Drought in Portugal: Current regime, comparison of indices and impacts on extreme wildfires

The effect of spatiotemporal characteristics of drought and wet years on the development of fire occurrence in natural regions of western Iran (Lorestan Province)

Understanding the spatiotemporal relationships of droughts and fires in natural regions is very important to improve decision-making in fire management. For this purpose, the natural regions of Lorestan Province in the west of Iran were selected. Fire data from MODIS satellite products and monthly rainfall data of the province were extracted to estimate the SPI and PDSI for the statistical period of 2000 to 2021. The study examined the annual and monthly correlation between fires and droughts in the province. The results showed that June and July had the highest frequency of fires. The annual fires in the natural regions have been an increasing trend. 2019 experienced the highest number of fires. Winter and spring drought events had a significant correlation with spring and summer fires. In the wetness year of 2019, the frequency of fires was higher than in the dryness year of 2005. The highest fire events were observed in poor to moderate rangelands (0.05 < NDVI < 0.15) in wetness conditions. Despite the smaller area of high-fire risk areas in wetness conditions, a higher frequency of fires can be expected due to the availability of plant biomass during the peak fire period. Although drought is clearly a contributing factor in the spread of fires in the Zagros, the relationship between drought and fire is influenced by more local factors. The map of areas with high fire risk in this study can be used as a preliminary map to identify high-risk areas, especially during critical seasons, and be prioritized by planners.

Humans versus models: a comparative assessment of ecosystem services models and stakeholders' perceptions

Mapping the production of Ecosystem Services (ES) is imperative for sustainable ecosystem management. Likewise, incorporating expert knowledge enhances ES research. Here, we calculate eight multi-temporal ES indicators for mainland Portugal using a spatial modelling approach. These indicators are then integrated into the novel ASEBIO index-Assessment of Ecosystem Services and Biodiversity-which depicts a combined ES potential based on CORINE Land Cover, using a multi-criteria evaluation method with weights defined by stakeholders through an Analytical Hierarchy Process (AHP). Outputs from the modelling show how ES have changed in Portugal in relation to land use changes, including trade-offs between 1990 and 2018. The composed ASEBIO index is compared against the stakeholders' valuation of ES potential for the year 2018. The results reveal a significant mismatch between the ES potential perceived by stakeholders and the models, with stakeholder estimates being 32.8% higher on average. All the selected ES were overestimated by the stakeholders. Drought regulation and erosion prevention have the highest contrasts, while water purification, food production and recreation are the most closely aligned among both approaches. Providing the first national overview about the status of multiple ES over a 28 year-period, our findings highlight potential disparities between data-driven and stakeholder-based evaluations. Therefore, we suggest the need for integrative strategies that consider scientific models with expert knowledge for more effective ES assessments and land-use planning. This approach could help bridge the gap between data-driven models and human perspectives, resulting in more balanced and inclusive decision-making.

Assessing wildfire impact on Trigonella elliptica habitat using random forest modeling

Wildfires have a significant impact on ecosystems worldwide, especially on the degradation of arid and semi-arid rangelands. This research focuses on assessing the effects of wildfires on the habitat of Trigonella elliptica, a valuable herb species found in the central rangelands of Iran. To achieve this, the Random Forest (RF) algorithm has been deployed to predict T. elliptica habitat and fire hazard using socio-environmental variables in Yazd province, Iran. 225 fire points and 103 habitat locations were used for model training and testing. The IncNodePurity index and Probability Curves (PC) have been utilized to determine the influence of socio-environmental variables. The combination of the prediction maps of the habitat and wildfires pointed out the possible damage due to fire. The high performance of the RF model is confirmed by the area under the curve (AUC) and the true skill statistic (TSS) values (0.90 and 0.81 for the habitat; 0.92 and 0.82 for the wildfire). The importance assessment of variables revealed that elevation, slope, and precipitation are the most influential variables in the distribution of T. elliptica, while distance to roads, population density, and wind speed are the key factors affecting wildfire occurrence. In the final map, a comparison of different regions of T. elliptica habitat under fire hazard with fire-free habitats using Kruskal-Wallis and Dunn tests indicated that the fire hazard in the T. elliptica habitat is a serious concern. Since the areas with the highest fire hazard and the highest presence of T. elliptica cover approximately 2311.38 km2, neglecting these regions could lead to the gradual reduction of T. elliptica, and create conditions for secondary succession dominated by less valuable annual species. The findings of this study underscore the importance of implementing fire management strategies, protection projects, and continuous monitoring to ensure the safety and conservation of the T. elliptica habitat.

