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Forested areas exhibit high spatial variability in the distribution of snow water equivalent (SWE). Previous work has focused on forested areas with respect to snow accumulation in adjacent clearings. There is generally less snow in forested areas with greater variability relative to open areas due to the influence of tree canopies. However, the length scale of the transition from open areas to forested conditions is uncertain. Hence, the goal of this paper is to determine the length scales associated with forest boundary effects on SWE accumulation distribution patterns within forest stands. To accomplish this, we utilize a unique ground‐penetrating radar data set collected during the NASA SnowEx campaign on Grand Mesa, Colorado, in February 2017 to determine spatial SWE distribution patterns of areas under canopy and in clearings, and the length scales of transitions between these patterns (i.e., the size of within‐stand boundary areas). We define within‐stand boundary areas as the transitional zone from a clearing to relatively stable SWE distribution, or background distribution patterns, within forest stands. The largest within‐stand boundary effect occurred on the leeward side of stands with a mean extent of 44 m, or 4.3 mean canopy heights. In contrast, windward within‐stand boundary effects showed a mean extent of 28 m, or 3.7 mean canopy heights. We present a conceptual framework of the complex wind dynamics that occur in forest stands to explain the within‐stand boundary effects on SWE distribution. Future investigations could improve understanding of this complex process and associated driving variables. Key Points: Boundary effects extend into forested areas 3.7 and 4.3 mean canopy heights on windward and leeward sides of stands, respectivelyThese effects are a result of complex wind dynamics including eddies and spatially varying effective roughness near forest boundariesSWE variability is significantly different in forest boundary affected areas relative to background under canopy variability [ABSTRACT FROM AUTHOR]

Abstract: Groundwater is a critical input to agricultural production across the globe. Current groundwater pumping rates frequently exceed recharge, often by a substantial amount, leading to groundwater depletion and potential declines in agricultural profits over time. As a result, many regions reliant on irrigated agriculture have proposed policies to manage groundwater use. Even when gains from aquifer management exist, there is little information about how policies affect individual producers sharing the resource. In this paper, we investigate the variability of groundwater management policy impacts across heterogeneous agricultural producers. To measure these impacts, we develop a hydroeconomic model that captures the important role of well capacity, productivity of water, and weather uncertainty. We use the model to simulate the impacts of groundwater management policies on producers in the High Plains aquifer of eastern Colorado and compare outcomes to a no‐policy baseline. The management policies considered include a pumping fee, a quantity restriction, and an irrigated acreage fee. We find that well capacity and soil type affect policy impacts but in ways that can qualitatively differ across policy type. Model results have important implications for the distributional impacts and political acceptability of groundwater management policies. [ABSTRACT FROM AUTHOR]

Reliable predictions of sediment transport and river morphology in response to variations in natural and human-induced drivers are necessary for river engineering and management. Because engineering and management applications may span a wide range of space and time scales, a broad spectrum of modeling approaches has been developed, ranging from suspended-sediment 'rating curves' to complex three-dimensional morphodynamic models. Suspended sediment rating curves are an attractive approach for evaluating changes in multi-year sediment budgets resulting from changes in flow regimes because they are simple to implement, computationally efficient, and the empirical parameters can be estimated from quantities that are commonly measured in the field (i.e., suspended sediment concentration and water discharge). However, the standard rating curve approach assumes a unique suspended sediment concentration for a given water discharge. This assumption is not valid in rivers where sediment supply varies enough to cause changes in particle size or changes in areal coverage of sediment on the bed; both of these changes cause variations in suspended sediment concentration for a given water discharge. More complex numerical models of hydraulics and morphodynamics have been developed to address such physical changes of the bed. This additional complexity comes at a cost in terms of computations as well as the type and amount of data required for model setup, calibration, and testing. Moreover, application of the resulting sediment-transport models may require observations of bed-sediment boundary conditions that require extensive (and expensive) observations or, alternatively, require the use of an additional model (subject to its own errors) merely to predict the bed-sediment boundary conditions for use by the transport model. In this paper we present a hybrid approach that combines aspects of the rating curve method and the more complex morphodynamic models. Our primary objective was to develop an approach complex enough to capture the processes related to sediment supply limitation but simple enough to allow for rapid calculations of multi-year sediment budgets. The approach relies on empirical relations between suspended sediment concentration and discharge but on a particle size specific basis and also tracks and incorporates the particle size distribution of the bed sediment. We have applied this approach to the Colorado River below Glen Canyon Dam (GCD), a reach that is particularly suited to such an approach because it is substantially sediment supply limited such that transport rates are strongly dependent on both water discharge and sediment supply. The results confirm the ability of the approach to simulate the effects of supply limitation, including periods of accumulation and bed fining as well as erosion and bed coarsening, using a very simple formulation. Although more empirical in nature than standard one-dimensional morphodynamic models, this alternative approach is attractive because its simplicity allows for rapid evaluation of multi-year sediment budgets under a range of flow regimes and sediment supply conditions, and also because it requires substantially less data for model setup and use. [ABSTRACT FROM AUTHOR]

