Article
Environmental Sciences
Martin Queinnec, Joanne C. White, Nicholas C. Coops
Summary: This study used ICESat-2 data to estimate forest structure in different boreal forest types in Ontario, Canada, including canopy height, cover, and height variability. Results showed strong agreement between ICESat-2 and airborne LiDAR for estimating canopy height in different forest development stages, but ICESat-2 tended to underestimate canopy height variability and cover compared to LiDAR data.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Micah Russell, Jan U. H. Eitel, Timothy E. Link, Carlos A. Silva
Summary: Forest canopies play a significant role in controlling the spatial distribution of snow cover. Airborne laser scanning (ALS) can be used to better characterize the three-dimensional distribution of canopy elements and to predict interception storage. ALS-derived canopy metrics, such as canopy length, whole-tree volume, and unobstructed returns, explain a large portion of the variability in snow interception volume, offering an improvement over traditional estimates based on LAI.
Article
Environmental Sciences
Tuo Feng, Laura Duncanson, Paul Montesano, Steven Hancock, David Minor, Eric Guenther, Amy Neuenschwander
Summary: The launch of ICESat-2 by NASA in September 2018 allows for the observation of high-resolution and three-dimensional surface elevations globally. This paper examines the accuracy of ICESat-2 data in boreal forests of North America, and finds strong agreements with the reference dataset LVIS in terms of terrain elevation and canopy height.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Agronomy
Martin Beland, Dennis D. Baldocchi
Summary: This study investigated the vertical profiles of foliage clumping and its impact on canopy photosynthesis in deciduous broadleaf forests. The research findings suggest that considering vertical profiles of foliage clumping can increase canopy photosynthesis through a greater contribution from shaded leaves in different canopy levels, leading to an optimization of photosynthesis. The study indicates that incorporating foliage clumping vertical profiles in TBMs could improve the accuracy of estimating canopy photosynthesis.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Article
Engineering, Environmental
Kalliopi Koutantou, Giulia Mazzotti, Philip Brunner, Clare Webster, Tobias Jonas
Summary: This study utilized UAV-borne LiDAR system to investigate snow cover dynamics in forests in the Swiss Alps, revealing differences in snow depth and depletion rate between north- and south-exposed slopes, as well as the impact of local forest structure on snow depth.
COLD REGIONS SCIENCE AND TECHNOLOGY
(2022)
Article
Agronomy
Daniel Kukenbrink, Fabian D. Schneider, Bernhard Schmid, Jean-Philippe Gastellu-Etchegorry, Michael E. Schaepman, Felix Morsdorf
Summary: The three-dimensional distribution of light within forest ecosystems plays a key role in species competition, coexistence, ecosystem functioning, productivity, and diversity. Recent advances in technology provide new insights into light distribution within forest canopies. Combining laser scanning and optical measurements, this study analyzes the impact of canopy structure and optical properties on light extinction in temperate and tropical forests. It is found that canopy structure drives light extinction, with tropical forests exhibiting larger 3D heterogeneity. The use of detailed 3D modeling is crucial for understanding light-related mechanisms affecting species in complex forest ecosystems.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Article
Water Resources
Jacob Staines, John W. Pomeroy
Summary: Vegetation structure is an important factor in shaping the spatial variation of snow accumulation under forest canopies. However, the fine-scale relationships between canopy density, snow interception, wind redistribution, and sub-canopy accumulation are poorly understood. This study analyzed forest structure and sub-canopy snow accumulation to assess the impact of snow-canopy interactions on spatial patterns of sub-canopy snow accumulation.
HYDROLOGICAL PROCESSES
(2023)
Article
Environmental Sciences
Bitam Ali, Feng Zhao, Zhenjiang Li, Qichao Zhao, Jiabei Gong, Lin Wang, Peng Tong, Yanhong Jiang, Wei Su, Yunfei Bao, Juan Li
Summary: The maturity and affordability of LiDAR sensors enable quick acquisition of 3D point cloud data for monitoring vegetation canopy traits, but there are few studies on reconstructing 3D structures and extracting fine-scale parameters from terrestrial LiDAR data, posing challenges in requiring large datasets for representation of canopy components.
