1990s长江流域降水趋势分析   总被引：2，自引：0，他引：2  

苏布达  姜彤  施雅风  Stefan BECKER  Marco GEMMER 《湖泊科学》2003,15(Z1):38-48

依据国家气象局提供的实测月降水和日降水资料,运用Mann-Kendall(M-K)非参数检验法验证了降水趋势,并通过空间插补法,由点扩展到面,分析了1990s长江流域降水变化特征,发现1990s长江流域降水变化以降水在时间和空间分布上的集中度的增加为主要特点:时间上,年降水的增加趋势以冬季1月和夏季6月降水的集中增加为主;一日降水量大于等于50mm的暴雨日数和暴雨量在1990s也有了较明显的增加.空间上,年降水、夏季降水、冬季降水的增加都以中下游区的增加为主,尤其以鄱阳湖水系、洞庭湖水系的降水增加为主.1990s长江流域春季和秋季降水的减少以5月和9月两个汛期月份的降水减少为主,除金沙江水系和洞庭湖水系等少数地区外,流域大部分地区降水呈减少趋势.上述1990s出现的降水趋势明显与近年来全球变暖背景下长江流域各地区不同的温度及水循环变异有关.  相似文献   

对长江宜昌站月平均径流量突变的分析     

江剑民  谷湘潜  游性恬 《湖泊科学》2003,15(Z1):131-137

本文简要叙述了一阶矩突变扫描式t检验和二阶矩突变扫描式F检验算法,并应用于长江宜昌水文站1882-2002年间历年月平均径流量的实测序列,划分出24个年际至十年际时间尺度的相对5级旱、涝时段及其变率特征,与有关长江上游洪水、干旱灾害的历史记载相吻合.  相似文献   

长江流域降水变化及其趋势演变   总被引：1，自引：0，他引：1  

Stefan BECKER  Marco GEMMER  姜彤 《湖泊科学》2003,15(Z1):123-130

本文对中国长江流域降水趋势进行了分析.指出对月降水量而言,20世纪后50年不同区域出现1不胃的降水趋势变化特征.趋势插补法研究表明中国降水时空分布趋势十分明显.对长江流域长期降水资料分析研究指出夏季月份降水时间更集中,而对年降水而言在一些站则表现出明显的周期变化.  相似文献   

1950s以来鄱阳湖流域降水变化趋势及其持续性特征     

霍雨  王腊春  陈晓玲  蒙海花 《湖泊科学》2011,23(3):454-462

以鄱阳湖流域1950s至2005年10个台站的日降水量为基础,采用距平分析、Mann-Kendall非参数检验对鄱阳湖流域1950s以来的年、季降水特征和变化趋势进行分析,并以此为基础,结合Hurat指数,从3年、5年、10年三个时间尺度上分析该流域未来降水的变化趋势.结果表明,鄱阳湖流域年内降水分配不均,年际变化较为...  相似文献   

长江口特大洪水浑浊带悬沙粒度分布特征     

董坚  何青  林建良  陈嘉民  周思敏  徐凡  谢卫明  郭磊城 《海洋通报》2023,(1):48-58

2020年长江流域发生了历史第二大洪水,大通站洪峰流量达到84 500 m3/s。本文基于2020年7月长江口特大洪水期间最大浑浊带多站位的水沙观测数据,重点分析了悬沙粒度组分的时空分布特征,并与常态水文条件下的粒度数据进行对比。结果表明：（1）最大浑浊带悬沙垂向平均中值粒径为10.4μm,变化范围为6～27μm,以黏性细颗粒泥沙为主;其中核心区南槽、北槽及北港的中值粒径分别为8.4μm、7.6μm和8.5μm,过渡区分别为7.2μm、16.4μm和14.5μm。（2）悬沙中值粒径垂向分布受不同组分影响,核心区底层中值粒径为8.8～9.6μm;底层黏土含量在28%～31%之间,粉砂含量在61%～64%之间,中值粒径主要受黏土及粉砂组分影响;过渡区北港和北槽垂向平均砂组分高达19%,南槽砂组分平均仅占5%,中值粒径主要受砂组分影响。（3）对比2013年洪季浑浊带数据,2020年粒径整体增大5.4μm,核心区黏土含量相较2013年减少12.7%,砂增加6.3%;过渡区北槽与北港平均粒径增大10μm。  相似文献   

