Because integrated management of a river basin requires the development of models that are used for many purposes, e.g., to assess risks and possible mitigation of droughts and floods, manage water rights, assess water quality, and simply to understand the hydrology of the basin, the development of a geodatabase from which models can access the various data needed to describe the systems being modeled is fundamental. In other words, a database from which models read input data and to which they write output data. In order for this concept to be useful and widely applicable, however, it must have a standard design. The recently developed ArcHydro data model facilitates the organization of data according to the “basin” principle and allows access to hydrologic information by models. The development of a basin-scale relational database using the ArcHydro schema and implemented in a Geographic Information System (GIS) is one of the contributions of this research. The Rio Grande/Bravo basin is the case study area for this research. This geodatabase represents the first major attempt to establish a more complete understanding of the basin as a whole, including spatial and temporal information from the United States of America and Mexico.

Raster tools represent a convenient means of analyzing watersheds from Digital Elevation Models (DEM), as well as calculating mean watershed values based on raster datasets describing parameter variations in space. These tools are effective when the number of grid cells in the analysis is not too great (e.g., less than 50 million cells). Difficulties in processing raster datasets over large regions are studied in this research. One of the most important contributions of this research is the application of a Raster-Network Regionalization technique, which utilizes raster-based analysis at the subregional scale in an efficient manner and combines the resulting subregional vector datasets into a regional database. Also, this methodology verifies the validity of dividing a basin into subregions for processing without compromising on the accuracy of the determined parameter values. This technique could also be applied at a local level when high resolution data, such as LIDAR data, area available. These data are so dense they typically preclude raster analysis over a relatively small area.

Another important contribution of this research is focused on implementing a robust structure for handling huge temporal data sets related to monitoring points such as hydrometric and climatic stations, reservoir inlets and outlets, water rights, etc. For the Rio Grande study area, the ArcGIS format is applied to the data tables obtained from the Mexican and American agencies in order to include and relate these time series to the monitoring and control points in the geodatabase. The standard time series format of the ArcHydro schema was changed to include a relationship to the agency from which data is obtained.

Since ArcHydro was designed to store hydrologic GIS data in a manner conducive to data export for model use, a toolset is proposed to exchange temporal information between the Geodatabase and the Hydrologic Engineering Center Data Storage System (HEC-DSS).

1. INTRODUCTION

The Rio Grande/Bravo is a transboundary water source shared by the United States and Mexico. At this time, Mexico has limited capacity to develop efficient management plans for the water in the Rio Grande/Bravo basin, given the existing infrastructure and methods of application and distribution of water. A continually increasing population, serious problems related to lack of sanitation and clean water, as well as regular high investments in infrastructures which are not achieving their objectives, are likely to force governments at various levels to search for alternative approaches, other than relying only on engineering solutions through supply management alone. The institutions concerned have yet to fully realize that successful water resources management requires a long term planning process from technical, economic, political, social, and environmental viewpoints.

In addition, some decisions about water management are only partially supported, causing alterations in the global ecosystem. For this reason it is necessary to improve the administration and management of water in this watershed. This will require assessment of water availability and how to manage it appropriately for agriculture, industry and other services, also taking into account ecosystem preservation.

Recent drought conditions have increased tensions over water sharing in this basin. Several areas of conflict and possible negotiated remedies have been identified, but there is a lack of data available to use in analysis of alternative solutions to these problems.

The development of a watershed-scale database for the Rio Grande/Bravo basin is fundamental. Minute 308 of the International Boundary Waters Commission (IBWC), June 28, 2002, states that it is very important to support projects that increase data exchange related to the management of hydrological information systems. These systems should include information from both sides of the basin in a timely manner to enable the IBWC to adopt principles and understandings under which both Governments provide the highest priority to fulfilling their respective obligations under the 1944 Water Treaty.

In part of this research project, the Center for Research in Water Resources (CRWR) of the University of Texas at Austin, the Texas Commission on Environmental Quality (TCEQ), the Mexican Institute of Water Technology (IMTA), and the National Water Commission (CNA) of Mexico have cooperated to develop the relational database containing geographic, hydrologic, hydraulic and related data for the basin, as shown in figure 1. This geospatial database was created using the ArcHydro data model schema for the entire Rio Grande/Bravo basin.

Fig. 1 Relational integration of thematic layers (Maidment, 2002)

2. STUDY AREA

The Rio Grande originates in the San Juan Mountains of southern Colorado. Flowing 858 kilometers from its headwaters and through the state of New Mexico, it enters Texas about 12 kilometers northwest of El Paso and then continues 2025 kilometers to the Gulf of Mexico. The figure 2 shows the total length of the river, as well as the political division of the Rio Grande/Bravo basin that includes the Hydrologic Unit Cataloging (HUCs) on the U.S. side and Cuencas and sub-Cuencas on the Mexican side..

The Rio Grande is the fifth longest river in North America (2895 Km), and among the 20 longest rivers in the world. The river carries little water compared to other rivers of its length. For this reason, it has been classified by the Encyclopedia of Water in the West (2002) as an exotic stream, which means that it tends to shrink in size as it flows downstream. This is typical of rivers that pass through arid regions. Most precipitation in the basin falls at either end of the river, as snow near its headwaters or as rain near its mouth.

The river collects rain, snowmelt and spring water from an area about 557,722 square kilometers including closed basins. The whole basin includes three states on the U.S. side (Colorado, New Mexico, and Texas), and five states on the Mexican side (Chihuahua, Coahuila, Durango, Nuevo Leon, and Tamaulipas). From the basin area, 225,380 Km² lies on the Mexican side and 242,994 Km² on the U.S. side, without considering closed basins.

Fig. 2 Political division of the Rio Grande/Bravo basin

The basin is divided in two sub basins, the Upper Rio Grande watersheds that include Colorado, New Mexico, and part of Texas, and the Lower Rio Grande Basin (LRGB) that includes parts of the Chihuahua, Durango, Coahuila, Nuevo Leon, Tamaulipas, and Texas states. The LRGB, from below Fort Quitman to the Gulf of Mexico and including the Rio Conchos and Pecos sub-basins, is used for the case study area, encompassing the drainage of all major tributaries downstream of El Paso and Ciudad Juarez. The portion of the basin that lies in this study area is known as Cuencas Del Rio Bravo del Norte by the Mexican agencies.

A part of the Rio Grande basin lies within North America’s largest desert, the Chihuahua Desert. Mexico irrigates about 1.1 million acres in the basin, while the United States irrigates about 993,000 acres. Only 98,000 acres of irrigated land lie upstream from Texas (The Alliance for the Rio Grande Heritage et al, 2000). The Conchos, San Pedro, San Rodrigo, Alamos, and San Juan Rivers are the primary tributaries in Mexico. The Pecos and Devil Rivers are the principal tributaries to the river in Texas (Figure 3).

The Rio Grande/Bravo basin is considered an arid to semi-arid region, dominated by agriculture and with limited supplies of both surface and groundwater. Average rainfall in the basin ranges from 200 – 900 millimeters with the highest values in the upper basin of the Rio Conchos (Patino et al, 2004). The Rio Conchos enters to the Rio Grande/Bravo near Presidio, Texas, just upstream of Big Bend National Park and Ojinaga, Mexico; in a region of mountains and canyons. The basin ranges from arid and suitable for crops, to semi-arid and hospitable to some crops only. Along the entire river, water lost through evaporation exceeds water gained from precipitation. The Lower Valley serves as temporary or permanent home for hundreds of bird species, and the river contributes vital fresh water to its gulf estuary (Tate, 2002).

