What question did this study set out to answer?

The aim is to assess the long-term changes in surface water extent and identify driving factors in Central Asia's dryland wetlands.

January 25, 2026Open Access

Long-Term Dynamics and Transitions of Surface Water Extent in the Dryland Wetlands of Central Asia Using a Hybrid Ensemble–Occurrence Approach

Key Points

The aim is to assess the long-term changes in surface water extent and identify driving factors in Central Asia's dryland wetlands.
Analyzed Landsat satellite data from 2000–2024 within Google Earth Engine.
Used modified Normalized Difference Water Index and other indices for water extraction.
Employed ensemble methods for mapping surface water extent across different SWE regimes.
Conducted trend analysis and evaluated hydroclimatic influences using statistical correlation methods.
Observed significant long-term declines in surface water, particularly in summer and fall.
Validated accuracy of water extent mapping with an F1-Score of approximately 0.85.
Identified flow regulation and temperature as major influences on seasonal surface water dynamics.

Abstract

Wetlands in dryland regions are rapidly degrading under the combined effects of climate change and human regulation, yet long-term, seasonally resolved assessments of surface water extent (SWE) and its dynamics remain scarce. Here, we map and analyze seasonal surface water extent (SWE) over the period 2000–2024 in the Ile River Delta (IRD), south-eastern Kazakhstan, using Landsat TM/ETM+/OLI data within the Google Earth Engine (GEE) framework. We integrate multiple indices using the modified Normalized Difference Water Index (mNDWI), Automated Water Extraction Index (AWEI) variants, Water Index 2015 (WI2015), and Multi-Band Water Index (MBWI) with dynamic Otsu thresholding. The resulting index-wise binary water maps are merged via ensemble agreement (intersection, majority, union) to delineate three SWE regimes: stable (persists most of the time), periodic (appears regularly but not in every season), and ephemeral (appears only occasionally). Validation against Sentinel-2 imagery showed high accuracy F1-Score/Overall accuracy (F1/OA ≈ 0.85/85%), confirming our workflow to be robust. Hydroclimatic drivers were evaluated through modified Mann–Kendall (MMK) and Spearman’s (r) correlations between SWE, discharge (D), water level (WL), precipitation (P), and air temperature (AT), while a hybrid ensemble–occurrence framework was applied to identify degradation and transition patterns. Trend analysis revealed significant long–term declines, most pronounced during summer and fall. Discharge is predominantly controlled by stable spring SWE, while discharge and temperature jointly influence periodic SWE in summer–fall, with warming reducing the delta surface water. Ephemeral SWE responds episodically to flow pulses, whereas precipitation played a limited role in this semi–arid region. Spatially, area(s) of interest (AOI)-II/III (the main distributary system) support the most extensive yet dynamic wetlands. In contrast, AOI-I and AOI-IV host smaller, more constrained wetland mosaics. AOI-I shows persistence under steady low flows, while AOI-IV reflects a stressed system with sporadic high-water levels. Overall, the results highlight the dominant influence of flow regulation and distributary allocation on IRD hydrology and the need for ecologically timed releases, targeted restoration, and transboundary cooperation to sustain delta resilience.

Long-Term Dynamics and Transitions of Surface Water Extent in the Dryland Wetlands of Central Asia Using a Hybrid Ensemble–Occurrence Approach

Key Points

Abstract

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