Classification and assessment of water bodies as adaptive structural measures for flood risk management planning

Severe rainfall events have become increasingly common in Europe. Flood defence engineering works are highly capital intensive and can be limited by land availability, leaving land and communities exposed to repeated flooding. Any adaptive drainage structure must have engineered inlets and outlets that control the water level and the rate of release. In Scotland, there are a relatively high number of drinking water reservoirs (operated by Scottish Water), which fall within this defined category and could contribute to flood management control. Reducing the rate of runoff from the upper reaches of a catchment will reduce the volume and peak flows of flood events downstream, thus allowing flood defences to be reduced in size, decreasing the corresponding capital costs. A database of retention basins with flood control potential has been developed for Scotland. The research shows that the majority of small and former drinking water reservoirs are kept full and their spillways are continuously in operation. Utilising some of the available capacity to contribute to flood control could reduce the costs of complying with the EU Flood Directive. Furthermore, the application of a previously developed classification model for Baden in Germany for the Scottish data set showed a lower diversity for basins in Scotland due to less developed infrastructure. The principle value of this approach is a clear and unambiguous categorisation, based on standard variables, which can help to promote communication and understanding between stakeholders.     

PROBABLE MAXIMUM FLOOD ESTIMATION-EASTERN UNITED STATES1

In 1982, the National Weather Service (NWS) published criteria for developing the spatial and temporal precipitation distribution characteristics of Probable Maximum Storms. The criteria, which are intended for use in the United States east of the 105th meridian, involve four variables: (1) location of the storm center, (2) storm-area size, (3) storm orientation, and (4) temporal arrangement of precipitation amounts. A computer program has been developed which applies the NWS criteria to produce hyetographs of spatially-averaged precipitation for a basin, or for each subbasin if the basin is subdividided. The basis and operational characteristics of the program are described, and an application is illustrated in which the program is used in conjunction with a precipitation-runoff simulation program (HEC-1) to compute a Probable Maximum Flood.     

WATERSHED CLASSIFICATION USING CANONICAL CORRESPONDENCE ANALYSIS AND CLUSTERING TECHNIQUES: A CAUTIONARY NOTE1

ABSTRACT: Watershed classification using multivariate techniques requires the incorporation of continuous datasets representing controlling environmental variables. Often, out of convenience and availability rather than importance to the structure of the system being modeled, the environmental data used originate from a variety of sources and scales. To demonstrate the importance of appropriate environmental data selection, classifications of six‐digit hydrologic units (1:24,000) across selected geographic areas within the Interior Columbia River Basin were produced. Canonical correspondence analysis was used to select and test environmental variables important in predicting Rosgen stream types and valley bottom classes. Then, hierarchical agglomerative clustering was used to group (classify) watersheds based on these variables. Statistically significant results were derived from the use of organized classification data with presumed predictive relationships to watershed properties, and a random distribution of environmental variables from the same datasets provided similar results. The results contained herein demonstrate that these analysis techniques do not necessarily select meaningful variables from a broad spectrum of data and that significant results are easily generated from randomly associated data. It is suggested that classifications produced using these multivariate techniques, especially when using multi‐scale data or data of unknown significance, are subject to invalid inferences and should be used with caution.     

Simulated interior floods and the flood experience in urban communities

The Hydrologic Engineering Center (HEC-1) model was used to construct synthetic hydrographs for isolated interior urban floods. Flood peak and lag time were very well preserved in simulated flows. Total volume was not adequately expressed. Lag time varied inversely with both urban development and storm intensity. Peak discharge varied with storm intensity, but this variability was well defined only at very high urbanization levels. An 175% increase in storm intensity produced a change of about 15% in peak discharge. Claims for flood damage correlated well with estimates of peak flow and lag time combined. Other measures of flood experience also correlated with the two features. Within the range of storms utilized, urban development factors consistently outranked storm intensity as a determining factor in flood damage.     

