西北东部极端降水事件及异常旱涝季节变化倾向   总被引：16，自引：10，他引：6  

赵庆云  赵红岩  刘新伟 《中国沙漠》2006,26(5):745-749

利用西北地区东部100个气象观测站1960\_2000年逐日降水资料,对降水、极端降水事件及异常旱涝区域面积的季节变化倾向进行了分析。结果表明:春、秋、冬季,虽然极端降水事件频次的变率小于降水距平百分率的变率,但两者的变化趋势一致,春、秋季呈上升趋势,冬季呈下降趋势,表明极端降水事件出现的多与少,基本决定了季节降水趋势的变化;夏季,暴雨出现的多与少不能完全决定夏季降水量的趋势,而大雨频次的变化趋势与降水距平百分率的变化趋势一致,略呈上升趋势。夏季降水异常偏少的区域面积呈减少趋势,表明干旱发生的区域面积缩小了;秋季降水异常偏少的区域面积从20世纪80年代中期开始明显的扩大,表明干旱发生的区域面积增大了;春、冬季,降水异常偏多、偏少的区域面积是对称变化的,即降水异常偏多的区域面积增多,则异常偏少的区域面积减少;反之亦然。  相似文献   

基于遗传算法的理想区间法在洪水灾情评价中的应用   总被引：8，自引：0，他引：8  

金菊良  张礼兵  魏一鸣 《地理科学》2004,24(5):586-590

洪水灾情评价的实质就是建立各洪水灾情评价指标与洪水灾情等级之间的非线性关系,目前在实际评价过程中反映这种关系的信息来源只有洪水灾情评价标准,而后者一般是以区间形式表示的。基于此,提出了基于加速遗传算法的改进理想区间法(AGAIIM)。AGAIIM直接由洪水灾情评价标准样本数据驱动,把利用全部隶属度值信息进行计算的洪水灾情相对等级值作为洪水灾情的评价结果,可避免应用最大隶属度原则进行判断所可能造成的失真,提高了洪水灾情评价的精度。AGAIIM方法直观、简便、通用,可在具有评价标准或具有已知评价指标值及其等级值样本系列的系统综合评价中推广应用。  相似文献   

两汉时期黄河水患与中游土地利用之关系   总被引：11，自引：0，他引：11  

王尚义 《地理学报》2003,58(1):73-82

对史料重新进行了综合分析和解读,结合现代水文、地貌、土壤侵蚀的观测研究成果,就两汉黄河下游水患和中游土地利用方式的环境后果,提出了新的观点：(1)《后汉书》有关水患的记载简单笼统,但对伊洛河洪灾记载相对详细。当时伊洛河曾多次发生大水,甚至发生淹及洛阳城门和皇家园林的特大洪水,这些洪水涌入黄河干流同样可能导致下游水患;(2)自AD11河决魏郡后,一直到AD69王景治河的58年间,下游既未堵塞决口也未大规模治理,洪水来时任由泛滥。显然《后汉书》中没有具体记载是有意或无意漏记;(3) 对史籍中东汉大水、水出等记载逐年逐次排查,发现东汉水患频率高于西汉,灾情也更为严重。王景新河仅使下游安定了36年而非过去认为的800年或83年;(4) 东汉时期中游农耕人口比西汉减少近3/4,而河口镇至龙门间农耕人口减少九成以上,同时迁入大量游牧民族。原始游牧对天然植被破坏极大,是造成东汉黄河下游水患加剧的主要原因。  相似文献   

三峡工程建设背景下的洞庭湖区治水方略探讨   总被引：8，自引：1，他引：7  

贺清云  朱翔 《地理研究》2003,22(2):160-168

在长江三峡工程建设的大背景下,本文分析了洞庭湖区的水灾减灾机制,探讨了洞庭湖区的治水方略,提出应充分发挥三峡水库的调蓄功能,协调江湖关系,改善冲淤关系,加强水利工程建设,实现三峡水库与湖南四水水库的优化调度  相似文献   

