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.     

EFFECT OF SIMULATED CLIMATE CHANGE ON SNOWMELT RUNOFF MODELING IN SELECTED BASINS1

ABSTRACT: The projected increase in the concentration of CO₂ and other greenhouse gases in the atmosphere is likely to result in a global temperature increase. This paper reports on the probable effects of a temperature increase and changes in transpiration on basin discharge in two different mountain snowmelt regions of the western United States. The hydrological effects of the climate changes are modeled with a relatively simple conceptual, semi-distributed snowmelt runoff model. Based on the model results, it may be concluded that increased air temperatures will result in a shift of snowmelt runoff to earlier in the snowmelt season. Furthermore, it is shown that it is very important to include the expected change in climate-related basin conditions resulting from the modeled temperature increase in the runoff simulation. The effect of adapting the model parameters to reflect the changed basin conditions resulted in a further shift of streamflow to April and an even more significant decrease of snowmelt runoff in June and July. If the air temperatures increase by approximately 5°C and precipitation and accumulated snow amounts remain about the same, runoff in April and May, averaged for the two basins, is expected to increase by 185 percent and 26 percent, respectively. The runoff in June and July will decrease by about 60 percent each month. Overall, the total seasonal runoff decreases by about 6 percent. If increased CO₂ concentrations further change basin conditions by reducing transpiration by the maximum amounts reported in the literature, then, combined with the 5°C temperature increase, the April, May, June, and July changes would average +230 percent, +40 percent, ?55 percent, and ?45 percent, respectively. The total seasonal runoff change would be +11 percent.     

REVISITING THE DEGREE-DAY METHOD FOR SNOWMELT COMPUTATIONS1

ABSTRACT: The simple, empirical degree-day approach for calculating snowmelt and runoff from mountain basins has been in use for more than 60 years. It is frequently suggested that the degree-day method be replaced by the more physically-based energy balance approach. The degree-day approach, however, maintains its popularity, applicability, and effectiveness. It is shown that the degree-day method is reliable for computing total snowmelt depths for periods of a week to the entire snowmelt season. It can also be used for daily snowmelt depths when utilized in connection with an adequate snowmelt runoff model for computing the basin runoff. The degree-day ratio is shown to vary seasonally as opposed to being constant as is often assumed. Additionally, in order to evaluate the degree-day ratio correctly, the changing snow cover extent in a basin during the snowmelt season must be taken into account. It is also possible to combine the degree-day approach with a radiation component so that short time interval (<24 hours) computations of snowmelt depth can be made. When snowmelt input is transformed to basin output (runoff) by a snowmelt runoff model, there is little difference between the degree-day approach and a radiation-based approach. This is fortuitous because the physically-based energy balance models will not soon displace the degree-day methods because of their excessive data requirements.     

RUNOFF SIMULATION USING RADAR RAINFALL DATA1

ABSTRACT: Rainfall data products generated with the national network of WSR-88D radars are an important new data source provided by the National Weather Service. Radar-based data include rainfall depth on an hourly basis for grid cells that are nominally 4 km square. The availability of such data enables application of improved techniques for rainfall-runoff simulation. A simple quasi-distributed approach that applies a linear runoff transform to grid-ded rainfall excess has been developed. The approach is an adaptation of the Clark conceptual runoff model, which employs translation and linear storage. Data development for, and results of, an initial application to a 4160 km² watershed in the Midwestern U.S. are illustrated.     

A COMPARISON OF GEOSTATISTICAL METHODOLOGIES USED TO ESTIMATE SNOW WATER EQUIVALENT1

ABSTRACT: The need to monitor and forecast water resources accurately, particularly in the western United States, is becoming increasingly critical as the demand for water continues to escalate. Consequently, the National Weather Service (NWS) has developed a geostatistical model that is used to obtain areal estimates of snow water equivalent (the thtal water content in all phases of the snowpack), a major source of water in the West. The areal snow water equivalent estimates are used to update the hydrologic simulation models maintained by the NWS and designed to produce extended streamflow forecasts for river systems throughout the United States. An alternative geostatistical technique has been proposed to estimate snow water equivalent. In this research, we describe the two methodologies and compare the accuracy of the estimates produced by each technique. We illustrate their application and compare their estimation accuracy using snow data collected in the North Fork Clearwater River basin in Idaho.     

GENERAL-CIRCULATION-MODEL SIMULATIONS OF FUTURE SNOWPACK IN THE WESTERN UNITED STATES1

ABSTRACT: April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western U.S. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.     