Multivariate Analysis of the Ecoregion Delineation for Aquatic Systems

The ecoregion concept is a popular method of understanding the spatial distribution of the environment', however, it has yet to be adequately demonstrated that the environment is distributed in accordance with these bounded units. In this paper, we generated a testable hypothesis based on the current usage of ecoregions: the ecoregion classification will allow for discrimination between lakes of different water quality. The ecoregion classification should also be more effective better than a comparably scaled classification based on political boundaries, land-use class, or random grouping. To test this hypothesis we used the Environmental Monitoring and Assessment Program (EMAP) lake water chemistry data from the northeast United States. The water chemistry data were reduced to four components using principal component analysis. For comparison to an optimal grouping of these data we used K-means cluster analysis to define the extent at which these lakes could be segregated into distinct classes. Jackknifed discriminant analysis was used to determine the classification rate of ecoregions, the three alternative spatial classification methods, and the clustering algorithm. The classification based on ecoregions was successful for 35% of the lakes included in this study, in comparison to the clustered groups accuracy of 98%. These results suggest that the large scale spatial distribution of ecosystem types is more complicated than that suggested by the present ecoregion boundaries. Further tests of ecoregion delineations are needed and alternative large-scale management strategies should be investigated.     

Effect of Classification Procedure on the Performance of Numerically Defined Ecological Regions

Ecological regionalizations define geographic regions exhibiting relative homogeneity in ecological (i.e., environmental and biotic) characteristics. Multivariate clustering methods have been used to define ecological regions based on subjectively chosen environmental variables. We developed and tested three procedures for defining ecological regions based on spatial modeling of a multivariate target pattern that is represented by compositional dissimilarities between locations (e.g., taxonomic dissimilarities). The procedures use a “training dataset” representing the target pattern and models this as a function of environmental variables. The model is then extrapolated to the entire domain of interest. Environmental data for our analysis were drawn from a 400 m grid covering all of Switzerland and consisted of 12 variables describing climate, topography and lithology. Our target patterns comprised land cover composition of each grid cell that was derived from interpretation of aerial photographs. For Regionalization 1 we used conventional cluster analysis of the environmental variables to define 60 hierarchically organized levels comprising from 5 to 300 regions. Regionalization 1 provided a base-case for comparison with the model-based regionalizations. Regionalization 2, 3 and 4 also comprised 60 hierarchically organized levels and were derived by modeling land cover composition for 4000 randomly selected “training” cells. Regionalization 2 was based on cluster analysis of environmental variables that were transformed based on a Generalized Dissimilarity Model (GDM). Regionalization 3 and 4 were defined by clustering the training cells based on their land cover composition followed by predictive modeling of the distribution of the land cover clusters using Classification and Regression Tree (CART) and Random Forest (RF) models. Independent test data (i.e. not used to train the models) were used to test the discrimination of land cover composition at all hierarchical levels of the regionalizations using the classification strength (CS) statistic. CS for all the model-based regionalizations was significantly higher than for Regionalization 1. Regionalization 3 and 4 performed significantly better than Regionalization 2 at finer hierarchical levels (many regions) and Regionalization 4 performed significantly better than Regionalization 3 for coarse levels of detail (few regions). Compositional modeling can significantly increase the performance of numerically defined ecological regionalizations. CART and RF-based models appear to produce stronger regionalizations because discriminating variables are able to change at each hierarchic level.     

STRATIFICATION OF VARIABILITY IN RUNOFF AND SEDIMENT YIELD BASED ON VEGETATION CHARACTERISTICS1

ABSTRACT: Runoff and sediment yield were collected from 100 plots during simulated rainfalls (100 mm/hr for 15 minutes) at antecedent soil moisture conditions. A clustering technique was used to stratify the variability of a single data set within a sagebrush‐grass community into four groups based on vegetation life form and amount of cover. The four cluster groups were grass, grass/shrub, shrub, and forb/grass and were found to be significantly different in plant height, surface roughness, soil bulk density, and soil organic matter. Stepwise multiple regression analyses were performed on the single data set and each cluster group. Results for individual groups resulted in more robust predictive equations for runoff (r²= 0.65–0.73) and sediment yield (r²= 0.37–0.91) than for equations developed from the single data set (r²= 0.56 for runoff and r²= 0.27 for sediment yield). The standard errors of the cluster group regression equations were also improved in three of the four group equations for both runoff and sediment yield compared to the single data set. Runoff was found to be significantly less (p >0.01) in the forb/grass group compared with other vegetation cluster groups, but this was influenced by four plots that produced little or no runoff. Sediment yield was not found to be significantly different among any cluster groups. Discriminant analysis was then used to identify important variables and develop a model to classify plots into one of the four cluster groups. The discriminant model could be incorporated into rangeland hydrology and erosion models. The percentage cover of grasses, shrubs, litter, and bare ground effectively stratified about 12 percent of the variation observed in runoff and 26 percent of the variability for sediment yield as determined by r².     

