Risk analysis for drought hazard in China: a case study in Huaibei Plain

In recent decades, risk management is significant to mitigate the severe status caused by droughts. As one of the primary components in risk analysis, drought hazard analysis is basic but important. In this paper, the framework of drought risk analysis and the methodology for drought hazard analysis are presented, and Huaibei Plain of China is chosen as the study area. The whole study region is divided into three parts (northern, central, and southern) by geographical factors, and a developed index named drought comprehensive Z index (DCZI) containing hydrological and meteorological factors is employed for drought hazard analysis in each area. By comparison, it implicates that DCZI is applicable for Huaibei Plain and indicates drought extent more objectively. Moreover, the results of drought hazard analysis reflect that the northern area is affected by droughts more seriously. As for the whole region, there is a great probability of severe drought. Finally, some policy recommendations on drought management are also made.     

Analyzing drought history using Fuzzy Integrated Drought Index (FIDI): a case study in the Neyshabour basin,Iran

In arid to semi-arid climates, monitoring drought is very complicated because of different hydrometeorology variables effect on it. It is proposed in this paper to develop Fuzzy Integrated Drought Index (FIDI) which combines most important effective factors in developing drought. At first, Variable Infiltration Capacity (VIC) model calibrated simulated runoff to outlet basin runoff data for years 1993–1995. Results represent high performance of model in simulating runoff of outlet basin. Then, Precipitation Anomaly Percentage Index (PAPI), actual Evapotranspiration Anomaly Percentage Index (EAPI), Runoff Anomaly Percentage Index (RAPI), and Soil Moisture Anomaly Percentage Index (SMAPI) were constructed. FIDI was compared with the PAPI, RAPI and SMAPI for the period of 1985 to 2014. The results indicate that (1) the FIDI has more ability in determining start and persistence of drought event compared with PAPI, RAPI, and SMAPI; (2) in the low time scales, PAPI and SMAPI have high correlation with FIDI, and in the higher time scales, RAPI has the high correlation with FIDI; (3) spatially, the middle, west, and portion of north have higher drought risk in the Neyshabour basin.     

Synoptic and remote sensing analysis of dust events in southwestern Iran

Southwest regions of Iran, due to dry environmental and climatic conditions, have been identified as one of the five major regions in the world. In recent years, large parts of Iran have been affected by suspended particles from the dust storms. The studied area is located in foothills of the Zagros Mountain Range just north of Persian Gulf in southwest of Iran. Dust and other meteorological data were prepared in 3-hour intervals from 12 synoptic weather stations. For tracking dust storms, satellite images of MODIS were used. Atmospheric conditions during the occurrence of dust storms were determined using NCEP reanalysis data. According to the statistical calculations, most storms occurred in the spring and summer. The lowest number of dust events occurred in the fall and winter particularly in December and January, when there are high possibilities of rainfall occurrence and dynamical instability conditions in the north and west of the region. The results illustrated that the highest amounts of hourly dust occurred in the afternoon and the lowest amounts occurred at 00UTC (3.30 am local times). It seems that it is closely related to the heating surface and the occurrence of local dry instabilities. Analyses of data showed that dust amounts (or volumes) in all the stations have two climactic peaks, first between 1982 and 1990 and second between 2005 and 2008 periods. These peaks can be related to a variety of factors including anthropogenic factors such as war, agricultural activities, dam construction, and widespread droughts.     

Spatiotemporal meteorological drought assessment: a case study in south-east Australia

Natural Hazards - An understanding on different aspects of droughts is crucial for effective water resources management. Australia has experienced notable droughts in recent years. The present...     

Investigating remote sensing indices to monitor drought impacts on a local scale (case study: Fars province,Iran)

As drought occurs in different climates, assessment of drought impacts on parameters such as vegetation cover is of utmost importance. Satellite remote sensing images with various spectral and spatial resolutions represent information about different land covers such as vegetation cover. Hence, the purpose of this study was to investigate the performance of satellite vegetation indices to monitor the agricultural drought on a local scale. In this regard, satellite images including Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) data were used to evaluate vegetation cover and their gradual changes effects on agricultural drought. Fars province in Iran with relatively low precipitation values was selected as the study area. Modified Perpendicular Drought Index (MPDI), MPDI1, Vegetation Condition Index (VCI), Normalized Difference Vegetation Index Anomalies (NDVIA), and Standardized Vegetation Index (SVI), were evaluated to select the remote sensing based index with the best performance in drought monitoring. The performance of such indices were investigated during 13 years (2000–2013) for MODIS and 29 years (1985–2013) for AVHRR. To assess the efficiency of the satellite indices in drought investigation, Standardized Precipitation Index (SPI) data of five selected stations were used for 3, 6, and 9 month periods on August. The results showed that NDVI-based vegetation indices had the highest correlation with SPI in cold climate and long-term timescale (6 and 9 month). The highest correlation values between remote sensing based indices and SPI were acquired, respectively, in 9-month and 6-month time-scales, with the values of 43.5% and 40%. Moreover, VCI showed the highest capability for agricultural drought investigating in different climate regions of the study area. Overall, the results proved that NDVI-based indices can be used for drought monitoring and assessment in a long-term timescale on a local time-scale.

