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Soil freeze–thaw processes play a fundamental role in the hydrology, geomorphology, ecology, thermodynamics, and soil chemistry of cold regions' landscapes. In understanding these processes, the temperature of the soil is used as a proxy to represent the partitioning of soil ice and water content via a soil freezing characteristic curve (SFCC). This mathematical construct relates the soil ice content to a specific temperature for a particular soil. SFCCs depend on many factors, including soil properties (e.g., porosity and composition), soil pore water pressure, dissolved salts, (hysteresis in) freezing/thawing point depression, and the degree of saturation, all of which can be site-specific and time-varying characteristics. SFCCs have been measured using various methods for diverse soils since 1921, but, to date, these data have not been broadly compared. This is in part because they had not previously been compiled in a single dataset. The dataset presented in this publication includes SFCC data digitized or received from authors, and it includes both historic and modern studies. The data are stored in an open-source repository, and an R package is available to facilitate their use. Aggregating the data has pointed out some data gaps, namely that there are few studies on coarse soils and comparably few in situ measurements of SFCCs in mountainous environments. It is hoped that this dataset (10.5281/zenodo.5592825;) will aid in the development of SFCC theory and improve SFCC approximations in soil freeze–thaw modelling activities. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive hydrometeorological dataset collected over the past two decades throughout the Cordillera Blanca, Peru. The data-recording sites, located in the upper portion of the Rio Santa valley, also known as the Callejon de Huaylas, span an elevation range of 3738–4750 m a.s.l. As many historical hydrological stations measuring daily discharge across the region became defunct after their installation in the 1950s, there was a need for new stations to be installed and an opportunity to increase the temporal resolution of the streamflow observations. Through inter-institutional collaboration, the hydrometeorological network described in this paper was deployed with the goal of evaluating how progressive glacier mass loss was impacting stream hydrology, and understanding better the local manifestation of climate change over diurnal to seasonal and interannual time scales. The four automatic weather stations supply detailed meteorological observations and are situated in a variety of mountain landscapes, with one on a high-mountain pass, another next to a glacial lake, and two in glacially carved valleys. Four additional temperature and relative humidity loggers complement the weather stations within the Llanganuco valley by providing these data across an elevation gradient. The six streamflow gauges are located in tributaries to the Rio Santa and collect high-temporal-resolution runoff data. The datasets presented here are available freely from 10.4211/hs.35a670e6c5824ff89b3b74fe45ca90e0 (Mateo et al., 2021). Combined, the hydrological and meteorological data collected throughout the Cordillera Blanca enable detailed research of atmospheric and hydrological processes in tropical high-mountain terrain. [ABSTRACT FROM AUTHOR]

Soil freeze-thaw processes play a fundamental role in the hydrology, geomorphology, ecology, thermodynamics and soil chemistry of a cold-regions landscape. In understanding these processes, the temperature of the soil is used as a proxy to represent the soil ice content through a soil freezing characteristic curve (SFCC). This mathematical construct relates the soil ice content to a specific temperature for a particular soil. SFCCs depend on many factors including soil properties (e.g., porosity, composition, etc.), soil pore water pressure, dissolved salts, (hysteresis in) freezing/thawing point depression, and degree of saturation, all of which can be site-specific and time varying. SFCCs have been measured using various methods for diverse soils since 1921, and to date this data has not been broadly compared, in part because it has not previously been compiled in a single data set. The dataset presented in this publication includes SFCC data digitized or received from authors, and includes both historic and modern studies. The data is stored in an open-source repository, and an R package is available to facilitate its use. Aggregating the data has pointed out some data gaps, namely that there are few studies of coarse soils, and comparably few in-situ measurements of SFCCs in mountainous environments. It is hoped that this dataset will aid in the development of SFCC theory, and improve SFCC approximations in soil freeze-thaw modelling activities. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive hydrometeorological dataset collected over the past two decades throughout the Cordillera Blanca, Peru. The data recording sites, located in the upper portion of the Rio Santa valley, also known as the Callejon de Huaylas, span an elevation range of 3738-4750 m a.s.l. As many historical hydrological stations measuring daily discharge across the region became defunct after their installation in the 1950s, there was a need for new stations to be installed and an opportunity to increase the temporal resolution of the streamflow observations. Through inter-institutional collaboration the hydrometeorological network described in this paper was deployed with goals to evaluate how progressive glacier mass loss was impacting stream hydrology, and to better understand the local manifestation of climate change over diurnal to seasonal and interannual time scales. The four automatic weather stations supply detailed meteorological observations, and are situated in a variety of mountain landscapes, with one on a high-mountain pass, another next to a glacial lake, and two in glacially carved valleys. Four additional temperature and relative humidity loggers complement the weather stations within the Llanganuco valley by providing these data across an elevation gradient. The six streamflow gauges are located in tributaries to the Rio Santa and collect high temporal resolution runoff data. The datasets presented here are available freely from https://doi.org/10.4211/hs.059794371790407abd749576df8fd121 (Mateo et al., 2021). Combined, the hydrological and meteorological data collected throughout the Cordillera Blanca enable detailed research of atmospheric and hydrological processes in tropical high-mountain terrain. [ABSTRACT FROM AUTHOR]

