Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS)1

Abstract: This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions (I_a), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I_a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.     

Effects of calibration on L-THIA GIS runoff and pollutant estimation

Urbanization can result in alteration of a watershed's hydrologic response and water quality. To simulate hydrologic and water quality impacts of land use changes, the Long-Term Hydrologic Impact Assessment (L-THIA) system has been used. The L-THIA system estimates pollutant loading based on direct runoff quantity and land use based pollutant coefficients. The accurate estimation of direct runoff is important in assessing water quality impacts of land use changes. An automated program was developed to calibrate the L-THIA model using the millions of curve number (CN) combinations associated with land uses and hydrologic soil groups. L-THIA calibration for the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana was performed using land use data for 1991 and daily rainfall data for six months of 1991 (January 1-June 30) to minimize errors associated with use of different temporal land use data and rainfall data. For the calibration period, the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The calibrated CN values were used for validation of the model for the same year (July 1-December 31), and the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The Nash-Sutcliffe coefficient was 0.52 for January 1, 1991 to December 31, 1991 using uncalibrated CN values. As shown in this study, the use of better input parameters for the L-THIA model can improve accuracy. The effects on direct runoff and pollutant estimation of the calibrated CN values in the L-THIA model were investigated for the LEC. Following calibration, the estimated average annual direct runoff for the LEC watershed increased by 34%, total nitrogen by 24%, total phosphorus by 22%, and total lead by 43%. This study demonstrates that the L-THIA model should be calibrated and validated prior to application in a particular watershed to more accurately assess the effects of land use changes on hydrology and water quality.     

GIS BASED LONG TERM HYDROLOGIC IMPACT EVALUATION FOR WATERSHED URBANIZATION1

ABSTRACT: To adequately manage impacts of ongoing or future land use changes in a watershed, the magnitude of their hydrologic impacts needs to be assessed. A grid based daily streamflow model was calibrated with two years of observed streamflow data, using time periods when land use data are available and verified by comparison of model predictions with observed streamflow data. Streamflow data were separated into direct runoff and baseflow to estimate the impacts of urbanization on each hydrologic component. Analysis of the ratio between direct runoff and total runoff from 30 years of simulation results and the change in these ratios with urbanization shows that estimated annual direct runoff increased from 49.2 percent (1973) to 63.1 percent (1984) and 65.0 percent (1991), indicating the effects of urbanization are greater on direct runoff than on total runoff. The direct runoff ratio also varies with annual rainfall, with dry year ratios larger than those for wet years. This suggests that the impact of urbanization on areas that are sensitive to runoff ratios, such as stream ecosystems, might be more serious during drier years than in wetter years in terms of water quality and water yield. This indicates that sustainable base‐flow is important to maintaining sound stream ecosystems.     

Effects of Spatial Distribution of Prairie Vegetation in an Agricultural Landscape on Curve Number Values

The curve number (CN) method is used to calculate runoff in many hydrologic models, including the Soil and Water Assessment Tool (SWAT). The CN method does not account for the spatial distribution of land cover types, an important factor controlling runoff patterns. The objective of this study was to empirically derive CN values that reflect the strategic placement of native prairie vegetation (NPV) within row crop agricultural landscapes. CNs were derived using precipitation and runoff data from a seven‐year period for 14 small watersheds in Iowa. The watersheds were planted with varying amounts of NPV located in different watershed positions. The least squares and asymptotic least squares methods (LSM) were used to derive CNs using an initial abstraction coefficient (λ) of 0.2 and 0.05. The CNs were verified using leave‐one‐out cross‐validation and adjustment for antecedent moisture conditions (AMC) was tested. The asymptotic method produced CN values for watersheds with NPV treatment that were 8.9 and 14.7% lower than watersheds with 100% row crop at λ = 0.2 and λ = 0.05, respectively. The derived CNs produced Nash‐Sutcliffe efficiency values ranging from 0.4 to 0.7 during validation. Our analyses show the CNs verified best for the asymptotic LSM, when using λ of 0.05 and adjusting for AMC. Further, comparison of derived CNs against an area weighted CN indicated that the placement of vegetation does impact the CN value. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Managing Uncertainty in Runoff Estimation with the U.S. Environmental Protection Agency National Stormwater Calculator

