STATISTICAL LOW FLOW ESTIMATION USING GIS ANALYSIS IN HUMID MONTANE REGIONS IN PUERTO RICO1

ABSTRACT: Statistical analysis of watershed parameters derived using a Geographical Information system (GIS) was done to develop equations for estimating the 7d–10yr, 30d–10yr, and 7d–2yr low flow for watersheds in humid montane regions of Puerto Rico. Digital elevation models and land use, geology, soils, and stream network coverages were used to evaluate 21 geomorphic, 10 stream channel, 9 relief, 7 geology, 4 climate, and 2 soil parameters for each watershed. To assess which parameters should be used for further investigation, a correlation analysis was used to determine the independence and collinearity among these parameters and their relationship with low flows. Multiple regression analyses using the selected parameters were then performed to develop the statistical models of low flows. The final models were selected in the basis of the Mallow Cp statistic, the adjusted R², the Press statistic, the degree of collinearity, and an analysis of the residuals. In the final models, drainage density, the ratio of length of tributaries to the length of the main channel, the percent of drainage area with northeast aspect, and the average weighted slope of the drainage were the most significant parameters. The final models had adjusted standard errors of 58.7 percent, 59.2 percent, and 48.6 percent for the 7d–10yr, 30d–10yr, and 7d–2yr low flows respectively. For comparison, the best model based on watershed parameters that can be easily measured without a GIS had an adjusted standard error of 82.8 percent.     

Using a GIS Model to Identify Internally Drained Areas and Runoff Contribution in a Glaciated Watershed1

Macholl, Jacob A., Katherine A. Clancy, and Paul M. McGinley, 2011. Using a GIS Model to Identify Internally Drained Areas and Runoff Contribution in a Glaciated Watershed. Journal of the American Water Resources Association (JAWRA) 47(1):114‐125. DOI: 10.1111/j.1752‐1688.2010.00495.x Abstract: Glaciated watersheds are not easily delineated using geographic information systems’ elevation‐based algorithms, especially where stream networks are disconnected and there are large regions of internally drained areas. This paper presents the results of an analysis using the Potential Contributing Source Area (PCSA) model to identify potential contributing areas, defined as areas from which runoff is physically capable of reaching a drainage network. The investigation was conducted to define the potential contributing areas in a glaciated region of northwest Wisconsin. The curve number (CN) method was used to predict runoff volumes in the watershed. The streamflows of four tributaries were measured and the runoff portion of the hydrograph quantified to be compared with runoff estimates calculated using the potential contributing areas and the traditional catchment area. Runoff producing events occurred, but the use of area‐weighted CN values was unsuccessful in modeling runoff due to all precipitation depths during the study period falling below the initial abstraction. A distributed CN approach provided runoff estimates that were generally better using the potential contributing areas compared with using the traditional catchment area. The extent of the minimum contributing area, estimated for a range of precipitation events, was found to be substantially less than the potential contributing areas, suggesting that the PCSA model delimits the maximum boundary of potential contributing areas.     

USING A GIS FOR ESTIMATING INPUT PARAMETERS IN URBAN STORMWATER QUALITY MODELING1

ABSTRACT: Geographic Information Systems (GIS) are being used increasingly as a method of preparing, analyzing, and displaying data for watershed analysis and modeling. Although GIS technology is a powerful tool for integrating and analyzing watershed characteristics, the initial preparation of the necessary database is often a time consuming and costly endeavor. This demonstration project assesses the viability of creating a cost-effective spatial database for urban stormwater modeling from existing digital and hard-copy data sources. The GIS was used to provide input parameters to the Source Loading and Management Model (SLANM), an empirical urban stormwater quality model. Land use characteristics, drainage boundaries, and soils information were geocoded and referenced to a base data layer consisting of transportation features. GIS overlay and data manipulation capabilities were utilized to preprocess the input data for the model. Model output was analyzed through postprocessing by GIS, and results were compared to a similar recent modeling study of the same watershed. The project, undertaken for a small urban watershed located in Plymouth, Minnesota, successfully demonstrates that the use of GIS in stormwater management can allow even small communities to reap the benefits of stormwater quality modeling.     

INTEGRATING GEOGRAPHIC INFORMATION SYSTEMS IN GROUND-WATER APPLICATIONS USING NUMERICAL MODELING TECHNIQUES1

ABSTRACT: The Sand and Gravel Aquifer is the sole source of potable water in Escambia County, Florida. In order to better understand the hydraulics of the aquifer, a numerical computer model of the aquifer was developed. The model applied a finite element technique which allowed for density-dependent transport and flow in three dimensions. The modeling technique was integrated with GIS to develop a system for optimal management of the resource. The GIS was the primary tool in the development of the model grid, as well as being the integral component in the modeling procedure. Multiple model grids were developed for simulating regional flow and local flow/transport phenomena. The model grids were generated by the GIS where nodal and element sequencing were recorded. The grid topology was stored in the GIS with the element numbers, node numbers, and the related hydrogeologic attributes. The Triangulated Irregular Network (TIN) module was used for transferring interpolated value between GIS coverages. TIN allowed a fit of the model grid to the physical dimensions of the aquifer and for interpolating boundary values for telescopically refined grids. Calculations between TIN surfaces provided the residuals of the dependent variable from observed TIN surfaces. Model calibration was conducted within the GIS environment through a combination of visual and relational querying. The GIS provided an integrated environment which facilitated model analyses and data storage and retrieval.     

