Miu sub-watershed: Flood vulnerability assessment using spatial model

Frequent floods and droughts, which cause significant material and intangible losses, are a result of watershed destruction especially in Central Sulawesi. Flash floods have been a common occurrence in portions of Central Sulawesi in recent years, and Miu Sub-watershed is one of those watersheds. Both the material and non-material effects were fairly significant, especially for the local population. The biophysical conditions of the area must be known in order to identify flood target areas and flood causes. The application of Geographic Information Systems is the technique used to assess floods. This study’s objective is a spatial examination of the Miu sub-watershed flood susceptibility. Flood-prone areas are analyzed using a variety of techniques, including overlaying, categorization, scoring, weighting, and modeling. The three types of flood danger classes are non-prone, medium, and prone. The Miu sub-watershed region has an area with a flood hazard class for the non-prone category of 64,255.173 ha, a medium category of 57,909.003 ha, and a vulnerable category of 4,838.917 ha. Bangga Village in Dolo Selatan Sub-district, Tuva Village in Gumbasa Sub-district, and Bolapapu Village in Kulawi Sub-district are the Miu Das regions with the widest category of high flood threat.


Introduction
Watersheds are a vital part of the forest ecosystem and play a crucial role in preserving natural stability [1,2].Nonetheless, a number of Indonesian watersheds endure a heavy burden due to the country's extremely high population density and intensive use of natural resources [3][4][5][6].This condition causes the watershed to deteriorate, with signs of an increase in flood events [7,8] erosion, landslides and sedimentation [9,10].
In Indonesia, the development of land use in several watersheds over the past three decades has contributed to watershed degradation.The frequent occurrence of floods and droughts is evidence [11,12].Even residential areas and public infrastructure were inundated by floods, causing extensive material and non-material damage and losses [13,14].
In recent years, flash floods in Central Sulawesi, particularly in the Miu sub-watershed, have occurred frequently.At the close of 2019 and the beginning of February 2020, two regency, namely Sigi and Poso, experienced flash flooding.The disaster has resulted in a substantial loss of life and property.The weak carrying capacity of the watershed is strongly suspected to be due, in part, to the conversion of forest land into plantations and paddy fields [15,16].
The area of non-forest land cover, including settlements in the Miu sub-watershed area is around 20 percent of the total area of the watershed, with a predominance of steep slopes (> 40%) covering 63 percent of the total area.This shows that the Miu sub-watershed area is very vulnerable to damage, especially by community land use activities.An adaptive prevention and control approach is needed, not only prioritizing technical approaches, but also adapting to social and cultural aspects [17][18][19].The combination of a technical approach with social, economic and cultural aspects is expected to be able to produce a flood prevention model that is adaptive to regional characteristics, social, economic characteristics and community culture [6,20].
Many efforts have been made to control the damage, from technical control to mitigating the impact of the disaster.However, the results are considered not optimal.This is indicated by flood events that occur on a wider scale and at relatively high time intervals.This research will try to identify with a spatial approach the level of vulnerability to flooding in the Miu sub-watershed area.This is necessary to make it easier for policy makers to carry out mitigation and adaptation efforts to existing flood vulnerabilities.

Material and methods
The research was carried out from April 2020 to November 2020, taking place in the Miu Sub-watershed area which is administratively within the Sigi Regency area consisting of 5 sub-districts namely Kulawi, South Dolo, Gumbasa, Lindu and Palolo.
To In this analysis the weight of each variable to identify the degree of influence on flood vulnerability is carried out using a quantification approach using the composite mapping analysis method (CMA).The relationship between the actual flood area and the flood vulnerability constituent variables is analyzed to reduce the score of each variable.Factors that have a relatively higher correlation compared to other factors are selected and used to construct a multiple linear regression model so that a flood hazard model will be obtained as follows: : elevation The vulnerability class will be divided into three classes which include non-prone, moderate, and high classes.The feasibility test of the model is carried out using the coinident level by comparing the flood hazard class with the actual flood events so as to get the percentage value of the distribution of floods in each hazard class.

Flood vulnerability mapping
In Table 1.The slope of the slope in the Miu sub-watershed area has 5 classes of slope, namely flat slope (0% -3%) covering an area of 4,000.41ha or the equivalent of 6.10% of the total area of the study area which has a score of 4. Wavy slopes (3% -8%) have an area of 1,663.21ha or equivalent to 2.54% of the total area of the study area which has a score of 3. The slightly class (8% -15%) has an area of 5,052.49ha or equivalent to 7.71% of the total area of the study area which has a score of 2. While the small hilly slope class (15% -30%) and (> 30%) has a score of 1 with a total area of 54,823.85ha or equivalent to 83.65% of the total area of the study area which is the largest area of the total area of the study.The data shows that almost all areas included in the Miu sub-watershed are on steep to very steep slopes.This is one of the factors causing the rapid flow of water into rivers which causes high flood intensity [21,22].The scoring slope map can be seen in Figure 1 (a).
While the distribution of the results of the height analysis in the Miu sub-watershed region ranges from 0 -2480.Determination of the altitude scoring in making a flood hazard map is obtained by overlaying the actual flood map with the height map.The elevation level on Miu sub-watershed is divided into 5 score classes with a range of each value of 500.The altitude scoring map is presented in Figure 1 (b).
It is known that the average incidence of flooding is at an altitude of 0 -1000 meters above sea level with a percentage of 98.45%.This is due to the fact that most of the Miu sub-watershed area has a hilly topography so that the large volume of water runoff caused by high rainfall at that time directly flowed into low-lying areas ( The results of the land cover analysis in Figure 1 (c) show that the level of land cover for forest appears to have the largest area among other land cover classes with an area of 51,908.14ha or the equivalent of 79.20% of the study area.The land use class for forests is given a score of 1 which shows the least influence on flood vulnerability.settlements, open land, bodies of water, and rice fields have the second largest area, namely 1,942.37 ha or equivalent to 2.96% of the area of the study area.Dry land farming has an area of 2,763.68 ha or the equivalent of 4.22% of the study area.This class has the highest score of 4, which indicates that areas that have sparse or no vegetation density in this case are settlements which greatly affect infiltration (the process of entry of water into the ground) resulting in surface runoff which can eventually cause flooding.The last land cover class, namely shrubs and dry land agriculture mixed with shrubs, covers an area of 8,925.77ha or the equivalent of 13.62% of the study area (Table 3).