The U.S. Environmental Protection Agency National Stormwater Calculator (NSWC) simplifies the task of estimating runoff through a straightforward simulation process based on the EPA Stormwater Management Model. The NSWC accesses localized climate and soil hydrology data, and options to experiment with low‐impact development (LID) features for parcels up to 5 ha in size. We discuss how the NSWC treats the urban hydrologic cycle and focus on the estimation uncertainty in soil hydrology and its impact on runoff simulation by comparing field‐measured soil hydrologic data from 12 cities to corresponding NSWC estimates in three case studies. The default NSWC hydraulic conductivity is 10.1 mm/h, which underestimates conductivity measurements for New Orleans, Louisiana (95 ± 27 mm/h) and overestimates that for Omaha, Nebraska (3.0 ± 1.0 mm/h). Across all cities, the NSWC prediction, on average, underestimated hydraulic conductivity by 10.5 mm/h compared to corresponding measured values. In evaluating how LID interact with soil hydrology and runoff response, we found direct hydrologic interaction with pre‐existing soil shows high sensitivity in runoff prediction, whereas LID isolated from soils show less impact. Simulations with LID on higher permeability soils indicate that nearly all of pre‐LID runoff is treated; while features interacting with less‐permeable soils treat only 50%. We highlight the NSWC as a screening‐level tool for site runoff dynamics and its suitability in stormwater management.     

Physically Based,Hydrologic Model Results Based on Three Precipitation Products1

Abstract: The main objective of the study is to examine the accuracy of and differences among simulated streamflows driven by rainfall estimates from a network of 22 rain gauges spread over a 2,170 km² watershed, NEXRAD Stage III radar data, and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite data. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA), a physically based, distributed parameter, grid‐structured, hydrologic model, was used to simulate the June‐2002 flooding event in the Upper Guadalupe River watershed in south central Texas. There were significant differences between the rainfall fields estimated by the three types of measurement technologies. These differences resulted in even larger differences in the simulated hydrologic response of the watershed. In general, simulations driven by radar rainfall yielded better results than those driven by satellite or rain‐gauge estimates. This study also presents an overview of effects of land cover changes on runoff and stream discharge. The results demonstrate that, for major rainfall events similar to the 2002 event, the effect of urbanization on the watershed in the past two decades would not have made any significant effect on the hydrologic response. The effect of urbanization on the hydrologic response increases as the size of the rainfall event decreases.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

Investigation of the Curve Number Method For Surface Runoff Estimation In Tropical Regions

This study tests the applicability of the curve number (CN) method within the Soil and Water Assessment Tool (SWAT) to estimate surface runoff at the watershed scale in tropical regions. To do this, surface runoff simulated using the CN method was compared with observed runoff in numerous rainfall‐runoff events in three small tropical watersheds located in the Upper Blue Nile basin, Ethiopia. The CN method generally performed well in simulating surface runoff in the studied watersheds (Nash‐Sutcliff efficiency [NSE] > 0.7; percent bias [PBIAS] < 32%). Moreover, there was no difference in the performance of the CN method in simulating surface runoff under low and high antecedent rainfall (PBIAS for both antecedent conditions: ~30%; modified NSE: ~0.4). It was also found that the method accurately estimated surface runoff at high rainfall intensity (e.g., PBIAS < 15%); however, at low rainfall intensity, the CN method repeatedly underestimated surface runoff (e.g., PBIAS > 60%). This was possibly due to low infiltrability and valley bottom saturated areas typical of many tropical soils, indicating that there is scope for further improvements in the parameterization/representation of tropical soils in the CN method for runoff estimation, to capture low rainfall‐intensity events. In this study the retention parameter was linked to the soil moisture content, which seems to be an appropriate approach to account for antecedent wetness conditions in the tropics.     

