Article
Engineering, Civil
Huiyuan Liu, Xiaozhou Xin, Zhongbo Su, Yijian Zeng, Ting Lian, Li Li, Shanshan Yu, Hailong Zhang
Summary: This study evaluates ten globally available monthly evapotranspiration (ET) products at site and basin scales. The results show that all products perform comparably and there is no single product with the best performance. FLUXCOM and GLDAS have outstanding performance at site and basin scales, respectively, while SynthesisET performs suboptimally at both validation scales. This study contributes to identifying proper candidates for hydrological analysis and improving ET algorithm.
JOURNAL OF HYDROLOGY
(2023)
Article
Biodiversity Conservation
Natalia Restrepo-Coupe, Loren P. Albert, Marcos Longo, Ian Baker, Naomi M. Levine, Lina M. Mercado, Alessandro C. da Araujo, Bradley O'Donnell Christoffersen, Marcos H. Costa, David R. Fitzjarrald, David Galbraith, Hewlley Imbuzeiro, Yadvinder Malhi, Celso von Randow, Xubin Zeng, Paul Moorcroft, Scott R. Saleska
Summary: The research reports the seasonality of latent heat, sensible heat, and radiation fluxes at four different tropical forest sites in the Amazon, investigating how vegetation and climate influence these fluxes. It was found that the model failure to capture observed dry-season increases in evapotranspiration was associated with model overestimations of Bowen ratios, canopy characteristics, and vegetation temperatures. These discrepancies significantly biased seasonal model estimates of net radiation, indicating the need for a better representation of energy-related parameters in current vegetation-atmosphere exchange models.
GLOBAL CHANGE BIOLOGY
(2021)
Article
Agronomy
Huijie Hu, Yongzong Lu, Yongguang Hu, Risheng Ding
Summary: Seasonal drought in China's lower slope hilly areas causes significant economic loss to tea production. Accurate determination of evapotranspiration (ET) is crucial for irrigation management. The surface renewal (SR) method is an accurate and inexpensive alternative to the eddy covariance (EC) method for calculating sensible heat flux. This study compared traditional (SRsnyder) and improved (SRchen) SR methods for calculating H over a tea field for a year, finding that SRchen showed better accuracy during spring, summer, and autumn. The study recommends using SRchen in the Yangtze River region's tea field ecosystem during those seasons, and SRsnyder in winter.
Article
Environmental Sciences
Michele L. de Oliveira, Carlos A. C. dos Santos, Gabriel de Oliveira, Madson T. Silva, Bernardo B. da Silva, John E. de B. L. Cunha, Anderson Ruhoff, Celso A. G. Santos
Summary: The spatio-temporal assessment of water and carbon fluxes in Brazil's Northeast region provides insights into the surface flux patterns in different vegetation types. The study shows that land degradation and climate impacts have led to reduced photosynthetic activity and increased vulnerability to desertification in the Caatinga biome, particularly in sparse areas. Dense Caatinga exhibits higher photosynthetic activity and greater resilience to climate effects. Compared to other biomes in the region, Caatinga has lower rates of evapotranspiration and gross primary production.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Agronomy
John M. Frank, William J. Massman
Summary: This study compares different calibration methods for fast-response hygrometers and their influence on the flux measurements. The results show that the choice of calibration method and the sensor technology can significantly affect the flux differences. The piecewise calibration method resulted in the smallest differences, but the Lyman-alpha and KH2O sensors experienced severe drifts. Oxygen correction and tube attenuation spectral correction were found to be influential factors. The impact of hygrometers on energy balance closure was minor compared to the choice of sonic anemometer.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Multidisciplinary Sciences
Mingjuan Xie, Xiaofei Ma, Yuangang Wang, Chaofan Li, Haiyang Shi, Xiuliang Yuan, Olaf Hellwich, Chunbo Chen, Wenqiang Zhang, Chen Zhang, Qing Ling, Ruixiang Gao, Yu Zhang, Friday Uchenna Ochege, Amaury Frankl, Philippe De Maeyer, Nina Buchmann, Iris Feigenwinter, Jorgen E. Olesen, Radoslaw Juszczak, Adrien Jacotot, Aino Korrensalo, Andrea Pitacco, Andrej Varlagin, Ankit Shekhar, Annalea Lohila, Arnaud Carrara, Aurore Brut, Bart Kruijt, Benjamin Loubet, Bernard Heinesch, Bogdan Chojnicki, Carole Helfter, Caroline Vincke, Changliang Shao, Christian Bernhofer, Christian Bruemmer, Christian Wille, Eeva-Stiina Tuittila, Eiko Nemitz, Franco Meggio, Gang Dong, Gary Lanigan, Georg Niedrist, Georg Wohlfahrt, Guoyi Zhou, Ignacio Goded, Thomas Gruenwald, Janusz Olejnik, Joachim Jansen, Johan Neirynck, Juha-Pekka Tuovinen, Junhui Zhang, Katja Klumpp, Kim Pilegaard, Ladislav Sigut, Leif Klemedtsson, Luca Tezza, Lukas Hoertnagl, Marek Urbaniak, Marilyn Roland, Marius Schmidt, Mark A. Sutton, Markus Hehn, Matthew Saunders, Matthias Mauder, Mika Aurela, Mika Korkiakoski, Mingyuan Du, Nadia Vendrame, Natalia Kowalska, Paul G. Leahy, Pavel Alekseychik, Peili Shi, Per Weslien, Shiping Chen, Silvano Fares, Thomas Friborg, Tiphaine Tallec, Tomomichi Kato, Torsten Sachs, Trofim Maximov, Umberto Morra di Cella, Uta Moderow, Yingnian Li, Yongtao He, Yoshiko Kosugi, Geping Luo
Summary: A framework combining machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS) was established to simulate daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of meteorological stations in Eurasia. The generated carbon-water flux datasets have the potential to improve assessments of ecosystem carbon-water dynamics.
