Analysis of drought hazards in North China: distribution and interpretation

This paper examines the characteristics of historical meteorological hazards and associated natural-anthropogenic variations in China, with specific attention given to the meteorological drought hazards occurring at very high frequency and affecting social?Ceconomic development in North China. Owing to an increasing awareness of meteorological droughts in this area, the aim of this contribution is to provide a comprehensive overview of meteorological droughts in North China by reviewing the meteorological references and their intrinsic linkages with climatic, geological, and anthropogenic controls. Our study highlights the region-wide meteorological droughts with a rather clear recurrence of 30 and 100?years, totally indicating Shanxi and Shandong being the predominated area suffering from extreme meteorological droughts. The spatial and temporal distribution of meteorological drought hazards in this region is considered to be a function of climatic, topographic, hydrological, and anthropogenic characteristics. In view of the wide distribution and linkage with geo-hazards and changes of dynasties, the meteorological drought hazard is one of the key issues for long-term social?Ceconomic harmonization. This study can be expected to prioritize drought mitigation measures and ensure regional sustainable development in North China.     

A composite index for drought hazard assessment using CPC rainfall time series data

Hazard analysis is the first step in any disaster management activity. Drought is a serious environmental hazard strongly limiting the agricultural production in the tropical countries like India. A comprehensive drought hazard map is useful for multiple perspectives such as agriculture, environment and hydrology. In this study, daily rainfall data of the Climate Prediction Centre during the south-west monsoon season (June–September) of 12 years, over India was analysed. Based on rainfall and rainy days, six indicators of drought were generated which were then synthesized into a composite index of drought hazard for every 10 × 10 km pixel. The weights for the composite index were generated through variance approach. The index has effectively captured the spatial variations in meteorological drought across India by showing a typical pattern with increasing hazardous area from east to west. The drought hazard map also shows considerable agreement with the climate classification map and the drought proneness map reported by other studies. Thus, the current study presents a simple and novel approach for drought hazard analysis, using the routinely available geospatial rainfall data products. The methodology can be extended to other geographies and disasters too. Use of time series data of longer period would improve the reliability of the composite drought hazard index.     

Drought risk assessment in the western part of Bangladesh

Though drought is a recurrent phenomenon in Bangladesh, very little attention has been so far paid to the mitigation and preparedness of droughts. This article presents a method for spatial assessment of drought risk in Bangladesh. A conceptual framework, which emphasizes the combined role of hazard and vulnerability in defining risk, is used for the study. Standardized precipitation index method in a GIS environment is used to map the spatial extents of drought hazards in different time steps. The key social and physical factors that define drought vulnerability in the context of Bangladesh are identified and corresponding thematic maps in district level are prepared. Composite drought vulnerability map is developed through the integration of those thematic maps. The risk is computed as the product of the hazard and vulnerability. The result shows that droughts pose highest risk to the northern and northwestern districts of Bangladesh.     

The assessment of drought relief by typhoon Saomai based on MODIS remote sensing data in Shanghai,China

Typhoons are one of the major natural hazards occurring frequently in Shanghai. The comprehensive assessment of drought relief by typhoon has become a major concern of scientists and government agencies in Shanghai, China. In this article, with the support of remote sensing data and the available data from local meteorological stations, the regional drought relief was investigated and the change of drought intensity was quantified by the typhoon “Saomai” between 5 and 8 August 2005. The precipitation anomaly calculated on the basis of recorded rainfall was adopted to analyze drought condition changes before and after the typhoon. Then, vegetation supply water index (VSWI) and normalized difference vegetation index (NDVI) were used to monitor the drought relief due to the consecutive shortage of summer rainfall. Impact of typhoon on drought was compared by VSWI before and after typhoon Saomei. The results showed that the typhoon alleviated the drought of the vegetation by more than 70 %, based on the spatial and temporal distribution of precipitation, the ground temperature, relative humidity, high temperature, NDVI from Shanghai area. The result shows that MODIS remote sensing data are a useful quantitative monitoring tool in drought relief by local typhoons. More strategies are necessary to be adopted for prevention and mitigation of meteorological disaster in Shanghai in recent years.     

