Research on Wildfire and Soil Water: A Bibliometric Analysis from 1990 to 2023
Abstract
:1. Introduction
2. Data and Methods
3. Results and Discussion
3.1. Temporal Trends of Publications and Citations
3.2. Related Journals
3.3. Productive Authors
3.4. Productive Affiliations and Countries
3.5. Temporal Evolution of Popular Keywords
3.5.1. Most Popular Keywords
3.5.2. Temporal Evolution of Keyword Frequencies
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Senande-Rivera, M.; Insua-Costa, D.; Miguez-Macho, G. Spatial and temporal expansion of global wildland fire activity in response to climate change. Nat. Commun. 2022, 13, 1208. [Google Scholar] [CrossRef] [PubMed]
- Xu, Z.; Zhang, Y.; Blöschl, G.; Piao, S. Mega Forest Fires Intensify Flood Magnitudes in Southeast Australia. Geophys. Res. Lett. 2023, 50, e2023GL103812. [Google Scholar] [CrossRef]
- Belongia, M.F.; Wagner, C.H.; Seipp, K.Q.; Ajami, N.K. Building water resilience in the face of cascading wildfire risks. Sci. Adv. 2023, 9, eadf9534. [Google Scholar] [CrossRef] [PubMed]
- González-Pelayo, O.; Prats, S.A.; Elsen, E.v.D.; Malvar, M.C.; Ritsema, C.; Bautista, S.; Keizer, J.J. The effects of wildfire frequency on post-fire soil surface water dynamics. Eur. J. For. Res. 2023, 143, 493–508. [Google Scholar] [CrossRef]
- Boyer, E.W.; Wagenbrenner, J.W.; Zhang, L. Wildfire and hydrological processes. Hydrol. Process. 2022, 36, e14640. [Google Scholar] [CrossRef]
- Godfree, R.C.; Knerr, N.; Encinas-Viso, F.; Albrecht, D.; Bush, D.; Cargill, D.C.; Clements, M.; Gueidan, C.; Guja, L.K.; Harwood, T.; et al. Implications of the 2019–2020 megafires for the biogeography and conservation of Australian vegetation. Nat. Commun. 2021, 12, 1023. [Google Scholar] [CrossRef]
- Schimel, D.; Baker, D. The wildfire factor. Nature 2002, 420, 29–30. [Google Scholar] [CrossRef]
- Loehman, R.A. Drivers of wildfire carbon emissions. Nat. Clim. Change 2020, 10, 1070–1071. [Google Scholar] [CrossRef]
- Moritz, M.A.; Batllori, E.; Bradstock, R.A.; Gill, A.M.; Handmer, J.; Hessburg, P.F.; Leonard, J.; McCaffrey, S.; Odion, D.C.; Schoennagel, T.; et al. Learning to coexist with wildfire. Nature 2014, 515, 58–66. [Google Scholar] [CrossRef]
- Langmann, B.; Duncan, B.; Textor, C.; Trentmann, J.; van der Werf, G.R. Vegetation fire emissions and their impact on air pollution and climate. Atmos. Environ. 2009, 43, 107–116. [Google Scholar] [CrossRef]
- Kpienbaareh, D.; Luginaah, I. After the flames then what? exploring the linkages between wildfires and household food security in the northern Savannah of Ghana. Int. J. Sustain. Dev. World Ecol. 2019, 26, 612–624. [Google Scholar] [CrossRef]
- Yao, Q.C.; Jiang, D.B.; Zheng, B.; Wang, X.C.; Zhu, X.L.; Fang, K.Y.; Shi, L.M.; Wang, Z.; Zhong, L.H.; Pei, Y.Y.; et al. Anthropogenic warming is a key climate indicator of rising urban fire activity in China. Natl. Sci. Rev. 2024, 11, nwae163. [Google Scholar] [CrossRef] [PubMed]
- Krueger, E.S.; Ochsner, T.E.; Quiring, S.M.; Engle, D.M.; Carlson, J.; Twidwell, D.; Fuhlendorf, S.D. Measured Soil Moisture is a Better Predictor of Large Growing-Season Wildfires than the Keetch–Byram Drought Index. Soil Sci. Soc. Am. J. 2017, 81, 490–502. [Google Scholar] [CrossRef]
- Krueger, E.S.; Ochsner, T.E.; Engle, D.M.; Carlson, J.; Twidwell, D.; Fuhlendorf, S.D. Soil Moisture Affects Growing-Season Wildfire Size in the Southern Great Plains. Soil Sci. Soc. Am. J. 2015, 79, 1567–1576. [Google Scholar] [CrossRef]
- Bartsch, A.; Balzter, H.; George, C. The influence of regional surface soil moisture anomalies on forest fires in Siberia observed from satellites. Environ. Res. Lett. 2009, 4, 045021. [Google Scholar] [CrossRef]
