基于分布式水文模拟的三峡区间洪水预报(Ⅰ)——模型构建及验证

长江三峡区间因暴雨形成的洪水峰高量大,对三峡水库的防洪安全和运行调度的影响很大.本论文依据三峡地区的地形地貌特征,采用基于GIS的机理性分布式水文模型,来模拟三峡区间入库洪水,以尽量减少洪水预报中的不确定性.利用近期建成的78个自动雨量站网监测的小时降雨信息作为模型的输入,对模型参数进行了率定和验证,结果表明:大多数洪水过程的模拟精度较好,但也有的模拟结果较差,其中降雨信息缺失是洪水预报不确定性的主要来源.     

Spatial plans and urban development trajectory in Kumasi,Ghana

This research uses empirical data to explore the link between spatial plans and ‘actual development’ occurring in Kumasi, Ghana. The research found that urban development is determined by both spatial plans and spontaneous informal development patterns (i.e. self-organisation). However, self-organisation is more widespread compared to spatially planned neighbourhoods. This phenomenon was expressed in a context of uncertainty created by weak institutional planning system which promote and reinforce haphazard development disregarding urban planning requirements. These findings provide a perspective on urban development that differs from that occurring in cities of developed countries, where planning institutions in consultation with urban residents determine the patterns of urban development. Unfortunately in Kumasi, self-organisation is not viewed as important in mainstream planning system. The paper concludes that more needs to be done in terms of understanding self-organisation processes, and the way they could be integrated into mainstream planning process to respond more fully to the urban development challenges in Kumasi.     

Some characteristics of very heavy rainfall over Orissa during summer monsoon season

Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing 20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the monsoon months and the season as a whole.     

中国点暴雨量极值的分布

暴雨极值是大型水利工程设计洪水重要依据之一。本文根据中国暴雨资料讨论了点暴雨量极值的主要内容,包括最大24小时点暴雨量、各历时最大点雨量、暴雨极值的季节变化;给出了大量最大点雨量记录图表;探讨了全国暴雨极值的地域分布规律及其影响因素。     

Inter-annual variability of summer monsoon rainfall over Orissa (India) in relation to cyclonic disturbances

The summer monsoon rainfall over Orissa, a state on the eastern coast of India, is more significantly related than Indian summer monsoon rainfall (ISMR) to the cyclonic disturbances developing over the Bay of Bengal. Orissa experiences floods and droughts very often due to variation in the characteristics of these disturbances. Hence, an attempt was made to find out the inter-annual variability in the rainfall over Orissa and the frequencies of different categories of cyclonic disturbances affecting Orissa during monsoon season (June–September). For this purpose, different statistical characteristics, such as mean, coefficient of variation, trends and periodicities in the rainfall and the frequencies of different categories of cyclonic disturbances affecting Orissa, were analysed from 100 years (1901–2000) of data. The basic objective of the study was to find out the contribution of inter-annual variability in the frequency of cyclonic disturbances to the inter-annual variability of monsoon rainfall over Orissa. The relationship between summer monsoon rainfall over Orissa and the frequency of cyclonic disturbances affecting Orissa shows temporal variation. The correlation between them has significantly decreased since the 1950s. The variation in their relationship is mainly due to the variation in the frequency of cyclonic disturbances affecting Orissa. The variability of both rainfall and total cyclonic disturbances has been above normal since the 1960s, leading to more floods and droughts over Orissa during recent years. The inter-annual variability of seasonal rainfall over Orissa and the frequency of cyclonic disturbances affecting Orissa during monsoon season show a quasi-biennial oscillation period of 2–2.8 years. There is least impact of El Nino southern oscillation (ENSO) on inter-annual variability of both the seasonal rainfall over Orissa and the frequencies of monsoon depressions/total cyclonic disturbances affecting Orissa.     

降雨因子对湖北省山地灾害影响的分析

根据湖北省1950～2003年726个山洪地质灾害样本,分析了其时空分布特征。滑动t-检验显示,逐年灾害数在1974年、1988年前后出现两次显著性突变增多（其中山洪、滑坡增多最明显）,逐年降雨量也相应有两次增加,二者相关系数可达0.3。表明我省年降雨量趋势性增加是灾害增多的主要诱因。进一步分析表明,暴雨以上强降雨是山洪、滑坡、泥石流、塌陷的主要诱因,连阴雨是崩塌的主要诱因,同时对滑坡、泥石流、塌陷有重要影响,对山洪灾害影响则较小。     