Fig. 3 The primary tributaries in the Rio Grande/Bravo basin

3. METHODOLOGY

3.1. COLLECTION OF THE GEO-SPATIAL DATA FROM ORIGINAL SOURCES

Hydrological information was obtained from Mexican and U.S. agencies for the project. The political boundaries, river network, water bodies and gauging stations on the Mexican side were collected from the National Water Commission (CNA), the Mexican Institute of Water Technology (IMTA), the University of Ciudad Juarez (UACJ), the Comision Internacional de Limites y Aguas (CILA), and the National Institute of Geography and Information (INEGI). The information for the U.S. side was obtained from the U.S. Geological Survey (USGS), the Texas Commission on Environmental Quality (TCEQ), the International Boundary Water Commission (IBWC), and the Texas Natural Resources Information System (TNRIS), among others agencies. The data collected from the original sources are included in table 1, as well as some of the data characteristics.

Errors were found in some of the hydrological information such as incorrect positions of some monitoring and control points, disconnected river reaches, incorrect location of some water bodies, etc. Part of the original information is shown in Figure 4. This information had to be edited in order to fix these errors.

The Mexican agencies usually use the Geographic Coordinate System and Lambert projection to create their geographic information. The Albers equal area projection was proposed for this project in order to preserve the areas. The Datum chosen was the NAD Datum 1983; the Geographic Coordinate System corresponds to the GCS_North_American_1983, while the Central Meridian is located at -103 degrees, near the center of the basin.

Table 1 Summary of the original data collected for the Rio Grande/Bravo basin

Description of data	Mexico	USA
Political boundaries (States included in the Rio Grande basin). Source: U.S. Department of Transportation. Scale: 1:250K	Available	Available
Basin Delineation. Source: USGS-HUC for the U.S. side (1:100K) Cuencas and Sub-Cuencas from IMTA and UACJ for the Mexican side (1:250K)	Available	Available
Hydrography (Stream network). Source: USGS for U.S. (Scale 1:100K). Mexican Institute of Water Technology (IMTA), National Water Commission (CNA), INEGI, and University of Ciudad Juarez (UACJ) for the Mexican side (Scale 1:250 K).	Available	Available
Water Bodies and dam locations. Source: USGS- HUC’S for the U.S. side (1: 100K). IMTA, CNA, INEGI, and UACJ for the Mexican side (1:250K)	Available	Available
Monitoring point’s location. Source: USGS, TCEQ, and IBWC for the U.S. side. IMTA, CNA, and CILA for the Mexican side as hydrometric and climatic stations.	Available	Available
Historical hydrometric information (time series). Sources: National Water Information System (NWIS) and the IBWC for the U.S. side (1940 – 2000). IMTA, CNA, and CILA for the Mexican side. Part of this information is included in the BANDAS software developed by the CNA that includes 67 hydrometric stations located in the Rio Grande/Bravo basin	Available	Available
Climatologic information (time series). Sources: USGS and PRISM for the U.S. side IMTA and CNA for the Mexican side. This information is included in the ERIC System (230 climatic stations on the Mexican side operating until 2002.)	Available	Available
Digital Elevation Model (DEM). Source (Seamless format): USGS for the U.S. side. Resolution: 30 m of cell size. Source on the Mexican side: INEGI. Cell size: 104 m	Available	Available
Control Points (Include water rights, return flow points, diversions, etc) This information was obtained from the TCEQ on the U.S. side; and from the CNA for the Mexican side. This information was available as a shapefile in ArcView 3.2	Available	Available

Fig. 4 Cuencas, Sub Cuencas and original hydrography of the Rio Bravo basin on the Mexican side

3.2. DEVELOPMENT OF THE GEOSPATIAL DATABASE

The development of a watershed-scale database is fundamental to analyzing water resource management problems in the basin. Even though separate research efforts have been carried out on each side of the river, there has not been an integral database that includes data from both sides of the Rio Grande/Bravo basin. As in many watersheds, knowledge and information available about the Lower Rio Grande/Bravo basin is fragmented, disjointed, incomplete, and sometimes inaccurate. Integrated management of a river basin requires the development of models that are used for many purposes, e.g., to assess risks and possible mitigation of droughts and floods, manage water rights, assess water quality, and simply to understand the hydrology of the basin. For this purpose a database is needed from which models can access the various data needed to describe the systems being modeled (figure 5). In other words, a database from which models read input data and to which they write output data. In order for this concept to work, however, it must have a standard design. The recently developed ArcHydro data model facilitates access to hydrologic information by models (Maidment, 2002).

Fig. 5 Hydrologic Information System (Maidment, 2002)

Creating the ArcHydro geospatial database for the entire 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 U.S. geospatial and temporal data for water resources. It is possible to obtain from the database information about climatology, water availability, water uses, hydraulic infrastructure, and drainage in the basin that are included as feature classes within the relational database (Figure 6). These data will permit models to calculate the state of water availability under different climatic and development scenarios and management plans in the future.

Fig. 6 ArcHydro data model for water resources

3.3. CLIPPING OR MERGING THE DATA SETS DEPENDING ON THEIR ORIGINAL EXTENT

In constructing the geodatabase for the Rio Grande/Bravo basin, data distributed on a national or state level had to be clipped; while data distributed at a county or Hydrologic Cataloging Unit level, had to be merged into a single and larger data set. Because the original DEM for Mexico existed for the whole country with a grid size of 104 m, it had to be clipped and resampled on a 30 m grid based on the basin boundaries. With respect to the USGS DEM for the U.S. side, the original seamless tiles are projected using the GCS_1983 and a grid resolution of 28.3 m; so they had to be reprojected and resampled to match the projection and characteristics chosen for the project. The result of this step is shown in Figure 7.

Fig. 7 Clipped DEMs for the basin including a 10 Km buffer

3.4. CREATING THE FEATURE DATASETS IN THE GEODATABASE

This step included the processing the available information into the ArcHydro Rio Grande/Bravo geodatabase. Several feature datasets were created that include feature classes related to each type of information. When working with huge basins like the Rio Grande/Bravo basin, the computer processor is not be able to handle the large raster datasets. This is handled by dividing the basin into sub-regions and processing the rasters individually for each region. The values obtained for each sub basin can be cascaded downstream to get the final parameters for control points for the entire basin. For this reason, the whole basin was divided into 9 hydrological subregions on the U.S. side, according to the USGS classification, and 7 hydrological subregions on the Mexican side, in order to apply the ArcHydro process subregion by subregion (Figure 8).

