Forest Meteorology Research Articles

A bibliometric analysis of the literature on crop yield prediction: insights from previous findings and prospects for future research.

This research presents a bibliometric analysis of articles predicting crop yield using machine learning methods. While several systematic review articles exist, a comprehensive bibliometric analysis illustrating the knowledge structure and research trends, along with collaboration networks among authors, institutions, and countries in this field, has not been conducted. The study focused on 826 articles published over a 32-year period (1992 to 2023) and revealed a significant increase in publications, particularly in recent years. Zhang Zhao from China authored the majority of articles, while the highest number of citations was associated with articles by Zhu Yan and Lobell. Leading countries in article publications are the USA, China, India, Germany, Australia, and Canada, showing strong interconnections in citing each other's research. The Chinese Academy of Sciences and the US Department of Agriculture are the institutions with the highest number of articles and citations in this domain. The journals Agricultural and Forest Meteorology and Remote Sensing are recognized as top ranking journals in this field (Q1). Based on co-occurrence analysis, three main thematic domains were identified: weather and crop yield prediction, plant growth simulation models, and crop yield prediction using remote sensing data. The research suggests a focus on variables such as disease, pests, insects, and soil salinity when predicting yield. Additionally, greater attention should be given to discussions on food security and crop yield, especially in developing countries.

AFM Special Issue Summary - Integrating Surface Flux with Boundary Layer Measurements

To help bridge science topics related to land-atmosphere interactions, we organized a virtual special issue in this journal (Agricultural and Forest Meteorology [AFM]) entitled, “Land-Atmosphere Interactions: Integrating Surface Flux with Boundary Layer Measurements.” The motivation for the special issue was driven by existing disciplinary barriers between research areas that all address land-atmosphere interactions. In particular, it addressed research silos between those who study features of the land surface, surface fluxes (including water, energy, and trace gases), atmospheric boundary layer growth and thermodynamics, and atmospheric composition and aerosols. The special issue sought to bring these communities together to integrate multiple observations across the soil-vegetation-atmosphere continuum with the aim of 1) improving broader understanding of land-atmosphere interactions, feedbacks, and coupling, 2) fostering new collaborations between atmospheric and surface flux scientists, and 3) identifying new paths for integrative research. Here, we provide an overview and synthesis of the special issue.

Meteorological history of low-forest-greenness events in Europe in 2002–2022

Abstract. Forest dieback in Europe has recently intensified and has become more extensive. This dieback is strongly influenced by meteorological variations of temperature, T2m, and precipitation, P, and can be monitored with forest greenness. This study quantitatively investigates the 3-year meteorological history preceding events of reduced forest greenness in Europe's temperate and Mediterranean biome with a systematic approach. A specific focus lies in the timing of unusually persistent and unusually strong anomalies of T2m and P, as well as their relation to synoptic weather systems. A pragmatic approach based on remote sensing observations of the normalized difference vegetation index (NDVI) serves to identify low-forest-NDVI events at the 50 km scale in Europe in June to August 2002–2022. We quantify the impact of the hottest summer on record in Europe in 2022, which, according to our criteria, negatively affected 37 % of temperate and Mediterranean forest regions, and thereby reduced forest greenness more extensively than any other summer in 2002–2022. The low-NDVI events occurred in particularly dry and hot summers, but their meteorological histories also featured significant anomalies further in the past, with clear differences between the temperate and Mediterranean biome. A key feature is the anomalous accumulation of dry periods (i.e., periods with a P deficit) over the preceding 26 and 34 months in the temperate and Mediterranean biome, respectively. In the temperate biome only, T2m was anomalously persistent during almost the same 26-month period and featured distinctive peaks late in the past three growing seasons. While anomalously strong hot–dry conditions were characteristic of temperate low-NDVI events already in the previous summer, we find hardly any other systematic meteorological precursor in the Mediterranean prior to the event year. The identified dry periods went along with reduced cyclone activity in the Mediterranean and positive anticyclone frequency in the temperate biome. The occurrence of these two weather systems is locally more nuanced, showing, e.g., consistently increased and decreased cyclone frequency over western and northern Europe, respectively, in all event summers. Finally, the systematic meteorological histories are useful to test whether locally observed meteorological impacts, e.g., structural overshoot, systematically influenced the investigated events. In summary, systematic investigations of the multi-annual meteorological history provided clear evidence of how surface weather and synoptic-scale weather systems over up to 3 years can negatively impact European forest greenness. The observation of the record-extensive low-NDVI event in the summer of 2022 underlines that understanding the forest–meteorology interaction is of particular relevance for forest dieback in a changing climate.

