University of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122Investigating the Changes of Major Cultivated Area of Qazvin Plain by Means of Multi-Temporal Satellite ImagesInvestigating the Changes of Major Cultivated Area of Qazvin Plain by Means of Multi-Temporal Satellite Images124337610.22077/jdcr.2025.8743.1106FAMasoudSoltaniAssistant Professor, Department of Water Science and Engineering, Faculty of Agriculture and Natural Resources,Imam Khomeini International University, Qazvin, Iran0000-0001-6762-457XBaharehBahmanabadiPhD in Irrigation and Drainage, Department of Water Science and Engineering, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran0000-0003-2350-0684AbbasKavianiAssociate Professor, Department of Water Science and Engineering, Faculty of Agriculture and Natural Resources,Imam Khomeini International University, Qazvin, Iran0000-0002-6286-0618Journal Article20250113<strong>Abstract</strong><br />Accurate estimation of cultivated area is essential for agricultural planning and water resource management. The integration of remote sensing data and machine learning algorithms can enhance the accuracy of such estimations. This study evaluates the effectiveness of the Random Forest algorithm in estimating the dominant cultivated areas by integrating 10-meter resolution Sentinel-1 and Sentinel-2 data within the Qazvin Plain irrigation network. First, the Jeffries-Matusita separability test was conducted to assess the spectral discrimination of six land use classes (wheat-barley/maize, alfalfa, fallow, bare_land, and urban areas) during Winter and Spring cropping seasons. The results indicated high separability for some classes, while others exhibited spectral overlap. Subsequently, the combination of radar and optical data with the Random Forest algorithm significantly improved classification accuracy. In the Winter, the classification achieved a kappa coefficient of 0.99 and an overall accuracy of 99.69%, while in the spring cropping season, the kappa coefficient was 0.98, with an overall accuracy of 98.93%. An analysis of cultivated area trends for wheat-barley, maize, and alfalfa over the past decade revealed an increase in maize cultivation and a decline in alfalfa during the spring season. In the Winter, wheat and barley cultivation expanded, likely due to their relatively higher resilience to climatic fluctuations and economic incentives. The analysis of cultivated area changes within the irrigation network indicated a general shift towards increased maize cultivation, with a growing preference for spring cropping over Winter cropping.<strong>Abstract</strong><br />Accurate estimation of cultivated area is essential for agricultural planning and water resource management. The integration of remote sensing data and machine learning algorithms can enhance the accuracy of such estimations. This study evaluates the effectiveness of the Random Forest algorithm in estimating the dominant cultivated areas by integrating 10-meter resolution Sentinel-1 and Sentinel-2 data within the Qazvin Plain irrigation network. First, the Jeffries-Matusita separability test was conducted to assess the spectral discrimination of six land use classes (wheat-barley/maize, alfalfa, fallow, bare_land, and urban areas) during Winter and Spring cropping seasons. The results indicated high separability for some classes, while others exhibited spectral overlap. Subsequently, the combination of radar and optical data with the Random Forest algorithm significantly improved classification accuracy. In the Winter, the classification achieved a kappa coefficient of 0.99 and an overall accuracy of 99.69%, while in the spring cropping season, the kappa coefficient was 0.98, with an overall accuracy of 98.93%. An analysis of cultivated area trends for wheat-barley, maize, and alfalfa over the past decade revealed an increase in maize cultivation and a decline in alfalfa during the spring season. In the Winter, wheat and barley cultivation expanded, likely due to their relatively higher resilience to climatic fluctuations and economic incentives. The analysis of cultivated area changes within the irrigation network indicated a general shift towards increased maize cultivation, with a growing preference for spring cropping over Winter cropping.https://jdcr.birjand.ac.ir/article_3376_14e422f05b68cc0139988e128ee880df.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122Investigating the Effect of Water Deficit and Different Feeding Methods on Some Functional, Physiological and Qualitative Traits of Safflower (Carthamus Tinctorius L.)Investigating the Effect of Water Deficit and Different Feeding Methods on Some Functional, Physiological and Qualitative Traits of Safflower (Carthamus Tinctorius L.)2546335010.22077/jdcr.2025.8746.1107FAMohammadhadiArianPhD Student, Department of Agriculture, Bi.C., Islamic Azad University, Birjand, Iran.0009-0002-8518-3047MohammadjavadSeghataleslamiprofessor, Department of Agriculture, Bi.C., Islamic Azad University, Birjand, Iran.RezaBaradaranAssociate Professor, Department of Agriculture, Bi.C., Islamic Azad University, Birjand, Iran.MehdiEbrahimiAssistant