A SIMPLE METHOD FOR ESTIMATING BASEFLOW AT UNGAGED LOCATIONS1

ABSTRACT: Baseflow, or water that enters a stream from slowly varying sources such as ground water, can be critical to humans and ecosystems. We evaluate a simple method for estimating base‐flow parameters at ungaged sites. The method uses one or more baseflow discharge measurements at the ungaged site and longterm streamflow data from a nearby gaged site. A given baseflow parameter, such as the median, is estimated as the product of the corresponding gage site parameter and the geometric mean of the ratios of the measured baseflow discharges and the concurrent discharges at the gage site. If baseflows at gaged and ungaged sites have a bivariate lognormal distribution with high correlation and nearly equal log variances, the estimated baseflow parameters are very accurate. We tested the proposed method using long‐term streamflow data from two watershed pairs in the Driftless Area of southwestern Wisconsin. For one watershed pair, the theoretical assumptions are well met; for the other the log‐variances are substantially different. In the first case, the method performs well for estimating both annual and long‐term baseflow parameters. In the second, the method performs remarkably well for estimating annual mean and annual median baseflow discharge, but less well for estimating the annual lower decile and the long‐term mean, median, and lower decile. In general, the use of four measurements in a year is not substantially better than the use of two.     

REGIONALIZATION AND PREDICTION OF ANNUAL FLOODS IN THE FRASER RIVER CATCHMENT,BRITISH COLUMBIA1

A method of predicting probability distributions of annual floods is presented and is applied to the Fraser River catchment of British Columbia. The Gumbel distribution is found to adequately describe the observed flood frequency data. Using the estimated Gumbel parameters, discriminant analysis is performed to separate basins into flood regions. Within each region, regression analysis is used to relate physiographic and climatic variables to the means and standard deviations of the annual flood series. The regression equations are applied to four test basins and the results indicate that the method is suitable for an estimation of annual floods.     

Evidence for Changing Flood Risk in New England Since the Late 20th Century1

Abstract: Long‐term flow records for watersheds with minimal human influence have shown trends in recent decades toward increasing streamflow at regional and national scales, especially for low flow quantiles like the annual minimum and annual median flows. Trends for high flow quantiles are less clear, despite recent research showing increased precipitation in the conterminous United States over the last century that has been brought about primarily by an increased frequency and intensity of events in the upper 10th percentile of the daily precipitation distribution – particularly in the Northeast. This study investigates trends in 28 long‐term annual flood series for New England watersheds with dominantly natural streamflow. The flood series are an average of 75 years in length and are continuous through 2006. Twenty‐five series show upward trends via the nonparametric Mann‐Kendall test, 40% (10) of which are statistically significant (p < 0.1). Moreover, an average standardized departures series for 23 of the study gages indicates that increasing flood magnitudes in New England occurred as a step change around 1970. The timing of this is broadly synchronous with a phase change in the low frequency variability of the North Atlantic Oscillation, a prominent upper atmospheric circulation pattern that is known to effect climate variability along the United States east coast. Identifiable hydroclimatic shifts should be considered when the affected flow records are used for flood frequency analyses. Special treatment of the flood series can improve the analyses and provide better estimates of flood magnitudes and frequencies under the prevailing hydroclimatic condition.     

PARAMETRIC/NONPARAMETRIC MIXTURE DENSITY ESTIMATION WITH APPLICATION TO FLOOD-FREQUENCY ANALYSIS1

Much attention has been invested in the model choice problem for peak annual flows, in the context of flood frequency analysis. The authors would sidestep this dilemma through non-parametric density estimation methodology, but recognize that the standard nonparametric estimators preclude the use of prior information and related data, and furthermore have virtually no tail at all. Here we offer a remedy for these inadequacies by introducing an estimator which mixes parametric and nonparametric density estimates. We prove that our mixture rule is consistent. By this procedure, we do allow incorporation of prior information, experience, and regional data information, but nevertheless provide a safeguard against incorrect model choice.     

