Reduction of ice masses concerning global warming is significantly changing geomorphology in high mountains. Formation of supraglacial lakes is one of such essential indications. Therefore, in the ...present study, we attempted to understand regional morphodynamics of supraglacial lakes, distributed in 17 glaciers within the Everest Himalaya. An average of 0.08 km2/yr lake expansion rate was noticed during the studied year. Decadal (2010–2019) lake morphodynamic study using high resolution satellite images revealed that only 161 out of total 2424 lakes were static, and mostly concentrated at the lower part of the ablation area with an alarming rate of surface area increase. We also found appearance of new cluster of lakes at higher elevations. We collected here statistical evidences of regional morphodynamics and key controlling factors to stabilize lakes. The parameters, viz., spatio-temporal distribution of lakes, their domain wise variation, multi-temporal (Seasonal to long-term) changes, lake density, and stability index were estimated and mapped. Finally, we concluded that new lake formations at higher elevation were triggered by gradual increase in temperature, decrease in glacier surface velocity, slope and ice thickness. The feature selection techniques indicated ice thickness as prior controlling factor followed by the surface velocity and slope to stabilize lakes at the lower part of ablation.
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•Higher resolution GeoEye images were used for the supraglacial lake dynamics study.•The constant and coalensing of supraglacial lakes were concentrated at the lower part of the ablation area.•Supraglacial lake dynamics were correlated with the glacier change.•Constant supraglacial lake and its change were monitored using feature selection techniques.
Glacial lakes are critical zones for future flooding and events such as glacial lake outburst floods, a threat to infrastructures and human life. A recent catastrophe (Chamoli flash flood) indicates ...its complex nature. Therefore, cross-linking of lake formation processes is essential. Our study describes the probability of glacial lake formation on a pixel basis for the Himalayan glaciers using logistic regression. Here, we used three causative factors, viz., climate, glacial and topographic, to determine how a future trigger of climate changes may affect the glacial and topographic parameters, which may generate new lakes. A total of 10,056 Himalayan glaciers were considered here for glacial lake formation probability mapping. Logistic regression analysis exhibits that precipitation, surface texture, slope, plan curvature, temperature and profile curvature yielded maximum weightage accordingly towards lake formation probability with an accuracy of 79% in receiver operating characteristics curve (ROC). In our results, central Himalayan glaciers were found to be more prone to lake formation, with 5.73% of pixels coming under a higher probability zone (>0.8 probability), followed by eastern (4.45%) and western (1.82%) parts. The lower part of the clean glacier and the higher part of the ablation area for highly debris-covered glacier gave a higher probability of lake formation. In the case of medium debris-covered glaciers, the lake formation probability decreases with an increase in distance from the end of the ablation area.
Research Highlights
Glaciers in the central Himalayas are more prone to glacial lake formation than other regions.
We used logistic regression techniques for the glacial lake formation mapping.
We formed a model for lake formation probability by taking some controlling parameters.
A comprehensive analysis of long-term water level trends is essential for freshwater sustainability. Given that Odisha heavily relies on agriculture, the monitoring and management of groundwater and ...its fluctuations are imperative for ensuring future sustainability in the state. Here, we analyzed the trend in Groundwater using water level data for a 30-year period (1990–2020) for the entire Odisha region. Moreover, to determine the long term variability, critical zones of future groundwater variability and controlling parameters of the water level change, we used spatio-temporal water level data of 746 locations. Water level rise of coastal districts during post-monsoon (POM), corresponds to the intensity of rainfall received, thus rising, however other districts of Odisha, showing decline in water level during the same season is due to shortage of rainfall, increase in population at a sudden, and over pumping due to industrial activities. Similarly, during pre-monsoon (PRM), water level shows an increasing trend in hard rock terrain of Odisha implying rabi crop irrigation, high density drainage network and lesser population density. Feature selection techniques were used in this study to know the parameters controlling most to this water level fluctuation in the entire Odisha state. Precipitation followed by landuse & landcover, lithology and population density are controlling the most for the long term water level change. Drainage, elevation, lithology and slope are positively related to the water level change while others are negatively related. It is also inferred that the districts like Mayurbhanj, Sundargarh, Keonjhar, Kandhamal, Boudh, Dhenkanal, Gajapati, Koraput and Kalahandi contain most of the high critical zone concerning future availability of groundwater while most of the coastal regions are safe.
Article Highlights
Water level trend analysis was performed taking 30 years of historical data.
Hardrock regions are prominent zones of declining in water level than the alluvium parts.
Precipitation followed by landuse & land cover, lithology and population density are controlling the most for the long-term water level change.
Hardrock regions contain most of the high critical zone concerning future availability of groundwater.
Most of the coastal regions are safe pertaining to future availability of groundwater.