Professor, Department of Optimization of Production and Processing of South Khorasan's Indigenous Medicinal Plants, ACECR of South Khorasan Province, Birjand, Iran.0000-0002-0047-333XJournal Article20250115Water deficit is one of the most important environmental deficites that affects the performance of many products by changing physiological and biochemical processes. for investigate the effect of nutrition methods and water deficit on the functional, physiological and qualitative traits of safllower, this research was carried out in the form of split plots based on a randomized complete block design in three replications and in two crop years of 2019-2020 and 2020-2021 in the research farm of Jahad Daneshgahi of birjand. Irrigation regime treatment includes two levels of full irrigation (100% water requirement) and water deficit (50% water requirement) as the main factor and considering the nutritional program. There were eight methods (control, NPK, humic acid (HA), fertilizing phosphate-2 (PB-2), NPK + HA, NPK + PB-2 , HA + PB-2.NPK+HA+PB-2).Water deficit decreased seed yield, number of bolls per plant, number of bolls per square meter, percentage of seed oil, number of seeds per boll, oil yield and weight of 1000 seeds, and increased the efficiency of water consumption for seed and oil production. Based on the results of the research, feeding increased functional traits and qualitative traits such as seed oil.Water deficit is one of the most important environmental deficites that affects the performance of many products by changing physiological and biochemical processes. for investigate the effect of nutrition methods and water deficit on the functional, physiological and qualitative traits of safllower, this research was carried out in the form of split plots based on a randomized complete block design in three replications and in two crop years of 2019-2020 and 2020-2021 in the research farm of Jahad Daneshgahi of birjand. Irrigation regime treatment includes two levels of full irrigation (100% water requirement) and water deficit (50% water requirement) as the main factor and considering the nutritional program. There were eight methods (control, NPK, humic acid (HA), fertilizing phosphate-2 (PB-2), NPK + HA, NPK + PB-2 , HA + PB-2.NPK+HA+PB-2).Water deficit decreased seed yield, number of bolls per plant, number of bolls per square meter, percentage of seed oil, number of seeds per boll, oil yield and weight of 1000 seeds, and increased the efficiency of water consumption for seed and oil production. Based on the results of the research, feeding increased functional traits and qualitative traits such as seed oil.https://jdcr.birjand.ac.ir/article_3350_b7ee0d0d4d5ef995aae0fc691e6d840d.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122Climate Change and Vegetation Cover in the Kahneh Watershed, Khorasan Razavi, Using Remote Sensing in the GEE EnvironmentClimate Change and Vegetation Cover in the Kahneh Watershed, Khorasan Razavi, Using Remote Sensing in the GEE Environment4762339910.22077/jdcr.2025.8922.1118FAMostafaDastoraniAssistant Professor, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University. Sabzevar, Iran.0000-0002-4271-0890MahdiZareiAssociate Professor, Research Center for Geographical Sciences and Social Studies, Hakim Sabzevari University, Sabzevar, Iran.MaliheQaderiEnvironmental Education Expert, Department of Environment of South Khorasan Province, Birjand, Iran.Journal Article20250210This study examines vegetation cover changes in the Kahneh watershed, over two periods: 2000–2012 and 2012–2024. As a semi-arid region, it is affected by climate change and precipitation fluctuations. The research assesses vegetation cover dynamics using NDVI, SPI, and monthly precipitation data within Google Earth Engine (GEE). NDVI data from satellite imagery was analyzed with SPI and monthly precipitation records. The study utilized GEE for large-scale remote sensing analysis. NDVI trends were examined across timeframes, and seasonal variations were assessed to determine the impact of precipitation fluctuations. SPI classified wet and dry years, linking precipitation anomalies with vegetation changes. NDVI values significantly increased in 2012–2024 compared to 2000–2012, indicating improved vegetation cover, especially in the later years. This improvement correlated with increased annual precipitation. However, SPI analysis revealed fewer wet years in 2012–2024, suggesting ongoing climate variability. Seasonal analysis showed vegetation cover improvements across all seasons, including dry periods, highlighting the positive effects of additional rainfall. The mean NDVI rose from 0.06 in 2000 to 0.10 in 2024, nearly doubling soil and vegetation improvement conditions. The study indicates that increased precipitation in 2012–2024 positively impacted vegetation cover in the Kahneh watershed. However, ongoing climate fluctuations and long-term climate change effects require further research. The study also highlights limitations in using only monthly data and emphasizes the need for integrating additional environmental factors for a more comprehensive analysis. This research provides