USING CURVE NUMBERS TO DETERMINE BASELINE VALUES OF GREEN-AMPT EFFECTIVE HYDRAULIC CONDUCTIVITIES1

ABSTRACT: Since the trend in infiltration modeling is currently toward process-based approaches such as the Green-Ampt equation, more emphasis is being placed on methods of determining appropriate parameters for this approach. The SCS curve number method is an accepted and commonly used empirical approach for estimating surface runoff, and is based on numerous data from a variety of sources. The time and expense of calibrating process-based infiltration parameters to measured data are often prohibitive. This study uses curve number predictions of runoff to develop equations to estimate the “baseline” hydraulic conductivities (K_b) for use in the Green-Ampt equation. Curve number predictions of runoff were made for 43 soils. K_b values in the Water Erosion Prediction Project (WEPP) model were then calibrated so that the annual runoff predicted by WEPP was equal to the curve number predictions. These calibrated values were used to derive an equation that estimated K_b based on the percent sand, percent clay, and cation exchange capacity of the soil. Estimated values of K_b from this equation compared favorably with measured values and values calibrated to measured natural runoff plot data. WEPP predictions of runoff using both optimized and estimated values of K_b were compared to curve number predictions of runoff and the measured values. The WEPP predictions using the optimized values of K_b were the best in terms of both average error and model efficiency. WEPP predictions using estimated values of K_b were shown to be superior to predictions obtained from the curve number method. The runoff predictions all tended to be biased high for small events and low for larger events when compared to the measured data. Confidence intervals for runoff predictions on both an annual and event basis were also developed for the WEPP model.     

Incorporating Variable Source Area Hydrology into a Spatially Distributed Direct Runoff Model1

Buchanan, Brian, Zachary M. Easton, Rebecca Schneider, and M. Todd Walter, 2011. Incorporating Variable Source Area Hydrology Into a Spatially Distributed Direct Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(1): 43‐60. DOI: 10.1111/j.1752‐1688.2011.00594.x Abstract: Few hydrologic models simulate both variable source area (VSA) hydrology, and runoff‐routing at high enough spatial resolutions to capture fine‐scale hydrologic pathways connecting VSA to the stream network. This paper describes a geographic information system‐based operational model that simulates the spatio‐temporal dynamics of VSA runoff generation and distributed runoff‐routing, including through complex artificial drainage networks. The model combines the Natural Resource Conservation Service’s Curve Number (CN) equation for estimating storm runoff with the topographic index concept for predicting the locations of VSA and a runoff‐routing algorithm into a new spatially distributed direct hydrograph (SDDH) model (SDDH‐VSA). Using a small agricultural watershed in central New York, SDDH‐VSA results were compared to those from a SDDH model using the traditional land use assumptions for the CN (SDDH‐CN). The SDDH‐VSA model generally agreed better with observed discharge than the SDDH‐CN model (average, Nash‐Sutcliffe efficiency of 0.69 vs. 0.58, respectively) and resulted in more realistic spatial patterns of runoff‐generating areas. The SDDH approach did not correctly capture the timing of runoff from small storms in dry periods. Despite this type of limitation, SDDH‐VSA extends the applicability of the SDDH technique to VSA conditions, providing a basis for new tools to help identify critical management areas and assess water quality risks due to landscape alterations.     

The Comparative Accuracy of Two Hydrologic Models in Simulating Warm‐Season Runoff for Two Small,Hillslope Catchments

This article assesses the performance of two hydrologic models in simulating warm‐season runoff for two upland, low‐yield micro‐catchments near Coshocton, Ohio. The two models, namely the Storm Water Management Model (SWMM) and the Gridded Surface‐Subsurface Hydrologic Analysis (GSSHA), were implemented with contrasting levels of complexity, with the former representing the catchments as lumped spatial units and computing evaporation only from standing water, and the latter incorporating fine‐scale variation in topography and soil properties and computing evapotranspiration from soil based on weather data. Our investigation began with uncalibrated model runs for 1990‐2003 except for 1994 using a priori parameter values. Then a set of calibration experiments were performed wherein the sensitivity of model performance to the length of calibration records was examined. Our results pointed to large errors associated with simulations from both models: even the calibrated models were unable to reproduce the seasonal and between‐catchment contrasts in runoff response. Using a priori parameter values, SWMM attained better results than GSSHA. However, with simple calibration, GSSHA outperformed SWMM in several respects. It was also found that extending the record of calibration rendered relatively minor changes to model performance. The practical and scientific implications of the findings are discussed.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Hydrologic Landscape Classification to Estimate Bristol Bay,Alaska Watershed Hydrology