Article
Engineering, Civil
T. Pluntke, C. Bernhofer, T. Grunwald, M. Renner, H. Prasse
Summary: This study found that climate change in Central Europe has led to increased variability in precipitation and increased evapotranspiration due to higher temperatures. This has resulted in lower and more variable infiltration and runoff. The study also revealed that the impact of climate change on evapotranspiration has been strengthening in recent decades.
JOURNAL OF HYDROLOGY
(2023)
Article
Agronomy
Weijie Zhang, Martin Jung, Mirco Migliavacca, Rafael Poyatos, Diego G. Miralles, Tarek S. El-Madany, Marta Galvagno, Arnaud Carrara, Nicola Arriga, Andreas Ibrom, Ivan Mammarella, Dario Papale, Jamie R. Cleverly, Michael Liddell, Georg Wohlfahrt, Christian Markwitz, Matthias Mauder, Eugenie Paul -Limoges, Marius Schmidt, Sebastian Wolf, Christian Bruemmer, M. Altaf Arain, Silvano Fares, Tomomichi Kato, Jonas Ardo, Walter Oechel, Chad Hanson, Mika Korkiakoski, Sebastien Biraud, Rainer Steinbrecher, Dave Billesbach, Leonardo Montagnani, William Woodgate, Changliang Shao, Nuno Carvalhais, Markus Reichstein, Jacob A. Nelson
Summary: We evaluated the underestimation of latent heat flux (LE) associated with high relative humidity (RH) for different eddy covariance (EC) systems using the FLUXNET2015 dataset. We found that closed-path EC systems showed the most significant underestimation when RH was above 70%, and the extent of underestimation varied among sites. We proposed a machine learning-based method to correct this underestimation and compared it with two energy balance closure-based LE correction approaches. Our results highlight the importance of considering the high RH bias in water fluxes when estimating ecosystem T/ET and WUE.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Ecology
Terenzio Zenone, Luca Vitale, Daniela Famulari, Vincenzo Magliulo
Summary: This study investigated the daily and seasonal patterns of evaporative fraction (EF) in a multi-year corn cultivation and evaluated the performance of five machine learning algorithms in predicting EF. The results showed that support vector machine and Gaussian process regression were the best algorithms. Cross-validation analysis confirmed the ability of machine learning to predict EF.
ECOLOGICAL PROCESSES
(2022)
Article
Engineering, Civil
Mingzhu Cao, Weiguang Wang, Wanqiu Xing, Jia Wei, Xintao Chen, Jinxing Li, Quanxi Shao
Summary: This study examined the uncertainties in remote sensing-based ET estimation by using three different models and three meteorological reanalysis products, resulting in nine calculation schemes. The results showed significant differences in the magnitude and temporal variation of ET estimates, with uncertainties potentially caused by energy balance closure issues and spatial scale mismatch.
JOURNAL OF HYDROLOGY
(2021)
Article
Agriculture, Multidisciplinary
Juan Miguel Ramirez-Cuesta, Simona Consoli, Domenico Longo, Giuseppe Longo-Minnolo, Diego S. Intrigliolo, Daniela Vanella
Summary: Land surface temperature (LST) is crucial in precision agriculture and crop evapotranspiration (ETc) calculations. This study analyzed the temporal dynamics of LST and its impact on heat fluxes using thermal imagery and surface energy balance approaches. The results showed significant LST variations even under steady meteorological conditions. These variations resulted in significant differences in heat fluxes, especially during fast-varying meteorological conditions. Therefore, accurate meteorological data or post-processing corrections are necessary when applying ETc maps for precision irrigation protocols.
