EFFECT OF RAINFALL EXCESS CALCULATIONS ON MODELED HYDROGRAPH ACCURACY AND UNIT-HYDROGRAPH PARAMETERS1

ABSTRACT: Two methods of computing rainfall excess in the U.S. Army Corps of Engineers’flood hydrograph package (HEC-1), the Initial and Uniform method and the Exponential method, are compared to evaluate the effects on modeled hydrograph accuracy. Two computed unit-hydrograph parameters, time of concentration and storage coefficient, were also compared. Rainfall and runoff data from 209 storms in 32 gaged basins in Illinois were used to calibrate the HEC-1 model. Three hydrograph characteristics - sum of incremental flows, peak discharge, and time of peak discharge - were used to evaluate modeled hydrograph accuracy. Mean percent error for each basin and hydrograph characteristic was computed. An evaluation of the mean errors indicates that, although some bias in modeled hydrograph accuracy is evident, rainfall excess computed using either method results in a computed hydrograph accuracy that is within generally accepted limits. Application of a linear-regression model shows no significant differences in computed values of unit-hydrograph parameters.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

MODELING RAINFALL-RUNOFF PROCESS INCLUDING LOSSES1

ABSTRACT: Existing discrete, linear rainfall-runoff models generally require the effective rainfall of a given storm as the input for computing the runoff hydrograph. This paper proposes a method for estimating, simultaneously, the optimal values of model parameters and the rainfall losses frem the measured rainfall hyetograph and the runoff hydrograph. The method involves an ARMA model for the rainfall-runoff process and a nonlinear iterative technique. The number of model parameters to be estimated for the ARMA model is much less than the unit hydrograph model. Applications of the model to three different watersheds show that the computed runoff hydrographs agree well with the measurements.     

MONTHLY RUNOFF PREDICTIONS BASED ON RAINFALL FORECASTS IN A SMALL OKLAHOMA WATERSHED1

ABSTRACT: Conditions under which monthly rainfall forecasts translate into monthly runoff predictions that could support water resources planning and management activities were investigated on a small watershed in central Oklahoma. Runoff response to rainfall forecasts was simulated using the hydrologic model SWAT. Eighteen scenarios were examined that represented combinations of wet, average, and dry antecedent rainfall conditions, with wet, normal, and dry forecasted rainfall. Results suggest that for the climatic and physiographic conditions under consideration, rainfall forecasts could offer potential application opportunities in surface water resources but only under certain conditions. Pronounced wet and dry antecedent rainfall conditions were shown to have greater impact on runoff than forecasts, particularly in the first month of a forecast period. Large forecast impacts on runoff occurred under wet antecedent conditions, when the fraction of forecasted rainfall contributing to runoff was greatest. Under dry antecedent conditions, most of the forecasted rainfall was absorbed in the soil profile, with little immediate runoff response. Persistent three‐month forecasts produced stronger impacts on runoff than one‐month forecasts due to cumulative effects in the hydrologic system. Runoff response to antecedent conditions and forecasts suggest a highly asymmetric utility function for rainfall forecasts, with greatest decision‐support potential for persistent wet forecasts under wet antecedent conditions when the forecast signal is least dampened by soil‐storage effects. Under average and dry antecedent conditions, rainfall forecasts showed little potential value for practical applications in surface water resources assessments.     

Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model1

Harshburger, Brian J., Von P. Walden, Karen S. Humes, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2012. Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(4): 643‐655. DOI: 10.1111/j.1752‐1688.2012.00642.x Abstract: As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1‐15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt‐dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak‐flow value is typically low. The model performance was assessed by computing the coefficient of determination (R²), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R² value for the mean ensemble is >0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are >0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West.     

CALIBRATION OF SNYDER COEFFICIENTS FOR PENNSYLVANIA1

ABSTRACT Unit hydrograph theory is one of the most widely used techniques to predict surface runoff. The present study is concerned with the Snyder unit hydrograph and the calibration of the Snyder coefficients for Pennsylvania. Twenty-seven study basins were selected, located randomly across the state. With the rainfall and runoff recorded for several events for each basin (more than 500 events were analyzed) unit hydrographs were calculated and the Snyder coefficients determined. A map of the coefficients was drawn to illustrate the variability in the coefficients and two equations using multiple regression theory were developed. The unexplained variability of the coefficients suggests that upper and lower bounds on the peak flow might be placed on storm hydrographs developed for ungaged watersheds.     

