Earth's terrestrial near-subsurface environment can be divided into relatively porous layers of soil, intact regolith, and sedimentary deposits above unweathered bedrock. Variations in the thicknesses of these layers control the hydrologic and biogeochemical responses of landscapes. Currently, Earth System Models approximate the thickness of these relatively permeable layers above bedrock as uniform globally, despite the fact that their thicknesses vary systematically with topography, climate, and geology. To meet the need for more realistic input data for models, we developed a high-resolution gridded global data set of the average thicknesses of soil, intact regolith, and sedimentary deposits within each 30 arcsec (1 km) pixel using the best available data for topography, climate, and geology as input. Our data set partitions the global land surface into upland hillslope, upland valley bottom, and lowland landscape components and uses models optimized for each landform type to estimate the thicknesses of each subsurface layer. On hillslopes, the data set is calibrated and validated using independent data sets of measured soil thicknesses from the U.S. and Europe and on lowlands using depth to bedrock observations from groundwater wells in the U.S. We anticipate that the data set will prove useful as an input to regional and global hydrological and ecosystems models.

Snowmelt from forested, mountainous environments in the western United States is a critical regional water resource for streamflow and ecological productivity. These landscapes are undergoing rapid changes from the combined effects of forest fires, insect infestation and climate change. Numerous observational studies demonstrate that trees control snowpack accumulation and ablation over scales of tens of metres. Representing forest heterogeneity in models is important for understanding how changes in climate and vegetation cover affect the snowpack; yet, many snow models simplify a forest into two categories: canopy covered and non-canopy covered. We combine existing parameterizations of mass and energy fluxes within a new three-dimensional framework informed by Airborne Laser Swath Mapping (ALSM)-derived canopy maps and evaluated with ALSM-derived snow depth maps to explicitly simulate snow cover in relation to heterogeneous canopy. Model results capture much of the observed snow variability depicted in the 1-m ALSM-derived snow depth maps. Observations and modelled results identify open areas <15 m from tree canopies as having more snow and more snow variability than areas >15 m from tree canopies, and modelled results predict that open areas <15 m from tree canopies have 30-40% more net snow water input than areas that are underneath tree canopies and 10-25% more net snow water input than areas that are >15 m from tree canopies. Furthermore, 1-m simulations give higher estimates for net snow water input than coarser resolution simulations, mainly in areas with fewer trees. These results suggest the importance of explicitly representing canopy edges in snow models.

Global land cover data are widely used in weather, climate, and hydrometeorological models. The Collection 5.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) product is found to have a substantial amount of interannual variability, with 40% of land pixels showing land cover change one or more times during 2001–10. This affects the global distribution of vegetation if any one year or many years of data are used, for example, to parameterize land processes in regional and global models. In this paper, a value-added global 0.5-km land cover climatology (a single representative map for 2001–10) is developed by weighting each land cover type by its corresponding confidence score for each year and using the highest-weighted land cover type in each pixel in the 2001–10 MODIS data. The climatology is validated by comparing it with the System for Terrestrial Ecosystem Parameterization database as well as additional pixels that are identified from the Google Earth proprietary software database. When compared with the data of any individual year, this climatology does not substantially alter the overall global frequencies of most land cover classes but does affect the global distribution of many land cover classes. In addition, it is validated as well as or better than the MODIS data for individual years. Also, it is based on higher-quality data and is validated better than the Global Land Cover Characteristics database, which is based on 1 year of Advanced Very High Resolution Radiometer data and represents a widely used first-generation global product.

Snow water equivalent (SWE) variability and its drivers over different regions remain uncertain due to lack of representativeness of point measurements and deficiencies of existing coarse‐resolution SWE products. Here, for the first time, we quantify and understand the snowpack change from 1982 to 2016 over conterminous United States at 4‐km pixels. Annual maximum SWE decreased significantly (p < 0.05) by 41% on average for 13% of snowy pixels over western United States. Snow season was shortened significantly by 34 days on average for 9% of snowy pixels over the United States, primarily caused by earlier ending and later arrival of the season over western and eastern United States, respectively. October–March mean temperature and accumulated precipitation largely explain the temporal variability of 1 April SWE over western United States, and considering temperature alone would exaggerate the warming effect on SWE decrease. In contrast, temperature plays the primary role in the 1 April SWE variability over eastern United States.

[1] In the current empirical study, we provide evidence about how the hydrologic responses of small mountain catchments are related to aspect (slope direction and exposure) at Redondo Peak, located in the Valles Caldera, New Mexico, United States. Specifically, we test the hypothesis that the transit time of water is related to the catchment aspect. Aspect is an easily measurable and transferable topographic characteristic that is related to the amount of direct solar radiation a particular catchment receives, and therefore, different catchments with different aspects have different rates of snow ablation, evapotranspiration, and water cycling in general. Transit times, which describe the time between when water enters the catchment as precipitation and when it leaves as stream flow, captures many hydrologic features such as flow path variability and the combined effects of water storage and water fluxes. We have designed an experiment that involves field data collection, isotopic analysis of stream and precipitation samples, and the estimation of transit times using lumped-parameter convolution for 15 sites in small (1-15 km 2 ) catchments that drain different aspects of Redondo Peak. Our data suggest that isotopic variability and estimated transit times are both related to aspect. Other potential relationships between topographical features (such as flow path length, slope gradient, and elevation) and isotopic measurements of stream water suggest that landscape and hydrological features are interconnected at Redondo Peak, but these links are not conclusive, suggesting that these topographic indicators do not fully explain the variability of water cycling in these small mountain catchments.