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1.
The drought during the months of June to September (JJAS) results in significant deficiency in the annual rainfall and affects the hydrological planning, disaster management, and the agriculture sector of India. Advance information on drought characteristics over the space may help in risk assessment over the country. This issue motivated the present study which deals with the prediction of drought during JJAS through standardized precipitation index (SPI) using nine general circulation models (GCM) product. Among these GCMs, three are the atmospheric and six are atmosphere–ocean coupled models. The performance of these GCM’s predicted SPI is examined against the observed SPI for the time period of 1982–2010. After a rigorous analysis, it can be concluded that the skill of prediction by GCM is not satisfactory, whereas the ability of the coupled models is better than the atmospheric models. An attempt has been made to improve the accuracy of predicted SPI using two different multi-model ensemble (MME) schemes, viz., arithmetic mean and weighted mean using singular value decomposition-based multiple linear regressions (SVD-MLR) of GCMs. It is found that among these MME techniques, SVD-MLR-based MME has more skill as compared to simple MME as well as individual GCMs.  相似文献   

2.
Drought, a frequent environmental disaster in the monsoon region of east China, significantly affects the agricultural economy. In recent years, researchers have emphasised drought risk management. This paper presents a preliminary method to analyse the risk of agricultural drought with regard to the loss of three main crops in individual prefecture-level cities in the monsoon region of east China. In this study, the agricultural drought risk is assessed by developing the index of consecutive rainless days and establishing loss rate curves based on the historical drought data from 1995 to 2008. The results show that the North China is seriously affected by drought hazard. Northeast China is the most sensitive to drought due to its large sown crop areas and weak irrigation. Approximately 11 % of the cities are in the extreme risk category; this category includes 26 % of the cultivated land area and 11 % of the total crop yields in the region. Twenty-three per cent of the cities, accounting for 28.5 % of the total cultivated land area and 26.4 % of the crop yields of the study area, are in high-risk areas, and 77 % of the cities with high and extreme risk levels are distributed in North and Northeast China. Moreover, 64 % of the cities in the monsoon region of East China are in moderate- and low-risk levels. These cities are primarily located south of the Yangtze River. In conclusion, minimising the risk of agricultural drought must be emphasised in northern China because of the high level of risk.  相似文献   

3.
开展农业干旱灾害风险评估,有利于定量认识农业旱灾和科学指导防旱抗旱工作。基于集对分析原理和模糊理论建立的模糊集对评价法,兼顾了信息的多尺度特征和评价等级的模糊性,概念清晰,计算简洁。构建了由旱灾危险性子系统、旱灾暴露性子系统、灾损敏感性子系统和抗旱能力子系统组成的干旱灾害风险评估体系和评价指标。将模糊集对评价法应用于2012年安徽省亳州市农业干旱灾害风险评估,研究结果表明,建议方法是可靠的,为农业干旱灾害风险评估提供了一种新途径。  相似文献   

4.
The traditional studies on drought disaster risk were based on the ground point data, which were unable to realize the continuity of space and the timeliness. It is shown that the monitoring and evaluation precision on drought were reduced significantly. However, remote sensing data in adequate spatial and temporal resolution can overcome these limitations. It can better monitor the crop in large area dynamically. This study presents a methodology for dynamic risk analysis and assessment of drought disaster to maize production in the northwest of Liaoning Province based on remote sensing data and GIS from the viewpoints of climatology, geography and disaster science. The model of dynamic risk assessment of drought disaster was established based on risk formation theory of natural disaster, and the expression of risk by integrating data came from sky, ground and space. The risk indexes were divided into four classes by data mining method, and the grade maps of drought disaster risk were drawn by GIS. It is shown that the spatial and temporal risk distributions of maize at each growth stage changed over time. The model has been verified against reduction in maize yield caused by drought. It demonstrated the reasonability, feasibility and reliability of the model and the methodology. The dynamic risk assessment of regional drought disaster for maize can be used as a tool, which can timely monitor the status (the possibility and extent of drought) and trends of regional drought disaster. The results obtained in this study can provide the latest information of regional drought disaster and the decision-making basis of disaster prevention and mitigation for government management and farmers.  相似文献   