On the Treatment of Soil Water Stress in GCM Simulations of Vegetation Physiology

Current land surface schemes in weather and climate models make use of the so-called coupled photosynthesis–stomatal conductance (A–gs) models of plant function to determine the surface fluxes that govern the terrestrial energy, water and carbon budgets. Plant physiology is controlled by many environmental factors, and a number of complex feedbacks are involved, but soil moisture control on root water uptake is primary, particularly in sub-tropical to temperate ecosystems. Land surface models represent plant water stress in different ways, but most implement a water stress factor, β, which ranges linearly (more recently also curvilinearly) between β = 1 for unstressed vegetation and β = 0 at the wilting point, expressed in terms of volumetric water content (θ). β is most commonly used to either limit A or gs, and hence carbon and water fluxes, and a pertinent research question is whether these treatments are in fact interchangeable. Following Egea et al. (Agricultural and Forest Meteorology, 2011, 151 (10), 1,370–1,384) and Verhoef et al. (Agricultural and Forest Meteorology, 2014, 191, 22–32), we have implemented new β treatments, reflecting higher levels of biophysical complexity in a state-of-the-art LSM, Joint UK Land Environment Simulator, by allowing root zone soil moisture to limit plant function non-linearly and via individual routes (carbon assimilation, stomatal conductance, or mesophyll conductance) as well as any (non-linear) combinations thereof. The treatment of β does matter to the prediction of water and carbon fluxes: this study demonstrates that it represents a key structural uncertainty in contemporary LSMs, in terms of predictions of gross primary productivity, energy fluxes and soil moisture evolution, both in terms of climate means and response to a number of European droughts, including the 2003 heat wave. Treatments allowing ß to act on vegetation fluxes via stomatal and mesophyll routes are able to simulate the spatiotemporal variability in water use efficiency with higher fidelity during the growing season; they also support a broader range of ecosystem responses, e.g., those observed in regions that are radiation limited or water limited. We conclude that current practice in weather and climate modelling is inconsistent, as well as too simplistic, failing to credibly simulate vegetation response to soil water stress across the typical range of variability that is encountered for current European weather and climate conditions, including extremes of land surface temperature and soil moisture drought. A generalized approach performs better in current climate conditions and promises to be, based on responses to recently observed extremes, more trustworthy for predicting the impacts of climate change.

Trend and research status of agronomy based on the Essential Science Indicators during 2009–2019

AbstractBased on the Essential Science Indicators (ESI) database, this study analyzed 734 top papers in the subject category of Agronomy from 2009 to 2019, which include 730 highly cited papers and seven hot papers in the field. All papers written in English, were from 3,540 authors; 1,225 organizations; and 91 countries/territories, published in 47 journals and book series in the field of Agronomy. The journals with the highest impact factor (IF) were Industrial Crops and Products, Plant and Soil, Agricultural and Forest Meteorology, Pest Management Science, and Field Crops Research. The countries and regions with the highest IF were United States, People's Republic of China, France, Germany, and Australia. The organizations with the highest average IF were INRA, University of Western Australia, Chinese Academy of Science, China Agriculture University, and University of California‐Davis. This work is useful for students identifying graduate schools and researchers selecting journals.

Новый подход к оценке площади поверхности хвои пихты сибирской

Новый подход к оценке площади поверхности хвои пихты сибирской

Application of data mining and machine learning in management accounting information system