Coupling heat wave and wildfire occurrence across multiple ecoregions within a Eurasia longitudinal gradient

Understanding the relationship between heat wave occurrence and wildfire spread represents a key priority in global change studies due to the significant threats posed on natural ecosystems and society. Previous studies have not explored the spatial and temporal mechanism underlying the relationship between heat waves and wildfires occurrence, especially over large geographical regions. This study seeks to investigate such a relationship with a focus on 37 ecoregions within a Eurasia longitudinal gradient. The analysis is based on the wildfire dataset provided by the GlobFire Final Fire Event Detection and the meteorological dataset ERA5-land from Copernicus Climate service. In both cases we focused on the 2001-2019 timeframe. By means of a 12 km square grid, three wildfire metrics, i.e., density, seasonality, and severity of wildfires, were computed as proxy of fire regime. Heat waves were also characterized in terms of periods, duration, and intensity for the same period. Statistical tests were performed to evaluate the different patterns of heat wave and wildfire occurrence in the 37 ecoregions within the study area. By using Geographically Weighted Regression (GWR) we modeled the spatial varying relationships between heat wave characteristics and wildfire metrics. As expected, our results suggest that the 37 ecoregions identified within the Eurasia longitudinal gradient differ in terms of fire regimes. However, the occurrence of heat waves did not show significant differences among ecoregions, but a more evident variability in terms of relationship between fire regime metrics and heat waves within the study area. The outcome of the GWR analysis allowed us to identify the spatial locations (i.e., hotspot areas) where the relationship between heat waves and wildfires is positive and significant. Hence, in hotspots the presence of heat waves can be seen as a driver of wildfire occurrence in forest and steppe ecosystems. The findings from this study could contribute to a more comprehensive assessment of wildfire patterns in this geographical region, thus supporting cross-regional prevention strategies for disaster risk mitigation.

Global vegetation, moisture, thermal and climate interactions intensify compound extreme events

Compound extreme events, encompassing drought, vegetation stress, wildfire severity, and heatwave intensity (CDVWHS), pose significant threats to societal, environmental, and health systems. Understanding the intricate relationships governing CDVWHS evolution and their interaction with climate teleconnections is crucial for effective climate adaptation strategies. This study leverages remote sensing, reanalysis data, and climate models to analyze CDVWHS during historical (1982-2014), near-future (2028-2060), and far-future (2068-2100) periods under two Shared Socioeconomic Pathways (SSP; 245 and 585). Our results show that reduced vegetation health, unfavorable temperature conditions, and low moisture conditions have negligible effects on vegetation density. However, they worsen the intensity of heatwaves and increase the risk of wildfires. Wildfires can persist when thermal conditions are poor despite favorable moisture levels. For example, despite adequate moisture availability, we link the 2012 Siberian wildfire in the Ob basin to anomalous negative thermal conditions and concurrent unfavorable thermal-moisture conditions. In contrast, the Amazon experiences extreme and exceptional drought associated with unfavorable moisture conditions in the same year. A comparative analysis of Siberian and North American fires reveals distinct burned area anomalies due to variations in vegetation density and wildfire fuel. The North American fires have lower positive anomalies in burned areas because of negative anomalous vegetation density, which reduced the amount of wildfire fuel. Furthermore, we examine basin-specific variability in climate teleconnections related to compound CDVWHS, revealing the primary modes of variability and evolution of CDVWHS through climate teleconnection patterns. Moreover, a substantial increase in the magnitude of heatwave severity emerges between the near and far future under SSP 585. This study underscores the urgency for targeted actions to enhance ecosystem resilience and safeguard vulnerable communities from CDVWHS impacts. Identifying CDVWHS hotspots and comprehending their complex relationships with environmental factors are essential for developing effective adaptation strategies in a changing climate.

