Investigating Drought Events and Their Consequences in Wildfires: An Application in China
Abstract
:1. Introduction
2. Data and Methods
2.1. Study Area
2.2. Data
2.3. Methodology
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Mansoor, S.; Farooq, I.; Kachroo, M.M.; Mahmoud, A.E.D.; Fawzy, M.; Popescu, S.M.; Alyemeni, M.N.; Sonne, C.; Rinklebe, J.; Ahmad, P. Elevation in wildfire frequencies with respect to the climate change. Environ. Manag. 2022, 301, 113769. [Google Scholar] [CrossRef]
- Mays, C.; Mcloughlin, S. End-permain burnout: The role of permain-triassic wildfires in extinction, carbon cycling, and environmental change in Eastern Gondwana. Palaios 2022, 37, 292–317. [Google Scholar] [CrossRef]
- Westerling, A.L. Increasing western US forest wildfire activity: Sensitivity to changes in the timing of spring. Philos. Trans. R. Soc. B Biol. Sci. 2016, 371, 20150178. [Google Scholar] [CrossRef] [Green Version]
- Field, R.D.; Werf, G.R.; Shen, S.S.P. Human amplification of drought-induced biomass burning in Indonesia since 1960. Nat. Geosci. 2009, 2, 185–188. [Google Scholar] [CrossRef]
- Brown, T.; Leach, S.; Wachter, B.; Gardunio, B. The Extreme 2018 Northern California Fire Season. Bull. Am. Meteorol. Soc. 2020, 101, S1–S4. [Google Scholar] [CrossRef] [Green Version]
- Boer, M.M.; Nolan, R.H.; Resco De Dios, V.; Clarke, H.; Price, O.F.; Bradstock, R.A. Changing Weather Extremes Call for Early Warning of Potential for Catastrophic Fire. Earths Future 2017, 5, 1196–1202. [Google Scholar]
- Pausas, J.G.; Keeley, J.E. A Burning Story: The Role of Fire in the History of Life. BioScience 2009, 59, 593–601. [Google Scholar] [CrossRef] [Green Version]
- Pausas, J.G.; Ribeiro, E. The global fire-productivity relationship. Glob. Ecol. Biogeogr. 2013, 22, 728–736. [Google Scholar] [CrossRef]
- Jones, M.W.; Abatzoglou, J.T.; Veraverbeke, S.; Andela, N.; Lasslop, G.; Forke, M.; Smith, A.J.P.; Burton, C.; Betts, R.A.; Werf, G.R.; et al. Global and Regional Trends and Drivers of Fire Under Climate Change. Rev. Geophys. 2022, 60, 1–76. [Google Scholar] [CrossRef]
- Archibald, S.; Roy, D.P.; Wilgen, B.W.; Scholes, R.J. What limits fire? An examination of drivers of burnt area in Southern Africa. Glob. Chang. Biol. 2009, 15, 613–630. [Google Scholar] [CrossRef] [Green Version]
- Kelley, D.I.; Bistinas, I.; Whitley, R.; Burton, C.; Marthews, T.R.; Dong, N. How contemporary bioclimatic and human controls change global fire regimes. Nat. Clim. Chang. 2019, 9, 690–696. [Google Scholar] [CrossRef] [Green Version]
- Parisien, M.A.; Moritz, M.A. Environmental controls on the distribution of wildfire at multiple spatial scales. Ecol. Monogr. 2009, 79, 127–154. [Google Scholar] [CrossRef]
- Turco, M.; von Hardenberg, J.; AghaKouchak, A.; Trigo, R.M. On the key role of droughts in the dynamics of summer fires in Mediterranean Europe. Sci. Rep. 2017, 7, 81. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ruffault, J.; Moron, V.; Trigo, R.M.; Curt, T. Objective identification of multiple large fire climatologies: An application to a Mediterranean ecosystem. Environ. Res. Lett. 2016, 11, 075006. [Google Scholar] [CrossRef] [Green Version]