Impact assessment of projected climate change on the hydrological regime in the SE Alps, Upper Soča River basin, Slovenia

According to climate change projections, the Alps will be one of the most affected regions in Europe. A basis for adaptation measures to climate changes is the quantification of the impact. This study investigates the impact of projected climate change on the hydrological cycle in the Upper So?a River basin. It is based on the use of climate model data as input for hydrological modelling. The climatic input data used were generated by a global climate model (IPCC A1B emission scenario) and downscaled for local use. Hydrological modelling was performed using the distributed hydrological model MIKE SHE. The simulated impact was quantified by comparing results of the hydrological modelling for the control period (1971–2000) and different scenario periods (2011–2040, 2041–2070, 2071–2100). The climate projections show an increase in the average temperature (+0.9, +2.3, +3.8°C) and negligible changes in average precipitation amounts in the scenario periods. More distinctive are changes in the temporal pattern of mean monthly values (up to +5.2°C and ±45% for precipitation), which result in warmer and wetter winters and hotter and drier summers in the scenario periods. The projected rise in temperature is reflected in the increased actual evapotranspiration, the reduction of snow amount and summer groundwater recharge. Changes of monthly and period average discharges follow the trends of the meteorological variables. Changes in precipitation patterns have a major influence on the projected hydrological cycle and are the most important source of uncertainty. Estimated extreme flows indicated increased hazards related to floods, especially in the near-future scenario period, while in the far future scenario period, distinctive drought conditions are projected.     

Trends and variability of meteorological drought over the districts of India using standardized precipitation index

Meteorological drought during the southwest monsoon season and for the northeast monsoon season over five meteorological subdivisions of India for the period 1901–2015 has been examined using district and all India standardized precipitation index (SPI). Whenever all India southwest monsoon rainfall was less than ?10% or below normal, for those years all India SPI was found as ?1 or less. Composite analysis of SPI for the below normal years, viz., less than ?15% and ?20% of normal rainfall years indicate that during those years more than 30% of country’s area was under drought condition, whenever all India southwest monsoon rainfall was –15% or less than normal. Trend analysis of monthly SPI for the monsoon months identified the districts experiencing significant increase in drought occurrences. Significant positive correlation has been found with the meteorological drought over most of the districts of central, northern and peninsular India, while negative correlation was seen over the districts of eastern India with NINO 3.4 SST. For the first time, meteorological drought analysis over districts and its association with equatorial pacific SST and probability analysis has been done for the northeast monsoon over the affected regions of south peninsular India. Temporal correlation of all India southwest monsoon SPI and south peninsular India northeast monsoon SPI has been done with the global SST to identify the teleconnection of drought in India with global parameters.     

基于大范围地面墒情监测的鄱阳湖流域农业干旱

以鄱阳湖流域为研究区, 基于2011—2020年22个墒情站的逐日地面墒情监测数据、1956—2020年49个雨量站的日降雨数据及2016—2019年墒情站所在灌区的气象数据, 采用考虑植被生理状态的土壤水分亏缺指数(SWDI)表征农业干旱, 分析不同尺度下墒情、包气带缺水量和降水量的时空分布, 评估SWDI在鄱阳湖流域农业干旱监测中的适用性, 揭示该流域农业干旱时空演变特征及其对气象干旱的响应规律, 初步探讨土壤质地与农业干旱强度的相关性。结果表明: ① SWDI对鄱阳湖流域农业干旱诊断具有较好的适用性; ②近10 a该流域农业干旱呈显著加重趋势, 其中2019—2020年发生流域性重度农业干旱, 且夏、秋、冬连旱, 是近10 a的主导季节性农业干旱, 对水稻、油菜等粮食产量影响显著; ③相较于气象干旱, 农业干旱发生、结束时间分别平均约晚2.5周和3周, 历时长10.1周, 频次更低, 干旱等级更小; ④砂土持水性最差, 易发生特大农业干旱, 黏土、黏壤土保水性最好, 轻旱和中旱发生概率较大, 壤土、砂壤土和壤砂土则介于二者之间。     

Regional analysis of streamflow drought: a case study in southwestern Iran

Droughts are complex natural hazards that, to a varying degree, affect some parts of the world every year. The range of drought impacts is related to drought occurring in different stages of the hydrological cycle and usually different types of droughts such as meteorological, agricultural, hydrological, and socio-economical are the most distinguished types. Hydrological drought includes streamflow and groundwater droughts. In this paper, streamflow drought was analyzed using the method of truncation level (at 70 % level) by daily discharges at 54 stations in southwestern Iran. Frequency analysis was carried out for annual maximum series of drought deficit volume and duration. 35 factors such as physiographic, climatic, geologic and vegetation were studied to carry out the regional analysis. According to conclusions of factor analysis, the six most effective factors include watershed area, the sum rain from December to February, the percentage of area with NDVI <0.1, the percentage of convex area, drainage density and the minimum of watershed elevation, explained 89.2 % of variance. The homogenous regions were determined by cluster analysis and discriminate function analysis. The suitable multivariate regression models were ascertained and evaluated for hydrological drought deficit volume with 2 years return period. The significance level of models was 0.01. The conclusion showed that the watershed area is the most effective factor that has a high correlation with drought deficit volume. Moreover, drought duration was not a suitable index for regional analysis.     