- Chuvieco, E.; Aguado, I.; Dimitrakopoulos, A.P. Conversion of fuel moisture content values to ignition potential for integrated fire danger assessment. Can. J. For. Res. 2004, 34, 2284–2293. [Google Scholar] [CrossRef]
- Vereecken, H.; Huisman, J.A.; Franssen, H.J.H.; Brüggemann, N.; Bogena, H.R.; Kollet, S.; Javaux, M.; van der Kruk, J.; Vanderborght, J. Soil hydrology: Recent methodological advances, challenges, and perspectives. Water Resour. Res. 2015, 51, 2616–2633. [Google Scholar] [CrossRef]
- Seneviratne, S.I.; Corti, T.; Davin, E.L.; Hirschi, M.; Jaeger, E.B.; Lehner, I.; Orlowsky, B.; Teuling, A.J. Investigating soil moisture—Climate interactions in a changing climate: A review. Earth-Sci. Rev. 2010, 99, 125–161. [Google Scholar] [CrossRef]
- Shein, E.V. Soil hydrology: Stages of development, current state, and nearest prospects. Eurasian Soil Sci. 2010, 43, 158–167. [Google Scholar] [CrossRef]
- Sungmin, O.; Hou, X.; Orth, R. Observational evidence of wildfire-promoting soil moisture anomalies. Sci. Rep. 2020, 10, 11008. [Google Scholar] [CrossRef]
- Jensen, D.; Reager, J.T.; Zajic, B.; Rousseau, N.; Rodell, M.; Hinkley, E. The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems. Environ. Res. Lett. 2018, 13, 014021. [Google Scholar] [CrossRef] [PubMed]
- Burapapol, K.; Nagasawa, R. Mapping Soil Moisture as an Indicator of Wildfire Risk Using Landsat 8 Images in Sri Lanna National Park, Northern Thailand. J. Agric. Sci. 2016, 8, 107. [Google Scholar] [CrossRef]
- Ebel, B.A.; Moody, J.A. Parameter estimation for multiple post-wildfire hydrologic models. Hydrol. Process. 2020, 34, 4049–4066. [Google Scholar] [CrossRef]
- Liu, T.; McGuire, L.A.; Oakley, N.; Cannon, F. Temporal changes in rainfall intensity–duration thresholds for post-wildfire flash floods in southern California. Nat. Hazards Earth Syst. Sci. 2022, 22, 361–376. [Google Scholar] [CrossRef]
- Nyman, P.; Sheridan, G.J.; Smith, H.G.; Lane, P.N. Modeling the effects of surface storage, macropore flow and water repellency on infiltration after wildfire. J. Hydrol. 2014, 513, 301–313. [Google Scholar] [CrossRef]
- Stiefel, L.C.; Cooley, S.C.; Johnson, B.G. Increased colluvial hollow discharge and subsequent recovery after a low intensity wildfire in the Blue Ridge Mountains, USA. Hydrol. Process. 2021, 35, e13971. [Google Scholar] [CrossRef]
- Ebel, B.A. The statistical power of post-fire soil-hydraulic property studies: Are we collecting sufficient infiltration measurements after wildland fires? J. Hydrol. 2022, 612, 128019. [Google Scholar] [CrossRef]
- Noske, P.J.; Lane, P.N.J.; Nyman, P.; Van der Sant, R.E.; Sheridan, G.J. Predicting post-wildfire overland flow using remotely sensed indicators of forest productivity. Hydrol. Process. 2022, 36, e14769. [Google Scholar] [CrossRef]
- Moody, J.A.; Shakesby, R.A.; Robichaud, P.R.; Cannon, S.H.; Martin, D.A. Current research issues related to post-wildfire runoff and erosion processes. Earth-Science Rev. 2013, 122, 10–37. [Google Scholar] [CrossRef]
- Krueger, E.S.; Levi, M.R.; Achieng, K.O.; Bolten, J.D.; Carlson, J.D.; Coops, N.C.; Holden, Z.A.; Magi, B.I.; Rigden, A.J.; Ochsner, T.E. Using soil moisture information to better understand and predict wildfire danger: A review of recent developments and outstanding questions. Int. J. Wildland Fire 2022, 32, 111–132. [Google Scholar] [CrossRef]
- Kumar, V.; Dharssi, I. Sources of soil dryness measures and forecasts for fire danger rating. Bureau Research Report No. 009. (Australian Government, Bureau of Meteorology). 2015. Available online: http://www.bom.gov.au/research/publications/researchreports/BRR-009.pdf (accessed on 15 May 2024).
