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A multi-model approach was applied to reconstruct long-term flow records in 32 ungauged rivers developed with small diversion hydropower stations. Potential hydrologic alteration was assessed for flow records simulated by a catchment similarity model and the multi-criteria Streamflow Prediction under Extreme Data-scarcity (SPED) framework. Model validation based on limited observed data suggests that the SPED flow predictions are substantially more accurate than those generated by the catchment similarity model (NSE of 0.74 and 0.22, respectively and Correlation Coefficient of 0.87 and 0.72, respectively). Both flow prediction techniques indicated that flow signatures were altered substantially by diversion hydropower. Mean annual flows decreased by a mean of 76–86% across the 32 rivers and flow became more predictable in most rivers (47–94% mean increase in predictability). Frequency and duration of high flows decreased and duration of low flow events increased substantially. Slopes of rising hydrograph limbs and recession limbs increased respectively by a mean of 123–161% and 254–720%. While direction of detected flow alteration was similar regardless of model choice, severity of alteration was consistently greater based on the analysis of flows simulated by the multi-objective SPED model. Overall, the agreement of the multi-model analysis indicates that the signal of flow alteration by diversion hydropower in the study rivers supersedes uncertainty associated with flow prediction. While both models may be appropriate for applications such as change detection analysis, prescriptive management actions, such as establishing flow targets for environmental flow regimes, should be based on flow records generated by models adept at simulating rainfall-runoff processes targeted to individual basins, such as SPED. [ABSTRACT FROM AUTHOR]

Streamflow prediction in ungauged basins is necessary to support water resources management decisions. Herein we refine and evaluate the Streamflow Prediction under Extreme Data-scarcity (SPED) model, a framework designed for streamflow prediction within regions of sparse hydrometeorological observation. With the SPED framework, inclusion of soft data directs optimization to balance runoff efficiency with the selection of hydrologically representative parameters. Here SPED is tested in catchments around the world, including four well-gauged catchments, by mimicking data-scarcity and comparing against data-intensive approaches. By differentiating equifinal models, SPED succeeds where traditional approaches are likely to fail: partially dissimilar reference/target catchments. For instance, in a pair of reference/target catchments with different base flow regimes, SPED outperforms a model calibrated only to maximize efficiency (NSE of 0.54 versus 0.08). SPED performs consistently (NSE range: 0.54–0.74) across the diverse climatological and physiographic settings tested and proves comparable to state-of-the-science methods that use robust data networks. [ABSTRACT FROM AUTHOR]

To manage flood risk, floodplains are often designated for uses that support flood storage and ecosystem conservation. In such cases, direct human uses of flood-prone land are often restricted. Despite effectiveness at reducing flood risk, the exclusion of direct human uses from flood-prone lands is not always possible. Additionally, where livelihoods are tied to the use of flood-prone land, such strategies may eliminate floodplain-related benefits. To support implementation of Integrated Flood Management suited to such contexts, we propose a framework in which the livelihood benefits of direct floodplain use are distinguished from those supplied through ecosystem services. Decision-makers may apply this approach where flood risk, ecosystem, and livelihood objectives must be balanced. Because flood adaptation strategies may involve risk-benefit trade-offs, we propose the integrated assessment of flood risk and probabilistic benefits to inform decision-making. Through parallel analysis of probabilistic damages and benefits, a broad suite of management actions may be evaluated to minimize flood risk while maximizing river-derived benefits. Application of the proposed framework and risk-benefit analysis may highlight effective solutions that reflect the pressures and opportunities of developing countries. For instance, measures that reduce flood risk by targeting coping capacity and adaptation, as opposed to flood exposure, may be emphasized. [ABSTRACT FROM PUBLISHER]