Across High Asia, the amount, timing, and spatial patterns of snow and ice melt play key roles in providing water for downstream irrigation, hydropower generation, and general consumption. The goal of this paper is to distinguish the specific contribution of seasonal snow versus glacier ice melt in the major basins of High Mountain Asia: Ganges, Brahmaputra, Indus, Amu Darya, and Syr Darya. Our methodology involves the application of MODIS-derived remote sensing products to separately calculate daily melt outputs from snow and glacier ice. Using an automated partitioning method, we generate daily maps of (1) snow over glacier ice, (2) exposed glacier ice, and (3) snow over land. These are inputs to a temperature index model that yields melt water volumes contributing to river flow. Results for the five major High Mountain Asia basins show that the western regions are heavily reliant on snow and ice melt sources for summer dry season flow when demand is at a peak, whereas monsoon rainfall dominates runoff during the summer period in the east. While uncertainty remains in the temperature index model applied here, our approach to partitioning melt from seasonal snow and glacier ice is both innovative and systematic and more constrained than previous efforts with similar goals.

Maps of snow cover serve as early indicators for hydrologic forecasts and as inputs to hydrologic models that inform water management strategies. Advances in snow cover mapping have led to increasing accuracy, but unsatisfactory treatment of vegetation's interference when mapping snow has led to maps that have limited utility for water forecasting. Vegetation affects snow mapping because ground surfaces not visible to the satellite produce uncertainty as to whether the ground is snow covered. At nadir, the forest canopy obscures the satellite view below the canopy. At oblique viewing angles, the forest floor is obscured by both the canopy and the projection of tree profiles onto the forest floor. We present a canopy correction method based on Moderate Resolution Imaging Spectroradiometer satellite imagery validated with field observations that mitigates geometric and georegistration issues associated with changing satellite acquisition angles in forested areas. The largest effect from a variable viewing zenith angle on the viewable gap fraction in forested areas occurs in moderately forested areas with 30–40% tree canopy coverage. Cloud cover frequently causes errors in snow identification, with some clouds identified as snow and some snow identified as cloud. A snow‐cloud identification method utilizes a time series of fractional vegetation and rock land‐surface data to flag snow‐cloud identification errors and improve snow‐map accuracy reducing bias by 20% over previous methods. Together, these contributions to snow‐mapping techniques could advance hydrologic forecasting in forested, snow‐dominated basins that comprise an estimated one fifth of Northern Hemisphere snow‐covered areas.

Water vulnerabilities in Central Asia are affected by a complex combination of climate-sensitive water sources, trans-boundary political tensions, infrastructure deficiencies and a lack of water management organization from community to federal levels. This study aims to clarify the drivers of water stress across the 440 km Naryn River basin, headwater stem to the Syr Darya and the disappearing North Aral Sea. We use a combination of human and physical geography approaches to understand the meltwater-controlled hydrology of the system (using hydrochemical mixing models) as well as the human-water experience (via community surveys). Surveys indicate that current water stress is primarily a function of water management and access issues resulting from the clunky transition from Soviet era large-scale agriculture to post-Soviet small-plot farming. Snow and ice meltwaters play a dominant role in the surface and ground water supplies to downstream communities across the study’s 4220 m elevation gradient, so future increases to water stress due to changes in volume and timing of water supply is likely given frozen waters’ high sensitivities to warming temperatures. The combined influence of social, political and climate-induced pressures on water supplies in the Naryn basin suggest the need for proactive planning and adaptation strategies, and warrant concern for similar melt-sourced Central Asian watersheds.

