Flood-affected Areas Research Articles

Regional flood resilience grading based on GEM-AHPSort II method: An objective and managerial factors integrated perspective

Flood resilience is the principal capability of the flood-affected areas to quickly eliminate the impact of floods. Motivated by the realistic demand of improving the regional flood resilience and reducing negative hazards caused by flood, regional flood resilience evaluation is carried out from the perspective of objective and managerial factors in this paper. Firstly, a novel Multi Criteria Decision Making (MCDM) method G1-EW-MGLA (GEM)-AHPSort II method is proposed by combining AHPSort II method, G1-EW method, and MGLA method. Secondly, the evaluation indicator system of regional flood resilience is constructed from the perspective of objective and managerial factors. Subsequently, the proposed method and indicator system were applied to the case of flood resilience evaluation in Hubei Province, China. The case study analysis results show that in the 17 regions involved in the evaluation, the number of regions with “medium-low resilience” and “low resilience” is close to half, and the flood resilience of the regions with high economic development tends to be a higher level. In addition, under the same case data, the evaluation results of the proposed GEM-AHPSort II method are compared against the EW-AHPSort II method and AHPSort II method. The indicator weights determination process of GEM-AHPSort II method has been improved compared with the other two methods, and the evaluation results are more practical. Finally, some management suggestions for effectively improving the regional flood resilience and reducing flood hazards were put forward. This paper can provide a reference for the government to formulate or improve relevant flood protection strategies.

Assessing the impact of floods on vegetation worldwide from a spatiotemporal perspective

The impact of flooding on vegetation ecosystems worldwide has resulted in severe and widespread threats. Despite this, there is a significant knowledge gap in understanding the impact of floods on vegetation. To gain a comprehensive understanding of the response mechanism of the global vegetation ecosystem to flood disasters, it is crucial to assess the loss of vegetation caused by flood events. In this study, we analyzed 3325 flood events around the world from 2001 to 2020, including the geographic distribution, start and end dates, duration, severity and affected areas. Using kernel density estimation, we assessed the exacerbated severity and magnitude of flood occurrences, identifying spatial clustering of events. Through moving average was utilized to reveal the prolonged trends in areas impacted by floods. Additionally, by spatially matching with global land cover products, we comprehensively explored the magnitude, range, and progression of the impact of floods on vegetation. The findings indicate that (1) Extreme flood events have been increasing in number, affected area, severity, and magnitude since the 21st century, with the majority of events occurring between 10°S-50°N. (2) Strong spatial clustering of flood events was identified in the southeast of North America, the southeast of South America, the east of Africa, the south of Europe, and the south of Asia. (3) Flood hazards in frequent flood-affected areas pose severe threats to the terrestrial vegetation ecosystem, highlighting the necessity of further detailed estimation of flood damages to vegetation at a global scale. This research provides an extensive evaluation of the impact of floods on vegetation at the global-national-regional scale, with a focus on understanding the temporal trends and spatial distribution characteristics over the past 20 years (2001–2020).

Household Flood Severity and Migration Extent in Central Java: Analysis of the Indonesian Family Life Survey.

Central Java, Indonesia, is prone to river and coastal flooding due to climate changes and geological factors. Migration is one possible adaptation to flooding, but research is limited due to lack of longitudinal spatially granular datasets on migration and metrics to identify flood-affected households. The available literature indicates social and economic barriers may limit mobility from flood prone areas. The Indonesian Family Life Survey (IFLS) provides self-reported data on household experiences with natural disasters among 1501 Central Java households followed over two waves (2007 and 2014). We examined how the severity of flooding, defined by household-level impacts captured by the IFLS (death, injury, financial loss, or relocation of a household member), influenced the extent of household movement in Central Java using a generalized ordered logit/partial proportional odds model. Households severely impacted by floods had 75% lower odds of moving farther away compared to those that did not experience floods. The most severely impacted households may be staying within flood-affected areas in Central Java. Public health, nutrition, and economic surveys should include modules focused on household experiences, impacts, and adaptations to facilitate the study of how climate changes are impacting these outcomes.