- Swetnam, T.W.; Betancourt, J.L. Mesoscale Disturbance and Ecological Response to Decadal Climatic Variability in the American Southwest. J. Clim. 1998, 11, 3128–3147. [Google Scholar] [CrossRef]
- Zhao, F.; Liu, Y. Important Meteorological Predictors for Long-Range Wildfires in China. For. Ecol. Manag. 2021, 499, 119638. [Google Scholar] [CrossRef]
- Wells, N.; Goddard, S.; Hayes, M.J. Self-Calibrating Palmer Drought Severity Index. J. Clim. 2004, 17, 2335–2351. [Google Scholar] [CrossRef]
- Palmer, W.C. Meteorological Drought; Office of Climatology Research Paper 45; Weather Bureau: Washington, DC, USA, 1965. [Google Scholar]
- Vicente-Serrano, S.M.; Beguería, S.; López-Moreno, J.I.A. Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Clim. 2010, 23, 1696–1718. [Google Scholar] [CrossRef] [Green Version]
- Yu, L.; Zhong, S.; Sun, B. The Climatology and Trend of Surface Wind Speed over Antarctica and the Southern Ocean and the Implication to Wind Energy Application. Atmosphere 2020, 11, 108–127. [Google Scholar] [CrossRef] [Green Version]
- You, Q.; Wu, T.; Shen, L.; Pepin, N.; Zhang, L.; Jiang, Z.; Wu, Z.; Kang, S.; AghaKouchak, A. Review of Snow Cover Variation over the Tibetan Plateau and Its Influence on the Broad Climate System. Earth-Sci. Rev. 2020, 201, 103043. [Google Scholar] [CrossRef]
- Fang, Z.; Liu, Z.; He, C.; Tu, M.; Zhao, R.; Lu, W. Will climate change make Chinese people more comfortable? A scenario analysis based on the weather preference index. Environ. Res. Lett. 2020, 15, 084028. [Google Scholar] [CrossRef]
- Chang, Y.; Zhu, Z.; Bu, R.; Li, Y.; Hu, Y. Environmental controls on the characteristics of mean number of forest fires and mean forest area burned (1987–2007) in China. For. Ecol. Manag. 2015, 356, 13–21. [Google Scholar] [CrossRef]
- Zhao, F.; Liu, Y. Atmospheric Circulation Patterns Associated with Wildfires in the Monsoon Regions of China. Geophys. Res. Lett. 2019, 46, 4873–4882. [Google Scholar] [CrossRef] [Green Version]
- Morisette, J.T.; Giglio, L.; Csiszar, I.; Justice, C.O. Validation of the MODIS active fire product over Southern Africa with ASTER data. Int. J. Remote Sens. 2005, 26, 4239–4264. [Google Scholar] [CrossRef]
- Morisette, J.T.; Giglio, L.; Csiszar, I.; Setzer, A.; Schroeder, W.; Morton, D.; Justice, C.O. Validation of MODIS Active Fire Detection Products Derived from Two Algorithms. Earth Interact. 2005, 9, 1–25. [Google Scholar] [CrossRef] [Green Version]
- Csiszar, I.; Morisette, J.; Giglio, L. Validation of active fire detection from moderate-resolution satellite sensors: The MODIS example in northern Eurasia. IEEE Trans. Geosci. Remote Sens. 2006, 44, 1757–1764. [Google Scholar] [CrossRef]
- Schroeder, W.; Prins, E.; Giglio, L.; Csiszar, I.; Schmidt, C.; Morisette, J.; Morton, D. Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data. Remote Sens. Environ. 2008, 112, 2711–2726. [Google Scholar] [CrossRef]
- Climatic Research Unit. CRU TS4.05: Climatic Research Unit (CRU) Time-Series (TS) Version 4.05 of High-Resolution Gridded Data of Month-by-Month Variation in Climate (January 1901–December 2020). NERC EDS Centre for Environmental Data Analysis. 2021. Available online: https://catalogue.ceda.ac.uk/uuid/c26a65020a5e4b80b20018f148556681 (accessed on 8 February 2023).