长沙市防洪建设中若干重要问题探讨     

毛德华  夏军  龚重惠 《地理研究》2003,22(6):716-724

探讨了全国重点防洪城市长沙市防洪建设中的若干重要问题:防洪标准、设计洪水位、防洪大堤高度等的确定;建设方针与程序、整体防洪能力建设、防洪建设与基础设施建设和景观建设协调发展等。长沙设计洪水位的确定应综合考虑以下几个方面:湘江长沙段洪水与其支流和东洞庭湖洪水不存在高标准洪水同期遭遇问题,更不存在同频率洪水遭遇问题;湘江洪水流量与水位关系不是长沙洪水设计的主要依据;而南洞庭湖洪水位顶托和河道槽蓄量减少是影响长沙洪水位高低的动、静态因素。目前,长沙城市堤防设防高度偏高,减少了大堤的稳定性,造成了无效投资,影响了城市景观。防洪工程建设应分期实施、先除险后加固、注重整体防洪能力的提高,并处理好与城市基础设施建设和景观建设的关系。  相似文献   

Identification of flood seasonality and drivers across Canada     

Jitendra Singh  Subimal Ghosh  Slobodan P. Simonovic  Subhankar Karmakar 《水文研究》2021,35(10):e14398

Floods are the most frequently occurring natural hazard in Canada. An in-depth understanding of flood seasonality and its drivers at a national scale is essential. Here, a circular, statistics-based approach is implemented to understand the seasonality of annual-maximum floods (streamflow) and to identify their responsible drivers across Canada. Nearly 80% and 70% of flood events were found to occur during spring and summer in eastern and western watersheds across Canada, respectively. Flooding in the eastern and western watersheds was primarily driven by snowmelt and extreme precipitation, respectively. This observation suggests that increases in temperature have led to early spring snowmelt-induced floods throughout eastern Canada. Our results indicate that precipitation (snowmelt) variability can exert large controls on the magnitude of flood peaks in western (eastern) watersheds in Canada. Further, the nonstationarity of flood peaks is modelled to account for impact of the dynamic behaviour of the identified flood drivers on extreme-flood magnitude by using a cluster of 74 generalized additive models for location scale and shape models, which can capture both the linear and nonlinear characteristics of flood-peak changes and can model its dependence on external covariates. Using nonstationary frequency analysis, we find that increasing precipitation and snowmelt magnitudes directly resulted in a significant increase in 50-year streamflow. Our results highlight an east–west asymmetry in flood seasonality, indicating the existence of a climate signal in flood observations. The understating of flood seasonality and flood responses under the dynamic characteristics of precipitation and snowmelt extremes may facilitate the predictability of such events, which can aid in predicting and managing their impacts.  相似文献   

Validation of the Flood‐PROOFS probabilistic forecasting system          下载免费PDF全文

P. Laiolo  S. Gabellani  N. Rebora  R. Rudari  L. Ferraris  S. Ratto  H. Stevenin  M. Cauduro 《水文研究》2014,28(9):3466-3481

Probabilistic hydrometeorological forecasting systems are becoming more and more an operational tool used by civil protection centres for issuing flood alerts. One of the most important requests of decision makers is related to the reliability of such systems and to the validation of their predictive performances. For these reasons, this work is devoted to the validation of a probabilistic flood forecasting system called Flood‐PRObabilistic Operational Forecasting System (Flood‐PROOFS). The system is operational in real time, since 2008, in Valle d'Aosta, an alpine Region of northern Italy. It is used by the Civil Protection regional service to issue warnings and by the local water company to protect its facilities. The system manages and uses both real‐time meteorological and satellite data and real‐time data on the operation of the control structures in dam and river, managed by the water company. It has proven a useful tool for flood forecasting and for managing complex situations, facilitating the dialogue between civil protection and the water company during crisis periods. The system uses both a limited area model forecast and a forecast issued by regional expert meteorologists. The main outputs are deterministic and probabilistic discharge forecasts in different outlet areas of the river network. The performance of the system has been evaluated on a 25 months period with different statistical methods such as Brier score and Rank histograms. The results highlight good performances of the system as support system for emitting warnings, but there is a lack of statistics especially for huge discharge events. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

A stochastic framework to assess the performance of flood warning systems based on rainfall‐runoff modeling          下载免费PDF全文