Flood prone levels in the miu sub-watershed area
The flood hazard map displays information about the class distribution of flood prone areas in the observation area (Figure 2).Based on Table 4 it can be seen that South Dolo, Gumbasa, Kulawi, Lindu and Palolo in the Miu sub-watershed area are included in the low to high flood vulnerability class.The distribution of flood hazard classes in the non-prone category in the Miu sub-watershed area has an area of 65539.97ha, the 6 medium category covers 5394.52 ha, and the vulnerable category covers 58544.03ha.The area with a category that has a high category of flood-prone area is Bangga Village, Dolo Selatan sub-district.

Discussion
One of the characteristics of the inundation zone is the slope of the slopes in the lowlands and basins.Multiple areas' inclinations can be used to characterise their topography [13,23].The slope is one of the factors that can increase the chance of flooding because the higher and the slope of the slope of a land, the water that is transmitted is higher and faster so that the possibility of inundation due to falling rainwater will flow directly and not inundate the area, so the risk of flooding be small [24][25][26].
Conversely, the gentler the slope, the slower the runoff flow and the greater the possibility of inundation or flooding, while the steeper the slope, the faster the surface runoff will occur [3,27].Land cover has a very large contribution to the occurrence of flooding, especially if land clearing activities are carried out in areas that have steep slopes and with soil types that cannot store water [28-7 30].The more open or the more land that is built up, the higher the effect on potential flood vulnerability, conversely the denser and wider a land is covered by vegetation, the lower the effect on potential flood vulnerability [31,32].As a result, land use has an effect on rainwater catchment areas and can be used to determine water catchment areas so that the causes of the increased volume of floods and floodaffected areas are obtained [5,33].
High levels of flood hazard are in areas with a moderately gentle to gentle slope and with average land cover for settlements, plantations and open land.This is due to the fact that if there is rain, the water will quickly flow on a sloping area and in that area there is no vegetation that functions as a water storage and retainer [34,35].
Even though the river's water level is still below average, stagnant water may occur at one location.[36].This condition is substantially still a shelter, but technically the handling can be different because one is caused by an overflow of water in the river, while the other is caused by no air flow due to obstruction of the channel [12,37,38].Flood events will pose a hazard if an event has the potential to cause physical and economic losses or threaten human life.The hazard that arises will give rise to vulnerability, namely a series of conditions that determine whether a hazard (both natural and manmade) that occurs will cause a disaster.
Physical vulnerability is the condition of settlements in the lowlands; shallow, narrow and meandering river conditions; It can also be a drainage condition.Meanwhile, socio-economic vulnerability can be seen from the number and density of the population, the livelihoods of the population and the economic conditions of the community [5,8,9].
Capacity are positive aspects that can reduce risk by reducing existing vulnerabilities (as the ability to deal with disaster situations).Law Number 24 of 2007 concerning Disaster Management states that risk is an event or series of events that threatens and disrupts people's lives and livelihoods caused by natural factors or non-natural factors as well as human factors resulting in human casualties, environmental damage, loss of property, and psychological impact.Disaster risk is defined as the potential loss in the form of death, life threat, material loss and disruption of the socio-economic activities of the community caused by a disasters [13,20,39].
So far, flood prevention and control in the Miu sub-watershed has prioritized technical aspects with the main emphasis being on the construction of flood control dams and mitigating flood disaster management.Efforts to prevent flooding are prioritized on the physical aspect alone.Meanwhile, the Miu sub-watershed area has been filled with various land use and forest product use activities, which have been going on for a long time.Experience in several places, flood prevention is carried out by combining various aspects in it, including social and economic aspects.

Conclusion
Identification of flood-prone areas in the Miu Sub-watershed through CMA calculations with GIS obtained the distribution and extent of different levels of flood vulnerability.The distribution of flood hazard classes for the non-prone category has an area of 64,255.173ha, the medium category covers 57,909.003ha, and the vulnerable category covers 4,838.917ha.Areas with a category that has a high flood-prone area are Bangga Village, Dolo Selatan sub-district.
Further research will continue to be needed, especially related to flood disaster mitigation in floodprone areas and assessment of flood impact reduction strategies through appropriate land use management.It is hoped that this will serve as a recommendation that can be used in developing management of the Miu Sub-watershed based on flood disaster mitigation.

Figure 1 .
Figure 1.Spatial data variables: a) Slope; b) Elevation; c) Land cover Flood-prone areas are areas that physically and climatologically have the possibility of flooding.The overlay results divide three classes of flood hazard: 1) low hazard; 2) medium prone and 3) high prone.Areas that have the highest total score are areas that are potentially flood hazard.The results of the analysis of flood hazard areas are areas that, from a physical and climatological point of view, have the possibility of flooding within a certain period of time and have the potential to damage nature.

Figure 2 .
Figure 2. Map of flood prone miu Sub-Watershed Areas.

Table 2 .
Distribution of floods based on elevation rating.

Table 4 .
Class of Land Use in various areas of Miu Sub-watershed