One of the persistent challenges of Land Surface Models (LSMs) is to determine a realistic yet efficient sub‐grid representation of heterogeneous landscapes. This is particularly important in emulating the fine‐scale and nonlinear interactions between water, energy, and biogeochemical fluxes at the land surface. In LSMs, landscape heterogeneity can be represented using sub‐grid tiling techniques, which partition macroscale grid cells (e.g., 1°) into smaller units or "tiles." However, there is currently no formal procedure to define the number of tiles required to adequately represent the heterogeneity of hydrologic processes within a macroscale grid cell, and across spatial scales. To address these challenges, a new approach is presented to diagnose sub‐grid process heterogeneity formally and to infer an optimal number of tiles per macroscale grid cell. The approach is demonstrated using the HydroBlocks modeling framework coupled to Noah‐MP LSM implemented over a 1.0‐degree domain in Western Colorado in the United States. Our results show that (a) a surrogate model can accurately infer the spatial structure of the LSM's time‐averaged hydrological fields, with over 95% overall R2 performance in the validation stage; (b) the optimal configurations for a target level of complexity can be determined using a multi‐objective Pareto efficiency analysis, which includes the simultaneous representation of the multi‐scale heterogeneity of several processes; (c) the use of ∼100 tiles effectively reproduces a quasi‐fully distributed LSM setup (i.e., 83,000 tiles) with approximately 1% of the computational expense. This method provides a path forward to efficiently determine the optimal tile configurations for LSMs while simultaneously considering the spatial heterogeneity and spatial accuracy of hydrologic processes. Key Points: A surrogate model can accurately predict the spatial structure of Land Surface Model's (LSM) hydrological output fieldsFor a target level of complexity, the optimal LSM tile configuration was determined using a multi‐objective Pareto efficiency analysisApproximately 100 tiles can effectively reproduce a quasi‐fully distributed LSM setup with 1% of the computational cost [ABSTRACT FROM AUTHOR]

We use 11 years of annual surveys in streams of the Southern Rockies of Colorado, USA, to examine the persistence and geomorphic effects of logjams. Each year's survey includes ∼300 logjams along more than 21 km of four mountain streams in primarily old‐growth subalpine forest. Streams alternate longitudinally between laterally confined reaches with a single channel and wider reaches with multithread‐channel planform. We distinguish logjam persistence and site persistence. Logjam persistence is the median timespan over which an individual jam is present. Site persistence describes the tendency for jams to disappear and then re‐form at the same site. We hypothesize that (a) site persistence is greatest in multithread reaches, (b) logjam persistence is greatest in multithread reaches, and (c) average backwater storage at each jam is greater in multithread reaches. We find that spatial and temporal metrics of site persistence differ significantly between single and multithread reaches. Individual logjam persistence does not differ significantly. Backwater storage is significantly greater in multithread reaches. Varying combinations of riparian forest age and average logjams per channel length explain variation in jam and site persistence and backwater storage via multivariate linear regression analyses. Over the 11 years of survey, a total of 429 distinct logjams were observed. Only 2.1% of the population was present for all 11 annual surveys. Median jam persistence is 1–2.5 years; median site persistence is 6–10 years. Despite the transience of most channel‐spanning logjams in the population, these jams create persistent effects in channel planform and backwater storage. Key Points: Logjam persistence (the median timespan over which a jam is present during the 11‐year study) is 1–2.5 yearsSite persistence (the median timespan over which at least one jam is present in retentive sites) is 6–10 yearsDespite the transience of most logjams, the jams create persistent effects in channel planform and backwater storage [ABSTRACT FROM AUTHOR]