Fire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons

This study analyzed fire-pollutant-meteorological variables and their impact on cardio-respiratory mortality in Portugal during wildfire season. Data of burned area, particulate matter with a diameter of 10 or 2.5 μm (μm) or less (PM10, PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, relative humidity, wind speed, aerosol optical depth and mortality rates of Circulatory System Disease (CSD), Respiratory System Disease (RSD), Pneumonia (PNEU), Chronic Obstructive Pulmonary Disease, and Asthma (ASMA), were used. Only the months of 2011-2020 wildfire season (June-July-August-September-October) with a burned area greater than 1,000 ha were considered. Principal component analysis was used on fire-pollutant-meteorological variables to create two indices called Pollutant-Burning Interaction (PBI) and Atmospheric-Pollutant Interaction (API). PBI was strongly correlated with the air pollutants and burned area while API was strongly correlated with temperature and relative humidity, and O3. Cluster analysis applied to PBI-API divided the data into two Clusters. Cluster 1 included colder and wetter months and higher NO2 concentration. Cluster 2 included warmer and dried months, and higher PM10, PM2.5, CO, and O3 concentrations. The clusters were subjected to Principal Component Linear Regression to better understand the relationship between mortality and PBI-API indices. Cluster 1 showed statistically significant (p-value < 0.05) correlation (r) between RSDxPBI (r RSD = 0.58) and PNEUxPBI (r PNEU = 0.67). Cluster 2 showed statistically significant correlations between RSDxPBI (r RSD = 0.48), PNEUxPBI (r PNEU = 0.47), COPDxPBI (r COPD = 0.45), CSDxAPI (r CSD = 0.70), RSDxAPI (r CSD = 0.71), PNEUxAPI (r PNEU = 0.49), and COPDxAPI (r PNEU = 0.62). Cluster 2 analysis indicates that the warmest, driest, and most polluted months of the wildfire season were associated with cardio-respiratory mortality.

Complex Organisms Must Deal with Complex Threats: How Does Amphibian Conservation Deal with Biphasic Life Cycles?

The unprecedented rate of global amphibian decline is attributed to The Anthropocene, with human actions triggering the Sixth Mass Extinction Event. Amphibians have suffered some of the most extreme declines, and their lack of response to conservation actions may reflect challenges faced by taxa that exhibit biphasic life histories. There is an urgent need to ensure that conservation measures are cost-effective and yield positive outcomes. Many conservation actions have failed to meet their intended goals of bolstering populations to ensure the persistence of species into the future. We suggest that past conservation efforts have not considered how different threats influence multiple life stages of amphibians, potentially leading to suboptimal outcomes for their conservation. Our review highlights the multitude of threats amphibians face at each life stage and the conservation actions used to mitigate these threats. We also draw attention to the paucity of studies that have employed multiple actions across more than one life stage. Conservation programs for biphasic amphibians, and the research that guides them, lack a multi-pronged approach to deal with multiple threats across the lifecycle. Conservation management programs must recognise the changing threat landscape for biphasic amphibians to reduce their notoriety as the most threatened vertebrate taxa globally.

Global exacerbation of episodic local vegetation greenness decline since the 21st century

Extreme climate-induced vegetation greenness decline significantly affects the stability of ecosystem function. Extreme climate events have occurred frequently in the recent 20 years and the possibility of climate anomalies is forecasted to increase in the future. But currently, the spatial and temporal response of episodic local vegetation decline to climate extremes at a global scale are still unclear. In this study, the detrend NDVI data was utilized as the indicator of vegetation growth, and a spatiotemporally contiguous recognition method was proposed to identify episodic large-scale vegetation decline events globally, subsequently, the spatiotemporal characteristics of these vegetation decline events and their interannual variation trends during 2000-2019 were explored. The results showed that (1) the spatiotemporally contiguous recognition method proposed by this paper was proven to be accurate in identifying the hotspot regions of large-scale vegetation decline. A total of 243 large-scale vegetation decline events were recognized globally during 2000-2019 drived by the method. (2) The global hotspots of large-scale vegetation decline were mainly distributed in the low-elevation areas at middle and low latitudes, especially at 15°S ~ 35°S, 15°N and 35°N, where covered north-western Africa, the Sahel, the Middle East, Central Asia, western India, the border of north-eastern China and Mongolia, western and south-central United States, northern Mexico, southern Africa, Australia, and southern and north-eastern South America. (3) Recent global episodic local vegetation decline has increased significantly since 2000, at the rate of 180,000 km² of vegetation decline areas increasing per year. Particular, the severity of vegetation decline grew significantly since 2010 at the regions where covered the latitudes of approximately 15°N, 30°N and 65°N. Additionally, the severity of vegetation decline ranging from 20°S to 30°S weakened significantly since 2010. These findings were expected to provide the valuable scientific understanding for global vegetation decline and ecosystem responses to frequent climate extremes.

