Geomorphic imprint of high-mountain floods: insights from the 2022 hydrological extreme across the upper Indus River catchment in the northwestern Himalayas

Abstract. The interaction of tectonics, surface processes, and climate extremes impacts how the landscape responds to extreme hydrological events. In 2022, an anomalous precipitation event occurred during the monsoon season along the lower–middle reaches of the upper Indus River, resulting in short-lived high-magnitude flooding and socioeconomic disruption downstream. To understand the spatial relationship between the geomorphic response and climatic controls of this flood event, as well as their primary triggers, we performed a landscape analysis using topographic metrics and quantified the causal association between hydroclimatic variables. Temperature anomalies in upstream glaciated subcatchments had a considerable impact on snow cover distribution, based on our observations. As snow cover changed, glacial-melt runoff rose, contributing to increased fluvial stream power after traversing higher-order reaches. The higher-order reaches of the upper Indus River received an anomalously high amount of precipitation, which, when combined with substantial glacial-melt discharge, contributed to an extreme flood across the high-relief, steep-gradient channels. The flood-affected regions had high mean basin ksn (normalized steepness index) values and stream length–gradient (SL) index values, with numerous spikes in their magnitudes along their channel profiles downstream. To determine how the lower–middle reaches of the upper Indus River responded to this flood event, we employed the enhanced vegetation index (EVI) and the normalized difference water index (NDWI) as change indicator metrics. We observed an inverse causal influence of the NDWI on the EVI and a statistically significant relationship between anomalous stream power and the relative EVI, suggesting that the downstream channel morphology changed rapidly during this episodic event and highlighting the EVI as a useful indicator of geomorphic change. We suggest that this extreme flood event resulted from the interaction of anomalous glacial melt and anomalous precipitation over a high-relief landscape, with a certain causal connection to anomalous temperature observed over the event duration. The synoptic observations suggest that this meteorological condition involves the interaction of the Indian summer monsoon (ISM) and western-disturbance (WD) moisture fluxes. However, the geomorphic consequences of such anomalous monsoon periods, as well as their influence on long-term landscape change, are still unclear.

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Publication Details

Journal
Earth Surface Dynamics
Published
2025-02-07
DOI
https://doi.org/10.5194/esurf-13-147-2025
Citations
2
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
2.60
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article

Geomorphic imprint of high-mountain floods: insights from the 2022 hydrological extreme across the upper Indus River catchment in the northwestern Himalayas

Mukunda Dev Behera, Kristen Cook, Abhishek Kashyap
2 citations
Earth Surface Dynamics
Cryospheric studies and observations
2.60
article

Geomorphic imprint of high-mountain floods: insights from the 2022 hydrological extreme across the upper Indus River catchment in the northwestern Himalayas

Mukunda Dev Behera, Kristen Cook, Abhishek Kashyap
article en
2 citations

Abstract

Abstract. The interaction of tectonics, surface processes, and climate extremes impacts how the landscape responds to extreme hydrological events. In 2022, an anomalous precipitation event occurred during the monsoon season along the lower–middle reaches of the upper Indus River, resulting in short-lived high-magnitude flooding and socioeconomic disruption downstream. To understand the spatial relationship between the geomorphic response and climatic controls of this flood event, as well as their primary triggers, we performed a landscape analysis using topographic metrics and quantified the causal association between hydroclimatic variables. Temperature anomalies in upstream glaciated subcatchments had a considerable impact on snow cover distribution, based on our observations. As snow cover changed, glacial-melt runoff rose, contributing to increased fluvial stream power after traversing higher-order reaches. The higher-order reaches of the upper Indus River received an anomalously high amount of precipitation, which, when combined with substantial glacial-melt discharge, contributed to an extreme flood across the high-relief, steep-gradient channels. The flood-affected regions had high mean basin ksn (normalized steepness index) values and stream length–gradient (SL) index values, with numerous spikes in their magnitudes along their channel profiles downstream. To determine how the lower–middle reaches of the upper Indus River responded to this flood event, we employed the enhanced vegetation index (EVI) and the normalized difference water index (NDWI) as change indicator metrics. We observed an inverse causal influence of the NDWI on the EVI and a statistically significant relationship between anomalous stream power and the relative EVI, suggesting that the downstream channel morphology changed rapidly during this episodic event and highlighting the EVI as a useful indicator of geomorphic change. We suggest that this extreme flood event resulted from the interaction of anomalous glacial melt and anomalous precipitation over a high-relief landscape, with a certain causal connection to anomalous temperature observed over the event duration. The synoptic observations suggest that this meteorological condition involves the interaction of the Indian summer monsoon (ISM) and western-disturbance (WD) moisture fluxes. However, the geomorphic consequences of such anomalous monsoon periods, as well as their influence on long-term landscape change, are still unclear.

Earth Surface DynamicsVol. 13(1)
Indian Institute of Technology Kharagpur (IN), Institut des Sciences de la Terre (FR), Université Gustave Eiffel (FR), Institut de Recherche pour le Développement (FR), Université Grenoble Alpes (FR)
Openalex Percentile: Top 14%
Cryospheric studies and observations
2.60
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