REGULATED RIVER MODELING FOR CLIMATE CHANGE IMPACT ASSESSMENT: THE MISSOURI RIVER1

ABSTRACT: The Great Plains of the United States, drained primanly by the Missouri River, are very sensitive to shifts in climate. The six main stem dams on the Missouri River control more than one‐half of the nearly 1.5 million square kilometer basin and can store three times the annual inflow from upstream. The dams are operated by the U.S. Army Corps of Engineers using a Master Manual that describes system priorities and benefits. The complex operational rules were incorporated into the Soil and Water Assessment Tool computer model (SWAT). SWAT is a distributed parameter rainfall‐runoff model capable of simulating the transpiration suppression effects of CO₂ enrichment. The new reservoir algorithms were calibrated using a 25‐year long historic record of basin climate and discharge records. Results demonstrate that it is possible to incorporate the operation of a highly regulated river system into a complex rainfall‐runoff model. The algorithms were then tested using extreme climate scenarios indicative of a prolonged drought, a short drought, and a ten percent increase in basin‐wide precipitation. It is apparent that the rules for operating the reservoirs will likely require modification if, for example, upper‐basin precipitation were to increase only ten percent under changed climate conditions.     

LAND SURFACE PARAMETERIZATIONS OF GCMs AND MACROSCALE HYDROLOGICAL MODELS1

ABSTRACT: Climatic variation and the possibility of anthropogenically-caused climatic change have emphasized the need for global hydrological cycle models able to simulate the impacts of climate on the atmosphere, continents and oceans. To date, global atmospheric and oceanic models have been developed but, to the best of the author's knowledge, there are no continental hydrological models. Instead, hydrological models continue to develop at the catchment scale and the land phase component of the global hydrologic cycle is modeled as parameterizations within atmospheric models. The author argues that this is not the best solution; that the present land surface components of atmospheric models do not accurately model land phase hydrology and that, instead, atmospheric and oceanic models should be linked to continental-scale hydrological models to form a true model of the global hydrological cycle.     

DOWNSCALED CLIMATE AND STREAMFLOW STUDY OF THE SOUTHWESTERN UNITED STATES1

ABSTRACT: Downscaling coarse resolution climate data to scales that are useful for impact assessment studies is receiving increased attention. Basin-scale hydrologic processes and other local climate impacts related to water resources such as reservoir management, crop and forest productivity, and ecosystem response require climate information at scales that are much finer than current and future GCM resolutions. The Regional Climate System Model (RCSM) is a dynamic downscaling system that has been used since 1994 for short-term precipitation and streamflow predictions and seasonal hindcast analysis with good skill. During the 1997–1998 winter, experimental seasonal forecasts were made in collaboration with the NOAA Climate Prediction Center and UCLA with promising results. Preliminary studies of a control and 2°CO₂ perturbation for the southwestern U.S. have been performed.     

EVALUATION OF PROBABILITY DENSITY FUNCTIONS IN PRECIPITATION MODELS FOR THE PACIFIC NORTHWEST1

ABSTRACT: Recent work has found that a one-parameter Weibull model of wet day precipitation amount based on the Weibull distribution provides a better fit to historical daily precipitation data for eastern U.S. sites than other one-parameter models. The general two-parameter Weibull distribution was compared in this study to other widely used distributions for describing the distribution of daily precipitation event sizes at 99 sites from the U.S. Pacific Northwest. Surprisingly little performance was sacrificed by reducing the two-parameter Weibull to a single-parameter distribution. Advantages of the single-parameter model included requiring only the mean wet day precipitation amount for calibration, invertibility for simulation purposes, and ease of analytical manipulation. The fit of the single-parameter Weibull to the 99 stations included in this study was significantly better than other single-parameter models tested, and performed as well as the widely endorsed, more cumbersome, two-parameter gamma model. Both the one-and two-parameter Weibull distributions are shown to have b-moments that are consistent with historical precipitation data, while the ratio of b-skew and b-variance in the gamma model is inconsistent with the historical recerd by this measure. In addition, it was found that the two-parameter gamma distribution was better fit using the method of moments estimators than maximum likelihood estimates. These findings suggested that the distribution in precipitation among sites in the Pacific Northwest with dramatically different settings are nearly identical if expressed in proportion to the mean site event size.     