Monitoring and mapping of drought in a semi-arid region: case of the Merguellil watershed, central Tunisia

Drought is defined as a period of time characterized by below-normal water availability, which may affect crops, animals and the environment. Recently, drought was shown to be more frequent and more intense, implying thereby the need for monitoring and analysis of this natural hazard. The present study aims to examine the spatial extent and temporal variation of droughts in the Merguellil watershed, located in central Tunisia. This contribution was mainly based on the analysis of annual and monthly rainfall time series recorded over the period (1983-2018) in 19 stations spread throughout the study watershed. Rainfall trend was first examined using the Mann-Kendall statistical test. Then, statistical (standard precipitation index (SPI) and Palmer drought severity index (PDSI)), spectral (continuous wavelet transform (CWT)) and mapping (geographical information system (GIS)) techniques were used to identify extreme dry events and to characterize their severity and their spatial and temporal extents. The results obtained revealed the recurrence and frequency of drought conditions in the Merguellil watershed over the study period. Seven drought sequences (1983-1984, 1986-1989, 1992-1995, 1999-2002, 2007-2009, 2013-2015 and 2017-2018), with different levels of severity, were distinguished based on the computed SPI and PDSI values. Spectral analysis of rainfall data also showed the occurrence of significant droughts in recent years. The period starting from 2010 was shown to be marked by recurrent episodes of drought in the Merguellil watershed. Extreme drought events mapping over this period confirmed drought severity at both time and space scales. All of these findings may be helpful for developing programs of water resource management in the study watershed.

A copula model integrating atmospheric moisture demand and supply for vegetation vulnerability mapping

Drought caused by various meteorological factors negatively affects vegetation. Constructing a joint probability distribution between vegetation and drought information may be appropriate to understand the vulnerability of vegetation to drought. In this study, a copula-based trivariate joint probability model is proposed to investigate the effects of various aspects of meteorological drought on vegetation (vegetation drought). Because drought can be caused by insufficient precipitation or excessive evapotranspiration, the meteorological drought risk for vegetation was divided into two aspects (atmospheric moisture supply and moisture demand). The vulnerability of vegetation drought was mapped when two aspects of meteorological drought occurred separately or simultaneously at high spatial resolution using remote sensing data. The results revealed that the response of vegetation was significantly different depending on the climatic stressors. Although the sensitivity of vegetation to each drought condition varied from region to region, it was found that vegetation was more vulnerable to drought caused by atmospheric moisture demand in most regions of Far East Asia. It has also been shown that drought conditions, which overlapped with insufficient precipitation and excessive evapotranspiration, can drive vegetation to a far more lethal level. Meanwhile, through comparison with the existing VTCI, the proposed Normalized Vegetation Temperature Condition Index (nVTCI) was found to be able to more rationally monitor vegetation drought in the Far East Asian region.

Prediction, validation, and uncertainties of a nation-wide post-fire soil erosion risk assessment in Portugal

Wildfires are a recurrent and increasing threat in mainland Portugal, where over 4.5 million hectares of forests and scrublands have burned over the last 38 years. These fire-affected landscapes have suffered an intensification of soil erosion processes, which can negatively affect soil carbon storage, reduce fertility and forest productivity, and can become a source of pollutants. The main objective of the present study is to produce a post-fire soil erosion risk map for the forest and shrubland areas in mainland Portugal and assess its reliability. To this end, the semi-empirical Morgan–Morgan–Finney erosion model was used to assess the potential post-fire soil erosion according to distinct burn severity and climate scenarios, and the accuracy of the predictions was verified by an uncertainty analysis and validated against independent field datasets. The proposed approach successfully allowed mapping post-fire soil erosion in Portugal and identified the areas with higher post-fire erosion risk for past and future climate extremes. The outcomes of this study comprise a set of tools to help forest managers in their decision-making for post-fire emergency stabilization, ensuring the adequate selection of areas for mitigation to minimize the economic and environmental losses caused by fire-enhanced soil erosion.

