Standardized Siting and Risk Analysis Decision Support Mechanisms for Water-Intensive Industries

This paper focuses on water for cooling industrial energy generation loads and energy and water for cooling large process loads. A challenge is that siting any large facility with substantial water demands without understanding baseline conditions and assessing potential multi-sector impacts on local water resources and systems may pose adverse long-term operational, economic, reputational, environmental quality, and societal risks. For any water-intensive industrial facility, it is important to evaluate water source availability and variability under changing conditions such as drought and regional growth. Water quality parameters should be evaluated for both the suitability of the source for operations and potential risks from facility discharge. It is also important to map the demand portfolio within a watershed to understand who uses water, how much, when, and for what purposes. This includes characterizing municipal, agricultural, industrial, and environmental demands, plus emerging uses. Data centers are a prominent example of the need to assess siting water risk, as they often consume substantial amounts of potable water for cooling and create direct competition with municipal needs.

The near-term opportunity involves standardized risk analysis mechanisms, including a tool to inform siting for facilities with high water demand. The tool should be based on an appropriate geographic unit of analysis and integrate geospatial layers to highlight relevant metrics from watershed dynamics plus factors like municipal and agricultural water demand. Inputs could include specific physical water parameters on availability, quality, meteorological variables, water stress, capacity and energy intensity of water resource recovery facilities, other nearby facilities and cross-sector competition, and governing water rights. The use of artificial intelligence to fuse different data sources, run models in real-time, and optimize operations given water supply conditions and projected demand scenarios could provide a powerful capability to readily update the tool. This resource could create a sophisticated, scalable methodology to enable informed decisions on relevant water parameters. As a comprehensive water stress resource map, it would allow for the comparison of risks and opportunities across different potential locations using consistent metrics integrated with existing techno-economic optimization tool outputs. Utilities and municipalities could thus better plan for future supply and demand, while operators could better understand the impact of facilities' water use plus the benefits of conservation. It could transform disparate, difficult-to-apply data sources into an actionable, evidence-based system, which is critical for strategic long-term investment and planning. As another layer of the envisioned tool, additional capabilities supporting the management and operation of water-intensive facilities in accordance with regional water availability and demand are needed. Operational water management considering watershed conditions would minimize negative risks and impacts during operation.

Success measures include demonstrating a decision support tool that can assess the capacity of selected U.S. regions to support water-intensive facilities; successful engagement with water-intensive industry decision makers; website use metrics, dataset downloads, application programming interface (API) queries; and possible data center siting studies around cooling cost optimization (or sensitivity analyses) based on location and cooling technologies.