Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

Background: The impact of ooding rises due to unplanned settlements, especially in developing and underdeveloped countries. This study tries to address these issues by mapping ood risk places and assessing their impact on population and household. Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is inuence and other slopes, and it has provided high and low value according to its role on ooding. Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to ooding. It depicts a signicant increasing trend of oods in the Morang district. Conclusion: This settlement risk map can help determine the ood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce ooding risk.


Introduction
The ood-affected more than 2 billion people worldwide from 1998 to 2017 (Floods, n.d.). It damages property, loss of life, and other infrastructure such as schools, hospitals. The people living near the ood plain are prone to this calamity due to a lack of residential planning, early warning system, and awareness (51370_icimodcbfews016. Pdf, n.d.). Several studies regarding disasters like oods have shown a signi cant increase in ood worldwide and might be more recent. This upcoming trend is due to climate change and unplanned settlements in ood-prone areas. Poor people of developing countries are overexposing residence in very high-risk areas (Poorly Planned Urban Development| PreventionWeb.Net, n.d.).
More than hundreds of people die in Nepal every summer, and monsoon rains trigger ooding in lower terrain and higher terrain landslides (150623_monsoon_hazard_analysis_ nal_. Pdf, n.d.; Petley et al., 2007). Few studies mapped ood risk and its vulnerability to the population and household (De Risi et al., 2020;Mioc et al., 2015;Rufat et al., 2015).
Flood is one of Nepal's major natural disasters, which had billions of dollars of property and life. These had increase exposure and economic loss that raised poverty and homeless in the Morang district of Nepal. These victims are increasing every year, preventing public life and property via reliable information through risk analysis mapping. These maps will provide essential information such as a safe place for settlement, agriculture, and higher risk areas with that necessary information to plan for residential, farming, emergency action plans, ood insurances, and ecological studies. Morang is the core industrial area located in the east of Nepal. It is prone to ooding during the monsoon season every year. Besides, unplanned rapid urbanization near banks of rivers has plummeted the exposure of ooding.
Several studies nd that the government lacks a ood risk map and assesses its vulnerability on population, household, and places to provide permission for settlement on a speci c area (13627_Local Governments and Disaster Risk Redu.Pdf, n.d.;150623_monsoon_hazard_analysis_ nal_. Pdf, n.d.; Aksha et al., 2020;World Bank, 2003). This study prepares a ood risk map of Morang district for settlement areas using six criteria: land use, drainage density, slope, rainfall, Dem, and soil. It will provide spatial information about very high risk and safe places for settlement that would support informed decision-making by the government and policymakers to minimize ood risk. Using such an approach, they can reduce the risk by restricting human settlement on very high risk and high-risk areas or shifting those who lived already through awareness campaigns and relief packages.

Study Area
Nepal's Morang district is at high risk of ooding where more than dozen villages faced due to ooding in Ratuwa, Bakraha, Lohandra, Chisang, Keshliya, and Singiya rivers (Over a Dozen Villages Prone to Flooding in Morang -Nepal, n.d.-a; Over Dozen Villages Prone to Flooding in Morang -MyRepublica -The New York Times Partner, Latest News of Nepal in English, Latest News Articles, n.d.). It shows a signi cant increase of oods every year and is kept in agship four by Nepal Risk Reduction Consortium n.d.;Nepal,n.d.). This hazard impacted more than two thousand families displaced, hundred killed in the last ve years. This study nds the high-risk and low-risk regions that will help people, communities, and local governments prepare settlements in safer places.

Data Collection
The study used historical past rainfall data from 2000 to 2019. Other datasets acquire from different sources, such as land use uses from Google Earth Engine (GEE) and soil data from the Food and Agriculture Organization (FAO). The drainage density, slope, Population, household data from Central Bureau Statistics (CBS, 2011), and Dem from earth data (Table 2.1).

Methods
This study used data from Earth data, GEE, and FAO data repository as described in Table 2.1 for preparing land use, soil, digital elevation, rainfall, drainage density, and slope map (Figure 2.2). From this data, the respective layers' maps generate using Google Earth Engine for risk assessment on the residential areas of Morang.
The overlay analysis has two basic terms in uence and scale. In uence is fundamental for analysis from six layers ( Table 2.2); used land use is the highest in uencer as proper land use planning in this study area can reduce ood impacts. It is overall critical of the layer. In contrast, the soil is less signi cant compared to the other ve parameters.
Evaluation criteria: For attribute of the data: Classi ed into ve categories, weightage 5 to 1, In this analysis scale from 1 to 5 is used to evaluate the layer's importance of attribute. Here one means less signi cance, and ve means most important. The scale is an essential attribute for ood risk mapping and assessment.

