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.     

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.     

EFFECT OF SIMULATED CLIMATE CHANGE ON SNOWMELT RUNOFF MODELING IN SELECTED BASINS1

ABSTRACT: The projected increase in the concentration of CO₂ and other greenhouse gases in the atmosphere is likely to result in a global temperature increase. This paper reports on the probable effects of a temperature increase and changes in transpiration on basin discharge in two different mountain snowmelt regions of the western United States. The hydrological effects of the climate changes are modeled with a relatively simple conceptual, semi-distributed snowmelt runoff model. Based on the model results, it may be concluded that increased air temperatures will result in a shift of snowmelt runoff to earlier in the snowmelt season. Furthermore, it is shown that it is very important to include the expected change in climate-related basin conditions resulting from the modeled temperature increase in the runoff simulation. The effect of adapting the model parameters to reflect the changed basin conditions resulted in a further shift of streamflow to April and an even more significant decrease of snowmelt runoff in June and July. If the air temperatures increase by approximately 5°C and precipitation and accumulated snow amounts remain about the same, runoff in April and May, averaged for the two basins, is expected to increase by 185 percent and 26 percent, respectively. The runoff in June and July will decrease by about 60 percent each month. Overall, the total seasonal runoff decreases by about 6 percent. If increased CO₂ concentrations further change basin conditions by reducing transpiration by the maximum amounts reported in the literature, then, combined with the 5°C temperature increase, the April, May, June, and July changes would average +230 percent, +40 percent, ?55 percent, and ?45 percent, respectively. The total seasonal runoff change would be +11 percent.     

PCN BASED METAL PARTITIONING IN URBAN SNOWMELT,RAINFALL/RUNOFF,AND RIVER FLOW SYSTEMS1

ABSTRACT: Drawing an analogy between the popular Soil Conservation Service curve number (SCS‐CN) method based infiltration and metal sorption processes, a new partitioning curve number (PCN) approach is suggested for partitioning of heavy metals into dissolved and particulate bound forms in urban snowmelt, rainfall/runoff, and river flow environments. The parameters, the potential maximum desorption, ψ, and the PCN analogous to the SCS‐CN parameters S and CN, respectively, are introduced. Under the condition of snowmelt, PCN (or ψ) is found to generally rely on temperature, relative humidity, pH, and chloride content; during a rainstorm, ψ is found to depend on the alkalinity and the pH of the rainwater; and in the river flow situation, PCN is found to generally depend on the temperature, pH, and chloride content. The advantage of using PCN instead of the widely used partitioning parameter, K_d, is found to lie in the PCN's efficacy to distinguish the adsorption (or sorption) behavior of metals in the above snowmelt, rainfall/runoff, and river flow situations, analogous to the hydrological behavior of watersheds.     

TEMPERATURE EFFECTS ON GREAT LAKES WATER BALANCE STUDIES1

ABSTRACT. Beginning of month water temperature profiles are estimated for each lake. These water temperature profiles along with surface water temperatures are used to determine the effects of thermal expansion and contraction of water on the net basin supply values obtained from water balance studies using end of month lake levels. It is demonstrated that net basin supply values (equivalent to precipitation on the lake minus the evaporation from the lake plus the runoff into the lake) obtained from water balance studies without accounting for the thermal expansion and contraction of water may be in error by as much as 100 percent during some months for each lake.     

Streamflow Response to Climate as Influenced by Geology and Elevation1

Mayer, Timothy D. and Seth W. Naman, 2011. Streamflow Response to Climate as Influenced by Geology and Elevation. Journal of the American Water Resources Association (JAWRA) 47(4):724‐738. DOI: 10.1111/j.1752‐1688.2011.00537.x Abstract: This study examines the regional streamflow response in 25 predominately unregulated basins to warmer winter temperatures and snowpack reductions over the last half century in the Klamath Basin of California and Oregon. Geologic controls of streamflow in the region result in two general stream types: surface‐dominated and groundwater‐dominated basins. Surface‐dominated basins were further differentiated into rain basins and snowmelt basins on the basis of elevation and timing of winter runoff. Streamflow characteristics and response to climate vary with stream type, as discussed in the study. Warmer winter temperatures and snowpack reductions have caused significantly earlier runoff peaks in both snowmelt and groundwater basins in the region. In the groundwater basins, the streamflow response to changes in snowpack is smoothed and delayed and the effects are extended longer in the summer. Our results indicate that absolute decreases in July‐September base flows are significantly greater, by an order of magnitude, in groundwater basins compared to surface‐dominated basins. The declines are important because groundwater basins sustain Upper Klamath Lake inflows and mainstem river flows during the typically dry summers of the area. Upper Klamath Lake April‐September net inflows have decreased an estimated 16% or 84 thousand acre‐feet (103.6 Mm³) since 1961, with the summer months showing proportionately more decline. These changes will exacerbate water supply problems for agriculture and natural resources in the region.     

