• Title/Summary/Keyword: Drought and fire

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Assessment of Drought on the Goseong-Sokcho Forest Fire in 2019 using Multi-year High-Resolution Synthetic Precipitation Data

  • Sim, Jihan;Oh, Jaiho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.379-379
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    • 2020
  • The influence of drought has increased due to global warming. In addition, forest fires have occurred more frequently due to droughts and resulted in property losses and casualty. In this study, the effects of drought on Goseong-Sokcho Forest Fire in 2019 were analyzed using high-resolution synthetic precipitation data. In order to determine the severity of drought, the average, 20%tile and 80%ile values were calculated using the synthetic precipitation data of the past 30 years and compared with the current climatology. We have investigated the multi-year accumulated precipitation data to determine the persistence of drought. In Goseong-Sokcho forest fire case, the two-year cumulative synthetic precipitation data shows a similar value to the climate, but the three-year cumulative synthetic precipitation data was close to the 20%ile lines of the climate value. It may expose that the shortage of precipitation in 2017 had persisted until 2019, despite abundant precipitation during the summer in 2018. Therefore, Goseong-Sokcho forest fire might be spread more rapidly by drought which has been persisted since 2017.

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Development of Mid-range Forecast Models of Forest Fire Risk Using Machine Learning (기계학습 기반의 산불위험 중기예보 모델 개발)

  • Park, Sumin;Son, Bokyung;Im, Jungho;Kang, Yoojin;Kwon, Chungeun;Kim, Sungyong
    • Korean Journal of Remote Sensing
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    • v.38 no.5_2
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    • pp.781-791
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    • 2022
  • It is crucial to provide forest fire risk forecast information to minimize forest fire-related losses. In this research, forecast models of forest fire risk at a mid-range (with lead times up to 7 days) scale were developed considering past, present and future conditions (i.e., forest fire risk, drought, and weather) through random forest machine learning over South Korea. The models were developed using weather forecast data from the Global Data Assessment and Prediction System, historical and current Fire Risk Index (FRI) information, and environmental factors (i.e., elevation, forest fire hazard index, and drought index). Three schemes were examined: scheme 1 using historical values of FRI and drought index, scheme 2 using historical values of FRI only, and scheme 3 using the temporal patterns of FRI and drought index. The models showed high accuracy (Pearson correlation coefficient >0.8, relative root mean square error <10%), regardless of the lead times, resulting in a good agreement with actual forest fire events. The use of the historical FRI itself as an input variable rather than the trend of the historical FRI produced more accurate results, regardless of the drought index used.

The Effects of Drought on Forest and Forecast of Drought by Climate Change in Gangwon Region

  • Chae, Hee-Mun;Lee, Sang-Sin;Um, Gi-Jeung
    • Journal of Forest and Environmental Science
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    • v.28 no.2
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    • pp.97-105
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    • 2012
  • A Gangwon region consisting of over 80% of forest area has industries that have been developed by utilizing its clean region image. However, the recent climate change has increased the forest disease & insect pest as well as the forest fire and the major cause is known to be the increase in the frequency of a drought occurrence. From the aspect of climate change, it can be said that drought and forest are important in every aspect of the adaptation and mitigation of climate change measure as they increase forest disease & insect pest that leads to desolation of usable forest resource. In addition, the increase of forest fire reduces resources that can absorb greenhouse gas, which leads to increase in green house emission. The purpose of this study is to provide a motive for concentrating administrative power for protecting forest in a Gangwon region by selecting a drought management needed local government through a drought forecast according to the climate change scenario of a Gangwon region.

Evaluating Impact Factors of Forest Fire Occurrences in Gangwon Province Using PLS-SEM: A Focus on Drought and Meteorological Factors (PLS-SEM을 이용한 강원도 산불 발생의 영향 요인 평가 : 가뭄 및 기상학적 요인을 중심으로)

  • Yoo, Jiyoung;Han, Jeongwoo;Kim, Dongwoo;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.41 no.3
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    • pp.209-217
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    • 2021
  • Although forest fires are more often triggered by artificial causes than by natural causes, the combustion conditions that spread forest fire damage over a large area are affected by natural phenomena. Therefore, using partial least squares structural equation modeling (PLS-SEM), which can analyze the dependent and causal relationships between various factors, this study evaluated the causal relationships and relative influences between forest fire, weather, and drought, taking Gangwon Province as our sample region. The results indicated that the impact of drought on forest fires was 27 % and that of the weather was 38 %. In addition, forest fires in spring accounted for about 60 % of total forest fires. This indicatesthat along with meteorological factors, the autumn and winter droughts in the previous year affected forest fires. In assessing the risk of forest fires, if severe meteorological droughts occur in autumn and winter, the probability of forest fires may increase in the spring of the following year.

