Projections of 21st Century Sierra Nevada Local Hydrologic Flow Components Using an Ensemble of General Circulation Models1

Abstract: Sierra Nevada snowmelt and runoff is a key source of water for many of California’s 38 million residents and nearly the entire population of western Nevada. The purpose of this study was to assess the impacts of expected 21st Century climatic changes in the Sierra Nevada at the subwatershed scale, for all hydrologic flow components, and for a suite of 16 General Circulation Models (GCMs) with two emission scenarios. The Soil and Water Assessment Tool (SWAT) was calibrated and validated at 35 unimpaired streamflow sites. Results show that temperatures are projected to increase throughout the Sierra Nevada, whereas precipitation projections vary between GCMs. These climatic changes drive a decrease in average annual streamflow and an advance of snowmelt and runoff by several weeks. The largest streamflow reductions were found in the mid‐range elevations due to less snow accumulation, whereas the higher elevation watersheds were more resilient due to colder temperatures. Simulation results showed that decreases in snowmelt affects not only streamflow, but evapotranspiration, surface, and subsurface flows, such that less water is available in spring and summer, thus potentially affecting aquatic and terrestrial ecosystems. Declining spring and summer flows did not equally affect all subwatersheds in the region, and the subwatershed perspective allowed for identification for the most sensitive basins throughout the Sierra Nevada.     

Characterizing Runoff and Water Yield for Headwater Catchments in the Southern Sierra Nevada

In a Mediterranean climate where much of the precipitation falls during winter, snowpacks serve as the primary source of dry season runoff. Increased warming has led to significant changes in hydrology of the western United States. An important question in this context is how to best manage forested catchments for water and other ecosystem services? Answering this basic question requires detailed understanding of hydrologic functioning of these catchments. Here, we depict the differences in hydrologic response of 10 catchments. Size of the study catchments ranges from 50 to 475 ha, and they span between 1,782 and 2,373 m elevation in the rain‐snow transitional zone. Mean annual streamflow ranged from 281 to 408 mm in the low elevation Providence and 436 to 656 mm in the high elevation Bull catchments, resulting in a 49 mm streamflow increase per 100 m (R² = 0.79) elevation gain, despite similar precipitation across the 10 catchments. Although high elevation Bull catchments received significantly more precipitation as snow and thus experienced a delayed melt, this increase in streamflow with elevation was mainly due to a reduction in evapotranspiration (ET) with elevation (45 mm/100 m, R² = 0.65). The reduction in ET was attributed to decline in vegetation density, growing season, and atmospheric demand with increasing elevation. These findings suggest changes in streamflow in response to climate warming may likely depend on how vegetation responds to those changes in climate.     

Long‐Term Trends in Streamflow and Precipitation in Northwest California and Southwest Oregon, 1953‐2012

Using nonparametric Mann‐Kendall tests, we assessed long‐term (1953‐2012) trends in streamflow and precipitation in Northern California and Southern Oregon at 26 sites regulated by dams and 41 “unregulated” sites. Few (9%) sites had significant decreasing trends in annual precipitation, but September precipitation declined at 70% of sites. Site characteristics such as runoff type (groundwater, snow, or rain) and dam regulation influenced streamflow trends. Decreasing streamflow trends outnumbered increasing trends for most months except at regulated sites for May‐September. Summer (July‐September) streamflow declined at many sites, including 73% of unregulated sites in September. Applying a LOESS regression model of antecedent precipitation vs. average monthly streamflow, we evaluated the underlying streamflow trend caused by factors other than precipitation. Decreasing trends in precipitation‐adjusted streamflow substantially outnumbered increasing trends for most months. As with streamflow, groundwater‐dominated sites had a greater percent of declining trends in precipitation‐adjusted streamflow than other runoff types. The most pristine surface‐runoff‐dominated watersheds within the study area showed no decreases in precipitation‐adjusted streamflow during the summer months. These results suggest that streamflow decreases at other sites were likely due to more increased human withdrawals and vegetation changes than to climate factors other than precipitation quantity.     