FOREST GROWTH IMPACT ON PEAK SNOW PACK MEASUREMENTS AT LONG TERM SNOW COURSES1

ABSTRACT: Snow course surveys in late winter provide stream‐flow forecasters with their best information for making water supply and flood forecasts for the subsequent spring and summer runoff period in mountainous regions of western North America. Snow survey data analyses are generally based on a 30‐year “normal” period. It is well documented that forest cover changes over time will affect snow accumulation on the ground within forests. This paper seeks to determine if forest cover changes over decades at long term snow courses decrease measured peak snow water equivalent (SWE) enough to affect runoff prediction. Annual peak SWE records were analyzed at four snow courses in two different forest types having at least 25 years of snowpack data to detect any decreases in SWE due to forest growth. No statistically significant decreases in annual peak SWE over time were found at any of these four snow courses. The wide range of annual winter precipitation and correspondingly highly variable peak snowpack accumulation, as well as many other weather and site variables, masked any minor trends in the data.     

DEVELOPMENT OF A GIS‐BASED FLOOD INFORMATION SYSTEM FOR FLOODPLAIN MODELING AND DAMAGE CALCULATION1

ABSTRACT: This work presents a flexible system called GIS‐based Flood Information System (GFIS) for floodplain modeling, flood damages calculation, and flood information support. It includes two major components, namely floodplain modeling and custom designed modules. Model parameters and input data are gathered, reviewed, and compiled using custom designed modules. Through these modules, it is possible for GFIS to control the process of flood‐plain modeling, presentation of simulation results, and calculation of flood damages. Empirical stage‐damage curves are used to calculate the flood damages. These curves were generated from stage‐damage surveys of anthropogenic structures, crops, etc., in the coastal region of a frequently flooded area in Chia‐I County, Taiwan. The average annual flood damages are calculated with exceedance probability and flood damages for the designed rainfalls of 2, 5, 10, 25, 50, 100, and 200 year recurrence intervals with a duration of 24 hours. The average annual flood depth in this study area can also be calculated using the same method. The primary advantages of GFIS are its ability to accurately predict the locations of flood area, depth, and duration; calculate flood damages in the floodplain; and compare the reduction of flood damages for flood mitigation plans.     

A NEW LOOK AT FLOOD RISK DETERMINATION1

ABSTRACT: The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.     

COMPARISON OF ANNUAL AND PARTIAL DURATION SERIES FLOODS ON THE MURRUMBIDGEE RIVER1

ABSTRACT: In current hydrologic practice flood frequency estimates are usually based upon either the annual or the partial duration series of floods. Recurrence intervals generated by each series are not equivalent, however, and conversion of recurrence intervals from one series to the other is usually achieved by reference to a mathematical function developed by Langbein in 1949. Data collected on the Murrumbidgee River in New South Wales suggest, however, that the Langbein conversion function does not always provide a reliable means of comparing recurrence intervals. For discharges more frequent than the three year annual flood the Langbein function understates the discrepancy between the two sets of recurrence interval by approximately 35 percent. Langbein's own North American data appear to be consistent with those collected on the Murrumbidgee River.     

PROJECTION OF URBANIZATION EFFECTS ON RUNOFF USING CLARK INSTANTANEOUS UNIT HYDROGRAPH PARAMETERS1

ABSTRACT: To alleviate serious flooding problems brought upon by rapid urbanization in the Beargrass Creek watershed, located in Louisville, Kentucky, the U.S. Army Corps of Engineers undertook a major flood study in 1973. In order to predict flood conditions in 1990, the year when the watershed was expected to undergo complete urbanization, trends in the Clark Instantaneous Unit Hydrograph (Clark IUH) parameters were utilized to determine the 1990 unit hydrograph and flood conditions. Based on the results from this flood study, this paper demonstrates the applicability of using projected Clark IUH parameters for modeling future runoff conditions in an urbanizing watershed. Values of these parameters, as estimated from maximum annual historical flood data, are used to develop regression models for predicting future Clark IUH parameters. Using the projected parameters, selected annual flood events since 1973 are simulated in order to verify the accuracy of these projections. Results show a close correspondence between the simulated and observed flood characteristics. Hence, the use of projected Clark IUH parameters is an appropriate procedure for modeling future runoff conditions in an urbanizing watershed.     