ABSTRACT In the traditional management accounting information processing method, the method used to solve the problem is often fixed due to excessive assumptions. In order to improve its operating efficiency, combined with artificial intelligence information technology, this paper uses data mining algorithms to conduct data acquisition and rule exploration. Moreover, this paper uses statistics, machine learning and other techniques to analyze the correlation between attribute values and transform data into knowledge needed for decision-making. In addition, this paper combines machine learning algorithms to build an intelligent management accounting information system and realizes the close connection between corporate finance and business, which helps to form a closed-loop management between financial analysis, risk management, performance management, and decision-making. Finally, this paper designs experiments to verify the performance of the model. The research results show that the system constructed in this paper satisfies the intelligent demand of accounting information. REFERENCES [1] Jie Cai, Jiawei Luo, Shulin Wang, and Sheng Yang. Feature selection in machine learning: A new perspective. Neurocomputing, 300:70–79, 2018. [2] J. N. Goetz, A Brenning, H Petschko, and P. Leopold. Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling. Computers and Geosciences, 81:1–11, 2015. [3] Hamid Darabi, Bahram Choubin, Omid Rahmati, Ali Torabi Haghighi, Biswajeet Pradhan, and Bjorn Klove. Urban flood risk mapping using the GARP and QUEST models: A comparative study of machine learning techniques. Journal of Hydrology, 569:142–154, 2019. [4] Alvin Rajkomar, Jeffrey Dean, and Isaac Kohane. Machine learning in medicine. England Journal of Medicine, 380(14):1347–58, apr 2019. [5] Yang Xin, Lingshuang Kong, Zhi Liu, Yuling Chen, Yanmiao Li, Hongliang Zhu, Mingcheng Gao, Haixia Hou, and Chunhua Wang. Machine Learning and Deep Learning Methods for Cybersecurity. IEEE Access, 6:35365–35381, 2018. [6] Logan Ward, Ankit Agrawal, Alok Choudhary, and Christopher Wolverton. A general-purpose machinelearning framework for predicting properties of inorganic materials. npj Computational Materials, 2, 2016. [7] Puyu Feng, Bin Wang, De Li Liu, Cathy Waters, and Qiang Yu. Incorporating machine learning with biophysical model can improve the evaluation of climate extremes impacts on wheat yield in south-eastern Australia. Agricultural and Forest Meteorology, 275:100–113, 2019. [8] Konstantina Kourou, Themis P. Exarchos, Konstantinos P. Exarchos, Michalis V. Karamouzis, and DimitriosI. Fotiadis. Machine learning applications in cancer prognosis and prediction, 2015. [9] Saleema Amershi, Maya Cakmak, W. Bradley Knox, and Todd Kulesza. Power to the people: The role of humans in interactive machine learning. AI Magazine, 35(4):105–120, 2014. [10] V Rodriguez-Galiano, M. Sanchez-Castillo, M. Chica- Olmo, and M. Chica-Rivas. Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines. Ore Geology Reviews, 71:804–818, 2015. [11] ConnorW Coley, Regina Barzilay, Tommi S Jaakkola, William H Green, and Klavs F Jensen. Prediction of Organic Reaction Outcomes Using Machine Learning. ACS Central Science, 3(5):434–443, may 2017. [12] Aritra Chowdhury, Elizabeth Kautz, Bulent Yener, and Daniel Lewis. Image driven machine learning methods for microstructure recognition. Computational MaterialsScience, 123:176–187, 2016.

Comments on “Large-scale afforestation significantly increases permanent surface water in China's vegetation restoration regions” by Zeng, Y., Yang, X., Fang, N., & Shi, Z. (2020). Agricultural and Forest Meteorology, 290, 108001

The paper “Large-scale afforestation significantly increases permanent surface water in China's vegetation restoration regions, Agricultural and Forest Meteorology, Volume 290, 15 August 2020, 108001” by Zeng et al. (2020) finds that northern China is greening up and that “vegetation cover is an important factor in controlling permanent water changes”. They suggest that afforestation partially caused the increase in surface water areas due to the “significant positive correlations between forest covers and surface water area”. The authors suggest that, except precipitation, “climatic factors were not the main factor influencing permanent water”. They attribute the increase in area of surface waterbody to the increase in dams, precipitation rise, and afforestation. This commentary aims at clarifying concepts of afforestation-water yield-river flow relations and offers an alternative explanation of the observed expansion of surface water areas in northern China. Using a simple water balance-based approach, we conduct a back-of-envelope calculation and show that afforestation and ‘greening up’ are not likely to cause an increase in water yield and surface water storage. We argue that the detected rise of permanent surface water changes in the study regions is a result of hydraulic infrastructure construction, urbanization, and increase in precipitation, perhaps not vegetation recovery from afforestation. We believe that large-scale afforestation is not likely to increase surface water resources in northern China as implied in Zeng et al (2020). Future process-based studies are needed to understand the sources of the local precipitation and the effects of revegetation on precipitation, soil improvement, and water yield.

