EFFECTS OF INTERANNUAL VARIATION OF PRECIPITATION ON STREAM DISCHARGE FROM RHODE RIVER SUBWATERSHEDS1

ABSTRACT: The purpose of this study was to determine the relationships between precipitation at the seasonal and annual scale and water discharge per surface area for seven contiguous first - and second-order tributaries of the Rhode River, a small tidal tributary to Chesapeake Bay, Maryland, USA. The goal was to quantify the effects of a wide range of precipitation, representative of inter-annual variations in weather in this region. The discharges measured included both overland storm flows and groundwater, since the aquifers were perched on a clay aquiclude. Precipitation varied from 824 to 1684 mm/yr and area-weighted Rhode River watershed discharge varied from 130 to 669 mm/yr with an average of 332 mm/yr or 29.1 percent of average precipitation. Average annual dis. charges from three first-order watersheds were significantly lower per surface area and varied from 16.0 to 21.9 percent of precipitation. Winter season precipitation varied from 125 to 541 mm. Area-weighted Rhode River winter discharge varied from 26.3 to 230 mm with an average of 115 mm or 43.9 percent of average precipitation. Spring season precipitation varied from 124 to 510 mm and watershed discharge varied from 40.0 to 321 mm with an average of 138 mm or 46.9 percent of average precipitation. In the summer and fall seasons, watershed discharge averaged 40.6 and 40.9 mm or 13.5 and 14.3 percent of average precipitation, respectively. Except in winter, the proportion of precipitation discharged in the streams increased rapidly with increasing volume of precipitation. Stream order showed a higher correlation with volume of discharge than vegetative cover on the watershed.     

UNCERTAINTIES IN ESTIMATING THE WATER BALANCE OF LAKES1

ABSTRACT: Evaluation of hydrologic methodology used in a number of water balance studies of lakes in the United States shows that most of these studies calculate one or more terms of the budget as the residual. A literature review was made of studies in which the primary purpose was error analysis of hydrologic measurement and interpretation. Estimates of precipitation can have a wide range of error, depending on the gage placement, gage spacing, and areal averaging technique. Errors in measurement of individual storms can be as high as 75 percent. Errors in short term averages are commonly in the 15-30 percent range, but decrease to about 5 percent or less for annual estimates. Errors in estimates of evaporation can also vary widely depending on instrumentation and methodology. The energy budget is the most accurate method of calculating evaporation; errors are in the 10–15 percent range. If pans are used that are located a distance from the lake of interest, errors can be considerable. Annual pan-to-lake coefficients should not be used for monthly estimates of evaporation because they differ from the commonly used coefficient of 0.7 by more than 100 percent. Errors in estimates of stream discharge are often considered to be within 5 percent. If the measuring section, type of flow profile, and other considerations, such as stage discharge relationship, are less than ideal errors in estimates of stream discharge can be considerably greater than 5 percent. Errors in estimating overland (nonchannelized) flow have not been evaluated, and in most lake studies this component is not mentioned. Comparison of several lake water balances in which the risdual consists solely of errors in measurement, shows that such a residual, if interpreted as ground water, can differ from an independent estimate of ground water by more than 100 percent.     

MAPPING REGIONAL PRECIPITATION INTENSITY DURATION FREQUENCY ESTIMATES1

ABSTRACT: For regional precipitation frequency analyses, methods are needed to spatially interpolate or smooth point intensity duration frequency (IDF) estimates at gage sites for the purposes of visualization and estimation at ungaged sites. In this study to update IDF estimates for Michigan, the assumption is made that for practical purposes, the entire state may be treated as a homogeneous region in which annual maximum precipitation is identically distributed at each site apart from a site‐specific scaling factor, commonly known as the index flood. Several interpolation and smoothing techniques are evaluated for IDF estimation at ungaged sites, including trend surface analysis, thin plate splines, inverse distance weighting, and several kriging algorithms. Ordinary block kriging is recommended as a practical and objective method for smoothing the variability in the index flood values and developing isopluvial maps.     