STREAMFLOW TRENDS IN WISCONSIN'S DRIFTLESS AREA1

ABSTRACT: Trends in streamflow characteristics were analyzed for streams in southwestern Wisconsin's Driftless Area by using data at selected gaging stations. The analyses indicate that annual low flows have increased significantly, whereas annual flood peaks have decreased. The same trends were not observed for forested areas of northern Wisconsin. Streamflow trends for other streams in southeastern Wisconsin draining predominantly agricultural land were similar to trends for Driftless Area streams for annual low flows. The causes for the trends are not well understood nor are the effects. Trends in annual precipitation do not explain the observed trends in streamflow. Other studies have found that erosion rates decreased significantly in the Driftless Area, and have attributed this reduction to a change of agricultural practices, which increase infiltration, decrease flood peaks, and increase low flows.     

CONTINUOUS SIMULATION FOR WATER QUALITY PLANNING1

ABSTRACT: This paper describes a methodology for the evaluation of water quality plans analogous to procedures used in flood control planning, where flood damage frequency curves provide the basis for determining flood control benefits. The proposed method uses continuous water quality simulation to develop long term information from which water quality frequency curves can be obtained. This frequency information allows the evaluation of the impact of proposed water quality control plans taking into consideration the variable nature of the water resource. Using treatment costs and other economic indicators of water quality, the frequency information can be used to estimate the cost-effectiveness and economic efficiency of alternative plans. The method is demonstrated in a semi-hypothetical environment; real hydrologic and climatic characteristics are assigned to a hypothetical watershed configuration. Alternative management plans are simulated and analyzed for both physical and economic impacts. The advantages of continuous simulation and its use in water quality planning are explored.     

A NONTRADITIONAL METHODOLOGY FOR FLOOD STAGE-DAMAGE CALCULATIONS1

ABSTRACT: This paper presents a new methodology to calculate economic losses from hypothetical, extreme flood events, such as the Probable Maximum Flood. The methodology uses economic data compiled from already-available secondary sources, such as U.S. Census data on magnetic tapes, utilizing microcomputer and other electronic media. Estimates of land elevations are obtained from topographic maps, and flood elevations axe estimated using, for example, a dam breach and flood routing (DAMBRK) model (Fread, 1984). The calculations are performed at a disaggregate spatial scale, by various land use and industrial classification categories. The basic areal units are city blocks (for urbanized areas), enumeration districts, and Census tracts. Depth-damage functions, which provide an estimate of damages as a proportion of the existing value of the structure, are estimated statistically. Computer software (called DAMAGE) is used to combine the economic, flood elevation, and depth-damage information to compute economic losses for different possible flood stages and for different inflow events. Two case studies are presented as illustrations of the method.     

Reconstructed Stream Flow for the Salt and Verde Rivers From Tree-Ring Data1

ABSTRACT: The Salt and Verde Rivers of central Arizona provide the water supply for metropolitan Phoenix and a considerable acreage of irrigated agriculture. Rapid urbanization has caused concern over future water supply and aggravated flooding in the already flood-prone Salt River Valley. Tree-ring data were used as a proxy source to extend the annual and seasonal runoff records back to A.D. 1580 and thus to determine whether the period of record for annual discharge adequately represents the long term flow characteristics of the two rivers. Results show that several periods of extended low flow have occurred during the past 400 years, many of which were more severe then any comparable period since 1890. The low flow periods appear to have a recurrence interval of about 22 years. Also the gaged records contain an above average number of high seasonal and annual flows when compared to the entire 400 years. The reconstructions contain important implications for future water supply and flood potentials in the Salt River Valley.     

Using Risk-Based Analysis and Geographic Information Systems to Assess Flooding Problems in an Urban Watershed in Rhode Island

This article provides an overview of the use of risk-based analysis (RBA) in flood damage assessment, and it illustrates the use of Geographic Information Systems (GIS) in identifying flood-prone areas, which can aid in flood-mitigation planning assistance. We use RBA to calculate expected annual flood damages in an urban watershed in the state of Rhode Island, USA. The method accounts for the uncertainty in the three primary relationships used in computing flood damage: (1) the probability that a given flood will produce a given amount of floodwater, (2) the probability that a given amount of floodwater will reach a certain stage or height, and (3) the probability that a certain stage of floodwater will produce a given amount of damage. A greater than 50% increase in expected annual flood damage is estimated for the future if previous development patterns continue and flood-mitigation measures are not taken. GIS is then used to create a map that shows where and how often floods might occur in the future, which can help (1) identify priority areas for flood-mitigation planning assistance and (2) disseminate information to public officials and other decision-makers.     