ESTIMATING LOW-FLOW QUANTILES FROM DRAINAGE-BASIN CHARACTERISTICS IN NEW HAMPSHIRE AND VERMONT1

ABSTRACT: This study systematically develops, validates, and compares alternative approaches for estimating quantiles of the distribution of annual minimum seven-day-average flows (7Q) for ungaged, unregulated drainage basins in New Hampshire and Vermont via regression on map-measurable drainage-basin characteristics. At 47 gaging stations in the region, the hypotheses that 7Q is log normally distributed and serially independent are not rejected, and the regional average spatial correlation is R= 0.35. Step-forward examination of a suite of potential predictor variables revealed that logarithm of drainage area, mean elevation, and fraction of basin covered with sand and gravel deposits are significant predictors of quantiles of 7Q. The regression equations were incorporated into four approaches to estimate the 7Q value with a nonexceedence probability of 0.1, 7Q10. Comparison of observed values and values predicted via a delete-one jackknife resampling validation indicates that one of the approaches gives estimates with acceptable bias and precision, with median relative error of 33 percent and prediction error of 64 percent. This is equivalent to the precision obtainable with only one to two years of gaging records. In spite of this limited precision, the approaches developed herein are useful for predicting 7Q quantiles at ungaged sites. Further improvement in precision will likely be possible only by exploiting the spatial correlation of annual 7Q.     

A CRITICAL APPROACH TO THE CALIBRATION OF A WATERSHED MODEL1

ABSTRACT: A complex watershed-scale water quality simulation model, the Hydrological Simulation Program-FORTRAN (HSPF) model, was calibrated for a 16 km² catchment. The simulation step size was 0.33 hours with predicted and recorded hydrologic flows compared on an annual and monthly basis during a total calibration period of four years. Unguided numerical optimization when applied alone did not yield a model parameter set with acceptable predictive capability; instead, it was necessary to apply a critical process that included sensitivity analysis, numerical optimization, and testing of derived model parameter sets to evaluate their performance for periods other than those for which they were determined. Using this critical calibration process, the model was proven to have significant predictive capability. Numerical optimization is an aid for model calibration, but it must not be used blindly.     

SPATIAL ANALYSIS FOR MONTHLY RAINFALL IN SOUTH FLORIDA1

ABSTRACT: Several methods have been developed to interpolate point rainfall data and integrate areal rainfall data from any network of stations. From previous studies, it can be concluded that models for spatial analysis of rainfall are dependent on topography, area of analysis, type of rainfall, and density of gauging network. The purpose of this study is to evaluate a set of six appropriate models for point and areal rainfall estimations over a 4000 square mile area in South Florida. In this study, a case of developing spatial continuity model for monthly rainfall from a database that had various lengths of records and missing data is documented. The spatial correlation and variogram models for monthly rainfall were developed. Six methods of spatial interpolation were applied and the results validated with historical observations. The results of the study indicate that the multiquadric, kriging, and optimal interpolation schemes are the best three methods for interpolation of monthly rainfall within the study area. The optimal and kriging methods have the advantage of providing estimates of the error of interpolation. The optimal interpolation method uses the spatial correlation function and the kriging method uses the variogram function. The two spatial functions are related. Either of the two methods provide good estimates of monthly point and areal rainfall in the study area.     

THE TWO‐DIMENSIONAL UPLAND EROSION MODEL CASC2D‐SED1

ABSTRACT: The two‐dimensional soil erosion model CASC2D‐SED simulates the dynamics of upland erosion during single rainstorms. The model is based on the raster‐based surface runoff calculations from CASC2D. Rainfall precipitation is distributed in time and space. Infiltration is calculated from the Green‐Ampt equations. Surface runoff is calculated from the diffusive wave approximation to the Saint‐Venant equations in two‐dimensions. Watershed data bases in raster Geographical Information System (GIS) provide information on the soil type, size fractions, soil erodibility, cropping management, and conservation practice factors for soil erosion calculations. Upland sediment transport is calculated for the size fractions (sand, silt, and clay), and the model displays the sediment flux, the amount of suspended sediment, and the net erosion and deposition using color graphics. The model has been tested on Goodwin Creek, Mississippi. The peak discharge and time to peak are within ± 20 percent and sediment transport rates within ?50 percent to 200 percent.     

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.     

