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.     

HYDROCLIMATIC VARIABILITY IN THE ROCKY MOUNTAINS1

ABSTRACT: The spatial and temporal variability of hydroclimatic elements were investigated in the central and northern Rocky Mountains (Colorado, Idaho, Montana, Utah, and Wyoming) during the 1951–1985 period. The three hydroclimatic elements studied were total water-year (October 1-September 30) streamflow (ST), winter (October 1-March 31) accumulated precipitation (PR), and April 1 snowpack (SN). An analysis of 14 virgin watersheds showed wide spatial djfferences in the temporal variability of SN, PR, and ST, and these were found to be caused largely by basin exposure to moist air flows. The more stable (low variability) basins were those exposed to prevailing northerly to westerly flow, while unstable (high variability) basins were exposed to occasional southwesterly to southeasterly moist flow. Snowpack was the better indicator of ST in 11 of the 14 watersheds, explaining 37 to 87 percent of the ST variance. Analysis of the spatial variability, based on all SN and PR data from across the study area, revealed 11 discrete climatic regions. Both SN and PR exhibited coherent regions of stable and unstable temporal variability. The average variability between stable and unstable regions differed by a factor of two, and the differences were best explained by the exposure of the mountain barrier to moist air flows.     

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.     

EFFECTS OF CLIMATE CHANGE ON HYDROLOGY AND WATER RESOURCES IN THE COLUMBIA RIVER BASIN1

ABSTRACT: As part of the National Assessment of Climate Change, the implications of future climate predictions derived from four global climate models (GCMs) were used to evaluate possible future changes to Pacific Northwest climate, the surface water response of the Columbia River basin, and the ability of the Columbia River reservoir system to meet regional water resources objectives. Two representative GCM simulations from the Hadley Centre (HC) and Max Planck Institute (MPI) were selected from a group of GCM simulations made available via the National Assessment for climate change. From these simulations, quasi-stationary, decadal mean temperature and precipitation changes were used to perturb historical records of precipitation and temperature data to create inferred conditions for 2025, 2045, and 2095. These perturbed records, which represent future climate in the experiments, were used to drive a macro-scale hydrology model of the Columbia River at 1/8 degree resolution. The altered streamflows simulated for each scenario were, in turn, used to drive a reservoir model, from which the ability of the system to meet water resources objectives was determined relative to a simulated hydrologic base case (current climate). Although the two GCM simulations showed somewhat different seasonal patterns for temperature change, in general the simulations show reasonably consistent basin average increases in temperature of about 1.8–2.1°C for 2025, and about 2.3–2.9°C for 2045. The HC simulations predict an annual average temperature increase of about 4.5°C for 2095. Changes in basin averaged winter precipitation range from -1 percent to + 20 percent for the HC and MPI scenarios, and summer precipitation is also variously affected. These changes in climate result in significant increases in winter runoff volumes due to increased winter precipitation and warmer winter temperatures, with resulting reductions in snowpack. Average March 1 basin average snow water equivalents are 75 to 85 percent of the base case for 2025, and 55 to 65 percent of the base case by 2045. By 2045 the reduced snowpack and earlier snow melt, coupled with higher evapotranspiration in early summer, would lead to earlier spring peak flows and reduced runoff volumes from April-September ranging from about 75 percent to 90 percent of the base case. Annual runoff volumes range from 85 percent to 110 percent of the base case in the simulations for 2045. These changes in streamflow create increased competition for water during the spring, summer, and early fall between non-firm energy production, irrigation, instream flow, and recreation. Flood control effectiveness is moderately reduced for most of the scenarios examined, and desirable navigation conditions on the Snake are generally enhanced or unchanged. Current levels of winter-dominated firm energy production are only significantly impacted for the MPI 2045 simulations.     

PRECIPITATION DISTRIBUTION IN COASTAL BRITISH COLUMBIA1

ABSTRACT: The spatial distribution and the temporal and spatial variation of the annual, seasonal, and monthly precipitation in two mountainous watersheds in southwestern British Columbia, Canada, have been analyzed using a detailed database for 1971–1990 in the Capilano and Seymour watersheds. The analysis showed that the precipitation increases up to the mid-position of the watersheds, and then either levels off or decreases. Precipitation on mountain slopes and in the valley at the same distance from the beginning of the slope is similar, and the barrier height is identified as the dominant parameter which influences the precipitation distribution. The temporal variation of the precipitation is the smallest at the mid-position of the watersheds. This variability is the least in the fall and winter and largest in the summer. Correlation between the precipitation accumulations at various stations is large, ranging from 0.80 for the wet period of October-March to 0.65 for the dry period of April-September for distances less than 32 km. Comparison with other studies and the analyses of precipitation and runoff data from coastal British Columbia showed that the results of this study are perhaps general and thus transferable to similar areas in the coastal Pacific Northwest.     

