A DISTRIBUTED DYNAMIC WATERSHED MODEL1

ABSTRACT: A distributed watershed model was developed to mathematically simulate overland and channel flow for a single-event storm. The modeled watersheds in the study were subdivided into rectangular grid elements. All hydrologically significant parameters, such as land slope, rainfall and precipitation excess, were assumed to be uniform within each element. The Green-Ampt method was adopted to generate precipitation excess for each element during the simulation period. A two-dimensional diffusion wave model was used for overland flow routing and an iterative Alternative Direction Implicit scheme was used to solve the simultaneous overland flow equations. Once the overland flow became inflow to the channel, a one-dimensional dynamic wave flood routing technique, based on a four-point, implicit, non-linear finite difference solution of the St. Venant equation of unsteady flow, was applied. A limited number of comparisons were made between simulated and observed hydrographs for areas of about one square mile. Given the appropriate parameters, the model was able to accurately simulate runoff for single-event storms. This paper describes a distributed watershed model developed to simulate overland and channel flow. Comparisons were made between simulated and observed hydrographs for three watersheds. The model was able to accurately simulate the runoff for single-event storms using 61-m by 61-m (200 ft by 200 ft) watershed grid elements.     

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.     

Examining Modeling Approaches for the Rainfall‐Runoff Process in Wildfire‐Affected Watersheds: Using San Dimas Experimental Forest

Wildfire can significantly change watershed hydrological processes resulting in increased risks for flooding, erosion, and debris flow. The goal of this study was to evaluate the predictive capability of hydrological models in estimating post‐fire runoff using data from the San Dimas Experimental Forest (SDEF), San Dimas, California. Four methods were chosen representing different types of post‐fire runoff prediction methods, including a Rule of Thumb, Modified Rational Method (MODRAT), HEC‐HMS Curve Number, and KINematic Runoff and EROSion Model 2 (KINEROS2). Results showed that simple, empirical peak flow models performed acceptably if calibrated correctly. However, these models do not reflect hydrological mechanisms and may not be applicable for predictions outside the area where they were calibrated. For pre‐fire conditions, the Curve Number approach implemented in HEC‐HMS provided more accurate results than KINEROS2, whereas for post‐fire conditions, the opposite was observed. Such a trend may imply fundamental changes from pre‐ to post‐fire hydrology. Analysis suggests that the runoff generation mechanism in the watershed may have temporarily changed due to fire effects from saturation‐excess runoff or subsurface storm dominated complex mechanisms to an infiltration‐excess dominated mechanism. Infiltration modeling using the Hydrus‐1D model supports this inference. Results of this study indicate that physically‐based approaches may better reflect this trend and have the potential to provide consistent and satisfactory prediction.     

APPLICATION OF THE GREEN-AMPT INFILTRATION EQUATION TO WATERSHED MODELING1

ABSTRACT: A computer model was developed, based on the Green-Ampt infiltration equation, to computed rainfall excess for a single precipitation event. The model requires an estimate of parameters related to hydraulic conductivity, wetting front section, and fillable porosity of the soil layers. Values of parameters were estimated from soil textural averages or regression equations based on percent sand, percent clay, and porosity. Average values of effective porosity and wetting front suction were largely acceptable due to the relatively low variability and low model sensitivity to the parameters. Hydraulic conductivity was the most erratic constituent of the loss rate computation due to the high variability and the high sensitivity of the computed infiltration to the parameter. The performance of the Green-Ampt infiltration model was tested through a comparison with the SCS curve number procedure. Seven watersheds and 23 storms with precipitation of one inch or greater were used in the comparison. For storms with less than one inch of rainfall excess, the SCS curve number procedure generally gave the best results; however, for six of the seven storms with precipitation excess greater than one inch, the Green-Ampt procedure delivered better results. In this comparison, both procedures used the same initial abstractions. The separation of rainfall losses into infiltration, interception, and surface retention is, in theory, an accurate method of estimating precipitation excess. In the second phase of the study using nine watersheds and 39 storms, interception and surface retention losses were computed by the Horton equations. Green-Ampt and interception parameters were estimated from value sin the literature, while the surface retention parameter was calibrated so that the computed runoff volumes matched observed volumes. A relationship was found between the surface retention storage capacity and the 15-day antecedent precipitation index, month of year, and precipitation amount.     