Rain-induced bioecological resuspension of radiocaesium in a polluted forest in Japan

It is the conventional understanding that rain removes aerosols from the atmosphere. However, the question of whether rain plays a role in releasing aerosols to the atmosphere has recently been posed by several researchers. In the present study, we show additional evidence for rain-induced aerosol emissions in a forest environment: the occurrence of radiocaesium-bearing aerosols in a Japanese forest due to rain. We carried out general radioactive aerosol observations in a typical mountainous village area within the exclusion zone in Fukushima Prefecture to determine the impacts and major drivers of the resuspension of radiocaesium originating from the nuclear accident in March 2011. We also conducted sampling according to the weather (with and without rain conditions) in a forest to clarify the sources of atmospheric radiocaesium in the polluted forest. We found that rain induces an increase in radiocaesium in the air in forests. With further investigations, we confirmed that the fungal spore sources of resuspended radiocaesium seemed to differ between rainy weather and nonrainy weather. Larger fungal particles (possibly macroconidia) are emitted during rainy conditions than during nonrainy weather, suggesting that splash generation by rain droplets is the major mechanism of the suspension of radiocaesium-bearing mould-like fungi. The present findings indicate that radiocaesium could be used as a tracer in such research fields as forest ecology, meteorology, climatology, public health and agriculture, in which fungal spores have significance.

Composition and Classification of Tree Species in a Degraded Tropical Humid Rainforest in Southwest Nigeria

Tree species information is essential for forest studies such as forest meteorology, botany and ecology, and across the relevant fields new techniques efficient for classifying tree species are desperately in demand. This study assessed tree species composition and classification in a degraded tropical rainforest in Southwest Nigeria. Data was collected from the Olukayode compartment of the study area of size 2 ha. Eight (8) Temporary sample plots of size 50 m x 50 m was laid using systematic line transect at 100 m intervals in the compartment. Hierarchical clustering in SPSS was used to find clusters of patterns in the measurement space. Tree species such as; Eucalyptus cameldulensis, Eucalyptus tereticornis, Khaya ivorensis, Khaya senegalensis,Nauclea diderichi, Terminalia randii, and Terminalia superba with a total frequency of 60 were identified, belonging to 3 different families. At similarity 5.0 from the dendrogram using ward linkage, samples 48 - 6 formed the first cluster, samples 28 - 9 constituted the second cluster while samples 20 - 13 constituted the third cluster. From the dendrogram using centroid linkage, at similarity 5.0, samples 59 - 7 formed the first cluster, samples 32 - 31 constituted the second cluster, and samples 8 - 28 formed the third cluster while the fourth cluster combined samples 17 - 21 which is a combination of trees from the three families. Histogram was used to show the diameter at breast height and total height distribution.

Characteristics of high‐impact agronomic journals

AbstractAgronomy journals form a core part of the process of scholarly communication and scientific research in the agronomic field. Determining the key features of high‐impact agronomic journals will be a central component for identifying the disciplinary development in the field of agronomy. In this study, we conducted a bibliometric study to fill this knowledge gap based on 64,703 articles published in 18 main agronomy journals since 1948 derived from the Scopus database. Our main findings were that (a) over 20% of publications in Advances in Agronomy and Agricultural and Forest Meteorology received more than 50 citations; (b) authors from the United States, China, the United Kingdom, Germany, and Australia published the most articles in these journals, comprising 22.4, 11.5, 10.7, 8.7, and 8.0% of the total number of publications, respectively; and (c) journals published in a given country had a greater number of papers published by authors of that country than by authors of other countries. Furthermore, three clusters for these 18 journals were identified that included the topics of agronomy, interactions between agronomy and soil sciences, and interactions between agronomy and plant sciences. The results of this study provide valuable insights regarding the current state of and future development trends in agronomic journals.

Conversion factors and general equations applied in agricultural and forest meteorology

Scientific communication in agricultural and forest meteorology requires a correct conversion of units and the adequate use of equations. In general, most of conversion and equations are found separately in a specific book, paper or document. Thus, here we propose a single document with conversion units of solar radiation, evapotranspiration, resource use efficiency, carbon balance, ecophysiology, trace gases and water; and general equations: Penman-Monteith, canopy conductance, decoupling factor and Bowen ratio. This document has a lot of value for teaching, for scientists and as a quick reference.