- Ebel, B.A. Wildfire impacts on soil-water retention in the Colorado Front Range, United States. Water Resour Res. 2012, 48, W12515.1–W12515.12. [Google Scholar] [CrossRef]
- Forkel, M.; Thonicke, K.; Beer, C.; Cramer, W.; Bartalev, S.; Schmullius, C. Extreme fire events are related to previous-year surface moisture conditions in permafrost-underlain larch forests of Siberia. Environ. Res. Lett. 2012, 7, 044021. [Google Scholar] [CrossRef]
- Rigden, A.J.; Powell, R.S.; Trevino, A.; McColl, K.A.; Huybers, P. Microwave Retrievals of Soil Moisture Improve Grassland Wildfire Predictions. Geophys. Res. Lett. 2020, 47, e2020GL091410. [Google Scholar] [CrossRef]
- Schaefer, A.J.; Magi, B.I. Land-Cover Dependent Relationships between Fire and Soil Moisture. Fire 2019, 2, 55. [Google Scholar] [CrossRef]
- Zhang, Y.; Chen, Y. Research trends and areas of focus on the Chinese Loess Plateau: A bibliometric analysis during 1991–2018. CATENA 2020, 194, 104798. [Google Scholar] [CrossRef]
- Chen, D.; Liu, Z.; Luo, Z.; Webber, M.; Chen, J. Bibliometric and visualized analysis of emergy research. Ecol. Eng. 2016, 90, 285–293. [Google Scholar] [CrossRef]
- Zyoud, S.H.; Al-Jabi, S.W.; Sweileh, W.M. Bibliometric analysis of scientific publications on waterpipe (narghile, shisha, hookah) tobacco smoking during the period 2003-2012. Tob. Induc. Dis. 2014, 12, 7. [Google Scholar] [CrossRef]
- Viana-Lora, A.; Nel-Lo-Andreu, M.G. Bibliometric analysis of trends in COVID-19 and tourism. Humanit. Soc. Sci. Commun. 2022, 9, 173. [Google Scholar] [CrossRef]
- Sa’ed, H.Z. Global research trends of Middle East respiratory syndrome coronavirus: A bibliometric analysis. BMC Infect. Dis. 2016, 16, 255. [Google Scholar] [CrossRef]
- Ellegaard, O.; Wallin, J.A. The bibliometric analysis of scholarly production: How great is the impact? Scientometrics 2015, 105, 1809–1831. [Google Scholar] [CrossRef]
- Li, T.; Cui, L.; Xu, Z.; Hu, R.; Joshi, P.K.; Song, X.; Tang, L.; Xia, A.; Wang, Y.; Guo, D.; et al. Quantitative Analysis of the Research Trends and Areas in Grassland Remote Sensing: A Scientometrics Analysis of Web of Science from 1980 to 2020. Remote Sens. 2021, 13, 1279. [Google Scholar] [CrossRef]
- Folharini, S.; Vieira, A.; Bento-Gonçalves, A.; Silva, S.; Marques, T.; Novais, J. Bibliometric Analysis on Wildfires and Protected Areas. Sustainability 2023, 15, 8536. [Google Scholar] [CrossRef]
- Haque, K.M.S.; Uddin, M.; Ampah, J.D.; Hossen, S.; Rokonuzzaman; Hossain, Y.; Hossain, S.; Rahman, Z. Wildfires in Australia: A bibliometric analysis and a glimpse on ‘Black Summer’ (2019/2020) disaster. Environ. Sci. Pollut. Res. 2023, 30, 73061–73086. [Google Scholar] [CrossRef] [PubMed]
- Neger, C.; Rosas-Paz, L.D. A Characterization of Fire-Management Research: A Bibliometric Review of Global Networks and Themes. Fire 2022, 5, 89. [Google Scholar] [CrossRef]
- Pan, M.; Zhang, S. Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis. Atmosphere 2023, 14, 1009. [Google Scholar] [CrossRef]
