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.     

HYDROLOGIC UNCERTAINTY MEASURE AND NETWORK DESIGN1

ABSTRACT: This paper presents a simple methodology, using the entropy concept, to estimate regional hydro logic uncertainty and information at both gaged and ungaged grids in a basin. The methodology described in this paper is applicable for (a) the selection of the optimum station from a dense network, using maximization of information transmission criteria, and (b) expansion of a network using data from an existing sparse network by means of the information interpolation concept and identification of the zones from minimum hydrologic information. The computation of single and joint entropy terms used in the above two cases depends upon single and multivariable probability density functions. In this paper, these terms are derived for the gamma distribution. The derived formulation for optimum hydrologic network design was tested using the data from a network of 29 rain gages on Sleeper River Experimental Watershed. For the purpose of network reduction, the watershed was divided into three subregions, and the optimum stations and their locations in each subregion were identified. To apply the network expansion methodology, only the network consisting of 13 stations was used, and feasible triangular elements were formed by joining the stations. Hydrologic information was calculated at various points on the line segments, and critical information zones were identified by plotting information contours. The entropy concept used in this paper, although derived for single and bivaviate gamma distribution, is general in type and can easily be modified for other distributions by a simple variable transformation criterion.     

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.     

A SURVEY OF THE U.S. NATIONAL PRECIPITATION NETWORK1

ABSTRACT: Numbers and record lengths of precipitation stations were surveyed in the conterminous United States using climatological data published in 1975 by the National Weather Service (NWS). The total numbers of nonrecording (8247) and recording (3036) gages were about the same as in the 1940s and less than in the late 1950s; about 70 percent of the nonrecording gages have record lengths of 25 years or more. State network densities were increased exponentially with population density and long term precipitation average. Except for a few states, precipitation stations maintained by the NWS are adequate in numbers to ensure a 95 percent statistical probability that state sample means will estimate true means within ± 5 percent.     

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.     

AN EMPIRICALLY‐BASED SEQUENTIAL GROUND WATER MONITORING NETWORK DESIGN PROCEDURE1

ABSTRACT: A procedure using a simple, empirically‐based model that makes efficient use of available information has been developed for designing a ground water monitoring well network. A moving plume is described by siting wells in a sequential manner, relying upon two‐dimensional concentration data obtained from previously installed wells to determine the locations of future wells. Data sets from two well known, densely monitored natural gradient tracer studies were used to test the procedure. Plumes defined by all information in the original networks were compared to those defined by reduced networks designed by the new procedure. The new procedure tracked the plumes using only a portion of that information. The new procedure could have reduced the number of wells in the original tests by about 50 percent without appreciable loss of plume information as measured by plume location and extent and by tracer mass.     

ESTIMATES OF MEAN CHLOROPHYLL-a CONCENTRATION: PRECISION,ACCURACY, AND SAMPLING DESIGN1

ABSTRACT: Data from 56 north-temperate lakes and reservoirs are used to develop models predicting temporal variance as a function of the mean chlorophyll-a concentration. Trophy, as estimated by mean chlorophyll-a concentration, is shown to have little effect on the sampling effort required to achieve a pre-determined level of precision for lakes sampled year-round. Collecting ten observations results in a coefficient of variation that averaged 20 percent; collecting more than ten observations yields increasingly marginal improvements in precision. The same guidelines apply to mesotrophic or eutrophic lakes sampled in the summer, whereas oligotrophic lakes sampled in the summer require fewer observations to achieve the same level of precision. The bias resulting from collecting too few observations is minimized if five or more observations are collected.     

A PRECIPITATION ESTIMATION TECHNIQUE FOR DEVELOPING ISOHYETS IN AN ARID AREA USING VEGETATION AND TOPOGRAPHIC PARAMETERS1

A technique is presented for developing an isohyet map for the Hualapai Valley, a closed hydrologic basin of about 315 square miles in the northwestern Great Basin in Nevada. In this basin there is practically no climatic data, and in the northwest Great Basin there are too few stations for determination of rainfall on a detailed basis. Using a vegetational typing to represent a range in elevation and precipitation, an initial mean annual rainfall is determined for selected points on a grid pattern. This rainfall is then modified by using topographic parameters of slope, orientation, exposure, and rainfall shadow effect. The resulting point determinations of mean annual rainfall are then smoothed using a trend surface analysis, and an isohyetal map is drawn from the smoothed points. The technique provides an estimated accuracy of one inch of mean annual precipitation and one mile of resolution on isohyets.     

