Abstract: Using remotely sensed Tropical Rainfall Measuring Mission (TRMM) 3B42 version 7 precipitation data, an investigation on extreme rainfall events (EREs) during the monsoon season has been conducted over the Northwest Himalaya (NWH) for the period of 1998–2013. The satellite precipitation data have been validated with gridded rain gauge data prepared by India Meteorological Department (IMD) using standard statistical measures. A strong positive correlation of 0.88 is found between both, supporting the use of 3B42 V7 for the study of rainfall over the region. The EREs have been identified using three indices corresponding to 98th, 99th, and 99.99th percentiles of the rainfall distribution over the region. The 98th and 99th percentile thresholds are suggested to be considered as extreme and very extreme events respectively whereas 99.99th percentile may correspond to the cloudburst events. The parametric t-test results indicate a significant increasing trend of the frequency of EREs whereas non-parametric Mann-Kendall test results yield no significant trend of EREs over the study region. As the sample size is small, therefore the significance of these results may not be ascertained. The elevation exhibits strong inverse relation with frequency and intensity of EREs over the NWH. A strong negative correlation of ∼0.8 and a poor negative correlation of ∼0.48 are obtained between the elevation and frequency of extremes exceeding 98th and 99th percentiles, and frequency of the cloudburst events, respectively. Whereas, elevation shows strong negative correlations of −0.85, −0.84, and −0.81 with rainfall intensities associated with 98th, 99th, and 99.99th percentiles, respectively. The plains and foothills of the NWH region experience the highest frequency of EREs. However, the peaks of the highest frequency of events are also observed at different elevation ranges at state-level analysis. This study is a contribution to the on-going research of extreme events over the mountainous terrain including disaster management study.

Abstract: Landslide is frequently occurring natural phenomenon causing land degradation in mountainous region of the world. The fragile Himalayan terrain of Uttarakhand often faces challenging and tough situation due to landslides, particularly in monsoon season. Change in rainfall pattern, anthropogenic activity, deforestation, construction on old landslide debris and Quaternary deposits and displacement of habitation from hill side to valley side are some significant increasing factors for the landslide susceptibility. Anthropogenic activities include very fast, unscientific and uncontrolled urbanization and these are considerably responsible to carved out the disaster viz., landslide, cloudburst and flash flood. Habitation and infrastructure development initiatives in close proximity of streams and rivers as also over Quaternary deposits and unplanned disposal of excavated rock and debris are observed to aggravate the fury of both, landslides and flash floods in the region. Mostly in monsoon season frequent disruption of road network by landslides cause hardship to tourists and pilgrims along with local people. During monsoon season torrential rainfall and cloudburst events are common which acts as basic factor for triggering the landslides in the area. It is therefore necessary to analyse the causes of landslides so as to suggest viable mitigation measures. The paper outlines slope instability and factors responsible for the landslide susceptibility in upper Alaknanda valley, Uttarakhand, India.

Abstract: Data Mining has been used extensively in various business and scientific applications for last few years. Data mining has been found to be providing a deep insight into understanding the hidden facts in huge databases. Data mining is an interdisciplinary subfield of computer science that discovers patterns in large data sets by using methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. In this paper, data mining technique for Interpretation of Weather Forecasts for one of the most disastrous weather phenomenon viz. cloudburst has been applied. Every year, cloudburst over hilly areas and coastal regions causes loss of lives and property. The forecasting and warning of these events is very difficult. There is no satisfactory technique for anticipating the occurrence of cloudbursts because of their small scale. A very fine network of radars is required to be able to detect the likelihood of a cloudburst and this would be prohibitively expensive. The warning of cloudburst could only be provided at a small lead time say a few hours in advance based on the interpretation of latest satellite imagery data, powerful radar (Doppler category), if available, or by using Model Output Statistics (MOS) models. Another dimension to forecasting this weather event has been identified by applying clustering technique on primary data forecasted by global and regional models of weather forecasting. A recent case of Cloudburst over Uttarakhand that caused a huge loss has been analyzed using k-means clustering technique of data mining. It has been observed that with the mining of Numerical Weather Prediction model forecast data, the signals of formation of cloudburst can be found3-4 days in advance.

Abstract: This study deals with the climate change and its impact on changing precipitation behaviour, consequent events of extreme rainfall (cloudburst), landslides and flash floods. In this work, TRMM (Tropical Rainfall Measuring Mission) 3B42RT(real time) precipitation data for 16 (1998-2013) years was utilized to understand the present variation of precipitation and extreme events such as cloudburst, flash floods, and landslides in Western Himalaya. It was observed that the extreme events are mainly restricted to the south of higher Himalaya, coinciding with high precipitation. Since, the higher Himalaya is bounded by MCT (Main Central Thrust), it could be envisaged that this zone has been acting as orographic barrier hence most of high precipitation and extreme events are confined below the area. This orographic barrier plays a significant role in controlling the expectancy and extent of high rainfall and thus triggering of the associated hazards like landslides. A case of Mandakini valley where Kedarnath disaster of June 2013 has caused loss of over five thousand lives and properties worth billions has been studied.

Abstract: Water Sensitive Urban Design (WSUD) is still in the “Opportunity”-phase of its stabilization process in Copenhagen, Denmark, indicating that there are controversies surrounding its proper use and the regulatory framework is not completely adapted to the new technology. In 2015 private land owners in Denmark could get up to 100% of the construction costs of climate adaptation measures funded by the utility companies, which resulted in a race to apply for this co-funding plan. In this study we briefly review the climate adaptation framework in Copenhagen, and then discuss how well different scenarios of WSUD in a case study area interact with this framework. The impacts of the different scenarios are assessed using the “WSUD-potential” tool, which builds upon the Three Points Approach. The results indicate that there is a schism between the city’s Cloudburst Management Plan on one side and its Climate Adaptation Plan and general service goal on the other side, which may result in over-sizing of the collective stormwater management system.

