Integrating multi-model frameworks to unravel the spatiotemporal dynamics of flash floods in the Tianshan Mountain, China

• Integrated long - term flash flood and environmental data for spatial analysis and modeling. • Used multi - model coupling to identify change mechanisms across CTM subregions. • Found accelerated post - 1995 flood risks due to extreme precipitation under climate change. • Identified flood mechanisms: terrain - driven rainstorms (ETM), landscape diversity and dams (NSTM), intensified precipitation (SSTM). The Tianshan Mountain in China (CTM), a critical water resource and climate change hotspot in Central Asia, faces escalating flash flood events due to global climate change and intensified human activities. This study applied the Geodetector (GD) to select driving factors with spatiotemporal variability of flash floods in the CTM from 1975 to 2015. The filtered drivers were integrated with historical flash flood data using the Geographically and Temporally Weighted Regression model (GTWR) to explore the spatiotemporal heterogeneity of the driving effects. Subsequently, the Partial Least Squares Structural Equation (PLS-SEM) was used to explore the direct and indirect influence pathways among driving factors. The analysis revealed a fluctuating upward trend in flash floods, accelerating after 1995 and showing different trends in various subregions after 2010. By the early 21st century, a symmetrical north–south distribution pattern emerged, with extreme precipitation events as the key driver. Terrain rainstorms were the main trigger in the eastern Tianshan Mountains (ETM), while landscape diversity, reduced snowmelt, and artificial flood control mitigated floods in the northern Tianshan Mountains (NSTM). The southern Tianshan Mountains (SSTM) experienced significant flood changes due to abundant precipitation. This study constructs a comprehensive analytical framework for investigating flash flood changes in the CTM by integrating GD, GTWR, and PLS-SEM models and proposes flash flood management strategies based on the identified mechanisms in different subzones.

Authors

Institutions

Publication Details

Journal
Ecological Indicators
Published
2025-02-26
DOI
https://doi.org/10.1016/j.ecolind.2025.113259
Citations
2
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
2.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating multi-model frameworks to unravel the spatiotemporal dynamics of flash floods in the Tianshan Mountain, China

Haiyan Fang, Guotao Zhang, Shufang Wu, Kadambot H. M. Siddique et al.
2 citations
Ecological Indicators
Flood Risk Assessment and Management
2.21
article

Integrating multi-model frameworks to unravel the spatiotemporal dynamics of flash floods in the Tianshan Mountain, China

Haiyan Fang, Guotao Zhang, Shufang Wu, Kadambot H. M. Siddique, Songqing Li, Biao Zhang
article en
2 citations

Abstract

• Integrated long - term flash flood and environmental data for spatial analysis and modeling. • Used multi - model coupling to identify change mechanisms across CTM subregions. • Found accelerated post - 1995 flood risks due to extreme precipitation under climate change. • Identified flood mechanisms: terrain - driven rainstorms (ETM), landscape diversity and dams (NSTM), intensified precipitation (SSTM). The Tianshan Mountain in China (CTM), a critical water resource and climate change hotspot in Central Asia, faces escalating flash flood events due to global climate change and intensified human activities. This study applied the Geodetector (GD) to select driving factors with spatiotemporal variability of flash floods in the CTM from 1975 to 2015. The filtered drivers were integrated with historical flash flood data using the Geographically and Temporally Weighted Regression model (GTWR) to explore the spatiotemporal heterogeneity of the driving effects. Subsequently, the Partial Least Squares Structural Equation (PLS-SEM) was used to explore the direct and indirect influence pathways among driving factors. The analysis revealed a fluctuating upward trend in flash floods, accelerating after 1995 and showing different trends in various subregions after 2010. By the early 21st century, a symmetrical north–south distribution pattern emerged, with extreme precipitation events as the key driver. Terrain rainstorms were the main trigger in the eastern Tianshan Mountains (ETM), while landscape diversity, reduced snowmelt, and artificial flood control mitigated floods in the northern Tianshan Mountains (NSTM). The southern Tianshan Mountains (SSTM) experienced significant flood changes due to abundant precipitation. This study constructs a comprehensive analytical framework for investigating flash flood changes in the CTM by integrating GD, GTWR, and PLS-SEM models and proposes flash flood management strategies based on the identified mechanisms in different subzones.

Ecological IndicatorsVol. 172
The University of Western Australia (AU), Chinese Academy of Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN), Northwest A&F University (CN)
Climate action
Openalex Percentile: Top 15%
Flood Risk Assessment and Management
2.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.