Influence of forest humidity on the distribution of forest fires in the territory of Serbia

2021 ◽  
Vol 14 (9) ◽  
pp. 8-14
Author(s):  
Stanimir Živanović
Keyword(s):  
Forest Fires ◽  
Drought Index ◽  
Aridity Index ◽  
Administrative District ◽  
Positive Correlation

In this study, we examined the dependence of the influence of forest humidity conditions on the variability of forest fires in Serbia. The changes in values of the Forest Aridity Index (FAI) and the De Martonne Drought Index (IDM) in the period 2009-2018 were analyzed, with an emphasis on 2012 and 2014. Data from ground meteorological measurements at 14 main meteorological stations on the territory of Serbia were used. The analysis of the FAI index determines a positive correlation on the activity of forest fires in the territory of Serbia. FAI values indicate marked increases for 2012 and 2017 when the largest number of forest fires was registered in Serbia. The lowest values of this index are for 2014, when we registered the smallest occurrence of forest fires in Serbia. Decrease in the value of the IDM index was observed during 2011, 2012 and 2017 correlated with a larger number of forest fires in the period. The greatest threat to forests from fire is in the administrative district of Kragujevac (region of Šumadija and Western Serbia) and Vranje (region of Southern and Eastern Serbia) and the lowest in the area of Sombor and Kikinda (region of Vojvodina). At nine of the fourteen meteorological stations, the De Martonne Drought Index (IDM) showed stronger connection with the occurrence of forest fires compared to the Forest Aridity Index (FAI).

scholarly journals A new early warning drought index for Ethiopia

2018 ◽  
Vol 9 (3) ◽  
pp. 624-630
Author(s):  
Yonas Tadesse ◽  
Aklilu Amsalu ◽  
Paolo Billi ◽  
Massimiliano Fazzini
Keyword(s):  
Early Warning ◽  
Drought Index ◽  
Aridity Index ◽  
Precipitation Index ◽  
Z Score ◽  
Standard Precipitation Index ◽  
Eastern Ethiopia ◽  
Rain Gauges ◽  
Dire Dawa ◽  
Seeding Time

Abstract This study investigates the occurrence of droughts in the Dire Dawa area of eastern Ethiopia. A new index based on the rainfall delay (Rd) with respect to the expected onset (and traditional) seeding time and other indices, i.e., the aridity index and the Z-score, alternatives to the Standard Precipitation Index (SPI), are used to test the validity of the new Rd index in identifying severe droughts extending back to 1955. Although only data of rain gauges located in the district of Dire Dawa were used, they proved, albeit with different accuracies, able to identify nation-wide droughts.

scholarly journals Selection Drought Index Calculation Methods Using Electre, Topsis, and Analytic Hierarchy Process

2018 ◽  
Vol 7 (4.44) ◽  
pp. 188
Author(s):  
Hadisuwito A.S ◽  
Hassan F.H
Keyword(s):  
Analytic Hierarchy Process ◽  
Forest Fires ◽  
Drought Index ◽  
Palmer Drought Severity Index ◽  
Severity Index ◽  
Drought Severity ◽  
Analytic Hierarchy ◽  
Forest Fire Danger ◽  
The Right ◽  
Hierarchy Process

The drought index is an essential indicator for calculating forest fires’ potential. Many methods are developed to maintain the drought index. However, they provide less suitable at many places. Every area has their own character, and each of methods has their own specification. The spot problem is how to find the right method for those places. The forest of Bukit Suharto, has particular character as one of the rain tropical forests, and it needs suitable method. Furthermore, this study is conducted to examine the right methods that compatible for the forest. They are: Palmer Drought Severity Index (PDSI), Keetch Byram Drought Index (KBDI), Reconnaissance Drought Index (RDI), Standard Precipitation Index (SPI), Effective Drought Index (EDI), McArthur Forest Fire Danger Index (MFFDI), and Standard Precipitation Evapotranspiration Index (SPEI). Every method has specific variables for the calculation, namely, the period, the data’s type, the formula’s complexity, the usability, and scale results’ type. On processing the seven methods, the researcher uses other techniques to asses them, namely, ELECTRE, TOPSIS, and Analytic Hierarchy Process. In final process, the conclusion is compared through the result. In summary, the results show that KBDI’s method is the most recommended, and TOPSIS is the best technique for recommendations. 

scholarly journals The Impact of Precipitation Regimes on Forest Fires in Yunnan Province, Southwest China

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Feng Chen ◽  
Shukui Niu ◽  
Xiaojuan Tong ◽  
Jinlong Zhao ◽  
Yu Sun ◽  
...  
Keyword(s):  
Forest Fires ◽  
Yunnan Province ◽  
Drought Index ◽  
Fire Regimes ◽  
Future Climate Change ◽  
Total Precipitation ◽  
Precipitation Regime ◽  
Precipitation Regimes ◽  
In Fire ◽  
The Impact

The amount, frequency, and duration of precipitation have important impact on the occurrence and severity of forest fires. To fully understand the effects of precipitation regimes on forest fires, a drought index was developed with number of consecutive dry days (daily precipitation less than 2 mm) and total precipitation, and the relationships of drought and precipitation with fire activities were investigated over two periods (i.e., 1982–1988 and 1989–2008) in five ecoregions of Yunnan Province. The results showed that precipitation regime had a significant relationship with fire activities during the two periods. However, the influence of the drought on fire activities varied by ecoregions, with more impacts in drier ecoregions IV-V and less impacts in the more humid ecoregions I–III. The drought was more closely related to fire activities than precipitation during the two study periods, especially in the drier ecoregions, indicating that the frequency and the duration of precipitation had significant influences on forest fires in the drier areas. Drought appears to offer a better explanation than total precipitation on temporal changes in fire regimes across the five ecoregions in Yunnan. Our findings have significant implications for forecasting the local fire dangers under the future climate change.