The mental and maternal health of women in flood-affected areas in Pakistan: a call for action

The mental and maternal health of women in flood-affected areas in Pakistan: a call for action

Photogrammetry Technology by Using DJI Phantom 4 RTK in Batang Mahat, Lima Puluh Kota Regency West Sumatera

Technological developments in the field of engineering have increased rapidly. The use of geospatial information becomes one of the bases for decision-making related to planning, managing, and evaluating a field, especially in engineering, which includes the field of measurement and making topographic maps or Digital Elevation Model (DEM). High-resolution geospatial information can create a high-resolution Digital Elevation Model (DEM) map that can be very useful in making models or maps of flood-affected areas. This research will use the photogrammetry technology with DJI Phantom 4 RTK to create the DEM data of Batang Mahat located in Lima Puluh Kota Regency, West Sumatra Province. 28 flights at predetermined points had carried out to measure the area of about 9 km2. All the results of photos captured by the drone will be imported to Agisoft Metashape 1.8.2 software to create the DEM data. The DEM was then compared with DEM data from DEMNAS and the measurement data of Batang Mahat by the SDABK office. The result shows that photogrammetry technology using DJI Phantom 4 RTK compared to measurement data and DEMNAS have a similar ground elevation but different river elevation. This is because the photogrammetry by using DJI Phantom 4 RTK is not equipped with LiDAR. An alternative to solve the problem is by combining the DEM data by DJI Phantom 4 RTK with data from terrestrial surveys. However, this method is quite expensive and ineffective in analyzing flood inundation compared to DEM data (8 m resolution) from DEMNAS.

An integrated convolutional neural network and sorting algorithm for image classification for efficient flood disaster management

Drones are used for post-flood disaster management and delivering relief goods to flood-affected areas. Autonomous drones are an alternative means of prioritizing assistance due to the lack of available technology and accessibility in many affected areas during floods. This study proposes a machine-learning approach designed and developed for autonomous drones to identify flood-affected areas with image classification. The proposed integrated approach can be used to deliver relief on a priority basis from the most affected areas to the least affected areas considering distance for efficiency. The proposed system uses a combined convolutional neural network (CNN) and sorting algorithm. The Inception v3 and DenseNet CNN approach can effectively detect flood severity. The Inception v3 shows better performance than DenseNet in terms of image classification. The Inception v3 and DenseNet architectures achieve 83% and 81% accuracy in our self-made flood level dataset, respectively. The integrated algorithm is used to sort the data efficiently. This study demonstrates the efficacy of CNN combined with a sorting algorithm for autonomous decision-making in robotic architecture.

Extraction and Classification of Flood-Affected Areas Based on MRF and Deep Learning

Floods can cause huge damage to society, the economy, and the environment. As a result, it is vital to determine the extent and type of land cover in flooded areas quickly and accurately in order to facilitate disaster relief and mitigation efforts. Synthetic aperture radar (SAR) is an all-weather, 24 h data source used to extract information about flood inundations, and its primary aim is to extract water body information for flood monitoring. In this study, we have studied the backscattering characteristics of water and non-water, combined the threshold segmentation method with Markov random fields (MRF), and embedded simulated annealing (SA) in the process of image noise reduction, resulting in the development of a water extraction method KI-MRF-SA with high accuracy in classification and high automation. Furthermore, object-scale adaptive convolutional neural networks (OSA-CNN) are introduced for the classification of optical images before the flood in order to provide reference data for flood inundation analysis. The method proposed in this study consists of the following three steps: (1) The Kittler and Illingworth (KI) thresholding algorithm is used for the segmentation of SAR images in order to determine the initial flood inundation extent; (2) MRF and SA algorithms are employed as a means to optimize the initial flood inundation extent, and the results are combined across multiple polarizations by using an intersection operation to determine the final flood inundation extent; and (3) As part of the flood mapping process, land cover types before the flood are classified using OSA-CNN and combined with flood inundation extents. According to the experimental results, it is evident that the proposed KI-MRF-SA method is capable of distinguishing water from non-water with significantly higher accuracy (3–5% improvement in the overall accuracy) than conventional thresholding methods. Combined with the classification method of OSA-CNN proposed in our earlier research, the overall classification accuracy of flood-affected areas could reach 92.7%.

Psychological Effect on children at Secondary Level after Flood Disaster District RajanPur

The aim of this study was to investigate the psychological effects of flooding on secondary school children in the Rajanpur, Jampur, Taunsa, Dera Ghazi Khan, and Fazalpur districts. A total of 150 students from public schools in flood-affected areas participated in the study, which used a non-probability convenience sampling approach and a self-administered questionnaire to collect data. The collected information was then analyzed using descriptive statistics, such as percentage and mean scores, with the Statistical Package for Social Science (SPSS). The study found that the majority of students experienced negative psychological impacts from the flooding, including impacts on their emotional, mental, and academic development. Although both male and female students were affected, females experienced higher levels of psychological effects. This study highlights the importance of reducing flood risk before disasters occur, which can greatly reduce the devastating effects of floods. To effectively manage risks, it is essential to have a thorough understanding of the causes and risks associated with flooding.

