Flood frequency analysis of river swat using Log Pearson type 3, Generalized Extreme Value,Normal, and Gumbel Max distribution methods

In Pakistan, floods are among the most devastating and recurring natural hazards. Flood hazard assessment requires flood event magnitude and probability of occurrence. Flood frequency analysis is the most common technique used for the at-site estimation of flood recurrence magnitude. This paper evaluates four most commonly used distribution methods, i.e., Generalized Extreme Value (GEV), Log Pearson 3 (LP3), Gumbel Max, and Normal for the flood frequency and estimation of flood recurrence. Different hydrological stations data namely Khwazakhela, Chakdarra, Panjkora, and Munda Headwork located at Swat river was taken from Provincial Irrigation Department, Khyber Pakhtunkhwa. The analysis is done for 5-, 10-, 25-, 50-, and 100-year return periods by using annual maximum discharge data from 1980 to 2016 (37 yr). Three goodness-of-fit tests were applied to the fitted distributions, i.e., Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared at 5% significance level. Results indicate that LP3 and GEV were ranked top two distributions at all locations while Gumbel Max and Normal were the least fitted having rank 3 and 4, respectively. Based on the goodness-of-fit ranking, LP3 was selected for the estimation of flood magnitude and return periods at Khwazakhela. Designed hydrographs based on probabilistic approach and flood 2010 hydrograph are presented for flood simulation.     

Investigating the flood damages in Lower Indus Basin since 2000: Spatiotemporal analyses of the major flood events

While historically significant for ancient civilizations, the Indus basin is also known for its floods and complex anthropogenic management history. Resulting from years of modifications by the pre-British era Mughal rulers followed by the post-partition division of river waters among the two neighbors, India and Pakistan, Pakistan faces severe management and financial challenges of water management. This study investigates the intricacies arising from this complicated management doctrine for the lower Indus basin. A detailed remote sensing-based analysis of the significant floods to hit the lower Indus basin since 2000 has been provided. Flood years were identified, and Moderate Resolution Imaging Spectroradiometer (MODIS) data for the years 2003, 2005, 2006, 2010, 2011, 2012, 2015, and 2016 were used to map their spatiotemporal extents. Almost all the flood water accumulated in the north is released in one river channel of the lower Indus basin. Further, the challenges were exacerbated due to the excessive rainfall in 2011 and 2012 in southeastern Sindh. A trend analysis of rainfall data shows an increase in the southern basin in the last 21 years, particularly toward the central plains and Sindh Province. The floodwater accumulated in the lower basin for as many as?~?425 days on average, stretching to?~?800 days of stagnancy in some places. The water stagnation period has been the highest in the river floodplain, highly populated and cultivated. The analyses of the current study suggest that the riverine channel has been better managed after the 2010 floods; however, the monsoon’s shift in 2011 and 2012 led to widespread disaster in low-lying regions of Sindh Province.

     

Simulation of a flood producing rainfall event of 29 July 2010 over north-west Pakistan using WRF-ARW model

Simulation of a flood producing rainfall event of 29 July 2010 over north-west Pakistan has been carried out using the Weather Research and Forecasting (WRF) model. This extraordinary rainfall event was localized over north-west Pakistan and recorded 274 mm of rainfall at Peshawar (34.02°N, 71.58°E), within a span of 24 h on that eventful day where monthly July normal rainfall is only 46.1 mm. The WRF model was run with the triple-nested domains of 27, 9, and 3 km horizontal resolution using Kain–Fritsch cumulus parameterization scheme having YSU planetary boundary layer. The model performance was evaluated by examining the different simulated parameters. The model-derived rainfall was compared with Pakistan Meteorological Department–observed rainfall. The model suggested that this flood producing heavy rainfall event over north-west region of Pakistan might be the result of an interaction of active monsoon flow with upper air westerly trough (mid-latitude). The north-west Pakistan was the meeting point of the southeasterly flow from the Bay of Bengal following monsoon trough and southwesterly flow from the Arabian Sea which helped to transport high magnitude of moisture. The vertical profile of the humidity showed that moisture content was reached up to upper troposphere during their mature stage (monsoon system usually did not extent up to that level) like a narrow vertical column where high amounts of rainfall were recorded. The other favourable conditions were strong vertical wind shear, low-level convergence and upper level divergence, and strong vorticity field which demarked the area of heavy rainfall. The WRF model might be able to simulate the flood producing rainfall event over north-west Pakistan and associated dynamical features reasonably well, though there were some spatial and temporal biases in the simulated rainfall pattern.     