Understanding the interactions between wind and trees: an introduction to the IUFRO 8th Wind and Trees Conference (2017)

AbstractThis paper discusses the advance in our understanding of the interaction between wind and trees over the last 25 years. It does this by comparing papers in this special issue of Forestry and a companion volume in Agricultural and Forest Meteorology, based on work presented at the 8th IUFRO Wind and Trees Conference in 2017, with papers published in book format after the 1st IUFRO Wind and Trees Conference in 1993. The analysis is divided into sections on ‘airflow and tree mechanics’, ‘forest management and ecology’, ‘tree adaptation and acclimation’ and ‘modelling and statistical techniques’. It is clear that in the last 25 years large advances have been made in our understanding of airflow and turbulence within and above forest canopies and the wind flow and wind loading around and on individual trees. There have also been important developments in the mechanistic and statistical modelling of wind damage risk to forests. Much of the progress has been aided by the enormous advances in measurement systems, computer power and modelling techniques. Furthermore, this knowledge is beginning to influence the approach to temperate and boreal forest management and the development of systems to mitigate the risk of wind damage. At the same time there has been a growing awareness of the ecological impact of wind in many forests around the world, including tropical forests. However, other areas of the effect of wind on trees have progressed much less in the last 25 years. This includes the process of fatiguing in the root-soil system, both during individual storms and over longer periods, and which is known to be a critical factor in the process of windthrow. In addition the exact nature of damage propagation within forests during a storm, and then in subsequent storms, has received relatively little attention although new studies using advanced computational methods are making advances. Of particular relevance, and despite the known critical importance of tree acclimation to the wind, there have been very few studies in the last 25 years on wind acclimation in full-size trees. This is an area of enormous importance in understanding how resistance to the wind varies for different species and between areas with different wind climates. In summary, overall much has been learnt since the 1st Wind and Trees conference but there remain many intriguing and exciting challenges ahead for this multi-disciplinary subject.

Diversity in geoscience: Participation, behaviour, and the division of scientific labour at a Canadian geoscience conference

Effective policies promoting diversity in geoscience require understanding of how the values and practices of the community support the inclusion of different social groups. As sites of knowledge exchange and professional development, academic conferences are important culturing institutions that can alleviate or reproduce barriers to diversity in geoscience. This study examines diversity at a 2017 geoscience conference, the joint Canadian Geophysical Union and Canadian Society of Agricultural and Forest Meteorology annual meeting, through observation of participation, presentation content, and behaviour in conference sessions. Across 256 observed presentations, women constituted 28% of speakers, whereas women of colour made up only 5%. Participation rates differed between disciplinary sections, with the most populous sessions (Hydrology and Earth Surface) having the lowest percentage of women. Examination of presentation content reveals that the methods and scholarly contributions of both women and people of colour differed from the majority, suggesting an intellectual division of labour in geoscience. Examination of audience behaviours between presenters reveals how a “chilly climate” can be experienced by women and other marginalized demographics in conferences. We argue that there is more to be done than simply increasing numbers of women or other minorities in geoscientific spaces, and we suggest pathways to making geoscience a more inclusive and democratic pursuit.

Agrometeorology in Croatia

ABSTRACTMeteorological and Hydrological Service was established 70 years ago and agrometeorological activities (soil temperature measurements and phenological observations) started in 1951. Scientific research is divided into an agricultural meteorology, forest meteorology and plant phenology. The basic purpose of research is the impact of regional climate change on the crop production, on the phenological stages of different plants as forest trees and shrubs, fruit-trees, olive-trees, grapevine and maize, and on the potential wildfire risk. In the operational tasks short-range and medium-range forecasts have been produced for TV and internet since 2004, radio since 1990 and specialized journals since 1988. For further development of Croatian agrometeorology, future plans are using monthly and seasonal forecasts for prediction of the development of yield of major agricultural crops, for irrigation purposes, as well as for potential risk of wildfires and applying satellite data and nowcasting for warning purposes in agriculture and in forest protection against fire.

Raising New Orleans: Historical Analogs and Future Environmental Risks

Raising New Orleans: Historical Analogs and Future Environmental Risks

An evaluation of forestry journals using bibliometric indices

The increasing number of scientific journals, especially over the last 20 years, created the need for methodologies based on simple metrics, to accurately capture the “quality” of those journals and their impact on the scientific community. Especially in the case of journals from the field of forestry, relatively little work has been conducted on providing valid journal classifications. In this paper we attempt to assess the impact of journals from this field in terms of bibliometric data. In addition to the already proposed metrics (complementary to the journal h-index), we also apply a new measure to rank journals, that provides a more balanced evaluation of the journal performance, by adjusting for various biases affecting the h-index. We examined the relationships between various bibliometric indicators proposed for assessing the journal impact and wo found high correlations between most indices, with only few exceptions. According to citation analysis, Canadian Journal of Forest Research, Journal of Vegetation Science, Forest Science, Tree Physiology, International Journal of Wildland Fire, Holzforschung, Trees-Structure and Function, Silva Fennica, Agricultural and Forest Meteorology and Wood and Fiber Science are the top forestry journals. These publish articles related to all the domains of forestry science. More specialized journals are also included, dealing with specific issues of scientific interest and also of major importance to the scientific community.

