Foresummer drought sensitivity of Landsat Peak NDVI. The black lines are the boundaries of the four watersheds: Coal Creek, Slate River, Washington Gulch and East River from left to right.

Ecosystems in headwater catchments are important for water resources downstream, regulating evapotranspiration and nutrient cycling. This paper mapped where the plants are more sensitive to early summer (or foresummer) drought conditions, and also identified key controls on drought resilience such as geomorphology and geology in addition to elevation and aspect.

This study mapped the spatial heterogeneity of plants’ drought sensitivity, based on the historical Landsat images and climate data. Using machine learning methods, the authors identified key controls on drought sensitivity, related to surface energy exchanges (i.e., potential net radiation), hydrological processes (i.e., microtopography and slope), and underlying geology. This remote-sensing-based approach can be used to identify the regions that are vulnerable or resilient to climate perturbations, as well as to inform future sampling, characterization, and modeling studies.

Summary

Ecosystems in headwater catchments are important for water resources downstream, regulating evapotranspiration and nutrient cycling. Climate model ensembles predict earlier snowmelt and reduced spring precipitation in the western North America, which creates “foresummer” droughts in the primary growing season of plants. This study (1) assessed the importance of early snowmelt and foresummer drought in controlling peak plant productivity, based on the historical Landsat normalized difference vegetation index (NDVI) and climate data; (2) mapped the spatial heterogeneity of drought sensitivity over the watershed-scale; and (3) identified the environmental controls on drought sensitivity within the East Water watershed (Colorado, USA). In support of the plot-based studies, results showed that that years with earlier snowmelt and drier foresummer conditions lead to lower peak NDVI; particularly in the low-elevation regions. In addition, the foresummer drought sensitivity is spatially heterogeneous, and primarily dependent on the plant type and elevation. Using machine learning methods, we identified additional key controls related to surface energy exchanges (i.e., potential net radiation), hydrological processes (i.e., microtopography and slope), and underlying geology. This remote-sensing-based approach for quantifying foresummer drought sensitivity can be used to identify the regions that are vulnerable or resilient to climate perturbations, as well as to inform future sampling, characterization, and modeling studies.

Citation

Wainwright, H. M. et al. (2020). Satellite-derived foresummer drought sensitivity of plant productivity in Rocky Mountain headwater catchments: spatial heterogeneity and geological-geomorphological control. Accepted in Environmental Research Letters. DOI: 10.1088/1748-9326/ab8fd0

Systematic integration of emerging technologies into watershed network and collaboration strategies hold potential to significantly advance predictive understanding of watershed hydrobiogeochemical behavior.

This invited commentary documented how the emerging technologies listed above are starting to advance key elements important for predicting watershed hydrobiogeochemical behavior, including watershed characterization, data and informatics, and modeling. The commentary also described and recommended a systematic community development of co-design strategies, whereby the emerging technologies could seamlessly weave together characterization, data and modeling capabilities across scales, enabling two-way, near-real time feedback between observation and modeling systems.

While society depends on watersheds for clean water, energy, agricultural productivity and other benefits, state-of-the-art scientific tools are not yet regularly used to underpin resource management. Recent advances in emerging technologies – together with instrumented watershed observatories, open-science principles and new modes of collaboration – offer significant potential to transform our ability to address complex scientific questions, develop generalizable insights, and propel accurate yet tractable approaches to predict watershed hydrobiogeochemical behavior. As resource managers struggle to make increasingly difficult decisions in the coming decades, we hope that the concepts described in this commentary will mobilize the scientific enterprise toward the systematic developments needed to provide actionable information over space and time scales useful for such decisions.

Summary

Several emerging technologies are now starting to reveal their promise for greatly enhancing the predictive understanding of watershed hydro-biogeochemical behavior, including machine learning and artificial intelligence, exascale computing, 5G wireless communications, and cloud data storage and compute capacity. We describe a co-design strategy to unify diverse characterization, data and simulation capabilities, allowing near real-time, autonomous communication and feedback between modelling and field observation systems. Paired with watershed observatory networks, open science principles, and radical collaboration strategies, the co-design strategies are expected to enable rapid progress on challenging scientific questions, such as: how do different types of watersheds respond to different stressors, such as climate change, droughts, floods, wildfire, and land-use? How will multiple stressors impact sustainability of municipal, industry, food, and energy systems that rely on water? Can generalizable metrics of resilience be identified and tracked? What is the minimum but sufficient amount of information needed to predict watershed behavior at temporal and spatial scales critical for underpinning resource management decisions? While systematic incorporation of emerging technologies and adoption of new modes of collaboration will require substantial coordination, resources and commitment to overcome technical, social, and organizational barriers, we are encouraged by the many recent efforts focused on advancing collaborations and tools across watershed communities, observatories, and government agencies.

