剪切波分裂中的快、慢波识别方法

本文改进了两种震相识别方法。用最大特征值法可识别快、慢剪切波到时,用波形识别算子法可确定快剪切波的到时及其序列。将两种方法结合起来,可比较和鉴别地震波的到时及其类型,从而可以避免将转换P波误认为快剪切波,达到最终确定剪切波到时及其序列的目的。以1985年禄劝Ms6.1地震为例,用上述方法进行了剪切波分裂的研究,结果与张性扩容各向异性假说是一致的。     

定点形变破年变异常自动识别应用研究

基于奇异谱分析算法,以新疆东风煤矿钻孔倾斜EW分量和巴里坤水平摆倾斜NS分量为例,在去除典型干扰及长周期趋势变化的基础上,拟合观测资料背景年变序列。对于残差时间序列,结合震例进行动态R值检验,自动提取破年变异常特征时段,递归求解出了最高R值评分对应的异常判定准则。进而自动识别出具有最佳映震效能的破年变异常时段,实现了破年变异常判定的自动化和定量化,提高了前兆异常信号识别的可靠性和准确性。     

基于加窗Hilbert变换的复偏振分析方法及其应用

考虑到传统Hilbert变换所隐含的无限长序列假设的实际局限性, 本文将多窗分析法引入到短时序列Hilbert变换中, 通过构建复协方差矩阵和对该矩阵的特征值与特征向量的求解, 获得三分量地震记录的时变偏振参数;基于不同波型的偏振特性与实测偏振参数, 采用线性_余弦权重函数或高斯权重函数自适应空间滤波, 识别与分离具有特定偏振特性的不同地震响应. 针对天然地震三分量记录的处理结果表明, 该方法在识别、分离具有特定偏振特性的不同地震响应方面具有一定的潜力.     

全球气候变化对新疆塔里木河流域水资源的可能性影响

结合77个气象站近50年的水文气象资料, 探讨了全球气候变化与塔里木河流域水资源变化间的相互关系. 通过参数和非参数检验, 发现了包括温度、降水和流量在内的水文时间序列的长期趋势. 检验了厄尔尼诺-南方涛动与3种时间序列间的可能联系. 研究结果表明, 在过去50年里, 温度在5%的置信水平下呈单调上升趋势, 降水也表现出了增加的趋势. 相应的时间序列在1986年附近有一个明显的跳跃, 这可能是气候变化影响的结果. 塔里木河源流区的径流量虽然呈现出明显的增加趋势, 但干流的径流量呈下降趋势. 研究结果表明, 厄尔尼诺-南方涛动与研究区内近50年的温度、降水、径流间不存在明显的联系. 塔里木河干流的水量缩减、河流干涸和生态系统恶化主要是人类活动造成的.     

北部湾5.1级强余震的短临预报

根据琼中、邕宁,广州等地磁台垂直分量日变形态“双低点”异常,地震序列缺震和地震迁移等方法,较成功地预报１９９５年３月２３日北部湾５．１级强余震。     

青海湖流域50年来(1956-2007年)河川径流量变化趋势——以布哈河和沙柳河为例

通过对青海湖流域布哈河和沙柳河50年来的河川径流量分析发现,布哈河和沙柳河年径流量50年来没有显著的变化趋势,这两条河流的河川径流量对青海湖水位下降所起的作用不明显;布哈河月平均流量的年际变化在1月、2月和3月有减少的趋势,沙柳河月平均流量的年际变化在1月、2月、4月和5月亦有减少的趋势;布哈河的径流量大于沙柳河的径流量,在55%-91%频率范围内,布哈河的径流量小于沙柳河的径流量,在其它频率范围内,布哈河的径流量显著大于沙柳河的径流量,在一年中,布哈河和沙柳河的月径流量具有显著的差异;布哈河来水丰沛期是20世纪60年代,贫乏期是90年代,70和80年代为平水期;沙柳河月径流量从20世纪60年代到90年代一直比较稳定,没有发生显著的变化.     