Abstract: Disaster Management is an effort to inquire into the process of a hazard turning to disaster to identify its causes and rectify the same through public policy with minimizing and preventing the damaging impact of a natural or manmade hazard. Disaster management as a subject es sentially deals with management of resources and information and as far as a disastrous event is concerned and also how effectively and seamlessly one coordinates these resources (Kapoor, 2010).Disaster management, at the individual and organizational level, deals with issues of planning, coordinating, communication and risk management. India has been traditionally vulnerable to natural disasters on account of its unique geographical locations and geological formations. Floods, droughts, cyclones, earthquakes and landslides have been recurrent phenomena. Disaster is a sudden and unfortunate event that brings with it great damage, loss, destruction and devastation to human life as well as property and also hampers the ongoing developmental projects in a particular area being affected by the disaster. The damage caused by disasters is immeasurable and varies with the geographical location, climate and the type of the earth surface/degree ofvulnerability (Arulsamy & Jeyadevi, 2016)Kinds of disastersThere are two types of disasters namely natural disasters and manmade disasters. The natural disasters such as flood, cyclones, hailstorms, cloudburst, heat and cold waves, snow avalanches, droughts, sea erosion, thunder and lightening, landslides and mud flows, earthquakes, mine fires, dam failures and general fires. Technological/Industrial disasters such as chemical and industrial disasters and nuclear accidents, accidental disasters such as urban and forest fires, oil spill, mine flooding incidents, collapse of huge building structures, bomb blasts, air, road and rail mishap and even biological disasters such as epidemics, pest attacks, cattle epidemic and food poisoning come under the category of man-made disasters (Modh,2009).Natural disastersCertain disasters occur in nature, without human provocation.FloodsFloods are sudden and temporary inundation of a large area as an overflowing of rivers or reservoirs. Floods are caused by rains, high winds, cyclones, tsunami, melting snow or dam burst. Floods can happen gradually or can happen suddenly due to heavy rain, breach of the water storage etc.Effects: During floods buildings built on weak foundations collapse endangering human lives and property. Damage may also be cause to roads, rail, dams, monuments, crop and cattle. Floods may cause landslides and soil erosion, human and livestock due to drowning, serious injuries and outbreak of epidemics, household articles, utilities such as water supply, sewerage, communication lines, transportation network and railway lines put at risk. Apart from the loss of human and cattle life, floods cause severe devastation of crops.Flood control: It can achieved through proper planning of flood control and management measures, a rational planning for flood management involves identification the flood prone areas and frequency and magnitude of flooding in flood prone areas, flood forecasting, a-forestation should be encouraged, buildings should be constructed on elevated areas. No major development should be permitted in flood prone areas.DroughtDrought is an event that results from lower than normal expected rainfall over a season or for some period of time. Shortfall in rains results in drying of rivers, lakes, reservoirs due to excessive withdrawal and poor recharge of ground water and loss of crop yield due to shortage ofwaterare some ofthe main indicators of drought. Causes: In the recent past droughts are increasing due to deforestation and environmental degradation, shortfall of rainfall .If rainfall is deficient by more than 10% of the annual average rainfall, then the condition is said to be draught. …

Abstract: Thousands of human lives are lost every year around the globe, apart from significant damage on property, animal life, etc., due to natural disasters (e.g., earthquake, flood, tsunami, hurricane and other storms, landslides, cloudburst, heat wave, forest fire). In this paper, we focus on reviewing the application of data mining and analytical techniques designed so far for (i) prediction, (ii) detection, and (iii) development of appropriate disaster management strategy based on the collected data from disasters. A detailed description of availability of data from geological observatories (seismological, hydrological), satellites, remote sensing and newer sources like social networking sites as twitter is presented. An extensive and in-depth literature study on current techniques for disaster prediction, detection and management has been done and the results are summarized according to various types of disasters. Finally a framework for building a disaster management database for India hosted on open source Big Data platform like Hadoop in a phased manner has been proposed. The study has special focus on India which ranks among top five counties in terms of absolute number of the loss of human life.

Abstract: Floods have been recurrent phenomena in the study area. A heavy precipitation, usually coming during the end months of the summer season in association with sudden cloudburst, leads to severe flooding in the study area. By now the catchment area of the river is already saturated and the high run-off swells the rivers beyond their capacity. The present study describes the application of HEC RAS Model for flood studies in the river Jhelum Kashmir valley. The peak flood records were used as inputs into HEC RAS model to find out the resultant expected flood levels. The resultant output generated by the model shows an overflow at maximum locations of the river under study for 50 years and above return period. This purpose is to give a hand to policy makers, planners and insurers, to develop a robust strategy for the development of flood mitigation measures and plans to minimise the losses associated with the disaster in the study area.

Abstract: The Bhagirathi River that originates from the snout of Gangotri Glacier at an elevation of about 4000 m is traditionally considered as the source of Ganga River. In June 2013, a multi-day cloudburst centred on the North Indian state of Uttarakhand caused devastating floods and landslides which resulted in massive loss of lives and property. This unusual rain event occurred during the tourist season in June, consequently trapping a large number of tourists and vendors in this area. Sudden release of stored water generated floods that created havoc downstream of most of the rivers in this area. This paper presents a description of the meteorological conditions which led to the catastrophic hydrological situation and flash flood as experienced in the large part of Bhagirathi basin in June 2013. The hydro-meteorological and discharge data for 14–18 June 2013 collected at an observatory near the snout of the Gangotri Glacier are analysed. This area normally receives less rainfall; the maximum monthly r...