TEMPORAL AND SPATIAL CHARACTERIZATION OF RAINFALL OVER CENTRAL AND SOUTH FLORIDA1

requency evaluation and spatial characterization of rainfall in Central and South Florida are presented. Point frequency analysis performed at all available sites has shown that the 2‐parameter Gamma probability density function is the best model for monthly rainfall frequency over Central and South Florida. The model's parameters estimated at 145 stations were used to provide monthly rainfall estimates for 10‐ and 100‐year dry and wet return periods. Experimental and theoretical variograms computed for these estimates, as well as the Kriging estimation variance maps, show that the existing rain gage network is less capable of resolving monthly rainfall variation in the wet season than the dry season. May is the dry‐to‐wet transition month, while October is the wet‐to‐dry transition month with average rainfall of 4.5 inches. Monthly average rainfall is above 7 inches during the wet season and below 3 inches during the dry season. Two‐thirds of the annual rainfall is accumulated in the wet season. Annual average rainfall is maximum (above 60 inches) in many areas along the east coast, and is minimum (below 45 inches) in many areas over Lake Okee‐chobee and Central Florida. Rainfall maps show a changing pattern between the wet and the dry seasons. Frontal rainfall occurs in the dry season, while convective rainfall, tropical depression, and hurricanes occur in the wet season. Average rainfall is higher along the east coast area in the dry season and it is higher along the west coast area in the wet season.     

TREE‐RING BASED RECONSTRUCTIONS OF INTERANNUAL TO DECADAL SCALE PRECIPITATION VARIABILITY FOR NORTHEASTERN UTAH SINCE 1226 A.D.1

ABSTRACT: Samples from 107 piñon pines (Pinns edulis) at four sites were used to develop a proxy record of annual (June to June) precipitation spanning the 1226 to 2001 AD interval for the Uinta Basin Watershed of northeastern Utah. The reconstruction reveals significant precipitation variability at interannual to decadal scales. Single‐year dry events before the instrumental period tended to be more severe than those after 1900. In general, decadal scale dry events were longer and more severe prior to 1900. In particular, dry events in the late 13th, 16th, and 18th Centuries surpass the magnitude and duration of droughts seen in the Uinta Basin after 1900. The last four decades of the 20th Century also represent one of the wettest periods in the reconstruction. The proxy record indicates that the instrumental record (approximately 1900 to the Present) underestimates the potential frequency and severity of severe, sustained droughts in this area, while over representing the prominence of wet episodes. In the longer record, the empirical probability of any decadal scale drought exceeding the duration of the 1954 through 1964 drought is 94 percent, while the probability for any wet event exceeding the duration of the 1965 through 1999 wet spell is only 1 percent. Hence, estimates of future water availability in the Uinta Basin and forecasts for exports to the Colorado River, based on the 1961 to 1990 and 1971 to 2000 “normal” periods, may be overly optimistic.     

AN EVALUATION OF FLOOD FREQUENCY ESTIMATES BASED ON RAINFALL/RUNOFF MODELING1

ABSTRACT: An evaluation of flood frequency estimates simulated from a rainfall/runoff model is based on (1) computation of the equivalent years of record for regional estimating equations based on 50 small stream sites in Oklahoma and (2) computation of the bias for synthetic flood estimates as compared to observed estimates at 97 small stream sites with at least 20 years of record in eight eastern states. Because of the high intercorrelation of synthetic flood estimates between watersheds, little or no regional (spatial) information may be added to the network as a result of the modeling activity. The equivalent years of record for the regional estimating equations based totally on synthetic flood discharges is shown to be considerably less than the length of rainfall record used to simulate the runoff. Furthermore, the flood estimates from the rainfall/runoff model consistently underestimate the flood discharges based on observed record, particularly for the larger floods. Depending on the way bias is computed, the synthetic estimate of the 100-year flood discharge varies from 11 to 29 percent less than the value based on observed record. In addition, the correlation between observed and synthetic flood frequency estimates at the same site is also investigated. The degree of correlation between these estimates appears to vary with recurrence interval. Unless the correlation between these two estimates is known, it is not possible to compute a weighted estimate with minimum variance.     

A SCALE‐INVARIANT GAUSS‐MARKOV MODEL FOR DESIGN STORM HYETOGRAPHS1

Abstract. Hyetographs are essential to many hydrological designs. Many studies have shown that hyetographs are specific to storm types and durations. Recent work presented evidence that dimensionless hyetographs are scale invariant. We show that the simple scaling property of rainfall guarantees that the normalized rainfall rates of different storm durations are identically distributed and propose a nonstationary Gauss‐Markov model based on the annual maximum events that arise from the dominant storm type. We derive the unique estimators for the parameters of the Gauss‐Markov model under two constraints that: (a) the typical peak rainfall rate is preserved, and (b) the most likely hyetograph is obtained. One attractive feature of this model is that it allows translating hyetographs between storms of different durations. Two examples illustrate our model.     