Women's Awareness of and Attitudes Towards the Flood Action Plan (FAP) of Bangladesh: A Comparative Study

/ Bangladesh has recently tested a program called the Flood Action Plan (FAP) to solve its chronic flood problem. The FAP envisages that all the major rivers of Bangladesh will eventually be embanked on both sides in order to prevent flooding. This paper reports on the responses of rural women to the possible impacts of the proposed embankment projects as outlined in the FAP. A further attempt is also made to compare their responses with the results of an earlier survey conducted among male respondents. Data for this study were collected from two rural areas of Bangladesh. It shows that almost all respondents had heard about the proposed construction and that they overwhelmingly support the embankment project of the FAP. Respondents are also aware of both positive and negative impacts of embankment construction. Similar findings were also reported by a previous study dealing with male responses to the embankment project. KEY WORDS: Flood Action Plan; Bangladesh; Women     

COMPARING METHODS OF HYDROLOGIC REGIONALIZATION1

ABSTRACT: Data splitting is used to compare methods of determining “homogeneous” hydrologic regions. The methods compared use cluster analysis based on similarity of hydrologic characteristics or similarity of characteristics of a stream's drainage basin. Data for 221 stations in Arizona are used to show that the methods, which are a modification of DeCoursey's scheme for defining regions, improve the fit of estimation data to the model, but that is is necessary to have an independent measure of predictive accuracy, such as that provided by data splitting, to demonstrate improved predictive accuracy. The methods used the complete linkage algorithm for cluster analysis and computed weighted average estimates of hydrologic characteristics at ungaged sites.     

The dilemma of flood control in the United States

In spite of increasing annual expenditures for flood control, losses from flooding continue to rise in the United States. This seeming contradiction arises from overdependence on federally supported structural solutions to flood problems. Nonstructural controls are initiated reluctantly at local levels of government because of constitutional questions, restrictions of local tax bases, lack of federal subsidies for nonstructural solutions, and the high costs of delineating flood hazard areas. The success of the National Flood Insurance Program is doubtful since only about five percent of the flood-prone communities in the United States have qualified for the regular program. Future reduction of flood losses is dependent upon increasing popular awareness of flood hazards and altering federal subsidy policies to reduce the impact of local land-use regulations.     

Hydrological classification of natural flow regimes to support environmental flow assessments in intensively regulated Mediterranean rivers, Segura River Basin (Spain)

Hydrological classification constitutes the first step of a new holistic framework for developing regional environmental flow criteria: the “Ecological Limits of Hydrologic Alteration (ELOHA)”. The aim of this study was to develop a classification for 390 stream sections of the Segura River Basin based on 73 hydrological indices that characterize their natural flow regimes. The hydrological indices were calculated with 25 years of natural monthly flows (1980/81–2005/06) derived from a rainfall-runoff model developed by the Spanish Ministry of Environment and Public Works. These indices included, at a monthly or annual basis, measures of duration of droughts and central tendency and dispersion of flow magnitude (average, low and high flow conditions). Principal Component Analysis (PCA) indicated high redundancy among most hydrological indices, as well as two gradients: flow magnitude for mainstream rivers and temporal variability for tributary streams. A classification with eight flow-regime classes was chosen as the most easily interpretable in the Segura River Basin, which was supported by ANOSIM analyses. These classes can be simplified in 4 broader groups, with different seasonal discharge pattern: large rivers, perennial stable streams, perennial seasonal streams and intermittent and ephemeral streams. They showed a high degree of spatial cohesion, following a gradient associated with climatic aridity from NW to SE, and were well defined in terms of the fundamental variables in Mediterranean streams: magnitude and temporal variability of flows. Therefore, this classification is a fundamental tool to support water management and planning in the Segura River Basin. Future research will allow us to study the flow alteration-ecological response relationship for each river type, and set the basis to design scientifically credible environmental flows following the ELOHA framework.     