insights into the effects of precipitation variability on semi-arid ecosystems, essential for sustainable land and water resource management.This study examines vegetation cover changes in the Kahneh watershed, over two periods: 2000–2012 and 2012–2024. As a semi-arid region, it is affected by climate change and precipitation fluctuations. The research assesses vegetation cover dynamics using NDVI, SPI, and monthly precipitation data within Google Earth Engine (GEE). NDVI data from satellite imagery was analyzed with SPI and monthly precipitation records. The study utilized GEE for large-scale remote sensing analysis. NDVI trends were examined across timeframes, and seasonal variations were assessed to determine the impact of precipitation fluctuations. SPI classified wet and dry years, linking precipitation anomalies with vegetation changes. NDVI values significantly increased in 2012–2024 compared to 2000–2012, indicating improved vegetation cover, especially in the later years. This improvement correlated with increased annual precipitation. However, SPI analysis revealed fewer wet years in 2012–2024, suggesting ongoing climate variability. Seasonal analysis showed vegetation cover improvements across all seasons, including dry periods, highlighting the positive effects of additional rainfall. The mean NDVI rose from 0.06 in 2000 to 0.10 in 2024, nearly doubling soil and vegetation improvement conditions. The study indicates that increased precipitation in 2012–2024 positively impacted vegetation cover in the Kahneh watershed. However, ongoing climate fluctuations and long-term climate change effects require further research. The study also highlights limitations in using only monthly data and emphasizes the need for integrating additional environmental factors for a more comprehensive analysis. This research provides insights into the effects of precipitation variability on semi-arid ecosystems, essential for sustainable land and water resource management.https://jdcr.birjand.ac.ir/article_3399_57f04bb2975420e3b4c73920c687cad7.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122Comparing the Performance of Gene Expression Programming Methods and Empirical Relationships in Predicting Daily Reference Evapotranspiration Across Different ClimatesComparing the Performance of Gene Expression Programming Methods and Empirical Relationships in Predicting Daily Reference Evapotranspiration Across Different Climates6380341910.22077/jdcr.2025.8966.1120FAُSamiraRahnamaGraduated with a PhD in Water Resources Engineering, Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran0000-0002-9256-8511FahimehKhadempourPh. D Student of Water Resources Engineering, Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, IranJournal Article20250216Evapotranspiration is one of the most important parameters, knowing it is essential for estimating plant water consumption and designing irrigation systems. The purpose of this research is to compare the performance of gene expression programming methods and empirical relationships in estimating daily reference evapotranspiration over a 20-year period (2001-2020) in three climates: arid (Birjand), Mediterranean (Gorgan), and very humid (Rasht). In order to compare the results of the gene expression algorithm in predicting reference evapotranspiration, 6 scenarios were defined according to the meteorological parameters affecting reference evapotranspiration. Also, in this research, empirical methods (Makkink, Pristly and Taylor, FAO Blaney Criddle, FAO Penman-Monteith, Hargreaves, Hargreaves- Samani, Irmak-Rs, and Irmak- Rn) were used to estimate daily reference evapotranspiration. Finally, the best model was selected based on the evaluation criteria RMSE, MAE, NSE, and R2. The results showed that in Birjand and Gorgan stations, scenario a provided a more favorable prediction due to considering the parameters of minimum temperature, maximum temperature, average air temperature, relative humidity, wind speed, sunshine hours, and reference evapotranspiration. At Rasht station, scenario b provided a more favorable prediction than other scenarios. Also, the Irmak-Rs method and the Hargreaves method, with a high R2 value, relatively good NSE, and lower RMSE and MAE values compared to other methods, can be a suitable alternative to the Penman-Monteith-FAO method on a daily scale in Mediterranean, very humid, and arid climates. Also, the Hargreaves- Samani method had the lowest accuracy (R2=0.5) in estimating reference evapotranspiration at all stations.Evapotranspiration is one of the most important parameters, knowing it is essential for estimating plant water consumption and designing irrigation systems. The purpose of this research is to compare the performance of gene expression programming methods and empirical relationships in estimating daily reference evapotranspiration over a 20-year period (2001-2020) in three climates: arid (Birjand), Mediterranean (Gorgan), and very humid (Rasht). In order to compare the results of the gene expression algorithm in predicting reference evapotranspiration, 6 scenarios were defined according to the meteorological parameters