Article
Chemistry, Analytical
Carlotta Ferrara, Nicola Puletti, Matteo Guasti, Roberto Scotti
Summary: This study used terrestrial and airborne laser scanning data to characterize the understory in a European beech and black pine forest in Italy. The results showed that upper understory density is associated with two specific airborne laser scanning metrics, while lower understory metrics are more related to one metric. Additionally, the study demonstrated the power of hand-held mobile TLS as a tool for measuring forest structural attributes and obtaining relevant ecological data.
Article
Forestry
Caden P. Chamberlain, Andrew J. Sanchez Meador, Andrea E. Thode
Summary: Accurate estimates of canopy base height (CBH) and canopy bulk density (CBD) are crucial for fire modeling. This study developed a method using airborne lidar data for estimating CBH and CBD, showing that airborne lidar produced more accurate estimates compared to traditional methods. The study also found that airborne lidar is more accurate at estimating CBH in unmanaged stands, while CBD estimates maintain similar accuracy regardless of management history.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Environmental Sciences
Maryam Poorazimy, Ghasem Ronoud, Xiaowei Yu, Ville Luoma, Juha Hyyppa, Ninni Saarinen, Ville Kankare, Mikko Vastaranta
Summary: This study investigates the feasibility of detecting species-specific individual tree crown growth using airborne laser scanning (ALS) measurements. The results show that ALS measurements are effective in detecting species-specific crown growth, with Scots pine exhibiting the highest growth.
Article
Marine & Freshwater Biology
Qiaosi Li, Timothy C. Bonebrake, Joseph R. Michalski, Frankie Kwan Kit Wong, Tung Fung
Summary: This study used multispectral Sentinel-2 images and airborne LiDAR Scanning datasets to investigate the effects of a super-typhoon and a moth pest on mangroves in Mai Po, Hong Kong. The results showed that moth larvae were more likely to damage leafy mangroves of Avicennia marina, and double-layered and single-layered short mangroves had better resistance to typhoons. NDVI recovered rapidly after disturbance, but significant changes in canopy structures were found from the ALS data.
ESTUARINE COASTAL AND SHELF SCIENCE
(2023)
Article
Forestry
Batistin Bour, Victor Danneyrolles, Yan Boucher, Richard A. Fournier, Luc Guindon
Summary: This study presents a method that combines a single airborne LiDAR acquisition and time since harvest maps to model height growth of post-logged black spruce-dominated forests. The results demonstrate the strong predictive power of the model in accurately predicting forest productivity with high spatial resolution, showing different forest growth patterns based on topographical variables.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Biodiversity Conservation
Langning Huo, Joachim Strengbom, Tomas Lundmark, Per Westerfelt, Eva Lindberg
Summary: In sustainable forest resource management, establishing forest conservation areas is crucial for maintaining forest biodiversity. However, assessing the conservation value of forests can be challenging due to their large and remote nature. This study explores the use of dense airborne laser scanning (ALS) data to estimate conservation values, specifically focusing on identifying different types of indicator trees.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Patrick D. Broxton, C. David Moeser, Adrian Harpold
Summary: Accurately modeling the effects of variable forest structure and change on snow distribution and persistence is critical, but most models simplify forest effects on snowpack mass and energy budgets. Coarse simulations often predict higher under-canopy radiation, faster snow ablation, and earlier snow disappearance compared to fine-scale simulations.
