AN ANALYSIS OF SEASONAL FECAL COLIFORM LEVELS IN THE TCHEFUNCTE RWER1

ABSTRACT: A model for estimating seasonal fecal coliform concentrations in the Tchefuncte River as a function of river discharge was developed. Data on fecal coliform concentration were obtained from the Louisiana Department of Health and Hospitals and were available for a period of 15 years (1975 through 1992) from three locations. Stream flow data were obtained from a gaging station of the U. S. Geological Survey at Folsom, Louisiana. These data were available for 49 years (1943 through 1991). The climate of the area is characterized by different precipitation/runoff mechanisms for the summer and winter seasons. The division for seasons used in this analysis was May through October (summer season), and November through April (winter season). Because of the combined effects of climatic mechanisms causing precipitation and the seasonal variation of evapotranspiration, runoff is greater in the winter season resulting in higher fecal coliform counts in the Tchefuncte River. Statistical analysis revealed a statistically significant relationship between fecal coliform concentration and discharge for each season, at each of three sites on the Tchefuncte River.     

A river water quality model integrated with a web-based geographic information system

Scientists often use mathematical models to assess river water quality. However, the application of the models in environmental management and risk assessment is quite limited because of the difficulty of preparing input data and interpreting model output. This paper presents a study that links ArcIMS, a Web-based Geographic Information System (GIS) software to ROUT, a national and regional scale river model which evolved from the US Environmental Protection Agency's Water Use Improvement and Impairment Model, to create a WWW-GIS-based river simulation model called GIS-ROUT. GIS-ROUT is used to predict chemical concentrations in perennially flowing rivers throughout the continental United States that receive discharges from more than 10,000 publicly owned wastewater treatment plants (WWTPs). The WWTP chemical loadings are calculated from per capita per day disposal of product ingredients and the population served by each plant. Each WWTP, containing data on treatment type and influent and effluent flows, is spatially associated with a specific receiving river segment. Based on user defined treatment-type removal rates for a particular chemical, an effluent concentration for each WWTP is calculated and used as input to the river model. Over 360,000 km of rivers are modeled, incorporating dilution and first order loss of the chemical in each river segment. The integration of spatial data, GIS, the WWW, and modeling in GIS-ROUT makes it possible to organize and analyze data spatially, and view results on interactive maps as well as tables and distribution charts. The integration allows scientists and managers in different locations to coordinate and share their estimations for environmental exposure and risk assessments.     

CHANGING NEAR‐STREAM LAND USE AND RWER CHANNEL MORPHOLOGY IN THE VENEZUELAN ANDES1

ABSTRACT: The shape of a river channel is linked to surrounding land use through interacting hydrologic and geologic processes. This study analyzes the relationship between the change in near‐stream land use and the shape of the adjacent river channel over time. Three watersheds in the foothills of the Venezuelan Andes that have experienced differing degrees of development were studied to determine river channel width, sinuosity, and position relative to surrounding land use. Change in land use over time was obtained from multiple‐date aerial photographs (1946 and 1980) referenced to 1996 Landsat Thematic Mapper (TM) satellite imagery, and verified by field inspection. Measurements of land‐use type and amount and river channel morphology from the two dates were made using geographic information system (GIS) methods. The three watersheds differed in the extent of deforestation, the location of remaining forested land, and how much land‐use change had already occurred by 1946. Change in river channel morphology was greatest at the most deforested sites. Valley shape and channel constraint also had a discernible effect on change in channel morphology. This study introduces a method for analyzing change in coupled terrestrial‐aquatic systems based on multiple‐date, remotely sensed data and GIS analysis of spatial properties. The results document human impacts on river channels through a comparison of multiple watersheds over a 35‐year time interval.     

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.     

Application of Likelihood Ratio and Logistic Regression Models to Landslide Susceptibility Mapping Using GIS

For landslide susceptibility mapping, this study applied and verified a Bayesian probability model, a likelihood ratio and statistical model, and logistic regression to Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite imagery and field surveys; and a spatial database was constructed from topographic maps, soil type, forest cover, geology and land cover. The factors that influence landslide occurrence, such as slope gradient, slope aspect, and curvature of topography, were calculated from the topographic database. Soil texture, material, drainage, and effective depth were extracted from the soil database, while forest type, diameter, and density were extracted from the forest database. Land cover was classified from Landsat TM satellite imagery using unsupervised classification. The likelihood ratio and logistic regression coefficient were overlaid to determine each factors rating for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared with known landslide locations. The logistic regression model had higher prediction accuracy than the likelihood ratio model. The method can be used to reduce hazards associated with landslides and to land cover planning. Note: This version was published online in June 2005 with the cover date of August 2004.     

Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin1

Gebremichael, Mekonnen, Emmanouil N. Anagnostou, and Menberu M. Bitew, 2010. Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin. Journal of the American Water Resources Association (JAWRA) 46(2):361-366. DOI: 10.1111/j.1752-1688.2010.00428.x. Abstract: Given the increasingly higher resolution and data accessibility, satellite precipitation products could be useful for hydrological application in the Nile River Basin, which is characterized by lack of reasonably dense hydrological in situ sensors and lack of access to the existing dataset. However, in the absence of both extreme caution and research results for the Nile basin, the satellite rainfall (SR) products may not be used, or may even be used erroneously. We identify two steps that are critical to enhance the value of SR products for hydrological applications in the Nile basin. The first step is to establish representative validation sites in the Nile basin. The validation site will help to quantify the errors in the different kinds of SR products, which will be used to select the best products for the Nile basin, include the errors in decision making, and design strategies to minimize the errors. Using rainfall measurements collected from the unprecedented high-density rain gauge network over a small region within the Nile basin, we indicate that SR estimates could be subject to significant errors, and quantification of estimation errors by way of establishing validation sites is critically important in order to use the SR products. The second step is to identify the degree of hydrologic model complexity required to obtain more accurate hydrologic simulation results for the Nile basin when using SR products as input. The level of model complexity may depend on basin size and SR algorithm, and further research is needed to spell out this dependence for the Nile basin.     

NETWORK DESIGN FOR WATER SUPPLY FORECASTING IN THE WEST1

ABSTRACT: The objective is to develop techniques to evaluate how changes in basic data networks can improve accuracy of water supply forecasts for mountainous areas. The approach used was to first quantify how additional data would improve our knowledge of winter precipitation, and second to estimate how this knowledge translates, quantitatively, into improvement in forecast accuracy. A software system called DATANET was developed to analyze each specific gage network alternative. This system sets up a fine mesh of grid points over the basin. The long-term winter mean precipitation at each grid point is estimated using a simple atmospheric model of the orographic precipitation process. The mean runoff at each grid point is computed from the long-term mean precipitation estimate. The basic runoff model is calibrated to produce the observed long-term runoff. The error analysis is accomplished by comparing the error in forecasts based on the best possible estimate of precipitation using all available data with the error in the forecasts based on the best possible estimate of winter precipitation using only the gaged data. Different data network configurations of gage sites can be compared in terms of forecast errors.     

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.     

AUTOMATED WEB GIS BASED HYDROGRAPH ANALYSIS TOOL,WHAT1

The separation of the base flow component from a varying streamflow hydrograph is called “hydrograph analysis.” In this study, two digital filter based separation modules, the BFLOW and Eckhardt filters, were incorporated into the Web based Hydrograph Analysis Tool (WHAT) system. A statistical component was also developed to provide fundamental information for flow frequency analysis and time series analysis. The Web Geographic Information System (GIS) version of the WHAT system accesses and uses U.S. Geological Survey (USGS) daily streamflow data from the USGS web server. The results from the Eckhardt filter method were compared with the results from the BFLOW filter method that was previously validated, since measured base flow data were not available for this study. Following validation, the two digital filter methods in the WHAT system were run for 50 Indiana gaging stations. The Nash‐Sutcliffe coefficient values comparing the results of the two digital filter methods were over 0.91 for all 50 gaging stations, suggesting the filtered base flow using the Eckhardt filter method will typically match measured base flow. Manual separation of base flow from streamflow can lead to inconsistency in the results, while the WHAT system provides consistent results in less than a minute. Although base flow separation algorithms in the WHAT system cannot consider reservoir release and snowmelt that can affect stream hydrographs, the Web based WHAT system provides an efficient tool for hydrologic model calibration and validation. The base flow information from the WHAT system can also play an important role for sustainable ground water and surface water exploitation, including irrigation and industrial uses, and estimation of pollutant loading from both base flow and direct runoff. Thus, best management practices can be appropriately applied to reduce and intercept pollutant leaching if base flow contributes significant amounts of pollutants to the stream. This Web GIS based system also demonstrates how remote, distributed resources can be shared through the Internet using Web programming.     

A COMPUTERIZED DATA BASE FOR FLOOD PREDICTION MODELING1

ABSTRACT: A computerized geographic information system (GIS) was created in support of data requirements by a hydrologic model designed to predict the runoff hydrograph from ungaged basins. Some geomorphologic characteristics (i.e., channel lengths) were manually measured from topographic maps, while other parameters such as drainage area and number of channels of a specified order, land use, and soil type were digitized and manipulated through use of the GIS. The model required the generation of an integrated Soil Conservation Service (SCS) curve number for the entire basin. To this end, soil associations and land use (generated from analysis of Landsat satellite data) were merged in the GIS to acquire a map representing SCS runoff curve numbers. The volume of runoff obtained from the Watershed Hydrology Simulation (WAHS) Model using this map was compared to the volume computed by hydrograph separation and found to be accurate within 19 percent error. To quantify the effect of changing land use on basin hydrology, the GIS was used to vary percentages from the drainage area from forest to bare soil. By changing the basin runoff curve numbers, significant changes in peak discharge were noted; however, the time to peak discharge remained essentially independent of change in area of land use. The GIS capability eliminated many of the more traditional manual phases of data input arid manipulation, thereby allowing researchers to concentrate on the development and calibration of the model and the interpretation of presumably more accurate results.     