APPLICATIONS OF A GIS FOR MODELING THE SENSITIVITY OF WATER RESOURCES TO ALTERATIONS IN CLIMATE IN THE GUNNISON RIVER BASIN,COLORADO1

ABSTRACT: The Gunnison River drains a mountainous basin in western Colorado, and is a large contributor of water to the Colorado River. As part of a study to assess water resource sensitivity to alterations in climate in the Gunnison River basin, climatic and hydrologic processes are being modeled. A geographic information system (GIS) is being used in this study as a link between data and modelers - serving as a common data base for project personnel with differing specialties, providing a means to investigate the effects of scale on model results, and providing a framework for the transfer of parameter values among models. Specific applications presented include: (1) developing elevation grids for a precipitation model from digital elevation model (DEM) point-elevation values, and visualizing the effects of grid resolution on model results; (2) using a GIS to facilitate the definition and parameterization of a distributed-parameters, watershed model in multiple basins; and (3) nesting atmospheric and hydrologic models to produce possible scenarios of climate change.     

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.     

ESTIMATING REGIONAL SNOW WATER EQUIVALENT WITH A SIMPLE SIMULATION MODEL1

A simple simulation model designed to monitor snow-packs of the central Sierra Nevada is described. The model estimates average snow water equivalent for rectangular subregions in the area. Static subregion characteristics, daily precipitation and mean and minimum air temperatures measured at three index stations are the only needed input values. A water balance technique simulates daily snowpack changes in each subregion. Reasonable basinwide water equivalent values are produced. The procedure should be useful for estimating snow water distribution in large mountainous watersheds.     

Probabilistic Streamflow Generation Model for Data Sparse Arid Watersheds1

Abstract: The authors present a model that generates streamflow for ephemeral arid streams. The model consists of a stochastic hourly precipitation point process model and a conceptual model that transforms precipitation into flow. It was applied to the Santa Cruz River at the border crossing from Mexico into Southern Arizona. The model was constructed for four different seasons and three categories of inter‐annual variability for the wet seasons of summer and winter. The drainage area is ungauged and precipitation information was inferred from a precipitation gauge downstream. The precipitation gauge record was evaluated against simulated precipitation from a mesoscale numerical weather prediction model, and was found to be the representative of the regional precipitation variability. The flow generation was found to reproduce the variability in the observed record at the daily, seasonal and annual time scales, and it is suitable for use in planning studies for the study site.     

NETWORK DESIGN FOR WATER SUPPLY FORECASTING IN THE WEST1

ABSTRACT: The objective is to develop techniques to evaluate how changes in basic data networks can improve accuracy of water supply forecasts for mountainous areas. The approach used was to first quantify how additional data would improve our knowledge of winter precipitation, and second to estimate how this knowledge translates, quantitatively, into improvement in forecast accuracy. A software system called DATANET was developed to analyze each specific gage network alternative. This system sets up a fine mesh of grid points over the basin. The long-term winter mean precipitation at each grid point is estimated using a simple atmospheric model of the orographic precipitation process. The mean runoff at each grid point is computed from the long-term mean precipitation estimate. The basic runoff model is calibrated to produce the observed long-term runoff. The error analysis is accomplished by comparing the error in forecasts based on the best possible estimate of precipitation using all available data with the error in the forecasts based on the best possible estimate of winter precipitation using only the gaged data. Different data network configurations of gage sites can be compared in terms of forecast errors.     

Assessing the Impact of Areal Precipitation Input on Streamflow Simulations Using the SWAT Model1