Bark beetles have impacted over 58 million acres of coniferous forest in the Western US since 2000. Most beetle impacted forests are in snow dominated, water limited headwater basins, which generate a disproportionate fraction of water supplies. Previous studies show mixed impacts of bark beetle outbreaks on streamflow with the potential to cause increased or decreased flows, but these studies either predate long‐term snowpack data, are model‐based, or examine only mountain pine beetle outbreaks. Ours is the first study to use an empirical, climate‐normalized paired catchment approach to quantify streamflow response to spruce beetle kill. Using 27 years of climate and streamflow observations from southwest Colorado, we show that in three of the six beetle impacted study basins, annual climate‐normalized streamflow increased by 22%–37% for at least three to 6 years after the beetle outbreak. Impacted basins exhibited no decreased flows and flows in unimpacted control basins remained unchanged. Among impacted basins, no single basin characteristic clearly explained variation of streamflow response. Higher runoff ratios during snowmelt contribute anywhere from 9% to 64% of streamflow increases, implying the importance of both snow and growing season processes in driving streamflow increases. These findings show variable, sometimes substantial streamflow increases in critical water supply basins following beetle kill in subalpine spruce forests, and contrast with evidence of unchanged or decreased streamflow following beetle kill in lower elevation pine forests in colder northern Colorado basins, highlighting the importance of climate and forest composition in refining hydrologic predictions following mountain forest disturbances. Plain Language Summary: Since 2000, bark beetles have damaged over 58 million acres of conifer forest in the Western US. Forest canopy has large but complex effects on snow and water use in mountain areas, which are important sources of streamflow. Previous studies exploring how beetle kill affects streamflow show mixed results, with some suggesting that beetle kill causes increased streamflow and others finding no significant effects or decreases. We use measurements of streamflow and climate in six beetle impacted basins and two unaffected basins in southwest Colorado to determine if streamflow changed after a spruce beetle outbreak. We found that streamflow increased by 22%–37% in three out of six study basins after beetle kill, while streamflow in unaffected basins did not change. Streamflow increased both during and before/after the snowmelt season. These findings suggest that beetle kill can substantially increase streamflow in ways that are not accounted for in water resource management and planning, but variable response between basins and forest types remains challenging to predict. Key Points: Streamflow increased in three of six mountain basins after a spruce beetle outbreak, while streamflow in control basins remained unchangedAmong impacted basins, no single factor or basin characteristic fully explained variation in streamflow response to beetle killHigher streamflow after spruce beetle contrasts with reported unchanged or lower streamflow after pine beetle in other Colorado basins [ABSTRACT FROM AUTHOR]