RESEARCH: Issues Related to Greenhouse Effect,Productivity Modeling,and Nutrient Cycling: A Case Study of Indian Wetlands

/ Models available in the literature on nutrient uptake, lightavailability, and chlorophyll growth have been suitably modified andintegrated through the computer program CHLORF (written in "C"language), which has the advantage of being amenable to simulation undervarious combinations of input variables. The model has been used forsensitivity analysis in order to identify the most sensitive set ofparameters whose control can form an appropriate basis for evolving pragmaticmanagement strategies. In addition, greenhouse mitigation potential has beencomputed in terms of assimilation of carbon dioxide for a case study ofIndian wetlands.KEY WORDS: Wetland; Nutrient cycling; Modeling; Greenhouse effect     

聚类分析及其在土地利用分类中的应用

本文通过探讨聚类分析的模式相似性测度,计算方法和步骤,结合土地利用的实际,提出了分类指标,并给出了土地利用聚类分析的计算方法和步骤。     

DEVELOPMENT OF A FRACTURED MEDIUM FLOW MODEL FOR A WASTE SITE1

ABSTRACT: A three‐dimensional fractured medium flow model was developed for the Bear Creek Valley (BCV) S‐3 site of the Oak Ridge Reservation (ORR) using SWIFT III. The numerical modeling for this site focused on a conceptual model established through the analysis of heterogeneous geologic units and matrix fracture properties of the subsurface in the BCV area. The SWIFT III modeling analysis was based on the previous modeling studies that used MODFLOW and MODPATH. A rigorous calibration was obtained first by comparing simulated results with the existing data on ground water levels and then by comparing pumping test results with the simulated ground water levels. A satisfactory agreement between observed and simulated results was obtained. The calibrated model was used to determine sustained yield from a ground water interceptor trench. Different withdrawal rates were used to simulate the performance of the trench for the sustained withdrawal of ground water.     

Mapping Outlets of Iowa Flood Center and National Water Center River Networks for Hydrologic Model Comparison

River networks based on Digital Elevation Model (DEM) data differ depending on the DEM resolution, accuracy, and algorithms used for network extraction. As spatial scale increases, the differences diminish. This study explores methods that identify the scale where networks obtained by different methods agree within some margin of error. The problem is relevant for comparing hydrologic models built around the two networks. An example is the need to compare streamflow prediction from the Hillslope Link Model (HLM) operated by the Iowa Flood Center (IFC) and the National Water Model (NWM) operated by the National Water Center of the National Oceanic and Atmospheric Administration. The HLM uses landscape decomposition into hillslopes and channel links while the NWM uses the NHDPlus dataset as its basic spatial support. While the HLM resolves the scale of the NHDPlus, the outlets of the latter do not necessarily correspond to the nodes of the HLM model. The authors evaluated two methods to map the outlets of NHDPlus to outlets on the IFC network. The methods compare the upstream areas of the channels and their spatial location. Both methods displayed similar performance and identified matches for about 80% of the outlets with a tolerance of 10% in errors in the upstream area. As the aggregation scale increases, the number of matches also increases. At the scale of 100 km², 90% of the outlets have matches with tolerance of 5%. The authors recommend this scale for comparing the HLM and NWM streamflow predictions.     

