Regional flood frequency analysis using GIS, L-moment and geostatistical methods

A realistic estimation of flood magnitude for a given return period is essential for successful operation and economical design of pivotal hydraulic structures such as dams, reservoirs and spillways, bridges, small culverts, urban drainage systems, flood plain zoning, economic evaluation of flood protection projects, etc. The flood frequency analysis is generally used for flood estimation, entirely based on the assumption that the floods are random and the floods in future are supposed to bear similar statistical properties that have occurred in the past. If adequate data are available at-site flood frequency analysis is used, otherwise regional flood frequency analysis (RFFA) is preferred for flood estimation. The RFFA for various small and medium catchments of India with different approaches have been carried out and reported in the literature. The focus of the present study is to carry out the RFFA using different approaches i.e. conventional method and L-moment and comparing the results for the Krishna and Penner subzone 3(h) of India. It was found that the values of growth factors obtained by the conventional method are higher than those of L-moment methods, thus leading to conservative estimate of the peak floods.

Regional flood frequency analysis by combining self-organizing feature map and fuzzy clustering

A basin -wide flood frequency analysis using Index flood and L-moment s approach offers an attractive solution to provide flood quant ile estimations at hundreds of ungauged sites within the Red River Basin of the North . L-moments diagrams and hierarchical clustering techniques were used initially to delineate hydrologic regions within the basin . Although the northern plain is relatively flat and almost monotonous, the analyses have show n that four homogeneous regions could be established for the basin . The whole basin as a region is also established for the purpose of flood estimations along the main stem . Appropriate probability distrib utions are fitted to t he pooled regional flood peak s in each region . Monte Carlo simulations are performed to decide the best distribution for each region , and the dominant distributions found are the Log -Pearson Type III and the generalized Pareto distrib utions . The regression of index flood with the physical factors of drainage area and basin slopes for two of the five regions are not very satisfactory . However, t he flood quantile estimates are sufficient for preliminary planning purposes. Basis for Reg ional Flood Frequency Analysis and L -moments The Red River of the North Basin has 91 gauged sites but that number was not sufficient for economic planning purposes as flood quantile estimations at hundreds of ungauged sites within the basin were required . Regional flood frequency analysis is a good alternative approach to flood quantile estimation using a single station approach. It is well accepted that using a regional approach in flood frequency analysis is effective in extending the flood information at a site to sites within a homogeneous region. Recent papers by Burn and Goel (2000), Cunderlik and Burn (2002), Pfister et al. (2002), and Lim and Lye (2003) are examples of such undertakings. The extension enables flood quantile estimates for any site i n a region to be expressed or inferred in terms of flood data recorded at all gauging sites in that region. Design flood estimations using a regional approach can often be carried out using methods such as the index -flood method and the direct regression o n quantiles method.

Flood frequency analysis estimates reliable design flood, which is critical for the safety of any hydraulic, hydrologic construction and management. The overall objective of this study is to perform flood frequency analysis for Seonath and Hasdeo river basins of Chhattisgarh state, India. In this study, homogeneous regions are delineated by Ward cluster analysis. Cluster variables are L-moment ratios of annual maximum events and catchment characters. Index flood is performed for parametric quantile estimation of flood events. L-moments are employed in regionalization, frequency distribution selection, and distribution parameter estimation. Locally weighted polynomial model (Locfit) is performed for at-site frequency analysis. Flood quantiles are estimated for regions and at sites. In regional flood frequency analysis, regionalisation based on annual maximum flood series shows better flood quantiles than regionalisation based on site characteristics. It reveals that geophysical homogeneity does not mean hydrologic homogeneity. Regional formulae for annual mean discharge are formulated based on catchment character for estimation of flood quantiles for ungauged catchments.KeywordsFlood frequency analysisCluster analysisL-momentsIndex floodLocfit