PRECISION AGRICULTURE
(2022)
Article
Environmental Sciences
Amanda do Nascimento Ferreira, Andreia de Almeida, Sergio Koide, Ricardo Tezini Minoti, Mario Benjamim Baptista de Siqueira
Summary: This study aims to evaluate the SWAT model's capability in simulating evapotranspiration in a Brazilian Cerrado-dominated watershed. Hydrological modeling of the Gama watershed was conducted, monitoring hydrometeorological and turbulent flow variables in weather station and EC tower. SWAT simulations using different methods showed fair results, with the PM method demonstrating the best fitness.
Article
Agronomy
Saad Kibria, Sara Masia, Janez Susnik, Tim Martijn Hessels
Summary: This research critically compares ETa estimates obtained using ground-based, remotely sensed, and simulated data, showing relatively small and consistent variation between the methods, with the remote sensing method deviating and in need of further improvement.
AGRICULTURAL WATER MANAGEMENT
(2021)
Article
Agronomy
Hassan Awada, Simone Di Prima, Costantino Sirca, Filippo Giadrossich, Serena Marras, Donatella Spano, Mario Pirastru
Summary: Satellite remote sensing-based surface energy balance techniques are useful for quantifying actual evapotranspiration, but continuous time series of daily crop actual evapotranspiration are more valuable in agriculture water management. The integrated modeling approach in this research successfully constructed continuous time series of daily ETc act and showed good agreement with observed dynamics.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Meteorology & Atmospheric Sciences
Jianbin Zhang, Zexia Duan, Shaohui Zhou, Yubin Li, Zhiqiu Gao
Summary: This study examined the accuracy of the random forest model in gap filling sensible and latent heat fluxes using observation data from a site in eastern China. The results showed that net radiation was the most important input variable, and the random forest model reliably filled the gaps with high accuracy compared to other models.
ATMOSPHERIC MEASUREMENT TECHNIQUES
(2023)
Article
Agronomy
Umar Waqas Liaqat, Usman Khalid Awan, Matthew Francis McCabe, Minha Choi
AGRICULTURAL WATER MANAGEMENT
(2016)
Article
Environmental Sciences
Muhammad Azmat, Minha Choi, Tae-Woong Kim, Umar Waqas Liaqat
ENVIRONMENTAL EARTH SCIENCES
(2016)
Article
Water Resources
Usman Khalid Awan, Umar Waqas Liaqat, Minha Choi, Ali Ismaeel
HYDROLOGY RESEARCH
(2016)
Article
Agronomy
Usman Khalid Awan, Mirzakhayot Ibrakhimov, Bogachan Benli, John P. A. Lamers, Umar Waqas Liaqat
IRRIGATION SCIENCE
(2017)
Article
Environmental Sciences
Muhammad Azmat, Umar Waqas Liaqat, Muhammad Uzair Qamar, Usman Khalid Awan
REGIONAL ENVIRONMENTAL CHANGE
(2017)
Article
Engineering, Civil
Muhammad Imran Khan, Dong Liu, Qiang Fu, Shuhua Dong, Umar Waqas Liaqat, Muhammad Abrar Faiz, Yuxiang Hu, Qaisar Saddique
WATER RESOURCES MANAGEMENT
(2016)
Article
Water Resources
Usman Khalid Awan, Umar Waqas Liaqat, Minha Choi, Ali Ismaeel
HYDROLOGY RESEARCH
(2016)
Article
Green & Sustainable Science & Technology
Umar Waqas Liaqat, Minha Choi
JOURNAL OF CLEANER PRODUCTION
(2017)
Article
Agronomy
Muhammad Sarfraz Khan, Umar Waqas Liaqat, Jongjin Baik, Minha Choi
AGRICULTURAL AND FOREST METEOROLOGY
(2018)
Article
Agronomy
Mirzakhayot Ibrakhimov, Usman Khalid Awan, Biju George, Umar Waqas Liaqat
AGRICULTURAL WATER MANAGEMENT
(2018)
Article
Nuclear Science & Technology
Qurat-ul-ain Sahi, Yong-Soo Kim
NUCLEAR ENGINEERING AND TECHNOLOGY
(2018)
Article
Agronomy
Jongjin Baik, Umar Waqas Liaqat, Minha Choi
AGRICULTURAL AND FOREST METEOROLOGY
(2018)
Article
Water Resources
Umar Waqas Liaqat, Minha Choi, Usman Khalid Awan
HYDROLOGICAL PROCESSES
(2015)
Article
Geography
Fazlullah Akhtar, Usman Khalid Awan, Bernhard Tischbein, Umar Waqas Liaqat
Article
Agronomy
Wenyi Xu, Bo Elberling, Per Lennart Ambus
Summary: The frequency and extent of wildfires in the Arctic have been increasing due to climate change. In this study, researchers conducted experiments in West Greenland to investigate the long-term impacts of climate warming on post-fire carbon dioxide exchange in arctic tundra ecosystems. They found that fire increased soil organic phosphorus concentrations and burned areas remained a net CO2 source five years after the fire. However, with four to five years of summer warming, the burned areas turned into a net CO2 sink.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yuanhang Yang, Jiabo Yin, Shengyu Kang, Louise J. Slater, Xihui Gu, Aliaksandr Volchak
