Diagram showing key sulfur cycling processes in the Colorado East River watershed. Image courtesy of Patricia Fox.

The Science

Climate change is expected to increase the release of sulfur from rocks – the largest pool of sulfur on earth – into rivers and lakes, which could lead to deteriorating water quality. Researchers identified the major forms of sulfur in different parts of a pristine mountainous watershed, including in rocks, soils, and sediments near rivers. Biological conversion of sulfur to organic forms in shallow soils and sediments were found to serve as a limited sink for newly released sulfur, meaning this biological transformation would store, or ‘hold onto’, the element. In near-river sediments, however, sulfur was converted to the mineral mackinawite, which does not dissolve in water. These near-river sediments may hold more sulfur as earth’s climate changes. This process could partially offset the increased sulfur released from rocks and lower the risk of sulfur contamination in freshwater.

The Impact

Sulfur is a naturally occurring element which is abundant on earth and stored primarily in rocks. However, research has shown that climate change may be resulting in high amounts of sulfur in freshwater systems; warmer temperatures may increase weathering, or rock deterioration, which releases sulfur in the process, and water cycle changes may lead to less water available to dilute the element. This study used a holistic approach to better understand how sulfur moves between rocks, soils and water in an undisturbed ecosystem. A highly sensitive method, called x-ray absorption spectroscopy, provided new information on how sulfur is released from rocks in addition to the exact chemical forms of sulfur found in rocks, soils, and in the sediments next to rivers. This research allows for a deeper understanding of sulfur cycling that can help to make better predictions of water quality and watershed responses to climate change.

Summary

Sulfur is an important component of the earth’s crust, and its cycling has critical impacts on water quality and human health. Weathering of pyrite, an abundant mineral containing sulfur, is the primary pathway by which sulfur enters surface waters. Although biological cycling of sulfur in watershed ecosystems ultimately mediates the release of sulfur to rivers and the ocean, climate change has led to water cycle alterations that may enhance pyrite weathering rates and therefore the amount of sulfur released from these minerals. In this study, the researchers identified the major forms of sulfur across a pristine mountainous watershed, including shale bedrock, hillslope soils, and near-river sediments using a highly sensitive technique called x-ray absorption spectroscopy. When shale weathering occurred, pyrite was transformed into sulfate, with large accumulations of elemental sulfur. Close to the river, the researchers observed precipitation of mackinawite, another mineral containing sulfur, in water-saturated sediments. By contrast, shallow, unsaturated soil and sediment contained primarily organic sulfur compounds. The whole-watershed approach, combined with a highly-sensitive analytical technique, shows that riverine sulfur exports are controlled by a balance of rock weathering and biological cycling, where sulfur retention in saturated sediments may partially offset the increased release of sulfur from rocks.

Citation

Fox, P. M., et al. Sulfur Biogeochemical Cycling and Redox Dynamics in a Shale-Dominated Mountainous Watershed. Journal of Geophysical Research: Biogeosciences 127, e2021JG006769 (2022). [DOI: 10.1029/2021JG006769]

Quantifying influences of hot spots/moments over total system function as control point influence (CPI) provides opportunities to reveal governing processes through cross- site and multi-scale comparisons.

The Science

The Critical Zone – the environment from fresh bedrock to canopy – involves very different environmental properties and processes. Therefore, studying this environment at multiple time scales is needed to better predict and understand ecosystem fluxes, exchange rates and biogeochemical functioning. Hot spots and hot moments (HSHMs) are regions or times in the environment that, when compared to surrounding areas or intervening times, experience high reaction rates and significantly influence environmental processes or natural resource quality. Researchers reviewed models, questions and recent findings involving HSHMs to better understand how they impact nutrient dynamics, greenhouse gas emissions, and water and energy exchanges in the critical zone.

The Impact

HSHMs can largely impact environmental processes and natural resource quality. Studying and quantifying HSHMs can help address natural resource management issues such as groundwater contamination, heavy metal transport, and toxic algal blooms by identifying dominant times and regions that control carbon, nutrient, water and energy exchanges. To better understand the Critical Zone and HSHMs that largely influence these ecosystem processes, researchers have provided a description of the HSHMs concept, example applications, and a path forward using numerical modeling. Incorporating HSHMs into critical zone science can help better predict ecosystem function and manage natural resource quality as earth’s climate changes.

