CLIMATOLOGICAL WATERSHED CALIBRATION1

ABSTRACT: This study tests the hypothesis that climatic data can be used to develop a watershed model so that stream flow changes following forest harvest can be determined. Measured independent variables were precipitation, daily maximum and minimum temperature, and concurrent relative humidity. Computed variables were humidity deficit, saturated vapor pressure, and ambient vapor pressure. These climatic variables were combined to compute a monthly evaporation index. Finally, the evaporation index and monthly precipitation were regressed with measured monthly stream flow and the monthly estimates of stream flow were combined for the hydrologic year. A regression of predicted versus measured annual stream flow had a standard error of 1.5 inches (within 6.1 percent of the measured value). When 10, 15, and 20 years of data were used to develop the regression equations, predicted minus measured stream flow for the last 7 years of record (1972–1978) were within 16.8, 11.5, and 9.7 percent of the measured mean, respectively. Although single watershed calibration can be used in special conditions, the paired watershed approach is expected to remain the preferred method for determining the effects of forest management on the water resource.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

PREDICTION OF PEAK FLOWS ON SMALL WATERSHEDS IN OREGON FOR USE IN CULVERT DESIGN1

ABSTRACT: Using data from 80 Oregon watersheds that ranged in size from 0.54 km² to 27.45 km², equations were developed to predict peak flows for use in culvert design on forest roads. Oregon was divided into six physiographic regions based on previous studies of flood frequency. In each region, data on annual peak flow from gaging stations with more than 20 years of record were analyzed using four flood frequency distributions: type 1 extremal, two parameter-log normal, three parameter-log normal, and log-Pearson type III. The log-Pearson type III distribution was found to be suitable for use in all regions of the State, based on the chi-square goodness-of-fit-test. Flood magnitudes having recurrence intervals of 10, 25, 50, and 100 years were related to physical and climatic characteristics of drainage basins by multiple regression. Drainage basin size was the most important variable in explaining the variation of flood peaks in all regions. Mean basin elevation and mean annual precipitation were also significantly related to flood peaks in two regions of western Oregon. The standard error of the estimate for the regression relationships ranged from 26 to 84 percent.     

PRECIPITATION MEASUREMENT BIASES IN THE UNITED STATES1

ABSTRACT: Gage-induced biases in monthly precipitation are estimated and removed at 1818 stations across the continental United States from 1950 through 1987. Deleterious effects of the wind and wetting losses on the interior walls of the gage were considered. These “corrected” estimates were obtained using site-specific information including wind speed, shelter-height air temperature, gage height, and sheltering. Wind speed and air temperature were interpolated at stations for which these data were not available using a spherically-based, nearest neighbor interpolation procedure. Results indicate that, as expected, biases are greater in the winter than the summer owing to the increased problems (particularly wind-induced) of measuring snowfall. In summer, percent errors range between 4 and 6 percent over nearly three-quarters of the United States with slightly larger errors over the Rocky Mountains. By contrast, winter biases are highly correlated with snowfall totals and percentage errors increase poleward, mimicking patterns of snowfall frequency. Since these biases are not trivial, they must be accounted for in order to obtain accurate and reliable time-series. If these biases are not properly addressed, serious errors can be introduced into climate change, hydrologic modeling, and environmental impact research.     

黄土高原植被类型变化和空间分布对气象因子变化的响应

利用基于GIS的黄土高原植被类型分布图,结合黄土高原地区标准气象站的气象因子资料,对黄土高原植被类型变化和空间分布对气象因子变化的响应关系进行了分析。结果显示:从东南到西北,年降水量、月平均最高气温、月平均最低气温逐渐减少,年平均气温、全年日照时数、全年最大蒸散量、平均风速逐渐增加,植被类型由东南湿润半湿润森林、半干旱森林草原往西北转变成轻干旱、重半干旱的温性草原、干旱的荒漠半荒漠植被。     

Climatic and agricultural contributions to changing loads in two watersheds in Ohio