SPACE-TIME VALIDATION OF A THUNDERSTORM RAINFALL MODEL1

A probability model for predicting the occurrence and magnitude of thunderstorm rainfall developed in the southwestern United States was tested in the metropolitan Chicago area with reasonable success, especially for the moderate to the extreme runoff-producing events. The model requires the estimation of two parameters, the mean number of events per year and the conditional probability of rain given that an event has occurred. To tie in the data from more than one gage in an area, an event can be defined in several ways, such as the areal mean rainfall exceeding 0.50 inch and at least one gage receiving more than 1.0 inch. This type of definition allows both of the model parameters to be obtained from daily warm-season rainfall records. Regardless of the definition used a Poisson distribution adequately described the number of events per season. A negative binomial distribution was derived as representing the frequency density function for rainfall where several gages are employed in defining a storm. Chicago data fit both distributions very well at events with relatively high return periods. The results indicate the possibility of using the model on a regional basis where limited amount of data may be used to estimate parameters for extensive areas.     

Display and interpretation of fire behavior probabilities for long-term planning

Fire management planning for wildlands traditionally uses fire behavior estimated on the basis of worst-case weather at a specific site, but more realistic estimates can be obtained by considering the entire distribution of possible sites and weather conditions. Probability distributions of four widely used fire behavior variables were derived for four test cases in the Northern Rockies and Northern Intermountain Zone. The variables were rate of spread, fireline intensity, fire perimeter length-to-width ratio, and scorch height. Results were depicted in simple line graphs, three-dimensional pin graphs, and tables; they ranged from the cumulative probability of one variable to joint probabilities of four variables. Increasing the number of variables depicted increased the amount and scope of information available. Examples of interpreting the graphs and tables show how these techniques can be used in long-term fire program planning, fire suppression, management of various resources affected by fire, and interdisciplinary resource planning.     

STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

ABSTRACT: A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas-Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi-state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical record.     

RELIABILITY OF THE DESIGN STORM CONCEPT IN EVALUATING RUNOFF PEAK FLOW1

A comparative study was undertaken to evaluate peak runoff flow rates using (1) a continuous series of actual rainfall events and (2) design storms. The ILLUDAS computer model was used to simulate runoff over a catchment within the city of Montreal, Canada. A ten-year period, five-minute increment rainfall data base was used to derive peak flow frequency curves. Two types of design storms were analyzed: one derived from intensity duration frequency curves (Chicago type), the other from averaging actual rainfall patterns (Huff type). Antecedent soil moisture conditions were considered in the analyses. It was found that the probability distribution of runoff peak flow was sensitive to the choice of design storm pattern and to the antecedent soil moisture condition. A symmetrical, Chicago-type design storm with antecedent dry soil moisture produced a flow frequency curve similar to the one obtained from a series of historical rainfall events.     

RAINFALL POINT INTENSITIES IN AN AIR MASS THUNDERSTORM ENVIRONMENT: WALNUT GULCH,ARIZONA1

ABSTRACT: Point rainfall intensities for a given return period are often used to formulate design storms for rainfall/runoff models to simulate design floods. These design floods are in turn used to design bridges, culverts, and a variety of drainage and flood control structures. The projected rapid growth in the southwestern United States will require very substantial monetary investments in drainage infrastructure. Accurate estimates of point rainfall intensities are critical to ensure both safe designs while not wasting dollars in overdesign. Rainfall point intensities (accumulated rainfall depth over a specified duration) for 5‐, 15‐, 30‐, and 60‐minute durations for the 2‐, 5‐, 10‐, 25‐, 50‐, and 100‐year return periods were determined for southeast Arizona. Thirty‐five years of rainfall record (1961 to 1995) were used in this study. The records came from 20 stations that were grouped into five sets of four independent stations to extend the rainfall records. The stations are in the USDA‐ARS Walnut Gulch Experimental Watershed (WGEW), which is representative of large portions of the Southwest whose runoff generation is dominated by air‐mass thunderstorms. The 5‐, 15‐, 30‐, and 60‐minute maximum intensities per year followed log‐normal distributions. The mean point rainfall intensities of the five sets of gages are very close (between 0 and 11 percent) to the NOAA values of the 5‐, 15‐, 30‐, and 60‐minute durations for all return periods. Much larger differences between the mean point rainfall intensities for all durations were found when these results were compared to those of a previous study done with a shorter rainfall record (between 14 and 33 percent for the 25‐, 50‐, and 100‐year return‐periods). The difference between the largest and the smallest values of point rainfall intensities recorded by each group, for all durations, usually increases as the return period increases.     