Citation

Hubbard, S.S., C. Varadharajan, Y. Wu, H. Wainwright and D. Dwivedi, Emerging technologies and radical collaboration to advance predictive understanding of watershed hydrobiogeochemistry, Hydrological Processes, 35, DOI: 10.1002/hyp.13807

A series of hypothetical numerical experiments with and without lateral groundwater flow is performed to isolate the role of lateral groundwater flow which are often over-simplified in traditional hydrologic model. Results show that that peak flows increase up to 57% when lateral groundwater flow processes are included.

The Upper Colorado River Basin (UCRB) is subject to climate extremes that pose a challenge to simulate and predict. Open questions remain about the correct model physical parameterization for accurate simulation of large, headwaters systems with a mix of terrain. Results show that including lateral groundwater flow component not only improving simulation accuracy but also quantifying the role of subsurface hydrological processes.

Stream flow time series for two representative stations in the Upper Colorado River Basin. Blue lines are observed daily flow, red and green lines are simulated flows from lateral and no lateral simulations respectively.

Summary

The Upper Colorado River Basin (UCRB) is subject to climate extremes that pose a challenge to simulate and predict. Open questions remain about the correct model physical parameterization for accurate simulation of large, headwaters systems with a mix of terrain. This study focusses on the role of lateral groundwater flow on total annual and peak streamflow in the UCRB using a physical hydrology model, ParFlow. Results for the simulated water year of 1983 (the high snowmelt year that almost destroyed the Glen Canyon Dam), suggest an increase in peak flow of up to 57% when lateral groundwater flow processed are included. This is an unexpected result for flood conditions, which are generally assumed to be independent of groundwater. Including lateral groundwater flow produces 25% to 50% more the larger downstream rivers in the domain and 20% to 40% less flow in headwater streams. These changes are mainly driven by hydraulic gradients in the subsurface which are often over-simplified in traditional hydrology models and can only be captured when lateral flow is considered. Lastly, the authors find that the impact of including lateral groundwater flow on the simulated flows exceeds the impact of an order of magnitude change in hydraulic conductivity. While the results focus on the UCRB, the authors feel that these simulations have relevance to other headwater systems worldwide.

Citation

Tran, H., J. Zhang, J.-M. Cohard, L. E. Condon, and R. M. Maxwell (2020), Simulating Groundwater-Streamflow Connections in the Upper Colorado River Basin, Groundwater, 58(3), 392-405, DOI: 10.1111/gwat.13000.

Multiresolution meshes are generated using a single error-threshold criterion, e.g. error in the approximation of topographic slope, thereby reducing the number of free parameters needed by other approaches. In the Lower Triangle Region of the East River CO watershed, two of such criteria are chosen: topographic slope and topographic curvature. Simulation results show that using curvature as refinement criteria is preferable in mountainous catchments.

The approach to generate multiresolution meshes is general in that it can be used with different criteria to refine a given mesh. Thus, it will make it possible to generate meshes to obtain accurate results for a broad range of processes.

Ponding water depth computed on the multiresolution meshes generated by a slope-based refinement criterion (left); and a curvature-based refinement criterion (right).

Summary

Multiresolution mesh generation usually utilizes a number of free parameters, which are tuned in a rather empirical manner. This study uses wavelet analysis—a mathematical method for signal analysis—to reduce the number of free parameters to exactly one: the acceptable error threshold. The authors apply the wavelet analysis on bed slope and the bed curvature to generate multiresolution meshes for high-intensity overland flow simulations. Case studies ranging from laboratory scale experiments to a sub-catchment of the East River Watershed, CO were carried out to compare results obtained on these meshes. For the latter case, computational results show that meshes generated by the curvature-based criterion give a more accurate prediction of stream discharge, which implies that in mountainous watersheds these flow processes are controlled by the curvature of the terrain. The wavelet approach is general enough to be used for different criteria to drive mesh refinement in addition to the ones demonstrated in the manuscript.

Citation

Özgen-Xian, I., G. Kesserwani, D. Caviedes-Voullième, S. Molins, Z. Xu, D. Dwivedi, J. D. Moulton, and C. I. Steefel (2020), Wavelet-based local mesh refinement for rainfall–runoff simulations, Journal of Hydroinformatics, DOI: 10.2166/hydro.2020.198.

Schematic of the biogeochemical pathways cycling nitrogen at the capillary fringe of the Rifle floodplain, Colorado.

Alluvial sediments subject to the seasonal rise and fall of groundwater are regions of outsized biogeochemical activity relative to their spatial extent in many floodplain environments. This study documents significant changes in the nitrogen cycle under fluctuating hydrological conditions.

This manuscript significantly improves our understanding of the global nitrogen cycling by using natural abundance stable isotopes to document pathways and mechanisms leading to the accumulation and dissipation of nitrate under aerobic and anaerobic conditions.