SOIL MOISTURE SENSORS FOR URBAN LANDSCAPE IRRIGATION: EFFECTIVENESS AND RELIABILITY1

ABSTRACT: Granular matrix soil moisture sensors were used to control urban landscape irrigation in Boulder, Colorado, during 1997. The purpose of the study was to evaluate the effectiveness and reliability of the technology for water conservation. The 23 test sites included a traffic median, a small city park, and 21 residential sites. The results were very good. The system limited actual applications to an average of 73 percent of the theoretical requirement. This resulted in an average saving of $331 per installed sensor. The sensors were highly reliable. All 23 sensors were placed in service at least three years prior to the 1997 study during earlier studies. Of these, only two had failed by the beginning of the 1997 study, both due to external factors. Including replacement of these failed sensors, the total repair cost for the 1997 irrigation season was less than $270. The effort required to maintain each system was small, only about 6–7 minutes per visit. Each site was visited weekly for this study, but less frequent visits could be made in practice. The sensors observed in this study performed well, significantly reduced water consumption, and were easy to monitor and maintain. Soil moisture sensors appear to be a useful and economical tool for urban water conservation.     

TEMPORAL RESPONSES OF SURFACE‐WATER AND GROUND‐WATER TO PRECIPITATION IN ILLINOIS1

ABSTRACT: Illinois data from 168 months (1986–1999) were investigated to determine the responses of surface‐water and ground‐water resources to precipitation. Such responses were generally within the month of occurrence or one to two months later, with recovery being reached another one to three months into the future, depending on season of the year. Although the drought of 1988 immediately impacted surface‐water and ground‐water resources, the time of recovery was substantially longer compared to those of individual dry months, generally continuing for several months. The extremely wet summer of 1993 resulted in elevated responses in water resources almost immediately, but in this instance continued through the following fall and winter, into the spring of 1994.     

PRECIPITATION CHANGES FROM 1956 TO 1996 ON THE WALNUT GULCH EXPERIMENTAL WATERSHED1

ABSTRACT: The climate of Southern Arizona is dominated by summer precipitation, which accounts for over 60 percent of the annual total. Summer and non‐summer precipitation data from the USDA‐ARS Walnut Gulch Experimental Watershed are analyzed to identify trends in precipitation characteristics from 1956 to 1996. During this period, annual precipitation increased. The annual precipitation increase can be attributed to an increase in precipitation during non‐summer months, and is paralleled by an increase in the proportion of annual precipitation contributed during non‐summer months. This finding is consistent with previously reported increases in non‐summer precipitation in the southwestern United States. Detailed event data were analyzed to provide insight into the characteristics of precipitation events during this time period. Precipitation event data were characterized based on the number of events, event precipitation amount, 30‐minute event intensity, and event duration. The trend in non‐summer precipitation appears to be a result of increased event frequency since the number of events increased during nonsummer months, although the average amount per event, average event intensity, and average event duration did not. During the summer “monsoon” season, the frequency of recorded precipitation events increased but the average precipitation amount per event decreased. Knowledge of precipitation trends and the characteristics of events that make up a precipitation time series is a critical first step in understanding and managing water resources in semiarid ecosystems.     

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.     

PREDICTING THE SUMMER TEMPERATURE OF SMALL STREAMS IN SOUTHWESTERN WISCONSIN1

ABSTRACT: One of the biggest challenges in managing cold water streams in the Midwest is understanding how stream temperature is controlled by the complex interactions among meteorologic processes, channel geometry, and ground water inflow. Inflow of cold ground water, shade provided by riparian vegetation, and channel width are the most important factors controlling summer stream temperatures. A simple screening model was used to quantitatively evaluate the importance of these factors and guide management decisions. The model uses an analytical solution to the heat transport equation to predict steady‐state temperature throughout a stream reach. The model matches field data from four streams in southwestern Wisconsin quite well (typically within 1°C) and helps explain the observed warming and cooling trends along each stream reach. The distribution of ground water inflow throughout a stream reach has an important influence on stream temperature, and springs are especially effective at providing thermal refuge for fish. Although simple, this model provides insight into the importance of ground water and the impact different management strategies, such as planting trees to increase shade, may have on summer stream temperature.     

MEAN AREAL PRECIPITATION FOR DAILY HYDROLOGIC MODELING IN MOUNTAINOUS REGIONS1

ABSTRACT: A procedure using detrended kriging has been developed to calculate daily values of mean areal precipitation (MAP) for input to hydrologic models. The important features of this procedure that overcome weaknesses in existing MAP procedures are: (1) specific precipitation-elevation relationships are determined for each time period as opposed to using relationships based on climatological averages, (2) spatial variability is incorporated by estimating precipitation for each grid cell over a watershed, (3) the spatial correlation structure of precipitation is explicitly modeled, and (4) station weights for precipitation estimates are determined objectively and optimally. Detailed cross-validation testing of the procedure was done for the Reynolds Creek research watershed in southwestern Idaho. The procedure is suitable for use in operational streamflow forecasting.     