基于离散Gabor变换的磁暴识别

以地磁秒数据为研究对象,通过离散Gabor变换将时域的地磁数据转换至二维时频面,提取Gabor变换谱图的均值和方差作为特征值,使用支持向量机实现地磁正常数据与磁暴干扰数据的自动分类识别。对5个地磁台的200组地磁秒数据进行计算分析,结果表明该方法对测试样本数据的识别率可达94%。     

地电阻率的年变畸变异常分析

讨论分析了3种地电阻率年变畸变异常,即年变幅度增大型、年变幅度减小型、年变畸变混合型。并针对不同的异常给出了相关分析方法,为识别和使用这类异常提供了一定的思路和科学依据。     

顾及InSAR形变特征的斜坡灾害隐患早期识别遥感方法

广东省2020年在册地质灾害隐患点4744处，威胁24.95万人，但近年发生多起重大地质灾害并不在已发现的隐患点库内，全面识别排查潜在隐患仍是当前和今后一段时期防灾减灾重要任务之一。合成孔径雷达干涉测量区域范围大、形变反演灵敏度高，可以弥补传统地面调查及光学遥感技术不足。研究以广州黄埔区为例，采用2019年1月至2022年4月Sentinel-1A长时序雷达数据，综合利用SBAS-InSAR时序形变信息结合地形级实景三维模型解译风险斜坡，识别出研究区崩滑流斜坡变形潜在隐患风险84处，抽取15%比例开展外业调查5处具有显著形变的滑坡崩塌风险，证明该方法具有可行性，并对综合遥感识别地质灾害提出建议。     

地震事件的多重时空聚类算法研究

地震序列是一组在一定的时间和空间范围内连续发生的地震事件，其发震机制具有某种内在联系，包含着地震孕育、发生、发展过程的丰富信息，是研究地震孕育、发震构造、区域应力特征及地震活动趋势的重要依据.实际的地震序列经常在时间和空间上重叠并淹没在海量的背景地震事件中，使得准确高效地识别地震序列仍然存在难度.本文基于ST-DBSCAN和DBSCAN两种聚类算法，采用先松后紧的参数设置策略，通过多次聚类逐渐寻找最佳的地震序列的方法构建了多重时空聚类算法，并同时获得每一个地震序列的展布方向、持续时间、序列类型等地震序列的特征参数.通过对理论合成地震目录和六盘山及其邻区内的实际地震目录的测试表明，该算法不需要预先设置地震序列的个数，可以有效的识别小震群；避免使用时空耦合距离参数，使参数的设置更具有实际意义；采用多次聚类策略，提高了聚类的有效性和准确性；计算效率高节约内存，能够对数量庞大的地震目录进行聚类；能够获得地震序列的相关统计参数，为进一步的定量分析提供依据；能够在含有噪点的数据集中有效识别具有复杂时空分布的地震序列，解决了因发震构造形状复杂所造导致的震群分布复杂无法识别的问题.     

Simulated runoff responses to land use in the middle and upstream reaches of Taoerhe River basin,Northeast China,in wet,average and dry years

Study on runoff variations and responses can lay a foundation for flood control, water allocation and integrated river basin management. This study applied the Soil and Water Assessment Tool model to simulate the effects of land use on annual and monthly runoff in the Middle and Upstream Reaches of Taoerhe River basin, Northeast China, under the wet, average and dry climate conditions through scenario analysis. The results showed that from the early 1970s to 2000, land use change with an increase in farmland (17.0%) and decreases in forest (10.6%), grassland (4.6%) and water body (3.1%) caused increases in annual and monthly runoff. This effect was more distinct in the wet season or in the wet year, suggesting that land use change from the early 1970s to 2000 may increase the flood potential in the wet season. Increases in precipitation and air temperature from the average to wet year led to annual and monthly (March and from June to December) runoff increases, while a decrease in precipitation and an increase in air temperature from the average to dry year induced decreases in annual and monthly (all months except March) runoff, and moreover, these effects were more remarkable in the wet season than those in the dry season. Due to the integrated effects of changing land use and climate conditions, the annual runoff increased (decreased) by 70.1 mm (25.2 mm) or 197.4% (71.0%) from the average to wet (dry) year. In conclusion, climate conditions, especially precipitation, played an important role in runoff variations while land use change was secondary over the study area, and furthermore, the effects of changes in land use and/or climate conditions on monthly runoff were larger in the wet season. Copyright © 2012 John Wiley & Sons, Ltd.     