ON PRECIPITATION SENSOR NETWORK DENSITIES FOR EVALUATING WINTERTIME OROGRAPHIC CLOUD SEEDING EXPERIMENTS1

Principal component analysis is used to investigate density requirements of wintertime orographic cloud seeding experiment precipitation sensor networks. Three passes in the vicinity of Climax, Colorado are studied. The eighteen or more evenly spaced precipitation sensors of each pass are almost completely described by three principal components. These three principal components appear to represent (i) mean precipitation, (ii) slope orientation to storm systems, and (iii) elevation. Evaluation of these principal components is implemented with two distribution-free tests, a proportionality test and the runs test. The results of this study suggest that the loss of experimental information caused by low density precipitation sensor networks may be of little consequence.     

SERENDIPITY: CAPTURING A DESIGN LEVEL PRECIPITATION EVENT1

ABSTRACT: On February 23–24, 1998, a frontal system moved across the U.S. Department of Energy's 3,500 km² Nevada Test Site (NTS) and resulted in significant depths of precipitation at all recording gages on the NTS. A preliminary analysis suggested that this precipitation event was of the magnitude and duration for which many flood mitigation structures have been designed. Given the data and field observations available and the potential implications of the event on the methodologies used to size flood mitigation structures throughout the West, a detailed analysis of this event was undertaken. The goals of this study were to compare this event with the regulatory design precipitation event, compare the estimated peak flow rates from the rainfall/runoff model used to size the flood mitigation structures at a radioactive waste management site with the estimated peak flows from the precipitation event, and examine if modification of the standard source of the design depths of precipitation is warranted.     

APPLICATION OF GEOGRAPHIC INFORMATION SYSTEMS TO GROUNDWATER MONITORING NETWORK DESIGN1

ABSTRACT: Effective monitoring configurations for contaminant detection in groundwater can be designed by analyzing the spatial relationships between candidate sampling sites and aquifer zones susceptible to contamination. Examples of such zones are the domain underlying the contaminant source, zones of probable contaminant migration, and areas occupied by water supply wells. Geographic information systems (GIS) are well-suited to performing key groundwater monitoring network design tasks, such as calculating values for distance variables which quantify the proximity of candidate sites to zones of high pollution susceptibility, and utilizing these variables to quantify relative monitoring value throughout a model domain. Through a case study application, this paper outlines the utility of GIS for detection-based groundwater quality monitoring network design. The results suggest that GIS capabilities for analyzing spatially referenced data can enhance the field-applicability of established methodologies for groundwater monitoring network design.     

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).     

400 YEARS OF CENTRAL CALIFORNIA PRECIPITATION VARIABILITY RECONSTRUCTED FROM TREE-RINGS1

ABSTRACT: Coastal central California is a region that has never been the subject of tree-ring studies. New tree-ring chronologies developed from cores of big cone spruce (Pseudotusuga macrocarpa (Torr.) Mayr.) growing in the Transverse Ranges of central Santa Barbara county were used to reconstruct precipitation fluctuations for this region. To verify the new reconstructions, calibration with recorded rainfall using cross-validation, comparison with other reconstructions, and documentary evidence from historical sources were utilized. The precipitation reconstructions show that there have not been fluctuations in mean precipitation on time scales longer than 30 years, but there have been major fluctuations in precipitation variability including changes in the frequency of extremes and rare events that have not occurred in the modern record.     

RESERVOIR WATER QUALITY SAMPLING DESIGN1

ABSTRACT: The design of monitoring programs often serves as one of the major sources of error or uncertainty in water quality data. Properly designed programs should minimize uncertainty or at least provide a means by which variability can be partitioned into recognizable components. While the design of sampling programs has received recent attention, commonly employed strategies for limnological sampling of lakes may not be completely appropriate for many reservoirs. Based on NES data, reservoirs are generally larger, deeper, and morphologically more complex than natural lakes. Reservoirs also receive a majority of their inflow from a single tributary located a considerable distance from the point of outflow. The result is the establishment of marked physical, biological, and chemical gradients from headwater to dam. The existence of horizontal as well as vertical gradients, and their importance in water quality sampling design were the subject of intensive transect sampling efforts at DeGray Lake, a U.S. Army Corps of Engineers reservoir in southern Arkansas. Data collected were used to partition Variance, identify areas of similarity, and demonstrate how an equitable sampling program might be designed.     