     

Quantitative analysis of earthquake fatalities: case of Iran

Earthquakes in Iran are major and chronic disasters, but there is a seemingly downward trend in the number of lives lost from earthquake disasters in the past five decades. This paper particularly examines whether factors such as urbanization, literacy rate, wealth, and retrofitting measures have contributed to the declining trend of fatalities over past decades. Data records of 1960–2010 have been used to demonstrate the fatalities trend and a shorter series of 1990–2010 has been used to carry out a statistical analysis due to limited availability of information on retrofitting practices in the country. Regression models run in two stages. The first stage consists of normalized fatalities of Iran’s earthquakes, regressed on urbanization, wealth, and retrofitting. The second stage involves the measure of retrofit as the dependent variable regressed over urbanization and/or wealth as explanatory variables. The resulted regression models clearly explain the importance of retrofitting measure in saving lives in earthquakes disasters, as well as providing economic advantages and robust environment to the population. The study provides significant guidance for public policy. Undoubtedly, retrofitting, started in the country from 1990, has decreased the number of deaths; nonetheless, the measure is found to be mostly enforced in the cities and not in rural areas. Decision makers can use the results of this study to prioritize retrofit in rural areas, more than ever, and as much as possible.     

基于copula函数的区域干旱分析方法

提出不同网格干旱等级影响下的区域干旱指数。采用copula函数,建立了区域干旱历时和干旱强度的联合分布,计算联合分布的重现期,并对实际重现期作区间估计。所提出的区域干旱指数能够反映研究区域内发生干旱的严重程度和该区内不同干旱等级所影响面积的大小,且联合分布同时考虑了干旱历时和干旱强度,更全面地反映区域的干旱状况。重庆市2006年干旱实证分析表明,区域干旱指数能够较好地描述本次干旱的发生发展过程,并计算出联合分布的重现期为118年。     

Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China

A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows.     

The role of blocking system in heavy precipitation of Iran (a case study: southeast of Iran January 2008)

This article concerns the analysis of the heavy precipitation, which allows investigating the effect of the blocking system on the unusual precipitation and temperature occurrence in Iran. The days of January 2008 have been the coldest days during the history of recorded data in Iran. Variation of precipitation during January 2008 compared with long-term data (30 years) shows the maximum positive anomaly in the stations located in southeast of Iran. However, the precipitation in consecutive days, 14–15 and 15–16 of January, produce a more important proportion of the heavy precipitation in this region. In order to study the role of the blocking system related to heavy precipitation in January 2008, the position and movement of the atmospheric systems including cyclones, anticyclones, fronts, and wind fields have been analyzed by the use of synoptic maps by the environment to circulation approach. Consequently, the weather maps indicated that the blocking system over the north of the Caspian Sea has caused the relatively deep low trough on January 5, 7, 14, 15, and 16, 2008, while the thermal and moisture gradients in the warm section of air masses have produced heavy precipitation. As a result, wind field of low levels (850 hPa) provided remarkable moisture fed by the Arabian Sea, Oman Sea, and Persian Gulf in the study area. Furthermore, the speed of wavelength and the position of the blocking system associated with the heavy precipitation can be clearly identified.     

Temporal and spatial evaluation of environmental noise in urban area: a case study in Iran

Environmental noise pollution is a disrupting factor in the urban areas which can lead to adverse health effects, behavior and quality of life. Present study was carried out in Tabriz (Iran) and aimed to achieve a real condition of noise pollution. Thirty-five measurement stations were selected, and noise levels were recorded. The equivalent noise level in (A) frequency weighting network, route-mean-square sound pressure level, minimum sound pressure level, maximum sound pressure level and noise pollution level were computed as applicable indices. Temporal and spatial variability of these noise indices were plotted by Arc GIS. Public awareness about the noise pollution was assessed through interview. Mixed model and pairwise comparisons were used for comparison of noise indices based on stations and times. It was found that noise levels were significantly different and higher than permissible levels at most stations, especially at heavily travelled crossroads and squares. Mean equivalent noise level for morning, noon, afternoon and night was 71.35 ± 7.49, 71.63 ± 4.90, 70.67 ± 4.52 and 68.74 ± 5.22 dB(A), respectively. The noise indices of all stations and measurement times had significant difference (p value = 0.028 and 0.019, respectively). It was observed that in normal traffic, the highest sound levels are produced by buses, trucks and motorbikes due to low-technology engines. Using the horn was the first reflex of the most drivers. A main part of the noise pollution problem of the studied city can be attributed to driving culture and non-compliance with traffic laws.     