5.
李敏  张铭锋  朱黎明  黄金柏 《水文》2023,43(4):39-44
气象干旱发展到一定程度可以传递为水文干旱。以潘家口水库流域1961—2010年逐月平均降水数据和潘家口水库的入库径流序列为基础数据,分别计算了1、3、6、12个月时间尺度的标准化降水指数（SPI）和标准化径流指数（SRI）,以表征研究区域的气象干旱和水文干旱。基于条件分布模型,分析了不同时间尺度的气象干旱传递到未来的不同等级和不同的预测期（或滞后期）的水文干旱的概率。结果表明,当SPI时间尺度较短或预测期（滞后期）较短时,其对应的SRI水文干旱等级越倾向于维持与SPI相同的干旱等级;随着SPI时间尺度的增长或预测期（滞后期）延长,其对应的SRI水文干旱等级略低于气象干旱或恢复到正常状态。  相似文献   

6.
The Niger River basin is drought-prone, and farmers are often exposed to the vagaries of severe weather and extreme climate events of the region. Spatiotemporal characteristics of drought are important for its mitigation. With 52 years of gauged-based monthly rainfall, the study investigates the potentials of Standardized Precipitation Index (SPI) as standard measure for meteorological drought, its characterization, early warning systems and use in weather index-based insurance. Gamma probability distribution type 2, which best fits the rainfall frequency distribution of the region, was used for the transformation of the skewed rainfall data to derive the SPI. Results showed 9, 5, 5 and 6 drought events of severe to extreme intensities occurred in the headwaters of the basin, inner delta, middle Niger, and lower Niger sub-watersheds, respectively. Their magnitudes were in the range 1–5, 2–6, 2–8 and 2–7, respectively. Spatially, results further showed that the 1970s and 1980s drought events were dominantly of moderate (SPI values ?1 to ?1.49) and severe (SPI values ?1.5 to ?1.99) intensities, respectively, with sporadic cases of severe to extreme drought intensities occurring in 1970s and extreme to exceptional intensities in the 1980s. Further investigations show that 3-month SPI indicated 85% of variance in the standardized cereal crop yield, which suites well as weather index insurance variable. The study therefore proposes SPI weather index-based insurance as a pathway forward to ameliorate the negative impacts on insured farmers in this region in terms of indemnity payouts whenever drought disaster occurs.  相似文献   

7.
This article investigates whether the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived global terrestrial Drought Severity Index (DSI) had the capability of detecting regional drought over subtropical southwestern China. Monthly, remotely sensed DSI data with 0.05° spatial resolution were used to characterize the extent, duration, and severity of drought from 2000 to 2010. We reported that southwestern China suffered from incipient to extreme droughts from November 2009 to March 2010 (referred to as the “drought period”). The area affected by drought occupied approximately 74 % of the total area of the study region, in which a moderate drought, severe drought, and an extreme drought accounted for 20, 12.7, and 13.2 % of the total area, respectively; particularly in March 2010, droughts of severe and extreme intensity covered the largest areas of drought, which were 16.1 and 18.6 %, respectively. Spatially, eastern Yunnan, western Guizhou, and Guangxi suffered from persistent droughts whose intensities ranged from mild to extreme during the drought period. Pearson’s correlation analyses were performed between DSI and the in situ meteorological station-based Standardized Precipitation Index (SPI) for validating the monitoring results of the DSI. The results showed that the DSI corresponded favorably with the time scales of the SPI; meanwhile, the DSI showed its highest correlation (mean: r = 0.58) with a three-month SPI. Furthermore, similar spatial patterns and temporal variations were found between the DSI and the three-month SPI, as well as the agro-meteorological drought observation data, when monitoring drought. Our analysis suggests that the DSI can be used for near-real-time drought monitoring with fine resolution across subtropical southwestern China, or other similar regions, based solely on MODIS-derived evapotranspiration/potential evapotranspiration and Normalized Difference Vegetation Index data.  相似文献   