J. Yazdi  S. A. A. Salehi Neyshabouri  S. Golian 《水文研究》2014,28(17):4718-4731

Nowadays, Flood Forecasting and Warning Systems (FFWSs) are known as the most inexpensive and efficient non‐structural measures for flood damage mitigation in the world. Benefit to cost of the FFWSs has been reported to be several times of other flood mitigation measures. Beside these advantages, uncertainty in flood predictions is a subject that may affect FFWS's reliability and the benefits of these systems. Determining the reliability of advanced flood warning systems based on the rainfall–runoff models is a challenge in assessment of the FFWS performance which is the subject of this study. In this paper, a stochastic methodology is proposed to provide the uncertainty band of the rainfall–runoff model and to calculate the probability of acceptable forecasts. The proposed method is based on Monte Carlo simulation and multivariate analysis of the predicted time and discharge error data sets. For this purpose, after the calibration of the rainfall–runoff model, the probability distributions of input calibration parameters and uncertainty band of the model are estimated through the Bayesian inference. Then, data sets of the time and discharge errors are calculated using the Monte Carlo simulation, and the probability of acceptable model forecasts is calculated by multivariate analysis of data using copula functions. The proposed approach was applied for a small watershed in Iran as a case study. The results showed using rainfall–runoff modeling based on real‐time precipitation is not enough to attain high performance for FFWSs in small watersheds, and it seems using weather forecasts as the inputs of rainfall–runoff models is essential to increase lead times and the reliability of FFWSs in small watersheds. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Fluvial transport of suspended sediment and organic carbon during flood events in a large agricultural catchment in southwest France     

Chantha Oeurng  Sabine Sauvage  Alexandra Coynel  Eric Maneux  Henri Etcheber  José‐Miguel Sánchez‐Pérez 《水文研究》2011,25(15):2365-2378

Water draining from a large agricultural catchment of 1 110 km² in southwest France was sampled over an 18‐month period to determine the temporal variability in suspended sediment (SS) and dissolved (DOC) and particulate organic carbon (POC) transport during flood events, with quantification of fluxes and controlling factors, and to analyze the relationships between discharge and SS, DOC and POC. A total of 15 flood events were analyzed, providing extensive data on SS, POC and DOC during floods. There was high variability in SS, POC and DOC transport during different seasonal floods, with SS varying by event from 513 to 41 750 t; POC from 12 to 748 t and DOC from 9 to 218 t. Overall, 76 and 62% of total fluxes of POC and DOC occurred within 22% of the study period. POC and DOC export from the Save catchment amounted to 3090 t and 1240 t, equivalent to 1·8 t km^?2 y^?1 and 0·7 t km^?2 y^?1, respectively. Statistical analyses showed that total precipitation, flood discharge and total water yield were the major factors controlling SS, POC and DOC transport from the catchment. The relationships between SS, POC and DOC and discharge over temporal flood events resulted in different hysteresis patterns, which were used to deduce dissolved and particulate origins. In both clockwise and anticlockwise hysteresis, POC mainly followed the same patterns as discharge and SS. The DOC‐discharge relationship was mainly characterized by alternating clockwise and anticlockwise hysteresis due to dilution effects of water originating from different sources in the whole catchment. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

Confidence interval of real‐time forecast stages provided by the STAFOM‐RCM model: the case study of the Tiber River (Italy)          下载免费PDF全文

Silvia Barbetta  Tommaso Moramarco  Luca Brocca  Marco Franchini  Florisa Melone 《水文研究》2014,28(3):729-743

This study proposes a statistically based procedure to quantify the confidence interval (CI) to be associated to the stages forecast by a simple model called STAge FOrecasting Model‐Rating Curve Model (STAFOM‐RCM). This model can be used for single river reaches characterized by different intermediate drainage areas and mean wave travel times when real‐time stage records, cross section surveys and rating curves are available at both ends. The model requires, at each time of forecast, an estimate of the lateral contribution q_for between the two sections delimiting the reach. The CI of the stage is provided by analyzing the statistical properties of model output in terms of lateral flow, and it is derived from the CI of the lateral contribution q_for which, in turn, is set up by associating to each q_for the q_opt which allows STAFOM‐RCM to reproduce the exact observed stage. From an operative point of view, the q_for values are ranked in order of magnitude and subdivided in classes where the q_opt values can be represented through normal distributions of proper mean and variance from which an interval of selected confidence level for q_for is computed and transferred to the stage. Three river reaches of the Tiber river, in central Italy, are used as case study. A sensitivity analysis is also performed in order to identify the minimum calibration set of flood events. The CIs obtained are consistent with the level of confidence selected and have practical utility. An interesting aspect is that different CI widths can be produced for the same forecast stage since they depend on the estimate of q_for made at the time of forecast. Overall, the proposed procedure for CI estimate is simple and can be conveniently adapted for other forecasting models provided that they have physically based parameters which need to be updated during the forecast. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献