Separating the effects of climate change and human activities on runoff over different time scales in the Zhang River basin

Most studies on separating the effects of climate change and human activities on runoff are mainly conducted at an annual scale with few analyses over different time scales, which is especially essential for regional water resources management. This paper investigates the impacts of climate change and human activities on runoff changes at annual, seasonal and monthly time scales in the Zhang River basin in North China. Firstly, the changing trends and inflection point are analyzed for hydro-climatic series over different time scales. Then the hydrological modeling based method and sensitivity based method are used to separate the effects. The results show that the effect of climate change is stronger than that of human activities on annual runoff changes. However, the driving factors on runoff are different at seasonal scale. In the wet season, the effect of human activities on runoff, accounting for 57 %, is stronger than that of climate change, while in the dry season climate change is the dominant factor for runoff reduction and the contribution rate is 72 %. Furthermore, the effects of climate change and human activities on monthly runoff changes are various in different months. The separated effects over different time scales in this study may provide more scientific basis for the water resources adaptive management over different time scales in this basin.     

The role of climate change and human interventions in affecting watershed runoff responses

Identifying the role of the two main driving factors—climate change and human interventions—in influencing runoff processes is essential for sustainable water resources management. For this purpose, runoff regime change detection methods were used to divide the available hydroclimatic variables into a baseline and a disturbed period. We applied hydrological modelling and the climate elasticity of runoff method to determine the contribution of climate change and human interventions to changes in runoff. The hydrological model, SWAT, was calibrated during the baseline period and used to simulate the naturalized runoff pattern for the disturbed period. Significant changes in runoff in the study watershed were detected from 1982, suggesting that human interventions play a dominant role in influencing runoff. The combined effects of climate change and human interventions resulted in a 41.3 mm (23.9%) decrease in runoff during the disturbed period, contributing about 40% and 60% to the total runoff change, respectively. Furthermore, analysis of changes in land cover dynamics in the watershed over the past four decades supported these changes in runoff. Contrary to other decades, the discrepancy between naturalized and observed runoff was small in the 2010s, likely due to increased baseflow as a result of storage and/or release of excess water during the dry season. This study contributes to our understanding of how climate change and human interventions affect hydrological responses of watersheds, which is important for future sustainable water management and drought adaptation.     

Impact of climate change on water resources in southern Taiwan

This study investigates the impact of climate change on water resources in southern Taiwan. The upstream catchment of Shin-Fa Bridge station in the Kao-Pen Creek basin was the study area chosen herein. The historical trends of meteorological variables, such as mean daily temperature, mean daily precipitation on wet days, monthly wet days, and the transition probabilities of daily precipitation occurrence in each month, at the Kao-Hsiung meteorological station, near the catchments were detected using a non-parametric statistical test. The trends of these meteorological variables were then employed to generate runoff in future climatic conditions using a continuous rainfall–runoff model. The analytical results indicate that the transition probabilities of daily precipitation occurrence significantly influence precipitation generation, and generated runoff for future climatic conditions in southern Taiwan was found to rise during the wet season and decline during the dry season.     

Effects of snow-depth change on spring runoff in cryosphere areas of China

Based on snow-depth and measured runoff data in the 19 river basins of the cryosphere areas of China, changes in cold season snow depth (CSSD) and spring runoff, and the relationship between CSSD and spring runoff were analysed. Decreasing trends in CSSD were detected mainly in the plains (plateaus), while increasing trends were found mainly in the mountainous regions. Different combinations of precipitation and temperature may be responsible for these results. The response of spring runoff to CSSD change varied greatly under climate warming. The runoff in April and May was commonly affected by CSSD, while the runoff in March was less affected by CSSD, but more by the increasing temperature causing more snowmelt in March. Due to relatively greater snow accumulation in spring, the runoff during spring was less affected by CSSD in the southern Tienshan Mountains.     

基于径流分析的淮河流域汛期旱涝急转研究

本文基于淮河流域吴家渡水文监测站1950-2007年月径流量资料,通过定义长、短周期径流旱涝急转指数,分析了淮河流域汛期径流旱涝急转现象(分旱转涝和涝转旱两种类型),研究结果表明:1)长周期径流旱涝急转在1986年以前发生次数较多,而1986年以后发生次数相对较少;2)各相邻月间的短周期旱涝急转的年际振荡以6-7月最多,且其长期变化规律与长周期旱涝急转年际振荡变化相似;3)长、短周期旱涝急转频次呈现不断减少的趋势,但全旱和全涝频次则有增加的趋势;4)2000s汛期长周期旱转涝、短周期6-7月旱转涝有逐渐增加的趋势,分析认为这种旱涝急转变化是导致淮河流域汛期径流量增加的主要原因之一.     

