Nationwide water availability data for energy-water modeling

The purpose of this effort is to explore where the availability of water could be a limiting factor in the siting of new electric power generation. To support this analysis, water availability is mapped at the county level for the conterminous United States (3109 counties). Five water sources are individually considered, including unappropriated surface water, unappropriated groundwater, appropriated water (western U.S. only), municipal wastewater and brackish groundwater. Also mapped is projected growth in non-thermoelectric consumptive water demand to 2035. Finally, the water availability metrics are accompanied by estimated costs associated with utilizing that particular supply of water. Ultimately these data sets are being developed for use in the National Renewable Energy Laboratories' (NREL) Regional Energy Deployment System (ReEDS) model, designed to investigate the likely deployment of new energy installations in the U.S., subject to a number of constraints, particularly water

Energy-water analysis of the 10-year WECC transmission planning study cases.

In 2011 the Department of Energy's Office of Electricity embarked on a comprehensive program to assist our Nation's three primary electric interconnections with long term transmission planning. Given the growing concern over water resources in the western U.S. the Western Electricity Coordinating Council (WECC) requested assistance with integrating water resource considerations into their broader electric transmission planning. The result is a project with three overarching objectives: (1) Develop an integrated Energy-Water Decision Support System (DSS) that will enable planners in the Western Interconnection to analyze the potential implications of water stress for transmission and resource planning. (2) Pursue the formulation and development of the Energy-Water DSS through a strongly collaborative process between the Western Electricity Coordinating Council (WECC), Western Governors Association (WGA), the Western States Water Council (WSWC) and their associated stakeholder teams. (3) Exercise the Energy-Water DSS to investigate water stress implications of the transmission planning scenarios put forward by WECC, WGA, and WSWC. The foundation for the Energy-Water DSS is Sandia National Laboratories Energy-Power-Water Simulation (EPWSim) model (Tidwell et al. 2009). The modeling framework targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. This framework provides an interactive environment to explore trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., state, county, watershed, interconnection). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. The framework currently supports modules for calculating water withdrawal and consumption for current and planned electric power generation; projected water demand from competing use sectors; and, surface and groundwater availability. WECC's long range planning is organized according to two target planning horizons, a 10-year and a 20-year. This study supports WECC in the 10-year planning endeavor. In this case the water implications associated with four of WECC's alternative future study cases (described below) are calculated and reported. In future phases of planning we will work with WECC to craft study cases that aim to reduce the thermoelectric footprint of the interconnection and/or limit production in the most water stressed regions of the West

Merging spatially variant physical process models under an optimized systems dynamics framework.

The complexity of water resource issues, its interconnectedness to other systems, and the involvement of competing stakeholders often overwhelm decision-makers and inhibit the creation of clear management strategies. While a range of modeling tools and procedures exist to address these problems, they tend to be case specific and generally emphasize either a quantitative and overly analytic approach or present a qualitative dialogue-based approach lacking the ability to fully explore consequences of different policy decisions. The integration of these two approaches is needed to drive toward final decisions and engender effective outcomes. Given these limitations, the Computer Assisted Dispute Resolution system (CADRe) was developed to aid in stakeholder inclusive resource planning. This modeling and negotiation system uniquely addresses resource concerns by developing a spatially varying system dynamics model as well as innovative global optimization search techniques to maximize outcomes from participatory dialogues. Ultimately, the core system architecture of CADRe also serves as the cornerstone upon which key scientific innovation and challenges can be addressed

Designing a water leasing market for the Mimbres River, New Mexico.

The objective of this study is to develop a conceptual framework for establishing water leasing markets in New Mexico using the Mimbres River as a test case. Given the past and growing stress over water in New Mexico and the Mimbres River in particular, this work will develop a mechanism for the short term, efficient, temporary transfer of water from one user to another while avoiding adverse effects on any user not directly involved in the transaction (i.e., third party effects). Toward establishing a water leasing market, five basic tasks were performed, (1) a series of stakeholder meetings were conducted to identify and address concerns and interests of basin residents, (2) several gauges were installed on irrigation ditches to aid in the monitoring and management of water resources in the basin, (3) the hydrologic/market model and decision support interface was extended to include the Middle and Lower reaches of the Mimbres River, (4) experiments were conducted to aid in design of the water leasing market, and (5) a set of rules governing a water leasing market was drafted for future adoption by basin residents and the New Mexico Office of the State Engineer

Monitoring stream stage, channel profile, and aqueous conductivity with time domain reflectometry (TDR).