Intermittent snow depth observations can be leveraged with data assimilation (DA) to improve model estimates of snow water equivalent (SWE) at the point scale. A key consideration for scaling assimilation to the basin scale is its performance at forested locations—where canopy‐snow interactions affect snow accumulation and melt, yet are difficult to model and parameterize. We implement a particle filter (PF) technique to assimilate intermittent snow depth observations into the Flexible Snow Model, and validate model outputs against snow density and SWE measurements across adjacent forest and open sites, at two locations with different climates and forest structures. Assimilation reduces snow depth error by 70%–90%, density error by 5%–30%, and SWE error by 50%–70% at forest locations (relative to controls). The PF simulates the seasonal evolution of the snowpack under forest canopy, including where interception losses decrease SWE in the forest during accumulation, and shading reduces melt during the ablation season (relative to open sites). Model outputs are sensitive to canopy‐related parameters, but DA reduces the range in snow depth and SWE estimates resulting from variations or uncertainties in these parameters by over 50%. These results demonstrate that the importance of accurately measuring, estimating, or calibrating canopy‐related parameters is reduced when snow depth observations are assimilated. Finally, we assimilate remotely sensed snow depth observations at 50 m resolution across the East River Basin, Colorado (1,000 km2). Across elevations, the PF increases estimated precipitation at forested sites by ∼15% relative to open sites, likely compensating for excessive sublimation of intercepted snow. Key Points: Data assimilation improves modeled snow depth, density, and SWE at forested sites in two contrasting climates and over multiple yearsAssimilation reduces apparent model output sensitivity to forest canopy parameters that are difficult to measure or calibrateAssimilation increases estimated precipitation in the forest relative to the open, likely due to excessive sublimation of intercepted snow [ABSTRACT FROM AUTHOR]

Snowpack accumulation in forested watersheds depends on the amount of snow intercepted in the canopy and its partitioning into sublimation, unloading, and melt. A lack of canopy snow measurements limits our ability to evaluate models that simulate canopy processes and predict snowpack. We tested whether monitoring changes in wind‐induced tree sway is a viable technique for detecting snow interception and quantifying canopy snow water equivalent (SWE). Over a 6 year period in Colorado, we monitored hourly sway of two conifers, each instrumented with an accelerometer sampling at 12 Hz. We developed an approach to distinguish changes in sway frequency due to thermal effects on tree rigidity versus intercepted snow mass. Over 60% of days with canopy snow had a sway signal that could not be distinguished from thermal effects. However, larger changes in tree sway could not generally be attributed to thermal effects, and canopy snow was present 93%–95% of the time, as confirmed with classified PhenoCam imagery. Using sway tests, we converted changes in sway to canopy SWE, which were correlated with total snowstorm amounts from a nearby SNOTEL site (Spearman r = 0.72 to 0.80, p < 0.001). Greater canopy SWE was associated with storm temperatures between −7°C and 0°C and wind speeds less than 4 m s−1. Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. Monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and distinguishing thermal and snow mass effects on tree sway. Key Points: Six years of tree sway data from accelerometers on two conifers revealed changes in sway frequency at sub‐daily to seasonal scalesAfter accounting for thaw‐freeze cycles, changes in tree sway due to snow interception were detected and checked with time‐lapse imagesSway data yielded canopy snow mass estimates consistent with snowfall data and storm conditions [ABSTRACT FROM AUTHOR]

