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.     

ESTIMATING RUNOFF VOLUMES FROM URBAN AREAS1

ABSTRACT: Estimations of runoff volumes from urban areas can be made by the equation Q = a A σ(P_e– b), where Q is the runoff volume, a is the part of the total area A Contributing to runoff, P_e is the rainfall amount for a single event, and b is the initial rainfall losses. For the evaluation of a and b, rainfall/runoff measurements were made in five areas of sizes between 0.035 km² and 1.450 km². By linear regression analysis of rainfall volumes versus runoff volumes, the initial rainfall losses were found to vary from 0.38 mm to 0.70 mm for the different areas. The parts of the areas contributing to runoff were found to be proportional to the impermeable parts of the mas. The equation is applicable in urban areas with well defined paved surfaces and roofs and with a negligible amount of runoff from permeable areas.     

Rainfall conditions and rainwater harvesting potential in the urban area of Khartoum

Runoff water management is among the inherent challenges which face the sustainability of the development of arid urban centers. These areas are particularly at risk from flooding due to rainfall concentration in few heavy showers. On the other hand, they are susceptible to drought. The capital of Sudan (Khartoum) stands as exemplary for these issues. Hence, this research study aims at investigating the potential of applying rainwater harvesting (RWH) in Khartoum City Center as a potential urban runoff management tool. Rapid urbanization coupled with the extension of impervious surfaces has intensified the heat island in Khartoum. Consequently, increased frequency of heat waves and dust storms during the dry summer and streets flooding during the rainy season have led to environmental, economical, and health problems. The study starts with exposing the rainfall behavior in Khartoum by investigating rainfall variability, number of raindays, distribution of rain over the season, probability of daily rainfall, maximum daily rainfall and deficit/surplus of rain through time. The daily rainfall data show that very strong falls of >30 mm occur almost once every wet season. Decreased intra- and inter-annual rainfall surpluses as well as increased rainfall concentration in the month of August have been taking place. The 30-year rainfall variability is calculated at decade interval since 1941. Increasing variability is revealed with 1981–2010 having coefficients of variation of 66.6% for the annual values and 108.8–118.0% for the wettest months (July–September). Under the aforementioned rainfall conditions, this paper then explores the potential of RWH in Khartoum City Center as an option for storm water management since the drainage system covers only 40% of the study area. The potential runoff from the 6.5 km² center area is computed using the United States Natural Resources Conservation Services method (US-NRCS), where a weighted Curve Number (CN) of 94% is found, confirming dominant imperviousness. Rainfall threshold for runoff generation is found to be 3.3 mm. A 24,000 m³ runoff generated from a 13.1 mm rainfall (with 80% probability and one year return period) equals the drainage system capacity. An extreme rainfall of 30 mm produces a runoff equivalent to fourfold the drainage capacity. It is suggested that the former and latter volumes mentioned above could be harvested by applying the rational method from 18% and 80% rooftops of the commercial and business district area, respectively. Based on the above results, six potential sites can be chosen for RWH with a total roof catchment area of 39,558 m² and potential rooftop RWH per unit area of 0.033 m³. These results reflect the RWH potential for effective urban runoff management and better water resources utilization. RWH would provide an alternative source of water to tackle the drought phenomenon.     

COMPUTATION OF RUNOFF REDUCTION CAUSED BY FARM PONDS1

ABSTRACT: A two-parameter farm pond storage index, FPSI, was Used to adjust computed surface. runoff using the partial area runoff contribution resulting from runoff captured by farm ponds. The validity of the index method was tested by fitting a continuous accounting version of the Soil Conservation Service curve number procedure to surface runoff data from each of three watersheds, first with and then without the FPSI routine. Evapotranspiration computed with the Jensen-Haise method and rainfall were input to the model. A linear relationship was assumed between the storage index and the portion of the controlled drainage area that was contributing to runoff. Adjusting the computed runoff with the FPSI reduced the coefficient of variation of monthly measured versus computed surface runoff for each of the three watersheds. The correlation coefficients for the same comparisons were increased. The annual predicted surface runoff Was improved for 12 of the 17 station years of data tested. The farm pond storage index could be used with any surface runoff model to improve the prediction of runoff from watersheds with drainage areas greater than 1 square mile and with about 20 percent or more of the drainage area controlled by farm ponds.     