NUMERICAL MODEL OF A TRACER TEST ON THE SANTA CLARA RWER,VENTURA COUNTY,CALIFORNIA1

ABSTRACT: To better understand the flow processes, solute-trans. port processes, and ground-water/surface-water interactions on the Santa Clara River in Ventura County, California, a 24-hour fluorescent-dye tracer study was performed under steady-state flow conditions on a 45-km reach of the river. The study reach includes perennial (uppermost and lowermost) subreaches and ephemeral subreaches of the lower Piru Creek and the middle Santa Clara River. The tracer-test data were used to calibrate a one-dimensional flow model (DAFLOW) and a solute-transport model (BLTM). The dye-arrival times at each sample location were simulated by calibrating the velocity parameters in DAFLOW. The simulations of dye transport indicated that (1) ground-water recharge explains the loss of mass in the ephemeral middle subreaches, and (2) ground-water recharge does not explain the loss of mass in the perennial uppermost and lowermost subreaches. The observed tracer curves in the perennial subreaches were indicative of sorptive dye losses, transient storage, and (or) photodecay - these phenomena were simulated using a linear decay term. However, analysis of the linear decay terms indicated that photodecay was not a dominant source of dye loss.     

DENSITY CURRENT INTRUSIONS IN AN ICE-COVERED URBAN LAKE1

ABSTRACT: Evidence is presented that snowmelt runoff from an urban watershed can produce density current intrusions (underflows) in a lake. Several episodes of density current intrusions are documented. Water temperatures and salinities measured near the bottom of a 10 m deep Minneapolis lake during the late winter warming periods in 1989, 1990, 1991, and 1995 show significant rapid changes which are correlated with observed higher air temperatures and snowmelt runoff. The snowmelt runoff entering this particular lake (Ryan Lake) has increased electrical conductivity, salinity, and density. The source of the salinity is the salt spread on urban streets in the winter. Heating of littoral waters in spring may also contribute to the occurrence of the sinking flows, but is clearly not the only cause.     

USING FIELD SCALE MODELS TO PREDICT PEAK FLOWS ON AGRICULTURAL WATERSHEDS1

The goal of this study was to develop a methodology for generating storm hydrographs at a watershed scale based on daily runoff estimates from a field scale model. The methodology was evaluated on a small agricultural watershed using the ADAPT field scale process model. A comparison of observed and predicted peak flows for 11 of the largest events that occurred in a three year period gave r² values of 0.84, 0.82, and 0.81 when the watershed was subdivided into 1, 5, and 10 sub watersheds. However, all other statistical measures improved when the watershed was subdivided into at least five sub watersheds. Guidelines need to be developed on the use of the procedure but it first needs to be evaluated on several watersheds that exhibit a range in sizes, land uses, slopes, and soil properties.     

SNOWPACK CHANGES RESULTING FROM TIMBER HARVEST INTERCEPTION,REDISTRIBUTION, AND EVAPORATION1

ABSTRACT: Three processes were examined as causing snowpack changes in forest clearings. Two of the three contribute to increases and one counteracts by reducing snowpack. The two that increase snowpack are redistribution and decreased loss to interception. Snow evaporation from a clearing counteracts snowpack increases. Research has indicated that as vegetation density increases, so too does the loss to interception. As snow in the canopy reaches the limit that the canopy can hold (the threshold amount) evaporation increases. Aerodynamics of the forest canopy were studied as well. As timber is cut, wind patterns are disturbed, creating disruptions in the wind velocity gradient depositing snow in openings. This redistribution leads to an increased snow water equivalent and augments runoff. Snow evaporation was shown to increase proportionally with opening size. Evaporation offsets the water yield gains derived from forest cut. It was found that this offset is inclusive to the measurements of water yield changes in experimental forests. An optimal size of harvest block may be five tree heights in width as suggested by numerous studies.     

APPLICATION OF DIFFUSIVE TANK MODEL IN DRAINAGE ANALYSIS OF PADDY FIELDS1

ABSTRACT: A diffusive tank model has been successfully applied to the simulation of runoff from paddy fields in Japan because it can well describe the features of local water flows. The main goal of the study is to evaluate the performance of the diffusive tank model with the calibrated parameters obtained in Jyau‐Shi to simulate discharge from paddy fields in two experimental catchments located in the areas of Shing‐Ying and Ta‐Liao, Southwestern Taiwan. The simulations were verified by comparing the model results with observed runoff data from the two experimental catchments. The model predicted the discharge from the paddy fields well. This indicates that the model with the calibrated parameters may be used in other paddy fields in Taiwan.     