STORM RUNOFF PREDICTION BASED ON A SPATIALLY DISTRIBUTED TRAVEL TIME METHOD UTILIZING REMOTE SENSING AND GIS1

ABSTRACT: In this study, remotely sensed data and geographic information system (GIS) tools were used to estimate storm runoff response for Simms Creek watershed in the Etonia basin in northeast Florida. Land cover information from digital orthophoto quarter quadrangles (DOQQ), and enhanced thematic mapper plus (ETM+) were analyzed for the years 1990, 1995, and 2000. The corresponding infiltration excess runoff response of the study area was estimated using the U.S. Department of Agriculture (USDA), Natural Resources Conservation Service Curve Number (NRCS‐CN) method. A digital elevation model (DEM)/GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. A comparison of predicted to observed stream response shows that the model predicts the total runoff volume with an efficiency of 0.98, the peak flow rate at an efficiency of 0.85, and the full direct runoff hydrograph with an average efficiency of 0.65. The DEM/GIS travel time model can be used to predict the runoff response of ungaged watersheds and is useful for predicting runoff hydrographs resulting from proposed large scale changes in the land use.     

A SURVEY OF HYDROLOGY COURSE CONTENT IN NORTH AMERICAN UNIVERSITIES1

ABSTRACT: This report presents the results of a survey of hydrology faculties of colleges and universities in the United States and Canada. Information is presented on topics covered in classes, allocation of class periods to individual topics, textbooks, prerequisites, computer use, and accreditation categories for hydrology courses offered by engineering departments. Hydrology courses generally require courses in fluid mechanics, mathematics, statistics, and computer science as prerequisites. Topics that receive the largest allocation of time in both introductory and advanced courses include rainfall-runoff relations, the hydrologic cycle, routing and open channel flow, and statistics. Advanced courses place greater emphasis on watershed models than do the introductory courses. Hydrology courses at both levels allocate the smallest amounts of time to snow hydrology ground-water hydrology, and “other topics.” Very few courses include field or experimental work. In a discipline where computer modeling is a major tool, this lack of field and data-collection experience may lead students to underestimate the uncertainties associated with data used to calibrate models and the modeling results themselves. Survey responses on hydrology courses taught in departments other than civil engineering were too few to permit detailed analysis. Most of these courses spend approximately two-thirds of available class time on the same topics as presented in engineering hydrology courses. The balance of class time is spent on topics that emphasize the specialized interest of the particular discipline, such as soil physics and soil moisture in agricultural engineering.     

APPLICATION OF AN INTEGRATED BASIN-SCALE HYDROLOGIC MODEL TO SIMULATE SURFACE-WATER AND GROUND-WATER INTERACTIONS1

ABSTRACT: Hydrologic models have become an indispensable tool for studying processes and water management in watersheds. A physically-based, distributed-parameter model, Basin-Scale Hydro-logic Model (BSIIM), has been developed to simulate the hydrologic response of large drainage basins. The model formulation is based on equations describing water movement both on the surface and in the subsurface. The model incorporates detailed information on climate, digital elevation, and soil moisture budget, as well as surface-water and ground-water systems. This model has been applied to the Big Darby Creek Watershed, Ohio in a 28-year simulation of rainfall-runoff processes. Unknown coefficients for controlling runoff, storativity, hydraulic conductivity, and streambed permeability are determined by a trial-and-error calibration. The performance of model calibration and predictive capability of the model was evaluated based on the correlation between simulated and observed daily stream discharges. Discrepancies between observed and simulated results exist because of limited precipitation data and simplifying assumptions related to soil, land use, and geology.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

WATERSHED MODELS AND THEIR APPLICABILITY TO CONJUNCTIVE USE MANAGEMENT1

ABSTRACT: Techniques employed to simulate infiltration and subsurface ground-water flow were examined for a number of available watershed models. The large number of processes that these models simulate prohibits detailed analysis of subsurface flow, due to excessive computer and data requirements. Such models emphasize surface flow and include only that portion of water lost to the subsurface and the portion returned to the stream as baseflow. Problems were examined in adopting conjunctive use models, which allow the coordinated exploitation and management of both surface and ground-water resources. The application of conjunctive use models in water resources management is expected to increase dramatically over the next decade.     