A common problem in flood frequency analysis is estimation, from a short gauged record, of the flood corresponding to a return period of 50–1000 years. One would expect that an estimate of the historical maximum event; i.e., the maximum flood in a period of perhaps 100–200 years, would, if properly included in the estimation procedure, improve the resulting estimate of the flood magnitude at the given return period. We attempt to assess the value of historical information using computer simulation. An annual flood sequence and a historical maximum event are generated from ah extreme‐value distribution (of type I or II) and quantitiles of the distribution are estimated by maximum likelihood, both including the excluding the historical event. After many such simulations have been performed the accuracy of the quantile estimates is assessed. We also consider the effect of errors in the magnitude of historical discharge estimates and the use of historical data in regional flood frequency analysis.

A catastrophic landslide dam breach induced debris flow initiated in Da-Cu-Keng stream, Ruifang town, when typhoon Xangsane hit Taiwan on November 1, 2000. Different available methodologies were used to model the natural dam breach induced debris flow and using field topography the hazard zones affected by debris mixtures were delineated. The numerical finite element or finite difference method is time consuming for the simulation of debris flow inundation areas and hence a rules-based GIS (Geographic Information System) analysis is proposed in this study. The model emphasizes the downstream inundated fan-shaped areas covered by debris mixtures through the overflow point. Topography and gradient are assumed to dominate the debris masses deposition mechanism in the GIS analysis. The approach considers the parameters’ effects, such as the runout distance, the debris masses magnitude and the inundated areas. The results of this study reveal that the GIS process using the rule-based approach speeds up the processing of delineating the hazard zones and assessment, which can be applied to early-warning and preliminary inundation hazardous mapping.

The dramatic loss of Louisiana's coastal wetlands and barrier shorelines is well recognized by government agencies, industries, universities, and the public. Between 1932 and 1990, the deltaic plain of the Mississippi River lost over 680,000 acres of land due to a complex suite of causes. Controversy and debate continues as to the causes of coastal land loss in Louisiana. Estimates of the human contribution of man to the land loss problem ranges between 10 percent and 90 percent (Britsch and Kemp, 1990; Penland et al., 1990, Penland et al., 1992; Turner, 1997). Several government agencies and industries have been targeted as the primary agent of coastal land loss including the U.S. Army Corps of Engineers (USACE) and the oil and gas industry. The role of natural processes and the multiple causality of the coastal land loss problem often have been overlooked (Boesch et al., 1994). In an effort to further our understanding and knowledge of the coastal land loss problem in Louisiana, the Gas Research Institute (GRI) sponsored a research project through the Argonne National Laboratory (ANL) entitled Natural and Human Causes of Coastal Land Loss in in cooperation with the U.S. Geological Survey (USGS). The study team consisted of scientists from GRI, ANL, Louisiana State University (LSU), University of New Orleans (UNO), USGS, USACE, and the Louisiana Universities Marine Consortium (LUMCON). This study focused on three major land loss research tasks: 1.) Geologic Processes, 2.) Vegetative processes, and 3.) Spatial Geographical Information System (GIS) Analysis. Through these research tasks, the objectives of this study are to quantify and rank the causes of coastal land loss within the Mississippi River delta plain in southeastern Louisiana. This study took advantage of continuing research by the USGS in framework geology and subsidence processes, and the USACE in GIS analysis, framework geology, and subsidence processes (Dunbar et al., 1990, Dunbar et al., 1992, Britsch and Dunbar, 1993; Williams et al., 1993). The geological processes task focused on the Holocene evolution of the Mississippi River delta plain in an effort to identify the regional geological controls on coastal land loss over the last 18,000 years. The vegetative processes task conducted field investigations into the role of salt-water intrusion and soil inundation in plant dieback. The GIS analysis task focused on quantifying the geomorphic forms and processes of coastal land loss using the USACE coastal land loss database. In this report, the results of the GIS geomorphic classification of coastal land loss are presented.