USE OF SOIL MOISTURE PROBES TO ESTIMATE GROUND WATER RECHARGE AT AN OIL SPILL SITE1

Soil moisture data collected using an automated data logging system were used to estimate ground water recharge at a crude oil spill research site near Bemidji, Minnesota. Three different soil moisture probes were tested in the laboratory as well as the field conditions of limited power supply and extreme weather typical of northern Minnesota: a self‐contained reflectometer probe, and two time domain reflectometry (TDR) probes, 30 and 50 cm long. Recharge was estimated using an unsaturated zone water balance method. Recharge estimates for 1999 using the laboratory calibrations were 13 to 30 percent greater than estimates based on the factory calibrations. Recharge indicated by the self‐contained probes was 170 percent to 210 percent greater than the estimates for the TDR probes regardless of calibration method. Results indicate that the anomalously large recharge estimates for the self‐contained probes are not the result of inaccurate measurements of volumetric moisture content, but result from the presence of crude oil, or borehole leakage. Of the probes tested, the 50 cm long TDR probe yielded recharge estimates that compared most favorably to estimates based on a method utilizing water table fluctuations. Recharge rates for this probe represented 24 to 27 percent of 1999 precipitation. Recharge based on the 30 cm long horizontal TDR probes was 29 to 37 percent of 1999 precipitation. By comparison, recharge based on the water table fluctuation method represented about 29 percent of precipitation.     

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.     

RAINGAGE NETWORK DESIGN USING NEXRAD PRECIPITATION ESTIMATES1

ABSTRACT: A general framework is proposed for using precipitation estimates from NEXRAD weather radars in raingage network design. NEXRAD precipitation products are used to represent space time rainfall fields, which can be sampled by hypothetical raingage networks. A stochastic model is used to simulate gage observations based on the areal average precipitation for radar grid cells. The stochastic model accounts for subgrid variability of precipitation within the cell and gage measurement errors. The approach is ideally suited to raingage network design in regions with strong climatic variations in rainfall where conventional methods are sometimes lacking. A case study example involving the estimation of areal average precipitation for catchments in the Catskill Mountains illustrates the approach. The case study shows how the simulation approach can be used to quantify the effects of gage density, basin size, spatial variation of precipitation, and gage measurement error, on network estimates of areal average precipitation. Although the quality of NEXRAD precipitation products imposes limitations on their use in network design, weather radars can provide valuable information for empirical assessment of rain‐gage network estimation errors. Still, the biggest challenge in quantifying estimation errors is understanding subgrid spatial variability. The results from the case study show that the spatial correlation of precipitation at subgrid scales (4 km and less) is difficult to quantify, especially for short sampling durations. Network estimation errors for hourly precipitation are extremely sensitive to the uncertainty in subgrid spatial variability, although for storm total accumulation, they are much less sensitive.     

EVALUATION OF NEXRAD STAGE III PRECIPITATION DATA OVER A SEMIARID REGION1

This study examines NEXRAD Stage III product (hourly, cell size 4 km by 4 km) for its ability in estimating precipitation in central New Mexico, a semiarid area. A comparison between Stage III and a network of gauge precipitation estimates during 1995 to 2001 indicates that Stage III (1) overestimates the hourly conditional mean (CM) precipitation by 33 percent in the monsoon season and 55 percent in the nonmonsoon season; (2) overestimates the hourly CM precipitation for concurrent radar‐gauge pairs (nonzero value) by 13 percent in the monsoon season and 6 percent in the nonmonsoon season; (3) overestimates the seasonal precipitation accumulation by 11 to 88 percent in monsoon season and underestimates by 18 to 89 percent in the nonmonsoon season; and (4) either overestimates annual precipitation accumulation up to 28.2 percent or underestimates it up to 11.9 percent. A truncation of 57 to 72 percent of the total rainfall hours is observed in the Stage III data in the nonmonsoon season, which may be the main cause for both the underestimation of the radar rainfall accumulation and the lower conditional probability of radar rainfall detection in the nonmonsoon season. The study results indicate that the truncation caused loss of small rainfall amounts (events) is not effectively corrected by the real‐time rain gauge calibration that can adjust the rainfall rates but cannot recover the truncated small rainfall events. However, the truncation error in the monsoon season may be suppressed due to the larger rainfall rate and/or combined effect of overestimates by bright band and hail contaminations, virga, advection, etc. In general, improvement in NEXRAD performance since the monsoon season in 1998 is observed, which is consistent with the systematic improvement in the NEXRAD network.     