Summary

The Critical Zone encapsulates interacting ecosystem levels from the atmosphere to soil, groundwater and bedrock. Differences in these environments occur at multiple scales, posing challenges to understanding the zone holistically. However, predicting how this zone functions is critical to protecting natural resources and monitoring environmental processes such as water and element cycling.

HSHMs can significantly impact environmental quality and functioning – for example, spring melt and storm events can result in hot moments that largely contribute to mercury loading into nearby water bodies, having direct consequences for fish spawning and ecosystem health. Because of their substantial environmental influence, quantifying and modeling these moments and areas in the Critical Zone can help scientists better predict and manage ecosystem function and natural resource quality. Scientists’ review of HSHMs shows that incorporating them into modeling can help quantify ecosystem processes such as nutrient dynamics, greenhouse gas emissions, and water and energy exchange in the critical zone.

Citation

Arora, B., Briggs, M.A., Zarnetske, J.P., Stegen, J., Gomez-Velez, J.D., Dwivedi, D. and Steefel, C., 2022. Hot Spots and Hot Moments in the Critical Zone: Identification of and Incorporation into Reactive Transport Models. Biogeochemistry of the Critical Zone (2022), DOI: 10.1007/978-3-030-95921-0_2.

To tackle geoscientific issues, there is a pressing need to establish an open, inclusive, and collaborative network at an international scale that aims for equitable access to funding, equipment, training, research resources, and mentors. Image by Diana Swantek, Lawrence Berkeley National Laboratory

The Science

Geoscience fields such as Volcanology, Geochemistry, and Petrology (VGP) are extremely broad, involving applications and research questions ranging from planetary geology to the creation of mountains. For this reason, working across traditional disciplinary VGP boundaries has been largely limited to specific challenges and application areas. This has prevented broad sharing of metadata, standards, protocols and models as scientists move from one application area to the next, thereby keeping the VGP field in “stamp-collecting” mode. To allow for future innovation in VGP, there is an urgent need to advance collaboration, increase resource efficiency, and create transferable knowledge in VGP through Integrated, Coordinated, Open, and Networked (ICON) science. In this article, scientists described the elements of, challenges to, and path forward in implementing ICON principles within VGP.

The Impact

Advancing collaboration and resources in the field of geoscience can close knowledge gaps and break barriers that limit scientific development and progress in addressing global issues. A team of researchers advocated for the development of an international network-of-networks framework that can create meaningful connections with all relevant groups represented and working together as equals. This framework can mobilize the scientific community and serve as a foundation for a more international, collaborative, and open science model underpinned by strong communication channels.

Summary

This article belongs to a collection of commentaries (Goldman et al., 2021, https://doi.org/10.1029/2021ea002099) spanning geoscience on the state and future of Integrated, Coordinated, Open, and Networked (ICON) science. To implement ICON principles in VGP, researchers advocated for an open, inclusive, collaborative and evolving model of an international coordinated network. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that can contribute to more innovative ways of coordinating and sharing research. Establishing ICON in VGP also entails implementing effective measures to enhance access to funding, equipment, resources, and mentors that can optimize equity and advancement in the earth sciences.

Citation

Arora, B., Currin, A., Dwivedi, D., Fru, M.I.N., McLeod, C.L. and Roman, D.C., “Volcanology, Geochemistry, and Petrology Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science”. Earth and Space Science 9: 4 (2022), DOI: 10.1029/2021EA002120

Digital elevation model of the East River Watershed, overlain by an aerial photograph and geophysical data used in this study.

The Science

Because they provide more than half of earth’s freshwater, mountainous watersheds are often referred to as the world’s “water towers”. Climate change can influence watershed function and how they provide water to communities downstream. To predict the impact of this change, scientists must understand how water flows in the ground and how the earth’s properties affect this flow. However, measuring the earth’s properties is difficult – especially over a large area. Researchers have tested how to use observations from space or from the air to estimate the earth’s properties. The team demonstrates this method at a mountainous watershed close to Crested Butte, CO, one of the best characterized watersheds in the world. The team demonstrates that, although the relationships are complex, the earth’s subsurface properties vary with properties on the earth’s surface, such as the angle of hillslopes, their gradient, elevation, and the vegetation that grows on them. Using these relationships, researchers can predict what the subsurface looks like and map features in the subsurface that are controlling groundwater flow.