Elevation in wildfire frequencies with respect to the climate change

Forests have been undergoing through immense pressure due to the factors like human activities; procurement of forest products and climate change which is a major factor influencing this pressure buildup on forests. Climate change and temperature increase caused by anthropogenic activities have notably affected forests and wildlife on a global scale. High temperature increases the soil-water evaporation, resulting in drier soils, and water loss in forest flora. The incidence of forest fires has doubled since 1984 and these are linked to global warming. Drought influences fuel moisture by bringing about physiological changes in forest vegetation leading to forest fires. Forest resilience is hampered because of temperature and drought stress at the developing stage of plant's life cycle leading to the shift in plant species in those areas. Forest fire incidences can be managed with proper management strategies such as sustainable, community and urban forest management. A careful monitoring of stress precursors, subsistence uses of forests, ecological education and planting of near native and new indigenous plant species are the tools that can aid in efficient forest management.

Meteorological droughts in part of southeastern Brazil: Understanding the last 100 years

Droughts have negatively influenced tropical regions on the planet with southeastern Brazil standing out. The objective of this study was to analyze droughts with different magnitudes since the ending of 19th and beginning of the 20th centuries based on the Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI), in the locations of São Paulo city (SP - city), metropolitan regions of Belo Horizonte (MR-BH) and Campinas (MR-Campinas), Lavras (South-MG), and Piracicaba (ME-SP). Two different periods were considered: i) wet period (SPI6 and SPEI6) and; ii) summer period (SPI4 and SPEI4). Considering the SPI indexes, the hydrological year of 2013/2014 was the driest observed for South-MG, ME-SP and MR-Campinas, while for MR-BH and SP-city, 1970/1971 and 1962/1963 were the driest, respectively. MR-BH and SP city showed different variability of 1970/1971 and 1962/1963, respectively. We could detect three periods with several consecutive droughts: 1908/1918; 1968/1981 and 2013/2019. Based on SPEI, the 2013/2014 hydrological year was the driest for all the regions, except for SP city, for which 1998/1999 and 1962/1963 were the driest, and MR-BH for which 1970/1971 and 2000/2001 were the driest. Precipitation might be the main factor to evaluate the occurrence of droughts in the studied locations, which indicates SPI is a satisfactory drought indicator for the region.

Perceptions of Public Officers Towards the Effects of Climate Change on Ecosystem Services: A Case-Study From Northern Portugal

How institutional stakeholders perceive the supply and demand of ecosystem services (ES) under distinct contexts determines which planning actions are deemed priority or not. Public officers play a crucial role in social-ecological management and decision-making processes, but there is a paucity of research exploring their perceptions on ES supply and demand under a changing climate. We address this gap through an exploratory study that analyses the views of public officers on the potential impacts of climate-change related drivers on multiple ES in a major administrative region from Portugal (EU NUTS 3). We combined qualitative spatial data from participatory maps and semi-quantitative answers from questionnaire-based surveys with 22 officers from public institutions contributing to territorial planning. Contrary to other similar studies, public officers shared a common view on the importance of ES. This view aligns with scientific projections on how a changing climate is expected to influence ES in the region over the next decade. In agreement with other observations in Mediterranean regions, the most perceivably valued ES concerned tangible socio-economic benefits (e.g., periurban agriculture and wine production). Surprisingly, despite the region’s potential for cultural ES, and considering the impacts that climate change may hold on them, recreation and tourism did not seem to be embedded in the officers’ views. We explore the implications of our findings for territorial planning and social-ecological adaptation, considering that the way stakeholders manage the territory in response to climate change depends on the extent to which they are aware and expect to experience climatic consequences in the future.

Assessment of vegetation growth and drought conditions using satellite-based vegetation health indices in Jing-Jin-Ji region of China

