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<p>Flooding represents a significant risk within the Red River Delta (RRD) of Vietnam, where accelerated urbanization and agricultural expansion have amplified hydrological vulnerabilities. In contrast to earlier models that fail to account for the diversity of land use in flood evaluations, this research meticulously analyzed flood sensitivity in both urban and agricultural settings through the utilization of the Artificial Bee Colony-Adaptive Neuro Fuzzy Inference System (ABC-ANFIS) model in conjunction with Sentinel-2 imagery, while classifying land use utilizing the U-shaped Network (U-Net). To overcome this challenge, a dual-model framework was established, comprising ABC–ANFIS 1 for construction locales and ABC–ANFIS 2 for agricultural territories, facilitating distinct analyses of the flood sensitivity formation mechanisms across the two land use cover types (LULC). This methodology not only enhanced the predictive capabilities of the model through the ABC algorithm but also allowed for the precise identification of variances in flood causative factors between construction and agricultural zones. The model’s outputs exhibited exceptional performance (R²<sub>train</sub> = 0.86), identifying precipitation as the predominant influencing variable (R² = 0.46 for construction development; 0.44 for agricultural activities); while slope and proximity to water bodies demonstrated effects contingent upon land use type. Regions with heightened sensitivity are principally located in coastal provinces such as Nam Dinh and Thai Binh; in urban settings, areas of concern are primarily in central Hanoi and Hai Phong, while in agricultural zones, heightened sensitivity is observed along significant waterways like the Red River and Thai Binh River. The spatial configuration of the sensitivity map illustrated distinct differences between urban zones (characterized by clearly delineated flood boundaries influenced by infrastructure) and agricultural regions (exhibiting a more diffuse distribution shaped by topographical and hydrological factors). This methodology provided critical scientific insights for land use planning and flood management tailored to climate change in the RRD region.</p>

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Research on the Impact of Flood Sensitivity on Urban and Agricultural Areas in Low-lying and Flat Terrain: Effects on the Resilience and Recovery Capacity of the Red River Delta

  • 期刊论文

  • 发表日期：

    2026年4月3日

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  • Anh Ngoc Thi Do,
  • Tuyet Anh Thi Do,
  • The Van Pham,
  • Bui Thi Phuong Thuy,
  • Quyen Vu Thi

摘要

Flooding represents a significant risk within the Red River Delta (RRD) of Vietnam, where accelerated urbanization and agricultural expansion have amplified hydrological vulnerabilities. In contrast to earlier models that fail to account for the diversity of land use in flood evaluations, this research meticulously analyzed flood sensitivity in both urban and agricultural settings through the utilization of the Artificial Bee Colony-Adaptive Neuro Fuzzy Inference System (ABC-ANFIS) model in conjunction with Sentinel-2 imagery, while classifying land use utilizing the U-shaped Network (U-Net). To overcome this challenge, a dual-model framework was established, comprising ABC–ANFIS 1 for construction locales and ABC–ANFIS 2 for agricultural territories, facilitating distinct analyses of the flood sensitivity formation mechanisms across the two land use cover types (LULC). This methodology not only enhanced the predictive capabilities of the model through the ABC algorithm but also allowed for the precise identification of variances in flood causative factors between construction and agricultural zones. The model’s outputs exhibited exceptional performance (R²train = 0.86), identifying precipitation as the predominant influencing variable (R² = 0.46 for construction development; 0.44 for agricultural activities); while slope and proximity to water bodies demonstrated effects contingent upon land use type. Regions with heightened sensitivity are principally located in coastal provinces such as Nam Dinh and Thai Binh; in urban settings, areas of concern are primarily in central Hanoi and Hai Phong, while in agricultural zones, heightened sensitivity is observed along significant waterways like the Red River and Thai Binh River. The spatial configuration of the sensitivity map illustrated distinct differences between urban zones (characterized by clearly delineated flood boundaries influenced by infrastructure) and agricultural regions (exhibiting a more diffuse distribution shaped by topographical and hydrological factors). This methodology provided critical scientific insights for land use planning and flood management tailored to climate change in the RRD region.