Extreme flood in Pakistan: Is Pakistan paying the cost of climate change? A short communication

Global warming is one of the foremost causes of changes in climate patterns around the world. Pakistan is among the top ten countries affected by global warming. Today, Pakistan is facing severe consequences of global warming in the form of an extreme flood. It affected 33 million people, destroyed 1.5 million homes, and caused $2.3 billion in crop damage. It has also damaged more than 2000 km of roads, cutting off connectivity to provinces and major cities. Thus, inflation in Pakistan has reached its highest level, i.e. 26 % – 27 %, and a severe food crisis is not far away. Recently, Pakistan noted a record temperature of 40 °C in several territories, notably 51 °C in Jacobabad. The study reported that high temperatures, melting glaciers, heavy monsoon rains, government inattention, and poor governance are the key reasons of this severe flood. Moreover, in 2080, the average temperature in Pakistan is predicted to increase by 4.38 degrees Celsius. The study suggested that Supply of cheap seeds and fertilizers to farmers, maintenance of water supply infrastructure, availability of food and medicines through domestic and foreign assistance, and reduction of electricity rates and taxes in flood-affected areas can be the solution to stop this crisis. Similarly, building dams, investing in technology and training, and educating the general public about environmental change should be included in the long-term goals to avoid future disasters.

Integrated Flood Hazard Vulnerability Modeling of Neluwa (Sri Lanka) Using Analytical Hierarchy Process and Geospatial Techniques

This research aimed to apply the geospatial techniques and Analytical Hierarchy Process (AHP) approach to find vulnerable areas in terms of flooding in the Neluwa area, Sri Lanka. The study incorporated nine relevant criteria for the vulnerability classification under three sub-criteria; the built environment, physical environment, and socio-economic environment. Under the built environment, road networks and buildings were chosen as sub-criteria. The Normalized Difference Vegetation Index (NDVI), slope, elevation, water bodies, and stream density were taken as physical criteria. Land use and population density were considered as socio-economic criteria. All the criteria are set correctly in raster data, and their contents were well adduced. The study consisted of the use of different levels of criteria and combinations of different processes. The analytical results reveal that 14.24% and 30.24% of the total area are at a very-high risk and high risk for flooding, respectively. Only 5.17% of the land was classified as a risk-free area. Eastern, central, and western divisions of the study area are highly vulnerable to floods due to their low slopes. Based on the produced maps, the spatial extents and levels of risk were systematically identified. Data obtained through qualitative judgments related to the field were validated based on the approach used. The potential of this approach is effective in assessing the spatial vulnerability of these flood-affected areas. Using such criteria and a model-based approach will be constructive in identifying different flood scenarios and in providing a remunerative guideline for potential anticipatory measures and better land-based planning in the area.

Peran Kepala Desa dalam Menanggulangi Banjir di Desa Monas Kecamatan Monano Kabupaten Gorontalo Utara

This study aims to determine the Role of Village Heads in Overcoming Floods in Monas Village, Monano District, North Gorontalo Regency. This research consists of three focuses, namely Coordinator, Motivator and supervision. The research method used is descriptive qualitative. The results of the study concluded that the coordinator carried out with the Regional Disaster Management Agency (BPBD), BPD, and the head of the hamlet about flood management in Monas Village was not optimal, so that in the event of a flood, BPBD was considered slow in preparing emergency response places or posts, setting up public kitchens, providing basic needs for the community. The village government also lacks monitoring of the condition of the area and environment in Monas village. Lack of dredging and installation of fugitives in flood-affected areas. The motivator carried out by the Village Head in flood management in Monas Village has not been optimal. This can be seen from the lack of participation between the village government and the community in tackling floods, supervision in tackling floods in Monas Village has not been optimal. This can be seen from the attitude or habit of the community who always throw garbage in the river area, the participation of people in flood-affected areas is still very low, the village government rarely checks environmental conditions such as river conditions, waterways and others so that the community also lacks the encouragement to maintain or maintain the cleanliness of the environment.