耕作措施对土壤入渗产流影响的实验研究

采用人工模拟降雨和室内分析相结合的方法,研究了黄土区不同耕作措施对降雨入渗的影响。结果表明：①不同耕作管理措施对降雨入渗的影响效用不同,在相同雨强和坡度下,降雨入渗速率表现为：耙耱地〉人工掏挖〉直线坡,在中小雨强和较短滞后情况下,这种情况表现更为显著;②不同耕作管理措施对降雨产流的影响效用不同,在相同雨强和坡度下,产流滞后表现为：耙耱地〉人工掏挖〉直线坡,在中小雨强和较短滞后情况下,这种情况表现更为显著;③根据水量平衡原理,得出了不同耕作管理措施不同坡度下入渗及产流滞后随雨强的变化关系式。上述结果为黄土高原坡耕地水土流失的治理和管理,提供了一定的理论依据。     

Thermal Characteristics of Stormwater Runoff from Asphalt and Sod Surfaces1

Abstract: Urban impervious surfaces absorb and store thermal energy, particularly during warm summer months. During a rainfall/runoff event, thermal energy is transferred from the impervious surface to the runoff, causing it to become warmer. As this higher temperature runoff enters receiving waters, it can be harmful to coldwater habitat. In an urban watershed, impervious asphalt surfaces (roads, parking lots, and driveways) and pervious residential lawns comprise a significant portion of the watershed area. A paired asphalt‐turfgrass sod plot was constructed to compare the thermal runoff characteristics between asphalt and turfgrass sod surfaces, to identify meteorological variables that influence these thermal characteristics, and to evaluate evaporative heat loss for runoff from asphalt surfaces. Rainfall simulations were conducted during the summers of 2004 and 2005 under a range of climatic conditions. Asphalt surface temperatures immediately prior to rainfall simulations averaged 43.6°C and decreased an average of 12.3°C over 60 min as rain cooled the surface. In contrast, presimulation sod surface temperatures averaged only 23.3°C and increased an average of 1.3°C throughout the rainfall events. Heat transferred from the asphalt to the runoff resulted in initial asphalt runoff temperatures averaging 35.0°C that decreased by an average of 4.1°C at the end of the event. Sod runoff temperatures averaged only 25.5°C and remained fairly constant throughout the simulations. Multivariable regression equations were developed to predict (1) average asphalt surface temperature (R² = 0.90) and average asphalt runoff temperature (R² = 0.92) as a function of solar radiation, rain temperature, and wind speed, and (2) average sod surface temperature (R² = 0.85) and average sod runoff temperature (R² = 0.94) as a function of solar radiation, rain temperature, rain intensity, and wind speed. Based on a heat balance analysis, existing evaporation equations developed from studies on lakes were not adequate to predict evaporation from runoff on a heated impervious surface. The combined heat from the asphalt and sod plots was an average of 38% less than the total heat had the total area consisted solely of asphalt.     

Estimating Lag to Peak between Rainfall and Peak Streamflow with a Mixed‐Effects Model

We test the use of a mixed‐effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km²). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed‐effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15‐min rainfall depth for individual storms as explanatory features. Based on a remove‐one‐site cross‐validation analysis, the prediction errors of this model ranged from ?42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfall–runoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.     

RUNOFF AND SEDIMENT YIELD UNDER GRAZING IN FOOTHILLS FESCUE GRASSLANDS OF ALBERTA1

ABSTRACT: Grazing can have a profound impact on infiltration and thus runoff and erosion. The objectives of this study were to quantify the effects of select grazing systems on rainfall and snowmelt induced runoff and sediment yield from sloped areas of the foothills fescue grasslands of Alberta, Canada. The effects of two grazing intensities (heavy and very heavy) for two durations (short duration and continuous throughout the growing season) were compared to an ungrazed control between June 1988 and April 1991. Runoff was measured using 1-rn² runoff frames and collection bucket systems. Sediment yields were then determined on samples from the collected runoff. Snowmelt was the dominant source of runoff. Snowmelt runoff was higher from the heavily grazed areas than from the very heavily grazed areas, due to the higher standing vegetation which accumulated snow in the former areas. Sediment yields as a result of snowmelt were generally low in all areas. Only a few summer storms caused runoff. Runoff volumes and sediment yields from summer rainstorms were low, due to low rainfall and to generally dry antecedent soil moisture conditions. The greatest risk of summer runoff, and thus sediment yield, appears to occur in August.     