DETERMINATION OF SEDIMENT YIELD BY TRANSFERRING RAINFALL DATA1

ABSTRACT: A methodology for obtaining the optimal design value to allow for sediment storage in a reservoir is presented for the situation where no data on sediment loads in the incoming streams are available. Information concerning the amount of sediment delivered to the reservoir over its life-time is obtained by a sediment yield model which uses data on rainfall amount and duration obtained from a nearby experimental watershed. Bayesian Decision Theory is used to obtain the optimal storage requirements in order to consider the natural variation of rainfall and the sampling error due to the short rainfall record available. The normally difficult calculations involved were made tractable by the use of simplifications and approximations valid in the context of the problem. Results show that sediment storage requirements can be calculated in this manner and that consideration of the uncertainties involved leads to a storage requirement substantially larger than that calculated without such consideration.     

HYDROLOGIC DESIGN CONSIDERATIONS OF CONSTRUCTED WETLANDS FOR URBAN STORMWATER RUNOFF1

ABSTRACT: The successful design of constructed wetlands requires a continuous supply of water or vegetation that can withstand drought conditions. Having a constant water source is the best alternative to insure species diversity throughout the season. Consequently, detention structure designs should be based on times between events as well as on hydrologic return periods, since between events is when most evaporation and infiltration losses are likely to occur. In arid or semi-arid environments, this is a difficult process because of long interevent times and seasonal changes in precipitation patterns. This discussion is predicated on the assumption that phytoplankton, epiphytic algae, and emergent vegetation require moist conditions to be effective at removing nutrients, metals and other pollutants. There are drought tolerant species of vegetation that can be used in constructed wetlands but it may take several days to re-establish the attached bacteria communities necessary for optimum pollutant removal. This paper examines a stochastic framework to examine the probability of extended dry periods based on historic rainfall data. The number of consecutive dry days is selected for a specified level of assurance. By multiplying this value by the sum of daily system losses, an overall pond volume can be determined that ensures a minimum depth of water. To illustrate the utility of the approach, the method is applied to a site in Spokane, Washington.     

HEAVY RAINFALL DISTRIBUTIONS BY SEASON IN LOUISIANA: SYNOPTIC INTERPRETATIONS AND QUANTILE ESTIMATES1

ABSTRACT: In most studies, quantile estimates of extreme 24-hour rainfall are given in annual probabilities. The probability of experiencing an excessive storm event, however, differs throughout the year. As a result, this paper explored the differences between heavy rainfall distributions by season in Louisiana. It was concluded by using the Kruskal-Wallis and Mann-Whitney tests that the distribution of heavy rainfall events differs significantly between particular seasons at the sites near the Gulf Coast. Furthermore, seasonal frequency curves varied dramatically at the four sites examined. Mixed distributions within these data were not found to be problematic, but the mechanisms that produced the events were found to change seasonally. Extreme heavy rainfall events in winter and spring were primarily generated by frontal weather systems, while summer and fall events had high proportions of events produced by tropical disturbances and airmass (free-convective) conditions.     

SPATIAL ANALYSIS FOR MONTHLY RAINFALL IN SOUTH FLORIDA1

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

CLIMATE FACTOR FOR SMALL-BASIN FLOOD FREQUENCY1

ABSTRACT: A climate factor, C_T, (T = 2–, 25-, and 100-year recurrence intervals) that delineates regional trends in small-basin flood frequency was derived using data from 71 long-term rainfall record sites. Values of C_T at these sites were developed by a regression analysis that related rainfall-runoff model estimates of T-year floods to a sample set of 50 model calibrations. C_T was regionalized via kriging to develop maps depicting its geographic variation for a large part of the United States east of the 105th meridian. Kriged estimates of C_T and basin-runoff characteristics were used to compute regionalized T-year floods for 200 small drainage basins. Observed T-year flood estimates also were developed for these sites. Regionalized floods are shown to account for a large percentage of the variability in observed flood estimates with coefficients of determination ranging from 0.89 for 2-year floods to 0.82 for 100-year floods. The relative importance of the factors comprising regionalized flood estimates is evaluated in terms of scale (size of drainage area), basin-runoff characteristics (rainfall. runoff model parameters), and climate (C_T).     

