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.     

GAGE DENSITY AND LOCATION FOR ESTIMATING MEAN ANNUAL PRECIPITATION IN MOUNTAINOUS AREAS1

ABSTRACT: Data from a network of 45 shielded precipitation gages on the Reynolds Creek Experimental Watershed in Southwestern Idaho were analyzed to determine the optimum gage density for estimating mean annual precipitation. Four subsets of the 45 gage network were used to derive a curve of mean annual precipitation versus number of gages with a confidence band at the 95 percent level. When less than 20 gages were used in the estimate, the confidence interval widens rapidly. Estimates were improved by stratifying gages on the basis of plant cover class or by elevation bands. Sixty-four percent of the variation in mean annual precipitation was accounted for by elevation and cover class. The aspect and hydrologic soil classification were not statistically significant.     

FOG DRIP IN THE BULL RUN MUNICIPAL WATERSHED,OREGON1

ABSTRACT: Net precipitation under old growth Douglas fir forest in the Bull Run Municipal Watershed (Portland, Oregon) totaled 1739 mm during a 4Cbweek period, 387 mm more than in adjacent clearcut areas. Expressing data on a full water year basis and adjusting gross precipitation for losses due to rainfall interception suggest fog drip could have added 882 mm (35 in) of water to total precipitation during a year when precipitation measured 2160 mm in a rain gage in a nearby clearing. Standard rain gages installed in open areas where fog is common may be collecting up to 30 percent less precipitation than would be collected in the forest. Long term forest management (Le., timber harvest) in the watershed could reduce annual water yield and, more importantly, summer stream flow by reducing fog drip.     

A NOTE ON AREAL RAINFALL DEFINITION

A discussion is presented of the likely sources of error in defining areal rainfall on a storm basis. These include the instrumental error, sampling fluctuations over the area, and network density. The analysis of dense raingage data provides some perspective of the magnitude of the errors that might be encountered from the natural variability of rainfall. Except for one watershed in Arizona, the coefficient of variation, based on a sample of storm totals from the individual gages in various size areas, remains relatively constant with increasing area for a particular storm. The error due to rainfall variability over the area is probably the most important and must be considered in experiments which attempt to resolve small-area hydrologic problems.     

Long‐Term High‐Resolution Radar Rainfall Fields for Urban Hydrology

Accurate records of high‐resolution rainfall fields are essential in urban hydrology, and are lacking in many areas. We develop a high‐resolution (15 min, 1 km²) radar rainfall data set for Charlotte, North Carolina during the 2001‐2010 period using the Hydro‐NEXRAD system with radar reflectivity from the National Weather Service Weather Surveillance Radar 1988 Doppler weather radar located in Greer, South Carolina. A dense network of 71 rain gages is used for estimating and correcting radar rainfall biases. Radar rainfall estimates with daily mean field bias (MFB) correction accurately capture the spatial and temporal structure of extreme rainfall, but bias correction at finer timescales can improve cold‐season and tropical cyclone rainfall estimates. Approximately 25 rain gages are sufficient to estimate daily MFB over an area of at least 2,500 km², suggesting that robust bias correction is feasible in many urban areas. Conditional (rain‐rate dependent) bias can be removed, but at the expense of other performance criteria such as mean square error. Hydro‐NEXRAD radar rainfall estimates are also compared with the coarser resolution (hourly, 16 km²) Stage IV operational rainfall product. Stage IV is adequate for flood water balance studies but is insufficient for applications such as urban flood modeling, in which the temporal and spatial scales of relevant hydrologic processes are short. We recommend the increased use of high‐resolution radar rainfall fields in urban hydrology.     

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.     

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.     

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.     

APPLICATION OF KRIGING TO ESTIMATING MEAN ANNUAL PRECIPITATION IN A REGION OF OROGRAPHIC INFLUENCE1

ABSTRACT: Estimates of mean annual precipitation (MAP) over areas are the starting point for all computations of water and chemical balances for drainage basins and surface water bodies. Any errors in the estimates of MAP are propagated through the balance computations. These errors can be due to: (1) failures of individual gages to collect the amount of precpitation that actually falls; (2) operator errors; and (3) failure of the raingage network to adequately sample the region of interest. This paper attempts to evaluate the last of these types of error by applying kriging in two different approaches to estimating MAP in New Hampshire and Vermont, USA. The data base is the 1951–1980 normal precipitation at 120 raingages in the two states and in adjacent portions of bordering states and provinces. In the first approach, kriging is applied directly to the MAP values, while in the second, kriging is applied to a “precipitation delivery factor” that represents the MAP with the orographic effect removed. The first approach gives slightly better kriged estimates of MAP at seven validation stations that were not included in the original analysis, but results in an error surface that is highly contorted and in larger maximum errors over most of the region. The second approach had a considerably smoother error surface and, thus, is generally preferable as a basis for point and areal estimates of MAP. MAP estimates in the region have 95 percent confidence intervals of about 20 cm/yr at low and moderate elevations, and up to 35 cm/yr at high elevations. These uncertainties amount to about 20 percent of estimated MAP values.     