affecting reference evapotranspiration. Also, in this research, empirical methods (Makkink, Pristly and Taylor, FAO Blaney Criddle, FAO Penman-Monteith, Hargreaves, Hargreaves- Samani, Irmak-Rs, and Irmak- Rn) were used to estimate daily reference evapotranspiration. Finally, the best model was selected based on the evaluation criteria RMSE, MAE, NSE, and R2. The results showed that in Birjand and Gorgan stations, scenario a provided a more favorable prediction due to considering the parameters of minimum temperature, maximum temperature, average air temperature, relative humidity, wind speed, sunshine hours, and reference evapotranspiration. At Rasht station, scenario b provided a more favorable prediction than other scenarios. Also, the Irmak-Rs method and the Hargreaves method, with a high R2 value, relatively good NSE, and lower RMSE and MAE values compared to other methods, can be a suitable alternative to the Penman-Monteith-FAO method on a daily scale in Mediterranean, very humid, and arid climates. Also, the Hargreaves- Samani method had the lowest accuracy (R2=0.5) in estimating reference evapotranspiration at all stations.https://jdcr.birjand.ac.ir/article_3419_4a533591763dfa743a13affab1a85793.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122Evaluation of Tolerance to Drought in the End of Growing Season in Wheat Cultivars and Identification of High-Yielding GenotypesEvaluation of Tolerance to Drought in the End of Growing Season in Wheat Cultivars and Identification of High-Yielding Genotypes8196319810.22077/jdcr.2025.3198FABijanHaghighatiAssistant Professor of Soil and Water Research Department, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shahrekord, Iran0000-0001-9948-5957Journal Article20241127The drought stress significantly impacts the quantity and quality of wheat yield. To assess the tolerance of new wheat cultivars and lines to this stress, a split-plot experiment was conducted in a randomized complete block design with three replications over two years at the Chehartagh Research Station in Shahrekord. Treatments included three levels of irrigation cessation as main plots (full irrigation, irrigation cut off at flowering, and grain filling stages) and seven wheat genotypes as subplots (Mihan, Heydari, Pishgam, CD-93-9, CD-93-10, CD-91-12, and CD-92-6). Results showed that irrigation cut off significantly affected grain yield and vegetative characteristics at the 1% level. The highest grain yield of 10.26 tons per hectare was obtained under full irrigation conditions from the Mihan cultivar. The average grain yield under full irrigation, irrigation cessation at the grain filling stage, and irrigation cessation at the flowering stage was 8.74, 5.27, and 3.94 tons per hectare, respectively, indicating significant differences among treatments. Under irrigation cut of at the flowering stage, the genotype CD-93-10 exhibited the highest grain yield of 4.44 tons per hectare, significantly differing from other genotypes. Therefore, in the event of irrigation cessation or reduced water consumption during the final growth stages, this genotype demonstrated a 6 to 25% higher yield potential compared to other genotypes and is recommended for cultivation in such conditions.The drought stress significantly impacts the quantity and quality of wheat yield. To assess the tolerance of new wheat cultivars and lines to this stress, a split-plot experiment was conducted in a randomized complete block design with three replications over two years at the Chehartagh Research Station in Shahrekord. Treatments included three levels of irrigation cessation as main plots (full irrigation, irrigation cut off at flowering, and grain filling stages) and seven wheat genotypes as subplots (Mihan, Heydari, Pishgam, CD-93-9, CD-93-10, CD-91-12, and CD-92-6). Results showed that irrigation cut off significantly affected grain yield and vegetative characteristics at the 1% level. The highest grain yield of 10.26 tons per hectare was obtained under full irrigation conditions from the Mihan cultivar. The average grain yield under full irrigation, irrigation cessation at the grain filling stage, and irrigation cessation at the flowering stage was 8.74, 5.27, and 3.94 tons per hectare, respectively, indicating significant differences among treatments. Under irrigation cut of at the flowering stage, the genotype CD-93-10 exhibited the highest grain yield of 4.44 tons per hectare, significantly differing from other genotypes. Therefore, in the event of irrigation cessation or reduced water consumption during the final growth stages, this genotype demonstrated a 6 to 25% higher yield potential compared to other genotypes and is recommended for cultivation in such conditions.https://jdcr.birjand.ac.ir/article_3198_b08354f3688c4e4e8c52c207d7d5b8c3.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122Sensitivity Analysis of AquaCrop Input Parameters in Wheat Farms during Four Years (Case Study: Ahvaz And Shush Cities)Sensitivity Analysis of AquaCrop Input Parameters in Wheat Farms during Four Years (Case Study: Ahvaz And Shush Cities)97116339810.22077/jdcr.2025.8760.1108FAAdelBaviAssistant Professor