- dos Santos, S.M.B.; Bento-Gonçalves, A.; Vieira, A. Research on Wildfires and Remote Sensing in the Last Three Decades: A Bibliometric Analysis. Forests 2021, 12, 604. [Google Scholar] [CrossRef]
- Aria, M.; Cuccurullo, C. bibliometrix: An R-tool for comprehensive science mapping analysis. J. Informetr. 2017, 11, 959–975. [Google Scholar] [CrossRef]
- Li, T.; Cui, L.; Scotton, M.; Dong, J.; Xu, Z.; Che, R.; Tang, L.; Cai, S.; Wu, W.; Andreatta, D.; et al. Characteristics and trends of grassland degradation research. J. Soils Sediments 2022, 22, 1901–1912. [Google Scholar] [CrossRef]
- Li, T.; Cui, L.; Liu, L.; Chen, Y.; Liu, H.; Song, X.; Xu, Z. Advances in the study of global forest wildfires. J. Soils Sediments 2023, 23, 2654–2668. [Google Scholar] [CrossRef]
- Balch, J.K.; Iglesias, V.; Mahood, A.L.; Cook, M.C.; Amaral, C.; DeCastro, A.; Leyk, S.; McIntosh, T.L.; Nagy, R.C.; Denis, L.S.; et al. The fastest-growing and most destructive fires in the US (2001 to 2020). Science 2024, 386, 425–431. [Google Scholar] [CrossRef]
- Bousfield, C.G.; Lindenmayer, D.B.; Edwards, D.P. Substantial and increasing global losses of timber-producing forest due to wildfires. Nat. Geosci. 2023, 16, 1145–1150. [Google Scholar] [CrossRef]
- Doerr, S.H.; Shakesby, R.A.; Walsh, R. Soil water repellency: Its causes, characteristics and hydro-geomorphological significance. Earth-Science Rev. 2000, 51, 33–65. [Google Scholar] [CrossRef]
- DeBano, L.F.; Dekker, L.W. Water repellency bibliography. J. Hydrol. 2000, 231, 409–432. [Google Scholar]
- Doerr, S.H.; Shakesby, R.A.; Dekker, L.W.; Ritsema, C.J. Occurrence, prediction and hydrological effects of water repellency amongst major soil and land-use types in a humid temperate climate. Eur. J. Soil Sci. 2006, 57, 741–754. [Google Scholar] [CrossRef]
- Scott, D.F.; Van Wyk, D.B. The effects of wildfire on soil wettability and hydrological behaviour of an afforested catchment. J. Hydrol. 1990, 121, 239–256. [Google Scholar] [CrossRef]
- Shakesby, R.; Coelho, C.; Ferreira, A.; Terry, J.; Walsh, R. Wildfire Impacts on Soil-Erosion and Hydrology in Wet Mediterranean Forest, Portugal. Int. J. Wildland Fire 1993, 3, 95–110. [Google Scholar] [CrossRef]
- Debano, L.F.; Savage, S.M.; Hamilton, D.A. The Transfer of Heat and Hydrophobic Substances During Burning. Soil Sci. Soc. Am. J. 1976, 40, 779–782. [Google Scholar] [CrossRef]
- Shahlaee, A.K.; Nutter, W.L.; Burroughs, E.R.; Morris, L.A. Runoff and Sediment Production from Burned Forest Sites in the Georgia Piedmont. JAWRA J. Am. Water Resour. Assoc. 1991, 27, 485–493. [Google Scholar] [CrossRef]
- Hubbert, K.; Preisler, H.; Wohlgemuth, P.; Graham, R.; Narog, M. Prescribed burning effects on soil physical properties and soil water repellency in a steep chaparral watershed, southern California, USA. Geoderma 2005, 130, 284–298. [Google Scholar] [CrossRef]
- Terry, J.P.; Shakesby, R.A. Soil hydrophobicity effects on rainsplash: Simulated rainfall and photographic evidence. Earth Surf. Process. Landforms 1993, 18, 519–525. [Google Scholar] [CrossRef]