A Comparative Study of Least Square Support Vector Machines and Multiclass Alternating Decision Trees for Spatial Prediction of Rainfall-Induced Landslides in a Tropical Cyclones Area

The objective of this study is to explore and compare the least square support vector machine (LSSVM) and multiclass alternating decision tree (MADT) techniques for the spatial prediction of landslides. The Luc Yen district in Yen Bai province (Vietnam) has been selected as a case study. LSSVM and MADT are effective machine learning techniques of classification applied in other fields but not in the field of landslide hazard assessment. For this, Landslide inventory map was first constructed with 95 landslide locations identified from aerial photos and verified from field investigations. These landslide locations were then divided randomly into two parts for training (70 % locations) and validation (30 % locations) processes. Secondly, landslide affecting factors such as slope, aspect, elevation, curvature, lithology, land use, distance to roads, distance to faults, distance to rivers, and rainfall were selected and applied for landslide susceptibility assessment. Subsequently, the LSSVM and MADT models were built to assess the landslide susceptibility in the study area using training dataset. Finally, receiver operating characteristic curve and statistical index-based evaluations techniques were employed to validate the predictive capability of these models. As a result, both the LSSVM and MADT models have high performance for spatial prediction of landslides in the study area. Out of these, the MADT model (AUC = 0.853) outperforms the LSSVM model (AUC = 0.803). From the landslide study of Luc Yen district in Yen Bai province (Vietnam), it can be conclude that the LSSVM and MADT models can be applied in other areas of world also for and spatial prediction. Landslide susceptibility maps obtained from this study may be helpful in planning, decision making for natural hazard management of the areas susceptible to landslide hazards.     

Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam

The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years.     

An analysis of the drought in Yunnan, China, from a perspective of society drought severity

Drought disaster management entails not only understanding meteorological drought as a natural hazard but also evaluating the adverse societal impacts related to the economy and human lives. For the purpose of quantifying the drought severity from the perspective of society drought, a drought index, namely “Society Drought Severity Index” (SDSI), was put forward to analyze the drought in Yunnan Province of China. In SDSI for Yunnan, the drought severity was represented by the weighted discrepancy between the “appropriate” water needs and the total available water resources, inspired by the established Palmer Drought Severity Index (PDSI). Technically, the trend in historical water consumption records in agricultural, industrial, and domestic sectors was applied to represent the appropriate water needs; an apparent “runoff” was used to represent the available water resource in Yunnan. The SDSI of Yunnan revealed a trend toward increasing drought severity, which resulted from a combination of meteorological changes and water needs escalation. Moreover, the spatial center of the 2010 drought in Yunnan based on SDSI was different from that identified by PDSI, which exactly reflected the influence of water needs on drought severity. The SDSI was deemed to be a beneficial tool for drought disaster management and drought risk governance.     

Investigation of hydrological drought using Cumulative Standardized Precipitation Index (SPI 30) in the eastern Mediterranean region (Damascus,Syria)