Space-based monitoring of severe flooding of a southern state in India during south-west monsoon season of 2018

Kerala, a southern state of India, experienced a severe flooding due to multi-day extreme rain events during July and August months of 2018. This disaster was one of the worst floods to hit the state and resulted in heavy losses of lives and property. Natural Disaster Management Authority of India reported that 483 people lost their lives and more than 50 lakhs population were affected severely. This short communication focuses on examining this flood event using satellite remote sensing. It is reported that Kerala received an excess of about 56% rainfall during July and August from multi-day extreme rainfall episodes. Few regions of Kerala received the rainfall in the range of 270–300 mm on August 14 and 15. Hourly rainfall events in the excess of 25 mm have also been reported during heavy rainy days. The present study reports that multi-day heavy rainy events during July and August brought an accumulated rainfall of about 1600 mm, which resulted in extreme flooding over Kerala.

     

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.     

山区小流域洪水分布模式模拟与危险性评估

流域暴雨山洪过程时空异质性强,准确评估雨洪变化特性和洪水危险性对山洪灾害防治具有重要意义。以7个降雨特征指标和6个洪水特征指标刻画流域场次雨洪特性,采用中国山洪水文模型和洪水频率指标相结合,模拟和评估口前流域洪水过程及其危险性。结果表明：场次洪水洪峰模数、洪峰时间偏度、高脉冲历时占比、涨落洪速率与降雨总量、平均雨量、最大雨强、雨峰位置系数、基尼系数等降雨特征指标显著相关,三场致灾洪水过程的降雨均呈现量级大、强度大、历时短、暴雨中心偏中下游的特点;率定期和验证期的平均径流深相对误差均在9%以内,平均洪峰流量相对误差均在11%以内,平均峰现时间误差均在1.7 h以内,平均Nash-Sutcliffe系数为0.80和0.76;各场次洪水有0.0%～93.3%的河段流量达到一般危险及以上等级,三场致灾洪水过程的危险性等级最高,分别有80.0%、35.0%和1.7%的小流域河段流量达到高危险及以上等级。研究可为山区小流域暴雨洪水危险性评估、灾害响应和复盘等提供技术支撑。     

Development of roughness updating based on artificial neural network in a river hydraulic model for flash flood forecasting

Flood is the worst weather-related hazard in Taiwan because of steep terrain and storm. The tropical storm often results in disastrous flash flood. To provide reliable forecast of water stages in rivers is indispensable for proper actions in the emergency response during flood. The river hydraulic model based on dynamic wave theory using an implicit finite-difference method is developed with river roughness updating for flash flood forecast. The artificial neural network (ANN) is employed to update the roughness of rivers in accordance with the observed river stages at each time-step of the flood routing process. Several typhoon events at Tamsui River are utilized to evaluate the accuracy of flood forecasting. The results present the adaptive n-values of roughness for river hydraulic model that can provide a better flow state for subsequent forecasting at significant locations and longitudinal profiles along rivers.     

Integrated methodology for flood risk assessment and application in urban communities of Pakistan

Flood disasters and its consequent damages are on the rise globally. Pakistan has been experiencing an increase in flood frequency and severity along with resultant damages in the past. In addition to the regular practices of loss and damage estimation, current focus is on risk assessment of hazard-prone communities. Risk measurement is complex as scholars engaged in disaster science and management use different quantitative models with diverse interpretations. This study tries to provide clarity in conceptualizing disaster risk and proposes a risk assessment methodology with constituent components such as hazard, vulnerability (exposure and sensitivity) and coping/adaptive capacity. Three communities from different urban centers in Pakistan have been selected based on high flood frequency and intensity. A primary survey was conducted in selected urban communities to capture data on a number of variables relating to flood hazard, vulnerability and capacity to compute flood risk index. Households were categorized into different risk levels, such as can manage risk, can survive and cope, and cannot cope. It was found that risk levels varied significantly across the households of the three communities. Metropolitan city was found to be highly vulnerable as compared to smaller cities due to weak capacity. Households living in medium town had devised coping mechanisms to manage risk. The proposed methodology is tested and found operational for risk assessment of flood-prone areas and communities irrespective of locations and countries.     