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.     

VARIATION IN THE RELATIONSHIP BETWEEN SNOWMELT RUNOFF IN OREGON AND ENSO AND PDO1

ABSTRACT: The value of using climate indices such as ENSO or PDO in water resources predictions is dependent on understanding the local relationship between these indices and streamflow over time. This study identifies long term seasonal and spatial variations in the strength of El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) correlations with timing and magnitude of discharge in snowmelt streams in Oregon. ENSO is best correlated with variability in annual discharge, and PDO is best correlated with spring snowmelt timing and magnitude and timing of annual floods. Streams in the Cascades and Wallowa mountains show the strongest correlations, while the southernmost stream is not correlated with ENSO or PDO. ENSO correlations are weaker from 1920 to 1950 and vary significantly depending on whether Southern Oscillation Index (SOI) or Niño 3.4 is used. PDO correlations are strong from 1920 to 1950 and weak or insignificant other years. Although there are not consistent increasing or decreasing trends in annual discharge or spring snowmelt timing, there are significant increases in fractional winter runoff that are independent of precipitation, PDO, or ENSO and may indicate monotonic winter warming.     

RUNOFF RESPONSE FROM TWO RECLAIMED WATERSHEDS1

ABSTRACT: Detailed studies of the surface hydrology of reclaimed surface-mined watersheds for both rainfall and snowmelt events are non-existent for central Alberta yet this information is crucial for design of runoff conveyance and storage structures. A study was initiated in 1992 with principal objectives of quantifying surface runoff for both summer rainfall and spring snowmelt events and identifying the dominant flow processes occurring in two reclaimed watersheds. Snowmelt accounted for 86 and 100% of annual watershed runoff in 1993 and 1994, respectively. The highest instantaneous peak flow was recorded during a summer rainfall event with a return period of greater than 50 years. Infiltration-excess overland flow was identified as the dominant flow process occurring within the Sandy Subsoil Watershed, whereas saturation overland flow was the principal runoff process occurring within the West Watershed.     

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.     

REVISITING THE DEGREE-DAY METHOD FOR SNOWMELT COMPUTATIONS1

ABSTRACT: The simple, empirical degree-day approach for calculating snowmelt and runoff from mountain basins has been in use for more than 60 years. It is frequently suggested that the degree-day method be replaced by the more physically-based energy balance approach. The degree-day approach, however, maintains its popularity, applicability, and effectiveness. It is shown that the degree-day method is reliable for computing total snowmelt depths for periods of a week to the entire snowmelt season. It can also be used for daily snowmelt depths when utilized in connection with an adequate snowmelt runoff model for computing the basin runoff. The degree-day ratio is shown to vary seasonally as opposed to being constant as is often assumed. Additionally, in order to evaluate the degree-day ratio correctly, the changing snow cover extent in a basin during the snowmelt season must be taken into account. It is also possible to combine the degree-day approach with a radiation component so that short time interval (<24 hours) computations of snowmelt depth can be made. When snowmelt input is transformed to basin output (runoff) by a snowmelt runoff model, there is little difference between the degree-day approach and a radiation-based approach. This is fortuitous because the physically-based energy balance models will not soon displace the degree-day methods because of their excessive data requirements.     

MONTHLY RUNOFF DISTRIBUTION RELATED TO BASIN GEOGRAPHY1

ABSTRACT: Mean monthly runoff from ungaged drainage basins that have significant snowpacks each year can be estimated quite well by assuming that the time duration between snowfall and snowmelt is the predominant factor in temporal runoff distribution. That time span is related to basin temperatures which are, in turn, functions of basin elevation and latitude. Regional hydrologic analyses of gaged basin data create regression equations for estimating runoff distribution by month. These equations then can be applied to ungaged basins. Basin latitude and mean elevation are two independent variables that can be used in estimating monthly runoff distributions.     

