Natural Hazard Mortality in Nepal

Using publicly available disaster database DesInventar from 1971 – 2011, we analyzed which hazard contributes the most to fatalities in Nepal; how mortality is clustered at the village level; and how they are distributed across temporal scale. It is published in peer-reviewed journal Environmental Hazards and can be downloaded from the below link.

http://www.tandfonline.com/eprint/mZu8ZrEItXCMRJtYBwY8/full

Spatial and temporal analysis of natural hazard mortality in Nepal

Sanam K. Aksha, Luke Juran, & Lynn M. Resler

Abstract:

The impacts of natural hazards are typically measured in terms of loss of human lives and economic damage, and recent studies demonstrate that deaths attributed to natural hazards have increased. Using the publicly available DesInventar database, we examined spatial and temporal patterns of natural hazard mortality from 1971 to 2011 at the district and village levels of Nepal and identified natural hazards that contributed most to mortality. Spatial clusters of mortality at the district and village levels were detected using local and global spatial autocorrelation measures (Moran’s I). Landslides (41.91%) and floods (32.52%) accounted for approximately three quarters of natural hazard mortalities over the study period. A Global Moran’s I test positively confirmed clustering at both the district (0.199, p < 0.001) and village (0.256, p < 0.001) levels, whereas a Local Moran’s I test further detected clustering in the central and terai regions, where dynamic geologic and geomorphic processes combined with human-environment interaction constitute major risk factors. A better understanding of multihazard mortality patterns across geographic landscapes and time has the potential to aid policy makers, planners, and local officers to more efficiently allocate scarce capital and human resources to reduce mortality.

Flooding and agent-based modeling (ABM)

When we talk about computer modeling, the language used is so tough to understand and full of jargons. If you are beginner, it’s almost impossible to get through it. This is what I felt when I tried to understand about hydrological modeling, in particular, flood modeling. The flooding events around the globe often come with message that the related information are not efficiently communicated during and after the event.

 

While discussing these issues I found one interesting paper about agent-based flood modeling by Dawson et. al. 2011 entitled “An agent based model for risk-based flood incident management” published in Natural Hazards. The more interesting stuff is this 4:19 minute long YouTube video which explains how this model works. To my knowledge this kind of video is not common explaining about how it works. If you are interested about the model itself, you can follow this link to Newcastle University page.

 

 

 

Full citation of paper: Dawson, R.J., Peppe, R. and Wang, M. 2011. An Agent-based Model for Risk-based Flood Incident Management. Natural Hazards, 59(1): 167-189



 

Role of social media during Seti Flood 2012 Nepal

Nepal is highly prone to natural hazards like Earthquake, Floods, Landslides, and Glacial Lake Outbursts Flood (GLOF). Every year flood creates havoc during the monsoon period as it accounts for two-third of the total precipitation in the country. The rivers originating from the high Himalayan region are the perennial source of water for the downstream people. Due to high relief and unstable slopes these rivers carry high sediment loads and volume causing flooding downstream. People in the mid hills and southern parts of the country face floods every year and have been a routine for coping with them. Loss of agricultural land, destruction of the highway for a month and temporary water logging are some of the common examples reported in the media.

Unforeseen Disaster, Unprecedented Suffering

In late July 2010, Pakistan northern region received heavy monsoonal rainfall which caused recorded flooding in the history. It claimed around 2000 human lives leaving millions homeless and submerging many hectares of fertile land (BBC, Oxfam, Alertnet, Wikipedia). Due to large devastating impact, the UN Secretary termed it ‘a slow-motion tsunami’. Likewise, a cloudburst hit Leh region in Jammu and Kashmir, India and killed 100 people. A large mudslide occurred in Zhoqu county, north western china and claimed 1500 lives which is very uncommon place for such event. Other himalyan countries like Nepal, Bhutan and downstream country Bangladesh also experienced floods.