Analysis of flood causes and associated socio-economic damages in the Hindukush region

Pakistan is exposed to numerous hazards, but the problem of recurrent floods has been causing massive losses to lives and other properties. Swat valley is no exception to it. In this paper, an attempt has been made to analyse the causes and associated socio-economic impacts of floods on the Swat valley, Pakistan. Swat valley falls in the Hindukush region, North-west-Pakistan. The valley has been studied with special reference to its physical and socio-economic environment. Similarly, three-sample villages were also randomly selected from the active floodplain for micro-level analysis. The sample villages include Ningolai, Delay and Ghureijo. All the three-sample communities are located on the right bank of river Swat. This area is located in the active flood zone of Swat valley. The analysis revealed that in the study area, floods occur during summer season, which is mainly caused by heavy rainfall as well as rapid melting of snow and glacier. Besides these, there are some floods intensifying factors, which accelerate intensity of floods and enhance resultant damages in the valley. It was found that during flood season, water overflows the natural levees and trigger tremendous loses to housing, agricultural land, standing crops and other properties. The flood-related Government Departments have only implemented limited structural mitigation measures. However, in addition to structural measure, land-use zoning and flood abatement strategies would largely help in reducing the adverse consequences of this recurrent phenomenon.     

Comparison of TRMM-based flood indices for Gaziantep,Turkey

Floods are the most common natural disasters threatening the welfare of humanity. Gaziantep, a city located in a semi-arid region of Turkey, is occasionally flooded, and in May 2014, a flood not only caused property damage, but also resulted in the death of a lady who became trapped in flood waters. The fatality and property damage of flash floods arise from the limited response time for remediation. Despite improvements in numerical weather predictions, forecasting flash floods is not easy. Due to its frequent observations, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) real-time (RT) 3B42RT data are tested for Gaziantep flood predictions in this study. During TRMM era, six floods occurred in Gaziantep. Three-hourly 3B42RT data covering the 2000- to 2014-year period indicated high rain rates during months in which floods were observed. Also daily variation of rainfall was well represented. High-intensity rain (HIR), cumulative distribution functions (CDF) and Gaziantep Flood Index (GAFI) indices are developed for flood characterization. HIR, calculated as 10 mm/h, detected October and December of 2010 floods. CDFs with 99, 98.5, 95 and 91.3% indicated 4 floods occurred in August 2005, June 2007, October 2010 and December 2010, respectively. GAFI was able to detect 4 out of 6 occurrences (August 2005, June 2007, October 2010 and December 2010) as values ranging from 1 to 2.63 are selected for monthly precipitation. In the missed occurrence, 3B42RT did not indicate any rainfall. Although only rain rates are used in flood characterization, the results are promising, and the simplicity of the methodology favors its usage. Also, methodology can easily be implemented to TRMM following missions such as Global Precipitation Measurement Mission.     

Forecasting flood risk in the Indus River system using hydrological parameters and its damage assessment

Hydrological parameters are among the widely used parameters in assessing flood risk. On the other hand, anticipated flood damages, in case of flooding, are estimated with the help of expected losses in areas nearer to the watercourse. The major source of almost every-year flooding in Pakistan is the Indus River system that comprises the major rivers of Pakistan. We first use observed data to construct simulated data models based on various probability distributions namely normal, lognormal, Weibull, largest extreme value, gamma-3, and log-Pearson type-3 distributions and thereby compute probable maximum flood. Secondly, we perform log-Pearson type-3 analysis with and without historic adjustment on the observed data series of 17 years to forecast floods with return periods T of 2, 5, 10, 25, 50, 100, and 200 years. We also categorize the river structures based on the risk of flooding. Lastly, we estimate risk of flood damages in terms of expected losses based on observed data. The present study reveals that the log-Pearson type-3 distribution is relatively better for estimating probable maximum flood. We use exceedence probability to assess the risk of flooding in the various structures of the said rivers. The analysis shows that flood damages in Pakistan may be reduced by increasing the design capacity of the structures and also by giving awareness to people about the flood-generating factors.     

The Indus flood of 2010 in Pakistan: a perspective analysis using remote sensing data

The Indus flood in 2010 was one of the greatest river disasters in recent history, which affected more than 14 million people in Pakistan. Although excessive rainfall between July and September 2010 has been cited as the major causative factor for this disaster, the human interventions in the river system over the years made this disaster a catastrophe. Geomorphic analysis suggests that the Indus River has had a very dynamic regime in the past. However, the river has now been constrained by embankments on both sides, and several barrages have been constructed along the river. As a result, the river has been aggrading rapidly during the last few decades due to its exceptionally high sediment load particularly in reaches upstream of the barrages. This in turn has caused significant increase in cross-valley gradient leading to breaches upstream of the barrages and inundation of large areas. Our flow accumulation analysis using SRTM data not only supports this interpretation but also points out that there are several reaches along the Indus River, which are still vulnerable to such breaches and flooding. Even though the Indus flood in 2010 was characterized by exceptionally high discharges, our experience in working on Himalayan rivers and similar recent events in rivers in Nepal and India suggest that such events can occur at relatively low discharges. It is therefore of utmost importance to identify such areas and plan mitigation measures as soon as possible. We emphasize the role of geomorphology in flood analysis and management and urge the river managers to take urgent steps to incorporate the geomorphic understanding of Himalayan rivers in river management plans.     