Summary

In the current study, researchers characterize the nitrogen biogeochemistry of the subsurface at the Rifle Field Site, Colorado, as snowmelt driven fluctuations in water table depth change the saturation profile of the vadose zone sediments and hence their redox status. Depth-resolved water samples were collected over the course of a year with analysis of porewater nitrogen concentrations, nitrous oxide and nitrogen gas, and the natural abundance stable isotopes of nitrate (15NNO3 and (18ONO3) used to determine the role that abiotic and biological mechanisms play in the fate of nitrate. The study concludes that biological nitrogen cycling in Rifle sediments was predominantly attributable to temporally uncoupled nitrification-denitrification reactions. These reactions occur sequentially as aerobic conditions, favoring nitrification and the accumulation of nitrate, give way to anaerobic conditions, which favor denitrification rather than anaerobic ammonium oxidation, as the water table rises.

Citation

Bouskill, N. J., M. E. Conrad, M. Bill, E. L. Brodie, Y. Cheng, C. Hobson, M. Forbes, K. L. Casciotti, and K. H. Williams (2019), Evidence for Microbial Mediated NO3− Cycling Within Floodplain Sediments During Groundwater Fluctuations, Frontiers in Earth Science, 7(189), DOI: 10.3389/feart.2019.00189.

Photo: Root ingrowth cores were made out of nylon mesh (2-mm mesh size) which allowed roots to grow into and colonize the soil core. Root exclusion cores were made out of finer-sized nylon mesh (50-µm mesh size) that prevented root colonization.

Rising winter air temperatures are reducing seasonal snow cover in many temperate ecosystems, but the role of plant roots in moderating the impact of snowpack loss on bacterial or fungal communities remains poorly resolved. This study showed that declining winter snowpack and impacts to plant roots have direct effects on the diversity and abundance of soil bacteria and fungal communities with important consequences for N cycling in northern hardwood forests.

Summary

Impacts to soil biogeochemical processes have been investigated as they pertain to climate induced warming, with temperature increases having impacts on snow-dominated systems including reduced snowpack and early onset of melt. Little work to date has focused on the role that roots play in enhancing or moderating nutrient cycling in soils by bacteria and fungi. To address this gap in knowledge, root ingrowth and exclusion cores (216 cores total) were incubated in situ for 29 months at the Hubbard Brook Experimental Forest in central New Hampshire (USA) that has experienced winter snowpack decline over the past 50 years. Both a declining winter snowpack and its effect on plant roots each had a direct effect on the diversity and abundance of soil bacteria and fungal communities and interacted to reduce rates of soil N cycling in this northern hardwood forest. Such results are thought to be broadly relevant to other temperate ecosystems where climate change and climate disturbance are impacting snowpack, such as many mountainous regions worldwide.

Citation

Sorensen, P. O., J. M. Bhatnagar, L. Christenson, J. Duran, T. Fahey, M. C. Fisk, A. C. Finzi, P. M. Groffman, J. L. Morse, and P. H. Templer (2019), Roots Mediate the Effects of Snowpack Decline on Soil Bacteria, Fungi, and Nitrogen Cycling in a Northern Hardwood Forest, FRONTIERS IN MICROBIOLOGY, 10, DOI: 10.3389/fmicb.2019.00926.

Subsurface flow and transport. a. Seasonal variation in subsurface flow. b. Flow rates along soil, weathering zone, and bedrock. c. Seasonality of subsurface flow and specific conductance (SC) of discharging water. d. Concentration–discharge relation for SC.

Quantifying connections between snowmelt infiltration and seasonal variations in solute export to surface waters is frequently confounded by a lack of critical measurements. This study introduces a novel approach whereby distributions of fluid flow paths are highly resolved through the use of critical subsurface measurements to reveal their strong temporal sensitivity to snowpack accumulation and melt timing.

This study presents a novel methodological approach to quantify how hillslope subsurface flow and chemical transport contribute to stream flow and water quality.

Summary

Although most of the water entering watersheds permeates through soil and underlying bedrock before entering rivers, subsurface flow paths and their influence on river water chemistry are poorly understood. This study presents a new framework for quantifying depth- and time-dependent subsurface flow and solute transport along an intensively studied hillslope that utilizes in-situ hydrologic and geochemical measurements to constrain predictions. Results quantify the importance of abrupt groundwater excursions accompanying snowmelt for mobilizing dissolved chemicals in soil and weathered bedrock, with the latter responsible for the greatest contribution to solute export. The new concept of subsurface concentration-discharge relations was developed through this work that provides information needed to mechanistically explain solute concentrations and flow measured in rivers. With information on topography, meteorology, and subsurface hydraulic properties, this framework is broadly transferrable to other hillslope and watershed settings.

Citation

T.K. Tokunaga et al., “Depth- and time-resolved distributions of snowmelt-driven hillslope subsurface flow and transport and their contributions to surface waters.” Water Resources Research 55, 9474-9499 (2019). [DOI:10.1029/2019WR025093].