Measuring the Effects of a Flood Control Project: Hedonic Land Price Approach

This article aims to measure the effects of a flood control project planned for the Chitose River Basin in Hokkaido Prefecture, Japan, using hedonic land price functions. In these functions, "annual expected depth of flood water" is introduced as an explanatory variable to represent the effect of the flood control project. Comparing the approach with the method of "the economic analysis of flood control projects", which has been a conventional evaluation method widely used in Japan, the efficiency and limitations of our approach are discussed.     

Application of Index Procedures to Flood Frequency Analysis in Turkey1

Abstract: This study investigates the regional analysis of annual maximum flood series of 48 stream gauging stations in the basins of the West Mediterranean Region in Turkey. The region is divided into three homogeneous subregions according to both Student‐t test and Dalrymple homogeneity test. The regional relationships of mean annual flood per unit area‐drainage area and coefficient of skew‐coefficient of variation are obtained. Two statistically meaningful relationships of the mean flood per unit area‐drainage area and a unique relationship between skewness and variation coefficients exist. Results show that the index‐flood method may be applicable to each homogenous subregion to estimate flood quantiles in the study area.     

Flood area and damage estimation in Zhejiang,China

A GIS-based method to estimate flood area and damage is presented in this paper, which is oriented to developing countries like China, where labor is readily available for GIS data collecting, and tools such as, HEC-GeoRAS might not be readily available. At present local authorities in developing countries are often not predisposed to pay for commercial GIS platforms. To calculate flood area, two cases, non-source flood and source flood, are distinguished and a seed-spread algorithm suitable for source-flooding is described. The flood damage estimation is calculated in raster format by overlaying the flood area range with thematic maps and relating this to other socioeconomic data. Several measures used to improve the geometric accuracy and computing efficiency are presented. The management issues related to the application of this method, including the cost-effectiveness of approximate method in practice and supplementing two technical lines (self-programming and adopting commercial GIS software) to each other, are also discussed. The applications show that this approach has practical significance to flood fighting and control in developing countries like China.     

Will Evolving Climate Conditions Increase the Risk of Floods of the Large U.S.‐Canada Transboundary Richelieu River Basin?

In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.     

BIVARIATE FREQUENCY ANALYSIS OF FLOODS USING COPULAS1

Abstract: Bivariate flood frequency analysis offers improved understanding of the complex flood process and useful information in preparing flood mitigation measures. However, difficulties arise from limited bivariate distribution functions available to jointly model the correlated flood peak and volume that have different univariate marginal distributions. Copulas are functions that link univariate distribution functions to form bivariate distribution functions, which can overcome such difficulties. The objective of this study was to analyze bivariate frequency of flood peak and volume using copulas. Separate univariate distributions of flood peak and volume are first fitted from observed data. Copulas are then employed to model the dependence between flood peak and volume and join the predetermined univariate marginal distributions to construct the bivariate distribution. The bivariate probabilities and associated return periods are calculated in terms of univariate marginal distributions and copulas. The advantage of using copulas is that they can separate the effect of dependence from the effects of the marginal distributions. In addition, explicit relationships between joint and univariate return periods are made possible when copulas are employed to construct bivariate distribution of floods. The annual floods of Tongtou flow gauge station in the Jhuoshuei River, Taiwan, are used to illustrate bivariate flood frequency analysis.     

GENERALIZED SKEW COEFFICIENTS OF ANNUAL FLOODS FOR LOUISIANA STREAMS1

ABSTRACT: A generalized skew map for Louisiana streams was developed using data from Louisiana, Mississippi, Arkansas, and Texas with 20 or more years of annual flood records. A comparison between the newly developed Louisiana Generalized Skew Map (LGSM) and the generalized skew map recommended by the U.S. Water Resources Council (WRCGSM) was performed. The mean square error for the LGSM was 16 percent less than that of WRCGSM in direct application of the two maps. Performance of the new map was compared with the WRCGSM and with a regional analysis procedure through its application to the Log Pearson Type 3 (LP3) distribution. Two-thirds of the stations tested had lower standardized root mean square deviations (SRMSD) by a narrow margin using the skew coefficients obtained from LGSM instead of WRCGSM. The regional analysis also performed as well as the LGSM in terms of SRMSD. Thus, it was concluded that both LGSM and the regional analysis provide a more reliable tool for flood frequency analysis for Louisiana streams with short annual flood records.