ESTIMATION OF SOIL MOISTURE WITH API ALGORITHMS AND MICROWAVE EMISSION1

Large area soil moisture estimations are required to describe input to cloud prediction models, rainfall distribution models, and global crop yield models. Satellite mounted microwave sensor systems that as yet can only detect moisture at the surface have been suggested as a means of acquiring large area estimates. Relations previously discovered between microwave emission at the 1.55 cm wavelength and surface moisture as represented by an antecedent precipitation index were used to provide a pseudo infiltration estimation. Infiltration estimates based on surface wetness on a daily basis were then used to calculate the soil moisture in the surface 0–23 cm of the soil by use of a modified antecedent precipitation index. Reasonably good results were obtained (R²= 0.7162) when predicted soil moisture for the surface 23 cm was compared to measured moisture. Where the technique was modified to use only an estimate of surface moisture each three days an R² value of 0.7116 resulted for the same data set. Correlations between predicted and actual soil moisture fall off rapidly for repeat observations more than three days apart. The algorithms developed in this study may be used over relatively flat agricultural lands to provide improved estimates of soil moisture to a depth greater than the depth of penetration for the sensor.     

AN EVALUATION OF PRECIPITATION GAGE DENSITY IN A MOUNTAINOUS TERRAIN1

ABSTRACT: Inter-station analysis was employed to evaluate the adequacy of the precipitation network in topographically complex West Virginia. A 25-year period was determined as the minimum lingth of record needed for relatively stable and fairly accurate estimates of long-term (50-year) precipitation and in frequency analysis. Data from the 83 National Weather Service stations with 25-year records were adjusted for consistency and evaluated separately by zones east (31 stations) and west (52 stations) of the Appalachian divide. Correlation coefficients (r) and average standard errors of estimate were computed for all station pairs within 50 miles distance and 1000 feet elevation difference of each other. The third polynomial equation of inter-station distance eliminated using elevation and land slope as the criteria in network design in this mountainous terrain. A network with (r) = 0.9 estimates annual precipitation with accuracy as great as 5 percent, but requires about 250 additional gages (i.e., about 200 percent of the present density).     

EFFECTS OF TOPOGRAPHY AND SOIL PROPERTIES ON RECHARGE AT TWO SITES IN AN AGRICULTURAL FIELD1

ABSTRACT: Field experiments were conducted from 1992 to 1995 to estimate ground water recharge rates at two sites located within a 2.7‐hectare agricultural field. The field lies in a sand plain setting in central Minnesota and is cropped continuously in field corn. The sites are located at a topographically high (upland) site and a topographically low (lowland) site in an effort to quantify the effects of depression focusing of recharge. Three site‐specific methods were used to estimate recharge rates: well hydrograph analysis, chlorofluorocarbon age dating, and an unsaturated zone water balance. All three recharge methods indicated that recharge rates at the lowland site (annual average of all methods of 29 cm) exceeded those at the upland site (annual average of 18 cm). On an annual basis, estimates by the individual methods ranged from 12 to 44 percent of precipitation at the upland site and from 21 to 83 percent at the lowland site. The difference in recharge rates between the sites is primarily attributed to depression focusing of surface water runon at the lowland site. However, two other factors were also important: the presence of thin lamellae at the upland site, and coarser textured soils below a depth of 1.5 m at the lowland site.     

Water movement within the unsaturated zone in four agricultural areas of the United States

Millions of tons of agricultural fertilizer and pesticides are applied annually in the USA. Due to the potential for these chemicals to migrate to groundwater, a study was conducted in 2004 using field data to calculate water budgets, rates of groundwater recharge and times of water travel through the unsaturated zone and to identify factors that influence these phenomena. Precipitation was the only water input at sites in Indiana and Maryland; irrigation accounted for about 80% of total water input at sites in California and Washington. Recharge at the Indiana site (47.5 cm) and at the Maryland site (31.5 cm) were equivalent to 51 and 32%, respectively, of annual precipitation and occurred between growing seasons. Recharge at the California site (42.3 cm) and Washington site (11.9 cm) occurred in response to irrigation events and was about 29 and 13% of total water input, respectively. Average residence time of water in the unsaturated zone, calculated using a piston-flow approach, ranged from less than 1 yr at the Indiana site to more than 8 yr at the Washington site. Results of bromide tracer tests indicate that at three of the four sites, a fraction of the water applied at land surface may have traveled to the water table in less than 1 yr. The timing and intensity of precipitation and irrigation were the dominant factors controlling recharge, suggesting that the time of the year at which chemicals are applied may be important for chemical transport through the unsaturated zone.     

