Presentations from MRCSP 2019 partners meeting with overviews of the program, technical work, policies, synergistic projects, the new regional initiative, and next steps.

Data sets include information on emissions of air pollutants, description of 3-D meteorological state of the atmosphere, and output from the CMAQ model over the northern hemisphere and contiguous U.S. This dataset is not publicly accessible because: This research was conducted a part of the primary author's Ph.D. dissertation at the University of North Carolina at Chapel Hill. All data sets were created on the UNC computers and are housed there. Since the data sets are not directly available to the EPA investigator, they are not included in ScienceHub. It can be accessed through the following means: Data sets can be accessed by contacting Dr. Sarav Arunachalam at UNC - sarav@email.unc.edu. Format: Model input (3D meteorological fields and 3D emission files) and output are in netcdf format. Observational data sets used are publicly available and typically available as ascii files. This dataset is associated with the following publication: Vennam, L., W. Vizuete, K. Talgo, M. Omary, F. Binkowski, J. Xing, R. Mathur, and S. Arunachalam. Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 122(24): 13,472–13,494, (2017).

Key Findings: Monte Carlo approach looking a uncertainty in system parameters (e.g., geology and well leakage parameters) and impact to groundwater. For all but the highest leakage scenarios, leakage was well below the threshold set by the IPCC and proxy indicators of pH and TDS were low. NRAP Tools: NRAP-IAM-CS Location: Ordos Basin, China  

An open source computational toolset to accelerate and de-risk technology development and commercialization through first-principles, multi-scale modeling, optimization and uncertainty quantification.

This package includes the data and Python files for the publication "Non‐Gaussian parameter inference for hydrogeological models using Stein Variational Gradient Descent".

This study documents the development of a semi-distributed hydrological model aimed at reflecting the dominant controls on observed streamflow spatial variability. The process is presented through the case study of the Thur catchment (Switzerland, 1702 km2), an alpine and pre–alpine catchment where streamflow (measured at 10 subcatchments) has different spatial characteristics in terms of amounts, seasonal patterns, and dominance of baseflow. In order to appraise the dominant controls on streamflow spatial variability, and build a model that reflects them, we follow a two–stages approach. In a first stage, we identify the main climatic or landscape properties that control the spatial variability of streamflow signatures. This stage is based on correlation analysis, complemented by expert judgment to identify the most plausible cause-effect relationships. In a second stage, the results of the previous analysis are used to develop a set of model experiments aimed at determining an appropriate model representation of the Thur catchment. These experiments confirm that only a hydrological model that accounts for the heterogeneity of precipitation, snow related processes, and landscape features such as geology, produces hydrographs that have signatures similar to the observed ones. This model provides consistent results in space–time validation, which is promising for predictions in ungauged basins. The presented methodology for model building can be transferred to other case studies, since the data used in this work (meteorological variables, streamflow, morphology and geology maps) is available in numerous regions around the globe.

Data for the 9 figures contained in the paper, A SOFTWARE FRAMEWORK FOR ASSESSING THE RESILIENCE OF DRINKING WATER SYSTEMS TO DISASTERS WITH AN EXAMPLE EARTHQUAKE CASE STUDY. This dataset is associated with the following publication: Klise, K., M. Bynum, D. Moriarty, and R. Murray. A SOFTWARE FRAMEWORK FOR ASSESSING THE RESILIENCE OF DRINKING WATER SYSTEMS TO DISASTERS WITH AN EXAMPLE EARTHQUAKE CASE STUDY. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 95: 420-431, (2017).

FRACGEN/NFFLOW is a DOE sponsored project to simulate the behavior of tight, fractured, strata-bound reservoirs that arise from irregular, discontinuous, or clustered networks of fractures. This distribution includes the PC programs and user interfaces for fracture network generation, discrete fracture reservoir simulation, and visualization of fracture networks and reservoir performance. New features in this release are optional fixed pressure boundary conditions, permeable unfractured layers, liquid data handling, sorption, and stress sensitive aperture modeling.

Final report on the CO2 injection test in the Mt. Simon Formation addressing the objective and scope of the East Bend project, and results of the validation project.

Modeling and Optimizing Surfactant Structure to Improve Oil Recovery by Chemical Flooding at the University of Texas DOE/BC/10841-10

DOE/BC/10841-5

This dataset is for an analysis that used the MARKAL linear optimization model to compare the carbon emissions profiles and system-wide global warming potential of the U.S. energy system over a series of model runs in which the power sector is required to meet a specific carbon dioxide reduction target across a number of scenarios in which the availability of natural gas changes. Scenarios are run with carbon dioxide emissions and a range of upstream methane emission leakage rates from natural gas production along with upstream methane and carbon dioxide emissions associated with production of coal and oil. This dataset is associated with the following publication: Lenox , C., and O. Kaplan. Role of natural gas in meeting an electric sector emissions reduction strategy and effects on greenhouse gas emissions. Energy Economics. Elsevier B.V., Amsterdam, NETHERLANDS, 60: 460-468, (2016).