Infant and Young Child Feeding (IYCF) practices and it’s determinants in flood-affected communities in Edo State, Nigeria

The immediate effect of child malnutrition in Africa is morbidity. In the longer term, it limits the child’s potential for life even when the child manages to survive its instantaneous effects. This cross-sectional study focused on investigating the socio-demographic determinants of the components of Infant and Young Child Feeding (IYCF) in flood-affected Local Government Areas (LGAs) in Edo State, Nigeria. A total of 400 mothers were interviewed using a semi-structured questionnaire. Results from this current study indicate that only about 48% of mothers surveyed exclusively breastfed theirs under 5 children. Also, only about 55% of mothers initiated breastfeeding within 1 hour of birth and gave colostrum, and about 45% of the mothers actually adhered strictly to the prescribed complementary feeding practice of giving nutritionally adequate and safe complementary foods alongside breastfeeding at six months up till 2 years of age and even beyond. Education, source of income, marital status, and access to healthcare facilities were strong influencers of misconceptions and other factors impeding the implementation of the core components of IYCF as observed in this study. Flood remains a significant contributing factor depleting household food security structures leading to maternal and infant malnutrition. A concerted governmental coordinated intervention is required to relieve flood-affected families of the burden of malnutrition and infectious diseases. Training and retraining of health workers will be helpful in strengthening community involvement in implementing and monitoring IYCF components in the community. Longer maternity leave for nursing mothers should be strongly advocated for.

Community of analysis mitigation and adaptation to the flood disaster overload of Lake Tempe, Wajo Regency

<p>In South Sulawesi, Wajo Regency is one of the areas prone to flooding during the rainy season. Floods that occur in the area cause inundation. The inundation that occurred was caused by the overflow of Lake Tempe. This research was conducted in Laelo Village, Tempe District, which is located around the Tempe Lake Coast. This location was chosen purposively with the consideration that the area has become a frequent flood in the western part of the kelurahan (the part near the lake). The village has a low contour in the west and high in the east. The research design is descriptive and qualitative which aims to describe the state or status of the phenomenon. The purpose of the research is to analyze the forms of adaptation and mitigation that will be carried out by communities in flood-affected areas. This research uses field surveys, in-depth interviews, making field notes, and documentation. The data collection method was carried out using purposive sampling because the desired sample in the study was only people living in the coastal area of the lake, namely in Laelo Village which was only affected by flooding, not the entire Laelo Village community. Data analysis techniques in qualitative descriptive research are carried out with interactive analysis in the form of cycles. Data analysis was carried out simultaneously with the implementation process of data collection. The results of interviews with the community show that they understand that flooding is an ordinary natural phenomenon which is an overflow of a lake, but they do not know why there is a flood. Some people who live on the shores of the lake feel that almost every year they are exposed to floods from the lake. Where the form of adaptation they do is to raise the pole of the house and prepare a boat that is moored under the house to be used as a means of transportation in the event of a flood. Several forms of mitigation that have been carried out are water hyacinth retaining embankments, and making taller bridges with concrete connecting roads from house to house. Information has been found regarding evacuation signs with the evacuation route installed, the mosque is used as a place to disseminate information related to the incident and development of the flood. It is better to form a disaster-resilient village in the area to create an area that is more prepared to face disasters.</p>

Coping with floods: impacts, preparedness and resilience capacity of Greek micro-, small- and medium-sized enterprises in flood-affected areas

PurposeThis paper aims to investigate aspects of flood experience, attitudes and responses of micro-, small- and medium-sized enterprises (MSMEs) in Greece and to indicate a typology of strategies associated with their relative effort to build flood resilience capacity.Design/methodology/approachA qualitative study protocol was used, based on pertinent literature that considers how business entities withstand, adapt and/or recover from non-linear climate change impacts, natural hazards and extreme weather. Data was obtained by conducting semi-structured interviews with 82 MSMEs’ owners-managers who had recently experienced flooding.FindingsThe study reports limited activities of MSMEs towards flood resilience capacity despite the threat of relevant disasters. Findings suggest that most owners-managers of these enterprises are not adequately preparing their businesses for the impacts of flooding.Research limitations/implicationsThe findings call for multi-level and dynamic perspectives to be examined in assessing MSME resilience capacity to floods. It is attitudinal, managerial, organisational, behavioural and regulatory (as well as other institutional) factors that merit further investigation. Such an investigation would allow a better understanding as to whether these factors hinder or enable conditions for microeconomic flood preparedness and resilience as well as how they may interact with each other or create feedback loops.Practical implicationsThe study carries managerial implications and policy recommendations in terms of nurturing opportunities towards awareness-raising campaigns for reducing deficits in managerial knowledge and competencies. It also encapsulates practical implications in terms of emphasising supporting mechanisms from key institutional stakeholders to allow MSMEs scan available options they have in effectively reinforcing the business premises from the forces of rising waters.Originality/valueMost of the related studies have examined flood impacts, responses and/or resilience capacity at the household- or community-level. Empirical work that is conducted to ascertain how MSMEs cope with flooding remains thin on the ground. In response to this, the current study and the typology of MSMEs’ strategic postures that are suggested seek to contribute to this under-researched topic.

