Review
Agronomy
Gordon B. Bonan, Edward G. Patton, John J. Finnigan, Dennis D. Baldocchi, Ian N. Harman
Summary: This article revisits a 30-40-year-old debate about the representation of plant canopies in weather forecast and climate models. The study finds that using a multilayer representation of plant canopies more accurately simulates fluxes compared to a single-layer representation. The differences between single-layer and multilayer representations suggest that the land surface modeling community should revisit the big-leaf surface flux parameterizations used in models.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Review
Environmental Sciences
Carlos Quemada, Jose M. Perez-Escudero, Ramon Gonzalo, Inigo Ederra, Luis G. Santesteban, Nazareth Torres, Juan Carlos Iriarte
Summary: This paper reviews various remote sensing techniques for monitoring plant water status, categorizing them based on the part of the plant being measured. The study presents the trends in published papers, the most common sensors used, and the water indicators identified. Overall, it highlights the significant correlation between estimated and measured data, providing valuable insights for irrigation management.
Article
Biodiversity Conservation
Lei Zhou, Wen Zhou, Jijing Chen, Xiyan Xu, Yonglin Wang, Jie Zhuang, Yonggang Chi
Summary: The study integrated four remote sensing indices to estimate land surface phenology across different land cover types. The results showed that the remote sensing indices can capture land surface phenology, but with varying abilities across different cover types. The integration of multiple remote sensing indices can improve the accuracy of estimating land surface phenology.
ECOLOGICAL INDICATORS
(2022)
Editorial Material
Environmental Sciences
Yunjun Yao, Xiaotong Zhang, Gad Levy, Kun Jia, Ayad M. Fadhil Al-Quraishi
Summary: This article discusses the practical applications of remote sensing technology in estimating land-ocean heat fluxes, including radiation, latent heat flux, atmospheric water vapor, vegetation cover, and biomass. The research in this field helps scientists understand the strengths and weaknesses of remote sensing technology in monitoring surface energy, water, and carbon budgets, and provides practical guidance for applying this technology.
Article
Engineering, Ocean
Mingzhu Song, Shiyao Wang, Penglu Zhao, Yantong Chen, Junsheng Wang
Summary: This study investigated the imaging mechanism of Kelvin wake in visible spectral remote sensing and proposed a method to quantify the reflectance resolution for Kelvin wake imaging on rough sea surfaces. The research also analyzed the impact of different factors on reflectance resolution, established an imaging chain model, and simulated the changes in imaging results.
APPLIED OCEAN RESEARCH
(2021)
Review
Plant Sciences
Bin J. W. Chen, Shuqing N. Teng, Guang Zheng, Lijuan Cui, Shao-peng Li, Arie Staal, Jan U. H. Eitel, Thomas W. Crowther, Miguel Berdugo, Lidong Mo, Haozhi Ma, Lalasia Bialic-Murphy, Constantin M. Zohner, Daniel S. Maynard, Colin Averill, Jian Zhang, Qiang He, Jochem B. Evers, Niels P. R. Anten, Hezi Yizhaq, Ilan Stavi, Eli Argaman, Uri Basson, Zhiwei Xu, Ming-Juan Zhang, Kechang Niu, Quan-Xing Liu, Chi Xu
Summary: This article explores how remote sensing technologies can be used to infer plant-plant interactions and their roles in shaping plant-based systems at different levels, including individual, community, and landscape. Remote sensing data can detect the key attributes of ecosystems derived from plant-plant interactions. By combining remote sensing techniques with theories, models, experiments, and data analysis algorithms, we can better understand biotic interactions and scale ecological patterns.
JOURNAL OF ECOLOGY
(2022)
Editorial Material
Microbiology
Kaitlin M. Gold
Summary: Plant disease sensing is an emerging discipline that holds great promise for modern agriculture by utilizing proximal and/or remote sensing for disease detection and diagnosis. Despite its revolutionary potential, challenges remain in both fundamental research and field application for plant disease sensing.