Surfactant concentration is one of the important factors in determining foam generation and propagation.When surfactant solutionis flowing in a reservoir formation, surfactants will be diluted by flow dispersion, retained in dead-end pores, adsorbed on rock surfaces, or precipitated due to ion exchange. All these physical and chemical aspects complicate the problem of foam. The loss of surfactant will be detrimental to the performance of gas foam. Information of surfactant concentration profiles in reservoir formations is essential for gas foaming technique development. This research was designed to investigate the transport and adsorption phenomena of surfactants in porous media. The major objective of this research is to investigate with mathematical models the transport and dynamic adsorption of surfactants in porous media. The mathematical models have taken into account the convection, dispersion, capacitance, and adsorption effects on concentrations of surfactants. Numerical methods and computer programs have been developed which can be used to match experimental results and to determine the characterization parameters in the models. The models can be included in foam simulation programs to calculate surfactant concentration profiles in porousmedia. A flow experimental method was developed to measure the effluent surfactant concentration, which will be used to determine the model parameters. Commercial foaming agent Alipal CD-128 was used in this study. Equilibrium adsorption and surfactant precipitation have been tested. Tracer solutions with a nonadsorbing solute such as dextrose and sucrose were used to determine the dispersion parameters for the experimental sandpack; thus, the adsorption of the surfactant in the test sand can be identified with an adequate model.

Final technical report discussing the project background, the Michigan Basin large scale injection test, regional analyses, and additional studies.

The Mobility Trends County Modeling dataset consists of the accumulation of the three performance metrics: VMT, GHG, and TMS, alongside each of the trend indicators: GDP, Population, Lane Miles, Unemployment Rate, Charging Stations, Telework, Unlinked Passenger Trips, E-commerce, Population Density, and on-demand service revenue. The goal of Mobility Trends and Future Demand research project is to enhance FHWA’s empirical understanding of the impact of trends on travel behavior and transportation demand, and ultimately system performance and the user experience. At the core of this research project is the identification and analysis of trends to support a variety of modeling, forecasting, and ‘what if’ projections to support policy and decision making.

The Mobility Trends County Modeling dataset consists of the accumulation of the three performance metrics: VMT, GHG, and TMS, alongside each of the trend indicators: GDP, Population, Lane Miles, Unemployment Rate, Charging Stations, Telework, Unlinked Passenger Trips, E-commerce, Population Density, and on-demand service revenue. The goal of Mobility Trends and Future Demand research project is to enhance FHWA’s empirical understanding of the impact of trends on travel behavior and transportation demand, and ultimately system performance and the user experience. At the core of this research project is the identification and analysis of trends to support a variety of modeling, forecasting, and ‘what if’ projections to support policy and decision making.

DOE/BC/10841-15 Modeling and Optimizing Surfactant Structure to Improve Oil Recovery by Chemical Flooding at the University of Texas--Final Report

NIPER-498

Numerical Modeling of Massive Hydraulic Fractures, Annual Report; July 1983

Numerical Modeling of Massive Hydraulic Fractures, First Annual Report; September 1980-August 1981

The library contains over 260 documents regarding nuclear energy projects of DOE.

This paper summarizes semi-analytical and closed-form solutions that can be used to assess the poroelastic stress changes induced within a porous formation (reservoir) during a pore pressure change. Further, solutions are presented for the stress discontinuities at the interfaces between reservoirs and the rocks that surround them. When used in combination with rock failure criteria, these solutions enable relatively simple analyses of the potential for induced fracturing or fault reactivation within a reservoir or the rock immediately adjacent to it. The latter , in particular, is useful for assessing if the hydraulic integrity of the surrounding rock (i.e., the bounding seal) will be affected by a pore pressure change. The use of the approach presented in this paper is illustrated with an analysis of a pinnacle reef with dimensions and properties representative of reefs in the Zama oil field, northwestern Alberta, Canada. Scenarios of pore pressure decrease (during historical production operations) and pore pressure increase (during several years of acid gas injection operations) are analyzed, for three different idealizations of reservoir properties and geometry (two plane strain and one axisymmetric). These results suggest that that the potential for induced fracturing is not significant at any point within the reservoir or the surrounding rock for both the production and injection scenarios that were simulated. Similarly, fault reactivation was not predicted for the reservoir or any of the points that were analyzed in the surrounding rock. However, fault orientations having the greatest potential for reactivating during historical production operations were identified; thus, illustrating a means of using geomechanical models to focus geological characterization efforts on the features that are most critical to acid gas containment. (PDF) Poroelastic Modelling of Production and Injection-Induced Stress Changes in a Pinnacle Reef. Available from: https://www.researchgate.net/publication/313904468_Poroelastic_Modelling_of_Production_and_Injection-Induced_Stress_Changes_in_a_Pinnacle_Reef [accessed Sep 25 2018].