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.     

WATERSHED CONFIGURATION AND GEOGRAPHIC INFORMATION SYSTEM PARAMETERIZATION FOR SPUR MODEL HYDROLOGIC SIMULATIONS1

ABSTRACT: A grid cell geographic information system (GIS) is used to parameterize SPUR, a quasi-physically based surface runoff model in which a watershed is configured as a set of stream segments and contributing areas. GIS analysis techniques produce various watershed configurations by progressive simplification of a stream network delineated from digital elevation models (DEM). We used three watershed configurations: ≥ 2nd, ≥ 4th, and ≥ 13th Shreve order networks, where the watershed contains 28, 15, and 1 channel segments with 66, 37, and 3 contributing areas, respectively. Watershed configuration controls simulated daily and monthly sums of runoff volumes. For the climatic and topographic setting in southeastern Arizona the ≥ 4th order configuration of the stream network and contributing areas produces results that are typically as good as the ≥ 2nd order network. However both are consistently better than the ≥ 13th order configuration. Due to the degree of parameterization in SPUR, model simulations cannot be significantly improved by increasing watershed configuration beyond the ≥ 4th order network. However, a range of Soil Conservation Service curve numbers derived from rainfall/runoff data can affect model simulations. Higher curve numbers yield better results for the ≥ 2nd order network while lower curve numbers yield better results for the ≥ 4th order network.     

COMPARATIVE EVALUATION OF LAND COVER DATA SOURCES FOR EROSION PREDICTION1

ABSTRACT: A fundamental problem in protecting surface drinking water supplies is the identification of sites highly susceptible to soil erosion and other forms of nonpoint source (NPS) pollution. The New York City Department of Environmental Protection is trying to identify erodible sites as part of a program aimed at avoiding costly filtration. New York City's 2,000 square mile watershed system is well suited for analysis with geographic information systems (GIS); an increasingly important tool to determine the spatial distribution of sensitive NPS pollution areas. This study used a GIS to compare three land cover sources for input into the Modified Universal Soil Loss Equation (MUSLE), a model estimating soil loss from rangeland and forests, for a tributary watershed within New York City's water supply system. Sources included both conventional data (aerial photography) and Landsat data (MSS and TM images). Although land cover classifications varied significantly across these sources, location-specific and aggregate watershed predictions of the MUSLE were very similar. We conclude that using Landsat TM imagery with a hybrid classification algorithm provides a rapid, objective means of developing large area land cover databases for use in the MUSLE, thus presenting an attractive alternative to photo interpretation.     

EXPOSURE ASSESSMENT OF POPULATIONS USING ENVIRONMENTAL MODELING,DEMOGRAPHIC ANALYSIS,AND GIS1

ABSTRACT: Simulation of ground-water flow and fate of contaminants in the subsurface environment constitutes a major phase of most environmental assessment and site remediation studies. These simulation studies yield information on spatial and temporal distributions of contaminants in the subsurface media. An important use of this information is to conduct exposure assessment studies. Spatial and temporal distributions of both chemical concentrations and exposed populations render this integrated exposure analysis task rather difficult. Geographic Information Systems (GIS), on the other hand, provide a platform in which layered, spatially distributed databases can be manipulated with ease, thereby simplifying exposure analysis tasks significantly. In this paper, we describe procedures that combine the simulation models and demographic databases under a GIS platform to automate the exposure assessment phase of a typical health assessment study. Procedures developed herein significantly simplify the post-processing phase of the analysis, and render the overall task more ‘user friendly.’ A site-specific application is included as a demonstration of the proposed process.     

LANDSAT MID-INFRARED DATA AND GIS IN REGIONAL SURFACE SOIL-MOISTURE ASSESSMENT1

ABSTRACT: Landsat satellite Thematic Mapper (TM) data were used to assess regional soil moisture conditions. The mid-infrared (MIR) data of TM band 7 were overlain onto four principal land-use categories (Agricultural/Irrigated, Urban/Clearings, Forest/ Wetlands, Water) using a geographic information system (GIS). M data were used to assess four qualitative surface soil-moisture conditions (water/very wet, wet, moist, and dry) within each land-use category of a 208,354 ha southwestern Florida study area. The MIR response was inversely related to the qualitative surface soil-moisture content. Integration of Landsat TM MIR data with land use through GIS appears to be a useful technique for high-resolution regional soil moisture assessment, and further research to reline this technique is recommended.