Neural Network Input Selection for Hydrological Forecasting Affected by Snowmelt1

Abstract: Snowmelt largely affects runoff in watersheds in Nordic countries. Neural networks (NN) are particularly attractive for streamflow forecasting whereas they rely at least on daily streamflow and precipitation observations. The selection of pertinent model inputs is a major concern in NNs implementation. This study investigates performance of auxiliary NN inputs that allow short‐term streamflow forecasting without resorting to a deterministic snowmelt routine. A case study is presented for the Rivière des Anglais watershed (700 km²) located in Southern Québec, Canada. Streamflow (Q), precipitations (rain R and snow S, or total P), temperature (T) and snow lying (A) observations, combined with climatic and snowmelt proxy data, including snowmelt flow (Q_SM) obtained from a deterministic model, were tested. NN implemented with antecedent Q and R produced the largest gains in performance. Introducing increments of A and T to the NNs further improved the performance. Long‐term averages, seasonal data, and Q_SM failed to improve the networks.     

POTENTIAL IMPACTS OF CLIMATE CHANGE ON CALIFORNIA HYDROLOGY1

ABSTRACT: Previous reports based on climate change scenarios have suggested that California will be subjected to increased wintertime and decreased summertime streamflow. Due to the uncertainty of projections in future climate, a new range of potential climatological future temperature shifts and precipitation ratios is applied to the Sacramento Soil Moisture Accounting Model and Anderson Snow Model in order to determine hydrologic sensitivities. Two general circulation models (GCMs) were used in this analysis: one that is warm and wet (HadCM2 run 1) and one that is cool and dry (PCM run B06.06), relative to the GCM projections for California that were part of the Third Assessment Report of the Intergovernmental Panel on Climate Change. A set of specified incremental temperature shifts from 1.5°C to 5.0°C and precipitation ratios from 0.70 to 1.30 were also used as input to the snow and soil moisture accounting models, providing for additional scenarios (e.g., warm/dry, cool/wet). Hydrologic calculations were performed for a set of California river basins that extend from the coastal mountains and Sierra Nevada northern region to the southern Sierra Nevada region; these were applied to a water allocation analysis in a companion paper. Results indicate that for all snow‐producing cases, a larger proportion of the streamflow volume will occur earlier in the year. The amount and timing is dependent on the characteristics of each basin, particularly the elevation. Increased temperatures lead to a higher freezing line, therefore less snow accumulation and increased melting below the freezing height. The hydrologic response varies for each scenario, and the resulting solution set provides bounds to the range of possible change in streamflow, snowmelt, snow water equivalent, and the change in the magnitude of annual high flows. An important result that appears for all snowmelt driven runoff basins, is that late winter snow accumulation decreases by 50 percent toward the end of this century.     

Use of Hydrologic Landscape Classification to Diagnose Streamflow Predictability in Oregon

We implement a spatially lumped hydrologic model to predict daily streamflow at 88 catchments within the state of Oregon and analyze its performance using the Oregon Hydrologic Landscape (OHL) classification. OHL is used to identify the physio‐climatic conditions that favor high (or low) streamflow predictability. High prediction catchments (Nash‐Sutcliffe efficiency of (NS) > 0.75) are mainly classified as rain dominated with very wet climate, low aquifer permeability, and low to medium soil permeability. Most of them are located west of the Cascade Mountain Range. Conversely, most low prediction catchments (NS < 0.6) are classified as snow‐dominated with high aquifer permeability and medium to high soil permeability. They are mainly located in the volcano‐influenced High Cascades region. Using a subset of 36 catchments, we further test if class‐specific model parameters can be developed to predict at ungauged catchments. In most catchments, OHL class‐specific parameters provide predictions that are on par with individually calibrated parameters (NS decline < 10%). However, large NS declines are observed in OHL classes where predictability is not high enough. Results suggest higher uncertainty in rain‐to‐snow transition of precipitation phase and external gains/losses of deep groundwater are major factors for low prediction in Oregon. Moreover, regionalized estimation of model parameters is more useful in regions where conditions favor good streamflow predictability.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

