GENETIC PROGRAMMING AND ITS APPLICATION IN REAL‐TIME RUNOFF FORECASTING1

ABSTRACT: Genetic programming (GP), a relatively new evolutionary technique, is demonstrated in this study to evolve codes for the solution of problems. First, a simple example in the area of symbolic regression is considered. GP is then applied to real‐time runoff forecasting for the Orgeval catchment in France. In this study, GP functions as an error updating scheme to complement a rainfall‐runoff model, MIKE11/NAM. Hourly runoff forecasts of different updating intervals are performed for forecast horizons of up to nine hours. The results show that the proposed updating scheme is able to predict the runoff quite accurately for all updating intervals considered and particularly for updating intervals not exceeding the time of concentration of the catchment. The results are also compared with those of an earlier study, by the World Meteorological Organization, in which autoregression and Kalman filter were used as the updating methods. Comparisons show that GP is a better updating tool for real‐time flow forecasting. Another important finding from this study is that nondimensionalizing the variables enhances the symbolic regression process significantly.     

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.     

AN EVALUATION OF FLOOD FREQUENCY ESTIMATES BASED ON RAINFALL/RUNOFF MODELING1

ABSTRACT: An evaluation of flood frequency estimates simulated from a rainfall/runoff model is based on (1) computation of the equivalent years of record for regional estimating equations based on 50 small stream sites in Oklahoma and (2) computation of the bias for synthetic flood estimates as compared to observed estimates at 97 small stream sites with at least 20 years of record in eight eastern states. Because of the high intercorrelation of synthetic flood estimates between watersheds, little or no regional (spatial) information may be added to the network as a result of the modeling activity. The equivalent years of record for the regional estimating equations based totally on synthetic flood discharges is shown to be considerably less than the length of rainfall record used to simulate the runoff. Furthermore, the flood estimates from the rainfall/runoff model consistently underestimate the flood discharges based on observed record, particularly for the larger floods. Depending on the way bias is computed, the synthetic estimate of the 100-year flood discharge varies from 11 to 29 percent less than the value based on observed record. In addition, the correlation between observed and synthetic flood frequency estimates at the same site is also investigated. The degree of correlation between these estimates appears to vary with recurrence interval. Unless the correlation between these two estimates is known, it is not possible to compute a weighted estimate with minimum variance.     

CONTRIBUTIONS OF RAINFALL TO CONSTITUENT LOADS IN STORM RUNOFF FROM URBAN CATCHMENTS1

ABSTRACT: Rainfall is a significant source of some constituents, particularly nitrogen species, in storm runoff from urban catchments. Median contributions of rainfall to storm runoff loads of 12 constituents from 31 urban catchments, representing eight geographic locations within the United States, ranged from 2 percent for suspended solids to 74 percent for total nitrite plus nitrate nitrogen. The median contribution of total nitrogen in rainfall to runoff loads was 41 percent. Median contributions of total-recoverable lead in rainfall to runoff loads varied by as much as an order of magnitude between catchments in the same geographic location. This indicates that average estimates of rainfall contributions to constituent loading in storm runoff may not be suitable in studies requiring accurate constituent mass-balance computations.     

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.     

SYSTEMS FOR RAINFALL AND RUNOFF USE,TUCSON, ARIZONA1

Rainfall and runoff in the Tucson, Arizona, urban area can be used to augment residential and municipal water supplies. Residential rainfall-harvesting systems include a catchment surface, collection and concentration components, separation and treatment units, storage capacity and distribution capability. A system to control runoff can divert water from urban washes for use in parks or other landscaped areas or can be used to enhance recharge to groundwater reservoirs. A reduction in flood hazards or peaks is a concurrent benefit of controlling and diverting runoff.     

IMPROVED RAINFALL/RUNOFF ESTIMATES USING REMOTELY SENSED SOIL MOISTURE1

ABSTRACT: Remotely sensed soil moisture data measured during the Southern Great Plains 1997 (SGP97) experiment in Oklahoma were used to characterize antecedent soil moisture conditions for the Soil Conservation Service (SCS) curve number method. The precipitation‐adjusted curve number and the soil moisture were strongly related (r²= 0.70). Remotely sensed soil moisture fields were used to adjust the curve numbers and the runoff estimates for five watersheds, in the Little Washita watershed; the results ranged from 2.8 km² to 601.6 km². The soil moisture data were applied at two spatial scales, a finer one (800 m) measuring spatial resolution and a coarser one (28 km). The root mean square error (RMSE) and the mean absolute error (MAE) of the runoff estimated by the standard SCS method was reduced by nearly 50 percent when the 800 m soil moisture data were used to adjust the curve number. The coarser scale soil moisture data also significantly reduced the error in the runoff predictions with 41 percent and 28 percent reductions in MAE and RMSE, respectively. The results suggest that remote sensing of soil moisture, when combined with the SCS method, can improve rainfall runoff predictions at a range of spatial scales.     