DOE/BC/14893-6

In the conceptual design of the seismic history match workflow, the 4-D seismic amplitude data are used as a reference to update dynamic simulation results and the underlying geologic model in an iterative manner to better match the 4-D seismic response, which will result in reduced uncertainty regarding simulation results. The schema outlines the forward modeling (top figure) and inverse modeling (bottom figure). On one side (top, left to right) with a forward modeling approach, the CO2 simulation plumes are computed based on the geologic model properties input. On the other side (bottom, right to left) with an inverse modeling approach, the CO2 plume actual shapes and locations are measured with 4-D seismic. Both models are compared using their respective petroelastic properties, and a misfit is calculated. After that, the geologic model is updated using appropriate adjustments and the simulation is recomputed. The iterative process continues until the misfit threshold is met.

This dataset concerns the development of models for describing the acute toxicity of major ions to Ceriodaphnia dubia using data from single salt tests and binary mixture tests described in two other datasets under this research effort. It provides the data used in model development in the associated journal article. It also provides concentration-response data and associated general chemistry conditions for 3 experiments consisting of 14 toxicity tests on more complex mixtures of major ions based on data regarding elevated major ions in effluents and receiving waters, which was used for testing the models. . This dataset is associated with the following publication: Erickson, R., D. Mount, T. Highland, R. Hockett, D. Hoff, T. Norberg-King, and K. Peterson. The acute toxicity of major ion salts to Ceriodaphnia dubia: III. Mathematical models for mixture toxicity. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 1-13, (2017).

This dataset represents the impervious surface coefficients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Land Cover Data. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the NLCD Impervious Surfaces raster(imp2011) which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2011 Landsat satellite data.

This dataset (STATSGO_Set1 and STATSGO_Set2) represents the soil characteristics within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the STATSGO landscape rasters. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the STATSGO landscape rasters for the conterminous USA. Individual rasters (Landscape Layers) of organic material (om), permeability (perm), water table depth (wtdep), depth to bedrock (rckdep), percent clay (clay), and percent sand (sand) were used to calculate soil characteristics for each NHDPlusV2 catchment. The soil characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type. The STATSGO data are distributed in two sets, STATSGO_Set1 and STATSGO_Set2, based on common NoData locations in each set of soil GIS layers (see ftp://newftp.epa.gov/EPADataCommons/ORD/NHDPlusLandscapeAttributes/StreamCat/Documentation/ReadMe.html).

This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated upstream catchments riparian area to provide watershed-level metrics for imperviousness values within the NLCD. This data set is derived from the NLCD Impervious Surfaces raster(imp2001) which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2001 Landsat satellite data.(see Data Structure and Attribute Information for a description of each metric).

This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated upstream catchments riparian area to provide watershed-level metrics for imperviousness values within the NLCD. This data set is derived from the NLCD Impervious Surfaces raster(imp2006) which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2006 Landsat satellite data.

This dataset represents the population and housing unit density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds riparian buffers based on 2010 US Census data. Densities are calculated for every block group and watershed averages are calculated for every local NHDPlusV2 catchment(see Data Sources for links to NHDPlusV2 data and Census Data). This data set is derived from The TIGER/Line Files and related database (.dbf) files for the conterminous USA. It was downloaded as Block Group-Level Census 2010 SF1 Data in File Geodatabase Format (ArcGIS version 10.0). The landscape raster (LR) was produced based on the data compiled from the questions asked of all people and about every housing unit. The (block-group population / block group area) and (block-group housing units / block group area) were summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated upstream catchments riparian area to provide watershed-level metrics for imperviousness values within the NLCD. This data set is derived from the NLCD Impervious Surfaces raster(imp2011) which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2011 Landsat satellite data.(see Data Structure and Attribute Information for a description of each metric).

This dataset represents the impervious surface coefficients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Land Cover Data. AOI boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-AOI boundaries and then links them through an off-network flow table. This data set is derived from the NLCD Impervious Surfaces raster which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2001 Landsat satellite data.

This dataset represents the impervious surface coefficients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Land Cover Data. AOI boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-AOI boundaries and then links them through an off-network flow table. This data set is derived from the NLCD Impervious Surfaces raster which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2008 Landsat satellite data.