Fig. 8 Hydrological subregions of the Rio Grande/Bravo basin

3.5. OBTAINING TIME SERIES DATA FOR THE BASIN

Climatic and hydrological time series data were collected and imported from the BANDAS, ERIC (On the Mexican side), and NWIS (on the U.S. side) systems corresponding to monitoring points located in the Rio Grande/Bravo basin. Average annual precipitation was obtained from 230 climatic stations located on the Mexican side. Around 2100 control points among water rights, hydrometric stations, water diversions, return flow points, etc., were identified in the whole basin (figure 9)

Fig. 9 Control Points identified in the Rio Grande/Bravo basin

3.6. IMPORTING TIME SERIES INTO THE GEODATABASE

The ArcGIS format is applied to all the time series data in order to include and relate them to the monitoring and control points in the geodatabase. The Time Series standard format of the ArcHydro schema was changed, adding one more table called TSGroup that contains information related to the agency from which the data is derived. Two tables describing the agencies and variables included in the Geodatabase are shown below.

Table 2. Variables Included in the Geodatabase

Table 3. Agencies Participating to Create the Geodatabase

Users can select a specific monitoring point within the geodatabase and several relationships have been established for it, so they can identify the agencies from which the temporal data was derived, as well as the type of variable. The Rio Conchos runoff to the Rio Grande/Bravo is shown in the table 4

Table 4. Monthly Runoff at the Gage Station Rio Conchos-Ojinaga

Also, a time series viewer was applied in order to plot the behavior of the temporal information (figure 10). The information related to runoff from the Rio Conchos to the Rio Grande/Bravo is shown below; where you can see the total discharge to the Rio Grande identified by the identification number (HydroID) 1040700007. The regional HydroIDs 2020100051 and 2010100005 correspond to the discharge to the Rio Grande from Mexico and the U.S. respectively.

Fig. 10. Monthly Runoff Volume from the Rio Conchos to the Rio Grande

3.7. APPLYING REGIONAL HYDROID’S

A unique ten-digit identification number called the Regional HydroID was assigned to every feature class according to the following classification:

The first digit (from left to right) indicates the hydrological region. Region 13 on the U.S. side was identified with the number 1, and number 2 identified region 24 on the Mexican side. The second 2 digits describe the Hydrologic SubRegion. The basin is divided in 9 subregions on the U.S. side and 7 subregions on the Mexican side. The next two digits correspond to the feature class. The value 01 was assigned for the ControlPoint feature class, while the value 02 was assigned for edges (River network). The waterbody feature class was identified as 03, Watershed as 04; and so on. The last five digits describe the feature number, with a maximum of 99,999 values. The Regional HydroID for the Rio Conchos basin is shown in table 5 as an example.

Table 5 Regional HydroID for the Rio Conchos Basin with original Mexican Code preserved.

3.8. WRAPHYDRO DATA MODEL SCHEMA

A particular application of the ArcHydro data schema called WRAPHydro was applied to each of the Rio Grande/Bravo hydrological subregions in order to create the necessary fields required by the Water Right Analysis Package (WRAP) model (Wurbs, 2001). The WRAPHydro data model was derived from the ArcHydro model and is tailored specifically for the WRAP project developed jointly with the TCEQ (Gopalan, 2002). It is shown in figure 11. The WRAP is a hydrological simulation model for evaluating existing water right permits, permit approvals for new water rights, and overall water management in Texas under a priority based water allocation system (Wurbs, 2001).

Fig. 11. WRAPHydro Data Model.

All of the fields created by the WRAPHydro schema were populated using the WRAPHydro tools developed at the CRWR (Whiteaker, 2004). These tools consist of a set of public domain utilities developed on top of the ArcHydro data model. The tools are accessed through the WRAPHydro toolbar, where they are grouped by functions into two menus and five buttons (Figure 12). The purpose of this toolkit is to process GIS data in order to calculate parameters used by WRAP and tabulated for each ControlPoint including: average curve number, average annual precipitation, total upstream drainage area, and next downstream ControlPoint

Fig. 12. WRAPHydro Toolbar.

3.9. APPLYING THE WRAPHYDRO TOOLS

For each hydrological subregion, the HUCs or SubCuencas that make up the subregion were selected, including a 10 Km buffer around the HUCs called the BufferWatershed feature class. All the streams that lie within each subregion plus buffer were selected and exported to create the WRAP-Flowline feature class. After this step, a digital elevation model (DEM) of the buffered area was clipped and processed using the ArcHydro Terrain Analysis tool. The catchments for each stream segment (WRAPCatchments) of the WRAP-Flowline class were created with the WRAPHydro Delineate Watershed tool. The DrainID of the delineated catchments was populated by the HydroIDs of the WRAP-Flowline segment draining to it. In order to create a geometric river network (the HydroNetwork), the hydrography information had to be checked. Every stream must be connected and the flow direction assigned correctly. The HydroNetwork is an essential part of this data model, created from edges (WRAPFlowlines) and the control points. The topological connections of the edges and control points in a geometric network enables tracing of water movement upstream and downstream through streams, rivers, and water bodies. Relationships built from the control points connect drainage areas and point features such as diversion points to the HydroNetwork. This HydroNetwork allows calculation of the distance between any two points on a flow path. A new feature class called WRAPEdge was created using the HydroNetwork selecting all streams lying in the hydrological subregion. In order to find the total drainage area for each control point, it is necessary to determine the incremental watersheds that contribute to each junction, then their value is accumulated moving downstream. Watershed drainage area, average curve number and average precipitation were calculated for each delineated watershed using the WRAPHydro tools. The Once the incremental values for the drainage area, curve number and precipitation were determined for each watershed, these values were consolidated to add in the effects of all the area contributing to each junction.

Figure 13 shows the result of comparing the SubCuencas of the Rio Conchos basin defined by the Instituto Nacional de Estadistica, Geografia e Informatica of Mexico (INEGI)--represented by a continuous line--and the watershed defined by the WRAPHydro Tools--represented by polygons.The connectivity among control points is shown in figure 14. The SubCuencas were defined using a 1:250K scale topographic map, while the watersheds were calculated from a 1:100K scale WRAPEdge (from a digitized map) and a DEM grid size of 30 m. The points represent the related water rights, gage stations, and return flow control points.

Fig. 13. Rio Conchos Basin Delineation Fig. 14. Rio Conchos Basin Connectivity

3.10. RASTER-NETWORK REGIONALIZATION PROCESS

The research presented in this project introduces a Raster-Network Regionalization Technique, which allows a large region to be divided into hydrological distinct subregions where raster analyses may be performed in a feasible manner. A summation of raster values over watersheds can be easily determined using the watersheds as distinct zones which define the area of analysis for the zonal statistics tool in ArcGIS. This tool calculates statistics such as mean, sum, max, and min for each zone by reading the values of cells within each zone and performing the necessary statistical operations. Thus, with this approach, accumulated grids whose cell values are influenced by all upstream cells are no longer needed. The only cells of a watershed that an analyst is interested in are the cells that lie directly over that watershed (Whiteaker, 2004).

Once attribute values have been determined for watersheds, these values can be transferred to outlet junctions, and then consolidated throughout the stream network in the vector domain. The watersheds become the basic processing unit with basin-wide coverage, while the raster coverage can be reduced to each individual watershed’s extent. Thus, watersheds effectively replace grid cells as the “units” of analysis.

This allows a basin or region to be divided into hydrologically distinct subregions, in which the necessary raster analyses takes place. The smaller size of the subregions permits faster raster processing, while results from raster analysis are stored on vector watersheds to be accumulated at the basin level. The Consolidation and Accumulation options from the WRAPHydro tools are then used to accumulate watershed parameters across the entire basin.