Use of observed hydroclimatic trends to constrain projections of snowmelt season runoff in the Rio Grande headwaters

A method is developed for choosing 21st Century streamflow projections among widely varying results from a large ensemble of climate model-driven simulations. We quantify observed trends in climate–streamflow relationships in the Rio Grande headwaters, which has experienced warming temperature and declining snowpack since the mid-20th Century. Prominent trends in the snowmelt runoff season are used to assess corresponding statistics in downscaled global climate model projections. We define “Observationally Consistent (OC)” simulations as those that reproduce historical changes to linear statistics of diminished snowpack–streamflow coupling in the headwaters and an associated increase in the contribution of spring season (post-peak snowpack) precipitation to streamflow. Only a modest fraction of the ensemble of simulations meets these consistency metrics. The subset of OC simulations projects significant decreases in headwaters flow, whereas the simulations that poorly replicate historical trends exhibit a much wider range of projected changes. These results bolster confidence in model-based projections of declining runoff in the Rio Grande headwaters in the snowmelt runoff season and offer an example of a methodology for evaluating model-based projections in basins with similar hydroclimates that have experienced pronounced climate changes in the recent historical record.     

Runoff Simulation of the Headwaters of the Yellow River Using The SWAT Model With Three Snowmelt Algorithms1

Abstract: The Soil and Water Assessment Tool (SWAT) model combined with different snowmelt algorithms was evaluated for runoff simulation of an 114,345 km² mountainous river basin (the headwaters of the Yellow River), where snowmelt is a significant process. The three snowmelt algorithms incorporated into SWAT were as follows: (1) the temperature‐index, (2) the temperature‐index plus elevation band, and (3) the energy budget based SNOW17. The SNOW17 is more complex than the temperature‐based snowmelt algorithms, and requires more detailed meteorological and topographical inputs. In order to apply the SNOW17 in the SWAT framework, SWAT was modified to operate at the pixel scale rather than the normal Hydrologic Response Unit scale. The three snowmelt algorithms were evaluated under two parameter scenarios, the default and the calibrated parameters scenarios. Under the default parameters scenario, the parameter values were determined based on a review of the current literature. The purpose of this type of evaluation was to assess the applicability of SWAT in ungauged basins, where there is little observed data available for calibration. Under the calibrated parameters scenario, the parameters were calibrated using an automatic calibration program, the Shuffled Complex Evolution (SCE‐UA). The purpose of this type of evaluation was to assess the applicability of SWAT in gauged basins. Two time periods (1975‐1985 and 1986‐1990) of monthly runoff data were used in this study to evaluate the performance of SWAT with different snowmelt algorithms. Under the default parameters scenario, the SWAT model with complex energy budget based SNOW17 performed the best for both time periods. Under the calibrated parameters scenario, the parameters were calibrated using monthly runoff from 1975‐1985 and validated using monthly runoff from 1986‐1990. After parameter calibration, the performance of SWAT with the three snowmelt algorithms was improved from the default parameters scenario. Further, the SWAT model with temperature‐index plus elevation band performed as well as the SWAT model with SNOW17. The SWAT model with temperature‐index algorithm performed the poorest for both time periods under both scenarios. Therefore, it is suggested that the SNOW17 model be used for modeling ungauged basins; however, for gauged basins, the SNOW17 and simple temperature‐index plus elevation band models could provide almost equally good runoff simulation results.     

RUNOFF AND SEDIMENT YIELD UNDER GRAZING IN FOOTHILLS FESCUE GRASSLANDS OF ALBERTA1

ABSTRACT: Grazing can have a profound impact on infiltration and thus runoff and erosion. The objectives of this study were to quantify the effects of select grazing systems on rainfall and snowmelt induced runoff and sediment yield from sloped areas of the foothills fescue grasslands of Alberta, Canada. The effects of two grazing intensities (heavy and very heavy) for two durations (short duration and continuous throughout the growing season) were compared to an ungrazed control between June 1988 and April 1991. Runoff was measured using 1-rn² runoff frames and collection bucket systems. Sediment yields were then determined on samples from the collected runoff. Snowmelt was the dominant source of runoff. Snowmelt runoff was higher from the heavily grazed areas than from the very heavily grazed areas, due to the higher standing vegetation which accumulated snow in the former areas. Sediment yields as a result of snowmelt were generally low in all areas. Only a few summer storms caused runoff. Runoff volumes and sediment yields from summer rainstorms were low, due to low rainfall and to generally dry antecedent soil moisture conditions. The greatest risk of summer runoff, and thus sediment yield, appears to occur in August.     