Multivariate assessment of the occurrence of compound Hazards at the pan-Asian region

  • Davy Jean Abella;Kuk-Hyun Ahn
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.166-166
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    • 2023
  • Compound hazards (CHs) are two or more extreme climate events combined which occur simultaneously in the same region at the same time. Compared to individual hazards, the combination of hazards that cause CHs can result in greater economic losses and deaths. While several extreme climate events have been recorded across Asia for the past decades, many studies have only focused on a single hazard. In this study, we assess the spatiotemporal pattern of dry compound hazards which includes drought, heatwave, fire and wind across Asia for the last 42 years (1980-2021) using the historical data from ERA5 Reanalysis dataset. We utilize a daily spatial data of each climate event to assess the occurrence of such compound hazards on a daily basis. Heatwave, fire and wind hazard occurrences are analyzed using daily percentile-based thresholds while a pre-defined threshold for SPI is applied for drought occurrence. Then, the occurrence of each type of compound hazard is taken from overlapping the map of daily occurrences of a single hazard. Lastly, a multivariate assessment are conducted to quantify the occurrence frequency, hotspots and trends of each type of compound hazard across Asia. By conducting a multivariate analysis of the occurrence of these compound hazards, we identify the relationships and interactions in dry compound hazards including droughts, heatwaves, fires, and winds, ultimately leading to better-informed decisions and strategies in the natural risk management.

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Estimation of Available Days for a Cloud Seeding Experiment in Korea (한반도 목적별 인공강우 실험가능일 추정)

  • Jung, Woonseon;Chang, Ki-Ho;Cha, Joo Wan;Ku, Jung Mo;Lee, Chulkyu
    • Journal of Environmental Science International
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    • v.31 no.2
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    • pp.117-129
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    • 2022
  • In this study, we investigated the characteristics of the meteorological and environmental conditions for a cloud seeding experiment over the Korean peninsula and estimated the available days for the same. The conditions of available days appropriate for a cloud seeding experiment were classified according to four purposes: water resources, drought relief, forest fire prevention, and air quality improvement. The average number of available days for a cloud seeding experiment were 91.27 (water resources), 45.93-51.11 (drought relief), 40.28-46.00 (forest fire prevention), and 42.19-44.60 days/year (air quality improvement). If six experiments were carried out per available day for a cloud seeding experiment, the number of times cloud seeding experiments could be conducted per year in a continuously operating system were estimated as 547.62 (water resources), 275.58-306.66 (drought relief), 241.68-276.00 (forest fire prevention), and 253.14-267.60 times/year (air quality improvement). From this result, it was possible to determine the appropriate meteorological and environmental conditions and statistically estimate the available days for a cloud seeding experiment. The data on the available days for a cloud seeding experiment might be useful for preparing and performing such an experiment.

Correlation Analysis of Forest Fire Occurrences by Change of Standardized Precipitation Index (SPI 변화에 따른 산불발생과의 관계 분석)

  • YOON, Suk-Hee;WON, Myoung-Soo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.2
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    • pp.14-26
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    • 2016
  • This study analyzed the correlation between the standardized precipitation index(SPI) and forest fire occurrences using monthly accumulative rainfall data since 1970 and regional fire occurrence data since 1991. To understand the relationship between the SPI and forest fire occurrences, the correlations among the SPI of nine main observatory weather stations including Seoul, number of fire occurrences, and log of fire occurrences were analyzed. We analyzed the correlation of SPI with fire occurrences in the 1990s and 2000s and found that in the 1990s, the SPI of 3 months showed high correlation in Gyeonggi, Gangwon, and Chungnam, while the SPI of 6 months showed high correlation in Chungbuk, and the SPI of 12 months showed high correlation in Gyeongnam, Gyenongbuk, Jeonnam, and Jeonbuk. In the 2000s, the SPI of 6 months showed high correlation with the fire frequency in Gyeonggi, Chungnam, Chungbuk, Jeonnam, and Jeonbuk, whereas the fire frequency in western Gangwon was highly correlated with the SPI of 3 months and, in eastern Gangwon, Gyeongnam, and Gyenongbuk, with the SPI of 1 month. In the 1990s, distinct differences in the drought condition between the SPI of 3 months and 12 months in the northern and southern regions of Korean Peninsula were found, whereas the differences in both the SPI of 1 month and 6 months were found in the Baekdudaegan region except western Gangwon since the 2000s. Therefore, this study suggests that we can develop a model to predict forest fire occurrences by applying the SPI of 1-month and 6-month data in the future.