8.
In the present study, the Standardized precipitation index (SPI) was employed to analyze the drought status of the Dapoling basin over a period of autumn from September to November, because drought events frequently occur during this period. Three time scales were used, 3-, 6- and 12-month time scale. Daily precipitation data from 13 weather stations covering a period of 31 years from 1980 to 2010 were collected, and the Tyson polygon method was used to calculate the monthly precipitation of the basin. Based on the SPI value, the classification of drought was provided. Besides, considering the fact that the length of sample used to calculate the SPI influences the accuracy on SPI estimation, in turn to lead to the uncertainty of drought classification, the bootstrap technique was employed to analyze the uncertainty of SPI estimation and drought assessment. Results showed that, for September, October or November, drought event mainly occurred in 1985, 1986, 1988, 1990, 1992, 1993, 1994, 1997, 1999, 2001, 2002 and 2007. Especially in 1999 and 2001, severe drought and extreme drought occurred. And the uncertainty analysis results indicated that in term of expected estimation, the two methods with consideration and no-consideration of impact of sample on SPI calculation has no considerable difference, while in term of confidence interval estimation of SPI, there are obviously different between the two methods. This means the impact of the sampling uncertainty on SPI calculation and drought assessment should be noted and not ignored.  相似文献   

9.
Drought is one of the most important natural hazards in Iran. It is especially more prevalent in arid and hyper arid regions where there are serious limitations in regard to providing sufficient water resources. On the other hand, drought modeling and particularly its prediction can play important role in water resources management under conditions of lack of sufficient water resources. Therefore, in this study, drought prediction in a hyper arid location of Iran (Ardakan region) has been surveyed based on the abilities of artificial neural. Standardized Precipitation Index (SPI) in different time scales (3, 6, 9, 12, and 24 monthly time series) computed based on the data gathered from four rain gauge stations. After evaluation and testing of different artificial neural networks (ANN) structures, gradient descent back propagation (traingd) network showed higher abilities than others. Then, the predictions of SPI time series with different monthly lag times (1:12 months) were tested. Generally, drought prediction by ANNs in the Ardakan region has shown considerable results with the correlation coefficient (R) more than 0.79 and in the most cases and it rises more than 0.90, which indicates the ANN’s ability of drought prediction.  相似文献   

10.
This study presents a methodology of risk early warning of maize drought disaster in Northwestern Liaoning Province from the viewpoints of climatology, geography, disaster science, environmental science, and so on. The study area was disaggregated into small grid cells, which has higher resolution than counties. Based on the daily meteorological data and maize yield data from 1997 to 2005, the risk early warning model was built up for drought disaster. The early warning crisis signs were considered from exogenous warning signs and endogenous warning signs. The probability of drought was taken as endogenous warnings sign, which was calculated by logistic regression model. Beside precipitation, wind speed and temperature were taken into consideration when assessing the drought. The optimal partition method was used to define the threshold of each warning grade. Take the year of 2009 as an example, this risk early warning model performed well in warning drought disasters of each maize-growing stage. Results obtained from the early warning model can guide the government to take emergency action to reduce the losses.  相似文献   

11.
地质灾害风险评价阈回归联合聚类分析   总被引：2，自引：0，他引：2  
根据吉林省近10年的地质灾害监测数据,采用统计方法讨论吉林省地质灾害风险评价问题,对地质灾害易发区进行划分。首先对系统聚类分析方法进行了改进,根据各种要素对地质灾害影响的程度引入了权重系数,分类后应用判别分析的方法检验出其精确度达到94.87%。为了进一步了解各种因素引致灾害的形式,掌握其在不同规模数值下形成灾害的特点及差异性,运用阈回归模型进行了数据拟合,因素的解释程度达到99.996 2%。加权聚类和阈回归方法对数据拟合程度的高精度,说明其在地质灾害风险评价问题中的适用性及灾害易发区划分的准确性。  相似文献   