- Harris, I.; Osborn, T.J.; Jones, P.; Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data 2020, 7, 109. [Google Scholar] [CrossRef] [Green Version]
- Barichivich, J.; Osborn, T.; Harris, I.; Schrier, G.; Jones, P. Drought: Monitoring global drought using the self-calibrating Palmer Drought Severity Index. Bull. Am. Meteorol. Soc. 2019, 100, S39–S40. [Google Scholar]
- Jain, P.; Wang, X.; Flannigan, M.D. Trend analysis of fire season length and extreme fire weather in North America between 1979 and 2015. Int. J. Wildland Fire 2017, 26, 1009. [Google Scholar] [CrossRef]
- Bedia, J.; Herrera, S.; Gutiérrez, J.M.; Benali, A.; Brands, S.; Mota, B.; Moreno, J.M. Global patterns in the sensitivity of burned area to fire-weather: Implications for climate change. Agric. For. Meteorol. 2015, 214–215, 369–379. [Google Scholar] [CrossRef] [Green Version]
- Andela, N.D.; Morton, C.; Giglio, L.; Chen, Y.; Werf, G.R.; Kasibhatla, P.S.; DeFries, R.S.; Collatz, G.J.; Hantson, S.; Kloster, S.; et al. A human-driven decline in global burned area. Science 2017, 356, 1356–1362. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Knorr, W.; Kaminski, T.; Arneth, A.; Weber, U. Impact of human population density on fire frequency at the global scale. Biogeosciences 2014, 11, 1085–1102. [Google Scholar] [CrossRef] [Green Version]
- Littell, J.S.; Peterson, D.L.; Riley, K.L.; Liu, Y.; Luce, C.H. A review of the relationships between drought and forest fire in the United States. Glob. Chang. Biol. 2016, 22, 2353–2369. [Google Scholar] [CrossRef]
- Abatzoglou, J.T.; Williams, A.P.; Boschetti, L.; Zubkova, M.; Kolden, C.A. Global patterns of interannual climate–fire relationships. Glob. Chang. Biol. 2018, 24, 5164–5175. [Google Scholar] [CrossRef]
- Archibald, S.; Lehmann, C.E.R.; Gómez-Dans, J.L.; Bradstock, R.A. Defining pyromes and global syndromes of fire regimes. Proc. Natl. Acad. Sci. USA 2013, 110, 6442–6447. [Google Scholar] [CrossRef] [Green Version]
- Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 1974, 19, 716–723. [Google Scholar] [CrossRef]
- Schoennagel, T.; Balch, J.K.; Brenkert-Smith, H.; Dennison, P.E.; Harvey, B.J.; Krawchuk, M.A.; Mietkiewicz, N.; Morgan, P.; Moritz, M.A.; Rasker, R.; et al. Adapt to more wildfire in western North American forests as climate changes. Proc. Natl. Acad. Sci. USA 2017, 114, 4582–4590. [Google Scholar] [CrossRef] [Green Version]
- Abatzoglou, J.T.; Williams, A.P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl. Acad. Sci. USA 2016, 113, 11770–11775. [Google Scholar] [CrossRef] [Green Version]
- Flannigan, M.D.; Krawchuk, M.A.; de Groot, W.J.; Wotton, B.M.; Gowman, L.M. Implications of changing climate for global wildland fire. Int. J. Wildland Fire 2009, 18, 483. [Google Scholar] [CrossRef]
- Ying, L.; Han, J.; Du, Y.; Shen, Z. Forest fire characteristics in China: Spatial patterns and determinants with thresholds. For. Ecol. Manag. 2018, 424, 345–354. [Google Scholar] [CrossRef]
- Dios, V.R.; de Yao, Y.; Camprubí, À.C.; Boer, M.M. Fire activity as measured by burned area reveals weak effects of ENSO in China. Nat. Commun. 2022, 13, 4316. [Google Scholar] [CrossRef]
- Fang, K.; Yao, Q.; Guo, Z.; Zheng, B.; Du, J.; Qi, F.; Yan, P.; Li, J.; Ou, T.; Liu, J.; et al. ENSO modulates wildfire activity in China. Nat. Commun. 2021, 12, 1764. [Google Scholar] [CrossRef]