Faculty of engineering,ShohadayeHoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, DashteAzadegan, Iran.Journal Article20250116The AquaCrop model is one of the crop models for wheat yield simulation, which is used by many researchers around the world. This model is sensitive to the input parameters, and knowing the level of this sensitivity helps users to use it faster and more accurately. Considering that the sensitivity analysis of the AquaCrop model to the input parameters has so far been limited by the use of data from experimental pilots; not enough information is available to extend it to real conditions in farmers' fields. To solve this problem, the present research was conducted using data collected during four consecutive years (2020 to 2023) in Shush and Ahvaz cities, Iran. The results showed that the AquaCrop model has a high sensitivity to changes in normalized water productivity, harvest index and maximum crop coefficient for transpiration (0.2<Sp<1.0), medium sensitivity to crop growth canopy coefficient (0.05<Sp<0.2 ) and had a low sensitivity (Sp<0.05) to the crop decline canopy coefficient and the initial crop canopy coefficient. This sensitivity was constant to spatial changes (from Shush to Ahvaz) but variable to temporal changes (from 2020 to 22023). In fact, with the improvement of wheat yield during the studied years, the sensitivity of the AquaCrop model decreased.The AquaCrop model is one of the crop models for wheat yield simulation, which is used by many researchers around the world. This model is sensitive to the input parameters, and knowing the level of this sensitivity helps users to use it faster and more accurately. Considering that the sensitivity analysis of the AquaCrop model to the input parameters has so far been limited by the use of data from experimental pilots; not enough information is available to extend it to real conditions in farmers' fields. To solve this problem, the present research was conducted using data collected during four consecutive years (2020 to 2023) in Shush and Ahvaz cities, Iran. The results showed that the AquaCrop model has a high sensitivity to changes in normalized water productivity, harvest index and maximum crop coefficient for transpiration (0.2<Sp<1.0), medium sensitivity to crop growth canopy coefficient (0.05<Sp<0.2 ) and had a low sensitivity (Sp<0.05) to the crop decline canopy coefficient and the initial crop canopy coefficient. This sensitivity was constant to spatial changes (from Shush to Ahvaz) but variable to temporal changes (from 2020 to 22023). In fact, with the improvement of wheat yield during the studied years, the sensitivity of the AquaCrop model decreased.https://jdcr.birjand.ac.ir/article_3398_384babc3e7faa44cf1ca671b74499c3b.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122Investigating the Role of Vegetation and Old Trees in the Walls of Urban Streets on the Range and Thermal Comfort of Pedestrians.Investigating the Role of Vegetation and Old Trees in the Walls of Urban Streets on the Range and Thermal Comfort of Pedestrians.117140359110.22077/jdcr.2025.8907.1117FAKarenFatahiAssistant Professor, Department of Architecture, Ilam Branch, Islamic Azad University, Ilam, Iran.0000-0002-0451-6798Journal Article20250207This study compares the effect of trees on the thermal comfort of pedestrians in urban streets with and without trees. This study used a survey and field method to investigate the effect of removing old trees and vegetation (boxwood, grass, and flowering shrubs) on the thermal comfort of pedestrians in four streets of Ilam. The statistical population consisted of 384 people (96 people per street) who were selected by simple random sampling. Data were collected using the American ASHRAE-55 standard questionnaire for subjective assessment of thermal comfort and MIC98586 data logger tools for recording climatic variables, Fluke 975 Air Meter for recording CO₂ concentration values, and TES1326 laser thermometer for recording skin surface temperature. Then, the data were analyzed using Pearson correlation and multivariate linear regression in SPSS27 software to examine the relationship between climatic variables and thermal comfort. The findings showed that the mean and standard deviation of the thermal comfort status of pedestrians for the treeless streets of Taleghani and Samandari are 0.52 ± 0.049 and 1.67 ± 0.745, respectively, and for the tree-lined streets of Pasdaran West and Pasdaran East-Middle, they are 1.43 ± 0.125 and 1.54 ± 0.325, respectively. The results showed that the presence of vegetation and trees in the walls of urban streets, due to their stable environmental reactivity, plays an important role in reducing the thermal crisis and the city's thermal island and preventing changes in thermal comfort status in urban microclimates.This study compares the effect of trees on the thermal comfort of pedestrians in urban streets with and without trees. This study used a survey and field method to investigate the effect of removing old trees and vegetation (boxwood, grass, and flowering shrubs) on the thermal comfort of pedestrians in four streets of Ilam. The statistical