Geomorphic Effects of Monsoon Floods on Indian Rivers

The southwest summer monsoon contributesthe bulk of India's rainfall. Consequently,almost all the geomorphic work by the rivers is carried out during the monsoonseason in general and the monsoon floods in particular. Indian rivers arecharacterized by high average flood discharges and large temporal variability. Thereis also significant spatial variation in the magnitude, frequency and power of floods, on account of regional variations in monsoon rainfall, basin characteristics andchannel geometry. As a result, the channel responses and the geomorphic effects also varyspatially. This paper describes the hydrological and geomorphological aspects, as well asthe geomorphic effects of monsoon floods in the Indian rivers. The geomorphic effects of floods are most impressive only in certainareas – the Himalaya, the Thar Desert, and the Indus-Ganga-Brahmaputra Plains. There are numerous instances of flood-induced changes in the channel dimension,position and pattern in these areas. In the Ganga-Brahmaputra Plains, the annualfloods appear to be geomorphologically more effective than the occasional large floods.In comparison, the rivers of the Indian Peninsula are, by and large, stable and thegeomorphic effects of floods are modest. Only large-magnitude floods that occur at aninterval of several years to decades are competent to modify the channel morphology in asignificant way. A synthesis of the various case studies available from the Indianregion indicates that often the absolute magnitude of a flood is not as important withrespect to the geomorphic effects as the flow stress and competence.     

淮河流域近500年洪旱事件演变特征分析

为了认识淮河流域过去500年洪旱事件发生规律并鉴别当前的洪旱情势,收集并对比分析了流域实测降雨资料、重建历史雨季降雨资料、历史旱涝等级资料、历史洪旱文献记录和历史调查洪水资料等多源洪旱灾害数据。以重建历史雨季降雨资料和历史旱涝等级资料为主要依据,通过滑动平均、频率计算、小波分析和突变检验等方法,分析流域过去500年洪水干旱时空分布特征和演变规律。结果表明,17世纪淮河流域洪旱灾害最严重,但20世纪极端洪旱事件发生频次最多。淮河流域洪旱事件存在40年左右的稳定长周期,主周期从18世纪的15~20年逐渐减少到19世纪的5年周期,近20年来出现2~3年的主周期,洪旱灾害事件呈增加趋势,流域社会经济发展面临着严峻的洪旱灾害威胁。     

黄土地区小流域降雨空间变化特征分析

利用黄土地区雨量站网较密,控制条件较好的小流域资料,统计分析了5min、15min、30min、60min时段降雨及次降雨空间变化的点面关系、频率特征及结构特征,研究了时段降雨分布同次降雨分布的内在联系,为进一步在产流模拟计算中的应用提供了基础。     

Spatial variability of rainfall trends in Iran

The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts.     

Hydrologic behavior and flood probability for selected arid basins in Makkah area, western Saudi Arabia

In arid regions, flash floods often occur as a consequence of excessive rainfall. Occasionally causing major loss of property and life, floods are large events of relatively short duration. Makkah area in western Saudi Arabia is characterized by high rainfall intensity that leads to flash floods. This study quantifies the hydrological characteristics and flood probability of some major wadis in western Saudi Arabia, including Na’man, Fatimah, and Usfan. Flood responses in these wadis vary due to the nature and rainfall distribution within these wadis. Rainfall frequency analysis was performed using selected annual maximums of 24-h rainfall from eight stations located in the area. Two of the most applied methods of statistical distribution, Gumbel’s extreme value distribution and log Pearson type III distribution, were applied to maximum daily rainfall data over 26 to 40 years. The Gumbel’s model was found to be the best fitting model for identifying and predicting future rainfall occurrence. Rainfall estimations from different return periods were identified. Probable maximum floods of the major wadis studied were also estimated for different return periods, which were extrapolated from the probable maximum precipitation.     

An integrated flood risk assessment model for property insurance industry in Taiwan

Taiwan is located in an area affected by Northwest Pacific typhoons, which are also one of the most important sources of rainfall to the island. Unfortunately, the abundant rainfall brought by typhoons frequently produces hazards. In recent years, typhoons and floods have caused serious damage, especially Typhoon Morakot in 2009. In this study, a probabilistic model is developed based on historical events which can be used to assess flood risk in Taiwan. There are 4 separate modules in this model, including a rainfall event module, a hydraulic module, a vulnerability module, and a financial loss module. Local data obtained from the Taiwan government are used to construct this model. Historical rainfall data for typhoon and flood events that have occurred since 1960, obtained from the Central Weather Bureau, are used for computing the maximum daily rainfall for each basin. In addition, the latest flood maps from the Water Resources Agency are collected to assess the probable inundation depth. A case study using the local data is carried out. Assessment is made to predict possible economic loss from different financial perspectives such as the total loss, insured loss, and loss exceeding probabilities. The assessment results can be used as a reference for making effective flood risk management strategies in Taiwan.     