- Marco, T.; José, R.-C.J.; Joaquín, B.; Sonia, J.; Pedro, M.J.; Carmen, L.M.; Antonello, P. Exacerbated fires in Mediterranean Europe due to anthropogenic warming projected with non-stationary climate-fire models. Nat. Commun. 2018, 9, 3821. [Google Scholar]
- Shao, D.; Chen, S.; Tan, X.; Gu, W. Drought characteristics over China during 1980–2015. Int. J. Climatol. 2018, 38, 3532–3545. [Google Scholar] [CrossRef]
- Tian, X.; McRae, D.J.; Jin, J.; Shu, L.; Zhao, F.; Wang, M. Wildfires and the Canadian Forest Fire Weather Index system for the Daxing’anling region of China. Int. J. Wildland Fire 2011, 20, 963–973. [Google Scholar] [CrossRef]
- Zhao, F.; Liu, Y.; Shu, L. Change in the fire season pattern from bimodal to unimodal under climate change: The case of Daxing’anling in Northeast China. Agric. For. Meteorol. 2020, 291, 108075. [Google Scholar] [CrossRef]
- Zhu, K.; Qiu, X.; Luo, Y.; Dai, M.; Lu, X.; Zang, C.; Zhang, W.; Gan, X.; Zhula, W. Spatial and temporal dynamics of water resources in typical ecosystems of the Dongjiang River Basin, China. J. Hydrol. 2022, 614, 128617. [Google Scholar] [CrossRef]
- Yuan, Z.; Liang, C.; Li, D. Urban stormwater management based on an analysis of climate change: A case study of the Hebei and Guangdong provinces. Landsc. Urban Plan. 2018, 177, 217–226. [Google Scholar] [CrossRef]
- Knorr, W.; Arneth, A.; Jiang, L. Demographic controls of future global fire risk. Nat. Clim. Chang. 2016, 6, 781–785. [Google Scholar] [CrossRef]
- He, J.; Pan, Z.; Liu, D.; Guo, X. Exploring the regional differences of ecosystem health and its driving factors in China. Sci. Total Environ. 2019, 673, 553–564. [Google Scholar] [CrossRef] [PubMed]
- Aishan, T.; Halik, Ü.; Kurban, A.; Cyffka, B.; Kuba, M.; Betz, F.; Keyimu, M. Eco-morphological response of floodplain forests (Populus euphratica Oliv.) to water diversion in the lower Tarim River, northwest China. Environ. Earth Sci. 2014, 73, 533–545. [Google Scholar] [CrossRef]
- Zhang, G.Q.; Xie, H.J.; Yao, T.D.; Kang, S.C. Water balance estimates of ten greatest lakes in China using ICESat and Landsat data. Chin. Sci. Bull. 2013, 58, 3815–3829. [Google Scholar] [CrossRef] [Green Version]
- Zhou, W.; Gang, C.; Zhou, l.; Chen, Y.; Li, J.; Ju, W.; Odeh, I. Dynamic of grassland vegetation degradation and its quantitative assessment in the northwest China. Acta Oecol. 2014, 55, 86–96. [Google Scholar] [CrossRef]
- Zhang, Z.; Xia, f.; Yang, D.; Huo, J.; Chen, H. Spatiotemporal characteristics in ecosystem service value and its interaction with human activities in Xinjiang, China. Ecol. Indic. 2020, 110, 105826. [Google Scholar] [CrossRef]
Region | Model | RhoIN | RhoOUT |
---|---|---|---|
NEC | 0.92 | 0.88 | |
NWC | 0.87 | 0.80 | |
NC | 0.63 | 0.50 | |
SWC | 0.49 | 0.31 | |
SC | 0.65 | 0.54 | |
CC | 0.84 | 0.76 | |
SEC | 0.74 | 0.66 |
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Yang, S.; Zeng, A.; Tigabu, M.; Wang, G.; Zhang, Z.; Zhu, H.; Guo, F. Investigating Drought Events and Their Consequences in Wildfires: An Application in China. Fire 2023, 6, 223. https://doi.org/10.3390/fire6060223
Yang S, Zeng A, Tigabu M, Wang G, Zhang Z, Zhu H, Guo F. Investigating Drought Events and Their Consequences in Wildfires: An Application in China. Fire. 2023; 6(6):223. https://doi.org/10.3390/fire6060223
Chicago/Turabian StyleYang, Song, Aicong Zeng, Mulualem Tigabu, Guangyu Wang, Zhen Zhang, He Zhu, and Futao Guo. 2023. "Investigating Drought Events and Their Consequences in Wildfires: An Application in China" Fire 6, no. 6: 223. https://doi.org/10.3390/fire6060223