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.     

WATER LOSS EQUATIONS AND COEFFICIENTS TO ESTIMATE RUNOFF FROM RAINFALL1

Infiltration models are based on physical characteristics of the soil and initial soil moisture. For a given soil it is based on the initial soil moisture distribution. A computer simulation model for flood runoff systems (FH-Model) was used to analyze 39 sets of rainfall-runoff data on four small watersheds ranging in size from 17 to 342 square kilometers located in the Yamaska River basin in Quebec. From these analyses, parameters and coefficients have been determined for a water loss (infiltration) equation. A method for determining the loss parameters, using a nonlinear least square curve fitting technique, is presented. Expressions were made to relate the loss parameters to antecedent precipitation. The equations were tested on 11 storm rainfall and runoff events on a watershed located in the same region and close agreements were found.     

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.     

NONLINEAR PROGRAMMING IN RIVER BASIN MODELING1

ABSTRACT: This paper explores the use of nonlinear programming in river basin water quality modelling. Applications recently reported in the literature, along with the author's experience with nonlinear programming, are reviewed. Results obtained using nonlinear programming are compared with the results obtained by other researchers using linear and dynamic programming to solve river basin water quality optimization problems. These water quality models have objective functions with continuous first partial derivatives, several inequality and variable bound constraints, and are of the form: minizie Σ^j=n_j=1Y_j(X_j) subject to Σ^j=n_j=1a_ijX_jb_i, i=1,2, …, m c_jX_jd_j, j= 1,2, …, n The variable X_i is the maximum allowable ratio of the BOD (biochemical oxygen demand) of the effluent outflow to the BOD of the wastewater inflow for treatment plant j, in the range c_j to d_j. The a_ijd and b_i are constants in the DO (dissolved oxygen) and BOD constraints. The resuks show, given certain assumptions about the data, that nonlinear programming is a better solution method for these problems than is either linear programming or dynamic programming.     

A SYSTEMS STUDY OF STORM RUNOFF PROBLEMS IN A NEW TOWN1

A system study was conducted on the use of a large number of small reservoirs dispersed throughout an urban community as a means of storm water pollution control. The study was based on an area within the “new city” of Columbia, Maryland. Water collected and stored in the reservoirs is treated for release or use in meeting sub-potable and potable water demands in the community. Design and performance criteria were developed for such a system. A simulation model and a computerized evaluation technique were used to select the optimal locations and system configurations. The results of this study indicated that such a system would be less expensive than a conventional engineering approach to storm water pollution control. Further, the benefits derived from use of the storm water as a water supply can offset a portion of the cost of pollution control. Several secondary benefits also result from this concept including erosion and sediment control, storm flow dampening, and recreational facilities. A program is now underway to demonstrate this concept in Columbia, Maryland.     

MODELING RUNOFF FROM VARIABLE SOURCE AREAS IN HUMID,SHALLOW WATER TABLE ENVIRONMENTS1

ABSTRACT: Variable Source Areas (VSAs) are zones with water saturated soils in forested wetlands fringing streams and creeks. Runoff from these areas is generated by saturation excess after a shallow water table rises and inundates the ground surface. In humid regions, like Florida and the Southeast, VSAs are believed to produce most of the runoff in shallow water table environments. Modeling the spatial extent and temporal fluctuation of a VSA is difficult because the formation of a VSA depends on a number of hydrological and morphological factors like rainfall intensity, soil texture, water table depth, and topographic attributes of the terrain. In this paper, we couple a digital elevation model with a two‐dimensional variable saturation model to illustrate the formation of a VSA at the hillside scale. The topography derived from the digital elevation model forms the upper domain geometry for the two‐dimensional finite element simulations of variable saturated flow. The objectives are: (1) to model the spatial and dynamic fluctuation of a VSA, and (2) to understand the roles of rainfall variability and terrain attributes on the formation of a VSA. Results show that hillsides with shallow water table depths, low saturated hydraulic conductivity, mild slopes, and concave slope curvature were more susceptible to runoff from a variable source. Runoff from a variable source showed little sensitivity to rainfall intensity. In general, landscapes with steep slopes generated a small VSA and a seepage face that vanished rapidly with time. In contrast, flat terrains are more amenable to VSA and retain ground surface inundation for longer periods of time.     

THE IMPORTANCE OF ACCURATE CURVE NUMBERS IN THE ESTIMATION OF STORM RUNOFF1

ABSTRACT: Storm runoff as calculated by the runoff curve number method is shown to be of varying sensitivity to both input rainfall and curve number. Using an assumed input error of 10%, a runoff error chart is given. Up to about 9 inches of rainfall, runoff is more sensitive to curve number than to rainfall. The importance of accurate curve number selection in this range is stressed.     