USE OF A GEOGRAPHIC INFORMATION SYSTEM TO ASSEMBLE INPUT-DATA SETS FOR A FINITE-DIFFERENCE MODEL OF GROUND-WATER FLOW1

ABSTRACT: A Geographic Information System (GIS) was used to expedite assembly of input-data sets for a model of ground-water flow in the Middle Patuxent River basin in Howard County, Maryland. The model grid was developed with GIS and used to select attributes from GIS data coverages. These attributes were then output from GIS into the input-data sets, which included model boundaries, regolith thickness, bedrock-surface altitude, stream locations, stream length, stream-bottom altitude, and trans-missivity. The ability to change large sets of spatial data quickly and accurately with GIS enhances the model-calibration process. (KEY TERMS: GIS; ground water; Piedmont; Maryland; MODFLOW.)     

基于GIS技术的重庆市危险废物管理信息系统研究

重庆市每年都会产生大量的危险废物，直接威胁到了重庆市的水环境及生态环境，因此，有效的管理重庆市的危险废物是处理和处置的重要保证。主要介绍了基于CIS危险废物管理信息系统的设计，将危险废物、计算机技术和GIS技术相结合，为危险废物的管理提供快捷、方便、科学的管理和决策支持。该系统包括六个子系统，分别是数据输入、数据查询、数据库管理和维护、模型库、决策支持、系统管理。该系统具有界面友好、操作方便、实用等特点，将在重庆市危险废物管理方面起到重要作用。     

DEVELOPMENT OF WATERSIIED MODELS FOR TWO SIERRA NEVADA BASINS USING A GEOGRAPHIC INFORMATION SYSTEM1

ABSTRACT: Techniques were developed using vector and raster data in a geographic information system (GIS) to define the spatial variability of watershed characteristics in the north-central Sierra Nevada of California and Nevada and to assist in computing model input parameters. The U.S. Geological Survey's Precipitation-Runoff Modeling System, a physically based, distributed-parameter watershed model, simulates runoff for a basin by partitioning a watershed into areas that each have a homogeneous hydrologic response to precipitation or snowmelt. These land units, known as hydrologic-response units (HRU's), are characterized according to physical properties, such as altitude, slope, aspect, land cover, soils, and geology, and climate patterns. Digital data were used to develop a GIS data base and HRIJ classification for the American River and Carson River basins. The following criteria are used in delineating HRU's: (1) Data layers are hydrologically significant and have a resolution appropriate to the watershed's natural spatial variability, (2) the technique for delineating HRU's accommodates different classification criteria and is reproducible, and (3) HRU's are not limited by hydrographic-subbasin boundaries. HRU's so defined are spatially noncontiguous. The result is an objective, efficient methodology for characterizing a watershed and for delineating HRU's. Also, digital data can be analyzed and transformed to assist in defining parameters and in calibrating the model.     

Towards Real‐Time Continental Scale Streamflow Simulation in Continuous and Discrete Space

The National Weather Service (NWS) forecasts floods at approximately 3,600 locations across the United States (U.S.). However, the river network, as defined by the 1:100,000 scale National Hydrography Dataset‐Plus (NHDPlus) dataset, consists of 2.7 million river segments. Through the National Flood Interoperability Experiment, a continental scale streamflow simulation and forecast system was implemented and continuously operated through the summer of 2015. This system leveraged the WRF‐Hydro framework, initialized on a 3‐km grid, the Routing Application for the Parallel Computation of Discharge river routing model, operating on the NHDPlus, and real‐time atmospheric forcing to continuously forecast streamflow. Although this system produced forecasts, this paper presents a study of the three‐month nowcast to demonstrate the capacity to seamlessly predict reach scale streamflow at the continental scale. In addition, this paper evaluates the impact of reservoirs, through a case study in Texas. Validation of the uncalibrated model using observed hourly streamflow at 5,701 U.S. Geological Survey gages shows 26% demonstrate PBias ≤ |25%|, 11% demonstrate Nash‐Sutcliffe Efficiency (NSE) ≥ 0.25, and 6% demonstrate both PBias ≤ |25%| and NSE ≥ 0.25. When evaluating the impact of reservoirs, the analysis shows when reservoirs are included, NSE ≥ 0.25 for 56% of the gages downstream while NSE ≥ 0.25 for 11% when they are not. The results presented here provide a benchmark for the evolving hydrology program within the NWS and supports their efforts to develop a reach scale flood forecasting system for the country.     