LAND SURFACE PARAMETERIZATIONS OF GCMs AND MACROSCALE HYDROLOGICAL MODELS1

ABSTRACT: Climatic variation and the possibility of anthropogenically-caused climatic change have emphasized the need for global hydrological cycle models able to simulate the impacts of climate on the atmosphere, continents and oceans. To date, global atmospheric and oceanic models have been developed but, to the best of the author's knowledge, there are no continental hydrological models. Instead, hydrological models continue to develop at the catchment scale and the land phase component of the global hydrologic cycle is modeled as parameterizations within atmospheric models. The author argues that this is not the best solution; that the present land surface components of atmospheric models do not accurately model land phase hydrology and that, instead, atmospheric and oceanic models should be linked to continental-scale hydrological models to form a true model of the global hydrological cycle.     

POTENTIAL CLIMATE CHANGE IMPACTS ON MOUNTAIN WATERSHEDS IN THE PACIFIC NORTHWEST1

ABSTRACT: Global climate change due to the buildup of greenhouse gases in the atmosphere has serious potential impacts on water resources in the Pacific Northwest. Climate scenarios produced by general circulation models (GCMs) do not provide enough spatial specificity for studying water resources in mountain watersheds. This study uses dynamical downscaling with a regional climate model (RCM) driven by a GCM to simulate climate change scenarios. The RCM uses a subgrid parameterization of orographic precipitation and land surface cover to simulate surface climate at the spatial scale suitable for the representation of topographic effects over mountainous regions. Numerical experiments have been performed to simulate the present-day climatology and the climate conditions corresponding to a doubling of atmospheric CO₂ concentration. The RCM results indicate an average warming of about 2.5°C, and precipitation generally increases over the Pacific Northwest and decreases over California. These simulations were used to drive a distributed hydrology model of two snow dominated watersheds, the American River and Middle Fork Flathead, in the Pacific Northwest to obtain more detailed estimates of the sensitivity of water resources to climate change. Results show that as more precipitation falls as rain rather than snow in the warmer climate, there is a 60 percent reduction in snowpack and a significant shift in the seasonal pattern of streamflow in the American River. Much less drastic changes are found in the Middle Fork Flathead where snowpack is only reduced by 18 percent and the seasonal pattern of streamflow remains intact. This study shows that the impacts of climate change on water resources are highly region specific. Furthermore, under the specific climate change scenario, the impacts are largely driven by the warming trend rather than the precipitation trend, which is small.     

FOREST HYDROLOGY IN THE PACIFIC NORTHWEST: ADDITIONAL RESEARCH NEEDS1

ABSTRACT: While much is known about the hydrology of forested mountain catchments in the Pacific Northwest, important research questions remain. For example, the dynamics of storm precipitation amounts and the modeling of catchment outflows represent a continuing research need. Without an improved understanding of the spatial and temporal aspects of storm precipitation patterns, our ability to evaluate and improve physically-based hydrologic models is limited. From a practical perspective, tens of thousands of kilometers of access roads have been constructed across forested catchments of the Pacific Northwest. Yet, few forestry research programs focus on road drainage (e.g., ditches, culverts, fords). The few studies that address this issue indicate road drainage systems need to function effectively over a wide range of flow events and terrain conditions. In addition, historical forest practices associated with hillslopes and riparian systems have altered the character of many Pacific Northwest aquatic ecosystems. If restoration of these systems is to be effective, research efforts are needed to better understand the linkages between riparian forests, geomorphic processes, and hydrologic disturbance regimes.     

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.     

SENSITIVITY OF A PRAIRIE WETLAND TO INCREASED TEMPERATURE AND SEASONAL PRECIPITATION CHANGES1

ABSTRACT: We assessed the potential effects of increased temperature and changes in amount and seasonal timing of precipitation on the hydrology and vegetation of a semi-permanent prairie wetland in North Dakota using a spatially-defined, rule-based simulation model. Simulations were run with increased temperatures of 2°C combined with a 10 percent increase or decrease in total growing season precipitation. Changes in precipitation were applied either evenly across all months or to individual seasons (spring, summer, or fall). The response of semi-permanent wetland P1 was relatively similar under most of the seasonal scenarios. A 10 percent increase in total growing season precipitation applied to summer months only, to fall months only, and over all months produced lower water levels compared to those resulting from the current climate due to increased evapotranspiration. Wetland hydrology was most affected by changes in spring precipitation and runoff. Vegetation response was relatively consistent across scenarios. Seven of the eight seasonal scenarios produced drier conditions with no open water and greater vegetation cover compared to those resulting from the current climate. Only when spring precipitation increased did the wetland maintain an extensive open water area (49 percent). Potential changes in climate that affect spring runoff, such as changes to spring precipitation and snow melt, may have the greatest impact on prairie wetland hydrology and vegetation. In addition, relatively small changes in water level during dry years may affect the period of time the wetland contains open water. Emergent vegetation, once it is established, can survive under drier conditions due to its ability to persist in shallow water with fluctuating levels. The model's sensitivity to changes in temperature and seasonal precipitation patterns accentuates the need for accurate regional climate change projections from general circulation models.     