Influence of the spatial variability of shear strength parameters on rainfall induced landslides: a case study of sandstone slope in Japan

Rainfall-induced landslides frequently occur in humid temperate regions worldwide. Research activity in understanding the mechanism of rainfall-induced landslides has recently focused on the probability of slope failure involving non-homogeneous soil profiles. This paper presents probabilistic analyses to assess the stability of unsaturated soil slope under rainfall. The influence of the spatial variability of shear strength parameters on the probability of rainfall-induced slope failure is conducted by means of a series of seepage and stability analyses of an infinite slope based on random fields. A case study of shallow failure located on sandstone slopes in Japan is used to verify the analysis framework. The results confirm that a probabilistic analysis can be efficiently used to qualify various locations of failure surface caused by spatial variability of soil shear strength for a shallow infinite slope failure due to rainfall.     

Juggling through Ghanaian urbanisation: flood hazard mapping of Kumasi

More recently, driven by rapid and unguided urbanisation and climate change, Ghanaian cities are increasingly becoming hotspots for severe flood-related events. This paper reviews urbanisation dynamics in Ghanaian cities, and maps flood hazard zones and access to flood relief services in Kumasi, drawing insight from multi-criteria analysis and spatial network analysis using ArcGIS 10.2. Findings indicate that flood hazard zones in Kumasi have been created by natural (e.g., climate change) and anthropogenic (e.g., urbanisation) factors, and the interaction thereof. While one would have expected the natural factors to guide, direct and steer the patterns of urban development from flood hazard zones, the GIS analysis shows that anthropogenic factors, particularly urbanisation, are increasingly concentrating population and physical structures in areas liable to flooding in the urban environment. This situation is compounded by rapid land cover/use changes and widespread haphazard development across the city. Regrettably, findings show that urban residents living in flood hazard zones in Kumasi are also geographically disadvantaged in terms of access to emergency services compared to those living in well-planned neighbourhoods.     

Adaptation of climate variability/extreme in arid environment of the Arabian peninsula by rainwater harvesting and management

Water management in Saudi Arabia is facing major challenges due to the limited water resources and increasing uncertainties caused by climate change. The rainfall and temperature records of the Saudi meteorological data for more than three decades were analyzed for policy suggestions in water sectors based on the changing rainfall patterns. The trends in the annual aridity and rain indices were also examined to define the changing climate conditions and for determining the dry months in different cities of the Kingdom. An increased annual and maximum rainfall was observed for six cities while a decreasing trend in both annual and maximum rainfall was observed for the same number of cities highlighting the variability of rainfall in the whole region. An increasing maximum rainfall with decreasing annual rainfall was observed for the rest of the cities signifying the more extreme rainfall evens and resulting floods of short durations. The changing rainfall trends were also observed for different months during 31 years of the recorded period in addition to the varying climate pattern for different cities within the same district. Finally, these preliminary assessments of any systematic changes in view of the increased rain intensities and extreme climate events are viewed to demonstrate the value rainwater harvesting and management as a local adaptation to the climate variability and extreme in the Kingdom.     

Flood events, fatalities and damages in India from 1978 to 2006

High temporal and spatial variability of rainfall qualifies India to be highly vulnerable to floods. Recurring floods of various magnitudes play havoc with the lives and property of the people, leading to unplanned development and unchecked environmental degradation, thwarting and retarding the overall development of the country. Therefore, the purpose of the present study is to analyze the types and trends in terms of flood events, frequency, number of people killed, injured, missing and economic damage both in space and time on the basis of a nationwide database published by India Meteorological Department, Pune, from 1978 to 2006. Analysis of these long-term data has revealed that 2,443 flood events claimed about 44,991 lives with the average of 1,551 lives each year. In terms of population size, these figures translate into a loss of 1.5 human lives per million of the population. A majority (56 %) of flood fatalities were caused during severe flood events. However, the frequency of these events was just 19 % in comparison with heavy rainfall events (65 %). In spatial context, flood-related fatalities are distributed all over the country with highest fatalities in Uttar Pradesh (17 %), Maharashtra (13 %), and Bihar and Gujarat (10 % each). Most fatalities occurred during the summer season monsoon months of August (30 %) followed by July (29 %) and September (20 %). The country suffered a cumulative flood-related economic loss of about 16 billion US$ between 1978 and 2006 and a maximum economic loss of 1.6 billion US$ in the year 2000 alone. The study further suggests that both flood events and fatalities have increased in India over a period of time.     