The flow of organic matter (OM) along rivers and retention within floodplains contributes significantly to terrestrial carbon storage and ecosystem function. The storage and cycling of OM largely depend upon hydrogeomorphic characteristics of streams and valleys, including channel geometry and the connectivity of water across and within the floodplain. To examine the role of river morphology on carbon dynamics in mountain streams, we (a) quantify organic carbon (OC) storage in fine sediment, litter, and wood along 24 forested gravel‐bed stream reaches in the Rocky Mountains of CO, USA, (b) examine morphological factors that regulate sediment and OC storage (e.g., channel width, slope, logjams), and (c) utilize fluorescence spectroscopy to examine how the composition of fluorescent dissolved OM in surface water and floodplain fine sediment are influenced by channel morphology. Multivariate regression of the study reaches, which have varying degrees of confinement, slope, and elevation, indicates that OC storage per area is higher in less confined valleys, in lower gradient stream reaches, and at higher elevations. Within unconfined valleys, limited storage of fine sediment and greater microbial transformation of OM in multithread channel reaches decreases OC storage per area (252 ± 39 Mg C ha−1) relative to single‐thread channel reaches (346 ± 177 Mg C ha−1). Positive feedbacks between channel morphology and persistent channel‐spanning logjams that divert flow into multiple channels may limit the aggradation of floodplain fine sediment. Although multithread stream reaches are less effective OC reservoirs, they are hotspots for OM decomposition and provide critical resources to downstream food webs. Plain Language Summary: Organic matter, in the form of byproducts of plants, insects, and microbes, is a critical component of healthy riverine ecosystems and contributes to carbon storage, which reduces carbon dioxide release to the atmosphere. To examine how the shapes of river channels and valleys influenced organic matter storage, we (a) surveyed 24 streams in the Colorado Rocky Mountains and collected soil samples to estimate carbon storage, (b) related differences in carbon storage to river morphology, and (c) examined how channel geometry influenced the molecular composition of dissolved organic matter. We found that carbon storage per area is higher in wider valleys, in lower gradient streams, and at higher elevations. Within wide valleys, streams with a single channel of flow stored more sediment and carbon than streams with numerous channels of flow. Complex river channels also increased the molecular transformation of carbon by microbial communities. Although complex river features are less efficient reservoirs for organic matter, they increase carbon availability to downstream food webs and play an important role in maintaining healthy ecosystems. Key Points: Less‐confined valleys store relatively more carbon per area in floodplain fine sediment and large wood than more confined valley segmentsWithin wide valleys, channels with single‐thread planforms store more carbon than more complex systems with multiple channels of flowLogjam abundance is linked to microbial transformation of organic matter and shallower fine sediment depth in complex multithread reaches [ABSTRACT FROM AUTHOR]

Water markets increasingly facilitate adaptation to water scarcity, but transaction costs can be barriers to expanded water marketing, particularly under water rights law in the western United States. However, transaction costs are rarely measured, and existing research commonly overlooks how transaction costs differ across individual water transfers and uncertainty in those costs. We collected hundreds of estimates of procedural transaction costs—costs incurred by transfer proponents for legal and hydrologic experts—by surveying 100 water professionals in the state of Colorado. There, water markets are among the most active in the United States, convey perhaps the most clearly defined private property rights of any state, and, unique to Colorado, require approval from specialized water courts. We elicited costs for water transfers with differing physical and legal characteristics, and we elicited separate assessments of (i) probabilities of legal outcomes for water transfers and (ii) transaction costs conditional on those outcomes. Then, we estimated expected transaction costs with a statistical model that combines (i) with (ii). The model reveals systematic differences in transaction costs, with scale economies and higher transaction costs for water‐scarce regions, senior water rights, and higher‐conflict legal outcomes. It also shows substantial transaction cost uncertainty, which itself can discourage trading. Our novel survey and estimation procedure develops a replicable approach for measuring transaction cost heterogeneity and uncertainty. Additionally, qualitative survey data we collected indicate transaction costs have increased over time due to growing competition for scarce water and that, despite high transaction costs, specialized water courts offer unique benefits. Key Points: Water market transaction costs are uncertain, and this uncertainty depends upon legal procedures for water rights transfersTransaction costs are higher in water‐scarce regions, for higher‐conflict transfers, and for senior water rights, and show scale economiesTransaction costs have grown over time due to increased competition for scarce water and more complex water rights operations [ABSTRACT FROM AUTHOR]