As permafrost thaws in the Arctic, new subsurface pathways open for the transport of groundwater, energy, and solutes. We identify different ways that these subsurface changes are driving observed surface consequences, including the potential for increased contaminant transport, modification to water resources, and enhanced rates of infrastructure (e.g. buildings and roads) damage. Further, as permafrost thaws it allows groundwater to transport carbon, nutrients, and other dissolved constituents from terrestrial to aquatic environments via progressively deeper subsurface flow paths. Cryohydrogeology, the study of groundwater in cold regions, should be included in northern research initiatives to account for this hidden catalyst of environmental and societal change. [ABSTRACT FROM AUTHOR]

The importance of water moving between the atmosphere and aquifers has led to efforts to develop and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water resource stress. In response to this need, we have developed GSFLOW–GRASS, a bundled set of open-source tools that develops inputs for, executes, and graphically displays the results of GSFLOW, the U.S. Geological Survey's coupled groundwater and surface-water flow model. In order to create a robust tool that can be widely implemented over diverse hydro(geo)logic settings, we built a series of GRASS GIS extensions that automatically discretizes a topological surface-water flow network that is linked with an underlying gridded groundwater domain. As inputs, GSFLOW–GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. We demonstrate the broad applicability of the toolbox by successfully testing it in environments with varying degrees of drainage integration, landscape relief, and grid resolution, as well as the presence of irregular coastal boundaries. These examples also show how GSFLOW–GRASS can be implemented to examine the role of groundwater–surface-water interactions in a diverse range of water resource and land management applications. [ABSTRACT FROM AUTHOR]

The source region of the Yellow River (SRYR) provides 35 % of the rivers annual discharge but is very sensitive to the climate change. The change in discharge from the SRYR has been attributed to both climatic and anthropogenic forces, and previous estimates of the impact of human activities on the change in discharge have been higher than 50 % of the total change. Considering the very low population density and limited land use change, this result is potentially inconsistent. Our study modifies the traditional Budyko separating approach to identify and quantify the climatic causes in discharge changes. Application of this new approach to the SRYR now highlights the role of the degrading permafrost, based on long-term observation data of the maximum frozen depth (MFD). Our results show that over the past half-century, the change in discharge in the SRYR was primarily controlled by climate change rather than local human activities. Increasing air temperature is generally a negative force on discharge whereas it also causes permafrost to degrade - a positive factor on discharge generation. Such conflicting effects enhance the uncertainty in assessments of the hydrological response to climate change in the SRYR. [ABSTRACT FROM AUTHOR]

Water flow through catchments sustains ecosystems and human activity, shapes landscapes, and links climate to the outermost layers of the solid Earth. The profound importance of water moving between the atmosphere and aquifers has led to efforts to develop and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, and thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water-resource stress. In response to this need, we have developed GSFLOW-GRASS, a straightforward set of open-source tools that develops inputs for and runs GSFLOW, the U.S. Geological Survey's coupled groundwater-surface-water flow model. As inputs, GSFLOW-GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. GSFLOW-GRASS is written in Python as a set of (1) GRASS GIS extensions, (2) input-file-builder scripts, and (3) visualization scripts. We developed a set of custom GRASS GIS commands that generate "hydrologic response units" for surface water, discretized topologically as sub-basins of the tributary network; build the MODFLOW grid; and add necessary attributes to each of these geospatial units. These GIS outputs are interpreted by a second set of Python scripts, which link them to hydrologic variables, build inputs to GSFLOW, and run GSFLOW. Lastly, GSFLOW output files are used to produce figures and time-lapse movies of simulation results using a third set of post-processing Python scripts. We demonstrate the broad applicability of these tools to diverse settings through examples based on: the high Peruvian Andes, the Channel Islands of California, and the formerly-glaciated Upper Mississippi valley in Minnesota. [ABSTRACT FROM AUTHOR]