With the Raster-Network Regionalization technique, the weight of processing is changed from the raster side to the vector side, resulting in several benefits due to reduced processing time, since much of the processing occurs in the vector domain rather that in the raster domain. Data storage requirements are reduced, since accumulation grids no longer need to be created. Also, the remaining grids can be split into hydrological distinct regions defined by one or more watersheds. This allows for faster processing on the raster side, more modular data storage, and less raster reprocessing effort if data in a given watershed changes. Even the largest basin can now be processed with high-resolution raster data too.

The technique has been successfully applied to the binational Rio Grande/Bravo basin, which has a contributing area of over 468,000 square kilometers and is divided in 16 hydrological subregions as it is shown in figure 1(9 on the U.S. side and 7 on the Mexican side). The results from the raster analysis of each subregion are merged on the vector side for determining the total drainage area flowing toward a specific control point, as well as its corresponding average precipitation, average curve number, and length downstream parameters.

Figure 15 shows the control points and main rivers in the portion of the Rio Grande/Bravo basin from El Paso/Cd. Juarez through the Gulf of Mexico. The connectivity among the river system, junctions and watersheds is shown in figure 16.

Fig. 15. Control Points and Main Rivers in the Rio Grande/Bravo basin

Fig. 16. Connectivity in the Rio Grande/Bravo basin

A schematic network diagram for the whole basin is shown in figure 17. This schematic network is a simplification of the HydroNetwork that consists of separate point and line feature classes called Schematic-Node and Schematic-Link, respectively. The schematic network is an abstract representation of the elements to which hydrologic or water management models can be applied, and it provides a simplified view of the connectivity of the river network and the control points. This kind of network is useful as a visual check to make sure that the hydrologic elements needed for a model are correctly linked in the landscape (Maidment, 2002)

Fig. 17. Schematic Network of the Rio Grande/Bravo basin

3.11. Exchange of Temporal Information

A tool called DSS Hydro tool for transferring around two million of historical records from an ArcHydro geodatabase into a HEC-DSS file and back to a geodatabase is being developed in this research for using with USACE HEC models. This tool consists of a set of public domain utilities developed in Visual Basic. The DSS Hydro toolbar operates in the ArcGIS ArcMap environment, and is comprised of four commands to transfer the temporal information (Figure 18). This tool utilizes an object library and objects classes within the geodatabase structure called DSS Time Series Catalog (DSSTSCatalog) that contains all relevant records and descriptors to automatically transfer the time series (Teasley et al, 2004)

Figure 18 DSS Hydro Tools

The original ArcHydro Time Series framework must be modified to create automatically the DSSTSCatalog table inside the ArcHydro structure when the ArcHydro schema is applied to a geodatabase. This table contains all necessary fields that are used as the descriptors to create the HEC-DSS files (figure 19).

Figure 21 Modified ArcHydro Time Series Framework

The DSSTSCatalog is populated automatically in a geodatabase using the “Writing DSS Catalog into the geodatabase” option included in the DSS Hydro toolbar, based on the temporal information contained in the time series table of the geodatabase. The DSSTSCatalog is the object class table within the geodatabase that contains the information related to the DSS data and its pathname, and represents the key step in transforming a time series from a geodatabase into the HEC-DSS format. The DSS pathname consists of six parts in the following format:

/A/B/C/D/E/F/

Where

A - Group name for the data such as a watershed name, study name or any identifier which allows the records to be recognized as belonging to a group.

B – The location identifier for the data. The location identifier may be a site name or organization ID such as a USGS gage ID or the HydroID of the monitoring point.

C - The parameter of the data such as flow, precipitation, storage, evaporation, etc.

D - the start date of the time series, and

E - The time interval for regular data or the block length for irregular interval data.

F - An optional descriptor that can be used for additional information about the data.

Once the DSSTSCatalog is created, the time series is transferred from the geodatabase to the HEC-DSS format using the “Transferring Time Series from GDB to HEC-DSS” option of the DSS Hydro toolbar, in order to create the HEC-DSS files that will be used for simulation purposes. After the simulation has been completed in any HEC models, is necessary to transfer back the time series results from the HEC-DSS files to the geodatabase. The “Transfer HEC-DSS Time Series to GDB” option of the DSS Hydro toolbar is used to perform this task. There are two options for exchanging temporal information; one of them uses a filter for transferring time series just related to one specific point, whereas another one is used to transfer all records contained in the HEC-DSS files (Figure 21).

Figure 21 Time series transfer between the geodatabase and the HEC-DSS

3.12. INSTALLING THE DSS HYDRO TOOLBAR DLL

· Open ArcMap

· Go to the Customize option in the Toolbars option.

Click the “Add from file” button and select the “DSSTSBridge_Jan05.DLL” from your folder where you have the dll

Activate the “HEC-DSS TIME SERIES TOOLBAR” option…..and now you should have the DSS Toolbar in your ArcMap document

3.13. DSS Hydro Toolbar Description (After you have installed the DLL in ArcMap)

1. Writing HEC-DSS Catalog into the geodatabase: This option allows populating automatically the DSSTSType table, which was created previously by the ArcHydro schema. This function takes the temporal information from the Time Series and the TSType tables included in the ArcHydro geodatabase. The TSType table must have the next structure in order to be able to transfer the temporal information.

2. Transferring Time Series from GDB to HEC-DSS: This function transfers all temporal information contained in the ArcHydro Time Series table into a HEC-DSS file. The DSSTSType is the key table to make this transferring.

3. Transfer HEC-DSS Time Series to the GDB without Filter. This option transfers ALL temporal information from the HEC-DSS files to the GDB.

Choose the HEC-DSS file from where you want to transfer the information. Select the number variable appearing in the A Part of the HEC-DSS file (Number 6 in this example). Select the Variable Type that should be the same appearing in the C Part of the HEC-DSS file (VOLUME-MONTHLY). Select the time interval units, and type the HEC-DSS A Part (6 for this example, and it must be the same value as appears in the A Part of the HEC-DSS table). Finally select the target geodatabase where you want to store this temporal information.

4. Transfer HEC-DSS Time Series to the GDB WITH filter. This option transfers JUST THE INFO RELATED TO ONE SPECIFIC POINT from the HEC-DSS files to the GDB.

Choose the HEC-DSS file from where you want to transfer the information. Select the HydroID of the Monitoring Point in the “Input B Part (Site ID)” box. This ID must be the same as appears in the B Part of the HEC-DSS table. Select the number variable appearing in the A Part of the HEC-DSS file (Number 6 in this example). Select the Variable Type that should be the same appearing in the C Part of the HEC-DSS file (VOLUME-MONTHLY). Select the time interval units, and type the HEC-DSS A Part (6 for this example, and it must be the same value as appears in the A Part of the HEC-DSS table). Finally select the target geodatabase where you want to store this temporal information.