Gender disparity in minimum dietary diversity failure among currently breastfed children aged 6-23 months in Bangladesh: evidence from Bangladesh Multiple Indicator Cluster Survey, 2019.

Research on children's dietary diversity plays a crucial role in designing effective health interventions. Thus, this study aimed to identify the factors contributing to minimum dietary diversity failure (MDDF) among male and female children aged 6-23 months in Bangladesh. The data for this study was obtained from the Bangladesh Multiple Indicator Cluster Survey, 2019, which included children currently breastfed within a specific age range. Multivariable binary logistic regression was employed to assess the strength and significance of the association. The findings revealed that approximately 59⋅4 % of children in Bangladesh experienced MDDF, with 57⋅8 % of male children and 61 % of female children affected. Proportion test uncovered a significant gender disparity (χ2=6⋅58, P-value = 0⋅01) among children aged 6-23 months. However, the multivariable binary logistic regression analysis revealed that both male and female children shared common risk factors for MDDF, which included child age, maternal educational status, wealth status, number of antenatal care visits, and division. In our study, we observed varied spatial patterns in minimal dietary diversity. Sherpur, Netrokona, Sunamganj, and Sylhet districts showed the highest failure rates. Notably, all are flood-affected areas, impacting food availability and diversity. For targeted regional development programmes, district mapping results may offer valuable insights to policymakers, especially in areas with a high prevalence of dietary diversity failure. By understanding these risk factors, policymakers and stakeholders can implement targeted strategies to improve dietary diversity among children, promoting better health and well-being for the young population in Bangladesh.

LiDAR DTM Application for Flood Inundation Modeling and Visualization (Case Study: Batu City, East Java)

LiDAR DTM has been widely used for simulating flood inundation from river overflows. This flood inundation simulation needs to be done as an alternative step in the flood control system and flood disaster mitigation to determine the estimated area affected by the flood. Flood simulation is a form of unsteady flow that is simulated with the HEC-RAS program that allows the user to perform one-dimensional steady flow, one and two-dimensional unsteady flow calculations, sediment transport/mobile bed computations, and water temperature/water quality modeling, and visualizes flooded areas and flood-affected areas using a geographic information system approach. Hydrological data is obtained from daily rainfall processing at the time of station rain. Hydrograph analysis was performed using the SCS CN model on the HEC-HMS software to estimate the flow rate and peak discharge. Watershed area, curve number, Impervious value, Initial ion, and time lag are parameters that affect hydrograph analysis. From the results of the hydrograph analysis, the peak discharge of the model is 119.992 m2/s. Meanwhile, hydraulic analysis using HEC-RAS resulted in an inundation of 364 m2 which inundated three villages, namely Bulukerto, Bumiaji and Sidomulyo villages. The depth of the inundated area ranged from 0-15 m with an average depth of 4.534 m. The Sidomulyo area affected by the flood inundation scenario is 4,924 meters with an area of 0,02 ha. Bumiaji village was flooded with an area of 0,007 ha with a scenario of inundation depth of 4,049 m. Bulukerto village which was affected by the flood has an area of 20,972,832 m2 with a scenario of inundation depth reaching 4,343 m. Then some land cover such as residential land that is inundated by this flood simulation is 0,002 ha. Buildings from residential areas that were flooded reached 209 buildings. Then the area of agricultural land affected is 0,02 ha. In addition, there are also green open spaces affected by this simulation with an inundation area of 0,003 ha.

Effect of recent floods on women’s reproductive health in Pakistan: an alarming situation

The most frequent natural calamity in developed and developing nations is flooding, which has significantly increased morbidity and mortality globally. Over the previous 30 years, flooding has harmed more than 2.8 billion people globally and claimed the lives of over 200,000 individuals. The effect of floods on a population’s health varies depending on the population’s vulnerability. It greatly impairs the quality of life of everyone in the affected area. However, pregnant women are more vulnerable to the negative impact of flood-related changes, and floods may have a variety of detrimental psychological and pathological impacts on women’s reproductive health. The UN Population Fund predicts that 1700 women will give birth each day, and ~500,000 pregnant women will be affected by the catastrophe of the flood. According to the United Nations Population Fund (UNFPA), about 650,000 pregnant women in flood-affected areas need maternal health services to ensure a healthy pregnancy and delivery. Up to 73,000 expectant mothers will require competent delivery attendants, neonatal care, and support in the upcoming month.