AN INTERDISCIPLINARY APPROACH TO VALUING WATER FROM BRUSH CONTROL1

ABSTRACT: An analytic methodology utilizing models from three disciplines is developed to assess the viability of brush control for water yield in the Frio River basin, Texas. Ecological, hydrologic, and economic models are used to portray changes in forage production and water supply resulting from brush control, and to value supplemental water produced through brush control. Site‐specific biophysical characteristics are used to simulate water yields from brush control across the watershed. Economic benefits from increased animal production for ranchers undertaking brush control are assessed. Benefits to Corpus Christi residential water consumers from ranchers' brush control activities are evaluated using the change in consumer surplus resulting from supplemental water produced through brush control. Results indicate an increase in water yield with brush control on 35 percent of the land area in the basin. However, the cost of brush control is more than the increase in returns it fosters on most range sites. Consumer surplus change for Corpus Christi residents over 25 years is zero under baseline conditions, implying subsidies for brush control in the Frio basin are not worthwhile at this time.     

SPATIAL AND TEMPORAL ANALYSIS OF AGRICULTURAL WATER REQUIREMENTS IN THE GULF COAST OF THE UNITED STATES1

ABSTRACT: Competition for water resources is becoming an increasingly important issue in the southeastern U.S. The potential impacts of future precipitation and runoff estimated by a transient global climate model (HADCM2) on competing water resources in the Southeast has been conducted. Issues of agricultural management, irrigation water withdrawals, and water quality were studied over three time periods: 1974–1993, 2020–2039, and 2080–2099 in five water basins identified previously as exhibiting water-related problems. These basins, which encompass the boundary between Alabama and Mississippi, cover four important agricultural counties in Mississippi. Irrigation water requirements generated by crop growth models for corn, soybeans, and winter wheat were coupled with monthly runoff for the impacted basins estimated by the SWAT water balance model. The results of the study reveal that in the next 20–40 years water availability in the southern portions of the study area will decline as much as 10 percent during times when water requirements for agricultural production are crucial. Maintaining or expanding existing crop yields under future climate regimes may require additional irrigation water and increase competition among other uses such as domestic, industrial, recreational, and ecosystem quality.     

VALIDATION OF AGNPS FOR SMALL WATERSHEDS USING AN INTEGRATED AGNPS/GIS SYSTEM1

ABSTRACT: The AGNPS (AGricultural NonPoint Source) model was evaluated for predicting runoff and sediment delivery from small watersheds of mild topography. Fifty sediment yield events were monitored from two watersheds and five nested subwater-sheds in East Central Illinois throughout the growing season of four years. Half of these events were used to calibrate parameters in the AGNPS model. Average calibrated parameters were used as input for the remaining events to obtain runoff and sediment yield data. These data were used to evaluate the suitability of the AGNPS model for predicting runoff and sediment yield from small, mild-sloped watersheds. An integrated AGNPS/GIS system was used to efficiently create the large number of data input changes necessary to this study. This system is one where the AGNPS model was integrated with the GRASS (Geographic Resources Analysis Support System) GIS (Geographical Information System) to develop a decision support tool to assist with management of runoff and erosion from agricultural watersheds. The integrated system assists with the development of input GIS layers to AGNPS, running the model, and interpretation of the results.     

USING SENSITIVITY ANALYSIS TO ASSIST PARAMETER ZONATION IN GROUND WATER FLOW MODEL1

ABSTRACT: For numerical modeling of ground water movement in a real aquifer system, the aquifer is usually divided into hydrogeologically defined zones, each with its own parameter values. The responses of the system, such as head or drawdown, are often available only in some of the zones. The estimated parameters of all the zones are based on the measured response in these limited zones. However, the estimates for some of the zones may be very uncertain, and these zones are therefore not justified by the data. In this paper, an approach is presented to understand which zone may produce uncertain parameter values and should be lumped with its neighbor. This approach is demonstrated using a regional numerical model for pumping test analysis in the Nottinghamshire aquifer, UK. A step-by-step process is used in identifying the aquifer zones and estimating their parameters based on the principle of using the smallest possible numbers of zones and parameters for adequate representation of the drawdown response. After the parameters of each zone are estimated, the sensitivity features of these parameters are examined. The results show that the parameters in one zone can be estimated properly by the drawdown in another zone only when there is significant sensitivity. For transmissivity, sensitivity between zones occurs when there is significant flow between them. For storativity, sufficient sensitivity can occur without large flows between the zones, provided that one zone causes significant drawdown in the other. This idea can be extended to the flow model for a large aquifer system. If the aquifer is divided in such a way that aquifer responses are not sensitive to the parameters in some of the zones, the parameters in those zones cannot be estimated properly and should be lumped into their neighboring zones. In this way, a simple but more reasonable model can be built.