- Miller, J.D.; Nyhan, J.W.; Yool, S.R. Modeling potential erosion due to the Cerro Grande Fire with a GIS-based implementation of the Revised Universal Soil Loss Equation. Int. J. Wildland Fire 2003, 12, 85–100. [Google Scholar] [CrossRef]
- Gabet, E.J. Post-fire thin debris flows: Sediment transport and numerical modelling. Earth Surf. Process. Landforms 2003, 28, 1341–1348. [Google Scholar] [CrossRef]
- Robichaud, P. Fire effects on infiltration rates after prescribed fire in Northern Rocky Mountain forests, USA. J. Hydrol. 2000, 231–232, 220–229. [Google Scholar] [CrossRef]
- Imeson, A.; Verstraten, J.; van Mulligen, E.; Sevink, J. The effects of fire and water repellency on infiltration and runoff under Mediterranean type forest. Catena 1992, 19, 345–361. [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]
- Yao, Q.; Brown, P.M.; Liu, S.; Rocca, M.E.; Trouet, V.; Zheng, B.; Chen, H.; Li, Y.; Liu, D.; Wang, X. Pacific-Atlantic Ocean influence on wildfires in northeast China (1774 to 2010). Geophys. Res. Lett. 2017, 44, 1025–1033. [Google Scholar] [CrossRef]
- Meng, M.; Gong, D.Y.; Lan, Y.F.; Yao, Q.C.; Shi, L.M.; Wang, Z. Significant Association Between Arctic Oscillation and Winter Wildfires in Southern China. Int. J. Disast. Risk Sci. 2024, 15, 820–830. [Google Scholar] [CrossRef]
- Baur, M.J.; Friend, A.D.; Pellegrini, A.F.A. Widespread and systematic effects of fire on plant–soil water relations. Nat. Geosci. 2024, 17, 1115–1120. [Google Scholar] [CrossRef]
- Ambadan, J.T.; Oja, M.; Gedalof, Z.; Berg, A.A. Satellite-Observed Soil Moisture as an Indicator of Wildfire Risk. Remote Sens. 2020, 12, 1543. [Google Scholar] [CrossRef]
- Chaleplis, K.; Walters, A.; Fang, B.; Lakshmi, V.; Gemitzi, A. A Soil Moisture and Vegetation-Based Susceptibility Mapping Approach to Wildfire Events in Greece. Remote Sens. 2024, 16, 1816. [Google Scholar] [CrossRef]
- Kerr, Y.H.; Waldteufel, P.; Wigneron, J.P.; Delwart, S.; Cabot, F.; Boutin, J. The SMOS Mission: New Tool for Monitoring Key Elements of the Global Water Cycle. Proc. IEEE 2010, 98, 666–687. [Google Scholar] [CrossRef]
- Zhang, F.; Zhang, L.W.; Shi, J.J.; Huang, J.F. Soil Moisture Monitoring Based on Land Surface Temperature-Vegetation Index Space Derived from MODIS Data. Pedosphere 2014, 24, 450–460. [Google Scholar] [CrossRef]
- Lu, Y.; Wei, C. Evaluation of microwave soil moisture data for monitoring live fuel moisture content (LFMC) over the coterminous United States. Sci. Total Environ. 2021, 771, 145410. [Google Scholar] [CrossRef] [PubMed]
- Bahadori, N.; Razavi-Termeh, S.V.; Sadeghi-Niaraki, A.; Al-Kindi, K.M.; Abuhmed, T.; Nazeri, B.; Choi, S.-M. Wildfire Susceptibility Mapping Using Deep Learning Algorithms in Two Satellite Imagery Dataset. Forests 2023, 14, 1325. [Google Scholar] [CrossRef]
Description | Results |
---|---|
Timespan | 1990–2023 |
Sources (journals, books, etc.) | 364 |
Documents | 1585 |
Annual growth rate % | 6.68 |