Article
Environmental Sciences
Junfang Zhao, Dongsheng Liu, Yun Cao, Lijuan Zhang, Huiwen Peng, Kaili Wang, Hongfei Xie, Chunzhi Wang
Summary: This study utilized the FORCCHN model and remote sensing data to simulate the carbon sequestration potential of forest ecosystems in China over the past 39 years, revealing a significant carbon sequestration potential with spatial regional differences in Chinese forests.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Agronomy
Salima Yousfi, Jose Marin, Lorena Parra, Jaime Lloret, Pedro Mauri
Summary: Turfgrass phenotyping is an important tool in grass breeding, and remote sensing techniques provide a rapid and accurate way to evaluate turfgrass growth under water stress. This study evaluated the differences in turfgrass mixtures under different irrigation conditions using remote sensing indices, and found that vegetation and water status indices can effectively distinguish drought-tolerant and susceptible turfgrass. Additionally, the study highlighted the advantages of using drone imagery to derive green area vegetation index for assessing turfgrass variability.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Plant Sciences
Liang He, Weiwei Sun, Xiang Chen, Liqi Han, Jincai Li, Yuanshan Ma, Youhong Song
Summary: This study successfully modeled the final morphology of maize canopy under increased interplant competition by revising the ADEL-Maize model, revealing the impact of increased plant density on canopy morphology. The research laid a foundation for studying the adaptability of maize under high interplant competition.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Environmental Sciences
Ali Bennour, Li Jia, Massimo Menenti, Chaolei Zheng, Yelong Zeng, Beatrice Asenso Barnieh, Min Jiang
Summary: This study developed and applied a new approach to calibrate hydrological models using distributed geospatial remote sensing data in the Lake Chad Basin in Africa. Through sensitivity analysis and optimization of influential parameters, the model performance was significantly improved. The new approach of using remote sensing ETa for a limited period of time showed robustness and good performance.
Article
Meteorology & Atmospheric Sciences
Tzu-Ying Yang, Cho-Ying Huang, Jehn-Yih Juang, Yi-Ying Chen, Chao-Tzuen Cheng, Min-Hui Lo
Summary: Fog plays a crucial role in maintaining montane cloud forest ecosystems. Future climate changes may impact the hydroclimatology of cloud forests. Increased rainfall intensity decreases the accumulation of canopy water, while higher water vapor concentrations lead to more nighttime condensation on leaves. Elevated CO2 concentrations have minimal effects on canopy water, but enhance photosynthesis and reduce transpiration. Evapotranspiration decreases in cloud forest regions, contrasting with the expected intensification in the global water cycle under global warming.
JOURNAL OF HYDROMETEOROLOGY
(2022)
Article
Agriculture, Multidisciplinary
Yuanyuan Pan, Wenxuan Wu, Jiawen Zhang, Yuejiao Zhao, Jiayi Zhang, Yangyang Gu, Xia Yao, Tao Cheng, Yan Zhu, Weixing Cao, Yongchao Tian
Summary: The calculation of Canopy scattering coefficient (CSC) is crucial for correcting the effect of canopy structure. However, accurately calculating crop DASF using multispectral UAV data remains a pressing problem. This study proposed a DASF(k-b) model based on RAGDD and BRF to estimate b and k. The results showed that CSCk-b had the best correction effect on canopy structure under different VZAs and improved the accuracy of estimating LNC and LCC compared to CSCg-NIR and VIs.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Ecology
Patrick Schwager, Christian Berg
Summary: Species distribution models based on a combination of remote sensing data and topographic/geological variables outperform models using individual variable types. Ensemble models perform slightly better compared to different model algorithms, identifying temperature, NDVI, and bedrock as important determinants of alpine plant species distribution. These models are crucial for conservation efforts in identifying suitable areas for either in-situ or ex-situ conservation.
BASIC AND APPLIED ECOLOGY
(2021)
Article
Environmental Sciences
Yapeng Zhao, Xiaozhe Yin, Yan Fu, Tianxiang Yue
Summary: The combination of machine learning algorithms with high-accuracy surface modeling offers new opportunities for predicting plant species diversity, with XGBoost combined with HASM showing the best performance.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Meteorology & Atmospheric Sciences
Cecile B. Menard, Richard Essery, Gerhard Krinner, Gabriele Arduini, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Emanuel Dutra, Xing Fang, Charles Fierz, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Hyungjun Kim, Matthieu Lafaysse, Thomas Marke, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Gerd Schaedler, Vladimir A. Semenov, Tatiana Smirnova, Ulrich Strasser, Sean Swenson, Dmitry Turkov, Nander Wever, Hua Yuan
Summary: The Earth System Model-Snow Model Intercomparison Project (ESM-SnowMIP) involved 27 models and found that current evaluation methods do not significantly enhance the identification of key new processes for modeling snow mass and energy budgets. The same modeling issues as previous snow MIPs were identified, with human errors causing anomalous model behavior.
