Alpine lakes in the interior of Tibet, endorheic Changtang Plateau (CP), serve as 'sentinels' regional climate change. Recent studies indicated that accelerated change has driven a widespread area expansion across CP, but comprehensive and accurate quantifications their storage changes are hitherto rare. This study integrated optical imagery digital elevation models to uncover fine spatial details lake water (LWS) CP at an annual timescale after new millennium (from 2002–2015). Validated by...

Accurate information of urban surface water is important for assessing the role it plays in ecosystem services under content urbanization and climate change. However, high-resolution monitoring bodies using remote sensing remains a challenge because limitation previous indices dark building shadow effect. To address this problem, we proposed an automated extraction method (UWEM) which combines new index, together with detection method. Firstly, trained parameters UWEM ZY-3 imagery Qingdao,...

Monitoring of the alpine lakes on endorheic Changtang Plateau is vitally important in understanding climate impacts hydrological cycle. Existing studies have revealed an accelerated lake expansion during 2000s compared with prior decades. However, partial hiatus recent Landsat archive affected continuation changes decade. Here we synergistically used imagery from and Huanjing satellites to enable a detailed monitoring area dynamics Plateau. Our results present that continued expand at rapid...

Abstract Lakes provide important water resources and many essential ecosystem services. Some of Earth's largest lakes recently reached record‐low levels, suggesting increasing threats from climate change anthropogenic activities. Yet, continuous monitoring lake levels is challenging at a global scale due to the sparse in situ gauging network limited spatial or temporal coverage satellite altimeters. A few pioneering studies used areas hypsometric curves reconstruct but suffered large...

Effective water resources management in California relies substantially on real-time information of snow equivalent (SWE) at basin scale and mountain ranges given that snowpacks provide the primary supply for State. However, SWE estimation based solely remote sensing, modeling, or ground observations does not meet contemporary operational requirements. In this context, study develops a data-fusion framework combines multi-source datasets including satellite-observed daily mean fractional...

Abstract In nearly all reservoirs, storage capacity is steadily lost due to trapping and accumulation of sediment. Despite critical importance freshwater supplies, reservoir sedimentation rates are poorly understood sparse bathymetry survey data challenges in modeling sequestration. Here, we proposed a novel approach estimate losses using high‐resolution Sentinel‐2 satellites daily situ water levels. Validated on eight reservoirs across the central western United States, estimated have mean...

The Integrated Valuation of Ecosystem Services and Trade-Offs (InVEST) model with the distributed hydrological Soil Water Assessment Tool (SWAT) were implemented. SWAT quantifies visualizes water production groundwater reserves in Mudanjiang River Basin, employing runoff modulus method to calculate recharge basin. This study aims assess model’s applicability cold basins subsequently analyze distribution characteristics, reserves, exploitable volume. It serves as a reference for judicious...

Improving high-resolution (meter-scale) mapping of snow-covered areas in complex and forested terrains is critical to understanding the responses species water systems climate change. Commercial imagery from Planet Labs, Inc. (Planet, San Francisco, CA, USA) can be used environmental science, as it has both high spatial (0.7–3.0 m) temporal (1–2 day) resolution. Deriving using traditional radiometric techniques have limitations due lack a shortwave infrared band that needed fully exploit...

Mountain snowpack provides critical water resources for forest and meadow ecosystems that are experiencing rapid change due to global warming. An accurate characterization of heterogeneity in these requires snow cover observations at high spatial resolutions, yet most existing datasets have a coarse resolution. To advance our observation capabilities meadows forests, we developed machine learning model generate snow-covered area (SCA) maps from PlanetScope imagery about 3-m The achieves...

Whereas many independent methods are used to estimate snow water equivalent (SWE) and its spatial distribution seasonal variability, a need exists for systematic characterization of inter-model differences at annual, seasonal, regional scales necessary quantify the associated uncertainty in these datasets. This study conducts multi-scale validation comparison, based on Airborne Snow Observatory data, five state-of-the-art SWE datasets Sierra Nevada, California, including three from...

Snow water equivalent (SWE) distribution at fine spatial scales (≤ 10 m) is difficult to estimate due modeling and observational constraints. However, the of SWE throughout spring snowmelt season often correlated timing snow disappearance. Here, we show that cover maps generated from PlanetScope’s constellation Dove Satellites can resolve 3 m date disappearance across seven alpine domains in California Colorado. Across a 5-year period (2019 – 2023), average uncertainty disappearance, or time...

Abstract Snow water equivalent (SWE) distribution at fine spatial scales (≤10 m) is difficult to estimate due modeling and observational constraints. However, the of SWE throughout spring snowmelt season often correlated timing snow disappearance. Here, we show that cover maps generated from PlanetScope's constellation Dove Satellites can resolve 3 m date disappearance across seven alpine domains in California Colorado. Across a 5‐year period (2019–2023), average uncertainty disappearance,...