Water markets are commonly described as failing to achieve efficient water management because of transaction cost barriers to trade. In the western United States, two sources of legal conflict frequently drive transaction costs: (1) negative externalities of trading and (2) uncertain property rights. Conflicts arise because water law applies a no‐injury rule that prevents water transfers from modifying water available to third‐party water rights and defines water rights by historical water use, among other reasons. Existing literature suggests many legal changes to reduce transaction costs, but no studies in the western United States quantify transaction costs under proposed future changes. Here we developed statistical models of transaction costs for water transfer proponents under four specific legal changes in the state of Colorado. Two legal changes would modify the no‐injury rule, and two aim to clarify property rights. Colorado hosts active markets and has recently experienced debate over such legal changes. By surveying 100 legal and hydrologic experts, we elicited transaction cost estimates and rankings of which legal changes were most likely to increase third‐party injury. The legal changes that aim to clarify property rights had significantly lower likelihoods of increasing injury. One of these legal changes, which would not limit transferable water to historical use in certain circumstances, also had the greatest reductions in proponents' transaction costs. Meanwhile, the legal changes that directly modify the no‐injury rule project substantial transaction cost savings but much higher likelihoods of increased injury. The results demonstrate trade‐offs between reducing transaction costs and increasing third‐party effects. Key Points: An economic survey quantified how legal changes impact transaction costs, completion times, and third‐party effects for water marketingSome legal changes project decreases in transaction costs and report less probable increases in third‐party effects, while others do notModifying water law to reduce transaction costs involves trade‐offs between these reductions and potential increases in third‐party effects [ABSTRACT FROM AUTHOR]

Understanding concentration‐discharge (C‐Q) relationships are essential for predicting chemical weathering and biogeochemical cycling under changing climate and anthropogenic conditions. Contrasting C‐Q relationships have been observed widely, yet a mechanistic framework that can interpret diverse patterns remains elusive. This work hypothesizes that seemingly disparate C‐Q patterns are driven by switching dominance of end‐member source waters and their chemical contrasts arising from subsurface biogeochemical heterogeneity. We use data from Coal Creek, a high‐elevation mountainous catchment in Colorado, and a recently developed watershed reactive transport model (BioRT‐Flux‐PIHM). Sensitivity analysis and Monte‐Carlo simulations (500 cases) show that reaction kinetics and thermodynamics and distribution of source materials across depths govern the chemistry gradients of shallow soil water and deeper groundwater entering the stream. The alternating dominance of organic‐poor yet geo‐solute‐rich groundwater under dry conditions and organic‐rich yet geo‐solute‐poor soil water during spring melt leads to the flushing pattern of dissolved organic carbon and the dilution pattern of geogenic solutes (e.g., Na, Ca, and Mg). In addition, the extent of concentration contrasts regulates the power law slopes (b) of C‐Q patterns via a general equation b=δbCratioCratio,1/2+Cratio+bmin. At low ratios of soil water versus groundwater concentrations (Cratio = Csw/Cgw < 0.6), dilution occurs; at high ratios (Cratio > 1.8), flushing arises; chemostasis occurs in between. This equation quantitatively interprets b values of 11 solutes (dissolved organic carbon, dissolved P, NO3−, K, Si, Ca, Mg, Na, Al, Mn, and Fe) from three catchments (Coal Creek, Shale Hills, and Plynlimon) of differing climate, geologic, and land cover conditions. This indicates potentially broad regulation of subsurface biogeochemical heterogeneity in determining C‐Q patterns and wide applications of this equation in quantifying b values, which can have broad implications for predicting chemical weathering and biogeochemical transformation at the watershed scale. Key Points: Contrasting C‐Q patterns are shaped by alternating dominance of soil water and groundwater with distinct water chemistriesDilution occurs for geogenic solutes concentrated in reactive rocks at depth, while flushing arises for biogenic solutes enriched in shallow soilsA relationship between C‐Q slope and soil‐groundwater concentration ratios is established, explaining C‐Q patterns of 11 solutes from three catchments [ABSTRACT FROM AUTHOR]

