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The development of relational databases from which simulation models can access data needed to describe the systems being modeled is fundamental to integrated river basin management, especially in shared, transboundary basins. Creating a geographically referenced database, a geodatabase, for the Rio Grande/Rio Bravo Basin represents the first major attempt to establish a more complete understanding of the basin as a whole, using both Mexican and United States geospatial and temporal water resources data. From the geodatabase, it is possible to obtain information about climatology, water availability, water uses, hydraulic infrastructure, and watershed properties in the basin. These data can be used in simulation models to calculate the state of basin water availability under different climatic and development scenarios and management plans in the future. This geodatabase is intended to be a tool to assist in sharing data to enhance binational cooperation between Mexico and the United States concerning water in this basin, providing accurate and reliable data necessary for analysis and resolution of water resources issues. DOI: 10.1061(ASCE)0733-9496(2007)133:5(416) CE Database subject headings: River basins; Texas; Water resources; Geographic information system; Databases; Water management.

An expert geographic information system (expert GIS) combines rule-based reasoning with spatial data representation and analysis. A limited, experimental expert GIS has been created by linking the Nexpert Object expert-system shell to the Arc/Info geographic information system (GIS), both running under the Unix operating system. The interface adds communication modules, which send and receive data and commands to and from each system. Linking an expert system with a GIS enables both the expert system and the GIS to perform new tasks, and opens the way for more complex spatial analyses and more flexible querying of GIS data bases than have been possible previously. Two types of application for the Arc-Nexpert interface are presented: (1) GIS advisors, which help novice users retrieve the information they need from GIS data bases; and (2) spatial expert systems, which access Arc/Info data as part of a Nexpert Object reasoning process. Examples of both types of application are presented.

Network routines are implemented within several geographic information systems (GISs). These routines are primarily used in traffic routing and allocation analyses, and very little work has been done on their application in water resources. This paper describes Dijkstra's algorithm, which is used for most network implementations in a GIS and how its routing and allocation techniques can be implemented for water flow and transport. Dijkstra's algorithm is limited by the fact that it requires the resistance to flow be known before the magnitude of the flow is determined, but these two variables are usually interdependent. The consequences of this limitation with regard to water-resources applications is discussed. The types of problems suitable for GIS water-network analysis are identified. Three applications - drainage-network verification and sizing using rational method, watershed isochrone determination, and steady-state flow computations - are discussed in detail, and their network application within the Arc/Info GIS is presented. These applications are embedded directly within a GIS, thus simplifying the modeling environment.

The feasibility of using an expert geographic information system (GIS) for long-term regional water-resources planning is evaluated through a case study examining an existing regional water-supply system. This system is comprised of an expert system that embodies the logical rules and expertise of water-resources planning experts as well as a geographic information system that stores and analyzes spatially distributed data. Normal water-demand forecasts and water-supply data along with appropriate analysis routines are used in this new planning tool, which attempts to follow the logic of current methods and permit plans to be updated and alternatives to be analyzed more rapidly. An example application of the system is presented which analyzes the existing water supply system for the Corpus Christi, Tex., area. Given annual yields for the reservoirs, water-demand forecasts, and institutional requirements, the expert GIS calculates potential water-supply deficits or excesses in the region over a 50-year planning horizon, and suggests efficient and cost-effective alternatives for developing additional water supplies in the event that deficits occur.

In cities across the country, as local land development regulations have become increasingly complicated and confusing, the costs to the development community and to city government have escalated. Substantial labor is often required to determine which permit requirements and design criteria apply to a particular development project. An expert system called SITE CODE is proposed as a tool for early assistance to automate the retrieval and provision of regulatory information. Study of land development regulations in Austin, Tx., San Diego, Calif., and Fairfax County, Va., reveals that for a regulation to be applicable to a development project, it must have administrative, spatial, and temporal jurisdiction over that development. SITE CODE makes use of the concept of jurisdiction to identify the set of regulations applicable to particular development projects. The permit requirements and design criteria contained in those regulations can be displayed or printed to create a customized land development code tailored to the interests of the user.

Some of the most important data sources on the Internet, useful for ground water modeling, are reviewed. USGS National Water Information System (NWIS), USGS National Water Quality Assessment (NAWQA), U.S. EPA STORET

Abstract: 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. [ABSTRACT FROM AUTHOR]

Abstract: This study assesses a large‐scale hydrologic modeling framework (WRF‐Hydro‐RAPID) in terms of its high‐resolution simulation of evapotranspiration (ET) and streamflow over Texas (drainage area: 464,135 km2). The reference observations used include eight‐day ET data from MODIS and FLUXNET, and daily river discharge data from 271 U.S. Geological Survey gauges located across a climate gradient. A recursive digital filter is applied to decompose the river discharge into surface runoff and base flow for comparison with the model counterparts. While the routing component of the model is pre‐calibrated, the land component is uncalibrated. Results show the model performance for ET and runoff is aridity‐dependent. ET is better predicted in a wet year than in a dry year. Streamflow is better predicted in wet regions with the highest efficiency ~0.7. In comparison, streamflow is most poorly predicted in dry regions with a large positive bias. Modeled ET bias is more strongly correlated with the base flow bias than surface runoff bias. These results complement previous evaluations by incorporating more spatial details. They also help identify potential processes for future model improvements. Indeed, improving the dry region streamflow simulation would require synergistic enhancements of ET, soil moisture and groundwater parameterizations in the current model configuration. Our assessments are important preliminary steps towards accurate large‐scale hydrologic forecasts. [ABSTRACT FROM AUTHOR]

The National Flood Interoperability Experiment is a research collaboration among academia, National Oceanic and Atmospheric Administration National Weather Service, and government and commercial partners to advance the application of the National Water Model for flood forecasting. In preparation for a Summer Institute at the National Water Center in June-July 2015, a demonstration version of a near real-time, high spatial resolution flood forecasting model was developed for the continental United States. The river and stream network was divided into 2.7 million reaches using the National Hydrography Dataset Plus geospatial dataset and it was demonstrated that the runoff into these stream reaches and the discharge within them could be computed in 10 min at the Texas Advanced Computing Center. This study presents a conceptual framework to connect information from high-resolution flood forecasting with real-time observations and flood inundation mapping and planning for local flood emergency response. [ABSTRACT FROM AUTHOR]