As our global climate warms, people, and economies utilizing water resources sourced by snow and ice melt in mountain areas are disproportionately affected relative to locations that rely on rainfall. Worldwide, the vast majority of those impacted by snowfall changing to rainfall and earlier melt from a warming climate live in Asia. The Brahmaputra River originates in the declining glaciers and snowfields of the Chinese and Bhutanese Himalaya before flowing to the mega population centers of the Bangladesh delta. Bhutan’s economy relies on water resource-dependent hydropower and agriculture imposing important questions about the impact of climate change on the long-term viability of water supplies in these important economic sectors. To clarify potential effects on water supplies in a warming world, and specifically to quantify the role of meltwater to river discharge in the headwaters of the Brahmaputra basin, we utilize a combined field observation-remote sensing approach to quantify river discharge source waters in a representative headwater basin, the Chamkhar Chhu. Using 4 years of water isotope and chemistry data together with a Bayesian Monte Carlo mixing model run seasonally in 2016, we find that the Chamkhar Chhu is mostly a rain-dominated basin at the lower elevation of our study domain (2591 m a.s.l.), with peak contributions from snowmelt in the early-monsoon and ice melt in the post-monsoon seasons. The radioactive tritium isotope shows glacier ice at the terminus was formed before the 1960s bomb spike while groundwater and river water samples taken in August (late monsoon) are sourced from mostly newer water inputs that show little tritium. The influence of the highly reacted Tsampa tributary, sourced by a debris covered glacier, and additional groundwater inputs generally increase major ion concentrations with distance from the glacier snout. An overall decreasing trend in the minimum snow and ice cover extent maps produced using MODIS Terra data from 2000 to 2017 suggest a lessening of cryospheric water resource availability in the basin, although this timeseries is short compared to the timescale of atmospheric-oceanic oscillations controlling snowfall. While decreasing snow and ice resources will likely lead to changing melt water contributions to river discharge, the overall impact on the water resources may be buffered by rainfall contributions as previous studies forecast an increase in precipitation for the region that will likely make up for lower melt water inputs.

Environmental context: Stable water isotopes δ18O and δ2H in atmospheric precipitation are valuable hydrologic tracers with varied applications, but measuring them over large scales is impractical. Precipitation isotope models (isoscapes) are instead needed to predict isotopes through space and time. Precipitation isotopes are affected by numerous variables ranging from orographic effects to phase changes to moisture mass origin, making them challenging to predict in complex geographies such as New Zealand. Improving data density together with recent advances in modelling approaches hold promise for improving accuracy of precipitation isoscapes in New Zealand and similar locations. Rationale: Precipitation isotope models based on global networks, such as the Global Network of Isotopes in Precipitation (GNIP), lack sufficient spatial and temporal resolution for hydrological applications in New Zealand due to sparse data coverage. Models driven by regional datasets are needed to improve accuracy of isotope predictions to increase utility in environmental research applications. Methodology: We develop Precipitation Isotopes New Zealand (PINZ) δ18O and δ2H isoscapes employing the Extreme Gradient Boosting (XGBoost) machine learning algorithm driven by a regional precipitation isotope database with high station density across New Zealand, and diverse climate and geographic predictors. We produce a national monthly precipitation isotope model at 5-km resolution. Model uncertainty associated with monthly predictions is evaluated using ‘leave one out’ cross validation (LOOCV, or jackknife) tests. Results: PINZ shows significant spatial and temporal variability in isotope values, with notable patterns related to New Zealand’s complex topography and climatic influences. Model performance on test data is described by a root mean square error of 1.83‰. Discussion: Although the model performs well overall, it exhibits limitations in predicting extreme precipitation δ18O values (most enriched and most depleted) and predicting δ18O of precipitation during periods of extreme weather conditions. Leveraging detailed local data and advanced algorithms, we demonstrate one way forward for improving isoscapes in complex environments.

We use remote sensing to enhance the interpretation of the first baseline dataset of hydrologic, isotopic and hydrochemical variables spanning 620 km of the upper Marañón River, in Andean Peru, from the steep alpine canyons to the lower lying jungle. Remote, data-scarce river systems are under increased hydropower development pressure to meet rising energy demands. The upstream-downstream river continuum, which serves as a conduit for resource exchange across ecosystems, is at risk, potentially endangering the people, environments, and economies that rely on river resources. The Marañón River, one of the final free-flowing headwater connections between the Andes and the Amazon, is the subject of myriad large-scale hydropower proposals. Due to challenging access, environmental data are scarce in the upper Marañón, limiting our ability to do system-wide river basin planning. We capture key processes and transitions in the context of hydropower development. Two hydrologic regimes control the Marañón dry-season flow: in the higher-elevation upper reaches, a substantial baseflow is fed by groundwater recharged from wet season rains, in contrast to the lower reaches where the mainstem discharge is controlled by rain-fed tributaries that receive rain from lowland Amazon moisture systems. Sustainability of the upper corridor’s dry-season baseflow appears to be more highly connected to the massive natural storage capacity of extensive wetlands in the puna (alpine grasslands) than with cryospheric water inputs. The extent and conservation of puna ecosystems and glacier reservoirs may be interdependent, bringing to bear important conservation questions in the context of changing climate and land use in the region. More generally, this case study demonstrates an efficient combined remote sensing and field observation approach to address data scarcity across regional scales in mountain basins facing imminent rapid change.