Evaluate Sequential Interventions for Adaptive Water Management in Large River Basins

Abstract Integrated River Basin Management (IRBM) and Adaptive Water Management (AWM) have been widely promoted as guiding principles, yet their practical realization at the basin scale remains difficult and underutilized. Sequential Interventions (SIs), stepwise actions applied in a predefined sequence at designated decision points, offer a practical and adaptive approach to implementing AWM. Such methods embody the iterative, learning‐by‐doing principles central to AWM, allowing strategies to evolve in response to monitoring results and changing conditions. This study develops a retrospective evaluation framework grounded in AWM, using an Integrated Hydrologic–Ecologic–Economic Model (IHEEM). The AWM‐grounded framework is employed to evaluate the effectiveness and relationships of SIs for the Yellow River Basin (YRB). The YRB is one of the world's most intensively managed basins, and SIs have been implemented in the basin since the 1980s, including major policies and infrastructure projects. The results show that SIs produce synergistic effects, progressively balancing upstream–downstream and human–nature water demands, enhancing environmental flows, and improving water‐use efficiency. In particular, the engineering intervention, that is, the Xiaolangdi Reservoir (XLD), plays a complementary role to policy interventions in maintaining downstream flows and sediment flushing. These findings illustrate how adaptive management, through iterative, evidence‐based interventions, can strengthen resilience in complex socio‐hydrological systems, and provide insights for advancing IRBM and AWM in large river basins globally with increasing hydrological and socio‐economic pressures.

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Journal
Water Resources Research
Published
2026-04-30
DOI
https://doi.org/10.1029/2025wr042451
Primary Topic
Water resources management and optimization
Type
article
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article

Evaluate Sequential Interventions for Adaptive Water Management in Large River Basins

Tingju Zhu, Yuhan Yan, Ximing Cai, Zhenxing Zhang
Water Resources Research
Water resources management and optimization
article

Evaluate Sequential Interventions for Adaptive Water Management in Large River Basins

Tingju Zhu, Yuhan Yan, Ximing Cai, Zhenxing Zhang
article en

Abstract

Abstract Integrated River Basin Management (IRBM) and Adaptive Water Management (AWM) have been widely promoted as guiding principles, yet their practical realization at the basin scale remains difficult and underutilized. Sequential Interventions (SIs), stepwise actions applied in a predefined sequence at designated decision points, offer a practical and adaptive approach to implementing AWM. Such methods embody the iterative, learning‐by‐doing principles central to AWM, allowing strategies to evolve in response to monitoring results and changing conditions. This study develops a retrospective evaluation framework grounded in AWM, using an Integrated Hydrologic–Ecologic–Economic Model (IHEEM). The AWM‐grounded framework is employed to evaluate the effectiveness and relationships of SIs for the Yellow River Basin (YRB). The YRB is one of the world's most intensively managed basins, and SIs have been implemented in the basin since the 1980s, including major policies and infrastructure projects. The results show that SIs produce synergistic effects, progressively balancing upstream–downstream and human–nature water demands, enhancing environmental flows, and improving water‐use efficiency. In particular, the engineering intervention, that is, the Xiaolangdi Reservoir (XLD), plays a complementary role to policy interventions in maintaining downstream flows and sediment flushing. These findings illustrate how adaptive management, through iterative, evidence‐based interventions, can strengthen resilience in complex socio‐hydrological systems, and provide insights for advancing IRBM and AWM in large river basins globally with increasing hydrological and socio‐economic pressures.

Water Resources ResearchVol. 62(5)
University of Illinois Urbana-Champaign (US), Illinois Archaeological Survey (US), Zhejiang University-University of Edinburgh Institute (CN), Zhejiang University (CN)
Openalex Percentile: Top 10%
Water resources management and optimization
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Evaluate Sequential Interventions for Adaptive Water Management in Large River Basins — Tingju Zhu, Yuhan Yan, et al. · Water Resources Research (2026) | TGRS Research Map | TGRS