4. WATER QUALITY DATA MODEL (WQDM) IN GIS FOR THE RIO GRANDE/BRAVO BASIN

Development of a Water Quality Data Model (WQDM) based on a framework developed in Visio 2000 and exported as a schema in mdb file. This data model will be implemented following criteria and parameters from the International Boundary Water Commission (IBWC), Texas Commission on Environmental Quality (TCEQ), United States Geological Survey (USGS), Environmental Protection Agency (EPA), Mexican National Water Commission (CAN), and the Mexican Natural Resources and Environmental Secretary (SEMARNAT). This georeferenced database will include spatial and temporal information, and would be implemented in a Geographic Information System (ArcGIS) following the ArcHydro data model structure developed at the Center for Research in Water Resources of the University of Texas at Austin (CRWR-UT). This relational database will be related to the Water Quantity Data Model for the Rio Grande/Bravo basin already developed at the CRWR-UT.

4.1. Data Collection

Data regarding to the water quality control points and its corresponding historical information on the American side was collected from the International Boundary Water Commission. This info is classified in two parts; one of them is included in the ‘IBWC Water Bulletins (http://www.ibwc.state.gov/EMD/Water_Bulletins/Water_Bulletins.htm)” and the other one is part of the “Texas Clean River Project (http://www.ibwc.state.gov/CRP/monstats.htm)”. The Clean River Project (CRP) is being achieved among several agencies such as IBWC and TCEQ. All original data is included in excel spreadsheets and cover info since 1990 – 2000 in the most cases. The rivers are classified by the TCEQ with a specific segment ID, which will be preserved in the Water Quality Data Model (WQDM). These river segments are reported as a shapefile in the TCEQ website (http://www.tnrcc.state.tx.us/gis/ourmaps.html). The waterbodies included in the WQDM will be gathered from the TCEQ for the American side, preserving its classification criteria. The river segments, water quality control points and waterbodies information on the Mexican side of the basin will be collected from the CNA or SEMARNAT agencies.

4.2. Developing the schema of the Water Quality Data Model (WQDM)

A water quality framework is being created in Visio 2000 to have the Rio Grande Water Quality UML file. This framework follows the ArcHydro data Model philosophy, but some changes are being made to the attribute tables of the feature classes, in order to met criteria and parameters required by the TCEQ, EPA, USGS, IBWC, CILA, and CNA.

Once the Water Quality Data Model UML has been created, it must be exported as mdb file to create the schema, which will be applied to a relational geodatabase in ArcCatalog.

4.3. Spatial reference information

Projected Coordinate System: NAD_1983_Albers

Projection: Albers

False_Easting: 1000000.00000000

False_Northing: 1000000.00000000

Central_Meridian: -103.00000000

Standard_Parallel_1: 27.41666667

Standard_Parallel_2: 34.91666667

Latitude_Of_Origin: 31.16666667

Linear Unit: Meter (1.000000)

Geographic Coordinate System:

GCS_North_American_1983

Datum: D_North_American_1983

Prime Meridian: 0

4.4. Entity and attribute information

4.4.1. Feature Class: HydroEdge

This feature class depicts the official TCEQ Stream Segments for the State of Texas as listed in Title 30, Chapter 307 of the Texas Administrative Code (TAC), also known as the Surface Water Quality Standards on the US side, and the official CNA or SEMARNAT Stream Segments for the Mexican side of the Rio Grande/Bravo basin. These are streams and waterbodies that have been individually defined by the TCEQ and the other participating agencies and assigned unique identification numbers. Intended to have relatively homogeneous chemical, physical, and hydrological characteristics, a segment provides a basic unit for assigning site-specific standards and for applying water quality management programs of the agency. Both "classified" and "unclassified" segments have been included in this feature class. Classified segments, also referred to as designated segments, refer to water bodies that are protected by site- specific criteria. The classified segments are listed and described in Appendix A and C of Chapter 307.10 of the TAC. The site-specific uses and criteria are described in Appendix A. Classified waters include most rivers and their major tributaries, major reservoirs, and estuaries. Unclassified waters are those smaller water bodies that do not have site-specific water quality standards assigned to them, but instead are protected by general standards that apply to all surface waters in the state. This feature class also identifies which segments and water bodies have been listed as impaired or threatened in the final draft of the Texas 2000 Clean Water Act Section 303(d) List (effective August 31, 2000) for the U.S. side of the Rio Grande/Bravo basin. An impaired segment is a water body which does not meet the standards set for its use, or is expected not to meet its use in the near future. The impaired code table associated with this feature class contains fields which indicate which segments are impaired and which pollutants are responsible for the failure of those segments to meet water quality standards. The hydrography described as HydroEdges in the Rio Grande/Bravo basin geodatabase for the water quantity developed in the CRWR is used to define these river segments within the WQDM.

a. Attribute: HydroID. This is the unique 10 digit identification number assigned by the CRWR. This ID will be used to establish the topology in the geometric network. The HydroID for this element would be assigned as described below:

The first digit indicates the country where the element is located. It was defined the number 1 for the segments located on the US side, and 2 for the segments located on the Mexican side. The next two digits indicate the feature class within the geodatabase. Number 02 was assigned to HydroEdge feature class, which contains the river segments. The next three digits correspond to the element number; and the last four digits describe the river segment classification from the corresponding agency (TCEQ and EPA on the US side and CNA or SEMARNAT on the Mexican side).

b. Attribute: HydroCode. This is the public identification number assigned by the TCEQ, USGS, EPA, IBWC, or CNA.

c. Attribute: ReachCode. This field is added to store the ReachFile from the EPA

d. Attribute: Name. The name of the classified or unclassified segment as it appears in the Texas Surface Water Quality Standards on the US side, and as it appears in the National Water Commission (CNA) or the Natural Resources and Environmental Secretary (SEMARNAT) classification on the Mexican side.

e. Attribute: LengthKm. This field indicates the river segment length in Km

f. Attribute: LengthDown. This field indicates the distance of the river segment to the outlet of the Rio Grande/Bravo basin, usually calculated in kilometers based on the HydroEdge attribute LengthKm.

g. Attribute: FlowDir. This field indicates flow direction of each river segment

h. Attribute: Agency_ID. This is a unique digit identification number as it appears in the TCEQ, EPA, IBWC, CILA, CNA, SEMARNAT, etc., databases for every river segment. This ID is usually the same as the HydroCode attribute

i. Attribute: SegmentClass. Classified: River Segments or water bodies that are protected by site-specific criteria as outlined in the TCEQ Surface Water Quality Standards. Unclassified: Smaller water bodies that do not have site-specific water quality standards assigned to them, but instead are protected by general standards that apply to all surface water in the state.

j. Attribute: SegmentType. Freshwater Stream: Inland waters which exhibit no measurable elevation changes due to normal tides. Tidal Stream: Descriptive of coastal waters which are subject to the ebb and flow of tides. For purposes of standards applicability, tidal waters are considered to be saltwater. Classified tidal waters include all bays and estuaries with a segment number that begins with 1323xx for the Texas side, all streams with the word tidal in the segment name, and the Gulf of Mexico. Reservoir: Any natural or artificial holding area used to store, regulate or control water. Estuary: Regions of interaction between rivers and near shore ocean water, where tidal action and river flow create a mixing of fresh and salt water.

k. Attribute: Location. Verbal description indicating where the stream segment or water body begins and ends.

l. Attribute: Basin. This field describes the name of the basin. Rio Grande/Bravo basin is the official name within the WQDM

m. Attribute: Region. This field describes the region where the stream segment is located, according to the TCEQ classification on the Texas side and the CNA classification on the Mexican side

n. Attribute: Impaired_Status. Single-character field indicating whether or not the water body was impaired in the 2000 Surface Water Quality Standards effective on September 1, 2000. GIS Maps are available with results about impairing for 2000, but not for year 2002 in the TCEQ website (http://www.tnrcc.state.tx.us/water/quality/data/wmt/data_by_basin.html). These results will be updated for 2002 in the WQDM.

o. Attribute: AgencImpairCode. A one-digit numeric code from the agency indicating why the water body is listed as impaired. This attribute will be related with the Impaired_Code_Table through the CRWR_ImpairedCode attribute.

p. Attribute: CRWR_ImpairedCode. A small integer related to the impaired code from the agency. There will be established a relationship between this attribute and the Impaired_Code_Table to describe why the river segment or waterbody is considered as impaired.