Terrestrial vegetation growth activity plays pivotal roles on regional development, which has attracted wide attention especially in water resources shortage areas. The paper investigated the spatiotemporal change characteristics of vegetation growth activity using satellite-based Vegetation Health Indices (VHIs) including smoothed Normalized Difference Vegetation Index (SMN), smoothed Brightness Temperature (SMT), Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and VHI, based on 7-day composite temporal resolution and 16 km spatial resolution gridded data, and also estimated the drought conditions for the period of 1982-2016 in Jing-Jin-Ji region of China. The Niño 3.4 was used as a substitution of El Niño Southern Oscillation (ENSO) to reveal vegetation sensitivity to ENSO using correlation and wavelet analysis. Results indicated that monthly SMN has increased throughout the year especially during growing season, starts at approximate April and ends at about October. The correlation analysis between SMN and SMT, SMN and precipitation indicated that the vegetation growth was affected by joint effects of temperature and precipitation. The VCI during growing season was positive trends dominated and vice versa for TCI. The relationships between VHIs and drought make it possible to identify and quantify drought intensity, duration and affected area using different ranges of VHIs. Generally, the intensity and affected area of drought had mainly decreased, but the trends varied for different drought intensities, regions and time periods. Large-scale global climate anomalies such as Niño 3.4 exerted obvious impacts on the VHIs. The Niño 3.4 was mainly negatively correlated to VCI and positively correlated to TCI, and the spatial distributions of areas with positive (negative) correlation coefficients were mainly opposite. The linear relationships between Niño 3.4 and VHIs were in accordance with results of nonlinear relationships revealed using wavelet analysis. The results are of great importance to assess the vegetation growth activity, to monitor and quantify drought using satellite-based VHIs in Jing-Jin-Ji region.

Future Seasonal Drought Conditions over the CORDEX-MENA/Arab Domain

Seasonal drought is often overlooked because its impacts are less devasting than meteorological or hydrological drought. Nevertheless, short-term drought can have significant impacts on soil moisture content, agricultural crop yield, and sand and dust storms. Using data obtained from bias-corrected regional climate modelling (RCM) outputs, future seasonal drought is investigated over the water-scarce Arab domain using SPI-3. The climate modelling outputs include three downscaled mainframe GCMs downscaled using a single RCM for two climate scenarios: RCP4.5 and RCP8.5. Results across the region exhibit spatial and temporal variability. For example, Rift Valley, in the eastern sub-Sahara, projects less frequent and less severe drought, particularly during the winter (DJF) months. Conversely, the Morocco Highlands and adjacent Mediterranean coast signals a dramatic increase in drought by end-century during winter (DJF) and spring (MAM). Moderate increase in drought indicated in the greater Mashreq in spring (MAM) can be linked to sand and dust storm risk. Thirdly, autumn drought (SON) is linked to increased forest fire risk in the Levant. Projected increases in drought frequency and severity call for adaptation measures to reduce impacts.

Assessing impacts of future climate change on extreme fire weather and pyro-regions in Iberian Peninsula

Weather conditions play an important role in wildfire activity. In many regions, future climate could lead to different fire weather, with impacts on the ignition, behaviour, and suppression of wildfires, which may, therefore, force new fire regimes. This study aimed to assess the evolution of fire weather indices and the Number of Extreme Days (NED) in the context of climate change. We estimated the impact of these changes on monthly Normalized Burnt Area (NBA) and in the spatial distribution of Pyro-Regions (PR), using a recently identified relationship between NED and NBA intra-annual patterns. The components of the Canadian Forest Fire Weather Index System (CFFWIS) in the Iberian Peninsula were analysed for present-day conditions and future climate scenarios, using daily data from ERA-Interim (1980-2014) and an ensemble of simulations from 11 EURO-CORDEX high spatial resolution models, for two future periods (2041-2070 and 2071-2100) and scenarios (RCP4.5 and RCP8.5). Results suggest a significant increase in future fire weather risk, especially in late spring and early autumn, and also in southern and eastern Iberian Peninsula. NED is expected to strongly increase in summer months in the four PRs, but also to decrease in March and April in the northwestern and southwestern PR. This could change the spatial distribution of PRs, with a general northwards movement: the northern PR is expected to disappear except north of the Cantabrian Mountains, being replaced by the northwestern PR; the southwestern PR is expected to grow and occupy part of the area currently in the northwestern PR; and a new PR could appear in parts of the current eastern PR. These PR changes follow the projected modifications in the major climate regions. Results suggest different fire regimes in the future, with higher fire weather risk, and a longer and harsher fire season.