Masih Ilyas, Shreedhar Maskey, Stefan Uhlenbrook, and Vladimir Smakhtin, 2011. Assessing the Impact of Areal Precipitation Input on Streamflow Simulations Using the SWAT Model. Journal of the American Water Resources Association (JAWRA) 47(1):179‐195. DOI: 10.1111/j.1752‐1688.2010.00502.x Abstract: Reduction of input uncertainty is a challenge in hydrological modeling. The widely used model Soil Water Assessment Tool (SWAT) uses the data of a precipitation gauge nearest to the centroid of each subcatchment as an input for that subcatchment. This may not represent overall catchment precipitation conditions well. This paper suggests an alternative – using areal precipitation obtained through interpolation. The effectiveness of this alternative is evaluated by comparing its simulations with those based on the standard SWAT precipitation input procedure. The model is applied to mountainous semiarid catchments in the Karkheh River basin, Iran. The model performance is evaluated at daily, monthly, and annual scales by using a number of performance indicators at 15 streamflow gauging stations each draining an area in the range of 590‐42,620 km². The comparison suggests that the use of areal precipitation improves model performance particularly in small subcatchments in the range of 600‐1,600 km². The modified areal precipitation input results in increased reliability of simulated streamflows in the areas of low rain gauge density. Both precipitation input methods result in reasonably good simulations for larger catchments (over 5,000 km²). The use of areal precipitation input improves the accuracy of simulated streamflows with spatial resolution and density of rain gauges having significant impact on results.     

EFFECTS OF CLIMATE CHANGE ON WATER RESOURCES IN THE DELAWARE RWER BASIN1

ABSTRACT: The effects of potential climate change on water resources in the Delaware River basin were determined. The study focused on two important water-resource components in the basin: (1) storage in the reservoirs that supply New York City, and (2) the position of the salt front in the Delaware River estuary. Current reservoir operating procedures provide for releases from the New York City reservoirs to maintain the position of the salt front in the estuary downstream from freshwater intakes and ground-water recharge zones in the Philadelphia metropolitan area. A hydrologic model of the basin was developed to simulate changes in New York City reservoir storage and the position of the salt front in the Delaware River estuary given changes in temperature and precipitation. Results of simulations indicated that storage depletion in the New York City reservoirs is a more likely effect of changes in temperature and precipitation than is the upstream movement of the salt front in the Delaware River estuary. In contrast, the results indicated that a rise in sea level would have a greater effect on movement of the salt front than on storage in the New York City reservoirs. The model simulations also projected that, by decreasing current mandated reservoir releases, a balance can be reached wherein the negative effects of climate change on storage in the New York City reservoirs and the position of the salt front in the Delaware River estuary are minimized. Finally, the results indicated that natural variability in climate is of such magnitude that its effects on water resources could overwhelm the effects of long-term trends in precipitation and temperature.     

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.     

Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins1

Jin, Xin and Venkataramana Sridhar, 2012. Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins. Journal of the American Water Resources Association (JAWRA) 48(2): 197‐220. DOI: 10.1111/j.1752‐1688.2011.00605.x Abstract: In the Pacific Northwest, warming climate has resulted in a lengthened growing season, declining snowpack, and earlier timing of spring runoff. This study characterizes the impact of climate change in two basins in Idaho, the Spokane River and the Boise River basins. We simulated the basin‐scale hydrology by coupling the downscaled precipitation and temperature outputs from a suite of global climate models and the Soil and Water Assessment Tool (SWAT), between 2010 and 2060 and assess the impacts of climate change on water resources in the region. For the Boise River basin, changes in precipitation ranged from ?3.8 to 36%. Changes in temperature were expected to be between 0.02 and 3.9°C. In the Spokane River region, changes in precipitation were expected to be between ?6.7 and 17.9%. Changes in temperature appeared between 0.1 and 3.5°C over a period of the next five decades between 2010 and 2060. Without bias‐correcting the simulated streamflow, in the Boise River basin, change in peak flows (March through June) was projected to range from ?58 to +106 m³/s and, for the Spokane River basin, the range was expected to be from ?198 to +88 m³/s. Both the basins exhibited substantial variability in precipitation, evapotranspiration, and recharge estimates, and this knowledge of possible hydrologic impacts at the watershed scale can help the stakeholders with possible options in their decision‐making process.     

EFFECTS OF IMPROVED PRECIPITATION ESTIMATES ON AUTOMATED RUNOFF MAPPING: EASTERN UNITED STATES1

ABSTRACT: We evaluated maps of runoff created by means of two automated procedures. We implemented each procedure using precipitation estimates of both 5-km and 10-km resolution from PRISM (Parameter-elevation Regressions on Independent Slopes Model). Our goal was to determine if using the 5-km PRISM estimates would improve map accuracy. Visual inspection showed good general agreement among our runoff maps, as well as between our maps and one produced using a manual method. A quantitative uncertainty analysis comparing runoff interpolated from our maps with gage data that had been withheld showed slightly smaller actual and percentage interpolation errors for the 5-km PRISM-based maps. Our analyses suggest a modest region-wide improvement in runoff map accuracy with the use of PRISM-based precipitation estimates of 5-km (compared to 10-km) resolution.     