Optimization of water filter station locations on polluted rivers of Jakarta

Flooding has always been one of the challenging problems Jakarta faces for decades, damaging not only the infrastructure but also the economic aspects of the city. Almost every year, significant losses are recorded in both parts, including for the residents who depend on it. One of the repressive steps for flood prevention is the placement of waste filtering stations on the rivers in multiple locations. According to the Ministry of Environment and Forestry representative for Jakarta, there are currently 28 waste filtering stations installed within Jakarta's 661.5 km2 region and 13 rivers. Continuously challenged with the increasing amount of waste, flood prevention efforts must include installing more filtering stations. Therefore, studying the optimum future station location to minimize the flooding hazard effectively becomes vital. This paper utilized the Hot Spot Spatial Analysis method to estimate several optimal areas that fit the criterion of previously built filtering stations. We obtained the local hotspot statistics for each parameter from the Getis-Ord local statistics equation. In addition, many necessary layers are also utilized, such as volume of waste filter points, population density, and flood-affected areas datasets to roughly approximate the real-world condition. This study aims to provide recommendations that can determine the optimal waste filtering points and provide a better solution for Jakarta from the problem of the harmful amount of waste in the river that could induce flooding hazards. The result shows that the waste filtering stations in the 13 major rivers in Jakarta are still not effective. This research helps to show the optimal locations suitable for constructing new waste filters.

Assessing Community Resilience from a Gendered Perspective: A Case Study of Flood Affected Areas of D.G. Khan, Pakistan

The current study aims to investigate the impact of floods in the rural areas of Dera Ghazi Khan, Punjab, Pakistan. Floods are a natural disaster that wreak havoc across the country but have disproportionate consequences for different genders. Flooding is a constant threat to the community resilience, especially in the remote areas. Lack of awareness and poverty makes the situation even more deplorable and triggers certain gendered issues in flood-affected areas. The prime concern of the current study is to highlight gendered issues, as an impact of floods in D.G. Khan Floods are a major natural disaster with greater impact on women rather than men due to work routine of the males. Floods have a major effect on the physical, social, and psychological aspects of a community which directly impact the lives of both men and women and increases their vulnerability. The current study has highlighted serious gender issues experienced by the inhabitants of D.G. Khan, further causing vulnerability for both genders, especially for women. Thereby, they become a more vulnerable part of the community. The feeling of suffering and helplessness that follows a natural disaster has a devastating impact on the population. As a result, the current case study has concentrated on the vulnerability of both genders, as there is a need to instill community resilience in both.

PHBS BAGI ANAK PENYINTAS BENCANA DI SDN INPRES 1 DESA ROGO KECAMATAN DOLO SELATAN KABUPATEN SIGI

In 2021 there were 3,058 disasters, 42.1% were floods. One of the flood-affected areas was Rogo Village, the disaster would be followed by the emergence of refugees who were not supported by adequate sanitation facilities, this could trigger an outbreak so that knowledge of PHBS especially a childrens needs to be improved. Behavior change is not instantaneous, to accelerate the process, efforts are needed to increase knowledge and supporting facilities. The academic community of public health faculty will provide education for students at Inpres 1 Rogo Elementary in South Dolo District, Sigi Regency regarding PHBS steps that must be carried out in post-disaster conditions. This community service was carried out on 16th July 2022, starting with a pre-test to measure the participants' prior knowledge regarding PHBS and after the counseling it would end with a post-test to measure their increases of knowledge. The activity was attended by 23 students and 4 teachers. Based on the results of the pre-post test, it is known that the extension materials can increase the participants' knowledge regarding PHBS, this can be seen from the increase in the post-test scores. The highest increase in knowledge related to handwashing steps in accordance with the Ministry of Health guidelines, the value increased from 0% to 92.34%. Meanwhile, students' understanding of the requirements for “Jajan Sehat” has not been maximized even after being given education, this is illustrated by the increases scores of in participant is 21.73% to 78.26%, this it lower than the increases a scores of participants in other sections.