Local and regional flood frequency analysis based on hierarchical Bayesian model in Dongting Lake Basin, China

A geographical information system (GIS) was used to develop a regression model designed to predict flood magnitudes in the Sandy and Clackamas river basins in Oregon. Manual methods of data assembly, input, storage, manipulation and analysis traditionally used to estimate basin characteristics were replaced with automated techniques using GIS-based computer hardware and software components. Separate GIS data layers representing (1) stream gage locations, (2) drainage basin boundaries, (3) hydrography, (4) water bodies, (5) precipitation, (6) landuse/land cover, (7) elevation and (8) soils were created and stored in a GIS data base. Several GIS computer programs were written to automate the spatial analysis process needed in the estimation of basin characteristic values using the various GIS data layers. Twelve basin characteristic data parameters were computed and used as independent variables in the regression model. Streamflow data from 19 gaged sites in the Sandy and Clackamas basins were used in a log Pearson Type III analysis to define flood magnitudes at 2-, 5-, 10-, 25-, 50- and 100-year recurrence intervals. Flood magnitudes were used as dependent variables and regressed against different sets of basin characteristics (independent variables) to determine the most significant independent variables used to explain peak discharge. Drainage area, average annual precipitation and percent area above 5000 feet proved to be the most significant explanatory variables for defining peak discharge characteristics in the Sandy and Clackamas river basins. The study demonstrated that a GIS can be successfully applied in the development of basin characteristics for a flood frequency analysis and can achieve the same level of accuracy as manual methods. Use of GIS technology reduced the time and cost associated with manual methods and allowed for more in-depth development and calibration of the regression model. With the development of GIS data layers and the use of GIS-based computer programs to automate the calculation of explanatory variables, regression equations can be developed and applied more quickly and easily. GIS proved to be ideally suited for flood frequency modeling applications by providing advanced computerized techniques for spatial analysis and data base management.

This study evaluates the suitability of Geographic Information Systems ( GIS ) for analysing Roman communication routes. We will use the Itinerarium Antonini Augusti Route XIX between Lucus Augusti and Asturica Augusta , as a case study. It questions the effectiveness of GIS in reconstructing historical road networks and proposes a methodology to address observed challenges. Applying this methodology reveals new issues and errors, highlighting limitations inherent in GIS tools and the available data. These findings emphasise the complexity of studying historical landscapes and the importance of integrating GIS with interdisciplinary methods. The research contributes to understanding Route XIX , while encouraging critical reflection on GIS ’s broader application in historical studies. Although GIS offers powerful spatial modelling and visualisation tools, its use for studying ancient roadways requires caution and methodological support. The study identifies its constraints as opportunities for refining GIS integration into historical landscape analysis and Roman route studies, fostering further research and critical evaluations.

Extremely great floods are among environmental events with the most disastrous consequences for the entire world. Estimates of their return periods and design values are of great importance in hydrologic modeling, engineering practice for water resources and reservoirs design and management, planning for weather-related emergencies, etc. Regional flood frequency analysis resolves the problem of estimating the extreme flood events for catchments having short data records or ungauged catchments. This paper analyzes annual maximum peak flood discharge data recorded from more than 50 stream flow gauging sites in Sicily, Italy, in order to derive regional flood frequency curves. First these data are analyzed to point out some problems concerning the homogeneity of the single time series. On the basis of the L-moments and using cluster analysis techniques, the entire region is subdivided in five subregions whose homogeneity is tested using the L-moments based heterogeneity measure. Comparative regional flood frequency analysis studies are carried out employing the L-moments based commonly used frequency distributions. Based on the L-moment ratio diagram and other statistic criteria, generalized extreme value (GEV) distribution is identified as the robust distribution for the study area. Regional flood frequency relationships are developed to estimate floods at various return periods for gauged and ungauged catchments in different subregions of the Sicily. These relationships have been implemented using the L-moment based GEV distribution and a regional relation between mean annual peak flood and some geomorphologic and climatic parameters of catchments.