The Impact

Protecting and monitoring groundwater is becoming increasingly critical in light of climate change and prolonged droughts. Understanding how the subsurface is impacting groundwater flow is crucial to predict how this resource may change over time and to develop management approaches. This research shows that critical subsurface properties can be predicted from observations of the Earth’s surface, which are much easier to measure. Knowing the Earth’s properties will eventually lead to a better management of groundwater resources and drought resilience.

Summary

Bedrock measurements are critical for predicting the hydrological response of watersheds to climate disturbances. However, estimating how water flows in the bedrock over watershed scales is difficult, particularly in areas where bedrock may be cracked. By linking data from subsurface and surface measurements, researchers used machine learning to test the covariability of above and belowground features throughout an entire watershed. The team studied the relationships between bedrock properties, surface formation features, and vegetation to show that relationships derived from machine learning can estimate most of their covariability. Using these relationships, the team predicted the bedrock properties across the watershed and showed that regions of lower variability provide better estimates. The results emphasize that this integrated approach can be used to derive bedrock characteristics on a smaller-scale, allowing for a better understanding of subsurface variations across an entire watershed. Knowing how bedrock may vary with surface properties may be critical to assess the impact of disturbances on freshwater function in these ecosystems.

Citation

Uhlemann, et al., Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics. Science Advances 8 (2022). [DOI: 10.1126/sciadv.abj2479]

From subsurface microbiology to above-ground ecosystem cycles and functioning, the progression of DOE-supported science has advanced understanding of environmental features and how they interact at different levels and scales.
Image by Diana Swantek, LBNL

The Science

Accessible and clean freshwater resources, including groundwater and prominent rivers worldwide, are dwindling because of contaminant and nutrient loads. Understanding how various contaminants move through, and affect, the environment is key to ensuring water security. For decades, the Department of Energy has significantly contributed to the progress of environmental sciences and has addressed challenges affecting Earth’s subsurface, such as treating radioactive waste and toxic chemicals in the environment. The researchers’ review manuscript presents insights from DOE-supported research that can be applied worldwide to examine the fate and effect of various contaminants and nutrients in freshwater systems.

The Impact

An estimated 65 percent of the human population lives in water-stressed regions. Freshwater resources supporting millions of people are becoming increasingly contaminated, posing a serious problem to developing a water-secure future. Here, the researchers summarized approximately 500 DOE-funded articles published from the late 1990s through today. The team explored implications of findings ranging from microbiology to large-scale ecosystem nutrient and chemical functioning in order to recommend future research directions. This review article is the first of its kind, referring to information gained across seven DOE research sites including the Savannah River Site in South Carolina, Oak Ridge Reservation in Tennessee, Hanford in Washington, Nevada National Security in Nevada, Riverton in Wyoming, and Rifle and East River in Colorado to synthesize the DOE Biological and Environmental Research (DOE BER) leading contributions to ecosystem sciences. This review also demonstrates how improved understanding of ecosystem functioning – from the subsurface to the atmosphere – has advanced knowledge critical to address issues of water contamination.

Summary

Water security is critical for human health, food and energy production, and economic development. As the Earth’s population reaches nine billion, the demand for freshwater resources has intensified. However, climate change may lead to changes in hydrology and disturbances such as wildfires, droughts, floods, and land-use changes that can impact water availability and quality. DOE-funded research has significantly contributed to progressing environmental sciences since the late 1980s. Findings from this research have addressed groundwater quality issues, such as treating radioactive waste and toxic chemicals. These efforts have developed an advanced understanding of ecosystem processes, valuable field monitoring strategies, predictive capabilities, and approaches that consider data at different scales to efficiently tackle the complexity of Earth’s ecosystems. Researchers have synthesized and documented these scientific advancements to generalize and apply them to a range of global water security problems.

Citation

Dwivedi, D., Steefel, C. I., Arora, B., Banfield, J., Bargar, J., Boyanov, M. I., Brooks, S. C., Chen, X., Hubbard, S. S., Kaplan, D. I., Kemner, K. M., Nico, P. S., O’Loughlin, E. J., Pierce, E. M., Painter, S. L., Scheibe, T. D., Wainwright, H. M., Williams, K. H., and Zavarin, M. From legacy contamination to watershed systems science: a review of scientific insights and technologies developed through DOE-supported research in water and energy security. Environmental Research Letters, Accepted, 2022, DOI: 10.1088/1748-9326/ac59a9

Biogeoscience is an interdisciplinary field, meaning it relates to multiple branches of knowledge. ICON principles are needed to address global problems – however, various challenges hinder ICON in biogeosciences, such as cultural and institutional barriers that prevent data sharing and cross-border collaborations. Scientists recommended short- and long-term solutions based on actions people can take to break these barriers.