Tree species classification based on explicit tree structure feature parameters derived from static terrestrial laser scanning data

Tree species information is essential for forest studies such as forest meteorology, botany and ecology, and across the relevant fields new techniques efficient for classifying tree species are desperately demanded. For this requirement, the state-of-the-art remote sensing technology of static terrestrial laser scanning (TLS) shows the potential of handling it, since TLS can represent tree structures in details. However, the literature review suggests that the endeavors of introducing TLS into tree species classification are still in shortage. Aimed at this technical gap, this study attempted TLS for distinguishing four typical boreal tree species, i.e. Norway spruce (Picea abies), Scots pine (Pinus sylvestris), European aspen (Populus tremula) and pedunculate oak (Quercus robur). After a theoretical comparison of the generic mechanisms of TLS- and airborne laser scanning (ALS)-based forest mapping, explicit tree structure (ETS) feature parameters, rather than conventional ALS-derived statistical-sense feature parameters, were proposed and derived from TLS point clouds. Then, based on a support-vector-machine (SVM) classifier, the specific classification was operated in a leave-one-out-for-cross-validation (LOOCV) mode. Tests indicated that the proposed TLS-based ETS feature parameters and the used classification algorithm can be validated for implementing the task of classifying the four tree species (the maximum total accuracy reaches 90.00% and the robust total accuracy reaches 77.5%). Overall, as a leading endeavor, this study has developed a procedural frame for TLS-based tree species classification.

복잡지형의 온대산림에서 에디 공분산으로 관측된 CO2플럭스의 야간 자료 보정에 관하여

Nighttime correction of CO2 flux is one of the most important and challenging tasks in eddy covariance measurements over a complex mountainous terrain. In this study, we have scrutinized the quality and the credibility of the CO2 flux datasets which were produced by employing three different methods of nighttime correction, i.e., (1) friction velocity (u) correction, (2) light response curve (LRC) correction, and (3) advection-based van Gorsel (VG) correction. The whole year datasets used in our analysis were collected at the two KoFlux tower sites (i.e., GDK deciduous forest site at the upper hill and GCK coniferous forest site at the lower hill) located in the valley of Gwangneung National Arboretum in central Korea. The resultant magnitudes and patterns of ecosystem respiration (RE), gross primary productivity (GPP), and net ecosystem exchange (NEE) of CO2 showed marked differences among the datasets produced with three different correction methods, which were also site-specific. The examination from micrometeorological and ecological perspectives suggests that the major cause of some inconsistency seems to be associated with the advection of CO2 along the sloping terrain and the inappropriate selection of the correction data that might have been * Corresponding Author : Joon Kim (joon@snu.ac.kr) 234 Korean Journal of Agricultural and Forest Meteorology, Vol. 16, No. 3 already affected by advective flows. The comparison with the results from other studies indicated that the overall characteristics of the corrected CO2 fluxes at GDK and GCK (except those with LRC correction) were well within the ranges reported in the literature for various ecosystems in East Asia in similar latitudes. However, our study also implies that there will be always a room for further improvement in the present datasets. Therefore, caution must be exercised for the data users in order to properly use the updated version of datasets through transparent, open and participatory communication with data producers.

Retracted: Comparative Evaluation of Radiation-Based Methods for Estimation of Potential Evapotranspiration

AbstractEvapotranspiration has a major role in agricultural and forest meteorology researches, hydrological cycle, irrigation scheduling, and water resources management. There are many methods to estimate the potential evapotranspiration including mass transfer, radiation, temperature, and pan evaporation-based methods. The present study aims to compare radiation-based methods to determine the best method under different weather conditions. The results discussed in this paper are from the data collected in the study area, but the method can be used in other similar regions. For this purpose, weather data was collected from 181 synoptic stations in 31 provinces of Iran. The potential evapotranspiration was estimated using 22 radiation-based methods and compared with the Food and Agriculture Organization of the United Nations (FAO) Penman-Monteith method. The results show that the Stephens method estimates the potential evapotranspiration better than other methods for provinces of Iran. However, the values ...