Although important for riverine solute and nutrient fluxes, the connections between biogeochemical processes and subsurface hydrology remain poorly characterized. We investigate these couplings in the East River, CO, a high-elevation shale-dominated catchment in the Rocky Mountains, using concentration-discharge (C-Q) relationships for major cations, anions, and organic carbon. Dissolved organic carbon (DOC) displays a positive C-Q relationship with clockwise hysteresis, indicating mobilization and depletion of DOC in the upper soil horizons and emphasizing the importance of shallow flow paths during snowmelt. Cation and anion concentrations demonstrate that carbonate weathering, which dominates solute fluxes, is promoted by both sulfuric acid derived from pyrite oxidation in the shale bedrock and carbonic acid derived from subsurface respiration. Sulfuric acid weathering dominates during base flow conditions when waters infiltrate below the inferred pyrite oxidation front, whereas carbonic acid weathering plays a dominant role during snowmelt as a result of shallow flow paths. Differential C-Q relationships between solutes suggest that infiltrating waters approach calcite saturation before reaching the pyrite oxidation front, after which sulfuric acid reduces carbonate alkalinity. This reduction in alkalinity results in CO2 outgassing when waters equilibrate to surface conditions, and reduces the riverine export of carbon and alkalinity by roughly 33% annually. Future changes in snowmelt dynamics that control the balance of carbonic and sulfuric acid weathering may substantially alter carbon cycling in the East River. Ultimately, we demonstrate that differential C-Q relationships between major solutes can provide unique insights into the complex subsurface flow and biogeochemical dynamics that operate at catchment scales. [ABSTRACT FROM AUTHOR]

Long-term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in hydrological processes and uncertainty in future climate conditions. In this study, we develop a Bayesian model to combine small-scale historical hydrological data with large-scale climate information to estimate groundwater dynamics at a floodplain site in Rifle, Colorado. Although we have only a few years of groundwater elevation measurements, we have 47 years of streamflow data from a gaging station approximately 43 km upstream and long-term climate prediction on the Upper Colorado River Basin. To estimate future daily groundwater dynamics, we first develop a time series model to downscale the monthly streamflow derived from climate information to daily streamflow, and then transform the daily streamflow to groundwater dynamics at the downstream floodplain site. We use Monte Carlo methods to estimate future groundwater dynamics at the site through sampling from the joint posterior probability distribution. The results suggest that although future groundwater levels are expected to be similar to the current levels, the timing of the high groundwater levels is predicted to occur about 1 month earlier. The developed framework is extendable to other sites to estimate future groundwater dynamics given disparate data sets and climate projections. Additionally, the obtained estimates are being used as input to a site-specific watershed reactive transport models to predict how climate-induced changes will influence future biogeochemical cycling relevant to a variety of ecosystem services. [ABSTRACT FROM AUTHOR]

The Colorado Front Range has a large elevation gradient with deep seasonal snowpack in the mountains and limited snow accumulation in the foothills and plains. This study examines how the sources of annual peak flows (snowmelt, rainfall, mixed) change with the fraction of time snow persists on the ground, snow persistence (SP), and whether these sources have changed over time. Sources of peak flows for 20 gaging stations are estimated using a gridded rain and snow model forced with PRISM daily precipitation and both PRISM and TopoWx temperature. The mean snowmelt contribution to peak flow is highly correlated with SP (r2 = 0.86-0.90). Watersheds with SP < 0.3 (low snow, elevation <2000 m) are rainfall-dominated, and watersheds with SP > 0.7 (persistent snow, elevation >3100 m) are mostly snowmelt-dominated, with mixed sources between these thresholds. Rainfall runoff peak flows are possible at all elevations, but their likelihood declines with increasing SP. Rainfall runoff from an extreme storm in September 2013 produced the highest annual peaks at many stations, including some snowmelt-dominated watersheds. Regional Kendall trend tests indicate that the contributions of snowmelt to peak flows and total annual inputs have declined in the mixed source zone. These changes may affect hydrographs, as analyses confirm that snowmelt runoff generally produces more attenuated peaks than rainfall runoff. Discrimination of peak flow source is sensitive to input data and model structure for mixed rain and snowmelt events, and both observation and modeling research are needed to help understand potential runoff changes in these conditions. [ABSTRACT FROM AUTHOR]

Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km3 during 1986-1990 and by 102 km3 during 1998-2004, similar to the TWS depletion recorded by GRACE (47 km3) during 2010-2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts. [ABSTRACT FROM AUTHOR]