AN APPLICATION RUNOFF MODEL STRATEGY FOR UNGAGED WATERSHEDS1

ABSTRACT: Mathematical models for predicting watershed surface flow responses are available, most of which are elaborate nonlinear numerical surface and channel flow models linked with infiltration models. Such models may be used to make predictions for ungaged areas, assuming an acceptable fitting of the model to the topography and roughness of the real system. For some application purposes, these models are impractical because of their complexity and expensive computer solutions. A procedure is developed that uses a complex model of an ungaged area to derive a simpler parametric nonlinear system model for repetitious simulation with input sequences. The predicted flow outputs are obtained with the simpler model at significant savings of money and time. The procedures for constructing a complex kinematic model of a 40 acre (161,880 m²) reference watershed and deriving the simpler system model are outlined. The results of predictions from both models are compared with a selected set of measured events, all having essentially the same initial conditions. Peak discharges ranged from 3 to 118 ft³/sec (0.085 to 3.34 m³/sec), which includes the largest event of record. The inherent limitations of lumped systems models are demonstrated, including the bias caused by their inability to model infiltration losses after rainfall ceases. Computer costs and times for the models were compared. The derived simple model has a cost advantage when repeated use of a model is required. Such an applications hydrologic model has an engineering tradeoff of reduced accuracy, and lumping bias, but is more economical for certain design purposes.     

Inferring Hydrograph Components from Rainfall and Streamflow Records Using a Kriging Method-Based Linear Cascade Reservoir Model1

Cheng, Shin-jen, 2010. Inferring Hydrograph Components From Rainfall and Streamflow Records Using a Kriging Method-Based Linear Cascade Reservoir Model. Journal of the American Water Resources Association (JAWRA) 46(6):1171–1191. DOI: 10.1111/j.1752-1688.2010.00484.x Abstract: This study investigates the characteristics of hydrograph components in a Taiwan watershed to determine their shapes based on observations. Hydrographs were modeled by a conceptual model of three linear cascade reservoirs. Mean rainfall was calculated using the block Kriging method. The optimal parameters for 42 events from 1966-2008 were calibrated using an optimal algorithm. Rationality of generated runoffs was well compared with a trusty model. Model efficacy was verified using seven averaged parameters with 25 other events. Hydrograph components were characterized based on 42 calibration results. The following conclusions were obtained: (1) except for multipeak storms, a correlation between base time of the surface runoff and soil antecedent moisture is a decreasing power relationship; (2) a correlation between time lag of the surface flow and soil antecedent moisture for single-peak storms is an increasing power relationship; (3) for single-peak events, times to peak of hydrograph components are an increasing power correlation corresponding to the peak time of rainfall; (4) the peak flows of hydrograph components are linearly proportional to that of total runoff, and the peak ratio for the surface runoff to total runoff is approximately 78 and 13% for subsurface runoff to total runoff; and (5) the relationships of total discharges have direct ratios between hydrograph components and observations of total runoffs, and a surface runoff is 60 and 32% for a subsurface runoff.     

Development and evaluation of the channel routing model and parameters within the National Water Model

The National Water Model (NWM) was deployed by the National Oceanic and Atmospheric Administration to simulate operational forecasts of hydrologic states across the continental United States. This paper describes the geospatial river network (“hydro-fabric”), physics, and parameters of the NWM, elucidating the challenges of extrapolating parameters a large scale with limited observations. A set of regression-based channel geometry parameters are evaluated for a subset of the 2.7 million NWM reaches, and the riverine compound channel scheme is described. Based on the results from regional streamflow experiments within the broader NWM context, the compound channel reduced the root mean squared error by 2% and improved median Nash–Sutcliffe efficiency by 16% compared with a non-compound formulation. Peak event analysis from 910 peak flow events across 26 basins matched from the US Flash Flood Observation Database revealed that the mean timing error is 3 h lagged behind the observations. The routing time step was also tested, for 5-min (default, operational setting) and 1-h increments. The model was computationally stable and able to convey the flood peaks, although the hydrograph shape and peak timing were altered.     

FLOOD EVENT MODELING - A STUDY OF TWO METHODS1

: Despite the advances in catchment modeling in recent years, engineers still face major problems in estimating flood flows. Application of unit hydrograph and runoff routing models to five United Kingdom catchments shows that either can be tuned to predict, on a test event, the routing effects of a catchment with equal accuracy. The larger remaining problem is the prediction of losses from rainfall and this study shows how alternative ways of describing the within event distribution of these losses can be an important factor controlling the success of the overall model. Other problems include the risks of extrapolation to larger events, baseflow separation methods, rainfall patterns, and inevitable errors in the data.     