Evaluating meteorological and hydrological impacts on forest fire occurrences using partial least squares-structural equation modeling: a case of Gyeonggi-do (부분최소제곱 구조방정식모형을 이용한 경기도 지역 산불 발생 요인에 대한 기상 및 수문학적 요인의 영향 분석)

  • Kim, Dongwook;Yoo, Jiyoung;Son, Ho Jun;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.54 no.3
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    • pp.145-156
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    • 2021
  • Forest fires have frequently occurred around the world, and the damages are increasing. In Korea, most forest fires are initiated by human activities, but climate factors such as temperature, humidity, and wind speed have a great impact on combustion environment of forest fires. In this study, therefore, based on statistics of forest fires in Gyeonggi-do over the past five years, meteorological and hydrological factors (i.e., temperature, humidity, wind speed, precipitation, and drought) were selected in order to quantitatively investigate causal relationships with forest fire. We applied a partial least squares structural equation model (PLS-SEM), which is suitable for analyzing causality and predicting latent variables. The overall results indicated that the measurement and structural models of the PLS-SEM were statistically significant for all evaluation criteria, and meteorological factors such as humidity, temperature, and wind speed affected by amount of -0.42, 0.23 and 0.15 of standardized path coefficient, respectively, on forest fires, whereas hydrological factor such as drought had an effect of 0.23 on forest fires. Therefore, as a practical method, the suggested model can be used for analyzing and evaluating influencing factors of forest fire and also for planning response and preparation of forest fire disasters.

Projecting forest fire potential in the Baekdudaegan of the Chungcheong region under the SSP scenario climate change using KBDI Drought Index (KBDI 가뭄지수를 이용한 SSP 기후변화 시나리오하의 충청지역 백두대간 산불 잠재력 전망)

  • Choi, Jaeyong;Kim, Su-Jin;Jung, Huicheul;Kim, Sung-Yeol;Moon, Geon-Soo
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.25 no.6
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    • pp.1-11
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    • 2022
  • Recently, climate change has been regarded as a major cause of large-scale forest fires worldwide, and there is concern that more frequent and severe forest fires will occur due to the level of greenhouse gas emissions. In this study, the daily Keetch and Byram Drought Index (KBDI) of the Baekdudaegan in Chungcheong region including Sobaeksan, Songnisan, and Woraksan National Parks were calculated to assess effect of climate change on the forest fire potential- severity of annual maximum KBDI and frequency of high KBDI days. The present (2000~2019) and future KBDI(2021~2040, 2041~2060, 2081~2090) were calculated based on the meteorological observation and the ensemble regional climate model of the SSP1-2.6 and SSP5-8.5 scenarios with a spatial resolution of 1-km provided by Korea Meteorological Administration(KMA). Under the SSP5-8.5 scenario, 6.5℃ increase and 14% precipitation increase are expected at the end of the 21st century. The severity of maximum daily KBDI increases by 48% (+50mm), and the frequency of high KBDI days (> 100 KBDI) increases more than 100 days, which means the high potential for serious forest fires. The analysis results showed that Songnisan National Park has the highest potential for forest fire risk and will continue to be high in intensity and frequency in the future. It is expected that the forest vulnerability of the Baekdudaegan in the Chungcheong region will greatly increase and the difficulty in preventing and suppressing forest fires will increase as the abundance of combustible materials increases along with climate changes.

Development of Large Fire Judgement Model Using Logistic Regression Equation (로지스틱 회귀식을 이용한 대형산불판정 모형 개발)

  • Lee, Byungdoo;Kim, Kyongha
    • Journal of Korean Society of Forest Science
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    • v.102 no.3
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    • pp.415-419
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    • 2013
  • To mitigate forest fire damage, it is needed to concentrate suppression resources on the fire having a high probability to become large in the initial stage. The objective of this study is to develop the large fire judgement model which can estimate large fire possibility index between the fire size and the related factors such as weather, terrain, and fuel. The results of logistic regression equation indicated that temperature, wind speed, continuous drought days, slope variance, forest area were related to the large fire possibility positively but elevation has negative relationship. This model may help decision-making about size of suppression resources, local residents evacuation and suppression priority.