12.
Risk assessment to China’s agricultural drought disaster in county unit   总被引：14，自引：7，他引：7  
Hao  Lu  Zhang  Xiaoyu  Liu  Shoudong 《Natural Hazards》2012,61(2):785-801
China faces drought disaster risk under the changing climate. Risk analysis is a suitable approach in order to design ex-ante measure able to anticipate effects of drought on agricultural production. In this article, with the support of historic drought disaster data from 583 agro-meteorological observations (1991–2009), a risk analysis method based on information diffusion theory was applied to create a new drought risk analysis model, and the risk of China’s agriculture drought disaster was evaluated on higher spatial resolution of county unit. The results show that in more than three hundred counties of China, risk probability was biyearly or annually when Drought Affected Index (DAI) was over 5%. When DAI was up to 40%, more than one hundred counties were prone to drought disaster annually or once every 5 years. This showed that the impact of drought disaster on China’s agriculture, whether in frequency or intensity, was large. With the different level of DAI, China’s agricultural drought risk pattern showed variable pattern characteristics. When DAI was low, the distribution of county agricultural drought risk in China presented the East–West pattern of differentiation, and high risk mainly lied in the eastern, low risk mainly in the western. On the other hand, when DAI was high, the distribution of county risk appeared a pattern of high in center, and the north areas higher than the south, increased gradually from southwest to northeast. Drought risk presents a clear zonal differentiation that may be result from stepped topography, different precipitation and hazard-affected bodies. Spread of high value area of drought risk in northern may be related to the southeast monsoon and ecological degradation in northern Ecotone.  相似文献   

13.
Drought is one of the major natural disasters occurring in China and causes severe impacts on agricultural production and food security. Therefore, agricultural drought vulnerability assessment has an important significance for reducing regional agricultural drought losses and drought disaster risks. In view of agricultural drought vulnerability assessment with the characteristics of multiple factors and uncertainty, we applied the fuzzy comprehensive evaluation framework to agricultural drought vulnerability model. The agricultural drought vulnerability assessment model was constructed based on the multi-layer and multi-index fuzzy clustering iterative method, which can better reveal the drought vulnerability (including sensitivity and adaptation capacity). Furthermore, the cycle iterative algorithm was used to obtain the optimal index weight vector of a given accuracy by setting the objective function. It provides a new approach to weight determination of agricultural drought vulnerability assessment. In this study, agricultural drought vulnerability of 65 cities (as well as leagues and states) in the Yellow River basin was investigated using a fuzzy clustering iterative model and visualized by using GIS technique. The results showed clear differences and regularities among the spatial distribution of agricultural drought vulnerability of different regions. A large number of the regions in the basin consisted of those exhibiting high to very high vulnerability and were mainly distributed throughout Qinghai, Gansu, northern Shaanxi, and southern Shanxi, accounting for 46 % of the total assessment units. However, the regions exhibiting very high vulnerability were not significantly affected by droughts. Most of the regions exhibiting moderate vulnerability (21.5 % of the assessment units) were mainly concentrated among agricultural irrigation areas, where agriculture is highly sensitive to droughts, and drought occurrence in these regions will likely cause heavy losses in the future. The regions exhibiting slight to low vulnerability were relatively concentrated, accounting for 32.3 % of the assessment units, and were mainly distributed in the plains of the lower reaches of the Yellow River, where the economy was rather well developed and the agricultural production conditions were relatively stronger.  相似文献   

