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<p>This study develops a system-dynamics-based Shared Vision Model (SVM), a core tool of Shared Vision Planning, for the Yeong–Seom Basin in South Korea, which experienced consecutive extreme droughts in 2022–2023, and applies it to quantify drought coping capacity at the medium-scale watershed level. The SVM integrates multipurpose dams, agricultural reservoirs, intake facilities, and streamflow gauging stations while reproducing operational rules such as water-supply adjustment standards and coordinated drought operations. Validation against 2022–2023 observations showed high reproducibility for most dams (R² = 0.93–0.99; NSE = 0.80–0.99). Although Boseonggang and Sueo Dams initially showed low performance, accuracy improved markedly after incorporating additional releases associated with coordinated drought operations, with corresponding improvements at downstream gauging stations confirming basin-wide flow continuity. Drought coping capacity was evaluated using 30 annual inflow ensemble scenarios derived from a 1995–2024 meteorological ensemble. Frequency–Duration–Magnitude indicators were calculated by drought stage and aggregated into a dimensionless coping-capacity index. The 2005 climate-outlook scenario produced the most severe basin-wide impacts overall, although other years were selected for specific watersheds and indicators. Under this scenario, supplier-based and consumer-based coping capacities differed systematically, especially where supply and demand locations were spatially separated. A ± 20% threshold sensitivity analysis showed that absolute DCC values varied with threshold assumptions, but the representative worst-case scenario, major vulnerable watersheds, and supplier–consumer contrasts remained broadly consistent. Countermeasure simulations demonstrated downstream protection effects, including improvement in the lower Seomjin watershed, supporting collaborative, scenario-based drought-risk evaluation using shared indicators and a common basin model.</p>

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A Shared Vision Model-Based Framework for Assessing Drought Coping Capacity in a Multi-Infrastructure Basin

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月29日

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  • Joohyung Lee,
  • Young-Oh Kim

摘要

This study develops a system-dynamics-based Shared Vision Model (SVM), a core tool of Shared Vision Planning, for the Yeong–Seom Basin in South Korea, which experienced consecutive extreme droughts in 2022–2023, and applies it to quantify drought coping capacity at the medium-scale watershed level. The SVM integrates multipurpose dams, agricultural reservoirs, intake facilities, and streamflow gauging stations while reproducing operational rules such as water-supply adjustment standards and coordinated drought operations. Validation against 2022–2023 observations showed high reproducibility for most dams (R² = 0.93–0.99; NSE = 0.80–0.99). Although Boseonggang and Sueo Dams initially showed low performance, accuracy improved markedly after incorporating additional releases associated with coordinated drought operations, with corresponding improvements at downstream gauging stations confirming basin-wide flow continuity. Drought coping capacity was evaluated using 30 annual inflow ensemble scenarios derived from a 1995–2024 meteorological ensemble. Frequency–Duration–Magnitude indicators were calculated by drought stage and aggregated into a dimensionless coping-capacity index. The 2005 climate-outlook scenario produced the most severe basin-wide impacts overall, although other years were selected for specific watersheds and indicators. Under this scenario, supplier-based and consumer-based coping capacities differed systematically, especially where supply and demand locations were spatially separated. A ± 20% threshold sensitivity analysis showed that absolute DCC values varied with threshold assumptions, but the representative worst-case scenario, major vulnerable watersheds, and supplier–consumer contrasts remained broadly consistent. Countermeasure simulations demonstrated downstream protection effects, including improvement in the lower Seomjin watershed, supporting collaborative, scenario-based drought-risk evaluation using shared indicators and a common basin model.