Forecasting drought revisited – the importance of spectral transformations to dominant atmospheric predictor variables

2020 ◽  
Author(s):  
Ashish Sharma ◽  
Ze Jiang ◽  
Fiona Johnson
Keyword(s):  
Forest Fires ◽  
Drought Index ◽  
Predictor Variables ◽  
Lead Times ◽  
Water Restriction ◽  
Climate Forecasts ◽  
Entire Country ◽  
The Future ◽  
Spectral Transformations ◽  
Decadal Climate

<p>As we write this abstract, Australia is experiencing widespread forest fires, Sydney has declared significant water restriction measures curtailing demand, and the entire country is experiencing a drought that is amongst the worst on record. Formulating a stable and practical approach for predicting drought into the future is being realised as an important need, as we enter an era of warmer climates that complicate this problem to an even greater extent. This study presents a novel basis for forecasting drought into the future. Use is made of a recently developed wavelets based methodology for transforming predictor variables so as to force greater consistency in spectral attributes with the response being modelled. Using a commonly adopted drought index, we demonstrate how the wavelets transformed predictor variables can be used to model the response with greater accuracy than otherwise. These transformed predictor variables are then used in conjunction with CMIP5 decadal climate forecasts to demonstrate the accuracy attainable at longer lead times than is currently possible. While our application focusses on the Australian mainland, the method is generic and can be adopted anywhere.</p>

scholarly journals Application of Meteorological and Hydrological Drought Indices to Establish Drought Classification Maps of the Ba River Basin in Vietnam

Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 49 ◽  
Author(s):  
Doan Quang Tri ◽  
Tran Tho Dat ◽  
Dinh Duc Truong
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Assessment Tool ◽  
Swat Model ◽  
Standardized Precipitation Index ◽  
Aridity Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Calibration And Validation

The objective of this study was to establish drought classification maps to simulate and calculate the lack of discharge in the Ba River basin in Vietnam. The maps were established using three meteorological drought indices (the Standardized Precipitation Index (SPI), the Drought Index (J), and the Ped Index (Ped)), the Soil and Water Assessment Tool (SWAT) model, and the hydrological drought index (KDrought). The results from the calculation of the SPI, Aridity Index (AI), and Ped at three stations (An Khe, Ayunpa, and MDrak) showed that the J index was suitable for the study area. Based on the J index, an extreme drought was predicted to occur at the Ayunpa, An Khe, and MDrak stations. During the calibration process, the SWAT Calibration Uncertainties Program (SWAT-CUP) model, with automatic algorithms, was used to select the parameters to optimize the SWAT model. For the calibration and validation, the observed discharge at two hydrology stations, An Khe and Cung Son, from the periods 1981–1991 and 1992–2002, respectively, were used. The simulated discharge was found to be acceptable, with the Nash–Sutcliffe efficiency (NSE), Percent bias (PBIAS), and R2 reaching good levels in both calibration and validation. The results from the calculation of the drought index (KDrought), and the established drought classification maps in 2016, showed that the most affected areas were the communes of the Gia Lai and Dak Lak provinces. The results from the simulation and calculations were found to be consistent with the situation that occurred in practice. The application of meteorological and hydrological drought indices, as well as the hydrological model, to support impact assessments of drought classification in space and time, as well as the establishment of forecasting and warning maps, will help managers to effectively plan policy responses to drought.

scholarly journals Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index

2019 ◽  
Vol 16 (2(SI)) ◽  
pp. 0477
Author(s):  
Hadisuwito Et al.
Keyword(s):  
Forest Fires ◽  
Drought Index ◽  
Preventive Measures ◽  
Preventive Measure ◽  
Fire Risk ◽  
Weather Conditions ◽  
Dry Season ◽  
Several Variables ◽  
The Government ◽  
And Training

Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data is needed about the weather. Therefore, we need an algorithm that can predict the dryness factor. So, the most significant fire potential can be predicted during the dry season. Moreover, daily prediction of the dry season is needed each day to conduct the best action then a qualified preventive measure can be carried out. The method used in this study is the backpropagation algorithm which has functions for calculating, testing and training the drought factors. By using empirical data, some data are trained and then tested until it can be concluded that 100% of the data already well recognized. Furthermore, some other data tested without training, then the result is 60% of the data match. In general, this algorithm shows promising results and can be applied more to complete several variables supporters.

scholarly journals Utilization of ECMWF Seasonal Rainfall Forecast System (SEAS5) for forest fire prediction over Sumatera Island, Indonesia

2021 ◽  
Vol 893 (1) ◽  
pp. 012042
Author(s):  
F Alfahmi ◽  
A Khaerima ◽  
A W Byantoro
Keyword(s):  
Forest Fires ◽  
Lead Time ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Seasonal Rainfall ◽  
Oxygen Production ◽  
Forecast System ◽  
The World ◽  
Sumatra Island ◽  
Calculated Number

Abstract As part of the lungs of the world, the forest which covers Sumatra Island has a significant impact on the world oxygen production and the absorption of carbon dioxide. Drought over Sumatra Island often causes forest fires that can damage the function of forests as the world's lungs. Prediction of the seasonality of forest fires is needed to prevent and overcome forest fires that will occur next month. This study utilized seasonal rainfall predictions to predict the incidence of forest fires based on the drought index obtained. The result showed that ECMWF SEAS5 had good performance to predict rainfall over Sumatera Island for the first until the fourth months (lead time of 0 - 3). The Negative Standardized Precipitation Index (SPI) coincided with the increasing number of the hotspots. Furthermore, a linear equation has been applied to the calculated number of hotspots based on SPI from ECMWF.

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