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.     

A MODIFIED RATIONAL FORMULA FOR FLOOD DESIGN IN SMALL BASINS1

ABSTRACT: New formulas and procedures under the framework of the Rational Formula are presented that are applicable to flood design problems for a small basin if the geometry of the basin can be approximated as an ellipse or a rhombus. Instead of making the assumption in the traditional rational formula that the rainfall is uniformly distributed in the whole duration (D_w) of a design storm, the new method modifies that assumption as: the rainfall is uniformly distributed only in each time interval CD) of the design storm hyetograph, thus extending the rational formula applicable to the case that the rainfall duration is less than the basin concentration time (T_c). The new method can be applied to estimate the flood design peak discharge, and to generate the flood hydrograph simultaneously. The derivation of the formulas is provided in detail in this paper, and an example is also included to illustrate how to apply the new formulas to the flood design problems in small basins.     

COMPUTATION OF STAGE-DISCHARGE RELATIONSHIPS AFFECTED BY UNSTEADY FLOW1

ABSTRACT: The dynamic relationship between stage and discharge which is unique to a particular flood for a selected station along the river can be determined via a mathematical model based on the complete one-dimensional equations of unsteady flow, i.e., the equations for the conservation of mass and momentum of the flood wave, and the Manning equation which accounts for energy losses. By assuming the bulk of the flood wave moves as a kinematic wave, the need for spatial resolution of the flood can be eliminated, and only the time variation of either the discharge or stage at the selected station is necessary for the computation of the other. The mathematical model can be used in river forecasting to convert the forecast discharge hydrograph into a stage hydrograph which properly reflects the unique dynamic stage-discharge relationship produced by the variable energy slope of the flood discharge. The model can be used also in stream gaging to convert a recorded stage hydrograph into a discharge hydrograph which properly accounts for the effects of unsteady flow. The model is applied to several observed floods at selected stations along the Lower Mississippi, Red, and Atchafalaya Rivers. The root mean square errors between observed and computed discharges are in the range of 3 to 7 percent, values well within the accuracy of the observations. A simple, easily-applied graphical procedure is also provided for estimating the magnitude of the effect of the unsteady flow on stage-discharge ratings. As a general rule, the dynamic effect may be significant if the channel bottom slope is less than 0.001 ft/ft (about 5 ft/mi) when the rate of change of stage is greater than about 0.10 ft/hr.     

Mid‐Range Streamflow Forecasts Based on Climate Modeling – Statistical Correction and Evaluation1

Abstract: Mid‐range streamflow predictions are extremely important for managing water resources. The ability to provide mid‐range (three to six months) streamflow forecasts enables considerable improvements in water resources system operations. The skill and economic value of such forecasts are of great interest. In this research, output from a general circulation model (GCM) is used to generate hydrologic input for mid‐range streamflow forecasts. Statistical procedures including: (1) transformation, (2) correction, (3) observation of ensemble average, (4) improvement of forecast, and (5) forecast skill test are conducted to minimize the error associated with different spatial resolution between the large‐scale GCM and the finer‐scale hydrologic model and to improve forecast skills. The accuracy of a streamflow forecast generated using a hydrologic model forced with GCM output for the basin was evaluated by forecast skill scores associated with the set of streamflow forecast values in a categorical forecast. Despite the generally low forecast skill score exhibited by the climate forecasting approach, precipitation forecast skill clearly improves when a conditional forecast is performed during the East Asia summer monsoon, June through August.     

PREDICTING TEMPORAL AND SPATIAL FLOOD DYNAMICS USING A PRECALIBRATED MODEL1

ABSTRACT: A large storm in December 1990 allowed the evaluation of flood predictions from a hydrologic model (TOPMODEL) that had been previously calibrated on the West Fork of Walker Branch Watershed, a gauged 37.5 ha catchment near Oak Ridge, Tennessee. The model predicts both hydrograph dynamics and the spatial distribution of overland flow using an index based on topography. Maximum extent of overland flow during the storm was determined from patterns of leaf litter removal from valley bottoms. Both the flood hydrograph and the extent of overland flow were accurately predicted using model parameters obtained from a three-month period of normal flow conditions during 1983.     