Copula-based Joint Drought Index using SPI and EDDI and its application to climate change

The drought index, which mainly focuses on the moisture supply side of the atmosphere, which has been mainly used in the field of drought monitoring, has limitations that cannot reflect drought caused by changes in various climate variables such as an increase in surface air temperature due to global warming. To overcome these limitations, various evaporation demand-based drought indices have been proposed, focusing on the aspect of atmospheric moisture demand. However, drought indices that consider only precipitation or the demand for atmospheric evaporation are difficult to comprehensively interpret drought caused by various climatic factors. The novelty of this study is to propose a new drought index to simultaneously monitor droughts occurring in terms of atmospheric moisture supply and demand. The proposed Copula-based Joint Drought Index (CJDI) combines the Standardized Precipitation Index and the Evaporative Demand Drought Index using copula. Since CJDI reflects the correlation between the two drought indices, it is shown that CJDI can better monitor Korea's past droughts than other drought indices. It is found that quantification of past drought using CJDI can be used to objectively recognize the level of drought currently in progress by combining with drought severity-duration-frequency curves derived from partial duration series. As a result of analyzing the future drought pattern in Korea, it was revealed that the drought would be alleviated by about 11% in the case of SPI and SPEI, but the drought would intensify by about 89% in the case of EDDI. In the case of CJDI, it is projected that the drought is likely to intensify to about 17%. From the perspective of better reproducing past droughts and projecting a more convincing future drought than other drought indices, CJDI is expected to be fully utilized as a drought index to monitor droughts and establish climate change adaptation policies.

Integrating multiple factors to optimize watchtower deployment for wildfire detection

Traditional human-vision-based watchtower systems are being gradually replaced by the machine-vision-based watchtower system. The visual range of machine-vision-based watchtower is smaller than the range of traditional human-vision-based watchtower, which has led to a sharp increase in the number of towers that should be deployed. Consequently, the overlapping area between watchtowers is larger and overlaps are more frequent than in conventional watchtower networks. This poses an urgent challenge: identifying the optimal locations for deployment. If the number of required watchtowers must be increased to extend the detection coverage, overlaps among watchtowers are inevitable and result in viewshed redundancy. However, this redundancy of the viewshed resources of the watchtowers has not been utilized in the design of fire detection systems. Moreover, fire ignition factors, such as climatic factors, fuels, and human behaviour, cause the fire occurrence risk to differ among forest areas. Thus, the fire risk map of the area should also be considered in watchtower deployment. A fire risk model is used as the first step in producing the fire risk map, which is used to propose a new watchtower deployment model for optimizing the watchtower system by integrating viewshed analysis, location allocation, and multi-coverage of the high-fire-risk area while considering the budget constraints for providing optimal coverage. We use a real dataset of a forest park to evaluate the applicability of our approach. The proposed approach is evaluated against the FV-NB (Full coVerage with No Budget constraint) algorithm and the XV-B (maXimum possible coVerage with a Budget constraint) algorithm in terms of performance. The evaluation results demonstrate that our approach realizes higher coverage gain and excellent multiple-coverage of the fire risk area by integrating the viewshed and the fire risk level into location allocation while satisfying requirements on the overall coverage and budget. The proposed approach is more suitable in the environments with moderate watchtower density, in which overlapping areas are frequent. It offers as much as 8.9-17.3% improvement of multiple-coverage of the high-fire-risk area.

Study of trends and mapping of drought events in Tunisia and their impacts on agricultural production

The objective of this research is to explore spatial extent and temporal pattern of historical droughts and their impacts on agricultural production in Tunisia. This contribution was based on monthly rainfall series recorded from September 1973 to August 2016 in 16 main meteorological stations in Tunisia. The Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI) and the annual Potential Evapotranspiration (PET) were computed and used to characterize the gravity of climatic events and their spatial and temporal variations. A database of strategic crop productions and Agricultural Gross Domestic Product (AGDP) variation has been collected from FAO's official website. Based on SPI and RDI, strongly correlated indices (R = 0.99; p < .05), it is demonstrated that Tunisia has experienced several multi-year droughts (3 to 7 years) with different severities. During 1981, Tunisia suffered a generalized drought. However during 1996, severe to extreme humidity was observed over 70% of Tunisian territory (SPI and RDI values >1.5). Series of normal or near-normal years were recorded during 50% of the study period. Variation in cereal production showed the strongest correlation with RDI (R_Wheat/RDI = 0.66), followed by olive oil (R_{Olive.Oil/ RDI} = 0.45) and citrus fruits (R_Citrus/RDI = 0.43). The outputs of this research could be useful for main stakeholders to identify compromised measure (subsidies, insurance) improving management of agricultural activities to mitigate drought impacts at farm level and over production zones.