石家庄地震前兆台网月评价系统     

周安聘  张环曦  董博 《地震地磁观测与研究》2017,38(4):225-230

基于VB语言,利用C/S架构,编写石家庄地震前兆台网月评价系统,设置不同功能单元,开展仪器运行监控、台网日常运维监控,通过界面选择相应日期,读取省前兆台网中心发布的《运行监控日报》等Excel文件,使用input box函数等在文本框中输入、统计、计算,并显示地震前兆台网月评价成绩及台网运行情况。  相似文献   

Spatio-temporal downscaling of projected precipitation in the 21st century: indication of a wetter monsoon over the Upper Mahanadi Basin,India     

Subbarao Pichuka 《水文科学杂志》2017,62(3):467-482

An attempt is made to assess the future trend of spatio-temporal variation of precipitation over a medium-sized river basin. The Statistical Downscaling Model (SDSM, version 4.2) is used to downscale the outputs from two general circulation models (GCMs) for three future epochs: epoch-1 (2011–2040), epoch-2 (2041–2070) and epoch-3 (2071–2100). Considering the Upper Mahanadi Basin as a test bed, the study results indicate a “wetter” monsoon (June–September) and the annual increase in precipitation is 12% during epoch-3, which is consistent for both GCMs. Monthly analyses indicate that the precipitation totals are likely to increase and the magnitude of increase is greater during monsoon months than non-monsoon months. The number of month-wise daily extremes increases in most months in the year. However, the maximum percentage increase (with respect to baseline period, 1971–2000) in the number of extreme events is found in the non-monsoon months (specifically before and after the monsoon).  相似文献   

Verification of short-term runoff forecasts for a small Philippine basin (Marikina)     

David Kneis  Catherine Abon  Axel Bronstert  Maik Heistermann 《水文科学杂志》2017,62(2):205-216

Storm runoff from the Marikina River Basin frequently causes flood events in the Philippine capital region Metro Manila. This paper presents and evaluates a system to predict short-term runoff from the upper part of that basin (380 km²). It was designed as a possible component of an operational warning system yet to be installed. For the purpose of forecast verification, hindcasts of streamflow were generated for a period of 15 months with a time-continuous, conceptual hydrological model. The latter was fed with real-time observations of rainfall. Both ground observations and weather radar data were tested as rainfall forcings. The radar-based precipitation estimates clearly outperformed the raingauge-based estimates in the hydrological verification. Nevertheless, the quality of the deterministic short-term runoff forecasts was found to be limited. For the radar-based predictions, the reduction of variance for lead times of 1, 2 and 3 hours was 0.61, 0.62 and 0.54, respectively, with reference to a “no-forecast” scenario, i.e. persistence. The probability of detection for major increases in streamflow was typically less than 0.5. Given the significance of flood events in the Marikina Basin, more effort needs to be put into the reduction of forecast errors and the quantification of remaining uncertainties.  相似文献   

Evaluation of nonlinear models for precipitation forecasting     

Abazar Solgi  Vahid Nourani  Mohammad Bagherian Marzouni 《水文科学杂志》2017,62(16):2695-2704

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.  相似文献   

Coupling snow accumulation and melt rate modules of monthly water balance models with the Jazim monthly water balance model     

Nadereh Tayefeh Neskili  Bahram Saghafian 《水文科学杂志》2017,62(14):2348-2368

Several models for simulation of water balance processes in semi-arid mountainous basins were developed by coupling different modules of existing water balance models (WBM). Snow accumulation and snowmelt rate relationships extracted from the McCabe-Markstrom, Guo, Rao-Al Wagdany and WASMOD-M WBMs, originally developed for basins with humid climate, were coupled with the Jazim WBM, primarily developed for arid basins. Karaj Basin, central Iran, with snowy autumn–winter and dry summer periods, was selected to assess model performance. The model parameters were optimized using a genetic algorithm (GA). All coupled models performed better than the non-modified (original) WBMs in the study basin. The coupled Jazim–McCabe-Markstrom model provided the best performance in simulating low and high monthly flows. It estimated the snowmelt runoff values more accurately than other proposed coupled models because the linear relationships used in the snow module of the McCabe-Markstrom model are more compatible with snow variations in the Karaj Basin.  相似文献