Variations in Newspaper Coverage on Water in the U.S. Intermountain West

Water is a salient issue in the Intermountain West of the United States (U.S.), with concerns ranging from water scarcity and drought to intermittent flooding and water quality risks. This paper investigates coverage of water issues across seven newspapers in the core of the U.S. Intermountain West region. Newspapers have the potential to set agendas and influence perceived salience of issues among consumers. The Intermountain West region shares common concerns about water supply and demand, climate change, and water quality. We investigate whether or not local daily newspaper coverage of water issues provides a more local or regional sensitivity. Findings from this exploratory study reveal differences in water coverage across local daily newspapers. The overall volume of water‐related articles differed across newspapers as did proportion of articles on specific water topics and connecting issues. Coverage of local issues was more dominant than might be expected given mass media trends, but water geography in articles extended across the U.S. and the world in every newspaper studied. Variations in newspaper coverage of water issues suggests more local nuance persists despite the experience of common water issues across the region.     

A 576‐Year Weber River Streamflow Reconstruction from Tree Rings for Water Resource Risk Assessment in the Wasatch Front,Utah

We present a 576‐year tree‐ring‐based reconstruction of streamflow for northern Utah's Weber River that exhibits considerable interannual and decadal‐scale variability. While the 20th Century instrumental period includes several extreme individual dry years, it was the century with the fewest such years of the entire reconstruction. Extended droughts were more severe in duration, magnitude, and intensity prior to the instrumental record, including the most protracted drought of the record, which spanned 16 years from 1703 to 1718. Extreme wet years and periods are also a regular feature of the reconstruction. A strong early 17th Century pluvial exceeds the early 20th Century pluvial in magnitude, duration, and intensity, and dwarfs the 1980s wet period that caused significant flooding along the Wasatch Front. The long‐term hydroclimatology of northern Utah is marked by considerable uncertainty; hence, our reconstruction provides water managers with a more complete record of water resource variability for assessment of the risk of droughts and floods for one of the largest and most rapidly growing population centers in the Intermountain West.     

COMBINATION OF RADAR AND GAUGE DATA IN A RAINFALL ARCHIVE SYSTEM1

ABSTRACT: Near real time daily rainfall estimates for the UK are available from three sources: a sparse network of gauges, radar data, or radar data adjusted by the sparse gauges. The PARAGON rainfall archive system, which has been developed by the UK Meteorological Office, is able to produce these estimates in near real time on a 5 km grid. The ability of these estimates to reproduce the 5 km grid point field derived later from a dense network of gauges is compared using case studies. Five techniques have been used to assess the relative quality of the various estimates. There is general agreement between the results of the various techniques. For the London radar there are examples of days when the rainfall estimate was improved by incorporating radar data; conversely, there are days when the radar data make it worse. Overall little evidence was found to suggest that adjusted radar data are consistently markedly better than gauge estimates. Discriminate use of radar data is recommended.     

ESTIMATION OF OPTIMAL YIELD IN YUN-LIN AREA OF TAIWAN USING DECISION ANALYSIS1

ABSTRACT: Ground water is a vital resource in the Yun-Lin area of Taiwan. A substantial amount is continuously extracted, creating adverse effects such as land subsidence and seawater intrusion. Minimizing these negative impacts depends on regulating the rate of groundwater withdrawal. An optimal yield must be determined to establish a sound water management policy. A wide range of safe yields for Yun-Lin have already been proposed based on constant hydrological and hydrogeological parameters. By extending the results of those investigations, this study presents a decision analysis model. The optimal yield concept is introduced as well. The proposed model incorporates a probability density function for rainfall recharge and a loss function, derived from fluctuations in the ground water table. Through decision analysis, the optimum yield is obtained by minimizing the expected value of the loss function. The optimal yield varies monthly because the probability density function is time dependent. Analysis results suggest that the cumulative optimum yield of ground water in the area is 1.26 × 10⁸ m³/year. If the probability distribution function for rainfall recharge is modified as new precipitation data become available, the above suggested yield may require revision in the future.     

Analysis of Extreme Summer Rainfall Using Climate Teleconnections and Typhoon Characteristics in South Korea1

Abstract: It is now widely acknowledged that climate variability modulates the frequency of extreme hydrological events. Traditional methodologies for hydrologic frequency analysis are not devised to account for variation in the exogenous teleconnections. Flood frequency analysis is further plagued by the assumptions of stationary in the causal structure as well as ergodicity. Here, we propose a dynamical hierarchical Bayesian analysis to account for exogenous forcing that govern the summer season rainfall. The precursors for Korean summer rainfall at different frequencies are identified utilizing wavelet and independent component analyses. The sea surface temperatures, the ensemble of rainfall predictions by General Circulation Model, in addition to the typhoon attributes were found to have direct correlation with extreme rainfall events and were used as inputs to the logistic regression model. The model parameters are estimated using Markov Chain Monte Carlo and the resulting posterior distributions associated with individual inputs are analyzed to advance our understanding of the spatiotemporal impact of the teleconnections. Eight rainfall stations throughout Korea are considered in this analysis. We demonstrate that the probability of occurrence of extreme events could be successfully projected at a 90% rate of correct classification of extreme events.