This paper investigates the possibility of applying light detection and ranging (LiDAR) point clouds and geographic information system (GIS) analyses for land use and land cover (LULC) change detection, mainly with a view to monitoring uncontrolled forest succession occurring on postagricultural lands. The research was conducted in a part of the administrative district of Milicz (in the central-west area of Poland). The areas of interest were parcels in which agricultural use has been abandoned and forest succession processes have progressed. The airborne laser scanning (ALS) data (acquired in 2007, 2012, and 2015) revealed detailed changes in land cover as a result of the progression in the forest succession process. Using the ALS data, the LULC changes and the progress of secondary forest succession are shown, and the vegetation parameters (LiDAR metrics) are presented.

This article identifies marginal land technically available for the production of energy crops in China, compares three models of yield prediction forMiscanthus × giganteus,Panicum virgatumL.(switchgrass), andJatropha, and estimates their spatially specific yields and technical potential for 2017. Geographic Information System (GIS) analysis of land use maps estimated that 185 Mha of marginal land was technically available for energy crops in China without using areas currently used for food production. Modeled yields were projected forMiscanthus × giganteus, a GIS‐based Environmental Policy Integrated Climate model for switchgrass and Global Agro‐Ecological Zone model forJatropha. GIS analysis and MiscanFor estimated more than 120 Mha marginal land was technically available forMiscanthuswith a total potential of 1,761 dry weight metric million tonne (DW Mt)/year. A total of 284 DW Mt/year of switchgrass could be obtained from 30 Mha marginal land, with an average yield of 9.5 DW t ha−1 year−1. More than 35 Mha marginal land was technically available forJatropha, delivering 9.7 Mt/year ofJatrophaseed. The total technical potential from available marginal land was calculated as 31.7 EJ/year forMiscanthus, 5.1 EJ/year for switchgrass, and 0.13 EJ/year forJatropha. A total technical bioenergy potential of 34.4 EJ/year was calculated by identifying best suited crop for each 1 km2grid cell based on the highest energy value among the three crops. The results indicate that the technical potential per hectare ofJatrophais unable to compete with that of the other two crops in each grid cell. This modeling study provides planners with spatial overviews that demonstrate the potential of these crops and where biomass production could be potentially distributed in China which needs field trials to test model assumptions and build experience necessary to translate into practicality.

Geographic information systems (GIS) analysis has not been widely used in underdeveloped countries to ensure that vulnerable populations have accessibility to primary health-care services. This study applied GIS methods to analyse the spatial accessibility to urban primary-care centres of the population in Kermanshah city, Islamic Republic of Iran, by age and sex groups. In a descriptive-analytical study over 3 time periods, network analysis, mean centre and standard distance methods were applied using ArcGIS 9.3. The analysis was based on a standard radius of 750 m distance from health centres, walking speed of 1 m/s and desired access time to health centres of 12.5 mins. The proportion of the population with inadequate geographical access to health centres rose from 47.3% in 1997 to 58.4% in 2012. The mean centre and standard distance mapping showed that the spatial distribution of health centres in Kermanshah needed to be adjusted to changes in population distribution.

Hurricane Harvey was an unprecedented event that resulted in immense damage to life and property. As a result, it is important to determine how this event, as well as past and future events like it, will impact engineering design equations that are based upon historical data, such as flood frequency analysis equations. This study seeks to contribute to this discussion by evaluating the extent to which Harvey influenced estimations of instantaneous peak discharges in rural ungauged basins in southeast Texas. Results indicate that Harvey significantly increased the computations of design floods using Log‐Pearson Type III analysis (e.g., 3–55% for 2‐year flood and 3–80% for the 100‐year flood). This subsequently impacted the estimation of instantaneous peak discharges through regional flood frequency analysis by up to 28%. These results highlight the influence that recent and future hurricanes can have on engineering design equations that are used for managing floodplains, assessing flood risk, and designing infrastructure such as levees, bridges, and culverts.