Neighborhood satisfaction,physical and perceived naturalness and openness

This study examined neighborhood satisfaction in relation to naturalness and openness. It used Geographic Information System (GIS) and Landsat satellite imagery to physically measure the environmental attributes. Through path analysis it examined the relationship among the attributes, resident ratings of those environmental attributes, their satisfaction with them, and their overall neighborhood satisfaction (n = 725). We expected overall neighborhood satisfaction to relate to the resident's ratings of the environmental attributes and to the physical measures of them. The path model showed that overall neighborhood satisfaction was associated directly with the physical measure of building density and indirectly with the physical measure of vegetation rate through perception and evaluation of them. The perceptions and evaluations of the attributes related to one another. With refinements, GIS and Landsat data geo-related to survey data can offer a powerful tool for understanding the complex nature of neighborhood satisfaction and behavior.     

Detection and mapping of water pollution variation in the Nile Delta using multivariate clustering and GIS techniques

The limited water resources of Egypt lead to widespread water-stress. Consequently, the use of marginal water sources, such as agricultural drainage waters, provides one of the national feasible solutions to the problem. However, the marginal quality of the drainage waters may restrict their use.The objective of this research is to develop a tool for planning and managing the reuse of agricultural drainage water for irrigation in the Nile Delta. This is achieved by classifying the pollution levels of drainage water into several categories using a statistical clustering approach that may ensure simple but accurate information about the pollution levels and water characteristics at any point within the drainage system.The derived clusters are then visualized by using a Geographical Information System (GIS) to draw thematic maps based on the entire Nile Delta, thus making GIS as a decision support system. The obtained maps may assist the decision makers in managing and controlling pollution in the Nile Delta regions. The clustering process also provides an effective overview of those spots in the Nile Delta where intensified monitoring activities are required. Consequently, the obtained results make a major contribution to the assessment and redesign of the Egyptian national water quality monitoring network.     

RASTER-BASED HYDROLOGIC MODELING OF SPATIALLY-VARIED SURFACE RUNOFF1

ABSTRACT: The proliferation of watershed databases in raster Geographic Information System (GIS) format and the availability of radar-estimated rainfall data foster rapid developments in raster-based surface runoff simulations. The two-dimensional physically-based rainfall-runoff model CASC2D simulates spatially-varied surface runoff while fully utilizing raster GIS and radar-rainfall data. The model uses the Green and Ampt infiltration method, and the diffusive wave formulation for overland and channel flow routing enables overbank flow storage and routing. CASC2D offers unique color capabilities to display the spatio-temporal variability of rainfall, cumulative infiltrated depth, and surface water depth as thunderstorms unfold. The model has been calibrated and independently verified to provide accurate simulations of catchment response to moving rainstorms on watersheds with spatially-varied infiltration. The model can accurately simulate surface runoff from flashfloods caused by intense thunderstorms moving across partial areas of a watershed.     

GIS‐Based Spatial Precipitation Estimation: A Comparison of Geostatistical Approaches1

Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km², which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models.     

基于遥感技术的艾比湖储水量和需水量研究

艾比湖湖水很浅,湖底平坦,沉积着巨厚的细沙和淤泥。依据自身特征及其他因素,针对艾比湖水量的收支情况,建立艾比湖的储水量和需水量的数学模型。其中艾比湖湖面面积数据是重要参数之一,利用遥感技术,采用资源卫星影像,结合Modis数据,解译提取获得。通过艾比湖储水量和需水量数据可以进一步预测艾比湖湖面面积的变化趋势,对本地区的生态及农业生产具有指征意义,为决策层制定防治对策提供科学依据。     

INTEGRATING A GEOGRAPHIC INFORMATION SYSTEM,A SCIENTIFIC VISUALIZATION SYSTEM,AND A PRECIPITATION MODEL1

ABSTRACT: Investigating natural, potential, and human-induced impacts on hydrologic systems commonly requires complex modeling with overlapping data requirements, plus massive amounts of one- to four-dimensional data at multiple scales and formats. Given the complexity of most hydrologic studies, the requisite software infrastructure must incorporate many components including simulation modeling and spatial analysis with a flexible, intuitive display. Integrating geographic information systems (GIS) and scientific visualization systems (SVS) provides such an infrastructure. This paper describes an integrated system consisting of an orographic precipitation model, a GIS, and an SVS. The results of this study provide a basis for improving the understanding of hydro-climatic processes in mountainous regions. An additional benefit of the integrated system, the value of which is often underestimated, is the improved ability to communicate model results, leading to a broader understanding of the model assumptions, sensitivities, and conclusions at a management level.