Results
The study region is divide into ve classes; the area with very high, higher, medium ood risks shown in dark blue to blue color. There are thirteen municipalities, and rural municipalities are from very high to medium risk, and four are in low and ood safe risk in Morang. The overlay analysis (Table 2.2) and attribute (Table 2.2) criteria prepare a ood risk analysis map of Morang District (Figure 3.1). The average population and settlement risk, and total are calculates using the zonal statistics tool, shown in the graph, chart, and map. The data of central bureau statics of population and household (CBS, 2011) with soil, land use, drainage density, slope, Dem, rainfall map uses for creating settlement at risk in the Morang district.
In the Morang district, around twenty-four percent population is at higher risk, whereas about more than three thousand settlements are prone to ooding. The terrain with closer proximity has chances of a ood, and higher elevation is safer than the lower one. This study shows signi cant results that almost more than fty percent of district areas are prone to ood. Therefore, people should be aware of this scenario by local government, a non-pro t organization, international non-pro t organization to provide equal land in other safer places from oods. It includes valuable information regarding land use planning, risk perception, settlement areas to the decision-maker, local government, and other stakeholders to plan residential regions of safer places.
The table shows the information about the ood risk of rural municipalities and muncipalities in Morang district (Table 3.1). The Sunawarshi, Ratuwamai, Pathari-Sanischare, and Urlabari municipalities have very high risk of ood with total population of 212632 and sum of 33821 households. Total population and households of 50385 and 10978 respectively with low risk in Miklajung and Budhiganga rural municipalities. Only two Letang and Kerabari are ood safe area in this district where settlement planning is possible and other region will be suitable for other purposes such as agriculture, industrial.

Discussion
This research will provide information about the district's ood risk area, which will locate a place that will impact by ood in the long term using six factors. It creates a potential ood risk analysis map for the settlement and population of Morang district. Morang is one of the most vulnerable districts for oods that affected more than thousands of households. Flood impact rises every year due to land-use changes, unplanned residential areas, and climate change. This increasing trend of a ood is worldwide causing the lives of millions of people. It is a rapid growth of urbanization without proper study of its terrain and risk of disaster in developing countries (Asian Development Bank, 2013; Disaster Risk Management in South Asia -A Regional Overview.Pdf, n.d.; Gu & Division, n.d.;World Bank, 2003b). Few studies try to understand the most common natural disaster like oods, landslides, and earthquakes locally, regionally, and nationally in Nepal (1321.Pdf, n.d.; Thapa, 2021;Tuladhar et al., 2015). Even proper study information is unable to capture these uncertainties that exist in these hazards and vulnerability. The research will depend on multiple assumptions, incomplete datasets, and imperfect models that lead to an error during risk analysis and assessment to minimize this risk. While performing risk analysis, should select careful consideration and impact factors such as sloping and in uence regarding the speci c study area (Rogelis et al., 2014; Vulnerability of Human Settlements to Flood Risk in the Core Area of Ibadan Metropolis, Nigeria, n.d.). A spatial approach plays a vital role in risk analysis and assessing its vulnerability of residential places (Lindley et al., 2007;Thapa, 2021;Westen, 2013 provide information about the location of very high risk, high-risk areas to support disaster management program. Therefore, remotely sensed data with geospatial technologies such as google earth engine and QGIS prepare maps and assess analysis regarding the risk of ood on settlement areas. This study introduces a spatial technique to identify the risk in the Morang district.

Conclusions
The ood risk map and assessment determine safer places from ood such as Letang, Kerbari municipality, where people can settle. Uralabari, Ratuwamau, Sunwarshi, Patahri are the municipality prone to upcoming ood. From this response, local government, residence, disaster management teams, security forces should be prepared during every summer and monsoon of these municipalities to reduce the loss of lives and property damage. Similar studies need the whole country for better preparedness, response, recovery, and natural disaster reduction. However, the government and exposed people to these prone are unaware of this due to lack of economic and human resources, and people no place to shift their settlement. Despite signi cant input from nonpro t organizations, international organizations warning people about a ood and its impact through awareness, there is an increasing number of deaths and property damage every year. This study suggests that more people live in a very high, highrisk area, increasing the risk every summer and monsoon. The solution might be living in safer places and performing other low and medium-risk activities such as farming and forest in high ood risk places to reduce its risk. Ethics approval and consent to participant Not applicable.

Availability of data and materials
The data used are cited with their sources, if data used in manuscript are not clear, the author is agreed for clari cation and sending of dataset on request.

Competing interests
There are no competing interests.

Funding
No funding.