Document average age | 8.19 |
Average citations per doc | 32.04 |
References | 59,437 |
Keywords plus (ID) | 3523 |
Author’s keywords (DE) | 4190 |
Authors (a unique count) | 6638 |
Authors of single-authored docs | 48 |
Single-authored docs | 57 |
Co-authors per doc | 5.57 |
International co-authorships % | 32.56 |
Journal | Publications | Journal | Total Citations |
---|---|---|---|
Science of the Total Environment | 90 | Journal of Hydrology | 3215 |
Catena | 79 | Hydrological Processes | 3060 |
International Journal of Wildland Fire | 75 | International Journal of Wildland Fire | 3042 |
Hydrological Processes | 62 | Catena | 2841 |
Forest Ecology and Management | 58 | Forest Ecology and Management | 2799 |
Geoderma | 52 | Geoderma | 2120 |
Journal of Hydrology | 51 | Water Resources Research | 1888 |
Land Degradation & Development | 31 | Science of the Total Environment | 1769 |
Earth Surface Processes and Landforms | 29 | Soil Science Society of America Journal | 1728 |
Forests | 27 | Earth Science Reviews | 1384 |
Water Resources Research | 23 | Global Change Biology | 1304 |
Fire-Switzerland | 21 | Soil Biology & Biochemistry | 1204 |
Journal of Geophysical Research: Earth Surface | 21 | Geomorphology | 1151 |
Rangeland Ecology & Management | 20 | Canadian Journal of Forest Research | 1038 |
Environmental Research Letters | 19 | Earth Surface Processes and Landforms | 1021 |
Geomorphology | 19 | Remote Sensing of Environment | 1018 |
Water | 18 | Science | 1007 |
Agricultural and Forest Meteorology | 17 | Ecology | 898 |
Ecosystems | 17 | Geophysical Research Letters | 870 |
Remote Sensing | 17 | Environmental Science & Technology | 837 |
Institution | Publications |
---|---|
University of Aveiro | 148 |
US Forest Service | 106 |
Colorado State University | 95 |
University of Melbourne | 78 |
University of Arizona | 75 |
Oregon State University | 68 |
University of Alberta | 59 |
Swansea University | 58 |
Northern Arizona University | 57 |
University of Valencia | 57 |
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Share and Cite
Zuo, F.; Yao, Q.; Shi, L.; Wang, Z.; Bai, M.; Fang, K.; Guo, F.; Yuan, L.; Zhang, W. Research on Wildfire and Soil Water: A Bibliometric Analysis from 1990 to 2023. Fire 2024, 7, 434. https://doi.org/10.3390/fire7120434
Zuo F, Yao Q, Shi L, Wang Z, Bai M, Fang K, Guo F, Yuan L, Zhang W. Research on Wildfire and Soil Water: A Bibliometric Analysis from 1990 to 2023. Fire. 2024; 7(12):434. https://doi.org/10.3390/fire7120434
Chicago/Turabian StyleZuo, Fenglin, Qichao Yao, Lamei Shi, Zhou Wang, Maowei Bai, Keyan Fang, Futao Guo, Lihua Yuan, and Weikang Zhang. 2024. "Research on Wildfire and Soil Water: A Bibliometric Analysis from 1990 to 2023" Fire 7, no. 12: 434. https://doi.org/10.3390/fire7120434
APA StyleZuo, F., Yao, Q., Shi, L., Wang, Z., Bai, M., Fang, K., Guo, F., Yuan, L., & Zhang, W. (2024). Research on Wildfire and Soil Water: A Bibliometric Analysis from 1990 to 2023. Fire, 7(12), 434. https://doi.org/10.3390/fire7120434