Effect of Snow Cover Conditions on the Hydrologic Regime: Case Study in a Pluvial‐Nival Watershed,Japan1

Abstract: Hydrologic monitoring in a small forested and mountainous headwater basin in Niigata Prefecture has been undertaken since 2000. An important characteristic of the basin is that the hydrologic regime contains pluvial elements year‐round, including rain‐on‐snow, in addition to spring snowmelt. We evaluated the effect of different snow cover conditions on the hydrologic regime by analyzing observed data in conjunction with model simulations of the snowpack. A degree‐day snow model is presented and applied to the study basin to enable estimation of the basin average snow water equivalent using air temperature at three representative elevations. Analysis of hydrological time series data and master recession curves showed that flow during the snowmelt season was generated by a combination of ground water flow having a recession constant of 0.018/day and diurnal melt water flow having a recession constant of 0.015/hour. Daily flows during the winter/snowmelt season showed greater persistence than daily flows during the warm season. The seasonal water balance indicated that the ratio of runoff to precipitation during the cold season (December to May) was about 90% every year. Seasonal snowpack plays an important role in defining the hydrologic regime, with winter precipitation and snowmelt runoff contributing about 65% of the annual runoff. The timing of the snowmelt season, indicated by the date of occurrence of the first significant snowmelt event, was correlated with the occurrence of low flow events. Model simulations showed that basin average snow water equivalent reached a peak around mid‐February to mid‐March, although further validation of the model is required at high elevation sites.     

VARIATIONS IN NORTHERN SIERRA NEVADA STREAMFLOW: IMPLICATIONS OF CLIMATE CHANGE1

ABSTRACT: Historical records of streamflow for an eastward- and a westward-draining stream in the northern Sierra Nevada have been analyzed for evidence of changes in runoff characteristics and patterns of variability. A trend of increasing and more variable winter streamflow began in the mid-1960s. Mean monthly streaniflow during December through March was substantially greater for water years 1965–1990 compared to water years 1939–1964. Increased winter and early-spring streamflow during the later period is attributed to small increases in temperature, which increase the rain-to-snow ratio at lower altitudes and cause the snowpack to melt earlier in the season at higher altitudes. The timing of snowmelt runoff on the western slope of the Sierra Nevada is more sensitive than it is on the eastern slope to changes in temperature, owing to predominantly lower altitudes on the west side. This difference in sensitivity suggests that basins on the east side of the Sierra Nevada have a more reliable water supply (as snow storage) than western-slope basins during warming trends.     

Observed Changes in Climate and Streamflow in the Upper Rio Grande Basin

Observed streamflow and climate data are used to test the hypothesis that climate change is already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways consistent with model‐based projections of 21st‐Century streamflow. Annual and monthly changes in streamflow volume and surface climate variables on the Upper Rio Grande, near its headwaters in southern Colorado, are assessed for water years 1958–2015. Results indicate winter and spring season temperatures in the basin have increased significantly, April 1 snow water equivalent (SWE) has decreased by approximately 25%, and streamflow has declined slightly in the April–July snowmelt runoff season. Small increases in precipitation have reduced the impact of declining snowpack on trends in streamflow. Changes in the snowpack–runoff relationship are noticeable in hydrographs of mean monthly streamflow, but are most apparent in the changing ratios of precipitation (rain + snow, and SWE) to streamflow and in the declining fraction of runoff attributable to snowpack or winter precipitation. The observed changes provide observational confirmation for model projections of decreasing runoff attributable to snowpack, and demonstrate the decreasing utility of snowpack for predicting subsequent streamflow on a seasonal basis in the Upper Rio Grande Basin.     