Hydrologic landscapes (HLs) have proven to be a useful tool for broad scale assessment and classification of landscapes across the United States as they help organize larger geographical areas into areas of similar hydrologic characteristics. We developed a HL classification for the Bristol Bay watershed of southwest Alaska that incorporates indices of annual climate and seasonality, terrain, geology, and the influences of large lakes and glaciers. A HL classification is particularly useful in this large watershed because of its hydrologic and landscape variability, important salmon fishery, variety of environmental and potential anthropogenic stressors, and lack of widespread hydrologic data. Following creation of Bristol Bay basin‐wide HL classes, we compared the HL distributions within watersheds grouped by two calculated runoff parameters derived from available long‐term streamflow records and found HL distributions within these groups provided predictive insight on hydrologic behavior. Using these developed runoff groups, we estimated expected hydrologic behavior in watersheds across the larger Bristol Bay watershed that lacked gauged streamflow records. The HL approach provides a scientific basis for estimating the first‐order hydrologic behavior of watersheds and landscapes that lack detailed hydrologic information.     

COMPOSITE VS. DISTRIBUTED CURVE NUMBERS: EFFECTS ON ESTIMATES OF STORM RUNOFF DEPTHS1

ABSTRACT: The U.S. Department of Agriculture Curve Number (CN) method is one of the most common and widely used techniques for estimating surface runoff and has been incorporated into a number of popular hydrologic models. The CN method has traditionally been applied using compositing techniques in which the area weighted average of all curve numbers is calculated for a watershed or a small number of sub-watersheds. CN compositing was originally developed as a time saving procedure, reducing the number of runoff calculations required. However, with the proliferation of high speed computers and geographic information systems, it is now feasible to use distributed CNs when applying the CN method. To determine the effect of using composited versus distributed CNs on runoff estimates, two simulations of idealized watersheds were developed to compare runoff depths using composite and distributed CNs. The results of these simulations were compared to the results of similar analyses performed on an urbanizing watershed located in central Indiana and show that runoff depth estimates using distributed CNs are as much as 100 percent higher than when composited CNs are used. Underestimation of runoff due to CN compositing is a result of the curvilinear relationship between CN and runoff depth and is most severe for wide CN ranges, low CN values, and low precipitation depths. For larger design storms, however, the difference in runoff computed using composite and distributed CNs is minimal.     

CALIBRATION OF STORM LOADS IN THE SOUTH PRONG WATERSHED,FLORIDA, USING BASINS/HSPF1

ABSTRACT: The South Prong watershed is a major tributary system of the Sebastian River and adjacent Indian River Lagoon. Continued urbanization of the Sebastian River drainage basin and other watersheds of the Indian River Lagoon is expected to increase runoff and nonpoint source pollutant loads. The St. Johns River Water Management District developed watershed simulation models to estimate potential impacts on the ecological systems of receiving waters and to assist planners in devising strategies to prevent further degradation of water resources. In the South Prong system, a storm water sampling program was carried out to calibrate the water quality components of the watershed model for total suspended solids (TSS), total phosphorous (TP), and total nitrogen (TN). During the period of May to November 1999, water quality and flow data were collected at three locations within the watershed. Two of the sampling stations were located at the downstream end of major watercourses. The third station was located at the watershed outlet. Five storm events were sampled and measured at each station. Sampling was conducted at appropriate intervals to represent the rising limb, peak, and recession limb of each storm event. The simulations were handled by HSPF (Hydrologic Simulation Program‐Fortran). Results include calibration of the hydrology and calibration of the individual storm loads. The hydrologic calibration was continuous over the period 1994 through 1999. Simulated storm runoff, storm loads, and event mean concentrations were compared with their corresponding observed values. The hydrologic calibration showed good results. The outcome of the individual storm calibrations was mixed. Overall, however, the simulated storm loads agreed reasonably well with measured loads for a majority of the storms.     

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.     