Monte Carlo simulation-aided analytical hierarchy process (AHP) for flood susceptibility mapping in Gabes Basin (southeastern Tunisia)

Flash floods are among the most severe hazards which have disastrous environmental, human, and economic impacts. This study is interested in the characterization of flood hazard in Gabes Catchment (southeastern Tunisia), considered as an important step for flood management in the region. Analytical hierarchy process (AHP) and geographic information system are applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. However, the uncertainties that are associated with AHP techniques may significantly impact the results. Flood susceptibility is analyzed as a function of weights using Monte Carlo (MC) simulation and Global sensitivity analysis. AHP and MC–AHP models gave similar results. However, compared to AHP approach, MC–AHP confidence intervals (95%) of the overall scores had small overlaps. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin.     

The relevance of flood hazards and impacts in Turkey: What can be learned from different disaster loss databases?

Turkey has been severely affected by many natural hazards, in particular earthquakes and floods. Especially over the last two decades, these natural hazards have caused enormous human and economic damage. Although there is a large body of literature on earthquake hazards and risks in Turkey, comparatively little is known about flood hazards and risks. Therefore, this study aims to investigate the severity of flooding in comparison with other natural hazards in Turkey and to analyse the flood patterns by providing an overview of the temporal and spatial distribution of flood losses. These will act as a metric for the societal and economic impacts of flood hazards in Turkey. For this purpose, Turkey Disaster Database (TABB) was used for the years 1960–2014. As input for more detailed event analyses, the most severe flood events in Turkey for the same time interval will also be retrieved. Sufficiency of the TABB database to achieve the main aim of the study in terms of data quality and accuracy was also discussed. The TABB database was analysed and reviewed through comparison, mainly with the Emergency Events Database (EM-DAT), the Global Active Archive of Large Flood Events—Dartmouth Flood Observatory database, news archives and the scientific literature, with a focus on listing the most severe flood event. The comparative review of these data sources reveals big mismatches in the flood data, i.e. the reported number of events, number of affected people and economic loss all differ dramatically. Owing to the fact that the TABB is the only disaster loss database for Turkey, it is important to explore the reasons for the mismatches between TABB and the other sources with regard to aspects of accuracy and data quality. Therefore, biases and fallacies in the TABB loss data are also discussed. The comparative TABB database analyses show that large mismatches between global and national databases can occur. Current global and national databases for monitoring losses from national hazards suffer from a number of limitations, which in turn could lead to misinterpretations of the loss data. Since loss data collection is gaining more and more attention, e.g. in the Sendai Framework for Disaster Risk Reduction 2015–2030, this study offers a framework for developing guidelines for the Turkey Disaster Database (TABB), implications on how to standardize national loss databases and implement across the other hazard events in Turkey.     

太湖流域应对特大洪水防洪工程效益模拟

防洪效益评估对防洪工程投资决策与减灾对策制定具有重要意义。建立集成了与太湖流域防洪效益评估相关的系列模型和方法,包括含降雨产流与平原净雨计算的水文分析方法、由河网水动力学模型和平原区域洪水分析模型组成的大尺度水力学模型、综合流域社会经济和淹没因素的洪灾损失评估模型。模拟了太湖流域遇特大洪水的灾害损失,开展了不同防洪工程应对流域性特大洪水减灾效益的预测分析。结果表明:1999年型200年一遇降雨将会给太湖流域造成高达568.29亿元的直接经济损失,外排动力增强30%至100%的防洪效益介于26.69亿元到45.70亿元之间,新建圩区、太浦河拓宽的防洪效益依次减小,而圩区泵排能力增加30%的防洪效益仅为0.65亿元。基于研究成果提出了增设外排泵站、加强圩区科学调度、通过保险分担风险等应对特大洪水的对策措施建议,为太湖流域特大洪水的防治提供支撑和参考。     

