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101.
Impact of climate indicators on continental‐scale potential groundwater recharge in Africa 
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下载免费PDF全文 In the last decades, human activity has been contributing to climate change that is closely associated with an increase in temperatures, increase in evaporation, intensification of extreme dry and wet rainfall events, and widespread melting of snow and ice. Understanding the intricate linkage between climate warming and the hydrological cycle is crucial for sustainable management of groundwater resources, especially in a vulnerable continent like Africa. This study investigates the relationship between climate‐change drivers and potential groundwater recharge (PGR) patterns across Africa for a long‐term record (1960–2010). Water‐balance components were simulated by using the PCR‐GLOBWB model and were reproduced in both gridded maps and latitudinal trends that vary in space with minima on the Tropics and maxima around the Equator. Statistical correlations between temperature, storm occurrences, drought, and PGR were examined in six climatic regions of Africa. Surprisingly, different effects of climate‐change controls on PGR were detected as a function of latitude in the last three decades (1980–2010). Temporal trends observed in the Northern Hemisphere of Africa reveal that the increase in temperature is significantly correlated to the decline of PGR, especially in the Northern Equatorial Africa. The climate indicators considered in this study were unable to explain the alarming negative trend of PGR observed in the Sahelian region, even though the Standardized Precipitation‐Evapotranspiration Index (SPEI) values report a 15% drought stress. On the other hand, increases in temperature have not been detected in the Southern Hemisphere of Africa, where increasing frequency of storm occurrences determine a rise of PGR, particularly in southern Africa. Time analysis highlights a strong seasonality effect, while PGR is in‐phase with rainfall patterns in the summer (Northern Hemisphere) and winter (Southern Hemisphere) and out‐of‐phase during the fall season. This study helps to elucidate the mechanism of the processes influencing groundwater resources in six climatic zones of Africa, even though modelling results need to be validated more extensively with direct measurements in future studies. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
102.
Critical rainfall statistics for predicting watershed flood responses: rethinking the design storm concept 下载免费PDF全文
下载免费PDF全文 Recent advances have been made to modernize estimates of probable precipitation scenarios; however, researchers and engineers often continue to assume that rainfall events can be described by a small set of event statistics, typically average intensity and event duration. Given the easy availability of precipitation data and advances in desk‐top computational tools, we suggest that it is time to rethink the ‘design storm’ concept. Design storms should include more holistic characteristics of flood‐inducing rain events, which, in addition to describing specific hydrologic responses, may also be watershed or regionally specific. We present a sensitivity analysis of nine precipitation event statistics from observed precipitation events within a 60‐year record for Tompkins County, NY, USA. We perform a two‐sample Kolmogorov–Smirnov (KS) test to objectively identify precipitation event statistics of importance for two related hydrologic responses: (1) peak outflow from the Six Mile Creek watershed and (2) peak depth within the reservoir behind the Six Mile Creek Dam. We identify the total precipitation depth, peak hourly intensity, average intensity, event duration, interevent duration, and several statistics defining the temporal distribution of precipitation events to be important rainfall statistics to consider for predicting the watershed flood responses. We found that the two hydrologic responses had different sets of statistically significant parameters. We demonstrate through a stochastic precipitation generation analysis the effects of starting from a constrained parameter set (intensity and duration) when predicting hydrologic responses as opposed to utilizing an expanded suite of rainfall statistics. In particular, we note that the reduced precipitation parameter set may underestimate the probability of high stream flows and therefore underestimate flood hazard. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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以甘肃省陇西站月降水资料为例,应用9种3维Archimedean Copulas函数构造了干旱历时、干旱烈度和烈度峰值的联合概率分布,并进行了多变量的拟合优度评价,利用优选出的3维非对称型M12 Copula函数,计算联合分布的重现期以及不同组合下的条件概率与条件重现期。结果表明,M12Copula函数可以描述干旱历时、干旱烈度和烈度峰值间的联合分布。由于Copula函数能够用来构建不同边缘分布的联合分布,可以获得变量间不同组合下的重现期,因而能够更全面客观地反映干旱的特征,是描述干旱多变量分布的一种有效途径。 相似文献
107.
位于中亚造山带与塔里木克拉通结合部位的新疆库鲁克塔格是研究中亚造山带及塔里木克拉通关系的一个关键地区。野外观测、显微构造分析以及Ar–Ar测年结果揭示:(1)库鲁克塔格地区震旦纪—早古生代岩系地层变形样式为底部强烈褶皱,面理密集向北缓倾,顶部褶皱较宽缓、劈理稀疏向北陡倾,构成具有向南构造指向的铲式构造样式;(2)库鲁克塔格地区基底与盖层之间存在一条E–W走向、厚度约2 km的韧性滑脱带,带内普遍发育糜棱岩及A型剪切褶皱等,糜棱岩面理向N或S缓倾、拉伸线理向NW或SE倾伏,不对称旋转构造及糜棱岩中石英晶格优选方位图(EBSD测试)指示韧性滑脱带上盘滑脱方向为自NW向SE;(3)韧性滑脱带中糜棱岩内白云母的Ar–Ar测年结果表明滑脱时代早于383 Ma。滑脱–褶皱构造是塔里木地块与中天山岩浆弧带碰撞后发生陆内俯冲的产物,说明塔里木盆地东北缘库鲁克塔格存在早古生代造山事件。 相似文献
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针对强震能否预测以及如何预测的科学难题,建立孕震断层多锁固段脆性破裂理论,发现强震孕育过程的指数规律：sf（k）=1.48ksc,其中sf（k）和sc分别为第k个锁固体断裂点与第一个锁固段膨胀起点对应的累加Be-nioff应变,可以利用锁固段在其变形膨胀点处开始发生的震群事件（加速性地震活动前兆）预测未来大震,并给出了强震四要素相关预测方法。通过对诸多历史强震（如邢台地震、海城地震、汶川地震、玉树地震等）的回溯性检验分析表明：强震可以预测,且其孕震过程都遵循着上述简单的共性力学规律。在此基础上,归纳出4种典型强震的孕震模式,即大震震级呈＂大—小—大＂型,大震震级呈连续上升型,锁固段快速连续破裂型与标准型。此外,根据相关强震预测理论方法,对有关抗震救灾未来研究的方向提出如下建议：建议加强活动断裂位置精确定位、性质判定的地震地质研究,并开展孕震区锁固段（闭锁区域）判识的地质与地球物理研究等。 相似文献
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