The Eastern Mediterranean region has been exposed to drought episodes, which have been occurring more frequently during the last decades. The objective of the present paper is to study the precipitation regime of the Damascus (Mazzeh) meteoric station by analysing drought characteristics using the Standardized Precipitation Index (SPI) and comparing this with the drought in Cyprus. The cumulative drought conceptis proposed to characterize long-term hydrologic drought, which affects the shallow groundwater productivity in terms of quantity and quality. Gamma probability distribution was fitted to the long-term annual precipitation in Damascus from 1918–1919 to 2007–2008 (n = 90 years). Generally, a decreasing trend of 17% to the mean annual rainfall of Damascus and 13% to the mean annual rainfall of Cyprus was estimated between 1970 and 2000. The SPI identifies three major extended drought periods: (1) 9 years of severe drought (1954–1963) with an average 20% precipitation deficit per year compared to the mean. (2) 8 years of severe drought (1983–1991) with a 27% deficit per year on average. (3) 9 years of extreme drought (1993–2002) with a 31% deficit per year on average. The cumulative standardized precipitation index (SPI 30) demonstrates positive values for the first period and is indicative of having no effect on the global water balance. SPI 30 exhibits sensitive equilibrium with near zero values / a near zero value (±1.5) for the second period. For the third period, however, the SPI 30 decreases below ?10 indicating an extreme hydrological drought that has negative consequences on the recent groundwater recharge. It is required to develop and implement a sustainable groundwater management strategy to reduce long-terms drought risks. Generally, the SPI 30 in Cyprus is parallel to that in Damascus with a 3–5 year delay. Thus, the central zone of the Eastern Mediterranean region is facing big challenges and has been suffering from three decades of moderate to severe hydrological drought (SPI 30=?5 to ?10) causing a severe decrease in springs discharges of the region. Therefore, in order to reduce the climate change effects on water resources, it is necessary to adopt a sustainable proactive management plan during the frequent severe droughts.     

气候变化对澜湄流域气象水文干旱时空特性的影响

受全球气候变化影响,澜沧江-湄公河流域气象水文干旱发生了较大变化,预测未来流域干旱的时空变化与传播特征是应对气候变化、开展澜湄水资源合作的基础。利用SWAT模型通过气陆耦合方式模拟了澜沧江-湄公河流域历史（1960—2005年）和未来时期（2022—2050年,2051—2080年）的水文过程,采用标准化降水指数和标准化径流指数预估并分析了流域未来气象水文干旱时空变化趋势。结果表明:①澜沧江-湄公河流域未来降水呈增长趋势,气象干旱将有所缓解,但降水年内分配不均与流域蒸发的增加,将导致水文干旱更为严峻,干旱从气象到水文的传播过程加剧;②水文干旱具有明显的空间异质性,允景洪和清盛站的水文干旱最为严重,琅勃拉邦、穆达汉和巴色站次之,万象站最弱;③未来流域水文干旱事件发生频次略有减少,但其中重旱、特旱事件占比增加,极端干旱将趋多趋强,且空间变化更加显著。     

Assessment of drought hazard impact on wheat cultivation using standardized precipitation index in Iran

The assessment of drought hazard impacts on wheat cultivation as a strategic crop in Iran is essential for making mitigation plans to reduce the impact of drought. Standardized precipitation index has gained importance in recent years as a potential drought indicator and is being used more frequently for assessment of drought hazard in many countries. In the present study, the calculated standardized precipitation index for 48 stations dataset in the 30-year time scale fulfilled 30 statistical matrices. The drought hazard index map was produced by sum overlaying the spatial representations of 30 statistical matrices and categorized into four levels of low, moderate, high, and very high, which demonstrated probability of drought occurrences of 10–20 %, 20–30 %, 30–40 %, and 40–50 %, respectively. Finally, after the general division of zonal statistics in drought hazard index map of Iran, major drought hazard zones were geographically classified into five zones. The statistical analysis showed a significant correlation (R ²?=?0.701 to 0.648) between drought occurrences and wheat cultivation including surface area and total production for these drought hazard zones.     

Severity–duration–frequency curves in the mitigation of drought impact: an agricultural case study

Severity–duration–frequency (SDF) curves are very useful in the analysis of drought phenomena. Station-level information obtained from SDF curves can be interpolated to obtain severity maps for fixed return period, in order to jointly analyse the spatial variability of drought characteristics (e.g. severity, duration and frequency). This approach is limited because the severity is usually quantified through indices that use hydrological and meteorological data, depending on the type of requirements. Therefore, drought indices can only reflect hydrological conditions, but are unable to quantify economic losses associated with droughts. In other words, SDF curves do not allow effective quantification of the impact expected with a certain return period. This paper proposes the methodology drought economic risk assessment (DERA) as an approach that emphasizes the importance of the relationship between a generic drought index (which quantifies water deficit) and the economic impact of the failure to meet water demand. Using integrated SDF curves, this relationship enables drought severity and corresponding impacts to be mapped. This procedure was applied to agricultural droughts (sunflower crop) in Umbria Region (central Italy). The agricultural drought impact variable was identified by sunflower yield (Y); the economic impact variable by net benefit depletion (EL); and the drought index by Relative Severity Index (RSI), which is quantifiable by a soil–water balance model. The relationships Y = g(RSI) and EL = f(Y) were specifically determined. Using DERA, it was possible to derive curves for SDF, impact–duration–frequency, and economic losses–duration–frequency (ELDF), which were then used to map severity, impact and economic losses for the assigned return period and duration. From the ELDF curves, further information was obtained by mapping critical drought durations for the assigned return period and economic loss threshold. The case study supports the potential of the proposed approach, both in the planning and real-time management of drought effects.     