Summary: This study investigates the impacts of water and heat stress on carbon uptake in China and explores the driving mechanisms of droughts using a machine learning model. The results show that droughts are mostly driven by atmospheric dryness, with precipitation, relative humidity, and temperature playing dominant roles. Water and heat stress have negative impacts on carbon assimilation, and drought occurrence is projected to increase significantly in the future. Improving ecosystem resilience to climate warming is crucial in mitigating the negative effects of droughts on carbon uptake.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ningbo Cui, Shunsheng Zheng, Shouzheng Jiang, Mingjun Wang, Lu Zhao, Ziling He, Yu Feng, Yaosheng Wang, Daozhi Gong, Chunwei Liu, Rangjian Qiu
Summary: This study proposes a method to partition evapotranspiration (ET) into its components in agroforestry systems. The method is based on water-carbon coupling theory and flux conservation hypothesis. The results show that the partitioned components agree well with measurements from other sensors. The study also finds that atmospheric evaporation demand and vegetation factors greatly influence the components of ET, and increased tree leaf area limits understory grass transpiration.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xinhao Li, Tianshan Zha, Andrew Black, Xin Jia, Rachhpal S. Jassal, Peng Liu, Yun Tian, Chuan Jin, Ruizhi Yang, Feng Zhang, Haiqun Yu, Jing Xie
Summary: With the rapid increase of urbanization, evapotranspiration (ET) in urban forests has become increasingly important in urban hydrology and climate. However, there is still a large uncertainty regarding the factors that regulate ET in urban areas. This study investigates the temporal variations of ET in an urban forest park in Beijing using the eddy-covariance technique. The results show that daily ET is close to zero during winter but reaches 3-6 mm day-1 in summer. Daily ET increases with vapor pressure deficit (VPD) and soil water content (SWC). Monthly ET increases linearly with normalized difference vegetation index and shows a strong correlation with surface conductance (gs), while exhibiting saturated responses to increasing monthly precipitation (PPT). Annual ET ranges from 326 to 566 mm, and soil water replenishment through PPT from the previous year is responsible for the generally higher monthly ET in spring relative to PPT. Biotic factors and PPT seasonality play essential roles in regulating ET at different scales.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Zhaogang Liu, Zhi Chen, Meng Yang, Tianxiang Hao, Guirui Yu, Xianjin Zhu, Weikang Zhang, Lexin Ma, Xiaojun Dou, Yong Lin, Wenxing Luo, Lang Han, Mingyu Sun, Shiping Chen, Gang Dong, Yanhong Gao, Yanbin Hao, Shicheng Jiang, Yingnian Li, Yuzhe Li, Shaomin Liu, Peili Shi, Junlei Tan, Yakun Tang, Xiaoping Xin, Fawei Zhang, Yangjian Zhang, Liang Zhao, Li Zhou, Zhilin Zhu
Summary: This study investigates the responses of temperate grassland (TG) and alpine grassland (AG) to climate change by studying carbon (C) fluxes across different regions in China. The results reveal that water factors consistently increase C fluxes, while temperature factors have opposite effects on TG and AG. The study enhances our understanding of C sinks and grassland sensitivity to climate change.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Peng Li, Huijie Li, Bingcheng Si, Tao Zhou, Chunhua Zhang, Min Li
Summary: This study mapped the distribution of forest age on the Chinese Loess Plateau using the LandTrendr algorithm. The results show that the LT algorithm is a convenient, efficient, and reliable method for identifying forest age. The findings have important implications for assessing and quantifying biomass and carbon sequestration in afforestation efforts on the Chinese Loess Plateau.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Review
Agronomy
Yean-Uk Kim, Heidi Webber, Samuel G. K. Adiku, Rogerio de S. Noia Junior, Jean-Charles Deswarte, Senthold Asseng, Frank Ewert
Summary: As climate change is expected to increase the intensity and frequency of extreme weather events, it is crucial to assess their impact on cropping systems and explore adaptation options. Process-based crop models (PBCMs) have improved in simulating the impacts of major extreme weather events, but still struggle to reproduce low crop yields under wet conditions. This article provides an overview of the yield-loss mechanisms of excessive rainfall in cereals and the associated modelling approaches, aiming to guide improvements in PBCMs.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xiaodong Liu, Yingjie Feng, Xinyu Zhao, Zijie Cui, Peiling Liu, Xiuzhi Chen, Qianmei Zhang, Juxiu Liu