WATER QUALITY MONITORING NETWORK DESIGN: A PROBLEM OF MULTI-OBJECTIVE DECISION MAKING1

ABSTRACT: Hydrologic data network design is a fairly complicated problem where questions as to the number of gages required, time frequencies to be selected, and benefits/costs of monitoring still remain unresolved. These issues are intensified in case of water quality variables as they are more error-prone, costly, and time consuming to sample. The basic difficulty underlying the design and evaluation of monitoring systems is the lack of an objective criterion to assess: (a) the efficiency, and (b) cost-effectiveness of a network. A statistical procedure based on the entropy principle of information theory is proposed to address the evaluation of both factors. Efficiency is measured quantitatively in terms of the information produced by a network. Similarly, benefits of monitoring are described by informative measures for an objective evaluation of cost-effectiveness. The study presented demonstrates the applicability of the entropy method in assessing the efficiency and the benefits of an existing water quality monitoring network. The method is applied for temporal and spatial features of monitoring, handled as both separate and combined problems. The results are shown in the case of the highly polluted Porsuk River in Turkey. The strengths and shortcomings of the proposed methodology are discussed, with recommendations for future research on the application of the entropy principle in network design.     

RESPONSE OF GREEN‐AMPT MEIN‐LARSEN SIMULATED RUNOFF VOLUMES TO TEMPORALLY AGGREGATED PRECIPITATION1

ABSTRACT: Data collection frequency in automated systems is user determined and can range from seconds to hours or days. Currently, there is no standard or recommended frequency interval for collecting precipitation data from automated systems for input to event‐based models such as Green‐Ampt Mein‐Larsen (GAML). Data from 47 storm events at seven locations were used to simulate the response of GAML excess rainfall to temporally aggregated precipitation data. No difference in model efficiency was recognized when comparing one‐minute interval data (R²= 1.00) to five‐minute data (R²= 1.00). Very little model efficiency was lost at a 10‐minute (R²= 0.96) interval. After 10‐minutes, decline in efficiency became more rapid with R²= 0.16 at one hour. The combined effect of time interval with respect to drainage area, hydraulic conductivity, maximum 30‐minute intensity, and total precipitation also revealed similar results.     

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.     

NEW ZEALAND'S NATIONAL WATER QUALITY MONITORING NETWORK - DESIGN AND FIRST YEAR'S OPERATION1

ABSTRACT: The design and implementation of a national surface water quality monitoring network for New Zealand are described. Some of the lessons learned from the first year of operation are also addressed. Underpinning the design, and specified in advance, are the goal and objectives, the data quality assurance system, and the mechanism for data interpretation and reporting. Because of the difficulties associated with the use of a multitude of different agencies, only one agency is involved in field work and one laboratory undertakes the analysis. Staff training has been given a high priority. The network has been designed to give good trend detectability for regular sampling over a 5–10 year period.     

OBSERVATION WELL NETWORK DESIGN FOR PUMPING TESTS IN UNCONFINED AQUIFERS1

ABSTRACT: This paper presents a method for determining locations of observation wells to be used in conducting pumping tests in unconfined aquifers. Sensitivity coefficients, the distribution of relative errors, and the correlation coefficients between four aquifer parameters (horizontal and vertical hydraulic conductivities K_r and K_z, storage coefficient S, and specific yield S_y) are used as the criteria for the design of observation well networks and the interpretation of pumping tests. The contours of the relative errors over a vertical profile are very useful in selecting the “best” location of an observation well. Results from theoretical analyses suggest that a wide range of locations is suitable for the determination of K_r and that good locations for the determination of K_z and S may be poorly suited for the determination of S_y. Consideration must be given to the position and lengths of the pumping well screen in the selection of observation well locations. For a given location, the quality of test data can be improved by using high pumping rates and frequent sampling of drawdowns. We found that a minimum of two and preferably three observation locations are needed along a given transect. Results of the four parameters from a single well analysis may contain higher uncertainties. However, composite analyses of multiple observation wells can reduce the correlation between the four aquifer parameters, particularly between K_r and S_y, thus, improving the quality of parameter estimation. Results from two pumping tests conducted at sites located in Nebraska were examined with regard to the proposed methodology.