HYDROLOGIC RESPONSE OF MASSACHUSETTS WATERSHEDS1

Hydrologic response, defined as the annual direct runoff divided by the annual precipitation, was computed for twenty-one watersheds in or near western Massachusetts, using a total of 232 years of hydrologic records. Variability of the results over the period of analysis was greater than is desirable to inspire confidence in the usefulness of the hydrologic response function; however, the results do suggest that the hydrologic response concept, with appropriate refinements, could be applied successfully to the problem of delineating hydrologic provinces and determination of drainage and storage in unregulated watersheds.     

Linking Hydrologic Alteration to Biological Impairment in Urbanizing Streams of the Puget Lowland,Washington, USA1

Abstract: We used a retrospective approach to identify hydrologic metrics with the greatest potential for ecological relevance for use as resource management tools (i.e., hydrologic indicators) in rapidly urbanizing basins of the Puget Lowland. We proposed four criteria for identifying useful hydrologic indicators: (1) sensitive to urbanization consistent with expected hydrologic response, (2) demonstrate statistically significant trends in urbanizing basins (and not in undeveloped basins), (3) be correlated with measures of biological response to urbanization, and (4) be relatively insensitive to potentially confounding variables like basin area. Data utilized in the analysis included gauged flow and benthic macroinvertebrate data collected at 16 locations in 11 King County stream basins. Fifteen hydrologic metrics were calculated from daily average flow data and the Pacific Northwest Benthic Index of Biological Integrity (B‐IBI) was used to represent the gradient of response of stream macroinvertebrates to urbanization. Urbanization was represented by percent Total Impervious Area (%TIA) and percent urban land cover (%Urban). We found eight hydrologic metrics that were significantly correlated with B‐IBI scores (Low Pulse Count and Duration; High Pulse Count, Duration, and Range; Flow Reversals, T_Qmean, and R‐B Index). Although there appeared to be a great deal of redundancy among these metrics with respect to their response to urbanization, only two of the metrics tested – High Pulse Count and High Pulse Range – best met all four criteria we established for selecting hydrologic indicators. The increase in these high pulse metrics with respect to urbanization is the result of an increase in winter high pulses and the occurrence of high pulse events during summer (increasing the frequency and range of high pulses), when practically none would have occurred prior to development. We performed an initial evaluation of the usefulness of our hydrologic indicators by calculating and comparing hydrologic metrics derived from continuous hydrologic simulations of selected basin management alternatives for Miller Creek, one of the most highly urbanized basins used in our study. We found that the preferred basin management alternative appeared to be effective in restoring some flow metrics close to simulated fully forested conditions (e.g., T_Qmean), but less effective in restoring other metrics such as High Pulse Count and Range. If future research continues to support our hypothesis that the flow regime, particularly High Pulse Count and Range, is an important control of biotic integrity in Puget Lowland streams, it would have significant implications for stormwater management.     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

MACROSCALE HYDROLOGIC MODELING FOR REGIONAL CLIMATE ASSESSMENT STUDIES IN THE SOUTHEASTERN UMTED STATES1

ABSTRACT: A macroscale hydrologic model is developed for regional climate assessment studies under way in the southeastern United States. The hydrologic modeling strategy is developed to optimize spatial representation of basin characteristics while maximizing computational efficiency. The model employs the “grouped response unit” methodology, which follows the natural drainage pattern of the area. First order streams are delineated and their surface characteristics are tested so that areas with statistically similar characteristics can be combined into larger computational zones for modeling purposes. Hydrologic response units (HRU) are identified within the modeling units and a simple three‐layer water balance model, Soil and Water Assessment Tool (SWAT), is executed for each HRU. The runoff values are then convoluted using a triangular unit hydrograph and routed by Muskingum‐Cunge method. The methodology is shown to produce accurate results relative to other studies, when compared to observations. The model is used to evaluate the potential error in hydrologic assessments when using GCM predictions as climatic input in a rainfall‐runoff dominated environment. In such areas, the results from this study, although limited in temporal and spatial scope, appear to imply that use of GCM climate predictions in short term quantitative analyses studies in rainfall‐runoff dominated environments should proceed with caution.