University of Central Asia

Study region: In high elevation watersheds of Central Asia, snow is the main source of discharge. Spatially and temporally distributed snow water equivalent (SWE) measurements in-situ or remotely sensed have the potential to estimate whether seasons in a given year will be water-abundant or water-scarce. Study focus: Here we show the benefits of FLDAS-Central Asia SWE daily simulations retrieved since 2001 in a snow-fed basin of one of the water towers of Amu Darya. FLDAS estimations were compared with winter field measurements of SWE using a Mount Rose sampler. Despite its tendency to overestimate, FLDAS reliably captures the annual variability of SWE and reproduces temporal patterns with a RMSE of 107 mm. FLDAS was used to estimate the significance of nine snow-season metrics spanning accumulation and melt phases, trends with time. New hydrologic insights: The eastern plateau experienced a shorter accumulation and melt season accompanied by a drier snowpack and faster melt rates, driven by its more arid climate, enhanced wind-driven snow redistribution, strong radiation, and higher potential for total residual loss. In contrast, glaciated areas in high elevations of the east and north basin exhibited increasing seasonal snow and wetter conditions in these remote areas with complex topography where in-situ data is unavailable. This study highlights the need for continuous ground-based monitoring of SWE, given the strong correlation between snowmelt and discharge; and to reduce estimation uncertainties in this region.

Devastating snow avalanches are frequent in High Mountain Asia (HMA) yet remain undocumented with climate change impact drivers poorly understood. Here we introduce the first record of 60 million avalanche deposits across 10,701 small catchments, compiled from 33 years of Landsat data from 1990 until 2022 using a snow index. Potential damages from avalanches in areas at risk in HMA include nearly 20% of the buildings and up to 22% of the road network annually blocked by deposits temporarily disconnecting villages from food, energy, medicine, and communication infrastructures. Across 85% of HMA, no long-term trends of deposits were detected due to variable snow and temperature during winter. Nonetheless, in 15% of the 214 larger aggregated catchments comprising HMA, the number of deposits increased by 10 every year. Multivariate analysis among these increases of deposits and winter snow and temperature parameters from reanalysis data revealed that a few areas of western HMA experienced increases in snow water equivalent (5 mm in three decades) and air temperature (2 degrees C) contributing to the increase of avalanche activity. There, a decrease in snowfall of 50 mm, with an increase of rainfall, contributed to the formation of weak and unstable snowpacks. Most deposit trends could not be explained by snow-temperature variables because of the complex and variable interactions between avalanches and climate. These results call for an adoption of mitigation measures in HMA to address avalanche impacts on infrastructure and human lives, especially in areas where avalanche occurrence may increase with time due to climate tendencies.

Climate change is intensifying drought risks across Central Asia, with mountainous regions like Batken in southwestern Kyrgyzstan particularly vulnerable due to their complex topography, climatic variability, and socio-political marginality. Despite increasing recognition of these risks, localized evidence on the impacts of drought and the adaptive capacity of rural communities remains limited. This study combines meteorological data analysis, remote sensing indices (TCI, VCI, VHI), and community-based qualitative research to examine drought impacts on crop yields and adaptation strategies across diverse altitudinal zones in Batken. Our analysis reveals a fivefold increase in drought frequency in recent decades. In-situ observations show a seasonal shift in temperature trends, confirming community reports of rapid warming in March over the past 20 years. This warming has resulted in fruit crop losses during flowering stages and altered the timing of livestock migration to and from summer pastures, contributing to fodder scarcity and rising prices. Extensive community consultations uncovered a rich tapestry of locally developed adaptation strategies, tailored to the distinct challenges of each elevation zone. However, these efforts remain largely unsupported by formal state programs. By integrating scientific data with local knowledge, this research provides a nuanced, place-based understanding of climate vulnerability and resilience. The findings offer actionable insights for national adaptation planning and contribute to broader discussions on sustainable climate responses in marginal mountain regions.

Accurate cell segmentation is a fundamental task in computational pathology and biomedical image analysis, directly impacting applications such as disease diagnosis, cancer grading, and drug discovery. Despite recent advances in deep learning, existing methods often struggle with precise boundary delineation in densely packed and morphologically complex cellular structures. In this paper, we propose a novel boundary-guided dual encoder architecture that explicitly separates semantic region representation from structural boundary modeling. The proposed framework integrates a ResNet-50 based region encoder with a lightweight ResNet-18 boundary encoder, enabling effective multi-scale feature fusion through a boundary guided attention mechanism. This design enhances segmentation accuracy, particularly along ambiguous and low contrast boundaries. Experimental results on the BCCD dataset demonstrate that the proposed model achieves a Dice score of 95.85% and pixel accuracy of 97.47%, outperforming several state-of-the-art methods while maintaining significantly lower computational complexity. Specifically, the model requires only 12.70 M parameters and 36.86 GFLOPs, making it suitable for deployment in resource-constrained medical environments.

High-altitude glacier-lake systems in the eastern Pamir Plateau, Tajikistan, are highly sensitive elements of Central Asia’s cryosphere and are vital for sustaining regional water resources. The Yashilkul Lake is located within a tectonic depression dammed by an ancient rockslide, forming a large alpine lake. This lake is currently impacted by intensified warming, glacier retreat, and poorly quantified hydrological shift. The primary objective of this study is to assess multi-decadal changes in the Yashilkul and Bulunkul lakes and their surrounding cryosphere between 1994 and 2024. The changes were analyzed using multi-temporal Landsat imagery and unmanned aerial vehicle (UAV) surveys, complemented by in-situ meteorological observations from the Bulunkul meteorological station spanning the period from 1990 to 2024. Glacier and lake boundaries were extracted from Landsat data, primarily by applying the normalized difference water index, supplemented by manual delineation. UAV photogrammetry characterized dam morphology and adjacent ponds, and climate trends were evaluated with the modified Mann-Kendall test. A significant warming trend of 0.096°C/a and pronounced interannual precipitation variability have driven persistent glacier retreat and lake surface area fluctuations. The Yashilkul Lake’s surface area decreased from 36.40 (±1.15) km2 in 2010 to 31.94 (±0.54) km2 in 2020 and partially rebounded to 33.99 (±0.60) km2 in 2024, while the Bulunkul Lake’s surface area remained nearly stable owing to limited glacial influence. Additionally, UAV surveys conducted in 2022 and 2024 revealed main features of the Yashilkul Lake: rockslide-dammed origin, perched ponds along the dam body, and an artificial canal regulating its outflow. Nearby glaciers, particularly Glacier No. 369, exhibited strong frontal retreat and proglacial lake expansion. The proglacial lake expanded nearly fourfold from 0.08 (±0.01) km2 in 2000 to 0.33 (±0.02) km2 in 2024, raising concerns about potential glacial lake outburst floods that could impact the Yashilkul Lake and compromise the integrity of its natural dam. The findings highlight accelerating hydrological and cryospheric transformations in the Pamir Plateau, emphasizing the need for sustained monitoring of glacier-lake systems owing to their critical implications for water security, ecological stability, and downstream hazard management.