Tributary Plunging in an Urban Lake (Onondaga Lake): Drivers,Signatures, and Implications1

Abstract: A combination of long‐term fixed‐frequency and robotic monitoring information for a polluted urban lake, Onondaga Lake, New York, and two of its tributaries is used to resolve the propensity for, and occurrences of, tributary plunging. Cooler temperatures (T) and higher salinity (S) are primarily responsible for the elevated density and plunging of one of these polluted streams for the summer through early fall interval. In‐lake transport of this plunging tributary, which receives inputs from combined sewer overflows (CSOs), is tracked by its high S during dry weather, its high turbidity (T_n) with associated lower S (dilution with rainwater) following runoff events, and by its characteristic ionic composition. These signatures are documented extending from the creek mouth, through a connecting navigation channel, through the inflow zone of the lake, and into metalimnetic depths of pelagic portions of the lake. The entry of this polluted tributary below the depth interval(s) of primary production and contact recreation has important implications for the ongoing major rehabilitation program for this lake. The plunging phenomenon diminishes the benefits previously expected for related features of the lake’s water quality from ongoing management efforts to abate CSO inputs and reduce nonpoint nutrient loading from the tributary. Previously this tributary tended to instead enter the upper layers of the lake during the operation of an adjoining soda ash manufacturing facility (closure in 1986), as a result of high lake S caused by the industry’s ionic waste discharge.     

ANALYSIS AND PREDICTION OF SURFACE RUNOFF IN AN URBANIZING WATERSHED USING SATELLITE IMAGERY1

ABSTRACT: This paper demonstrates how satellite image data [e.g., from Landsat 5 Thematic Mapper (TM)], in conjunction with an urban growth model and simple runoff calculations, can be used to estimate future surface runoff and, by implication, water quality within a watershed. To illustrate the method, predictions of land use change and surface runoff are shown for Spring Creek Watershed, a medium sized urbanizing watershed in Central Pennsylvania. Land cover classifications for this watershed were created from images for summertime 1986 and 1996 and subsequently used as input to the Clarke urban growth model, called SLEUTH, to predict land use changes to the year 2025. Simulations with this model show a progressive growth in the percentage of urban pixels and in impervious surface area in the watershed but also an increase in woodland, primarily in previously clear‐cut areas. Given that woodland area will continue to increase in area, surface runoff into Spring Creek is predicted to remain only slightly above present level. However, should the woodland amount fail to increase, surface runoff is then predicted to increase more significantly during the next 25 years. Finally, the concept of urban sprawl is addressed within the context of predicted increases in urbanization by relating the implied increase in impervious surface area to population density within the watershed.     

POLLUTANTS ASSOCIATED WITH SAND AND SALT APPLIED TO ROADS IN MINNESOTA1

ABSTRACT: The component of snowmelt pollutant washoff due to sand and salt application to roadways in Minnesota is simulated. Laboratory methods are used to extract various pollutants from sand-salt mixtures commonly used in the Minneapolis-St. Paul Metropolitan Area of Minnesota for keeping winter road conditions safe. Values derived in the laboratory are compared with actual snowmelt runoff values to estimate the contribution of materials application. High concentrations of solids, phosphorus, lead and zinc in snowmelt from road surfaces axe due in part to sand and salt spread to improve winter driving conditions. The source of the sand and salt appears to be influential in determining the pollutant levels. Judicious use and careful application of materials can reduce the increment of pollution due to anti-skid sand and salt applied to road surfaces.     

GENERAL-CIRCULATION-MODEL SIMULATIONS OF FUTURE SNOWPACK IN THE WESTERN UNITED STATES1

ABSTRACT: April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western U.S. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.     

POTENTIAL CLIMATE CHANGE IMPACTS ON WATER RESOURCES IN THE GREAT PLAINS1

ABSTRACT: This paper reports on the current assessment of climate impacts on water resources, including aquatic ecosystems, agricultural demands, and water management, in the U.S. Great Plains. Climate change in the region may have profound effects on agricultural users, aquatic ecosystems, and urban and industrial users alike. In the central Great Plains Region, the potential impacts of climate changes include changes in winter snowfall and snow-melt, growing season rainfall amounts and intensities, minimum winter temperature, and summer time average temperature. Specifically, results from general circulation models indicate that both annual average temperatures and total annual precipitation will increase over the region. However, the seasonal patterns are not uniform. The combined effect of these changes in weather patterns and average seasonal climate will affect numerous sectors critical to the economic, social and ecological welfare of this region. Research is needed to better address the current competition among the water needs of agriculture, urban and industrial uses, and natural ecosystems, and then to look at potential changes. These diverse demands on water needs in this region compound the difficulty in managing water use and projecting the impact of climate changes among the various critical sectors in this region.