PRECIPITATION DIFFERENCES AMONGST GCMs USED FOR THE U.S. NATIONAL ASSESSMENT1

ABSTRACT: Two general circulation models (GCMs) used in the U.S. national assessment of the potential consequences of climate variability and change (CGCM1 and HadCM2) show a large increase in precipitation in the future over the southwestern U.S., particularly during winter. This precipitation increase is an extension of a larger region of increased precipitation in the Pacific Ocean off the west coast of North America that is associated with a deepened and southward-shifted Aleutian Low, a weaker subtropical high, and warmer sea surface temperatures (SSTs). The models differ in their simulation of precipitation anomalies over the southeastern U.S., with CGCM1 showing drier conditions and HadCM2 showing wetter conditions in the future. While both models show decreased frequency of Atlantic storms, consistent with decreased meridional and land/sea temperature gradients, the more coastal position of the storm track in CGCM1 results in less precipitation than modern along the eastern seaboard of the U.S. During summer, differences in land surface models within the two GCMs sometimes lead to differences in soil moisture that feed back to the precipitation over land due to available moisture.     

STORM CHARACTERISTICS OF CONVECTIVE-SCALE PRECIPITATION1

A classification scheme for convective precipitation, having applications in both analysis and modeling of meteorological and hydrological events, is presented. The method is based upon observations of rainfall at the ground, radar scans of storm events, and visible and infrared satellite imagery of larger storm systems. Empirical and theoretical frequency distributions are derived for total storm rainfall, rainfall duration and time between storms for each of the convective categories. This stratification is directly applicable to the experimental design and evaluation of weather modification projects and may be useful for the development and interpretation of meteorological and hydrological models. When atmospheric conditions limit storm development to cells, rainfall was seldom observed. Small clusters also produce small amounts of rainfall but have a longer lifetime than cells and are likely candidates for cloud seeding attempts to encourage their growth to large clusters. Large and nested clusters usually produce large amounts of natural precipitation. A few large storms account for most of a season's rainfall.     

Probabilistic Streamflow Generation Model for Data Sparse Arid Watersheds1

Abstract: The authors present a model that generates streamflow for ephemeral arid streams. The model consists of a stochastic hourly precipitation point process model and a conceptual model that transforms precipitation into flow. It was applied to the Santa Cruz River at the border crossing from Mexico into Southern Arizona. The model was constructed for four different seasons and three categories of inter‐annual variability for the wet seasons of summer and winter. The drainage area is ungauged and precipitation information was inferred from a precipitation gauge downstream. The precipitation gauge record was evaluated against simulated precipitation from a mesoscale numerical weather prediction model, and was found to be the representative of the regional precipitation variability. The flow generation was found to reproduce the variability in the observed record at the daily, seasonal and annual time scales, and it is suitable for use in planning studies for the study site.     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

RESPONSE OF GREEN‐AMPT MEIN‐LARSEN SIMULATED RUNOFF VOLUMES TO TEMPORALLY AGGREGATED PRECIPITATION1

ABSTRACT: Data collection frequency in automated systems is user determined and can range from seconds to hours or days. Currently, there is no standard or recommended frequency interval for collecting precipitation data from automated systems for input to event‐based models such as Green‐Ampt Mein‐Larsen (GAML). Data from 47 storm events at seven locations were used to simulate the response of GAML excess rainfall to temporally aggregated precipitation data. No difference in model efficiency was recognized when comparing one‐minute interval data (R²= 1.00) to five‐minute data (R²= 1.00). Very little model efficiency was lost at a 10‐minute (R²= 0.96) interval. After 10‐minutes, decline in efficiency became more rapid with R²= 0.16 at one hour. The combined effect of time interval with respect to drainage area, hydraulic conductivity, maximum 30‐minute intensity, and total precipitation also revealed similar results.