Abstract Net ecosystem productivity (NEP) represents a key indicator of terrestrial carbon sink strength and its response to hydroclimatic variability in dryland regions. However, basin-scale evidence on the long-term dynamics, persistence, and hydroclimatic regulation of NEP remains limited in the Yellow River Basin (YRB) under concurrent warming, drying, and rapid land-use change. Here, we generated an annual 1-km NEP dataset for 2001–2024 by integrating MODIS-based NPP with a regionally calibrated CASA framework and an evapotranspiration-constrained empirical heterotrophic respiration scheme. Temporal trends and persistence were quantified using Theil–Sen, Mann–Kendall, and Hurst analyses. Hydroclimatic controls were investigated using a random forest model interpreted with SHAP, incorporating predictors of water availability, atmospheric dryness, temperature, radiation, and drought conditions. Results show a modest increase in basin-mean NEP but strong spatial heterogeneity. Persistent carbon sinks were concentrated in the semi-humid southeastern YRB, whereas sustained declines occurred in water-limited and rapidly urbanizing regions. Trend–persistence coupling suggests that current improvement areas are likely to maintain their carbon sink function, while extensive regions may continue long-term degradation. Water availability was the dominant control, with saturation occurring at ~ 600 mm annual precipitation and 30–40% relative soil moisture. Atmospheric dryness strongly constrained NEP when vapor pressure deficit exceeded ~ 0.6 kPa, whereas temperature and radiation enhanced NEP mainly under weak moisture limitation. These results highlight that the stability of terrestrial carbon sinks in this large dryland basin is governed by interacting hydroclimatic constraints. The identified spatial patterns and process-based thresholds improve understanding of carbon–water coupling and provide scientific support for climate-adaptive carbon sink management in dryland river basins. Graphical Abstract This graphical abstract summarizes the workflow used to quantify spatiotemporal change and long-term persistence of net ecosystem productivity (NEP) across the Yellow River Basin during 2001–2024. Multi-source datasets (MODIS products, ERA5-Land and TerraClimate hydroclimate variables, land-use/land-cover, and basin boundaries) were quality-controlled, harmonized, and aggregated to an annual 1-km grid. NEP was constructed following a carbon-balance scheme (NEP = NPP − Rh), where NPP was reconstructed using a CASA light-use-efficiency framework and heterotrophic respiration (Rh) was estimated using a climate-driven empirical formulation; uncertainty was evaluated via consistency checks and Rh sensitivity tests. Long-term trends were detected using Theil–Sen slope and Mann–Kendall significance tests, and persistence was diagnosed using the Hurst exponent. Trend and persistence information were further combined to classify future tendency and identify areas with sustained increase or decrease. To attribute hydroclimatic controls, a Random Forest model was interpreted using SHAP, resolving nonlinear effects and ranking predictor importance. Results indicate strong spatial heterogeneity in NEP dynamics, with moisture supply variables (precipitation and soil moisture) dominating variability and vapor pressure deficit acting as the main atmospheric constraint. This framework supports carbon-sink stability assessment and climate-adaptive management in dryland river basins.

Abstract Debris cover on glaciers in High Mountain Asia (HMA) plays a critical role in shaping glacier evolution and downstream freshwater availability. In Karakoram, glacier melt significantly influences river discharge, yet the interplay of climate change and supraglacial debris cover remains insufficiently quantified. We developed a dynamic debris cover framework using the Spatial Processes in HYdrology (SPHY) model to investigate debris-glacier interactions in the Shigar Basin, Karakoram, Pakistan. Three scenarios (no debris, static debris, process-based dynamic debris) were assessed under four CMIP6 climate projections and emission pathways (SSP-1.26 to SSP-5.85) until 2100. Debris-covered ice accounted for 11% of total glaciated area by 2020 and will expand dramatically to 39% by 2100. Neglecting debris dynamics leads to significant overestimation of glacier retreat (18–25%) and meltwater contributions (40–52%). By 2091–2100, glacier area retains 94% of its 2020 extent under dynamic debris conditions versus only 75% without debris cover. Dynamic debris mitigates mass loss, reducing glacier-derived runoff from 57% to 51% while increasing snowmelt contributions from 25% to 27%. Under SSP-5.85, debris preserves ~ 24–25% more glacier area compared to no-debris scenarios. These findings demonstrate that current glacier models systematically tend to overestimate ice loss, requiring immediate integration of debris dynamics for accurate water security assessments across HMA as nearly 2 billion people are reliant on HMA water resources. Graphical Abstract This study presents an integrated framework to evaluate supraglacial debris cover (DC) impacts on glacier hydrology under climate change in the Shigar Basin, Karakoram. Satellite imagery processed through Google Earth Engine and the GERALDINE algorithm classified debris cover using the Normalized Difference Snow Index (NDSI). Dynamic debris cover evolution framework was developed and three debris scenarios (no debris, static debris, dynamic debris) were implemented in the SPHY glacio-hydrological model, calibrated with observed data and forced with bias-corrected ERA5-Land climate data. CMIP6 climate models under four SSPs were grouped into dry-cold, dry-warm, wet-cold, and wet-warm scenarios for 2021–2100 projections. Results show debris cover will expand from 11% to 39% by 2100, with dynamic debris scenarios preventing 18–25% overestimation of glacier retreat and retaining 94% of glacier area compared to 75% without debris cover. Uncertainty analysis confirms robust model performance, highlighting the critical importance of incorporating evolving debris dynamics in glacio-hydrological projections for accurate water resource assessments across High Mountain Asia.