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.     

SEDIMENT,NITRATE, AND AMMONIUM IN SURFACE RUNOFF FROM TWO TAHOE BASIN SOIL TYPES 1

ABSTRACT: Few studies have addressed the natural pollution potential of pristine subalpine forested watersheds on a site-specific basis. Consequently, specific source and amounts of nutrient discharge to tributaries of the Tahoe Basin are difficult to identify. The sediment content and nitrate and ammonium levels in surface runoff from two soil types (Meeks and Umpa), four plot conditions (wooded natural and disturbed, open natural and disturbed), and three slopes (gentle, moderate, and steep) were studied using rainfall simulation that applied a 9 cm h¹, 1-h event. A significant (P ≤ 0.005) two-way interaction between soil type and plot condition affected runoff nitrate concentration. Runoff from natural or disturbed open plots contained significantly (P = 0.05) greater nitrate than wooded plots. Peak concentrations of nitrate commonly occurred during early runoff, suggesting that peak nitrate discharge to Lake Tahoe tributaries can be expected during early runoff from snowmelt and summer precipitation events. The highest nitrate runoff concentration and 1-h cumulative loading from the 0.46 m² plots were 6.7 mg L-¹ (Umpa, open natural, 15–30 percent slope), and 0.7 mg (Umpa, open natural, ≥ 30 percent slope), respectively. Ammonium in surface runoff was generally below detection limits (≤ 0.05 μg L^?1). No statistical relationship between runoff nitrate and sediment discharge was detected.     

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.     

Modeling the Effect of Summertime Heating on Urban Runoff Temperature1

Abstract: The summertime heating of runoff in urban areas is recognized as a common and consistent urban climatological phenomenon. In this study, a simple thermal urban runoff model (TURM) is presented for the net energy flux at the impervious surfaces of urban areas to account for the heat transferred to runoff. The first step in developing TURM consists of calculating the various factors that control how urban impervious areas absorb heat and transfer it to moving water on the surface. The runoff temperature is determined based on the interactions of the physical characteristics of the impervious areas, the weather, and the heat transfer between the moving film of runoff and the impervious surface common in urban areas. Key surface and weather factors that affect runoff temperature predictions are type of impervious surface, air temperature, humidity, solar radiation before and during rain, rainfall intensity, and rainfall temperature. Runoff from pervious areas is considered separately and estimated using the Green‐Ampt Mein‐Larson rainfall excess method. Pervious runoff temperature is estimated as the rainfall temperature. Field measurements indicate that wet bulb temperature can be used as a surrogate for rainfall temperature and that runoff temperatures from sod average just 2°C higher than rainfall temperatures. Differences between measured and predicted impervious runoff temperature average approximately 2°C, indicating that TURM is a useful tool for determining runoff temperatures for typical urban areas.     

Effects of Lawn Maintenance on Nutrient Losses Via Overland Flow During Natural Rainfall Events1