Water Balances of Two Piedmont Headwater Catchments: Implications for Regional Hydrologic Landscape Classification

In the Piedmont of North Carolina, a traditionally water‐rich region, reservoirs that serve over 1 million people are under increasing pressure due to naturally occurring droughts and increasing land development. Innovative development approaches aim to maintain hydrologic conditions of the undisturbed landscape, but are based on insufficient target information. This study uses the hydrologic landscape concept to evaluate reference hydrology in small headwater catchments surrounding Falls Lake, a reservoir serving Raleigh and the greater Triangle area. Researchers collected one year of detailed data on water balance components, including precipitation, evapotranspiration, streamflow, and shallow subsurface storage from two headwater catchments representative of two hydrologic landscapes defined by differences in soils and topographic characteristics. The two catchments are similar in size and lie within the same physiographic region, and during the study period they showed similar water balances of 26‐30% Q, ?4 to 5% ΔS, 59‐65% evapotranspiration, and 9‐10% G. However, the steeper, more elevated catchment exhibited perennial streamflow and nongrowing season runoff ratios (Q/P) of 33%, whereas the flat, low‐lying stream was drier during the growing season and exhibited Q/P ratios of 52% during the nongrowing season. A hydrologic landscape defined by topography and soil characteristics helps characterize local‐scale reference hydrology and may contribute to better land management decisions.     

PHYSICAL HYDROLOGY AND THE EFFECTS OF FOREST HARVESTING IN THE PACIFIC NORTHWEST: A REVIEW1

The Pacific Northwest encompasses a range of hydrologic regimes that can be broadly characterized as either coastal (where rain and rain on snow are dominant) or interior (where snowmelt is dominant). Forest harvesting generally increases the fraction of precipitation that is available to become streamflow, increases rates of snowmelt, and modifies the runoff pathways by which water flows to the stream channel. Harvesting may potentially decrease the magnitude of hyporheic exchange flow through increases in fine sediment and clogging of bed materials and through changes in channel morphology, although the ecological consequences of these changes are unclear. In small headwater catchments, forest harvesting generally increases annual runoff and peak flows and reduces the severity of low flows, but exceptions have been observed for each effect. Low flows appear to be more sensitive to transpiration from vegetation in the riparian zone than in the rest of the catchment. Although it appears that harvesting increased only the more frequent, geomorphically benign peak flows in several studies, in others the treatment effect increased with return period. Recovery to pre‐harvest conditions appeared to occur within about 10 to 20 years in some coastal catchments but may take many decades in mountainous, snow dominated catchments.     

Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho,Western Wyoming,and Northern Nevada1

Clark, Gregory M., 2010. Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho, Western Wyoming, and Northern Nevada. Journal of the American Water Resources Association (JAWRA) 46(3):486-497. DOI: 10.1111/j.1752-1688.2009.00416.x Abstract: Recent studies have identified a pattern of earlier spring runoff across much of North America. Earlier spring runoff potentially poses numerous problems, including increased risk of flooding and reduced summer water supply for irrigation, power generation, and migratory fish passage. To identify changing runoff patterns in Idaho streams, streamflow records were analyzed for 26 U.S. Geological Survey gaging stations in Idaho, western Wyoming, and northern Nevada, each with a minimum of 41 years of record. The 26 stations are located on 23 unregulated and relatively pristine streams that drain areas ranging from 28 to >35,000 km². Four runoff parameters were trend tested at each station for both the period of historical record and from 1967 through 2007. Parameters tested were annual mean streamflow, annual minimum daily streamflow, and the dates of the 25th and 50th percentiles of the annual total streamflow. Results of a nonparametric Mann-Kendall trend test revealed a trend toward lower annual mean and annual minimum streamflows at a majority of the stations, as well as a trend toward earlier snowmelt runoff. Significant downward trends over the period of historical record were most prevalent for the annual minimum streamflow (12 stations) and the 50th percentile of streamflow (11 stations). At most stations, trends were more pronounced during the period from 1967 through 2007. A regional Kendall test for water years 1967 through 2007 revealed significant regional trends in the percent change in the annual mean and annual minimum streamflows (0.67% less per year and 0.62% less per year, respectively), the 25th percentile of streamflow (12.3 days earlier), and the 50th percentile of streamflow (11.5 days earlier).     