This dataset represents the population and housing unit density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on 2010 US Census data. Densities are calculated for every block group and watershed averages are calculated for every local NHDPlusV2 catchment. This data set is derived from The TIGER/Line Files and related database (.dbf) files for the conterminous USA. It was downloaded as Block Group-Level Census 2010 SF1 Data in File Geodatabase Format (ArcGIS version 10.0). The landscape raster (LR) was produced based on the data compiled from the questions asked of all people and about every housing unit. The (block-group population / block group area) and (block-group housing units / block group area) were summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the impervious surface coefficients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Land Cover Data. AOI boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-AOI boundaries and then links them through an off-network flow table. This data set is derived from the NLCD Impervious Surfaces raster which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2019 Landsat satellite data.

This dataset represents the impervious surface coefficients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Land Cover Data. AOI boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-AOI boundaries and then links them through an off-network flow table. This data set is derived from the NLCD Impervious Surfaces raster which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of circa 2016 Landsat satellite data.

This dataset represents total fresh surface-water withdrawals in agricultural land within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Measured as L/day as described in DOI: 10.1016/j.scitotenv.2020.137661

This dataset represents net anthropogenic Nitrogen within AOI: farm fertilizer + urban fertilizer + NOx deposition + CBNF + Human and Livestock food - crop N content - livestock N content within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents mean hillslope percent within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents deposition estimates of nutrients within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Atmospheric Deposition Program. The National Trends Network provides long-term records of precipitation chemistry across the United States. Individual rasters describe ammonium, nitrate, inorganic nitrogen, and average sulfur/nitrogen deposition per year. See Source Info for links to NADP. The nitrogen and sulfur characteristics (kg N/ha/yr) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

N from rock weathering (kg/ km2) within AOI

This dataset represents nitrogen surplus as kg N / yr, excluding biological N Fixation, within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents the density of road and stream crossings within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics. The landscape layer (raster) was developed by James Falcone of the USGS. US Census TIGER 2000 line files of roads and the NHDPlusV1 line files of all streams were converted to 30-meter grids where the presence of a street or stream was a 1 and everything else a 0. These were intersected and anything that was a 1 in both grids is the result. The density of road and stream crossings (crossings / square kilometer) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents percent area consisting of sandstone aquifers within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents percent area consisting of semiconsolidated sand aquifers within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This dataset represents mean percent are burned from wildfires within individual, local NHDPlusV2 catchments and upstream, contributing watersheds for each year for 1984-2018.

This dataset represents the characterization of global forest extent and change by year from 2001 through 2013 within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the Global Forest Change 2000–2013. These data are based on global tree cover loss for the period from 2001 to 2013 at a spatial resolution of 30m. The analysis used to create the landscape layer is based on Landsat data. Forest loss was defined as a stand-replacement disturbance or the complete removal of tree cover canopy at the Landsat pixel scale. This landscape layer is a disaggregation of total forest loss to annual time scales. Encoded as either 0 (no loss) or else a value in the range 1–13, representing loss detected primarily in the year 2001–2013, respectively. The forest loss by year characteristics (%) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI) within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on 23 other StreamCat metrics. The Index of Watershed Integrity (IWI) is based on first order approximations of relationships between stressors and six watershed functions: hydrologic regulation, regulation of water chemistry, sediment regulation, hydrologic connectivity, temperature regulation, and habitat provision. Link to paper: https://doi.org/10.1016/j.ecolind.2017.10.070 The Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

This dataset represents the wetness index within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the Composite Topographic Index (See Supplementary Info for Glossary of Terms). The Composite Topographic Index (CTI) is based on contributing area, slope, and overland flow and has been developed internally at the EPA for the EnviroAtls (http://edg.epa.gov/data/Public/ORD/EnviroAtlas/National/). As defined for use in EnviroAtlas datasets and as used here, “wet areas are typically created by runoff from natural land cover when rain falls on saturated soil. Surface and rill (or small channel) runoff carries excess water to lowland depressions or wet areas. Runoff collects in wet areas until they fill and overflow downstream. In this way, stream networks can be extended into new areas that would not be hydrologically connected during drier times. Wet area expansion and watershed hydrological connectivity differ between humid temperate and semi-arid and arid climates (where drought and soil crusts limit infiltration and produce flashier runoff)” (from https://enviroatlas.epa.gov/enviroatlas/datafactsheets/pdf/ESN/PercentForestonWetAreas.pdf). The Mean Composite Topographic Index (CTI)[Wetness Index] were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

WRRI's Statewide Water Assessment is an effort that will complement existing state agency water resource assessments. It will provide new, dynamic (updated frequently), spatially representative assessments of water budgets for the entire state of New Mexico. Projects included in the Statewide Water Assessment bring new technologies that expand existing studies and are applicable statewide. Of particular interest are water budget components for which state agencies require improved information, such as evapotranspiration (ET), crop consumptive use, groundwater recharge, and streamflow.