THE INFLUENCE OF CLIMATE VARIATION ON THE ESTIMATION OF LOW FLOWS USED TO PROTECT WATER QUALITY: A NATIONWIDE ASSESSMENT1

ABSTRACT: Historical flow records are used to estimate the regulatory low flows that serve a key function in setting discharge permit limits through the National Pollutant Discharge Elimination System, which provides a nationwide mechanism for protecting water quality. Use of historical records creates an implicit connection between water quality protection and climate variability. The longer the record, the more likely the low flow estimate will be based on a broad set of climate conditions, and thus provides adequate water quality protection in the future. Unfortunately, a long record often is not available at a specific location. This analysis examines the connection between climate variability and the variability of biologically based and hydrologically based low flow estimates at 176 sites from the Hydro‐Climatic Data Network, a collection of stream gages identified by the USGS as relatively free of anthropogenic influences. Results show that a record of 10 to 20 years is necessary for satisfactory estimates of regulatory low flows. Although it is possible to estimate a biologically based low flow from a record of less than 10 years, these estimates are highly uncertain and incorporate a bias that undermines water quality protection.     

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION1

ABSTRACT: Soil data comprise a basic input of SWAT (Soil and Water Assessment Tool) for a watershed application. For watersheds where site specific soil data are unavailable, the two U.S. Department of Agriculture (USDA) soil databases, the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) databases, may be the best alternatives. Although it has been noted that SWAT models using the STATSGO and SSURGO data may give different simulation results for water, sediment, and agricultural chemical yields, information is scarce on the effects of using these two databases in predicting streamflows that are predominantly generated from melting snow in spring. The objective of this study was to assess the effects of using STATSGO versus SSURGO as an input for the SWAT model's simulation of the streamflows in the upper 45 percent of the Elm River watershed in eastern North Dakota. Designating the model as SWAT‐STATSGO when the STATSGO data were used and SWAT‐SSURGO when the SSURGO data were used, SWAT‐STATSGO and SWAT‐SSURGO were separately calibrated and validated using the observed daily streamflows. The results indicated that SWAT‐SSURGO provided an overall better prediction of the discharges than SWAT‐STATSGO, although both did a good and comparable job of predicting the high streamflows. However, SWAT‐STATSGO predicted the low streamflows more accurately and had a slightly better performance during the validation period. In addition, the discrepancies between the discharges predicted by these two SWAT models tended to be larger at upstream locations than at those farther downstream within the study area.     

HYDROLOGIC AND HYDRAULIC RESEARCH IN MOUNTAIN RWERS1

ABSTRACT: Although our current (1990) knowledge of hydrologic and hydraulic processes is based on many years of study, there are river environments where these processes are complex and poorly understood. One of these environments is in mountainous areas, which cover about 25 percent of the United States. Use of conventional hydrologic and hydraulic techniques in mountain-river environments may produce erroneous results and interpretations in a wide spectrum of water-resources investigations. An ongoing U.S. Geological Survey research project is being conducted to improve the understanding of hydrologic and hydraulic processes of mountainous areas and to improve the results of subsequent hydrologic investigations. Future hydrologic and hydraulic research needs in mountainous areas are identified.     

PREDICTING MEASUREMENT ERROR OF AREAL MEAN PRECIPITATION DURING EXTREME EVENTS1

ABSTRACT: The areal mean precipitation (AMP) over a catchment is normally calculated using point measurements at rainfall gages. Error in AMP estimates occurs when an insufficient number of gages are used to sample precipitation which is highly variable in space. AMP error is investigated using historic, severe rainfalls with a set of hypothetical catchments and raingage networks. The potential magnitude of error is estimated for typical gage network densities and arrangements. Possible sources of error are evaluated, and a method is proposed for predicting the magnitude of error using data that are commonly available for severe, historic rainfall.     

INFLUENCE OF SMALL MAMMALS ON STORMFLOW RESPONSES OF PINE-COVERED CATCHMENTS1

ABSTRACT: The relative abundance of small mammals in five forest land cover types on the upper Coastal Plain of north Mississippi was determined. Burrowing mammals accounted for one-half of the total captures; one shrew species that accounted for over one-fourth of the total captures had a strong affinity for well-stocked pine plantations. The opportunity for detention and retention of rainfall was enhanced by burrowing activity. Reductions of stormflow volumes 12 to 15 years after replacing poor quality, upland hardwoods with loblolly pine were only partially explained by increased interception of rainfall; much of the residual reductions are postulated to be due to small mammal burrows. Small mammal activity deserves further study as an important aspect of forest land hydrology.     