Trend detection in hydrological time series by segment regression with application to Shiyang River Basin

Hydrological time series are generally subject to shift trends and abrupt changes. However, most of the methods used in the literature cannot detect both shift trends and abrupt changes simultaneously and have weak ability to detect multiple change points together. In this study, the segmented regression with constraints method, which can model both trend analysis and abrupt change detection, is introduced. The modified Akaike’s information criterion is used for model selection. As an application, the method is employed to analyse the mean annual temperature, precipitation, runoff and runoff coefficient time series in the Shiyang River Basin for the period from 1958 to 2003. The segmented regression model shows that the trends of the mean annual precipitation, temperature and runoff change over time, with different join (turning) points for different stations. The runoff pattern can potentially explained by the climate variables (precipitation and temperature). Runoff coefficients show slightly decreasing trends for Xiying, Huangyang, Gulang and Zamu catchments, slight increasing trends for Dongda and Dajing catchments and nearly no change for Xida catchment. No change points are found in runoff coefficient in all catchments.     

Trends in rainfall and runoff in the Blue Nile Basin: 1964–2003

Most of the water from the Nile originates in Ethiopia but there is no agreement on how land degradation or climate change affects the future flow in downstream countries. The objective of this paper is to improve the understanding of future conditions by analysing historical trends. During the period 1964–2003, the average monthly basin‐wide precipitation and monthly discharge data were collected and analysed statistically for two stations in the upper 30% of the Blue Nile Basin and monthly and 10‐day discharge data of one station at the Sudan–Ethiopia border. A rainfall–runoff model examined the causes for observed trends. The results show that, while there was no significant trend in the seasonal and annual basin‐wide average rainfall, significant increases in discharge during the long rainy season (June to September) were observed at all three stations. In the upper Blue Nile, the short rainy season flow (March to May) increased, while the dry season flow (October to February) stayed the same. At the Sudan border, the dry season flow decreased significantly with no change in the short rainy season flow. The difference in response was likely due to the construction of weir in the 1990s at the Lake Tana outlet that affected the upper Blue Nile discharge significantly but affected less than 10% of the discharge at the Sudan border. The rainfall–runoff model reproduced the observed trends, assuming that an additional 10% of the hillsides were eroded in the 40‐year time span and generated overland flow instead of interflow and base flow. Models concerning future trends in the Nile cannot assume that the landscape runoff processes will remain static. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulating the impacts of land-use and climate change on water resource availability for a large south Indian catchment

Abstract

A monthly rainfall-runoff model was calibrated for a large tropical catchment in southern India. Various land-use and climatic change scenarios were tested to assess their effects on mean annual runoff and assured water yield at the Bhavanisagar Reservoir in Tamil Nadu, India. The largest increase in runoff (19%) came from converting forest and savanna (the indigenous control scenario) to agriculture. Mean annual runoff decreased by 35% after conversion to commercial forest and 6% after partial conversion to tea plantations. The predicted climate scenarios of reduced dry season rainfall decreased the annual runoff by 5% while enhanced annual rainfall caused a 17% increase in runoff. Even if land-use and climate changes had relatively large effects on runoff, the changes in reservoir yield which can be assured every year, were often less severe. This was probably due to the buffering effect of the reservoir and variation in the mean annual runoff.     

Hydrological Response of Runoff to Climate Change of Typical Tributaries in Ebinur Lake Basin of Xinjiang

In recent years, the natural hydrology behaviors were greatly influenced by climate change. The relation between runoff and climate change are always the core of scientific hydrological study in arid region. This paper presents a multi-variate time series controlled auto-regressive (CAR) model based on hydrological and climatic data of typical tributaries Jinghe River in Ebinur Lake Basin of Xinjiang covering the period from 1957 to 2012. The aim is to study the climate change and its effects on runoff of the Jinghe River, Northwest China. The results showed the following: the runoff of the Jinghe River was unevenly distributed and has obvious seasonal changes throughout the year. It was concentrated in summer and has along dry season with less runoff. The monthly maximum river runoff was from June to September and accounted for 74% of annual runoff. The river runoff increased since the 1980s till the 1990s; in the 21st century there was a trend of decreasing. The oscillatory period of annual runoff series in the Jinghe River Basin was 21a and 13a, and these periods were more obvious, followed by 32a and 9a. The oscillation with a time scale of 21a and 13a was a fulltimed domain. The MRE is 6.54%, the MAE is 0.84 × 10⁸ m³, and the RMSE is 0.039. The CAR model passed the F-test and residual test, and the change trend of calculated and measured values of annual runoff is consistence, which means that the model was reasonable.