Trends in climatic variables, streamflow, agricultural practices, and loads of nutrients and suspended solids were estimated for 1976-1995 in the Maumee and Sandusky watersheds, two large agricultural basins draining to Lake Erie. To understand the contributions that various factors may have made to the trends in loads, earlier results of models linking loads to explanatory variables were combined with estimated trends in those variables. The study period was characterized by increases in temperature, wintertime precipitation and streamflow, conservation farming, and loads of nitrate and total suspended solids; decreases in snowfall and snow cover, fertilizer, manure from livestock, and loads of soluble reactive phosphorus; and relatively steady exports of total phosphorus. After removing the effects of trends in streamflow, nitrate loads increased much less while total suspended solids and total phosphorus loads declined. The analysis suggests that the nitrate increases were due largely to climatic factors, particularly increases in winter streamflow, decreases in snowfall and snow cover, and declining annual precipitation. Decreases in soluble reactive phosphorus were associated with changes in agricultural practices, particularly declines in fertilizer deliveries and head of livestock.     

SWMHMS - SMALL WATERSHED MONTHLY HYDROLOGIC MODELING SYSTEM1

ABSTRACT: SWMHMS is a conceptual computer modeling program developed to simulate monthly runoff from a small nonurban watershed. The input needed to run model simulations include daily precipitation, monthly data for evapotranspiration determination (average temperature, crop consumptive coefficients, and percent daylight hours), and six watershed parameter values. Evapotranspiration was calculated with the Blaney-Criddle equation while surface runoff was determined using the Soil Conservation Service curve number procedure. For watershed parameter evaluation, SWMHMS provides options for both optimization and sensitivity analysis. Observed runoff data are required along with the model input previously mentioned in order to conduct parameter optimization. SWMEIMS was tested with data from six watersheds located in different regions of the United States. Model accuracy was generally found to be very good except on watersheds having substantial snowfall accumulation. In having only six watershed parameters, SWMHMS is less complex to use than many other computer programs that calculate monthly runoff. Consequently, SWMHMS may find its greatest application as an educational tool for students learning principles of hydrologic modeling, such as parameter evaluation procedures and the impacts of input data uncertainty on model results.     

THE POTENTIAL EFFECTS OF GLOBAL WARMING ON THE PRIMARY PRODUCTIVITY OF A SUBALPINE LAKE1

ABSTRACT Atmospheric scientists have predicted that large-scale climatic changes will result from increasing levels of tropospheric CO₂ We have investigated the potential effects of climate change on the primary productivity of Castle Lake, a mountain lake in Northern California. Annual algal productivity was modeled empirically using 25 years of limnological data in order to establish predictive relationships between productivity and the climatic variables of accumulated snow depth and precipitation. The outputs of monthly temperature and precipitation from three general circulation models (GCMs) of doubled atmospheric CO₂ were then used in the regression model to predict annual algal productivity. In all cases, the GCM scenarios predicted increased algal productivity for Castle Lake under cenditions of doubled atmospheric CO₂The primary cause of enhanced productivity was the increased length of the growing season resulting from earlier spring ice-out.     

CLIMATE,SNOW COVER,GLACIERS, AND RUNOFF IN THE TIEN SHAN,CENTRAL ASIA1

ABSTRACT: The Pica Shan, a mountainous region located on the northern periphery of central Asia, has a wide range of climatic and hydrological conditions. On the basis of long term data from 348 meteorological and glaciological stations, the annual distribution of precipitation in different regions and elevational zones of the Tien Shan was calculated. Major climatic features are the entrance of moisture during spring-summer, small winter precipitation, decrease of precipitation towards the east and the center of the mountains or with distance up valleys, and increase of precipitation with altitude up to crest-lines of ranges. Annual total evaporation from snow can be 50–60 mm per year, reaching 30 percent of snow accumulation. Four main groups of rivers were identified: rivers with mainly snow nourishment, rivers with mainly glacial nourishment, rivers with mainly rain nourishment, and rivers with mainly ground water nourishment. Coefficient of runoff variation in Tien Shan's rivers is about 0.20, and coefficient of glacial runoff variation is about 0.15. Glacial runoff is 15–20 percent of the total volume of river runoff.     