population consisted of 384 people (96 people per street) who were selected by simple random sampling. Data were collected using the American ASHRAE-55 standard questionnaire for subjective assessment of thermal comfort and MIC98586 data logger tools for recording climatic variables, Fluke 975 Air Meter for recording CO₂ concentration values, and TES1326 laser thermometer for recording skin surface temperature. Then, the data were analyzed using Pearson correlation and multivariate linear regression in SPSS27 software to examine the relationship between climatic variables and thermal comfort. The findings showed that the mean and standard deviation of the thermal comfort status of pedestrians for the treeless streets of Taleghani and Samandari are 0.52 ± 0.049 and 1.67 ± 0.745, respectively, and for the tree-lined streets of Pasdaran West and Pasdaran East-Middle, they are 1.43 ± 0.125 and 1.54 ± 0.325, respectively. The results showed that the presence of vegetation and trees in the walls of urban streets, due to their stable environmental reactivity, plays an important role in reducing the thermal crisis and the city's thermal island and preventing changes in thermal comfort status in urban microclimates.https://jdcr.birjand.ac.ir/article_3591_9001ca429212011f4a4fda6c778cc318.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60763320251122A Review of Different Approaches to Bottom-Up Monitoring of MethaneA Review of Different Approaches to Bottom-Up Monitoring of Methane141172343110.22077/jdcr.2025.8956.1119FAAliRahimiPhD Student of Climatology, Tarbiat Modares University, Tehran, Iran.ManuchehrFarajzadehProfessor of Climatology, Department of Physical Geography, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran.0000-0002-4916-9304YousefGhavidel RahimiProfessor of Climatology, Department of Physical Geography, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran.0000-0003-1929-155XJournal Article20250215Among the greenhouse gases in the earth's atmosphere, methane is the most important cause of global warming caused by human activities, after carbon dioxide. Almost three-quarters of methane greenhouse gas emissions are of human origin, and for this reason, it is very important to continue measuring and recording its emission values with two approaches of bottom-up and top-down monitoring. In the research conducted in the field of methane greenhouse gas monitoring, the bottom-up monitoring approach is of great importance as a vital and necessary tool to identify and accurately measure the emission of this gas. In cases where researchers need accurate and local data, using a bottom-up monitoring approach can lead to actions to reduce methane emissions and help improve environmental management. The bottom-up monitoring approach of methane greenhouse gas is categorized based on methods such as direct or indirect measurements at the emission source location, types of detection sensors, laboratory studies, and sampling methods. Each of these methods has its own strengths and weaknesses, and usually, in order to choose one or more methods, it is necessary to consider conditions such as the geographical environment, the purpose of the research, and the degree of accuracy required. Bottom-up monitoring approach methods together with top-down monitoring approach methods provide an effective combination for comprehensive and complete monitoring of methane greenhouse gas and can play a key role in formulating environmental policies and emission reduction measures.Among the greenhouse gases in the earth's atmosphere, methane is the most important cause of global warming caused by human activities, after carbon dioxide. Almost three-quarters of methane greenhouse gas emissions are of human origin, and for this reason, it is very important to continue measuring and recording its emission values with two approaches of bottom-up and top-down monitoring. In the research conducted in the field of methane greenhouse gas monitoring, the bottom-up monitoring approach is of great importance as a vital and necessary tool to identify and accurately measure the emission of this gas. In cases where researchers need accurate and local data, using a bottom-up monitoring approach can lead to actions to reduce methane emissions and help improve environmental management. The bottom-up monitoring approach of methane greenhouse gas is categorized based on methods such as direct or indirect measurements at the emission source location, types of detection sensors, laboratory studies, and sampling methods. Each of these methods has its own strengths and weaknesses, and usually, in order to choose one or more methods, it is necessary to consider conditions such as the geographical environment, the purpose of the research, and the degree of accuracy required. Bottom-up monitoring approach methods together with top-down monitoring approach methods provide an effective combination for comprehensive and complete monitoring of methane greenhouse gas and can play a key role in formulating environmental policies and emission reduction measures.https://jdcr.birjand.ac.ir/article_3431_84c2d4860a0fc27bcf854c444fb8b400.pdf