Time domain reflectometry (TDR) operates by propagating a radar frequency electromagnetic pulse down a transmission line while monitoring the reflected signal. As the electromagnetic pulse propagates along the transmission line, it is subject to impedance by the dielectric properties of the media along the transmission line (e.g., air, water, sediment), reflection at dielectric discontinuities (e.g., air-water or water-sediment interface), and attenuation by electrically conductive materials (e.g., salts, clays). Taken together, these characteristics provide a basis for integrated stream monitoring; specifically, concurrent measurement of stream stage, channel profile and aqueous conductivity. Here, we make novel application of TDR within the context of stream monitoring. Efforts toward this goal followed three critical phases. First, a means of extracting the desired stream parameters from measured TDR traces was required. Analysis was complicated by the fact that interface location and aqueous conductivity vary concurrently and multiple interfaces may be present at any time. For this reason a physically based multisection model employing the S11 scatter function and Cole-Cole parameters for dielectric dispersion and loss was developed to analyze acquired TDR traces. Second, we explored the capability of this multisection modeling approach for interpreting TDR data acquired from complex environments, such as encountered in stream monitoring. A series of laboratory tank experiments were performed in which the depth of water, depth of sediment, and conductivity were varied systematically. Comparisons between modeled and independently measured data indicate that TDR measurements can be made with an accuracy of {+-}3.4x10{sup -3} m for sensing the location of an air/water or water/sediment interface and {+-}7.4% of actual for the aqueous conductivity. Third, monitoring stations were sited on the Rio Grande and Paria rivers to evaluate performance of the TDR system under normal field conditions. At the Rio Grande site (near Central Bridge in Albuquerque, New Mexico) continuous monitoring of stream stage and aqueous conductivity was performed for 6 months. Additionally, channel profile measurements were acquired at 7 locations across the river. At the Paria site (near Lee's Ferry, Arizona) stream stage and aqueous conductivity data were collected over a 4-month period. Comparisons drawn between our TDR measurements and USGS gage data indicate that the stream stage is accurate within {+-}0.88 cm, conductivity is accurate within {+-}11% of actual, and channel profile measurements agree within {+-}1.2 cm

Decision insight into stakeholder conflict for ERN.

Participatory modeling has become an important tool in facilitating resource decision making and dispute resolution. Approaches to modeling that are commonly used in this context often do not adequately account for important human factors. Current techniques provide insights into how certain human activities and variables affect resource outcomes; however, they do not directly simulate the complex variables that shape how, why, and under what conditions different human agents behave in ways that affect resources and human interactions related to them. Current approaches also do not adequately reveal how the effects of individual decisions scale up to have systemic level effects in complex resource systems. This lack of integration prevents the development of more robust models to support decision making and dispute resolution processes. Development of integrated tools is further hampered by the fact that collection of primary data for decision-making modeling is costly and time consuming. This project seeks to develop a new approach to resource modeling that incorporates both technical and behavioral modeling techniques into a single decision-making architecture. The modeling platform is enhanced by use of traditional and advanced processes and tools for expedited data capture. Specific objectives of the project are: (1) Develop a proof of concept for a new technical approach to resource modeling that combines the computational techniques of system dynamics and agent based modeling, (2) Develop an iterative, participatory modeling process supported with traditional and advance data capture techniques that may be utilized to facilitate decision making, dispute resolution, and collaborative learning processes, and (3) Examine potential applications of this technology and process. The development of this decision support architecture included both the engineering of the technology and the development of a participatory method to build and apply the technology. Stakeholder interaction with the model and associated data capture was facilitated through two very different modes of engagement, one a standard interface involving radio buttons, slider bars, graphs and plots, while the other utilized an immersive serious gaming interface. The decision support architecture developed through this project was piloted in the Middle Rio Grande Basin to examine how these tools might be utilized to promote enhanced understanding and decision-making in the context of complex water resource management issues. Potential applications of this architecture and its capacity to lead to enhanced understanding and decision-making was assessed through qualitative interviews with study participants who represented key stakeholders in the basin

Use of a dynamic simulation model to understand nitrogen cycling in the middle Rio Grande, NM.