A LANDSCAPE‐BASED APPROACH TO ESTIMATE RIPARIAN HYDROLOGICAL AND NITRATE REMOVAL FUNCTIONS1

ABSTRACT: This study evaluates a conceptual model developed for riparian zones in Ontario, Canada, that links landscape hydrogeological characteristics to riparian ground water hydrology and nitrate removal efficiency. Data from a range of riparian sites in the United States and Europe suggest that the riparian zone types identified in the model are consistent with patterns of riparian hydrology and nitrate flux and removal in many humid temperate landscapes. These data also support the view that a riparian width of less than 20 m is often sufficient for effective nitrate removal unless riparian sediments are coarse grained or nitrate transport occurs mainly in surface‐fed ground water seeps. This study assesses the possibility of using topographic, soil, surficial geology, and vegetation maps to determine landscape attributes linked by the model to riparian zone hydrological functioning and nitrate removal efficiency. Although mappable data can help in determining broad classes of riparian zones, field visits are necessary to determine non‐mappable riparian attributes such as seeps, organic horizons, and permeable sediment depth in the riparian zone. This research suggests that the conceptual model could be used for landscape management purposes in most temperate landscapes with minor modifications and that the hydrological component of the model could be adapted for contaminants other than nitrate.     

Conceptual Framework for the National Flood Interoperability Experiment

The National Flood Interoperability Experiment is a research collaboration among academia, National Oceanic and Atmospheric Administration National Weather Service, and government and commercial partners to advance the application of the National Water Model for flood forecasting. In preparation for a Summer Institute at the National Water Center in June‐July 2015, a demonstration version of a near real‐time, high spatial resolution flood forecasting model was developed for the continental United States. The river and stream network was divided into 2.7 million reaches using the National Hydrography Dataset Plus geospatial dataset and it was demonstrated that the runoff into these stream reaches and the discharge within them could be computed in 10 min at the Texas Advanced Computing Center. This study presents a conceptual framework to connect information from high‐resolution flood forecasting with real‐time observations and flood inundation mapping and planning for local flood emergency response.     

A Quantitative Method for Delineating Regions: An Example for the Western Corn Belt Plains Ecoregion of the USA

/ A method was developed to systematically delineate boundaries forecological classification of regions. The process entailed the use ofsmall-scale digital data to quantify spatial concordance among environmentalattribute data sets. The data sets were grouped into spatially related themesusing cluster analysis and multidimensional scaling. Selected data sets werethen used either individually or collectively to divide the study area intosubregions that exhibited different environmental attributes. The method wasapplied to a previously defined ecological unit, the western Corn Belt of thecentral United States. The results showed that the portion of the study areawith intensive corn and soybean production was identifiable using each of thethree input data sets selected for partitioning (soil associations; AVHRRremote-sensing imagery; and a combined data set of landform, forest, andsoils data). The classification of other portions of the study area washighly dependent on the type and scale of the input data. The systematicmethodology used here offers advantages over other methods for identifyingecological regions in that the results from the systematic approach can bereproduced, the boundaries between ecological units can be revised based onnew or more accurate data, important ecological processes are explicitlychosen to delineate boundaries, and transition zones between regions can bequantified.KEY WORDS: Ecoregions; Spatial analysis; Corn Belt; Iowa; GIS;Regionalization     

URBAN SERVICE PRICING AND LAND USE: SOME PRELIMINARY RESULTS1

ABSTRACT The use of public policy variables to control urban land use has been suggested or implied by a number of authors. This paper presents a conceptual foundation for doing so and the results of some empirical analyses based on this conceptual foundation. The method developed appears to constitute an alternative to more expensive approaches to the analysis of the relation between policy variables and land use. The empirical results tend to support earlier suggestions advanced by other researchers.     

A RECOMMENDED BASIC FORMAT FOR THE CLASSIFICATION OF INTERNATIONAL DATA ON CRUDE OIL AND NATURAL GAS RESERVES AND RESOURCES

Effective assessment of nonrenewable resources depends on both the availability and the interpretation of basic data. The quality of these data directly affects resource policy decisions based on them. It is vital to bring information on reserves and resources into sharper focus, by clearer definition of what has been measured, by orderly classification and by identification of the results of assessment in a way that stimulates their proper understanding and application. As part of the overall programme of the United Nations Centre for Natural Resources, Energy and Transport in the field of natural resources, an Expert Group was convened in New York from 28 March to 4 April to discuss a series of such basic questions concerning the international classification and measurement of crude oil and natural gas resources. Key conceptual principles and definitions were agreed as a basic framework within which governments could work towards an internally consistent and comprehensive international exchange of information. The Group also examined problems of measurement and the manner in which existing national data would be incorporated into an international classification. The report of the Group is reproduced in full below.