Spatial Calibration and Temporal Validation of Flow for Regional Scale Hydrologic Modeling1

Abstract: Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validation is performed at the river basin outlet without accounting for spatial variations in hydrological parameters within the subunits. In this study, we calibrated the model to capture the spatial variations in runoff at subwatershed level to assure local water balance, and validated the streamflow at key gaging stations along the river to assure temporal variability. Ohio and Arkansas‐White‐Red River Basins of the United States were modeled using Soil and Water Assessment Tool (SWAT) for the period from 1961 to 1990. R² values of average annual runoff at subwatersheds were 0.78 and 0.99 for the Ohio and Arkansas Basins. Observed and simulated annual and monthly streamflow from 1961 to 1990 is used for temporal validation at the gages. R² values estimated were greater than 0.6. In summary, spatially distributed calibration at subwatersheds and temporal validation at the stream gages accounted for the spatial and temporal hydrological patterns reasonably well in the two river basins. This study highlights the importance of spatially distributed calibration and validation in large river basins.     

GIS‐Based Spatial Precipitation Estimation: A Comparison of Geostatistical Approaches1

Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km², which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models.     

Decreased Runoff Response to Precipitation,Little Missouri River Basin,Northern Great Plains,USA

High variability in precipitation and streamflow in the semiarid northern Great Plains causes large uncertainty in water availability. This uncertainty is compounded by potential effects of future climate change. We examined historical variability in annual and growing season precipitation, temperature, and streamflow within the Little Missouri River Basin and identified differences in the runoff response to precipitation for the period 1976‐2012 compared to 1939‐1975 (n = 37 years in both cases). Computed mean values for the second half of the record showed little change (<5%) in annual or growing season precipitation, but average annual runoff at the basin outlet decreased by 22%, with 66% of the reduction in flow occurring during the growing season. Our results show a statistically significant (p < 0.10) 27% decrease in the annual runoff response to precipitation (runoff ratio). Surface‐water withdrawals for various uses appear to account for <12% of the reduction in average annual flow volume, and we found no published or reported evidence of substantial flow reduction caused by groundwater pumping in this basin. Results of our analysis suggest that increases in monthly average maximum and minimum temperatures, including >1°C increases in January through March, are the dominant driver of the observed decrease in runoff response to precipitation in the Little Missouri River Basin.     

Calibration and Uncertainty Analysis Using the Sparrow Model for Dissolved‐Solids Transport in the Upper Colorado River Basin

Salinity in the Upper Colorado River Basin (UCRB) is due to both natural sources and processes, and anthropogenic activities. Given economic damage due to salinity of $295 million in 2010, understanding salinity sources and production together with transport are of great importance. SPAtially Referenced Regressions On Watershed (SPARROW) is a nonlinear regression water quality model that simulates sources and transport of contaminants such as dissolved‐solids. However, SPARROW simulations of dissolved‐solids in the UCRB only represent conditions through 1998 due to limited data availability. More importantly, prior simulations focused on a single year calibration and its transferability to other years, and the validity of this approach is questionable, given the changing hydrologic and climatic conditions. This study presents different calibration approaches to assess the best approach for reducing model uncertainty. This study conducted simulations from 1999 to 2011, and the results showed good model accuracy. However, the number of monitoring stations decreased significantly in recent years resulting in higher model uncertainty. The uncertainty analysis was conducted using SPARROW results and bootstrapping. The results suggest that the watershed rankings based on salinity yields changed due to the uncertainty analysis and therefore, uncertainty consideration should be an important part of the management strategy.     

THE DEVELOPMENT OF THE NILE HYDROMETEOROLOGICAL FORECAST SYSTEM1

ABSTRACT: The National Oceanic and Atmospheric Administration is developing a river forecast system for the Nile River in Egypt. The river forecast system operates on scientific work stations using hydrometeorological models and software to predict inflows into the high Aswan Dam and forecast flow hydrographs at selected gaging locations above the dam The Nile Forecasting System (NFS) utilizes satellite imagery from the METEOSAT satellite as the input to the forecast system. Satellite imagery is used to estimate precipitation over the Blue Nile Basin using five different techniques. Observed precipitation data and climatic statistics are used to improve precipitation estimation. Precipitation data for grid locations are input to a distributed water balance model, a hill slope routing model, and a channel routing model. A customized Geographic Information System (GIS) was developed to show political boundaries, rivers, terrain elevation, and gaging network. The GIS was used to develop hydrologic parameters for the basin and is used for multiple display features.