WATER LEVEL FLUCTUATIONS IN AN URBAN POND: CLIMATIC OR ANTHROPOGENIC IMPACT?1

ABSTRACT: In 1996, the Illinois State Geological Survey began an investigation of fluctuating water levels in a pond in Cary, Illinois. The cause of the fluctuations appeared to be ground water discharge into a storm sewer recently installed by the Illinois Department of Transportation. However, analysis of climatic data provided an equally likely explanation of the fluctuations. Distinguishing the effect of climatic variations from the effect of the storm sewer was hampered by the lack of antecedent ground water and surface water data. In similar settings, it is recommended that ground water and surface water data be collected prior to initiating any infrastructure improvements.     

NWSRFS CALIBRATION PARAMETER SELECTION AND GEOLOGIC REASONING: PACIFIC NORTHWEST CASES1

ABSTRACT: The National Weather Service River Forecast System (NWSRFS) is the new hydrologic prediction model for the National Weather Service (NWS) and provides guidance to meteorologists who issue NWS Flood Warnings to the public. The primary submodel within NWSRFS is the Sacramento Soil Moisture Accounting (SAC-SMA) model, which predicts surface runoff as a function of meteorological, geological, and soil data calibrated over a watershed. The research presented here focuses on a different approach to NWSRFS calibrations: greater utilization of geologic and soil data, in order to give the model better predictive capability. Geologic understanding can create better insights for the initial estimation and subsequent adjustment of SAC-SMA parameters. Fifteen calibrated Pacific Northwest drainages reveal a variety of hydrogeologic responses. For example, results for the Mount Rainier drainages show the complex interaction between active glaciers, impermeable volcanic surfaces, and glacial sedimentary valleys. Unweathered volcanic terrains show flashy peak flows, fast flow recessions, and low baseflow. Sedimentary terrains display subdued peak flows, slow flow recessions, and higher baseflow. Operational implementation of these calibrations at the NWS's Northwest River Forecast Center has yielded more accurate predictive results since 1995. NWS hydrologic forecasters nationwide could benefit from using drainage basin geologic characteristics in understanding and improving model calibrations and real time forecasts.     

TREE-RING RECONSTRUCTION OF UPPER GILA RWER DISCHARGE1

ABSTRACT: Effective planning for use of water resources requires accurate information on hydrologic variability induced by climatic fluctuations. Tree-ring analysis is one method of extending our knowledge of hydrologic variability beyond the relatively short period covered by gaged streamflow records. In this paper, a network of recently developed tree-ring chronologies is used to reconstruct annual river discharge in the upper Gila River drainage in southeastern Arizona and southwestern Arizona since A.D. 1663. The need for data on hydrologic variability for this semi-arid basin is accentuated because water supply is inadequate to meet current demand. A reconstruction based on multiple linear regression (R²=0.66) indicates that 20th century is unusual for clustering of high-discharge years (early 1900s), severity of multiyear drought (1950s), and amplification of low-frequency discharge variations. Periods of low discharge recur at irregular intervals averaging about 20 years. Comparison with other tree-ring reconstructions shows that these low-flow periods are synchronous from the Gila Basin to the southern part of the Upper Colorado River Basin.     

PREDICTION OF MEAN ANNUAL FLOWS IN NORTH AND CENTRAL FLORIDA1

ABSTRACT: A frequency analysis approach for the prediction of flow characteristics at ungaged locations is applied to a region of high annual precipitation and low topography in north and central Florida. Stationary time series of annual flows are fitted with the lognormal distribution and estimated parameters of the distribution are fitted by third order trend surfaces. These explain 65 and 74 percent of the observed variances in the mean and standard deviation, respectively. Predictions of parameters are then made for several locations previously unused in the study and they are used to estimate the return periods of various flows from the lognormal distribution. Application of the Kolmogorov-Smirnov goodness-of-fit test suggests that only one of the five test stations can be considered significantly different from the observed data, confirming the applicability of this technique.     

GROUND-WATER RECHARGE THROUGH ACTWE SAND DUNES IN NORTHWESTERN NEVADA1

ABSTRACT: Most water-resouree investigations in semiarid basins of the Great Basin in western North America conclude that ground-water recharge from direct precipitation on the valley floor is negligible. However, many of these basins contain large areas covered by unvegetated, active sand dunes that may act as conduits for ground-water recharge. The potential for this previously undocumented recharge was investigated in an area covered by sand dunes in Desert Valley, northwestern Nevada, using a deep percolation model. The model uses daily measurements of precipitation and temperature th determine energy and moisture balances, from which estimates of long-term mean annual recharge are made. For the study area, the model calculated a mean annual recharge rate of as much as 1.3 inches per year, or 17 percent of the long-term mean precipitation. Model simulations also indicate that recharge would be virtually zero if the study area were covered by vegetation rather than dunes.     