The Science

Many environmental challenges such as climate change are global in scope and surpass national boundaries (Figure 1). These challenges involve local-to-global ecosystem processes (e.g., carbon or nitrogen cycling) that require observations across spatial scales. Tackling these grand challenges requires actions that are Integrated, Coordinated, Open, and Networked (ICON). A team of scientists lists several opportunities for ICON science, including organized experimentation and field observation across global sites to advance science and social progress.

The Impact

Biogeoscience requires multiscale global data and joint international community efforts to tackle environmental challenges. However, several technical, institutional, and cultural hurdles have remained major roadblocks toward scientific progress. ICON science aims to address these challenges and create transferable knowledge. In this article, researchers combine three related commentaries about the state of ICON science. They discuss the need to reduce geographical bias in data for enhancing scientific progress. The team identified actions people can take such as engaging local stakeholders across the globe, incentivizing collaborations, and developing training and workshops to advance biogeosciences.

Summary

Researchers combined three independent commentaries about the state of ICON principles and discussed the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (a) Global collaboration, technology transfer, and application, (b) Community engagement, community science, education, and stakeholder involvement, and (c) Field, experimental, remote sensing, and data research and application. To implement ICON principles in biogeosciences, the team calls for a suite of short and long-term actions, with an approach toward capacity building, cultural shifts, breaking barriers through reduced entry costs, building research networks, and promoting community engagement with open and fair research practices. They also suggest developing methods and instrumentation to confront global challenges and solve key questions in biogeosciences.

Citation

Dwivedi, D., Santos, A. L. D., Barnard, M. A., Crimmins, T. M., Malhotra, A., Rod, K. A., et al. (2022). Biogeosciences perspectives on Integrated, Coordinated, Open, Networked (ICON) science. Earth and Space Science, 9, e2021EA002119. DOI: 10.1029/2021EA002119

General overview of the Distributed Temperature Profiling (DTP) system (left) and example of collected soil and snow temperature data (right). The DTP system can be assembled in various lengths and provides measurements of snow thickness and temperature, soil temperature, and the depth of frozen and thawed soil layers.

The Science

Measuring soil and snow temperature at varying depths with high accuracy is critical to better predict and understand water and carbon fluxes. Temperature measurements of layers throughout snow and soil depths help scientists understand temperature fluctuations, heat and water fluxes, frozen and thawed soil depth, and snow thickness – all of which are essential to understand as earth’s temperature changes. However, obtaining these measurements in numerous locations with a high level of detail is difficult due to their total cost, the challenge of obtaining accurate measurements, and the potential disturbance caused by installation. This study presents the development and importance of a novel Distributed Temperature Profiling (DTP) system that makes it possible to measure temperature of soil and snow at varying depths in greater detail to address these challenges.

The Impact

With climate warming, soil temperature and snowpack is predicted to change, which can largely impact the global carbon cycle, terrestrial ecosystem functioning, and freshwater resources. Scientists developed a DTP system and demonstrated its potential for measuring soil and snow temperature at varying depths with a newly developed level of detail, high accuracy, and low cost, while also minimizing energy consumption and the effects of installation. Soil and snow temperature data are gathered with a high spatial resolution to capture both changes in snow depth and the thickness of soil freezing and thawing layers. This development can help improve scientists’ ability to predict and understand the heat and water fluxes in snow and soil across watershed scales, which is essential for assessing and managing water resources and how the global carbon cycle may be impacted by soil warming.

Summary

Studying ecosystems on multiple scales is required to better understand the complex behavior of the environment in a changing climate. To study thermal dynamics and temperature distribution in snowpack and soil, scientists have developed a DTP system – an efficient and easy-to-install sampling method that provides detailed and accurate temperature measurements at varying depths with a low cost.