THE POTENTIAL FOR INCREASING STREAMFLOW FROM SIERRA NEVADA WATERSHEDS1

The Sierra Nevada produces over 50 percent of California's water. Improvement of water yields from the Sierra Nevada through watershed management has long been suggested as a means of augmenting the state's water supply. Vegetation and snowpack management can increase runoff from small watersheds by reducing losses due to evapotranspiration, snow interception by canopy, and snow evaporation. Small clearcuts or group selection cuts creating openings less than half a hectare, with the narrow dimension from south to north, appear to be ideal for both increasing and delaying water delivery in the red fir-lodgepole pine and mixed-conifer types of the Sierra west slope. Such openings can have up to 40 percent more snow-water equivalent than does uncut forest. However, the water yield increase drops to 1/2-2 percent of current yield for an entire management unit, due to the small number of openings that can be cut at one time, physical and management constraints, and multiple use/sustained yield guidelines. As a rough forecast, water production from National Forest land in the Sierra Nevada can probably be increased by about 1 percent (0.6 cm) under intensive forest watershed management. Given the state of reservoir storage and water use in California, delaying streamflow is perhaps the greatest contribution watershed management can make to meeting future water demands.     

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐means clustering within a geographic information system, and validated, using summary statistics derived from measured soil moisture time series. Validation stations, located in the Sierra Nevada, include transect of sites that cross the rain‐to‐snow transition and a cluster of sites located at similar elevations in a snow‐dominated watershed. The SMRUs capture unique responses to varying climate conditions characterized by statistical measures of central tendency, dispersion, and extremes. A topographic position index and landform classification is the final step in the workflow to guide the optimal placement of soil moisture sensors at the local‐scale. The proposed workflow is highly flexible and can be implemented over a range of spatial scales and input datasets can be customized. Our approach captures a range of soil moisture responses to climate across California and can be used to design and optimize soil moisture monitoring strategies to support runoff forecasts for water supply management or to assess landscape conditions for forest and rangeland management.     

Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM1

Harshburger, Brian J., Karen S. Humes, Von P. Walden, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2010. Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM. Journal of the American Water Resources Association (JAWRA) 46(3):603-617. DOI: 10.1111/j.1752-1688.2010.00437.x Abstract: As demand for water continues to escalate in the western United States, so does the need for accurate streamflow forecasts. Here, we describe a methodology for generating short-to-medium range (1 to 15 days) streamflow forecasts using an enhanced version of the Snowmelt Runoff Model (SRM), snow-covered area data derived from MODIS products, data from Snow Telemetry stations, and meteorological forecasts. The methodology was tested on three mid-elevation, snowmelt-dominated basins ranging in size from 1,600 to 3,500 km². To optimize the model performance and aid in its operational implementation, two enhancements have been made to SRM: (1) the use of an antecedent temperature index method to track snowpack cold content, and (2) the use of both maximum and minimum critical temperatures to partition precipitation into rain, snow, or a mixture of rain and snow. The comparison of retrospective model simulations with observed streamflow shows that the enhancements significantly improve the model performance. Streamflow forecasts generated using the enhanced version of the model compare well with the observed streamflow for the earlier leadtimes; forecast performance diminishes with leadtime due to errors in the meteorological forecasts. The three basins modeled in this research are typical of many mid-elevation basins throughout the American West, thus there is potential for this methodology to be applied successfully to other mountainous basins.     