DISTRIBUTION AND STOCHASTIC GENERATION OF ANNUAL AND MONTHLY PRECIPITATION ON A MOUNTAINOUS WATERSHED IN SOUTHWEST IDAHO1

ABSTRACT: The 18-year precipitation record from the dense gage network on the Reynolds Creek Experimental Watershed located in southwest Idaho was used to determine the spatial distribution of annual and monthly precipitation on a mountainous watershed. Analyses of these data showed a linear relationship between annual amounts and elevation. This relationship was best when the gages were grouped into downwind and upwind sites. This grouping was appropriate because most of the winter storms moved over the watershed from the west and southwest, and the heaviest precipitation was on the west (downwind) side of the watershed. Gage sites along the western and southern watershed borders were most representative of the upwind gages on the east side, because they measured the precipitation from the air moving upwind onto the watershed. The maximum annual precipitation on the watershed was just leeward of the western watershed boundary. The monthly precipitation and elevation relationship was also best represented by grouping the gage sites into upwind and downwind sites. However, during the summer when there are only small amounts of pre cipitation and thunderstorms are the source of most precipitation, one equation can be used to represent the elevation relationship. This study also showed that the log-normal distribution could be used to generate the annual synthetic series, and the cube-root-normal distribution could be used to generate monthly synthetic series for all locations on the watershed.     

GENERATION OF SYNTHETIC AND MISSING CLIMATIC DATA FOR PUERTO RICO1

ABSTRACT: Climatic data such as temperature, solar radiation, relative humidity, and wind speed have been widely used to estimate evapotranspiration. Moat of the solar radiation data and portions of the relative humidity data are either not available or missing from the records in Puerto Rico. Depending upon the availability and data characteristics of records, three methods (including a regression technique, an averaging of historical data, and a regional average) were used to generate missing data, and a time series analysis was used to synthesize a series of climatic data. The limitations and applicability of each method are discussed. The results showed that the time series analysis method can be successfully used to synthesize a series of monthly solar radiations for several stations. The regression technique and the regional average can be successfully applied to generate missing monthly solar radiation data. The regression technique and the averaging of historical data have been satisfactorily used to interpolate missing monthly relative humidity. The explained variance (R²) varied from 0.68 to 0.88, which are both significant at the 0.05 level of significance.     

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.     

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.     

PREDICTING WILDERNESS SNOW WATER EQUIVALENT WITH NONWILDERNESS SNOW SENSORS1

ABSTRACT: Ten pairs of snow sensors were analyzed to investigate the feasibility of predicting snow water equivalent at high-elevation, telemetered snow sensor sites from lower-elevation sensors. The need for this analysis stems from an agreement between the California Department of Water Resources and the USDA Forest Service to temporarily allow snow sensors in California's wilderness areas so that a predictive relationship can be developed. After 10 or 15 years, the agreement calls for the sensors to be removed. Initial efforts to a priori select sensor pairs were based on proximity, colocation within a basin, and annual precipitation amount, but regression yielded poor fits (R² < 0.65) and high standard errors in eight of the ten cases. Analysis of the results suggested that eleva-tional similarity was the most important selection criteria, and that all available sensors near the target site should be analyzed via a regression screening. Using elevation for selection and the regression screening, five sensors that initially had poor fits were reanalyzed. Each of the five sensors was paired with between two and five new sensors, and R² values improved between 27 and 46 percent. Various data smoothing and editing algorithms were evaluated, but they rarely resulted in improved fits.     

1961—2008年新疆阿克苏地区降水、温度变化特征

利用阿克苏地区5个气象站1961—2008年的降水和温度资料,对近50 a来该地区气候变化及其趋势进行了分析。各气象站年降水量变化趋势基本一致,总体上都呈增加趋势。除库车县气象站年平均温度呈降低趋势外,其余呈上升趋势。总体上,阿克苏地区年降水量和年平均温度均呈上升趋势。     