Spence, Porchè L., Deanna L. Osmond, Wesley Childres, Joshua L. Heitman, and Wayne P. Robarge, 2012. Effects of Lawn Maintenance on Nutrient Losses Via Overland Flow During Natural Rainfall Events. Journal of the American Water Resources Association (JAWRA) 48(5): 909‐924. DOI: 10.1111/j.1752‐1688.2012.00658.x Abstract: A sampling system was used to evaluate the effect of residential lawn management on nutrient losses via overland flow generated during natural rainfall events from three residential landscapes: a high maintenance fescue lawn (HMFL), a low maintenance fescue lawn (LMFL), and a mixed forested residential landscape (FRL). A sampling system was located in designated areas within each landscape such that 100% of the runoff follows natural flow paths to the outlet ports and collects in sterile Nalgene^® B³ media bags (Thermo Fisher Scientific, Rochester, NY). A rainfall event was defined as producing ≥2.54 mm of water. A total of 87 rainfall events occurred during a 20‐month monitoring period. The total runoff volume collected from the LMFL was higher than from the HMFL and FRL, but on average <1% of the total rainfall was collected from the three landscapes. Mean nitrate concentrations from each lawn did not exceed 0.6 mg N/l. Nutrient unit area losses from the HMFL, LMFL, and FRL were 1,000 times less than fertilizer and throughfall inputs, which were due to the presence of well‐structured soils (low bulk densities) with high infiltration rates. This study demonstrated that the frequency of runoff, total runoff volumes, and nutrient losses during natural rainfall events are lower from highly maintained (i.e., irrigation, fertilizer application, and reseeding) densely uniform manicured lawns than low maintenance lawns and forested residential landscapes.     

Runoff Curve Numbers at the Agricultural Field‐Scale and Implications for Continuous Simulation Modeling

This study used monitoring in the waterways of agricultural fields to understand the use of the runoff curve number (CN) in continuous simulation models. The CN has a long history as a design tool for estimating runoff volumes for large, single storms on small watersheds, but its use in continuous simulation models to describe runoff from smaller storms and relatively small areas is more recent and controversial. We examined 788 nonwinter rainfall events on four agricultural fields over five years (2004‐2008) during which runoff was generated in 87 events. The largest 20 runoff events on each field generated approximately 90% of the total runoff volume. The runoff event CNs showed an inverse correlation with storm depth that could not consistently be explained by previous precipitation. We review how small areas of higher runoff generation within larger areas will systematically increase the apparent CN of the larger area as the storm size decreases. If this variation is not incorporated into a model explicitly, continuous simulation modelers must understand that when source areas are aggregated or when runoff generation is spatially variable, the overall CN is not unique when smaller storms are included in the calibration set.     

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.     

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.     

DEVELOPMENT OF DESIGN STORM HYETOGRAPHS FOR CINCINNATI,OHIO1

ABSTRACT A synthetic storm rainfall hyetograph for a one-year design frequency is derived from the one-year intensity-duration curve developed for Cincinnati, Ohio. Detailed rainfall data for a three-year period were collected from three raingages triangulating the Bloody Run Sewer Watershed, an urban drainage areas of 2380 acres'in Cincinnati, Ohio. The advancement of the synthetic storm pattern is obtained from an analysis of the antecedent precipitation immediately preceding the maximum period of three selected durations. Rains which produced excessive runoff at least for some duration were considered only. The same approach can be used for other design frequencies. The purpose of this study is to provide synthetic storm hyetographs to be used as input in deterministic mathematical models simulating urban storm water runoff for the design, analysis and possible surcharge prediction of sewer systems.     

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.     

Urbanization and Its Effect On Runoff in the Whiteoak Bayou Watershed,Texas1

Abstract: The capacity of a watershed to urbanize without changing its hydrologic response and the relationship between that response and the spatial configuration of the developed areas was studied. The study was conducted in the Whiteoak Bayou watershed (223 km²), located northwest of Houston, Texas, over an analysis period from 1949 to 2000. Annual development data were derived from parcel data collected by the Harris County Appraisal District. Using these data, measures of the spatial configuration of the watershed urban areas were calculated for each year. Based on regression models, it was determined that the annual runoff depths and annual peak flows depended on the annual precipitation depth, the developed area and the maximum 12‐h precipitation depth on the day and day before the peak flow took place. It was found that, since the early 1970s, when the watershed reached a 10% impervious area, annual runoff depths and peak flows have increased by 146% and 159%, respectively. However, urbanization is responsible for only 77% and 32% of the increase, respectively, while precipitation changes are responsible for the remaining 39% and 96%, respectively. Likewise, an analysis of the development data showed that, starting in the early 1970s, urbanization in the watershed consisted more of connecting already developed areas than of creating new ones, which increases the watershed’s conveyance capacity and explains the change in its response. Before generalizing conclusions, though, further research on other urban watersheds with different urbanization models appears to be necessary.     

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.