WATER RESOURCES RESEARCH
(2021)
Article
Meteorology & Atmospheric Sciences
Johanna Malle, Nick Rutter, Clare Webster, Giulia Mazzotti, Leanne Wake, Tobias Jonas
Summary: This study evaluated the point-scale simulations of CLM5 across different forest structures and solar angles at two climatically different locations, revealing that canopy structural shading of the snow surface exerted a primary control on Land Surface Albedo (LSA). The diurnal patterns of measured LSA showed strong effects of both azimuth and zenith angles, neither of which were adequately represented in simulations. In sparse forest environments, LSA were overestimated by up to 66%.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2021)
Article
Geography, Physical
Tristram D. L. Irvine-Fynn, Tom O. Holt, Timothy D. James, Mark W. Smith, Nick Rutter, Philip R. Porter, Andrew J. Hodson
Summary: In a warming Arctic, the increase in seasonal bare-ice extent due to rising glacier snowlines enhances the importance of turbulent energy fluxes for surface ablation and glacier mass balance. This study uses time-lapse photogrammetry to analyze the fine-scale supraglacial topography on a glacier in Svalbard. The results show that surface roughness is affected by supraglacial hydrology and temporal changes in albedo feedbacks, and the roughness parameter decreases and then increases following the exposure of bare-ice. The study also identifies the influence of hydrological drivers on plot-scale topography. This research provides an analytical framework for future studies on ice surface roughness and hydro-meteorological variables and aims to improve parameterizations of evolving bare-ice areas.
EARTH SURFACE PROCESSES AND LANDFORMS
(2022)
Article
Geochemistry & Geophysics
Emanuele Santi, Marco Brogioni, Marion Leduc-Leballeur, Giovanni Macelloni, Francesco Montomoli, Paolo Pampaloni, Juha Lemmetyinen, Juval Cohen, Helmut Rott, Thomas Nagler, Chris Derksen, Joshua King, Nick Rutter, Richard Essery, Cecile Menard, Melody Sandells, Michael Kern
Summary: This article presents the results of utilizing multifrequency synthetic aperture radar data within the framework of European Space Agency activities to retrieve snow information. The study assessed the capability of X- and Ku-bands SAR in retrieving snow parameters, with machine learning techniques, especially artificial neural networks, showing promising results. The research compared approaches based on experimental data and data simulated by dense medium radiative transfer, highlighting the efficiency of data-driven algorithms in estimating snow depth and snow water equivalent.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Amy Neuenschwander, Lori Magruder, Eric Guenther, Steven Hancock, Matt Purslow
Summary: This paper investigates the elevation measurements of the ICESat-2 satellite, focusing on the impact of atmospheric scattering and attenuation on radiometry and the differences in radiometry between day and night. The research finds that the radiometry characteristics of the ATLAS instrument vary among different forest types, with higher radiometry observed for weak beams. Additionally, the study observes lower radiometry for daytime acquisitions compared to nighttime acquisitions.
Article
Multidisciplinary Sciences
Steven Hancock, Ciara McGrath, Christopher Lowe, Ian Davenport, Iain Woodhouse
Summary: This paper discusses the use of airborne and spaceborne lidar technology for elevation measurement, addressing the cost and technological challenges of global mapping, and how technological developments can potentially reduce the cost of a global lidar system.
ROYAL SOCIETY OPEN SCIENCE
(2021)
Article
Water Resources
Julien Meloche, Alexandre Langlois, Nick Rutter, Donald McLennan, Alain Royer, Paul Billecocq, Serguei Ponomarenko
Summary: Increasing surface temperatures in the Arctic have reduced the extent and duration of annual snow cover, affecting polar ecosystems. Accurate monitoring of these ecosystems requires detailed information on snow cover properties at resolutions below 100 meters. In this study, a machine learning method using topographic parameters and the Random Forest algorithm was applied to an arctic landscape, providing predictions of snow depth distributions with good accuracy.