14.
Mining-induced water inrush is a sudden and destructive underground disaster caused by a mining disturbance. This disaster occurs frequently in the northern region of Shaanxi province in China due to overburden fractures in shallow seam mining, which pose a great threat to residents’ safety. It is therefore essential to construct an accurate prediction model. This study first applies selection hierarchy analysis to the main controlling factors of roof water inrush to study their weights using an analytic hierarchy process (AHP) including five factors: surface water catchment features, wateriness of the aquifer, water-resistant characteristics of aquiclude, combined influence of overburden, and mining disturbance characteristics. The grey relational analysis (GRA) method is used to calculate the correlation degree of each water inrush. The AHP-GRA method presents a comprehensive evaluative model combining the advantages of both approaches to analyze mining safety. Qualitative and quantitative indicators of the roof water inrush prediction model in shallow seam mining are established. Secondly, risk prediction of roof water inrush points and comprehensive water inrush is determined using engineering examples from the Hanjiawan coal mine. Results indicate that during safety mining, water inflow data are consistent with our prediction, thereby substantiating the model’s accuracy and providing a new method for predicting roof water inrush in shallow seam mining.  相似文献   

15.
Data reduction methods such as principal components analysis and factor analysis can be used to define drought prone areas of a basin. In this study, factor analysis method applied for the purpose of projecting the information space on the few dominant axes. The main aim of this study is regionalization of Lake Urmia Basin from the view of drought using factor analysis. For this purpose, monthly precipitation data of 30 weather stations in the period 1972–2009 were used. For each of the selected stations, 3- and 12-month Standardized Precipitation Index (SPI) values were calculated. Factor analysis conducted on SPI values to delineate the study area with respect to drought characteristics. Homogeneity of obtained regions tested using the S statistics proposed by Wiltshire. Results of factor analysis of 3- and 12-month SPI values showed that 5 (6) factors having eigenvalues >1 accounted for 68.08 (78.88) % of total variance. The Lake Urmia Basin was delineated into the five distinct homogeneous regions using the 3-month SPI time series. This was six in the case of the 12-month SPI time series. It can be concluded that there are different distinct regions in Lake Urmia Basin according to drought characteristics. The map of regions defined using the 3- and 6-month SPI time series presented in this paper for Lake Urmia Basin.  相似文献   

16.
Drought over a period threatens the water resources, agriculture, and socioeconomic activities. Therefore, it is crucial for decision makers to have a realistic anticipation of drought events to mitigate its impacts. Hence, this research aims at using the standardized precipitation index (SPI) to predict drought through time series analysis techniques. These adopted techniques are autoregressive integrating moving average (ARIMA) and feed-forward backpropagation neural network (FBNN) with different activation functions (sigmoid, bipolar sigmoid, and hyperbolic tangent). After that, the adequacy of these two techniques in predicting the drought conditions has been examined under arid ecosystems. The monthly precipitation data used in calculating the SPI time series (SPI 3, 6, 12, and 24 timescales) have been obtained from the tropical rainfall measuring mission (TRMM). The prediction of SPI was carried out and compared over six lead times from 1 to 6 using the model performance statistics (coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE)). The overall results prove an excellent performance of both predicting models for anticipating the drought conditions concerning model accuracy measures. Despite this, the FBNN models remain somewhat better than ARIMA models with R?≥?0.7865, MAE?≤?1.0637, and RMSE?≤?1.2466. Additionally, the FBNN based on hyperbolic tangent activation function demonstrated the best similarity between actual and predicted for SPI 24 by 98.44%. Eventually, all the activation function of FBNN models has good results respecting the SPI prediction with a small degree of variation among timescales. Therefore, any of these activation functions can be used equally even if the sigmoid and bipolar sigmoid functions are manifesting less adjusted R2 and higher errors (MAE and RMSE). In conclusion, the FBNN can be considered a promising technique for predicting the SPI as a drought monitoring index under arid ecosystems.  相似文献   

