Article
Multidisciplinary Sciences
A. Park Williams, Ben Livneh, Karen A. McKinnon, Winslow D. Hansen, Justin S. Mankin, Benjamin Cook, Jason E. Smerdon, Arianna M. Varuolo-Clarke, Nels R. Bjarke, Caroline S. Juang, Dennis P. Lettenmaier
Summary: Streamflow often increases after fire, and this effect has unclear persistence and importance to regional water resources. This study examines 72 forested basins in the western United States (WUS) and finds that multibasin mean streamflow significantly increases in the 6 water years after a fire. The streamflow response is proportional to the fire extent and is significant in all four seasons. Furthermore, historical fire-climate relationships and climate model projections suggest that wildfires will become more frequent in the coming decades, leading to increased regional streamflow.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Review
Environmental Sciences
Brian A. Ebel, Zachary M. Shephard, Michelle A. Walvoord, Sheila F. Murphy, Trevor F. Partridge, Kim S. Perkins
Summary: Wildfires are an increasing concern due to climate change, and their hydrologic effects are being studied using numerical models. This review examines the use of physically based distributed models to understand water resources after wildfires, focusing on geographic/ecohydrologic distribution, representation of hydrologic processes, model parameterization, and model performance. There are opportunities for improvement, such as applying models in underrepresented regions, incorporating all streamflow generation mechanisms, and integrating vegetation regrowth models with hydrologic models.
Article
Forestry
Xinyu Miao, Jian Li, Yunjie Mu, Cheng He, Yunfei Ma, Jie Chen, Wentao Wei, Demin Gao
Summary: This study introduces an enhanced window-based Transformer time series forecasting model aimed at improving the precision of forest fire predictions. Using remote sensing satellite and GIS technologies, a myriad of forest fire influencing factors were identified, and their interrelationships were estimated through a multicollinearity test. The proposed model demonstrated superior predictive performance, harnessing spatial background information efficiently and effectively utilizing the periodicity of forest fire factors.
Article
Engineering, Civil
K. A. Wampler, K. D. Bladon, M. Faramarzi
Summary: The increasing occurrence of large and severe wildfires poses a growing threat to forested watersheds and their ecosystem services. Previous research has shown that wildfires can lead to significant increases in peak flows and water yields, causing potential water quality concerns and management challenges. However, there is still uncertainty about post-fire hydrologic responses, particularly at large basin scales. To address this, we projected the impact of three large wildfires on streamflow in two important forested watersheds in Oregon. Using the SWAT model, we compared burned and unburned scenarios to identify drivers of post-fire water yield and peak flow changes.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Michelle E. Newcomer, Jennifer Underwood, Sheila F. Murphy, Craig Ulrich, Todd Schram, Stephen R. Maples, Jasquelin Pena, Erica R. Siirila-Woodburn, Marcus Trotta, Jay Jasperse, Donald Seymour, Susan S. Hubbard
Summary: This study investigates the impact of wildfires on hydrological changes in the Russian River Watershed in California and finds that the influence of wildfires ceases to increase beyond a certain threshold of burned area. Drought and climate conditions have a greater impact on streamflow variability compared to wildfires. This suggests that wildfire adaptation and drought factors in Mediterranean ecoregions buffer the hydrological response to fires.
WATER RESOURCES RESEARCH
(2023)
Article
Water Resources
Brenton A. Wilder, Jeremy T. Lancaster, Peter H. Cafferata, Drew B. R. Coe, Brian J. Swanson, Donald N. Lindsay, William R. Short, Alicia M. Kinoshita
Summary: The accuracy of the RCS method was found to be low, underestimating peak streamflow both before and after wildfires. Machine learning techniques were used to develop more accurate models for predicting post-fire peak streamflow, demonstrating the importance of data availability in improving flood risk assessment models.
HYDROLOGICAL PROCESSES
(2021)
Article
Computer Science, Interdisciplinary Applications
Michele Magni, Edwin H. Sutanudjaja, Youchen Shen, Derek Karssenberg
Summary: We propose a new hybrid framework that incorporates information from the PCR-GLOBWB model to improve streamflow simulations. By using simulated streamflow and state variables as predictors, along with catchment attributes and meteorological data, the random forest model can enhance estimates of river discharge worldwide. The model shows significant improvement in performance, even in poorly gauged and ungauged basins.
JOURNAL OF HYDROINFORMATICS
(2023)
Article
Environmental Studies
Shilei Liu, Jintao Xu
Summary: The establishment of protected areas is significantly associated with a decrease in fire risk, but the ownership of forests within protected areas plays a key role in determining fire activities. Insufficient compensation may be one of the reasons for higher fire risk in collectively or individually owned forests. A solution to this problem is the provision of more financial compensation within protected areas in China.
Article
Geosciences, Multidisciplinary
Alessandro Ielpi, Mathieu G. A. Lapotre
Summary: Wildfires cause changes in water, sediment, and biogeochemical fluxes in watersheds, especially due to soil destabilization and reduced evapotranspiration. Although local slope failures after wildfires are well-known, there is limited understanding of larger-scale sediment flux changes. This study develops a model to estimate sediment flux in a watershed heavily impacted by a megafire, and finds that post-fire channel widening and migration are linked to increased sediment flux to floodplain reaches.
Article
Engineering, Environmental
Viacheslav I. Kharuk, Evgenii I. Ponomarev, Galina A. Ivanova, Maria L. Dvinskaya, Sean C. P. Coogan, Mike D. Flannigan
Summary: Most wildfires in Siberia occur in larch forests, with warming leading to an increase in their frequency and area. Larch and Scots pine have adapted to periodic forest fires, contributing to their competitive advantage in the taiga.