SAMPLING ACCURACY OF PIT VS. STANDARD RAIN GAGES ON THE FERNOW EXPERIMENTAL FOREST1

ABSTRACT: Catch in standard (unshielded) rain gages exposed 3 feet above the land surface was compared with catch in pit (buried) gages exposed 1 inch above the land surface. These tests confirmed that catch in standard gages under estimates point rainfall in forest openings, as well as in conventional weather stations. Pit gages caught significantly (P=0.05) more rain than did standard gages at each of four locations tested. Catch increases ranged from 2.3 to 3.4 percent.     

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.     

THROUGHFALL IN PLANTED STANDS OF FOUR SOUTHERN PINE SPECIES IN EAST TEXAS1

Throughfall was measured during 1978–79 beneath the canopies of adjacent stands of four major southern pine species, all on identical soil type and topography in the Stephen F. Austin Experimental Forest. Observations from 44 storms in a randomized network of 15, 5.08 cm PVC gages in a 0.4 ha plot of each species showed that throughfall expressed as percent of storm precipitation, is greatest under longleaf pine and least under loblolly pine; throughfall under shortleaf and slash pine did not differ significantly. Generally, through-fall decreased with storm size and intensity, with distance from the nearest tree stem, and is greater during summer half-year (May–October). Canopy drips, apparently accounting for the greater throughfall for the gage position closer to the stems, were more numerous than reported elsewhere. The 5.08 cm PVC gages proved to be acceptable substitutes for standard nonrecording gages in measuring throughfall. A network of 15 such gages was sufficient to sample throughfall data with 90 percent accuracy in each of the four southern pine plantations.     

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.     

STORM CHARACTERISTICS OF CONVECTIVE-SCALE PRECIPITATION1

A classification scheme for convective precipitation, having applications in both analysis and modeling of meteorological and hydrological events, is presented. The method is based upon observations of rainfall at the ground, radar scans of storm events, and visible and infrared satellite imagery of larger storm systems. Empirical and theoretical frequency distributions are derived for total storm rainfall, rainfall duration and time between storms for each of the convective categories. This stratification is directly applicable to the experimental design and evaluation of weather modification projects and may be useful for the development and interpretation of meteorological and hydrological models. When atmospheric conditions limit storm development to cells, rainfall was seldom observed. Small clusters also produce small amounts of rainfall but have a longer lifetime than cells and are likely candidates for cloud seeding attempts to encourage their growth to large clusters. Large and nested clusters usually produce large amounts of natural precipitation. A few large storms account for most of a season's rainfall.     

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.     

USE OF RADAR TO DERWE A STORM INTENSITY-DURATION CURVE1

ABSTRACT: Rainstorms which exceed the design capacity of conveyance systems and cause extensive damage to structures and property, occur frequently in Alberta. After such a severe storm, an early and quick assessment of the storm's location and magnitude and the corresponding frequency for various duration (storm intensity-duration curve) is often required to estimate the damage. The storm intensity-duration curve is produced with information obtained from a sparse network of recording raingages, thus, creating a high degree of uncertainty in the result. Short-duration precipitation is usually quite variable in Alberta; hencea very dense network of recording precipitation stations would be required to provide precise measurements of the storm intensity-duration curve at all locations. Such a dense network does not exist in Alberta; it would be very expensive to install, maintain, and thus difficult to justify financially. One solution for obtaining a large amount of closely spaced in-intensity-duration values is to use weather radar. Using weather radar data, intensity-duration curves could be produced routinely for any set of prespecified locations. The radar data thus have the potential for facilitating the identification of the return period of rainfall events quickly, cheaply, and precisely when the long-term intensity-duration curves are available. As a pilot project to demonstrate the feasibility of the method and the potential of the radar data, computer software was developed to derive from archived radar data, intensity-duration values for up to a 2,500 2 area for a given storm.     

Rainfall Interception Based on Indirect Methods: A Case Study in Temperate Forests in Oaxaca,Mexico

Rainfall interception represents the amount of water trapped in natural cover that is not drained directly to the ground. Intercepted rainfall may evaporate after a rain event, making it one of the main drivers of water balance and hydrologic regionalization. This process can be affected by factors such as climate, altitude, vegetation type, and topography. Here is a simple method of calculating rainfall interception in temperate forests using in Santa Maria Yavesia, Oaxaca, and Mexico as an illustrative study area. We used two rain gauges to measure net precipitation (N_p) under the canopy at each study site and one gauge outside the canopy to obtain gross precipitation (G_p). Throughfall (T_h) was indirectly measured using hemispherical photographs. Rainfall interception was obtained through a combination T_h and G_p and N_p. The mean rainfall interception was 50.6% in the Abies forests, 23%–40% in the coniferous‐mixed forests, and 27.4% in the broad‐leaved forests. We classified rainfall events by intensity to determine the effect of canopy structure and precipitation and found that 75% of the events were weak events, 24% were moderate events, and 1% were strong events. In addition, we found that rainfall interception was lower when the intensity of precipitation was higher. Our method can be replicated in different ecosystems worldwide as a tool for assessing the influence of rainfall interception in terms of ecological services.     

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).     

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.