太湖流域应对特大洪水防洪工程效益模拟

防洪效益评估对防洪工程投资决策与减灾对策制定具有重要意义。建立集成了与太湖流域防洪效益评估相关的系列模型和方法,包括含降雨产流与平原净雨计算的水文分析方法、由河网水动力学模型和平原区域洪水分析模型组成的大尺度水力学模型、综合流域社会经济和淹没因素的洪灾损失评估模型。模拟了太湖流域遇特大洪水的灾害损失,开展了不同防洪工程应对流域性特大洪水减灾效益的预测分析。结果表明：1999年型200年一遇降雨将会给太湖流域造成高达568.29亿元的直接经济损失,外排动力增强30%至100%的防洪效益介于26.69亿元到45.70亿元之间,新建圩区、太浦河拓宽的防洪效益依次减小,而圩区泵排能力增加30%的防洪效益仅为0.65亿元。基于研究成果提出了增设外排泵站、加强圩区科学调度、通过保险分担风险等应对特大洪水的对策措施建议,为太湖流域特大洪水的防治提供支撑和参考。     

Flood mitigation due to extreme rainfall events in the inner Bangkok,Thailand

In the past decades, the influence of climate change has caused changes in the amount of rainfall in many areas which may affect the flood assessment and mitigation. This research aims to determine amount of rainfall which impacts on changes of the water levels in canals and evaluate the appropriate mitigation measures for floods in the inner Bangkok area, Bangkok Noi and Bangkok Yai districts of Bangkok. The maximum 1-day rainfall during 1997–2010 was determined under different return periods of 2, 5, 10, 25, 50 and 100 year. The MIKE 11 model was then applied to assess changes of the water levels in canals caused by design rainfall events for those return periods. The flood mitigation was also proposed by applying various pumping capacities and initial water levels, incorporating with building dykes and a floodgate. This study has found that the highest flood-risk areas are along Chak Phra and Bangkhunnon canals and the eastern part of Jakthong Canal while the lowest flood-risk area is Bangkok Yai district. Flood caused from the 10-year rainfall can be mitigated by building dykes with the height of 0.75 m [mean sea level (MSL)] and maintaining the initial water level of 0.70 m (MSL). Furthermore, it has also been found that flood caused from the 25-year rainfall can be mitigated by building the floodgate to prevent the flowing back water at Wat Yangsuttharam Canal. However, 50- and 100-year rainfalls seem to cause floods which are too large to mitigate.     

A macro-scale flood risk model for Jamaica with impact of climate variability

Floods account for more than half of the global hydrometeorological risks. Severe floods cause significant economic shocks and loss of lives, particularly for developing countries such as Jamaica. There is need for more information on the present and projected flood risks to justify macro-scale planning for climate change adaptation and facilitate the decision-making processes. In this study, a catalogue of 198 flood events occurring between 1678 and 2010 is compiled for Jamaica and used to examine the climatology, occurrence, trends, causes and duration of the island’s severe events. The annual flood risk is estimated to be a loss of life rate of 4 persons and estimated annual damage of USD96.3 million per annum in 2010 values and approximately 0.84 % of GDP per annum. Macro-scale models for flood risks (deaths and damages) are also developed using data from the flood catalogue and maximum precipitation at the town and parish level. The models examine the relationship between flood risks (death and damages) and extreme rainfall depths and intensities. Future climate risks of loss of lives and damages are predicted to increase 11 and 9 %, respectively, to 4.4 persons and USD105.2 million per annum.     

Hydrologic characteristics of floods in Ganges–Brahmaputra–Meghna (GBM) delta

In the middle of 2007, a severe flood affected the People’s Republic of Bangladesh. This is a natural disaster that takes people’s lives, destroys livestock, infrastructures and communication systems and, damages crops and fish ponds. Despite many adverse impacts, the flood situation is an accepted phenomenon to the citizens of Bangladesh, due to the immense increase of soil fertility due to the flood, plus, the recharge of aquifer, ecosystem and fish. The flood of 2007 was the 5th major flood of the last 20 years when more than thirty-five percent of the area of the country was inundated with flood water. As in the past, the flood of 2007 had its own significance. The geography of the country contains a floodplain delta of three major river basins: the Ganges, the Brahmaputra and the Meghna (GBM). The mean monthly rainfall plot from the TRMM satellite data has shown that for both the Meghna and Brahmaputra basins, the rainfall was higher during July 2007 than any other months of the last 2 years. This excess rainfall had accumulated in the Brahmaputra and Meghna rivers and carried downstream to Bangladesh. This was the main cause of the flooding in 2007. The first crossing above the danger level of the river waters was observed at Durgapur station of the Someswari and at Sunamganj station of the Surma on the nineteenth of July, 2007 inside Bangladesh. In terms of magnitude of the peak and duration of the flood, the Brahmaputra was higher in 2007 than during 2004. However, the Ganges river water level never crossed the danger level during flood of 2007. The Meghna was lower during the flood peak for the duration of the flood in 2007. The year–to-year variability in both the magnitude and duration of the flood suggests changes in rainfall and landuse pattern of the catchment.