STREAM TEMPERATURE CORRELATIONS WITH AIR TEMPERATURES IN MINNESOTA: IMPLICATIONS FOR CLIMATE WARMING1

ABSTRACT: Air temperatures are sometimes used as easy substitutes for stream temperatures. To examine the errors associated with this substitution, linear relationships between 39 Minnesota stream water temperature records and associated air temperature records were analyzed. From the lumped data set (38,082 daily data pairs), equations were derived for daily, weekly, monthly, and annual mean temperatures. Standard deviations between all measured and predicted water temperatures were 3.5°C (daily), 2.6°C (weekly), 1.9°C (monthly), and 1.3°C (annual). Separate analyses for each stream gaging station gave substantially lower standard deviations. Weather monitoring stations were, on average, 37.5 km from the stream. The measured water temperatures follow the annual air temperature cycle closely. No time lags were taken into account, and periods of ice cover were excluded from the analysis. If atmospheric CO₂ doubles in the future, air temperatures in Minnesota are projected (CCC GCM) to rise by 4.3°C in the warm season (April-October). This would translate into an average 4.1°C stream temperature rise, provided that stream shading would remain unaltered.     

SPATIAL ANALYSIS FOR MONTHLY RAINFALL IN SOUTH FLORIDA1

ABSTRACT: Several methods have been developed to interpolate point rainfall data and integrate areal rainfall data from any network of stations. From previous studies, it can be concluded that models for spatial analysis of rainfall are dependent on topography, area of analysis, type of rainfall, and density of gauging network. The purpose of this study is to evaluate a set of six appropriate models for point and areal rainfall estimations over a 4000 square mile area in South Florida. In this study, a case of developing spatial continuity model for monthly rainfall from a database that had various lengths of records and missing data is documented. The spatial correlation and variogram models for monthly rainfall were developed. Six methods of spatial interpolation were applied and the results validated with historical observations. The results of the study indicate that the multiquadric, kriging, and optimal interpolation schemes are the best three methods for interpolation of monthly rainfall within the study area. The optimal and kriging methods have the advantage of providing estimates of the error of interpolation. The optimal interpolation method uses the spatial correlation function and the kriging method uses the variogram function. The two spatial functions are related. Either of the two methods provide good estimates of monthly point and areal rainfall in the study area.     

ESTIMATING ATRAZINE LEACHING IN THE MIDWEST1

Data from seven Management Systems Evaluation Areas (MSEA) were used to test the sensitivity of a leaching model, Pesticide Root Zone Model-2, to a variety of hydrologic settings in the Midwest. Atrazine leaching was simulated because it was prevalent in the MSEA studies and is frequently detected in the region's groundwater. Short-term simulations used site specific soil and chemical parameters. Generalized simulations used data avail. able from regional soil databases and standardized variables. Accurate short-term simulations were precluded by lack of antecedent atrazine concentrations in the soil profile and water, suggesting that simulations using data for less than five years underestimate atrazine leaching. The seven sites were ranked in order of atrazine detection frequency (concentration > 0.2 μg L^-1) in soil water at 2 m depth in simulations. The rank order of the sites based on long-term simulations were similar to the ranks of sites based on atrazine detection frequency from groundwater monitoring. Simulations with Map Unit Use File (MUUF) soils data were more highly correlated with ranks of observed atrazine detection frequencies than were short-term simulations using site-specific soil data. Simulations using the MIJUIF data for soil parameters were sufficiently similarity to observed atrazine detection to allow the credible use of regional soils data for simulating leaching with PRZM-2 in a variety of Midwest soil and hydrologic conditions. This is encouraging for regional modeling efforts because soil parameters are among the most critical for operating PRZM-2 and many other leaching models.     

ANALYSIS AND MODELING OF LONG-TERM STREAM TEMPERATURES ON THE STEAMBOAT CREEK BASIN,OREGON: IMPLICATIONS FOR LAND USE AND FISH HABITAT1

ABSTRACT: Steamboat Creek basin is an important source of timber and provides crucial spawning and rearing habitat for anadromous steelhead trout (Oncorhynchus mykiss). Because stream temperatures are near the upper limit of tolerance for the survival of juvenile steelhead, the possible long-term effect of clear-cut logging on stream temperatures was assessed. Twenty-year (1969–1989) records of summer stream temperature and flow from four tributaries and two reaches of Steamboat Creek and Boulder Creek (a nearby unlogged watershed) were analyzed. Logging records for the Steamboat Creek basin and air temperature records also were used in the analysis. A time-series model of the components of stream temperature (seasonal cycle of solar radiation, air temperature, streamflow, an autoregressive term of order 1, and a linear trend variable) was fitted to the water-temperature data. The linear trend variable was significant in all the fitted models except Bend Creek (a tributary fed by cool ground-water discharge) and Boulder Creek. Because no trends in either climate (i.e., air temperature) or streamflow were found in the data, the trend variable was associated with the pre-1969 loss and subsequent regrowth of riparian vegetation and shading canopies.