HYDROLOGICAL PROCESSES
(2022)
Article
Environmental Sciences
Johannes N. Hansen, Steven Hancock, Ludwig Prade, Gerald M. Bonner, Haochang Chen, Ian Davenport, Brynmor E. Jones, Matthew Purslow
Summary: This paper investigates the potential for using diode lasers as an alternative to solid-state lasers in satellite lidar applications. The authors assess whether the novel lidar modalities necessitated by lower peak powers of diode lasers can match the design performance of existing instruments. The results show that diode lasers have the opportunity to be used in spaceborne lidars, potentially allowing wider coverage through their higher efficiencies.
Article
Environmental Sciences
Heather Kropp, Michael M. Loranty, Nick Rutter, Christopher G. Fletcher, Chris Derksen, Lawrence Mudryk, Markus Todt
Summary: The timing and rate of spring snowmelt in northern high latitudes are important for the environment. Forests and grasslands are more conducive to snowmelt compared to other land cover types.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
K. C. Cushman, John Armston, Ralph Dubayah, Laura Duncanson, Steven Hancock, David Janik, Kamil Kral, Martin Krucek, David M. Minor, Hao Tang, James R. Kellner
Summary: In this study, the sensitivity of Global Ecosystem Dynamics Investigation (GEDI) data and aboveground biomass density (AGBD) predictions to leaf phenology was tested. The results suggest that, with consideration of model choice, GEDI data without considering leaf status can be used for AGBD prediction, which increases data availability and reduces sampling error in some forests.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Meteorology & Atmospheric Sciences
Nick Rutter, Richard Essery, Robert Baxter, Steven Hancock, Maya Horton, Brian Huntley, Tim Reid, John Woodward
Summary: Longwave radiation is the main energy source for snowmelt in forests. Research in Sweden and Finland found that downwelling longwave radiation is enhanced under forest canopies, even for sparse canopies and clear skies. Accurate estimation of canopy density is important for predicting this enhancement. Regression models using above-canopy longwave radiation and air temperature as predictors can effectively predict sub-canopy longwave radiation. The influence of above-canopy shortwave radiation is limited, suggesting that hot trees have minimal impact on longwave radiation. However, on calm, clear nights, the influence of cold trees is apparent.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2023)
Article
Geography, Physical
Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, Julia Boike
Summary: This study found that CLM5.0 overestimated snow thermal conductivity, leading to a cold bias in wintertime soil temperatures. Two different approaches were proposed to reduce this bias: alternative parameterisations and the application of a correction factor. Improving simulated snow properties and heat flux is important for influencing Arctic winter carbon fluxes and budgets.
Review
Geography, Physical
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, Xiaolan Xu
Summary: Seasonal snow cover plays a significant role in the Earth's climate and water supply, but its decline and the lack of global SWE estimates pose challenges to water resource management and other applications. This paper reviews the potential of X- and Ku-band SAR for global SWE monitoring and discusses the interdisciplinary approach needed for accurate estimation.
Article
Geosciences, Multidisciplinary
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehvilainen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, Michael Kern
Summary: This study introduces the airborne SAR data and coincident in situ information collected by the European Space Agency's SnowSAR instrument during campaigns in Finland, Austria, and Canada. The research aims to support the development of snow water equivalent retrieval techniques using SAR.
EARTH SYSTEM SCIENCE DATA
(2022)
Article
Geography, Physical
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, Evan J. Wilcox
Summary: Topography and vegetation have a significant impact on the sub-pixel variability of Arctic snowpack properties, which is not considered in current passive microwave satellite SWE retrievals. This study simplified the observed variability of snowpack properties and incorporated them into SWE retrieval schemes. The simulations showed that considering the variability of snow depth and density improves the accuracy of the models.
Article
Geography, Physical
J. Meloche, A. Royer, A. Langlois, N. Rutter, V. Sasseville
Summary: Research has shown that using Structure from Motion (SfM) techniques to measure soil roughness can improve and optimize emissivity models of frozen Arctic soil, thereby enhancing the accuracy of microwave applications.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2021)
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)