Precipitation Amount and Intensity Trends Across Southwest Saudi Arabia

This study examines precipitation accumulation and intensity trends across a region in southwest Saudi Arabia characterized by distinct seasonal weather patterns and mountainous terrain. The region is an example of an arid/semiarid area faced with maintaining sustainable water resources with a growing population. Annual and seasonal trends in precipitation amount were examined from 29 rain gages divided among four geographically unique regions from 1945/1946 to 2009. Two of the regions displayed significantly declining annual trends over the time series using a Mann‐Kendall test modified for autocorrelation (α < 0.05). Seasonal analysis revealed insignificant declining trends in at least two of the regions during each season. The largest and most consistent declining trends occurred during wintertime where all regions experienced negative trends. Several intensity metrics were examined in the study area from four additional stations containing daily data from 1985 to 2011. Intensity metrics included total precipitation, wet day count, simple intensity index, maximum daily annual rainfall, and upper/lower precipitation distribution changes. In general, no coherent trends were found among the daily stations suggesting precipitation is intensifying across the study area. The work represents the first of its size in the study area, and one of few in the region due to the lack of available long‐term data needed to properly examine precipitation changes.     

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.     

A Fully Distributed Implementation of Mean Annual StreamFlow Regional Regression Equations1

Abstract: Estimates of mean annual streamflow are needed for a variety of hydrologic assessments. Away from gage locations, regional regression equations that are a function of upstream area, precipitation, and temperature are commonly used. Geographic information systems technology has facilitated their use for projects, but traditional approaches using the polygon overlay operator have been too inefficient for national scale applications. As an alternative, the Elevation Derivatives for National Applications (EDNA) database was used as a framework for a fully distributed implementation of mean annual streamflow regional regression equations. The raster “flow accumulation” operator was used to efficiently achieve spatially continuous parameterization of the equations for every 30 m grid cell of the conterminous United States (U.S.). Results were confirmed by comparing with measured flows at stations of the Hydro‐Climatic Data Network, and their applications value demonstrated in the development of a national geospatial hydropower assessment. Interactive tools at the EDNA website make possible the fast and efficient query of mean annual streamflow for any location in the conterminous U.S., providing a valuable complement to other national initiatives (StreamStats and the National Hydrography Dataset Plus).     

SENSITWITY OF IRRIGATION DEMAND IN A HUMID-TEMPERATE REGION TO HYPOTHETICAL CLIMATIC CHANGE1

ABSTRACT: An irrigation model based on a modified Thornthwaite water balance was used to simulate the effects of various hypothetical climatic changes on annual irrigation demand in a humidtemperate climate. The climatic-change scenarios consisted of combinations of changes in temperature, precipitation, and stomatal resistance of plants to transpiration. The objectives were to (1) examine the effects of long-term changes in these components of climatic change on annual irrigation demand, and (2) identify which of these factors would cause the largest changes in annual irrigation demand. Hypothetical climatic changes that only included increases in temperature and changes in precipitation resulted in increased annual irrigation demand, even with a 20 percent increase in precipitation. The model results showed that, for the ranges of changes in temperature and precipitation used in this study, changes in irrigation demand were more sensitive to changes in temperature than to changes in precipitation. Model results also indicated that increased stomatal resistance to transpiration counteracted the effects of increases in temperature and decreases in precipitation on irrigation demand. Changes in irrigation demand were even more sensitive to changes in stomatal resistance than to changes in temperature. A large amount of uncertainty is associated with predictions of future climatic conditions; however, uncertainty associated with natural climatic variability may be larger and may mask the effects of climatic change on irrigation demand.     

Streamflow Changes in the South Atlantic,United States During the Mid‐ and Late 20th Century1

Abstract: Repeated severe droughts over the last decade in the South Atlantic have raised concern that streamflow may be systematically decreasing, possibly due to climate variability. We examined the monthly and annual trends of streamflow, precipitation, and temperature in the South Atlantic for the time periods: 1934‐2005, 1934‐1969, and 1970‐2005. Streamflow and climate (temperature and precipitation) trends transitioned ca. 1970. From 1934 to 1969, streamflow and precipitation increased in southern regions and decreased in northern regions; temperature decreased throughout the South Atlantic. From 1970 to 2005, streamflow decreased, precipitation decreased, and temperature increased throughout the South Atlantic. It is unclear whether these will be continuing trends or simply part of a long‐term climatic oscillation. Whether these streamflow trends have been driven by climatic or anthropogenic changes, water resources management faces challenging prospects to adapt to decadal‐scale persistently wet and dry hydrologic conditions.