利用MODIS fAPAR傅立叶时间序列分析研究植被光合作用活动对净辐射和降雨的响应：青藏高原个例研究

气候变化对植被动力学有非常大的影响。为了定量描述气候变化对植被的影响，文章利用MODIS fAPAR 数据和NCEP 的净辐射和降雨再分析数据对青藏高原地区气候变化对植被的影响进行了时间序列分析。研究所用的数据时间跨度为2000年至2005年。首先利用NCEP 再分析数据建立了干旱度因子的时间序列，为了与MODIS fAPAR 具有相同的时间采样间隔，由NCEP的日净辐射和日降雨量得到每8天的平均净辐射和8日降雨的和。根据一定时间间隔的净辐射与降雨量的比可以用来衡量相对于可利用水分的剩余能量，因此该比值也是干旱灾害的度量。其次，对MODIS fAPAR 的傅立叶时间序列分析提供了两个植被光合作用对干旱相应的因子，即fAPAR的年平均值及其年振幅值。在时间和空间尺度上对植被光合作用活动与干旱指数之间的关系进行了定量分析。对湿年和干年之间的响应差异进行了比较。研究表明较干地区对气候变化的响应最为显著。分析应该扩展到更长的时间跨度以便更加有效地在时间和空间尺度上评估气候变化对植被动力学的影响。     

Early warning system for detection of urban pluvial flooding hazard levels in an ungauged basin

Prolonged and high intensity rainfall often saturates urban drainage systems and generates urban pluvial flooding, resulting in hazardous flash floods. The city most affected by urban flooding in Colombia (South America) is Barranquilla since lacks a proper storm water drainage system. Heavy rainfall produces flash floods to quickly become torrential streams that flow down the streets endangering pedestrians. This research describes a low-cost early warning system (EWS) to detect in real time the hazard level of a stream in an ungauged basin. The EWS indicates whether it is safe or not for pedestrians to cross a flooded street, based on certain criteria used to assess the hazard level of the torrent. A hydrological and hydraulic model calculates the flow, velocity and water level in all cross sections along the stream. The model uses only real-time measurements of rain gauges and topographic survey data to determine the hazard level. Finally, a wireless sensor network sends the alert to a web platform and warns the community in real time.

     

Riverine flood assessment in Jhang district in connection with ENSO and summer monsoon rainfall over Upper Indus Basin for 2010

Pakistan has experienced severe floods over the past decades due to climate variability. Among all the floods, the flood of 2010 was the worst in history. This study focuses on the assessment of (1) riverine flooding in the district Jhang (where Jhelum and Chenab rivers join, and the district was severely flood affected) and (2) south Asiatic summer monsoon rainfall patterns and anomalies considering the case of 2010 flood in Pakistan. The land use/cover change has been analyzed by using Landsat TM 30 m resolution satellite imageries for supervised classification, and three instances have been compared, i.e., pre-flooding, flooding, and post-flooding. The water flow accumulation, drainage density and pattern, and river catchment areas have been calculated by using Shutter Radar Topography Mission digital elevation model 90 m resolution. The standard deviation of south Asiatic summer monsoon rainfall patterns, anomalies and normal (1979–2008) has been calculated for July, August, and September by using rainfall data set of Era interim (0.75° × 0.75° resolution). El Niño Southern Oscillation has also been considered for its role in prevailing rainfall anomalies during the year 2010 over Upper Indus Basin region. Results show the considerable changing of land cover during the three instances in the Jhang district and water content in the rivers. Abnormal rainfall patterns over Upper Indus Basin region prevailed during summer monsoon months in the year 2010 and 2011. The El Niño (2009–2010) and its rapid phase transition to La Niña (2011–2012) may be the cause of severity and disturbances in rainfall patterns during the year 2010. The Geographical Information System techniques and model based simulated climate data sets have been used in this study which can be helpful in developing a monitoring tool for flood management.     

Investigating the impacts of typhoon-induced floods on the agriculture in the central region of Vietnam by using hydrological models and satellite data

Flooding associated with landing tropical cyclones (TCs) is one of the major natural hazards in the coastal region of Vietnam. Annually, approximately 5 or 6 TCs make landfall in Vietnam, bringing heavy rains and inducing flooding, particularly to the central coastal region because of its topography and geographic configuration. This study focuses on the modelling of typhoon-induced floods that have resulted in widespread damage to agriculture over the central Thua Thien Hue Province of Vietnam by coupling two well-known hydrological models, KINEROS2 and HEC-RAS (Daniel et al. in Open Hydrol J 5(1), 2011), and using GSMaP (Global Satellite Mapping of Precipitation) data as the satellite rainfall input. Landsat imagery and GIS are also used for mapping and analysing the inundated areas. The discharge and water level from the KINEROS2 and HEC-RAS models displayed acceptable results for the floods modelled from three selected typhoons; both the Nash–Sutcliffe simulation efficiency coefficient (NSE) and the coefficient of determination (R²) were greater than 0.6. The simulated inundation maps of these typhoon-induced floods were compared with those extracted from the Landsat imagery to assess consistency. The result revealed a similar spatial extension of the inundated agricultural areas. This information, together with the forecasted TC movements and associated rainfalls, will be helpful to plan methods for mitigating potential typhoon-induced flooding and damage, particularly damage to agricultural regions.