ROLE OF BASEFLOW IN RAINFALL-RUNOFF RELATIONS1

ABSTRACT. The role of initial baseflow, or the baseflow at the beginning of storm precipitation, in modifying mathematical rainfall-runoff relations is analyzed by using data from 95 storms over a drainage basin in Illinois. A regression model is set up with total runoff, surface runoff, baseflow runoff, and peak flow as dependent variables, and storm precipitation, initial baseflow, effective and total storm durations, and highest and lowest temperatures during the storm as independent variables. Stepwise regression analyses show that storm precipitation and initial baseflow are the most important variables for making dependent variable estimates. The standard error estimates using only storm precipitation and initial baseflow as predictors show a seasonal trend with a peak in July, August, or September. An understanding of the role of baseflow as an indicator of average soil moisture condition over the basin can be of great help in short-term reservoir regulation and flood warning.     

VERIFICATION OF THE RHEA-OROGRAPHIC-PRECIPITATION MODEL1

ABSTRACT: Observed April 1 snowpack accumulations within and near the Gunnison River basin in southwestern Colorado are compared with simulations from the Rhea-orographic-precipitation model to determine if the model simulates reliable magnitudes and temporal and spatial variability in winter precipitation for the basin. Twenty simulations of the Rhea model were performed using‘optimal’parameter sets determined for 10-kilometer (km) grids (10-km by 10-km grid cells) through stochastic calibration. Comparisons of Rhea-model simulations of winter precipitation with April 1 snowpack accumulations at 32 snowcourse stations were performed for the years 1972–1990. For most stations and most years the Rhea model reliably simulates the temporal and spatial variability in April 1 snowpack accumulations. However, in general, the Rhea-model underestimates April 1 snowpack accumulations in the Gunnison River basin area, and the underestimation is greatest for locations that receive the largest amount of snow. A significant portion of the error in Rhea-model simulations is due to the calibration of the Rhea model using gauge-catch precipitation measurements which can be as much as 50 percent below actual snowfall accumulations. Additional error in the Rhea-model simulations is a result of the comparison of gridded precipitation values to observed values measured at points.     

KALMAN FILTER CALCULATION OF SAMPLING FREQUENCY WHEN DETERMINING ANNUAL MEAN SOLUTE CONCENTRATIONS

ABSTRACT: A linear filter (Kalman filter) technique was used with a Streamflow-concentration model the minimize surface water quality sampling frequencies when determining annual mean solute concentrations with a predetermined allowable error. The Kalman filter technique used the stream discharge interval as a replacement for the more commonly used time interval. Using filter computations, the measurement error variance was minimized within the sample size constraints. The Kalman filter application proposed here is applicable only under several conditions including: monitoring is solely to estimate annual mean concentration; discharge measurement errors are negligible; the Streamflow-concentration model is valid; and monthly samples reflect the total variance of the solute in question.     

A COMPARATIVE ANALYSIS OF TECHNIQUES FOR SPATIAL INTERPOLATION OF PRECIPITATION1

One of the problems which often arises in engineering hydrology is to estimate data at a given site because either the data are missing or the site is ungaged. Such estimates can be made by spatial interpolation of data available at other sites. A number of spatial interpolation techniques are available today with varying degrees of complexity. It is the intent of this paper to compare the applicability of various proposed interpolation techniques for estimating annual precipitation at selected sites. The interpolation techniques analyzed include the commonly used Thiessen polygon, the classical polynomial interpolation by least-squares or Lagrange approach, the inverse distance technique, the multiquadric interpolation, the optimal interpolation and the Kriging technique. Thirty years of annual precipitation data at 29 stations located in the Region II of the North Central continental United States have been used for this study. The comparison is based on the error of estimates obtained at five selected sites. Results indicate that the Kriging and optimal interpolation techniques are superior to the other techniques. However, the multiquadric technique is almost as good as those two. The inverse distance interpolation and the Thiessen polygon gave fairly satisfactory results while the polynomial interpolation did not produce good results.     