The system provides depth-profiles of temperature measurements at newly detailed resolutions, and also enables automated data acquisition, management, and wireless transfer to other devices and computers. A novel calibration approach confirms an accuracy of up to +/– 0.015 ºC, which will allow scientists to better understand how temperature varies in the depth of snow and soil, enabling improved predictions of how rising temperatures may influence these resources and ultimately ecosystem health and functioning. By using the system in various environments, scientists showed that the DTP system reliably captures temperature dynamics throughout snow depth and the depth of frozen and thawed soil layers. This study advances understanding of how the intensity and timing in surface processes impacts below-ground temperature distribution. The development of the DTP system is an important step toward optimizing environmental data accuracy and modeling at low cost.

Citation

Dafflon, B., Wielandt, S., Lamb, J., McClure, P., Shirley, I., Uhlemann, S., Wang, C., Fiolleau, S., Brunetti, C., Akins, F.H., Fitzpatrick, J., Pullman, S., Busey, R., Ulrich, C., Peterson, J. and Hubbard, S.S., A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature. The Cryosphere 16(2), 719-736, 2022. https://doi.org/10.5194/tc-16-719-2022

Conceptual figure showing how the BASIN-3D broker would connect to various data sources across organizations and present an integrated view of the data to the user.
Figure from BASIN-3D Documentation

The Science

Earth data include measurements and model results of physical, chemical, and biological processes in ecosystems. The data are diverse and often stored across many databases, with different formats and conventions. BASIN-3D is a tool that helps lower the burden on scientists to integrate data for their research. It is designed as a “broker” that retrieves data on demand from different sources and transforms it into a unified view. This paper presents two applications of BASIN-3D to integrate time series (data collected at different time intervals). The first is for advanced search and exploration of data on a web portal. The second is to provide data to machine learning models for water quality predictions.

The Impact

The BASIN-3D software helps address some critical challenges faced by environmental researchers who use data from public and private sources. It helps automate the process of pulling together data from different sources. Thus it enables users to have access to the latest data available from providers of their choice, without having to manually download data and reconcile differences. This software can be used to support data integration for both web-based tools, as well as data analytics. It is applicable to environmental field and modeling studies requiring data integration.

Summary

Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) as a data brokering approach to reduce the data processing burden on scientists. BASIN-3D can synthesize diverse data from different sources on demand, without the need for additional storage. BASIN-3D is currently implemented to integrate time series earth observations across a hierarchy of spatial locations commonly used in field measurements (such as river basins, watersheds, sites, plots, wells). It has a framework to enable its users to map data sources of interest to a common format. The utility of this tool is demonstrated in two applications. The first is a web portal that allows scientific users to explore and access data through features such as an interactive map, graphs, and download. The second is a python package that can be embedded in scripts to input data to machine learning models for water quality predictions. Hence BASIN-3D can be used to support data integration for both web-based tools as well as data analytics.

Citation

Varadharajan, C. et al. BASIN-3D: “A brokering framework to integrate diverse environmental data”. Computers & Geosciences 105024 (2022) [DOI:10.1016/j.cageo.2021.105024].

Conceptual figure showing how the BASIN-3D broker would connect to various data sources across organizations and present an integrated view of the data to the user.

The Science

Earth data include measurements and model results of physical, chemical, and biological processes in ecosystems. The data are diverse and often stored across many databases, with different formats and conventions. BASIN-3D is a tool that helps lower the burden on scientists to integrate data for their research. It is designed as a “broker” that retrieves data on demand from different sources and transforms it into a unified view. This paper presents two applications of BASIN-3D to integrate time series (data collected at different time intervals). The first is for advanced search and exploration of data on a web portal. The second is to provide data to machine learning models for water quality predictions.

The Impact

The BASIN-3D software helps address some critical challenges faced by environmental researchers who use data from public and private sources. It helps automate the process of pulling together data from different sources. Thus it enables users to have access to the latest data available from providers of their choice, without having to manually download data and reconcile differences. This software can be used to support data integration for both web-based tools, as well as data analytics. It is applicable to environmental field and modeling studies requiring data integration.

Summary

Earth scientists expend significant effort integrating data from multiple data sources for both modeling and data analyses. We introduce BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) as a data brokering approach to reduce the data processing burden on scientists. BASIN-3D can synthesize diverse data from different sources on demand, without the need for additional storage. BASIN-3D is currently implemented to integrate time series earth observations across a hierarchy of spatial locations commonly used in field measurements (such as river basins, watersheds, sites, plots, wells). It has a framework to enable its users to map data sources of interest to a common format. The utility of this tool is demonstrated in two applications. The first is a web portal that allows scientific users to explore and access data through features such as an interactive map, graphs, and download. The second is a python package that can be embedded in scripts to input data to machine learning models for water quality predictions. Hence BASIN-3D can be used to support data integration for both web-based tools as well as data analytics.