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
(2021)
Article
Meteorology & Atmospheric Sciences
D. Saint-Martin, O. Geoffroy, A. Voldoire, J. Cattiaux, F. Brient, F. Chauvin, M. Chevallier, J. Colin, B. Decharme, C. Delire, H. Douville, J-F Gueremy, E. Joetzjer, A. Ribes, R. Roehrig, L. Terray, S. Valcke
Summary: The study investigates the increase in equilibrium climate sensitivity (ECS) in CNRM-CM6-1 and CNRM-CM6-1-HR compared to CNRM-CM5.1 using coupled ocean-atmosphere model climate change simulations. It finds that the change is primarily due to changes in the atmospheric component, particularly the cloud radiative responses with significant contributions from tropical longwave response and extratropical and tropical shortwave feedback changes.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2021)
Article
Meteorology & Atmospheric Sciences
A. Bernus, C. Ottle, N. Raoult
Summary: By analyzing the global distribution of lake characteristics and conducting a sensitivity analysis of FLake parameters, the study highlights the importance of lake depth, radiative parameters, and thermocline relaxation coefficient in different climate conditions.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2021)
Review
Environmental Sciences
N. MacBean, C. Bacour, N. Raoult, V. Bastrikov, E. N. Koffi, S. Kuppel, F. Maignan, C. Ottle, M. Peaucelle, D. Santaren, P. Peylin
Summary: This review presents the development of a carbon cycle data assimilation (DA) system for optimizing carbon cycle parameters in the ORCHIDEE TBM. The authors analyze the impact of assimilating different carbon cycle related datasets on CO2 fluxes and find that assimilating atmospheric CO2 data is crucial for improving predictions of the terrestrial land carbon sink.
GLOBAL BIOGEOCHEMICAL CYCLES
(2022)
Article
Multidisciplinary Sciences
Yuanyu Xie, Meiyun Lin, Bertrand Decharme, Christine Delire, Larry W. Horowitz, David M. Lawrence, Fang Li, Roland Seferian
Summary: The study predicts the impact of increased wildfires on air quality in a warming climate. The results show a significant increase in CO2 emissions from wildfires, leading to a twofold to threefold increase in PM2.5 pollution in the US Pacific Northwest. Even with strong mitigation efforts, PM2.5 in the western US is projected to increase by around 50%. These findings highlight the significant impact of wildfires on air quality.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Environmental Sciences
Lucas Hardouin, Christine Delire, Bertrand Decharme, David M. Lawrence, Julia E. M. S. Nabel, Victor Brovkin, Nathan Collier, Rosie Fisher, Forrest M. Hoffman, Charles D. Koven, Roland Seferian, Tobias Stacke
Summary: Global estimates of the land carbon sink based on terrestrial biosphere models (TBMs) often fail to consider the uncertainties introduced by the atmospheric forcing datasets used to drive these models. This study demonstrates that the atmospheric forcing plays a dominant role in the uncertainties of global gross primary productivity (GPP) and autotrophic respiration, but has a smaller impact on net primary productivity and heterotrophic respiration. Furthermore, the importance of forcing uncertainty varies significantly between global and regional scales, with regional differences in model flux estimates partially offsetting each other globally.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Geography, Physical
Nina Raoult, Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottle, Vladislav Bastrikov
Summary: Greenland ice sheet mass loss is accelerating due to increasing global temperatures. The amount of absorbed solar energy, determined by the ice sheet's surface albedo, plays a crucial role in driving snow and ice melting. By optimizing the albedo scheme in the ORCHIDEE land surface model, focusing on the edges of the ice sheet, we improve the model's fit to data by reducing the root-mean-square deviation by over 25% for the entire ice sheet during the summer months. This improvement is consistent for all years and is also observed at in situ sites from the PROMICE network.