A relationship will be established between a river segment and its corresponding water quality monitoring station (Identified as a Monitoring Point within the geodatabase). Another relationship will be established between the river segments (HydroEdge) and the HydroJunction feature class. The HydroJunction is a virtual point representing a monitoring point in the geometric network.

4.4.2. Feature Class: Monitoring Point

This feature class shows all surface water quality monitoring being conducted by the TCEQ or under TCEQ contract for Fiscal Year 2005 on the Texas side, and all water surface water quality monitoring identified by the CNA and SEMARNAT on the Mexican side. Other type of water quality points such as treatment plants location, waste water discharges, and hazardous points will be included in this feature class within the WQDM. The water quality stations on the US side of the Rio Grande/Bravo basin was downloaded from the IBWC website (http://www.ibwc.state.gov/CRP/monstats.htm), where user can find the monitoring point locations considered in the IBWC-Clean River Project. To support coordinated monitoring, the TCEQ has developed guidance for site selection and for sampling requirements for routine, special study, and targeted monitoring. In this website http://www.tnrcc.state.tx.us/water/quality/data/wqm/coop_monitoring_2005.html TCEQ provides more documents as support for the statewide coordinated monitoring effort on the Texas State.

a. Attribute: HydroID.

It indicates a unique feature identifier in the Water Quality Data Model assigned at the CRWR. This ID becomes the key to establish many relationships between the monitoring point and some elements included in the WQDM. The HydroID for this element would be assigned as described below:

The first digit indicates the country where the element is located. It was defined the number 1 for the water quality points located on the US side, and 2 for the control points located on the Mexican side. The next two digits indicate the feature class within the geodatabase. Number 01 was assigned to Monitoring Point feature class, which contains the water quality control points. The next three digits correspond to the element number; and the last four digits describe the water quality river segment where the water quality control point is measuring according to the TCEQ and EPA classification on the US side and CNA or SEMARNAT on the Mexican side.

4.4.3. Feature Class: Waterbody

This feature class will include the water bodies, impaired or not, located on the Rio Grande/Bravo basin on both sides of the basin. Waterbodies are all the significant ponds, lakes, and bays in the water system. The American waterbodies will be gathered from the USGS, EPA, and TCEQ, while the CAN and SEMARNAT will provide the waterbodies information on the Mexican side.

4.4.4. Feature Class: Watershed

This feature class will include information related to the drainage areas contributing flow from the land surface to the water system. The watershed information on the Mexican side is collected from the CNA and SEMARNAT, while this is being collected from EPA and TCEQ on the American side. The EPA manages water pollution using Total Maximum Daily Loads (TMDL) defined on watersheds draining to selected river segments or waterbodies, a different watershed layout than that used by the National Weather Service on the US. The WQDM is designed to allow any set of watersheds to be relationally connected to the hydro network, using the “area flows to a point on a line” concept to establish relationships between watersheds and HydroJunctions at their outlet location.

4.4.5. Feature Class: HydroJunction

This feature class includes a set of junctions located at the end of the river segments and at other strategic locations on the flow network. Usually the Monitoring Points, which preserve their original position, are represented by the HydroJunction on the flow network. HydroEdges and HydroJunctions are topologically connected in an ArcGIS geometric network, called the HydroNetwork and included as the backbone of the WQDM. Since HydroJuctions area topologically linked to the river segments (HydroEdges) in the geometric network, the combination of this network and the other relationships means that the classes in the WQDM framework are connected into an integrated data structure.

4.4.6. Time Series table

The inclusion time series data in the WQDM is not only to create a complete water quality data model for using the GIS environment, but also to build a relational database that would be accessible to many water quality models that operate separately of the GIS. The temporal information is captured and stored in a variety formats by each entity, so it is fundamental to have a standard design to manage large historical data sets. The original ArcHydro time series framework for the surface water is being modified to have a large container in GIS that allows storing many variables related to the water quality data that include millions of records. Under this concept, user may acquire, store, or deliver an entire water quality data set, including time series data files from water quality stations, as well as the geographic element associated to it.

4.4.7. TSGroup table

This table describes the entity that manages and publishes some information. In this table users can identify from where the information comes, using a unique identifier for each agency. A relationship is established between the temporal information in the time series table and the Monitoring Point feature class using the FeatureID as the key.

4.4.8. TSType table

The TSType table contains an index of the types of time series data stored in the time series table. A relationship is established between the TSType table and the Time Series table using the TSTypeID as the key.

4.4.9. Impaired Code Table

This table is associated with the HydroEdge and WaterBody feature classes within the WQDM to indicate which river segments are impaired. The impaired code table contains fields to describe which pollutants are responsible for the failure of river segments to meet water quality standards.

4.4.10. Agency responsible table

This table describes which entity is in charge of the water quality stations. A relationship is established between the Agency responsible table and the Monitoring Point feature class using the AgenResp_Code attribute as the key.

4.4.11. Topology and relationships among the feature classes

A geometric network called HydroNetwork is created to establish the topology among the elements within the WQDM. This HydroNetwork becomes the backbone of the WQDM structure, created from the river segments (HydroEdges) and the water quality monitoring stations (HydroJunctions). The topological connection of its HydroEdges and HydroJunctions in the WQDM enables tracing of water movement upstream and downstream through streams and waterbodies. Relationships built from the HydroJunctions connect drainage areas, waterbodies and any point features such as water quality stations or wastewater treatment plants to the HydroNetwork. Each relationship has a multiplicity, and all the relationships implemented are one-to-many. One-to-many multiplicity means that one HydroJunction may be associated with one or more features in the related class. For example, two HydroEdges (river segments) may drain into a single HydroJunction on a river network

4.5. Data processing

4.5.1. Creating HydroEdges

The original river segments (including the waterbodies) on the US side were extracted from TIGER/Line 92 data to create the initial Designated Stream Segments layer. Where that layer was lacking, missing streams and new reservoirs were table-digitized from TxDOT "half-scale" county map sheets. The Mexican side of the Amistad and Falcon reservoirs and the outlying boundaries of the border lakes were "heads-up" digitized from a digital map created in the early 1980s by the Texas Water Commission (from 1:250,000 AMS map sheets). The hydrography described as HydroEdges in the Rio Grande/Bravo basin geodatabase for the water quantity is being used to define these river segments within the WQDM (figure 22). Fragmented segments were merged in ArcInfo so that each displayed segment was represented by only one record in the table.