Summary: Understanding the impact of climate on litterfall production is crucial for simulating nutrient cycling in forest ecosystems. This study analyzed a 14-year litterfall dataset from two subtropical forests in South China and found that litterfall was mainly influenced by wind speed during the wet season and by temperature during the dry season. These findings have potential significance in improving our understanding of carbon and nutrient cycling in subtropical forest ecosystems under climate change conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ruonan Chen, Liangyun Liu, Zhunqiao Liu, Xinjie Liu, Jongmin Kim, Hyun Seok Kim, Hojin Lee, Genghong Wu, Chenhui Guo, Lianhong Gu
Summary: Solar-induced chlorophyll fluorescence (SIF) has the potential to estimate gross primary production (GPP), but the quantitative relationship between them is not constant. In this study, a mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) was developed, considering the seasonal variation in a key parameter of the model. The GPP estimates from this model were more accurate compared to other benchmark models, especially in extreme conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jingyi Zhu, Yanzheng Yang, Nan Meng, Ruonan Li, Jinfeng Ma, Hua Zheng
Summary: This study developed a random forest model using climate station and satellite data to generate high-precision precipitation datasets for the Qinghai-Tibet Plateau. By incorporating multisource satellite data, the model achieved a significant enhancement in precipitation accuracy and showed promising results in regions with limited meteorological stations and substantial spatial heterogeneity in precipitation patterns.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yulin Yan, Youngryel Ryu, Bolun Li, Benjamin Dechant, Sheir Afgen Zaheer, Minseok Kang
Summary: Sustainable rice farming practices are urgently needed to meet increasing food demand, cope with water scarcity, and mitigate climate change. Traditional farming methods that prioritize a single objective have proven to be insufficient, while simultaneously optimizing multiple competing objectives remains less explored. This study optimized farm management to increase rice yield, reduce irrigation water consumption, and tackle the dilemma of reducing GHG emissions. The results suggest that the optimized management can maintain or even increase crop yield, while reducing water demand and GHG emissions by more than 50%.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Sasha D. Hafner, Jesper N. Kamp, Johanna Pedersen
Summary: This study compared micrometeorological and wind tunnel measurements using a semi-empirical model to understand wind tunnel measurement error. The results showed differences in emission estimates between the two methods, but the ALFAM2 model was able to reproduce emission dynamics for both methods when considering differences in mass transfer. The study provides a template for integrating and comparing measurements from different methods, suggesting the use of wind tunnel measurements for model evaluation and parameter estimation.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Wenfang Xu, Wenping Yuan, Donghai Wu, Yao Zhang, Ruoque Shen, Xiaosheng Xia, Philippe Ciais, Juxiu Liu
Summary: In the summer of 2022, China experienced record-breaking heatwaves and droughts, which had a significant impact on plant growth. The study also found that heatwaves were more critical than droughts in limiting vegetation growth.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jiaqi Guo, Xiaohong Liu, Wensen Ge, Liangju Zhao, Wenjie Fan, Xinyu Zhang, Qiangqiang Lu, Xiaoyu Xing, Zihan Zhou
Summary: Vegetation photosynthetic phenology is an important indicator for understanding the impacts of climate change on terrestrial carbon cycle. This study evaluated and compared the abilities of different spectral indices to model photosynthetic phenology, and found that NIRv and PRI are effective proxies for monitoring photosynthetic phenology.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Arango Ruda Elizabeth, M. Altaf Arain
Summary: Temperate deciduous forests have significant impacts on regional and global water cycles. This study examined the effects of climate change and extreme weather events on the water use and evapotranspiration of a temperate deciduous forest in eastern North America. The results showed that photosynthetically active radiation and air temperature were the primary drivers of evapotranspiration, while vapor pressure deficit regulated water use efficiency. The study also found a changing trend in water use efficiency over the years, influenced by extreme weather conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)