Citation

Varadharajan, C. et al. BASIN-3D: “A brokering framework to integrate diverse environmental data”. Computers & Geosciences 105024 (2022) [DOI:10.1016/j.cageo.2021.105024].

The Watershed zonation method applies unsupervised clustering to various spatial data layers for grouping hillslopes with similar above/below-ground environmental features

The Science

More than half of earth’s freshwater comes from mountainous watersheds. Watersheds are a “system of systems,” meaning there are many interacting compartments – such as bedrock, soil, and snow plants – that affect their functioning. Predicting watershed behavior is challenging because there are different environmental processes and characteristics– both at different scales and levels, from bedrock to the atmosphere– that affect watershed function and water quality. To understand how watersheds may respond to droughts as climate changes, researchers used data from the Colorado East River Watershed to develop a watershed zonation approach–a method that uses machine learning to characterize entire watersheds by grouping zones of similar functioning and characteristics, like watershed “zip codes.” The team grouped hillslopes specifically since these features are a functional unit in hydrology, capturing waterflow and a range of environmental characteristics like elevation, topography, and vegetation. This method not only combines data of multiple state-of-the-art arbonne remote sensing data layers of multiple types and scales to identify zones with similar bedrock-to-canopy features, but also shows how these areas respond to disturbances in different ways to advance holistic and large-scale predictions of watershed response to change.

The Impact

Watershed function can significantly impact energy production, agriculture, and water quality and availability. Now that environmental disturbances such as drought, wildfires, and floods mark what many have called a “new normal” state, scientists can no longer depend on historical trends to project future watershed behavior, but instead need to develop new approaches to studying watershed response to environmental changes. However, predicting watershed behavior is challenging because watersheds are extremely heterogeneous including the complex interactions taking place across different Earth compartments from tree canopy to the deep subsurface as well as from one hillslope in a watershed to another. – Using machine learning, researchers organized the watershed research site into zones based on similar environmental features, and were able to show how different zones process/export nutrients and respond to droughts. By using multiscale spatial data layers to capture different characteristics throughout a watershed, this approach allows for more accurate large-scale predictions of watershed responses to climate change. Understanding these responses is critical for managing and protecting critical freshwater resources as water demand continues to increase.

Summary

In this study, we develop a watershed zonation approach for characterizing watershed organization and function in a tractable manner by integrating multiple spatial data layers. We hypothesize that (1) a hillslope is an appropriate unit for capturing the watershed-scale heterogeneity of key bedrock-through-canopy properties, and for quantifying the co-variability of these properties representing coupled ecohydrological and biogeochemical interactions; (2) remote sensing data layers and clustering methods can be used to identify watershed hillslope zones having the unique distributions of these properties relative to neighboring parcels; and (3) property suites associated with the identified zones can be used to understand zone-based functions, such as response to early snowmelt or drought, and solute exports to the river. We demonstrate this concept using unsupervised clustering methods that synthesize airborne remote sensing data (LiDAR, hyperspectral, and electromagnetic surveys) along with satellite and streamflow data collected in the East River Watershed, Crested Butte, Colorado, USA. Results show that (1) we can define the scale of hillslopes at which the hillslope-averaged metrics can capture the majority of the overall variability in key properties (such as elevation, net potential annual radiation and peak SWE), (2) elevation and aspect are independent controls on plant and snow signatures, (3) near-surface bedrock electrical resistivity (top 20 m) and geological structures are significantly correlated with surface topography and plan species distribution, and (4) K-means, hierarchical clustering, and Gaussian mixture clustering methods generate similar zonation patterns across the watershed. Using independently collected data, we show that the identified zones provide information about zone-based watershed functions, including foresummer drought sensitivity and river nitrogen exports. The approach is expected to be applicable to other sites and generally useful for guiding the selection of hillslope-experiment locations and informing model parameterization.

Citation

Wainwright, H. M., Uhlemann, S., Franklin, M., Falco, N., Bouskill, N. J., Newcomer, M., … & Hubbard, S. S. (2022). Watershed zonation approach for tractably quantifying above-and-belowground watershed heterogeneity and functions. Hydrol. Earth Syst. Sci., 26, 429–444, 2022, DOI: 10.5194/hess-26-429-2022.