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.     

Long‐Term High‐Resolution Radar Rainfall Fields for Urban Hydrology

Accurate records of high‐resolution rainfall fields are essential in urban hydrology, and are lacking in many areas. We develop a high‐resolution (15 min, 1 km²) radar rainfall data set for Charlotte, North Carolina during the 2001‐2010 period using the Hydro‐NEXRAD system with radar reflectivity from the National Weather Service Weather Surveillance Radar 1988 Doppler weather radar located in Greer, South Carolina. A dense network of 71 rain gages is used for estimating and correcting radar rainfall biases. Radar rainfall estimates with daily mean field bias (MFB) correction accurately capture the spatial and temporal structure of extreme rainfall, but bias correction at finer timescales can improve cold‐season and tropical cyclone rainfall estimates. Approximately 25 rain gages are sufficient to estimate daily MFB over an area of at least 2,500 km², suggesting that robust bias correction is feasible in many urban areas. Conditional (rain‐rate dependent) bias can be removed, but at the expense of other performance criteria such as mean square error. Hydro‐NEXRAD radar rainfall estimates are also compared with the coarser resolution (hourly, 16 km²) Stage IV operational rainfall product. Stage IV is adequate for flood water balance studies but is insufficient for applications such as urban flood modeling, in which the temporal and spatial scales of relevant hydrologic processes are short. We recommend the increased use of high‐resolution radar rainfall fields in urban hydrology.     

GENETIC PROGRAMMING: A NEW PARADIGM IN RAINFALL RUNOFF MODELING1

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

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.     

QUALITY OF RUNOFF FROM PLOTS WITH SIMULATED GRAZING1

ABSTRACT: Grazed pastures represent a potential source of non‐point pollution. In comparison to other nonpoint sources (e.g., row‐cropped lands), relatively little information exists regarding possible magnitudes of nutrient losses from grazed pasture, how those losses are affected by management variables, and how the losses can be minimized. The objective of this study was to measure concentrations of nitrogen (N), phosphorus (P), and solids in runoff from fescue plots and relate those measurements to simulated forage management strategy. The study was conducted at the University of Kentucky Maine Chance Agricultural Experiment Station north of Lexington. Plots (2.4 m wide by 6.1 m long) were constructed and established in Kentucky 31 fescue (Festuca arundinacea Schreb.) to represent pasture. The experimental treatments applied to the plots varied in terms of forage height and material applied (none, manure, or manure and urine). Runoff was sampled for six simulated rainfall events applied over the summer of 1997 and analyzed for nitrate N (NO₃‐N), ammonia N (NH3‐N), total Kjeldahl N (TKN), ortho‐P (PO₄‐P), total P (TP), and total suspended solids (TSS). All runoff constituents exhibited dependence on the date of simulated rainfall with generally higher concentrations measured when simulated rainfall followed relatively dry periods. The effects of forage height and manure addition were mixed. Highest runoff N concentrations were associated with the greatest forage heights, whereas highest P concentrations occurred for the least forage heights. Manure/urine addition increased runoff P concentrations relative to controls (no manure/urine) for both the greatest and least forage heights, but runoff N concentrations were increased only for the greatest forage heights. These findings indicate that runoff of N and P is at least as sensitive to amount and proximity of preceding rainfall and suggest that managing forage to stimulate growth and plant uptake can reduce runoff of N.     

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.     

PREDICTING STORMFLOW AND PEAKFLOW FROM SMALL BASINS IN HUMID AREAS BY THE R-INDEX METHOD1

ABSTRACT: A relatively simple nonlinear equation was fitted to 468 stormflows larger than 0.05 area inches on 11 forested basins from New Hampshire to South Carolina, providing a predictive method for use on forest and wildlands in humid regions. Stormflow in area inches (Q?) was: where R is the mean value of Q/P for all P larger than one inch, P is storm rainfall in inches, and I is the initial flow rate in ft³/sec/mi². S.E. was 0.3 inch of stormflow. Peakflow was similarly estimated, S.E. 26 ft³/sec/mi². The R-index method is proposed as a practical tool in forest and wildland management. Similar to the SCS runoff curve number method, the R-index method requires no prior assumptions about infiltration capacities of forest lands, but calls for the mapping of all first-order streams for the average storage capacity index R, i.e., the mean hydrologic response of the source areas. Tested against the runoff curve method on four independent basins, predictions by the R-index method were considerably more accurate when field information normally available to planners and managers was used in both methods.     

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.     

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.     

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.     

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.     

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.     

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.     

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

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

IMPACTS OF CALIFORNIA'S CLIMATIC REGIMES AND COASTAL LAND USE CHANGE ON STREAMFLOW CHARACTERISTICS1

ABSTRACT: To investigate the impacts of urbanization and climatic fluctuations on stream flow magnitude and variability in a Mediterranean climate, the HEC‐HMS rainfall/runoff model is used to simulate stream flow for a 14‐year period (October 1, 1988, to September 30, 2002) in the Atascadero Creek watershed located along the southern coast of California for 1929, 1998, and 2050 (estimated) land use conditions (8, 38 and 52 percent urban, respectively). The 14‐year period experienced a range of climatic conditions caused mainly by El Nino‐Southern Oscillation variations. A geographic information system is used to delineate the watershed and parameterize the model, which is calibrated using data from two stream flow and eight rainfall gauges. Urbanization is shown to increase peak discharges and runoff volume while decreasing stream flow variability. In all cases, the annual and 14‐year distributions of stream flow are shown to be highly skewed, with the annual maximum 24 hours of discharge accounting for 22 to 52 percent of the annual runoff and the maximum ten days of discharge from an average El Nino year producing 10 to 15 percent of the total 14‐year discharge. For the entire period of urbanization (1929 to 2050), the average increase in annual maximum discharges and runoff was 45 m³/s (300 percent) and 15 cm (350 percent), respectively. Additionally, the projected increase in urbanization from 1998 to 2050 is half the increase from 1929 to 1998; however, increases in runoff (22 m³/s and 7 cm) are similar for both scenarios because of the region's spatial development pattern.     

Hydrological Responses to Climate and Land‐Use Changes along the North American East Coast: A 110‐Year Historical Reconstruction

The North American east coast (NAEC) region experienced significant climate and land‐use changes in the past century. To explore how these changes have affected land water cycling, the Dynamic Land Ecosystem Model (DLEM 2.0) was used to investigate the spatial and temporal variability of runoff and river discharge during 1901‐2010 in the study area. Annual runoff over the NAEC was 420 ± 61 mm/yr (average ± standard deviation). Runoff increased in parts of the northern NAEC but decreased in some areas of the southern NAEC. Annual freshwater discharge from the study area was 378 ± 61 km³/yr (average ± standard deviation). Factorial simulation experiments suggested that climate change and variability explained 97.5% of the interannual variability of runoff and also resulted in the opposite changes in runoff in northern and southern regions of the NAEC. Land‐use change reduced runoff by 5‐22 mm/yr from 1931 to 2010, but the impacts were divergent over the Piedmont region and Coastal Plain areas of the southern NAEC. Land‐use change impacts were more significant at local and watershed spatial scales rather than at regional scales. Different responses of runoff to changing climate and land‐use should be noted in future water resource management. Hydrological impacts of afforestation and deforestation as well as urbanization should also be noted by land‐use policy makers.     

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

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

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.     

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.