A TECHNIQUE FOR MEASURING RAINFALL POTENTIAL1

ABSTRACT The roles played by thermodynamic stability and precipitable water in the production of rainfall are of prime importance. These two variables have been combined into a “Rainfall Potential” function by the use of multivariate statistical techniques. Data from weather stations in southern New Mexico and southwest Texas were used in the study. The results appear promising for further investigation, possibly in relation to the occurrence of rare but extremely heavy rains     

A SIMULATION OF SMOOTH-VARIABLE INTENSITY RAINFALL PATTERNS1

ABSTRACT: Continuous rainfall patterns are currently simulated by approximating them by stair-stepped (piece-wise) patterns. The effects of this approximation on infiltration and runoff processes are not well known. A new technique for simulating smooth-variable intensity rainfall patterns is presented. This technique is based on the fundamental principles of a moving water head in a container. The proposed technique is general and capable of simulating any rainfall pattern. However, as the rainfall pattern gets more complicated, the equipment required for simulation becomes more involved. The proposed technique has been tested experimentally. A close agreement was found between the theoretical and experimental simulations. It is concluded that the proposed technique might be very useful in studying the infiltration and runoff processes under variable intensity rainfall, especially for simple convex patterns.     

DISTRIBUTED RUNOFF FORMULATION DESIGNED FOR A PRECISION AGRICULTURAL LANDSCAPE MODELING SYSTEM1

A precision scale landscape model designed for agricultural applications is described in this paper. The Precision Agricultural Landscape Modeling System (PALMS) is a combination of two process‐based models: a diffusive wave runoff model with ponding (described in detail) and a biosphere model with a crops module (briefly reviewed). Several innovations, including numerical formulations for the hydrologic properties of the soil surface with crusting, slope/tillage angle interactions, and change of roughness and detention storage with cumulative precipitation have been included. The model is compared to observations on one 1.8 ha field planted with maize and soybeans during four growing seasons, and one 24 ha field planted with maize during one growing season. Daily average soil moisture is simulated well (within 5 percent volumetric), except in extended runoff/ponding episodes. Physical processes not simulated in the model suggest possible explanations for model errors. Planned improvements for PALMS are also presented.     

ASSESSMENT OF STORMWATER RUNOFF FOR RECYCLE IN COOLING TOWERS AT KSC,FLORIDA1

ABSTRACT: In addition to measuring the quantity of stormwater runoff generated during ten rainfall events from the Vehicle Assembly Building (VAB) area of Kennedy Space Center (KSC), historical rainfall records were also used for determining the feasibility of implementing a program of stormwater recycling to air conditioning cooling towers. It was projected that 0.182 million gallons per day (MGD) of runoff would be generated from the VAR area during a year of average rainfall (48 inches); only 0.117 MGD is required for coolant makeup water in the VAR area. Due to the seasonal variations in rainfall, stormwater recycling may not always meet all the cooling water demands.     

A TRIANGULAR MODEL OF DIMENSIONLESS RUNOFF PRODUCING RAINFALL HYETOGRAPHS IN TEXAS1

ABSTRACT: A synthetic triangular hyetograph for a large data base of Texas rainfall and runoff is needed. A hyetograph represents the temporal distribution of rainfall intensity at a point or over a watershed during a storm. Synthetic hyetographs are estimates of the expected time distribution for a design storm and principally are used in small watershed hydraulic structure design. A data base of more than 1,600 observed cumulative hyetographs that produced runoff from 91 small watersheds (generally less than about 50 km²) was used to provide statistical parameters for a simple triangular shaped hyetograph model. The model provides an estimate of the average hyetograph in dimensionless form for storm durations of 0 to 24 hours and 24 to 72 hours. As a result of this study, the authors concluded that the expected dimensionless cumulative hyetographs of 0 to 12 hour and 12 to 24 hour durations were sufficiently similar to be combined with minimal information loss. The analysis also suggests that dimensionless cumulative hyetographs are independent of the frequency level or return period of total storm depth and thus are readily used for many design applications. The two triangular hyetographs presented are intended to enhance small watershed design practice in applicable parts of Texas.     

CHARGES FOR URBAN RUNOFF: ISSUES IN IMPLEMENTATION1

ABSTRACT: Maryland officials have identified stormwater utilities as a potential method of financing programs to control nutrients in urban stormwater runoff that are proposed in Maryland's Chesapeake Bay Nutrient Reduction Plan. This paper reviews a number of issues related to the equity, efficiency and acceptability of user charge schemes. Overall, charges are found to be preferable to property taxes from both equity and efficiency perspectives. In addition, evidence suggests that elected officials will support creation of utilities. Obstacles to the implementation of utilities are identified.