IMPACTS OF SILVICULTURE ON FLATWOODS RUNOFF,WATER QUALITY,AND NUTRIENT BUDGETS1

ABSTRACT: Three forest watersheds were isolated by roads in poorly drained flatwoods of Florida. After 12 months of baseline calibration the forest in one watershed was harvested and regenerated with minimum disturbance, in the second watershed with maximum disturbance from common practices, and in the third watershed left intact as a control. Water yields from the maximum treatments increased a significant 250 percent while that from the minimum treatments increased 117 percent as compared to the control. Weed vegetation remaining after the minimum treatment continued significant water use. The water yield increases lasted only for one year. Water quality was reduced by both treatments with the most effect immediately after the maximum disturbance. Absolute levels of suspended sediments, potassium, and calcium remained relatively low. The maximum treatment caused significant changes in net cation balances only for one year. The information shows relative little effect of silvicultural practices in flatwoods on water quality as compared to data from upland forests. Water yield increases may be manipulated by the degree of harvest and weed control practices.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

EFFECTS OF INITIAL ABSTRACTION AND URBANIZATION ON ESTIMATED RUNOFF USING CN TECHNOLOGY1

ABSTRACT: Few studies have been conducted to explore the effects of initial abstraction on estimated direct runoff despite the widespread use of the curve number (CN) method in many hydrologic models to estimate direct runoff. In this study, use of a 5 percent ratio of initial abstraction (I_a) to storage (S) to estimate daily direct runoff with modified CN values for a 5 percent I_a/S value was investigated using the Long‐Term Hydrologic Impact Assessment (L‐THIA) geographic information system (GIS). In addition, the effects on estimated runoff of altering the hydrologic soil group due to urbanization were investigated. The L‐THIA model was applied to the Indiana Little Eagle Creek watershed with 5 percent and 20 percent I_a/S values, considering hydrologic soil group alteration due to urbanization. The results indicate that uses of a 5 percent l_a/S and modified CN values and Hydrologic Soil Group D for urbanized areas in model runs can improve long term direct runoff prediction.     

ASSESSMENT OF POSSIBLE IMPACTS OF CLIMATE CHANGE IN AN URBAN CATCHMENT1

ABSTRACT: Stationarity of rainfall statistical parameters is a fundamental assumption in hydraulic infrastructure design that may not be valid in an era of changing climate. This study develops a framework for examining the potential impacts of future increases in short duration rainfall intensity on urban infrastructure and natural ecosystems of small watersheds and demonstrates this approach for the Mission/Wagg Creek watershed in British Columbia, Canada. Nonstationarities in rainfall records are first analyzed with linear regression analysis, and the detected trends are extrapolated to build potential future rainfall scenarios. The Storm Water Management Model (SWMM) is used to analyze the effects of increased rainfall intensity on design peak flows and to assess future drainage infrastructure capacity according to the derived scenarios. While the framework provided herein may be modified for cases in which more complex distributions for rainfall intensity are needed and more sophisticated stormwater management models are available, linear regressions and SWMM are commonly used in practice and are applicable for the Mission/Wagg Creek watershed. Potential future impacts on stream health are assessed using methods based on equivalent total impervious area. In terms of impacts on the drainage infrastructure, the results of this study indicate that increases in short duration rainfall intensity may be expected in the future but that they would not create severe impacts in the Mission/Wagg Creek system. The equivalent levels of imperviousness, however, suggest that the impacts on stream health could be far more damaging.     

AN INTEGRATED ONE‐DIMENSIONAL AND TWO‐DIMENSIONAL URBAN STORMWATER FLOOD SIMULATION MODEL1

ABSTRACT: Flash flooding is the rapid flooding of low lying areas caused by the stormwater of intense rainfall associated with thunderstorms. Flash flooding occurs in many urban areas with relatively flat terrain and can result in severe property damage as well as the loss of lives. In this paper, an integrated one‐dimensional (1‐D) and two‐dimensional (2‐D) hydraulic simulation model has been established to simulate stormwater flooding processes in urban areas. With rainfall input, the model simulates 2‐D overland flow and 1‐D flow in underground stormwater pipes and drainage channels. Drainage channels are treated as special flow paths and arranged along one or more sides of a 2‐D computational grid. By using irregular computation grids, the model simulates unsteady flooding and drying processes over urban areas with complex drainage systems. The model results can provide spatial flood risk information (e.g., water depth, inundation time and flow velocity during flooding). The model was applied to the City of Beaumont, Texas, and validated with the recorded rainfall and runoff data from Tropical Storm Allison with good agreement.