In snowmelt-driven river systems, it is critical to enable reliable predictions of the spatiotemporal variability in seasonal snowpack to support local and regional water management. Previous studies have shown that assimilating satellite-station blended snow depth data sets can lead to improved snow predictions, which however do not always translate into improved streamflow predictions, especially in complex mountain regions. In this study, we explore how an existing optimal interpolation-based blending strategy can be enhanced to reduce biases in satellite snow depth products for improving streamflow predictions. Two major new considerations are explored, including: (1) incorporating terrain aspect and (2) incorporating areal snow coverage information. The methodology is applied to the bias reduction of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth estimates, which are then assimilated into the Noah land surface model via the ensemble Kalman Filtering (EnKF) for streamflow predictions in the Upper Colorado River Basin. Our results indicate that using only observations from low-elevation stations such as the Global Historical Climatology Network (GHCN) in the bias correction can lead to underestimation in streamflow, while using observations from high-elevation stations (e.g., the Snow Telemetry (SNOTEL) network) along with terrain aspect is critically important for achieving reliable streamflow predictions. Additionally incorporating areal snow coverage information from the Moderate Resolution Imaging Spectroradiometer (MODIS) can slightly improve the streamflow results further. [ABSTRACT FROM AUTHOR]

Spatial and temporal trends in stream chemistry were investigated in a large (1600 km2) alpine watershed in the southern Rocky Mountains of Colorado to help understand mechanisms of streamflow generation. We observed linear increases of concentrations of chemical constituents in streamflow as accumulated drainage area increased along the main channel of Saguache Creek. We tested two conceptual models of streamflow generation against our stream chemistry observations. One model is essentially two-dimensional and treats streamflow generation at the large watershed scale as the aggregation of runoff responses from individual hillslopes, primarily surface and shallow subsurface flow paths. Alternatively, a fully three-dimensional conceptual model treats streamflow generation as being controlled by a distribution of large-scale groundwater flow paths as well as surface and shallow subsurface flow paths. The structure and magnitude of groundwater contributions in streamflow as a function of increasing scale provided a key distinction between these two conceptual models. End-member mixing analysis and measurements of hydraulic head gradients in streambeds were used to quantify basin-scale groundwater contributions to streamflow with increasing spatial scale in the Saguache Creek watershed. Our data show that groundwater contributions are important in streamflow generation at all scales and, more importantly, that groundwater contributions to streamflow do increase with increasing watershed scale. These results favor the three-dimensional conceptual model in which long groundwater flow paths provide a streamflow generation process at large scales that is not operative at smaller scales. This finding indicates that large watersheds may be more than simply the aggregation of hillslopes and small catchments. [ABSTRACT FROM AUTHOR]

The scaling properties of channel-forming flows are investigated using a regional flow frequency model developed for snowmelt-dominated streams in Colorado. The model is derived from analyses of daily flow records at 32 gauging stations where we have independent measurements of the bankfull discharge. The study sites are located in alpine/subalpine basins with drainage areas ranging from 4 to 3700 km2. The frequency distribution of daily flows at these locations can be reproduced with a broken power law (BPL) function described by two free parameters. Both parameters are strongly correlated with drainage area, and based on these correlations, a regional model capable of predicting the frequency of daily flows above the mean annual flow was formulated. The applicability of the model was tested using daily flow records from 32 similar-size basins in Idaho. The frequency distributions of daily flows in snowmelt-dominated streams in Colorado and Idaho with highly predictable hydrographs (i.e., 1 year autocorrelation above 0.7) are well fitted by the BPL function. According to the model, the frequency of flows greater than bankfull decreases downstream from about 15 d/yr in headwater reaches to about 6 d/yr in downstream reaches. These results imply that the basin response to precipitation and runoff is nonlinear. This multiscaling behavior can be physically interpreted as the result of scale-dependent variations in runoff and sediment supply, which influence downstream trends in the bankfull channel geometry and intensity of sediment transport. [ABSTRACT FROM AUTHOR]