The application of GIS-based bivariate statistical methods for landslide hazards assessment in the upper Tons river valley,Western Himalaya,India

Landslides are one of the most frequent and common natural hazards in many parts of Himalaya. To reduce the potential risk, the landslide susceptibility maps are one of the first and most important steps in the landslide hazard mitigation. Earth observation satellite and geographical information system-based techniques have been used to derive and analyse various geo-environmental parameters significant to landslide hazards. In this study, a bivariate statistics method was used for spatial modelling of landslide susceptibility zones. For this purpose, thematic layers including landslide inventory, geology, slope angle, slope aspect, geomorphology, slope morphology, drainage density, lineament and land use/land cover were used. A large number of landslide occurrences have been observed in the upper Tons river valley area of Western Himalaya. The result has been used to spatially classify the study area into zones of very high, high, moderate, low and very low landslide susceptibility zones. About 72% of active landslides have been observed to occur in very high and high hazard zones. The result of the analysis was verified using the landslide location data. The validation result shows significant agreement between the susceptibility map and landslide location. The result can be used to reduce landslide hazards by proper planning.     

水文干旱研究进展

水文干旱是自然干旱中的一种重要类型,影响自然界水循环过程中蒸发、下渗和径流三大环节,关系着水文循环和水量平衡。当前的干旱研究多集中在气象干旱、农业干旱上。鉴于水文干旱研究的重要性和目前水文干旱研究的不足,对当前水文干旱研究进行了分类评述,提出了研究中存在的问题及主要发展方向,可为水文干旱的进一步研究提供参考。     

Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, India

Drought is a serious climatic condition that affects nearly all climatic zones worldwide, with semi-arid regions being especially susceptible to drought conditions because of their low annual precipitation and sensitivity to climate changes. Drought indices such as the standardized precipitation index (SPI) using meteorological data and vegetation indices from satellite data were developed for quantifying drought conditions. Remote sensing of semi-arid vegetation can provide vegetation indices which can be used to link drought conditions when correlated with various meteorological data based drought indices. The present study was carried out for drought monitoring for three districts namely Bhilwara, Kota and Udaipur of Rajasthan state in India using SPI, normalized difference vegetation index (NDVI), water supply vegetation index (WSVI) and vegetation condition index (VCI) derived from the Advanced Very High resolution Radiometer (AVHRR). The SPI was computed at different time scales of 1, 2, 3, 6, 9 and 12 months using monthly rainfall data. The NDVI and WSVI were correlated to the SPI and it was observed that for the three stations, the correlation coefficient was high for different time scales. Bhilwara district having the best correlation for the 9-month time scale shows late response while Kota district having the best correlation for 1-month shows fast response. On the basis of the SPI analysis, it was found that the area was worst affected by drought in the year 2002. This was validated on the basis of NDVI, WSVI and VCI. The study clearly shows that integrated analysis of ground measured data and satellite data has a great potential in drought monitoring.     

Tornado hazards on June 23 in Jiangsu Province,China: preliminary investigation and analysis

This paper reported a tornado hazard happened on June 23, 2016, in Yancheng city, Jiangsu Province. The moving footprint of this huge tornado was from west to east. Shuoji, Chenliang, Goudun, Banhu, Xingou, Wutan towns in Funing district and Sheyang town in Sheyang district were severely hit by this tornado. This tornado along with rainstorm and hailstorm had claimed 99 lives and caused more than 3800 flats to collapse as well as damaged 48 high-voltage circuits. As the cold air from northwest met the subtropical high pressure system that forms over relatively cool water bodies (i.e., Indian and Pacific Oceans), such a powerful meteorological phenomenon was initiated. The strong connective airflow intensified the development of this tornado. Based on the preliminary investigation and analysis of this tornado, cost-effective timber structures with adequate anchorage of the framing to foundations and adequate connection between walls and roofs may be recommended to ensure occupants safety and reduce potential damage in these extreme wind events. Additionally, it is suggested to utilize early warning system along with geographical information system (GIS), Global Positioning System (GPS), and remote sensing (RS) (3S) to monitor and precast the occurrence of rainfall, hailstorm, and tornado hazards in future.