“R1-R4” AND “BOISED” SEDIMENT PREDICTION MODEL TESTS USING FOREST ROADS IN GRANITICS1

ABSTRACT: Erosion and sedimentation data from research watersheds in the Silver Creek Study Area in central Idaho were used to test the prediction of logging road erosion using the R1-R4 sediment yield model, and sediment delivery using the “BOISED” sediment yield prediction model. Three small watersheds were instrumented and monitored such that erosion from newly constructed roads and sediment delivery to the mouths of the watersheds could be measured for four years following road construction. The errors for annual surface erosion predictions for the two standard road tests ranged from +31.2 t/ha/yr (+15 percent) to -30.3 t/ha/yr (-63 percent) with an average of zero t/ha/yr and a standard deviation of the differences of 18.7 t/ha/yr. The annual prediction errors for the three watershed scale tests had a greater range from -40.8 t/ha/yr (-70 percent) to +65.3 t/ha/yr (+38 percent) with a mean of -1.9 t/ha/yr and a standard deviation of the differences of 25.2 t/ha/yr. Sediment yields predicted by BOISED (watershed scale tests) were consistently greater (average of 2.5 times) than measured sediment yields. Hillslope sediment delivery coefficients in BOISED appear to be overly conservative to account for average site conditions and road locations, and thus over-predict sediment delivery. Mass erosion predictions from BOISED appear to predict volume well (465 tonnes actual versus 710 tonnes predicted, or a 35 percent difference) over 15 to 20 years, however mass wasting is more episodic than the model predicts.     

PREDICTING MEASUREMENT ERROR OF AREAL MEAN PRECIPITATION DURING EXTREME EVENTS1

ABSTRACT: The areal mean precipitation (AMP) over a catchment is normally calculated using point measurements at rainfall gages. Error in AMP estimates occurs when an insufficient number of gages are used to sample precipitation which is highly variable in space. AMP error is investigated using historic, severe rainfalls with a set of hypothetical catchments and raingage networks. The potential magnitude of error is estimated for typical gage network densities and arrangements. Possible sources of error are evaluated, and a method is proposed for predicting the magnitude of error using data that are commonly available for severe, historic rainfall.     

EVALUATION OF THE MAXEY-EAKIN METHOD FOR ESTIMATING RECHARGE TO GROUND-WATER BASINS IN NEVADA1

AESTRACT An evaluation of the Maxey-Eakin method for calculating recharge to ground-water basins in Nevada was performed. The evaluation consisted of comparing Maxey-Eakin estimates with independent estimates of recharge, and analyzing the nature of the differences between the groups of estimates. In the comparison with the Maxey-Eakin estimates, two different groups of independent estimates were used: (1) 40 recharge estimates that were identified from water budgets contained in reports by the Nevada Department of Conservation and Natural Resources and (2) 27 recharge estimates that were identified from previous studies that used models. The results of the comparisons indicate generally good agreement between the Maxey-Eakin estimates and both groups of independent estimates. To quantify this agreement, an analysis was conducted to estimate the uncertainty in the Maxey-Eakin method. The analysis produced an upper bound on the standard deviation of the Maxey-Eakin estimate for a given basin. For the group of 40 water-budget estimates, the upper bound on the standard deviation for an individual basin is 4,800 acre-ft/yr, and the corresponding coefficient of variation of the Maxey-Eakin estimate is no greater than 44 percent. For the group of 27 model estimates, the upper bound on the standard deviation is 4,100 acre-ft/yr, and the corresponding coefficient of variation is no greater than 24 percent.     

QUANTIFICATION OF THE WATER BUDGET AND NUTRIENT LOADING IN A SMALL PEATLAND1

ABSTRACT: Few water budgets exist for specific types of wetlands such as peatlands, even though such information provides the basis from which to investigate linkages between wetlands and upland ecosystems. In this study, we first determined the water budget and then estimated nutrient loading from an upland farm field into a 1.5 ha, kettle-block peatland. The wetland contains highly anisotropic peat and has no distinct, active layer of groundwater flow. We estimated the depth of the active layer using Fick's law of diffusion and quantified groundwater flow using a chemical mass balance model. Evapotranspiration was determined using MORECS, a semi-physical model based on the Penman-Monteith approach. Precipitation and surface outflow were measured using physical means. Groundwater provided the major inflow, 84 percent (44,418 m³) in 1993 and 88 percent (68,311 m³) in 1994. Surface outflow represented 54 percent (28,763 m³) of total outflows in 1993 and 48 percent (37,078 m³) in 1994. A comparison of several published water budgets for wetlands and lakes showed that error estimates for hydrologic components in this study are well within the range of error estimates calculated in other studies. Groundwater inflow estimates and nutrient concentrations of three springs were used to estimate agricultural nutrient loading to the site. During the study period, nutrient loading into the peatland via groundwater discharge averaged 24.74 kg K ha^-1, 1.83 kg total inorganic P ha^d, and 21.81 kg NO₃-N ha^-1.