Figure 22 Flowline resolution in the Rio Grande/Bravo basin

4.5.2. Creating Monitoring Points

Water quality stations, wastewater treatment plants, and other important control points are being included into the WQDB as a feature class called Monitoring Points. The water quality stations on the US side of the Rio Grande/Bravo basin was downloaded from the IBWC website (http://www.ibwc.state.gov/CRP/monstats.htm), where users can find the monitoring point locations considered in the IBWC-Clean River Project. To support coordinated monitoring, the TCEQ has developed guidance for site selection and for sampling requirements for routine, special study, and targeted monitoring. In this website http://www.tnrcc.state.tx.us/water/quality/data/wqm/coop_monitoring_2005.html

4.5.3. Creating the SnapControlPoint feature class

Because more than two monitoring points could be represented for just one HydroJunction in the geometric network, it is necessary to have one more feature class called SnapControlPoint. The SnapControlPoint is a point feature class that represents all monitoring points with all the features snapped to the right location on the network. The HydroCode is the unique identifier to establish the relationship between the SnapControlPoint and the Monitoring Point feature class. The main purpose of this feature class is to exchange information about water quality parameters between the HydroJunctions participating in the geometric network and the monitoring points, which maintain their original position.

4.5.4. Creating HydroJunctions

Since more than one monitoring point can exist at the same location, it is fundamental to have one point on the geometric network representing all of them. These points participating directly in the network are known as HydroJunctions in the ArcHydro jargon. The HydroID is the key to establish the relationship between the HydroJunctions and the monitoring points. This unique value will be assigned to the JunctionID value of the all monitoring points that are representing, so two or more monitoring points could have the same JunctionID.

4.5.5. Creating a geometric network

A geometric network is crated using the SnapControlPoint and HydroEdge feature classes. All points in the SnapControlPoint feature class are snapped 500 m to the HydroEdge element. In order to avoid dividing the river segments into several parts, this geometric network is built as a complex edge,

Also, the historical information related to the monitoring points is included in the time series table within the WQDM.

4.5.6. Discrepancy of the hydrologic data

There are some discrepancies in the information from the stream network RF1 used by the EPA, and the river network reported by the USGS (figure 23). For example, the Costilla Creek river, which is located between Colorado and New Mexico, and lies in the subregion 1302 according to the NHD classification, is an important tributary to the Rio Grande according to the USGS, but it is flowing to nowhere according to the RF1 system (1:500K).
A comparison for the river system is shown in figure 3, considering river versions from RF1, NHD (100K scale), and the drainage line produced from the Digital Elevation Model (30 m grid resolution).

Figure 23 Comparison between RF1 and NHD river network

Figure 24 River network comparisons among NHD, RF1, and DEM versions

· There are some inconsistencies in the hydrography of the upper basin. Figure 25 shows the comparison of the river network from RF1 and the NHD, after the last one was edited.

Figure 25 Comparison between the RF1 and fixed NHD stream network

5. CONCLUSIONS

A binational geodatabase was created that includes a relational database containing hydrologic, hydraulic and related data for the Rio Grande/Bravo basin. This geodatabase was development using the ArcHydro data model framework, and is being made available to Mexican and U.S. federal, state, and local organizations. This is a tool that can assist in promoting bi-national cooperation between Mexico and the United States concerning water in the Rio Grande basin, providing accurate and reliable data necessary for analysis and resolution of water resources issues. The first part of this research was to collect the hydrologic information from both Mexican and American agencies. Unfortunately this information did not have the same characteristics and accuracy in both sides, so it had to be edited, reprojected, and fixed in order to get unified criteria for the geodatabase.

One of the main purposes of this research is to develop and apply an operational method for the automated parameterization of large basins. There are a number of potential advantages to using automated digital terrain analysis techniques to derive parameters and variables for hydrologic models. The principle advantage is the speed and reproducibility with which the parameterization task can be accomplished. The development of a Raster-Network Regionalization technique for large basins utilizing raster-based analysis at the subregional scale in an efficient method is one of the most important contributions of this research. This methodology allows large regions to be divided into hydrological distinct subregions where raster analyses may be performed in a feasible manner. The results from each subregion are stored as attributes on vector data. The vector data are then merged, and appropriate values accumulated to obtain hydrologic parameter values for points of interest along the stream network, such as the drainage area, average Curve Number, average precipitation, and distanced from monitoring points to the basin outlet. The results from each subregion are stored as attributes on vector data. This technique uses the vector stream network as the pillar for the integration of subregions into a single region. The ArcGIS Hydro Data model is used to provide attributes with which to establish connectivity, as well as tools to perform the attribute accumulation. Also, this methodology helped to verify the validity of dividing a basin for processing without compromising on the accuracy of the parameter values determined. The Raster-Network Regionalization technique could also be applied at a local level when high resolution data, such as LIDAR data, area available. These data are so dense they typically preclude raster analysis over a relatively small area. In conclusion, this technique takes advantage to using automated digital terrain analysis technique to parameterize watershed over a range of scales. This can only be done rapidly and systematically using automated methods.

The Raster-Network Regionalization technique has been successfully applied for the binational Rio Grande/Bravo basin, which has a contributing area of over 468,000 km2 using high-resolution DEM. The drainage area for each control point is determined using the proposed technique and compared to reported stream gage contributing areas from the U.S. Geological Survey (USGS) and the National Water Commission (CNA) of Mexico. This comparison of the drainage areas for DEM-delineated watersheds to reported U. S. Geological Survey values validates the methodology for subdividing large basins into hydrologic subregions.

Non-contributing drainage areas such as depressions where the runoff is trapped were not considered in the Rio Grande/Bravo basin analysis.

A powerful conclusion from this research is that regional HydroID assignment is critical to the success of regionalization. The HydroID enables the connection between features in the landscape, including the connection of watersheds to outlet junctions, as well as the connection of junctions with next downstream junction. Also, it allows the integration of subregions into regions, through the update of the NextDownID in the most downstream junction in each region.

The main difference in processing watershed parameters using any traditional method and the Raster Network Regionalization technique proposed in this research is that in the traditional methods, raster data are used both for determining the local values as well as upstream accumulated values of the watershed parameters, whereas the technique applied in this research uses a combination of raster and vector data to find these parameters. The local areas are derived from raster and all the other values are determined in a vector environment.

The time series component of the Arc Hydro Data Model is being improved to more efficiently store and manage large numbers of time series records using a common data schema. One more table called TSGroup that contains information related to the agency from which the data is derived is added to the original ArcHydro structure. By this way, users will be able to select a specific monitoring point within the geodatabase and several relationships have been established for it, so they can identify the sources from which the temporal data were derived, as well as the type of variable. This new time series format is more robust and can handle more than five million records distributed in many variable types. This new framework is being applied to the Rio Grande/Bravo basin geodatabase to improve the management of temporal information gathered from U.S. and Mexican agencies.

A GIS toolset called DSS Hydro tool is being developed in this research. This will be used to transfer historical records from the Rio Grande/Bravo basin geodatabase into HEC-DSS files for using with USACE HEC models. This tool consists of a set of public domain utilities comprised of four commands that operates in the ArcGIS ArcMap environment.

