Spatial pattern analysis of fire events in Central India – A case study

The impact of fires on environment can have adverse effects. To fully understand the synoptic behaviour of fire events, information on the spatial distributions and their pattern are highly important. In this study, we used 9-year (1997–2005) integrated fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to geographically map the distribution of fire events in the Madhya Pradesh state, central India. We then used robust spatial metrics to test the spatial pattern of fire events against the hypothesis of complete spatial randomness (CSR). Specifically, we used the index of dispersion, Green's index, in addition to nearest neighbour statistic for testing CSR. Also, quantification of clustering is carried out using Ripley's K-function. To spatially map the fire events, we used Kernel density estimation that relies on bi-variate probability density functions. Results from using different spatial pattern metrics and nearest neighbour statistics suggested relatively high clustering of fire events in the study area. In addition, results from Ripley's K-function suggested the fire events to be clustered at a lag-distance of ～60 mile radius. By converting original fire ignition locations that are based on historical records to continuous density surfaces, the probability of fire events could be mapped effectively using kernel density estimation. As each fire event is the result of certain spatial process including biophysical and anthropogenic attributes, results from this study can provide useful information on fire management at a local district level. Also, the analysis presented in this study illustrates how spatial patterns in the point datasets can be quantified using different dispersion indices, clustering and density estimation techniques.     

Empirical statistical characterization and regionalization of amplitude–duration–frequency curves for extreme peak flows in the Lake Victoria Basin,East Africa

Abstract

This paper focuses on a regionalization attempt to partly solve data limitation problems in statistical analysis of high flows to derive discharge–duration–frequency (QDF) relationships. The analysis is based on 24 selected catchments in the Lake Victoria Basin (LVB) in East Africa. Characteristics of the theoretical QDF relationships were parameterized to capture their slopes of extreme value distributions (evd), tail behaviour and scaling measures. To enable QDF estimates to be obtained for ungauged catchments, interdependence relationships between the QDF parameters were identified, and regional regression models were developed to explain the regional difference in these parameters from physiographic characteristics. In validation of the regression models, from the lowest (5 years) to the highest (25 years) return periods considered, the percentage bias in the QDF estimates ranged from –2% for the 5-year return period to 27% for 25-year return period.

Editor D. Koutsoyiannis     

Discharge variability in Romania using Palmer indices and a simple atmospheric index of large-scale circulation

ABSTRACT

The aim of this study is to analyse the seasonal characteristics of four Palmer indices calculated on the basis of data from 27 meteorological stations in Romania, and the impact of these indices on river discharges in the period 1931–1998. Our research also tests the influence of large-scale atmospheric circulation on these indices and on discharge. For each season, developments in the empirical orthogonal functions (EOF) and multivariate EOF (MEOF) are achieved. The MEOF representation highlights the overall characteristics of the four Palmer indices. It maximizes specific information for each season compared with individual information of each Palmer index. We then identify geographical areas with homogeneous distribution, taking into account both the discharge distribution and the rotated EOF components of each Palmer index. Finally, we analysed the impact of large-scale atmospheric circulation on hydro-climatic events in Romania by means of the Greenland-Balkan Oscillation Index (GBOI), which is shown to have a greater influence on southeastern Europe than the North Atlantic Oscillation Index (NAOI).     

Assessment of severity of the extreme River Tyne flood in January 2005 using gauged and historical information

Abstract

The extreme Tyne (Northumbria, UK) flood in January 2005 provided the opportunity to reassess flood risk and to link peak discharge and flooded area to probability of occurrence. However, in spite of the UK guidance on flood risk assessment given in the Flood Estimation Handbook (FEH), there is still considerable subjectivity in deriving risk estimates. A particular problem for the Tyne arises from the effects of river bed gravel extraction both on the reliability of gauged discharges and in the interpretation of historical level data. In addition, attenuation and drawdown of Kielder Water has reduced downstream flood risk since 1982. Estimates from single-site, pooled estimates and historical information are compared. It is concluded that the return period of the observed flood was around 71 years on the lower Tyne and was probably the largest flood since 1815.     

Trivariate generalized extreme value distribution in flood frequency analysis

Abstract

The multivariate extension of the logistic model with generalized extreme value (GEV) marginals is applied to provide a regional at-site flood estimate. The maximum likelihood estimators of the parameters were obtained numerically by using a multivariable constrained optimization algorithm. The asymptotic results were checked by distribution sampling techniques in order to establish whether or not those results can be utilized for small samples. A region in northern Mexico with 21 gauging stations was selected to apply the model. Results were compared with those obtained by the most popular univariate distributions, the bivariate approach of the logistic model and three regional methods: station-year, index flood and L-moments. These show that there is a reduction in the standard error of fit when estimating the parameters of the marginal distribution with the trivariate distribution instead of its univariate and bivariate counterpart, and differences between at-site and regional at-site design events can be significant as return period increases.     

