Evidence-based indicator approach to guide environmental impact assessments of hydropower development

Global expansion of renewables, especially hydropower resources, has increased in recent years to meet the growing energy demands and fill worldwide gaps in the supply of electricity. Although expansion of hydropower has slowed in the US within the past four decades, existing hydropower capacity has an increasingly important role in electric power system reliability and resilience. However, hydropower induces significant environmental effects on river ecosystems – effects that are addressed through environmental impact assessment (EIA) processes that vary internationally. The need for effective EIA processes is increasing as environmental regulations are either stressed in developing countries undertaking rapid expansion of hydropower capacity or time- and resource-intensive in developed countries, like the United States. In response, many have suggested using basin-scale assessments or sustainability protocols (indicator approaches) to improve decision-making and ensure that best practices are employed during hydropower planning. However, EIAs still serve an important role in understanding the complex, local environmental effects of hydropower, which are the basis for designing mitigation strategies. To help address this gap, we developed an assemblage of tools that rely on a weight-of-evidence approach to determine the most relevant impacts of hydropower on primary components of the river ecosystem, as identified using river function indicators. A science-based questionnaire (SBQ) helps users identify which environmental indicators may be impacted during hydropower development as well as those indicators that have the highest levels of uncertainty. In situations where questions cannot be answered reliably, we also provide an environmental-envelope model (EEM) that predicts the likelihood of impacts to river functions based on attributes of hydropower facilities. The questionnaire, predictive model, and their outputs can assist stakeholders in identifying knowledge gaps and river functions that might require further investigation. Furthermore, we provide a river function linkage assessment tool (RFLAT), which translates the SBQ results into a network visualization of inter-dependent indicator relationships that may help formulate hypotheses about causal relationships that can be explored through environmental studies. We apply these spreadsheet-based tools to four existing hydropower projects and one hypothetical new hydropower project of varying sizes and environmental contexts. The prototype tools and visualizations described in this paper will be refined through stakeholder feedback and developed into a decision-support toolkit aimed at increasing the efficiency of the EIA processes that engender environmental studies but doing so without loss of rigor or transparency of rationale necessary for understanding, considering, and mitigating the environmental consequences of hydropower.