History and Development of the NRCS Lag Time Equation1

Abstract: Many of the hydrologic methods that are used in engineering practice today resulted from the Spring Flood of 1936, which blanketed the Northeastern portion of the United States. Because of the flood damage that was caused by this rainfall‐snowmelt event, many federal agencies including the U.S. Army Corp of Engineers and the Soil Conservation Service (SCS) implemented the hydrologic theories that were available in the literature at this time and developed hydrologic procedures for design flow estimation. Sherman had recently published his unit hydrograph theory in 1932, and later in 1938 Snyder, who had been charged by the Water Resource Council to develop a synthetic unit hydrograph, published his famous paper. The SCS unit hydrograph theory was developed by Victor Mockus in the late 1950s. Most if not all of the theories at that time reported the rainfall‐runoff process for floods as a surface phenomenon, and as such those theories all required some type of a timing parameter to estimate watershed response time. This article documents the development of the SCS lag equation.     

Pesticide transport pathways from a sloped Litchi orchard to an adjacent tropical stream as identified by hydrograph separation

This study was performed to identify the transport pathways of pesticides from a sloped litchi ( Sonn.) orchard to a nearby stream based on a three-component hydrograph separation (baseflow, interflow, surface runoff). Dissolved silica and electrical conductivity were chosen as representative tracers. During the study period (30 d), 0.4 and 0.01% of the applied mass of atrazine and chlorpyrifos, respectively, were detected in the stream after 151 mm of rainfall. Baseflow (80-96%) was the dominant hydrological flow component, followed by interflow (3-18%) and surface runoff (1-7%). Despite its small contribution to total discharge, surface runoff was the dominant atrazine transport pathway during the first days after application because pesticide concentrations in the surface runoff flow component declined quickly within several days. Preferential transport with interflow became the dominant pathway of atrazine. Because chlorpyrifos was detected in the stream water only twice, it was not included in the hydrograph separation. A feature of the surface runoff pathway was the coincidence of pesticide and discharge peaks. In contrast, peak concentrations of pesticides transported by interflow occurred during the hydrograph recession phases. Stormflow generation and pesticide transport depended on antecedent rainfall. The combination of high-resolution pesticide concentration measurements with a three-component hydrograph separation has been shown to be a suitable method to identify pesticide transport pathways under tropical conditions.     

EVALUATING HSPF IN AN ARID,URBANIZED WATERSHED1

ABSTRACT: The Hydrologic Simulation Program‐FORTRAN (HSPF) is a powerful time variable hydrologic model that has rarely been applied in arid environments. Here, the performance of HSPF in southern California was assessed, testing its ability to predict annual volume, daily average flow, and hourly flow. The model was parameterized with eight land use categories and physical watershed characteristics. It was calibrated using rainfall and measured flow over a five‐year period in a predominantly undeveloped watershed and it was validated using a subsequent 4‐year period. The process was repeated in a separate, predominantly urbanized watershed over the same time span. Annual volume predictions correlated well with measured flow in both the undeveloped and developed watersheds. Daily flow predictions correlated well with measured flow following rain events, but predictions were poor during extended dry weather periods in the developed watershed. This modeling difficulty during dry‐weather periods reflects the large influence of, and the poor accounting in the model for, artificially introduced water from human activities, such as landscape overwatering, that can be important sources of water in urbanized arid environments. Hourly flow predictions mistimed peak flows, reflecting spatial and temporal heterogeneity of rainfall within the watershed. Model correlation increased considerably when predictions were averaged over longer time periods, reaching an asymptote after an 11‐hour averaging window.     

MODELING NORTH CASCADES ANNUAL RUNOFF DISTRIBUTION USING DRAINAGE BASIN ELEVATION DISTRIBUTION1

ABSTRACT: The annual distribution of flow in a drainage basin within a given region is a function of many factors. These may include annual distribution of rainfall, basin orientation, ground cover, or presence of glaciers. Since the North Cascades region of northern Washington State has little variation in precipitation distribution by month, and the region has significant snowpack, one would predict that in an unregulated basin, basin elevation would be one of the most important factors impacting an annual hydrograph distribution. Such a prediction can be made since the higher a drainage basin is, the larger the portion of runoff that would occur as late spring snowmelt. Given that there is a relationship between elevation distribution and annual hydrograph, the problem becomes one of how to use this relationship to model an ungaged basin's hydrograph. This study concludes that, within the North Cascades region and perhaps within other regions, an effective method of determining annual flow distribution is to model ungaged flows in the same manner as flows from a gaged basin with an elevation distribution similar to that of the subject basin.