Resource allocation for regional earthquake risk mitigation: a case study of Tehran,Iran

This paper presents a new optimization model to help cities in seismically active developing countries decide (1) How much to spend on pre-earthquake mitigation versus waiting until after an event and paying for reconstruction or simply not rebuilding damaged buildings? (2) Which buildings to mitigate and how? and (3) Which buildings to reconstruct and how? It extends previously developed optimization models to consider the particular issues that arise in such countries. First, the model allows for the possibility that some damaged buildings will not be reconstructed immediately and keeps track of any lost building inventory. Second, buildings can be mitigated to, or when damaged, reconstructed to, any appropriate structural type and seismic design level. Finally, the model objectives include minimizing the chance of an extremely high death toll in any one earthquake and minimizing the average annual death toll across earthquakes. The model is illustrated through a case study analysis for Tehran, Iran.     

Identification of hazardous waste landfill site: a case study from Zanjan province, Iran

The study of landfill sites is one of the most important studies in landfill engineering, and the landfill site selection involves combination of engineering, science, and politics. This paper describes a comprehensive hazardous waste landfill site selection methodology with the combined utilization of geographic information system and multiple criteria analysis methods, as applied to the Zanjan province in Iran. The six main data categories that were used are geological/engineering geological, geomorphological, hydrological/hydrogeological, climatological, pedological, and social/economical criteria, which included 31 input layers in total. A suitability map for hazardous waste landfilling was prepared for study area with five classes from most suitable to completely unsuitable. Finally, out of the three sites, one site was selected which was chosen by the local authorities. Our work offers a comprehensive methodology and provides essential support for decision-makers in the assessment of hazardous waste management problems in Zanjan province in I.R. Iran and other developing cities in other countries.     

Hurst scaling with crossover of a drought indicator: a case study in Belem and Manaus,Brazil

Natural Hazards - Some Amazonia regions are vulnerable to natural disasters. Hurst analysis of hydrological events can provide more information than classical statistical methods. The objectives of...     

干旱频率分析研究进展

从干旱定义与识别、点干旱频率分析和区域干旱频率分析3个方面系统阐述了干旱频率分析研究进展和存在问题,归纳了适用于干旱频率分析的干旱定义,干旱识别存在的主要问题以及区域干旱频率分析研究的3种途径。提出综合利用研究区域水文气象特性、干旱成因、旱情、旱灾,并结合前期的大气环流条件等信息来描述和识别干旱,重点开展对干旱特征变量的理论分布、干旱事件重现期公式和经验频率公式等基本理论的研究,关注区域干旱频率分析,注重对径流、土壤水、地下水和供水系统的干旱特性分析。     

区域地下水流数值模拟的方法和实践 ——以华北平原为例

平原(盆地)和流域尺度的地下水流数值模拟对于区域地下水资源合理开发利用具有重要意义。本文在总结分析国内外区域地下水资源数值模型特点的基础上,重点介绍了华北平原区域地下水流数值模型,并指出了区域地下水流数值模拟中存在的问题。     

Forecasting of meteorological drought using Wavelet-ANFIS hybrid model for different time steps (case study: southeastern part of east Azerbaijan province, Iran)

Drought is accounted as one of the most natural hazards. Studying on drought is important for designing and managing of water resources systems. This research is carried out to evaluate the ability of Wavelet-ANN and adaptive neuro-fuzzy inference system (ANFIS) techniques for meteorological drought forecasting in southeastern part of East Azerbaijan province, Iran. The Wavelet-ANN and ANFIS models were first trained using the observed data recorded from 1952 to 1992 and then used to predict meteorological drought over the test period extending from 1992 to 2011. The performances of the different models were evaluated by comparing the corresponding values of root mean squared error coefficient of determination (R ²) and Nash–Sutcliffe model efficiency coefficient. In this study, more than 1,000 model structures including artificial neural network (ANN), adaptive neural-fuzzy inference system (ANFIS) and Wavelet-ANN models were tested in order to assess their ability to forecast the meteorological drought for one, two, and three time steps (6 months) ahead. It was demonstrated that wavelet transform can improve meteorological drought modeling. It was also shown that ANFIS models provided more accurate predictions than ANN models. This study confirmed that the optimum number of neurons in the hidden layer could not be always determined using specific formulas; hence, it should be determined using a trial-and-error method. Also, decomposition level in wavelet transform should be delineated according to the periodicity and seasonality of data series. The order of models with regard to their accuracy is as following: Wavelet-ANFIS, Wavelet-ANN, ANFIS, and ANN, respectively. To the best of our knowledge, no research has been published that explores coupling wavelet analysis with ANFIS for meteorological drought and no research has tested the efficiency of these models to forecast the meteorological drought in different time scales as of yet.