BIBLIOGRAPHY

Al-Sabhan, W., Mulligan, M., Blckburn, G.A. “A real-time hydrological model for flood prediction using GIS and the WWW.” Computers, Environment and Urban Systems, Vol. 27, (2003) pp. 9-32

Abrahart, R. J., et al. "MEDRUSH - Spatial and Temporal River-basin Modelling at Scales Commensurate with Global Environmental Change." In K. Kovar and H. P. Nachtnebel (eds.), Application of Geographic Information Systems in Hydrology and Water Resources Management (pp. 47-54). Proceedings of the HydroGIS '96 Conference, Vienna, Austria, 16-19 Apr. 1996. Netherlands: Krips Repro, Meppel.

Eaton, D. J., and Hurlbut, D. “Challenge in the Binational Management of Water Resources in the Rio Grande/Rio Bravo.” Lyndon B. Johnson School of Public Affairs, University of Texas at Austin, 1992.

ESRI. “FAQ: What is the maximum size a grid can be?” Article 14575 (2005)

Figurski, Melissa J. GIS Algorithms for Large Watersheds with Non-contributing Areas. Thesis. The University of Texas at Austin, 2001. CRWR Online Report 01-7. <http://www.crwr.utexas.edu/reports/2001/rpt01-7.shtml>.

Garbrecht, J, Martz, LW. “TOPAZ v 3.1: and automated digital landscape analysis tool for topographic evaluation, drainage identification, watershed segmentation and subcatchment parameterization.” TOPAZ User Manual, Report #2-00 Grazinglands Research Laboratory, USDA, Agricultural Research Service, El Reno, OK; (2000) 143

Funke, R., Schumann, A., Schultz, G.A. “Regionalization of parameters in mesoscale hydrological models.” International Association of Hydrological Science Publication n 254 (1999), 171-179

Goodall, J., Maidment, D., and Sorenson, J. “Representation of spatial and temporal data in ArcGIS.” AWRA GIS and Water Resources III Conference, (2004) Nashville, TN.

Gopalan, Hema. “WRAPHydro Data Model: Finding Input Parameters for the Water Rights Analysis Package.” Thesis. The University of Texas at Austin, 2003. CRWR Online Report 03-3 . <http://www.crwr.utexas.edu/reports/2003/rpt03-3.shtml>.

Hudgens, Bradley T., and David R. Maidment. “Geospatial Data in Water Availability Modeling.” Thesis. The University of Texas at Austin, 1999. CRWR Online Report 99-4. <http://www.crwr.utexas.edu/reports/1999/rpt99-4.shtml>.

International Boundary Water Commission (IBWC). “Convention between the United States and Mexico: Equitable Distribution of the Waters of the Rio Grande”. (1906). IBWC Online Report. http://www.ibwc.state.gov/Files/1906Conv.pdf

Jenson, S.K., Domingue, J.O., “Extracting topographic structure from digital elevation data for geographical information system analysis.” Photogrammetric Engineering and Remote Sensing 54 (1988), 1593-1600

Kite, GW. “Scaling of input data for macroscale hydrologic modeling.” Water Resources Research 31 (1995) 2769-2781

Lacroix, M.P., Martz, L.W., Kite, G.W., and Garbrecht, J. “Using digital terrain analysis modeling techniques for the parameterization of a hydrologic model.” Environmental Modeling & Software 17 (2002) 127-136

Maidment, David R. “Arc Hydro: GIS for Water Resources.” Redlands: ESRI Press, 2002.

Mason, David. An Analysis of a Methodology for Generating Watershed Parameters using GIS. Thesis. The University of Texas at Austin, 2000. CRWR Online Report 00-3. <http://www.crwr.utexas.edu/reports/2000/rpt00-3.shtml>.

Patino, C., McKinney, D., and Maidment, D. “Water Management Information System for the Rio Bravo/Grande Basin.” Proceedings ESRI User Conference, (GIS-Hydro 2004).San Diego, CA

http://www.crwr.utexas.edu/gis/gishydro04/time/Rio_Grande-Bravo_Basin.htm

Patino, C., McKinney, D; Maidment, D., Goodall, J., Martinez, P., Hinojosa, J.M., Quezada, V. “Water Management Information System for the Rio Bravo/Grande basin: Creation of a georeferenced data base.” Second International Symposium on Transboundary Water Management. 2004 Tucson, Arizona.

Patino, C., McKinney, D; and Maidment, D. “Development of a Hydrologic Geodatabase for the Rio Grande/Bravo Basin”. Geographic Information Systems and Water Resources III. AWRA Spring Specialty Conference. 2004. Nashville, Tennessee.

SCERP (Southwest Center for Environmental Research and Policy). “The US – Mexican border environment: Water issues along the U.S. – Mexican border.” Monograph No. 2 (2000).San Diego State University Press.

SCERP (Southwest Center for Environmental Research and Policy). “The US – Mexican border environment: Economy and environment for a sustainable border region: Now and in 2020.” Monograph No.3 (2002). San Diego State University Press.

Schumm, S.A. “To interpret the earth: Ten ways to be wrong.” Cambridge University Press, 133 pp (1998).

Spence, C., Dalton, A., Kite, G.W. “GIS supports hydrological modeling.” GIS World 8 (1) (1995), 62-65

Streit, Ulrich, and Hans Kleeberg. "GIS-based Regionalization in Hydrology: German Priority Programme on Spatial Transfer of Hydrological Information." In K. Kovar and H. P. Nachtnebel (eds.), Application of Geographic Information Systems in Hydrology and Water Resources Management (pp. 485-491). Proceedings of the HydroGIS '96 Conference, Vienna, Austria, 16-19 Apr. 1996. Netherlands: Krips Repro, Meppel, 1996.

Teasley, R. L., McKinney, D., and Patino, C. “Modeling the Forgotten River Segment of the Rio Grande/Bravo Basin.” The University of Texas at Austin 2004. CRWR Internal Report.

The alliance for the Rio Grande Heritage, Forest Guardians, Rio Grande Restoration, Defender of Wildlife, The Land and Water Fund of the Rockies, Amigos Bravos. “Diverting the Rio Grande” April, 2000.

http://www.fguardians.org/reports/mrgcdreportoverdiversions.html

The Encyclopedia of Water in the West 2002. “Rio Grande River Basin” http://www.waterwest.org/riverbasins/riogrande/riogrande.htm#Perspectives

Tribe, A. “Automated recognition of valley lines, drainage networks from grid digital elevation models: a review, a new method.” Journal of Hydrology 139 (1992) 263-293

US Department of State. “Utilization of waters of the Colorado and Tijuana Rivers and of the Rio Grande.” Treaty Series 994, Treaty between the United States of America and Mexico. Washington, DC: Government Printing Office (1946)

Whiteaker, Tim. Geographically Integrated Hydrologic Modeling Systems. Thesis. The University of Texas at Austin, 2004. CRWR Online Report 2004-04. < http://www.crwr.utexas.edu/reports/2004/rpt04-4.shtml >.

Wurbs, R. A. "Reference and Users Manual for the Water Rights Analysis Package (WRAP)." Texas Water Resources Institute, Jul. 2001.