Letter
Forestry
Ross Bradstock, Michael Bedward, Nicholas Wilson
Summary: The study found that logging has a much greater impact on above ground carbon stocks compared to wildfire, especially in Eucalypt forests. The commentator, however, challenges the findings of the study because they do not align with his expectations and questions the conclusions drawn.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Environmental Sciences
T. D. Penman, S. C. McColl-Gausden, B. A. Cirulis, D. Kultaev, D. A. Ababei, L. T. Bennett
Summary: The extent and impacts of wildfires are increasing worldwide. Fire management agencies use simulation models to understand fire behavior and reduce risks, with a major challenge being the accurate prediction of fuel variables across landscapes to improve the accuracy of fire behavior predictions.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Ecology
Shelby A. Weiss, Adrienne M. Marshall, Katherine R. Hayes, Dmitry J. Nicolsky, Brian Buma, Melissa S. Lucash
Summary: This study used a model to simulate the shifts in forest type under future climate change in interior Alaska and found that increased frequency and severity of wildfires favored a transition from conifer-dominated forests to broadleaf-deciduous forests. These results highlight the complex interactions between climate change and forests, as well as the non-linear nature of forest type shifts.
Article
Geosciences, Multidisciplinary
S. Sreedevi, T. I. Eldho, T. Jayasankar
Summary: This study evaluates the impacts of land use/land cover and climate change on hydrology and soil erosion processes in a humid tropical region in India. Using the SHETRAN model, the researchers compare past land use maps and climate data with future climate scenarios. The results show that land use, climate variability, and combined effects have different influences on streamflow and sediment load. The projections from a general circulation model indicate an increase in temperature, precipitation, streamflow, and sediment load in the future. The SHETRAN model proves to be effective in assessing the impact of climate change on hydrology and sediment yield, providing valuable insights for future river basin management.
Article
Forestry
Fatih Sari
Summary: Turkey's Mediterranean coast is at high risk of wildfires due to its dense forest cover and mild climate. Each year, an average of 250 wildfires occur, destroying over 10,000 hectares of land. This study investigated wildfires caused by lightning, stubble burning, discarded cigarette butts, and power lines in certain provinces of Turkey. Using the MaxEnt method, the spatial distribution of these wildfires was determined to identify risk zones. The findings highlight the importance of identifying the causes of wildfires for prediction and prevention.
JOURNAL OF FORESTRY RESEARCH
(2023)
Article
Ecology
Henrique Furstenau Togashi, Iain Colin Prentice, Bradley John Evans, David Ian Forrester, Paul Drake, Paul Feikema, Kim Brooksbank, Derek Eamus, Daniel Taylor
ECOLOGY AND EVOLUTION
(2015)
Article
Agronomy
P. M. Feikema, T. G. Baker
AGRICULTURAL WATER MANAGEMENT
(2011)
Article
Ecology
Peter Miehle, Michael Battaglia, Peter J. Sands, David I. Forrester, Paul M. Feikema, Stephen J. Livesley, Jim D. Morris, Stefan K. Arndt
ECOLOGICAL MODELLING
(2009)
Article
Computer Science, Interdisciplinary Applications
P. N. J. Lane, P. M. Feikema, C. B. Sherwin, M. C. Peel, A. C. Freebairn
ENVIRONMENTAL MODELLING & SOFTWARE
(2010)
Article
Computer Science, Interdisciplinary Applications
Paul M. Feikema, Gary J. Sheridan, Robert M. Argent, Patrick N. J. Lane, Rodger B. Grayson
ENVIRONMENTAL MODELLING & SOFTWARE
(2011)
Article
Forestry
Peter Miehle, Ruediger Grote, Michael Battaglia, Paul M. Feikema, Stefan K. Arndt
EUROPEAN JOURNAL OF FOREST RESEARCH
(2010)
Article
Forestry
Paul M. Feikema, Jim D. Morris, Craig R. Beverly, John J. Collopy, Thomas G. Baker, Patrick N. J. Lane
FOREST ECOLOGY AND MANAGEMENT
(2010)
Article
Plant Sciences
Richard Benyon, Shane Haydon, Rob Vertessy, Tom Hatton, George Kuczera, Paul Feikema, Patrick Lane
FUNCTIONAL PLANT BIOLOGY
(2010)
Article
Forestry
Paul M. Feikema, Joanna M. Sasse, Gamini D. Bandara
Article
Agronomy
Paul M. Feikema, Jim D. Morris, Luke D. Connell
Article
Engineering, Civil
Julien Lerat, Mark Thyer, David McInerney, Dmitri Kavetski, Fitsum Woldemeskel, Christopher Pickett-Heaps, Daeyhok Shin, Paul Feikema
JOURNAL OF HYDROLOGY
(2020)
Article
Geosciences, Multidisciplinary
Andrew Schepen, Tongtiegang Zhao, Q. J. Wang, Senlin Zhou, Paul Feikema
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2016)
Article
Biodiversity Conservation
Peter Miehle, Stephen J. Livesley, Changsheng Li, Paul M. Feikema, Mark A. Adams, Stefan K. Arndt
GLOBAL CHANGE BIOLOGY
(2006)
Article
Ecology
P Miehle, SJ Livesley, PM Feikema, C Li, SK Arndt
ECOLOGICAL MODELLING
(2006)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)