity and quality. The algorithms utilize the SCS TR-55 method for calculating runoff hydrographs for a single storm event and a first order pollutant washoff equation to generate pollutographs. Sensitivity analyses based on different policy scenarios is performed on a hypothetical watershed for the purpose of illustration. Three types of BMP measures, namely detention ponds (dry, wet, and extended wet ponds), infiltration trenches, and porous pavements are considered. It is found that the extended wet ponds have the best cost effective performance of the measures evaluated.     

DEVELOPMENT AND EVALUATION OF A DIMENSIONLESS UNIT HYDROGRAPH1

ABSTRACT: A generalized unit hydrograph method is developed and evaluated for ungaged watersheds. A key component in this method is the value of a dimensionless storage coefficient. Procedures to estimate this coefficient are given using calibrated values from 142 rainfall-runoff events gaged in watershed located mainly in the Eastern US. Only limited success was obtained in predicting this storage coefficient. Thirty-seven, independent rainfall-runoff events were used to test the proposed technique. The generalized unit hydrograph predicted the observed runoff hydrographs fairly well with considerable improvement in accuracy over the SCS dimensionless unit hydrograph. Approximately one-half of test storms had percent errors in predicted peak flow rates that were less than 34 percent compared to percent error of 88 percent with the SCS method.     

Eliciting preferences for wetland services: a way to manage conflicting land uses

A choice experiment was used to analyse the preferences of residents neighbouring the Erstein polder (Alsace, France) for the different services that it provides. The heterogeneous nature of these preferences was shown through the use of a latent class model. Whilst the population as a whole values the improvement in water quality and the contribution, even partial, to flood protection, preferences differ when it comes to biodiversity and public access to the site. This study shows the potential conflicts between the different uses of the Erstein polder. These conflicts represent different communication themes for the site managers.     

A PLANNING METHOD FOR EVALUATING DOWNSTREAM EFFECTS OF DETENTION BASINS1

While storm water detention basins are widely used for controlling increases in peak discharges that result from urbanization, recent research has indicated that under certain circumstances detention storage can actually cause increases in peak discharge rates. Because of the potential for detrimental downstream effects, storm water management policies often require downstream effects to be evaluated. Such evaluation requires the design engineer to collect additional topographic and land use data and make costly hydrologic analyses. Thus, a method, which is easy to apply and which would indicate whether or not a detailed hydrologic analysis of downstream impacts is necessary, should decrease the average cost of storm water management designs. A planning method that does not require either a large data base or a computer is presented. The time co-ordinates of runoff hydrographs are estimated using the time-of-concentration and the SCS runoff curve number; the discharge coordinates are estimated using a simple peak discharge equation. While the planning method does not require a detailed design of the detention basin, it does provide a reasonably accurate procedure for evaluating whether or not the installation of a detention basin will cause adverse downstream flooding.     

UNIT HYDROGRAPHS FOR DEVELOPING DESIGN FLOOD HYDROGRAPHS1

ABSTRACT: In Illinois, a procedure has been developed to derive unit hydrographs for generating 100-year and probable maximum flood hydrographs, on the basis of 11 parameters that define the hydrograph shape very well. Regional regressions of these parameters with basin factors show very high correlation. Thus satisfactory values of parameters can be determined for ungaged areas or those with a few years' record. The nonlinearity in unit hydrographs derived from usual floods is largely attributed to mixing within-channel and overbank-flow flood events. To minimize the effects of nonlinearity and to derive unit hydrographa suitable for calculating spillway design floods, use of the proposed method of developing such hydrographs is recommended.     

Simulation of Combined Best Management Practices and Low Impact Development for Sustainable Stormwater Management1

Damodaram, Chandana, Marcio H. Giacomoni, C. Prakash Khedun, Hillary Holmes, Andrea Ryan, William Saour, and Emily M. Zechman, 2010. Simulation of Combined Best Management Practices and Low Impact Development for Sustainable Stormwater Management. Journal of the American Water Resources Association (JAWRA) 1-12. DOI: 10.1111/j.1752-1688.2010.00462.x Abstract: Urbanization causes increased stormwater runoff volumes, leading to erosion, flooding, and the degradation of instream ecosystem health. Although Best Management Practices (BMPs) are used widely as a means for controlling flood runoff events, Low Impact Development (LID) options have been proposed as an alternative approach to better mimic the natural flow regime by using decentralized designs to control stormwater runoff at the source, rather than at a centralized location in the watershed. For highly urbanized areas, LID practices such as rainwater harvesting, green roofs, and permeable pavements can be used to retrofit existing infrastructure and reduce runoff volumes and peak flows. This paper describes a modeling approach to incorporate these LID practices in an existing hydrologic model to estimate the effects of LID choices on streamflow. The modeling approach has been applied to a watershed located on the campus of Texas A&M University in College Station, Texas, to predict the stormwater reductions resulting from retrofitting existing infrastructure with LID technologies. Results demonstrate that use of these LID practices yield significant stormwater control for small events and less control for flood events. A combined BMP-LID approach is tested for runoff control for both flood and frequent rainfall events.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.