Quantification of the Effects of Droughts on Daily Mortality in Spain at Different Timescales at Regional and National Levels: A Meta-Analysis

A performance assessment of two different indices (the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI)) for monitoring short-term and short–medium-term drought impacts on daily specific-cause mortality in Spain was conducted. To achieve a comprehensive, nationwide view, a meta-analysis was performed using a combination of provincial relative risks (RRs). Moreover, the subdivisions of Spain based on administrative, climatic, and demographic criteria to obtain the measures of combined risks were also taken into account. The results of the SPEI and SPI calculated at the same timescale were similar. Both showed that longer drought events produced greater RR values, for respiratory mortality. However, at the local administrative level, Galicia, Castilla-y-Leon, and Extremadura showed the greatest risk of daily mortality associated with drought episodes, with Andalucía, País Vasco, and other communities being notably impacted. Based on climatic regionalization, Northwest, Central, and Southern Spain were the regions most affected by different drought conditions for all analyzed causes of daily mortality, while the Mediterranean coastal region was less affected. Demographically, the regions with the highest proportion of people aged 65 years of age and over reflected the greatest risk of daily natural, circulatory, and respiratory mortality associated with drought episodes.

Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction

Predicting and mapping fire susceptibility is a top research priority in fire-prone forests worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB), Decision Tree (DT), and Multivariate Logistic Regression (MLP) machine learning methods for the prediction and mapping fire susceptibility across the Pu Mat National Park, Nghe An Province, Vietnam. The modeling methodology was formulated based on processing the information from the 57 historical fires and a set of nine spatially explicit explanatory variables, namely elevation, slope degree, aspect, average annual temperate, drought index, river density, land cover, and distance from roads and residential areas. Using the area under the receiver operating characteristic curve (AUC) and seven other performance metrics, the models were validated in terms of their abilities to elucidate the general fire behaviors in the Pu Mat National Park and to predict future fires. Despite a few differences between the AUC values, the BN model with an AUC value of 0.96 was dominant over the other models in predicting future fires. The second best was the DT model (AUC = 0.94), followed by the NB (AUC = 0.939), and MLR (AUC = 0.937) models. Our robust analysis demonstrated that these models are sufficiently robust in response to the training and validation datasets change. Further, the results revealed that moderate to high levels of fire susceptibilities are associated with ~19% of the Pu Mat National Park where human activities are numerous. This study and the resultant susceptibility maps provide a basis for developing more efficient fire-fighting strategies and reorganizing policies in favor of sustainable management of forest resources.

Short-term effects of drought on daily mortality in Spain from 2000 to 2009

Spain is a country of southern Europe that is prone to drought, and it is likely that this type of hydrological extreme will become substantially more frequent and intense in the 21st century, which could lead to greater health risks if adequate adaptive measures are not taken. For the first time, we calculated the relative risks (RRs) of daily natural (ICD10: A00-R99), circulatory (ICD10: I00-I99), and respiratory (ICD: J00-J99) mortality associated with drought events in each province of Spain from 2000 to 2009. For this purpose, we compared the performance of the Standardized Precipitation Index (SPI) and Standardized Precipitation- Evapotranspiration Index (SPEI) obtained at 1 month of accumulation (denoted as SPI-1/SPEI-1) to estimate the short-term risks of droughts on daily mortality using generalised linear models. Attributable risks were calculated from the RR data. The main findings of this study revealed statistically significant associations between the different causes of daily mortality and drought events for the different provinces of Spain, and clear spatial heterogeneity was observed across the country. Western Spain (northwest to southwest) was the region most affected, in contrast to northern and eastern Spain, and daily respiratory mortality was the group most strongly linked to the incidence of drought conditions. Moreover, for a considerable number of provinces, the effect of SPI-1 and SPEI-1 largely reflected the impact of atmospheric pollution and/or heatwaves; however, for other regions, the effect of drought conditions on daily mortality remained when these different climatic events were controlled in Poisson models. When the performances of the SPEI and SPI were compared to identify and estimate the risks of drought on daily mortality, the results were very similar, although there were slight differences in the specific causes of daily mortality.