Environmental and land use factors affecting phosphate hysteresis patterns of stream water during flood events (Carpathian Foothills,Poland)

Flood events play a substantial role in the circulation of catchment phosphate (PO₄^3?). The purpose of the research was to analyze the factors determining PO₄^3? hysteresis patterns (direction and width) during four types of floods: short and long rainfall floods and snowmelt floods on frozen and thawed soil. The research took place in small catchments (forested, agricultural, mixed‐use) in the Carpathian Foothills in Poland. Anticlockwise hysteresis was identified in the forested catchment during short and long rainfall floods. Under the same conditions, the clockwise direction was observed in the agricultural catchment. In the mixed‐use catchment, the direction of PO₄^3? hysteresis loops was various, driven by the share of water flowing from each part of the catchment. For snowmelt floods, the PO₄^3? hysteresis pattern was similar in all the streams studied (usually clockwise). The direction of PO₄^3? hysteresis loops depends on water circulation patterns, which are determined by the different influx times of particular runoff components. The stream recharge mechanism during a flood event is affected both by the factor initiating the event (precipitation, snowmelt) as well as by land use in the given catchment. Hysteresis loop width was determined by the pool of PO₄^3? in a given catchment during the time period immediately preceding a flood event as well as by the quantity of PO₄^3? flushed out of the soil. The greater a catchment's pool of PO₄^3? and the greater its ability to flush PO₄^3? out of the soil and into surface flow, the wider the hysteresis loops. Copyright © 2012 John Wiley & Sons, Ltd.     

Empirical models of rain-spells characteristics – A case study of a Mediterranean-arid climatic transect

Environmental (geomorphological, hydrological and ecological) processes are controlled by rainfall, particularly in the Mediterranean, semi-arid and arid regions. Rainfall was analyzed using the concept of rain-spells, i.e., a period of successive rain days preceded and followed by at least one day without rainfall. Daily data from 13 stations along a climatic transect extending from the Judean Mountains with a Mediterranean climate to the Dead Sea arid region in Israel were studied. Rain-spell characteristics (number, yield and duration), based on these data, are presented for different rainfall thresholds, which might be used for different environmental processes such as rock weathering, soil organic matter dynamics, landslides, overland flow and floods and soil erosion. Three estimation models have been developed in order to predict the mean annual Number of Rain-Spells (NRS), mean Rain-Spell Yield (RSY), and mean Rain-Spell Duration (RSD) for the mean annual rainfall and for any given rainfall threshold. These models can be used for current climatic conditions and for scenarios in which the rainfall total changes.     

Extreme Temperature Days in Hong Kong

Extreme temperature days for the period from 1947 to 1998 in Hong Kong were investigated. Significant decreasing trends of both warm and cold days were discovered. Warm days were more variable than cold days. It is found that extreme days were less persistent in the last decade. In winter, cold days were related to the intensified Siberian anticyclone bringing a cold, polar air mass and Northeast monsoon to south China, while zonal flow would create more frequent warm days. In summer, apart from the influence of tropical cyclones to the east or southeast of Hong Kong, the effect of strong and persistent southerly flow was another prominent factor producing extreme temperature days.     

Post‐Late Paleozoic Collisional Framework of Southern Great Altai

We outline the post-Late Paleozoic (latest Permian to Cenozoic) collisional framework of the southern Great Altai (Central Asia) produced by the convergence between the Tuva-Mongolia and Junggar continental terranes (microplates). The collisional structures in the region classified on the basis of their geometry and deformation style, dynamic metamorphism, and compositions of tectonites are of three main types: (1) mosaic terranes made up of large weakly deformed Paleozoic blocks separated by younger shear zones; (2) contractional deformation systems involving structures formed in post-Late Paleozoic time, parallel faults oriented along collisional deformation systems, and relict lenses of Paleozoic orogenic complexes; and (3) isolated zones of dynamic metamorphism composed mostly of collisional tectonites different in composition and alteration grade.     

Comparison of daily streamflow forecasts using extreme learning machines and the random forest method

ABSTRACT

Daily streamflow forecasting is a challenging and essential task for water resource management. The main goal of this study was to compare the accuracy of five data-driven models: extreme learning machine (basic ELM), extreme learning machine with kernels (ELM-kernel), random forest (RF), back-propagation neural network (BPNN) and support vector machine (SVR). The results show that the ELM-kernel model provided a superior alternative to the other models, and the basic ELM model had the poorest performance. To further evaluate the predictive capacities of the five models, the estimations of low flow and high flow in the testing dataset were compared. The RF model was slightly superior to the other models in predicting the peak flows, and the ELM-kernel model showed the highest prediction precision of low flows. There was no single model that showed obvious advantages over the other models in this study. Therefore, further exploration is required for the hydrological forecasting problems.