Modeling Discharge Rates Using a Coupled Modeled Approach for the Merced River in Yosemite National Park

This study describes the application of the NASA version of the Carnegie‐Ames‐Stanford Approach (CASA) ecosystem model coupled with a surface hydrologic routing scheme previously called the Hydrological Routing Algorithm (HYDRA) to model monthly discharge rates from 2000 to 2007 on the Merced River drainage in Yosemite National Park, California. To assess CASA‐HYDRA's capability to estimate actual water flows in extreme precipitation years, the focus of this study is the 2007 water year, which was very dry, and the 2005 water year, which was a moderately wet year in the historical record. Prior to comparisons to gauge records, CASA‐HYDRA snowmelt algorithms were modified with equations from the U.S. Department of Agriculture Snowmelt‐Runoff Model (SRM), which has been designed to predict daily streamflow in mountain basins where snowmelt is a major runoff factor. Results show that model predictions closely matched monthly flow rates at the Pohono Bridge gauge station (USGS#11266500), with R² = 0.67 and Nash‐Sutcliffe (E) = 0.65. By subdividing the upper Merced River basin into subbasins with high spatial resolution in the gridded modeling approach, we were able to determine which biophysical characteristics in the Sierra differed to the largest degree in extreme low‐flow and high‐flow years. Average elevation and snowpack accumulation were found to be the most important explanatory variables to understand subbasin contributions to monthly discharge rates.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

Groundwater Level Trends and Drivers in Two Northern New England Glacial Aquifers

We evaluated long‐term trends and predictors of groundwater levels by month from two well‐studied northern New England forested headwater glacial aquifers: Sleepers River, Vermont, 44 wells, 1992‐2013; and Hubbard Brook, New Hampshire, 15 wells, 1979‐2004. Based on Kendall Tau tests with Sen slope determination, a surprising number of well‐month combinations had negative trends (decreasing water levels) over the respective periods. Sleepers River had slightly more positive than negative trends overall, but among the significant trends (p < 0.1), negative trends dominated 67 to 40. At Hubbard Brook, negative trends outnumbered positive trends by a nearly 2:1 margin and all seven of the significant trends were negative. The negative trends occurred despite generally increasing trends in monthly and annual precipitation. This counterintuitive pattern may be a result of increased precipitation intensity causing higher runoff at the expense of recharge, such that evapotranspiration demand draws down groundwater storage. We evaluated predictors of month‐end water levels by multiple regression of 18 variables related to climate, streamflow, snowpack, and prior month water level. Monthly flow and prior month water level were the two strongest predictors for most months at both sites. The predictive power and ready availability of streamflow data can be exploited as a proxy to extend limited groundwater level records over longer time periods.     

Trends in Western U.S. Snowpack and Related Upper Colorado River Basin Streamflow1

Miller, W. Paul and Thomas C. Piechota, 2011. Trends in Western U.S. Snowpack and Related Upper Colorado River Basin Streamflow. Journal of the American Water Resources Association (JAWRA) 47(6):1197–1210. DOI: 10.1111/j.1752‐1688.2011.00565.x Abstract: Water resource managers in the Western United States (U.S.) are currently faced with the challenge of adapting to unprecedented drought and uncertain impacts of climate change. Recent research has indicated increasing regional temperature and changes to precipitation and streamflow characteristics throughout the Western U.S. As such, there is increased uncertainty in hydroclimatological forecasts, which impact reservoir operations and water availability throughout the Western U.S., particularly in the Colorado River Basin. Previous research by the authors hypothesized a change in the character of precipitation (i.e., the frequency and amount of rainfall and snowfall events) throughout the Colorado River Basin. In the current study, 398 snowpack telemetry stations were investigated for trends in cumulative precipitation, snow water equivalent, and precipitation events. Observations of snow water equivalent characteristics were compared to observations in streamflow characteristics. Results indicate that the timing of the last day of the snow season corresponds well to the volume of runoff observed over the traditional peak flow season (April through July); conversely, the timing of the first day of the snow season does not correspond well to the volume of runoff observed over the peak flow season. This is significant to water resource managers and river forecasters, as snowpack characteristics may be indicative of a productive or unproductive runoff season.