17.
选取内蒙古锡林郭勒盟与积雪有关的雪灾致灾指标, 以气温、 风速为气象条件孕灾环境指标, 坡度、 植被盖度为下垫面孕灾环境指标, 人口密度、 牧民纯收入、 人均GDP、 牲畜超载率等数据为承灾体脆弱性指标, 基于BP方法、 层次分析法、 建立了内蒙古锡林郭勒盟白灾综合风险评价体系, 并对其进行了风险评价与区划。为提高灾害评估的准确率, 白灾的灾害等级是以月为尺度进行评定, 选取的气象指标多数都是以月为尺度的指标。研究表明： 白灾与积雪因子高度相关, 是气候灾害, 积雪、 低温、 大风等气象因子长期作用的结果。对白灾尝试用BP神经网络法进行风险评估, 评估的灾害等级和实际灾害等级十分吻合, 用训练好的神经网络对各个旗县（1980 - 2015年）的白灾进行了风险评估, 评估效果理想。因此, 可以通过数值预报产品、 气候预测产品获取相关评价因子, 采用BP方法形成白灾风险预评估产品, 进而应用于雪灾风险评估业务中, 为相关部门提供决策依据。  相似文献   

18.
岩爆是地下工程开挖过程中硬质岩体存储的弹性应变能突然、迅速释放的动态过程。我国西南山区正在建设或拟建大量深埋长大隧道,勘察阶段岩爆的准确预测对有效设计和控制投资十分重要。从隧道工程勘察阶段线路比选与设计需求出发,针对隧道勘查期岩爆灾害预测指标获取难、预测精度低的问题,以该阶段岩爆预测指标的易获取性为前提,利用贝叶斯网络解决不确定性问题的有效性来反映岩爆烈度与各影响因素的相关关系。基于473组岩爆灾害案例,采用4个预测指标（地应力、地质构造、围岩级别和岩石强度）来构建岩爆烈度朴素贝叶斯概率分级预测模型,利用十折交叉验证方法确定模型预测精度达84.47%。将该模型应用于雅安—叶城高速公路跑马山1号隧道岩爆段落,预测结果显示:28次岩爆预测中有24次正确、4次错误,准确率高达85.71%;其中2组错误预测中,现场判别为轻微-中等岩爆,而本文模型预测为轻微岩爆。验证结果表明所建立的贝叶斯网络模型具有良好的预测性能,研究成果可为我国西南山区深埋长大硬岩隧道勘察设计期岩爆灾害预测提供技术支撑。  相似文献   

19.
Drought as a natural disaster impresses people living. The main tool in better management of such phenomena is to explain its characteristics, using drought indices. The indices use precipitation, temperature, streamflow, and other hydrological variables to explain such events. In this study, standardized precipitation index (SPI) and stream-flow drought index (SDI) were used to develop a new combined drought index (CDI) based on copula functions. The proposed index function was evaluated in Khuzestan, Yazd and Golestan provinces of Iran from 1982 to 2012. These areas introduce different climate conditions. The index was analyzed temporally and spatially. In the temporal analysis, CDI was calculated separately for each station and the finest index was chosen by Kolmogorov–Smirnov and Chi-squared tests. In the spatial analysis, CDI was computed for two main scenarios and twenty sub-scenarios for the whole area of Golestan Province. The optimum index was chosen based on comparison with initial SPI and SDI. The results showed that CDI is more meticulous than both singular SPI and SDI, as it can trace a drought onset earlier and drought duration more accurate than the two individual indices and obviously display extreme states.  相似文献   

20.
加权距离判别法在泥石流危险度评价中的应用   总被引：1，自引：0，他引：1  
将加权距离判别法引用到泥石流危险度分类中,建立了泥石流危险度分类模型。该模型选用了流域面积、主沟长度、流域最大相对高差、流域切割密度、主沟床弯曲系数、人口密度、泥沙补给长度比、植被覆盖率、一次泥石流（可能）最大冲出量和泥石流发生频率10项指标为建模参数,运用熵值法对这10个指标进行赋权,用已经分类的泥石流沟作为训练样本进行学习,建立了相应的判别准则。将待判泥石流沟样本代入判别准则进行判别分类,分类结果与传统分类结果100%吻合,验证了该模型的分类性能良好。该方法可以在实际工程中进行推广。  相似文献   

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