Abstract
The hydrological disasters have the largest share in global disaster list and in 2016 the Asia’s share was 41% of the global occurrence of flood disasters. The Jammu and Kashmir is one of the most flood-prone regions of the Indian Himalayas. In the 2014 floods, approximately 268 people died and 168004 houses were damaged. Pulwama, Srinagar, and Bandipora districts were severely affected with 102, 100 and 148 km 2 respectively submerged in floods. To predict and warn people before the actual event occur, the Early Warning Systems were developed. The Early Warning Systems (EWS) improve the preparedness of community towards the disaster. The EWS does not help to prevent floods but it helps to reduce the loss of life and property largely. A flood monitoring and EWS is proposed in this research work. This system is composed of base stations and a control center. The base station comprises of sensing module and processing module, which makes a localised prediction of water level and transmits predicted results and measured data to the control center. The control center uses a hybrid system of Adaptive Neuro-Fuzzy Inference System (ANFIS) model and the supervised machine learning technique, Linear Multiple Regression (LMR) model for water level prediction. This hybrid system presented the high accuracy of 93.53% for daily predictions and 99.91% for hourly predictions.
Highlights
The Floods are the most damaging disaster in terms of property and life
Out of all other continents, Asia is the most affected continent (Cavallo & Noy 2011; Table 1). As it was predicted by The Intergovernmental Panel on Climate Change (IPCC 2001) that flooding will worsen in decades to come because of the climate change
The climate change induces extreme precipitation (Mishra et al 2019), Glacier melting at faster rate, (Rafiq & Mishra 2016) extreme temperatures, cyclones, rise in ocean water levels (IPCC 2014)
Summary
The Floods are the most damaging disaster in terms of property and life. Flood is the most occurring disaster in the world as compared to other types of natural disasters. (Ahern et al 2005 & Kiran et al 2019). India has four river systems on a large scale viz. Aravalli, Ganges, Brahmaputra, and Indus that are large both in catchment size and drainage density. During August 18, 2008, Kosi floods, which impacted India and Nepal, affected more than 3 million people (Bhatt et al 2010). Apart from this example, there are numerous large-scale hydrological disasters which left parts of India devastated like Leh flashfloods 2010 (Thayyen et al 2013), Brahmaputra floods 2012 (Pal et al 2013), Kedarnath flashfloods 2013 (Rafiq et al 2019), J&K floods 2014 (Mishra 2015), and Tamilnadu floods 2015 (Mishra et al 2016). To mitigate the effects of floods a system is needed which can aware people before the occurrence of this hydrological disaster (Mishra & Rafiq 2019)
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