Water quality often limits the potential uses of scarce water resources in semiarid and arid regions. To best manage water quality one must understand the sources and sinks of both solutes and water to the river system. Nutrient concentration patterns can identify source and sink locations, but cannot always determine biotic processes that affect nutrient concentrations. Modeling tools can provide insight into these large-scale processes. To address questions about large-scale nitrogen removal in the Middle Rio Grande, NM, we created a system dynamics nitrate model using an existing integrated surface water--groundwater model of the region to evaluate our conceptual models of uptake and denitrification as potential nitrate removal mechanisms. We modeled denitrification in groundwater as a first-order process dependent only on concentration and used a 5% denitrification rate. Uptake was assumed to be proportional to transpiration and was modeled as a percentage of the evapotranspiration calculated within the model multiplied by the nitrate concentration in the water being transpired. We modeled riparian uptake as 90% and agricultural uptake as 50% of the respective evapotranspiration rates. Using these removal rates, our model results suggest that riparian uptake, agricultural uptake and denitrification in groundwater are all needed to produce the observed nitrate concentrations in the groundwater, conveyance channels, and river as well as the seasonal concentration patterns. The model results indicate that a total of 497 metric tons of nitrate-N are removed from the Middle Rio Grande annually. Where river nitrate concentrations are low and there are no large nitrate sources, nitrate behaves nearly conservatively and riparian and agricultural uptake are the most important removal mechanisms. Downstream of a large wastewater nitrate source, denitrification and agricultural uptake were responsible for approximately 90% of the nitrogen removal

Modeling the transfer of land and water from agricultural to urban uses in the Middle Rio Grande Basin, New Mexico.

Social and ecological scientists emphasize that effective natural resource management depends in part on understanding the dynamic relationship between the physical and non-physical process associated with resource consumption. In this case, the physical processes include hydrological, climatological and ecological dynamics, and the non-physical process include social, economic and cultural dynamics among humans who do the resource consumption. This project represents a case study aimed at modeling coupled social and physical processes in a single decision support system. In central New Mexico, individual land use decisions over the past five decades have resulted in the gradual transformation of the Middle Rio Grande Valley from a primarily rural agricultural landscape to a largely urban one. In the arid southwestern U.S., the aggregate impact of individual decisions about land use is uniquely important to understand, because scarce hydrological resources will likely limit the viability of resulting growth and development trajectories. This decision support tool is intended to help planners in the area look forward in their efforts to create a collectively defined 'desired' social landscape in the Middle Rio Grande. Our research question explored the ways in which socio-cultural values impact decisions regarding that landscape and associated land use. Because of the constraints hydrological resources place on land use, we first assumed that water use, as embodied in water rights, was a reasonable surrogate for land use. We thought that modeling the movement of water rights over time and across water source types (surface and ground) would provide planners with insight into the possibilities for certain types of decisions regarding social landscapes, and the impact those same decisions would have on those landscapes. We found that water rights transfer data in New Mexico is too incomplete and inaccurate to use as the basis for the model. Furthermore, because of its lack of accuracy and completeness, water rights ownership was a poor indicator of water and land usage habits and patterns. We also found that commitment among users in the Middle Rio Grande Valley is to an agricultural lifestyle, not to a community or place. This commitment is conditioned primarily by generational cohort and past experience. If conditions warrant, many would be willing to practice the lifestyle elsewhere. A related finding was that sometimes the pressure to sell was not the putative price of the land, but the taxes on the land. These taxes were, in turn, a function of the level of urbanization of the neighborhood. This urbanization impacted the quality of the agricultural lifestyle. The project also yielded some valuable lessons regarding the model development process. A facilitative and collaborative style (rather than a top-down, directive style) was most productive with the inter-disciplinary , inter-institutional team that worked on the project. This allowed for the emergence of a process model which combined small, discipline- and/or task-specific subgroups with larger, integrating team meetings. The project objective was to develop a model that could be used to run test scenarios in which we explored the potential impact of different policy options. We achieved that objective, although not with the level of success or modeling fidelity which we had hoped for. This report only describes very superficially the results of test scenarios, since more complete analysis of scenarios would require more time and effort. Our greatest obstacle in the successful completion of the project was that required data were sparse, of poor quality, or completely nonexistent. Moreover, we found no similar modeling or research efforts taking place at either the state or local level. This leads to a key finding of this project: that state and local policy decisions regarding land use, development, urbanization, and water resource allocation are being made with minimal data and without the benefit of economic or social policy analysis

Risk assessment of climate systems for national security.

Climate change, through drought, flooding, storms, heat waves, and melting Arctic ice, affects the production and flow of resource within and among geographical regions. The interactions among governments, populations, and sectors of the economy require integrated assessment based on risk, through uncertainty quantification (UQ). This project evaluated the capabilities with Sandia National Laboratories to perform such integrated analyses, as they relate to (inter)national security. The combining of the UQ results from climate models with hydrological and economic/infrastructure impact modeling appears to offer the best capability for national security risk assessments