Article
Geosciences, Multidisciplinary
Jan Polcher, Anthony Schrapffer, Eliott Dupont, Lucia Rinchiuso, Xudong Zhou, Olivier Boucher, Emmanuel Mouche, Catherine Ottle, Jerome Servonnat
Summary: Land surface models use atmospheric grid for spatial decomposition and providing lower boundary conditions to the atmosphere, while lateral water flows require higher spatial discretization closely linked to topographic details. This study proposes a methodology to tile the atmospheric grid into hydrological coherent units, allowing easy transfer of land variables for water transport. The quality of generated river networks is compared to original data to quantify degradation introduced by discretization method. The proposed sub-grid approach allows realistic river discharge and temperature predictions independent of atmospheric grid used in an off-line version of ORCHIDEE LSM over Europe.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2023)
Article
Geosciences, Multidisciplinary
Kandice L. Harper, Celine Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottle, Vladislav Bastrikov, Rodrigo San Martin, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, Pierre Defourny
Summary: The existing medium-resolution land cover time series provides detailed annual land cover maps at 300 m resolution from 1992 to 2020. To apply this series to Earth system and land surface models, land cover classes need to be converted into model-appropriate plant functional types (PFTs). A new ready-to-use data product has been created, which includes spatially explicit annual maps of PFT fractional composition at 300 m resolution for 1992-2020. This dataset has been used in land surface models to demonstrate its benefits over conventional maps.
EARTH SYSTEM SCIENCE DATA
(2023)
Article
Meteorology & Atmospheric Sciences
Ling Huang, Xuhui Wang, Yanzi Yan, Lei Jin, Kun Yang, Anping Chen, Rongshun Zheng, Catherine Ottle, Chenzhi Wang, Yaokui Cui, Shilong Piao
Summary: Lake surface water temperature (LSWT) is a key parameter in lake energy budget and is highly vulnerable to climate change. This study used a lake model to simulate LSWT for 91 large lakes across China over a 40-year period. The results show an overall warming trend in LSWT, but with large spatial variations. The study also identifies air temperature, downward longwave radiation, and wind speed as the most important climatic drivers for LSWT changes.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2023)
Article
Geosciences, Multidisciplinary
Anthony Bernus, Catherine Ottle
Summary: The study coupled the freshwater 1-D FLake lake model with the ORCHIDEE land surface model to simulate global lake energy balance. The results showed that atmospheric forcing had a significant impact on lake energy budget simulations, and higher resolution products led to improvements. The depth parameterization strategy had a minimal influence on the results. Systematic errors were observed in the simulation of ice phenology, which could be explained by scale effects and deficiencies in modeling snow-ice processes. The use of remote sensing data was suggested to improve the model results.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Geosciences, Multidisciplinary
Simon Munier, Bertrand Decharme
Summary: This paper presents a new global-scale river network and its associated hydro-geomorphological parameters, which improve model performance by increasing spatial resolution. The new river network and parameters are useful for hydrology and hydro-geology modeling, water resources monitoring, and climate studies.
EARTH SYSTEM SCIENCE DATA
(2022)
Article
Geosciences, Multidisciplinary
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quere, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frederic Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Ozgur Gurses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jurgen Knauer, Jan Ivar Korsbakken, Arne Kortzinger, Peter Landschutzer, Siv K. Lauvset, Nathalie Lefevre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rodenbeck, Thais M. Rosan, Jorg Schwinger, Clemens Schwingshackl, Roland Seferian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sonke Zaehle, Jiye Zeng
Summary: Accurate assessment of anthropogenic CO2 emissions and their redistribution among different components is critical for understanding the global carbon cycle. This study presents datasets and methodologies to quantify the major components of the global carbon budget. The results show changes in fossil fuel and land-use change emissions, as well as atmospheric CO2 concentration, ocean CO2 sink, and terrestrial CO2 sink.
EARTH SYSTEM SCIENCE DATA
(2022)
Article
Geosciences, Multidisciplinary
Thibault Guinaldo, Simon Munier, Patrick Le Moigne, Aaron Boone, Bertrand Decharme, Margarita Choulga, Delphine J. Leroux
Summary: This study aims to introduce a new lake mass module, MLake, into the river-routing model CTRIP to address specific mass balance issues of open-water bodies. The improved model shows a general enhancement in simulating discharge and variability, producing more realistic streamflows and lake level variations. Spatial scale-dependency and anthropization effects of selected lakes may affect the model's performance, but overall results indicate significant improvements in river-routing simulations and potential for future global water resources assessment.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2021)
Article
Geosciences, Multidisciplinary
Zun Yin, Catherine Ottle, Philippe Ciais, Feng Zhou, Xuhui Wang, Polcher Jan, Patrice Dumas, Shushi Peng, Laurent Li, Xudong Zhou, Yan Bo, Yi Xi, Shilong Piao
Summary: This study successfully simulated the streamflow of the Yellow River using a mechanistic global land surface model and quantified the impacts of irrigation and dam operation on streamflow fluctuations. The findings suggest that irrigation significantly reduces river streamflows, while dam operation has a greater impact on streamflow seasonality.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
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)
