BACKGROUND AND OBJECTIVES: Oil palm is one of the crops that has an essential role in Indonesia's engineering field. This condition has led to oil palm plantation intensification, which has been extensive to deforestation in Indonesia, including Jambi province. The main aim of this investigation is to evaluate deforestation and land change affected by oil palm expansion conducted by smallholders, which influences environmental change using remote sensing combined with a geographic information system approach. This study utilizes the change of oil Palm in spatial-temporal (spatial and temporal) in Jambi province related to land change and environmental impacts.METHODS: This research uses data from Landsat 8 satellite imagery. The land cover classification was done using the Maximum Likelihood approach, while the overlay method was used for land change ANALYSIS. Accuracy assessment of classification results uses a confusion matrix taking into account overall accuracy and Kappa Hat. Within the field observation, the validation class is the oil palm class, using documentation and plotting using the global positioning system, and other classes are validated using the Region of Interest collected through Google Earth. This research uses Aviation Reconnaissance Coverage Geographic Information System 10.1 software to transform the categorization results into vector data. FINDINGS: This study shows that the landcover classification results have high accuracy. This study shows that the area of oil palm land from 2015 to 2019 has increased along with a decrease in land used, such as forests and others. The area of oil palm land 2014 was 2,071,345 hectares, while the area in 2019 was 2,110,545 hectares. In other words, there was an increase in land cover due to land clearing and deforestation, namely 39.2 thousand hectares. The built-up area has also increased in the last five years, namely 165,358 hectares. The number of oil palm plantations tends to be greater in relatively plain areas compared to areas with relatively high altitudes and steep slopes. Small farmers'''' area of oil palm land increased by 1,000 hectares in 2014-2018. The most significant increase occurred in 2016-2017, around 38,889 hectares.CONCLUSION: This study demonstrates that using Landsat 8 imagery combined with GIS approaches provides the optimal method for an in-depth ANALYSIS of land cover changes related to oil palm expansion and land clearing that occur on a broader spatial scale and temporal in Jambi Province. This study shows that smallholder oil palm plantations in the Jambi region play an important role in increasing deforestation in Jambi Province, especially in Indonesia. This study is expected to serve as a valuable resource for informing policy decisions aimed at addressing the issue of deforestation resulting from the prospective increase of oil palm crops in the forthcoming period.

Investigation of the Temporal and Spatial Variation of Maximum Soil Temperature in Iran Extended Abstract Introduction The study of soil temperature in different depths of soil is important in climatology, hydrology, agrometeorology and water resource management. Different depths has a different temporal and spatial soil temperature variation. It represents the regional ground temperature regime. Furthermore, due to its rapid response to environmental changes, soil temperature is one of the most important indicators of climate change. The increase in soil temperature because of global warming can promotes disasters such as drought by increasing the water demand of agricultural products during the plant growth period. The increase in soil temperature also have a various consequences, include increasing evaporation from the soil surface, soil salinity in susceptible areas, which can lead to a decrease in soil yield and failure in plant growth. Therefore, knowledge of soil temperature changes in different environments is very important in climate studies. The aim of the current research is to analyze the spatial and temporal variations of soil temperature at different depths from five to 30cm of the ground and to investigate the existence of any kind of increasing or decreasing trend at different climates of Iran. Methodology Hourly soil temperature data (depths of 5, 10, 20 and 30 cm) were used in this research for the period of 1998-2017. The soil depth temperature is measured three times a day at 6: 30 am, 12: 30 pm, and 6: 30 pm local time (3, 9, and 3 p. m. UTC). These data have been received for 150 synoptic stations of Iran on a daily basis from the Iran Meteorological Organization (IRIMO). IRIMO monitored the quality of soil temperature for data entry, data recording, and data reformatting errors. Data availability, discrepancies, errors, and outliers were identified during the second stage. At the first step, temporal coefficient of variation were calculated for available soil temperature time series from five to 30 cm depths of each station. For this purpose, the average of three daily measurements of soil temperature was calculated and then the temporal coefficient of variation was obtained. In the next step, trend ANALYSIS of soil temperature has been investigated using the non-parametric Mann-Kendal test. The trend slope was calculated using Sen’s slope for each station in seasonal time scale. Trend ANALYSIS has been done for all three observations of the day. Results and Discussion The studied stations show significant spatial patterns in the temporal variability of soil temperature. In all four investigated depths, from five to 30 cm, the northwest parts of Iran, and some parts of Zagros and Alborz mountain ranges have high temporal coefficient of variation. In contrast, the stations located on the southern coasts and southern islands had the lowest temporal variability. In warm and cold seasons (summer and late autumn to mid-winter), the spatial changes of soil temperature at different depths are lower than spring and early autumn. However, in the warm period of the year, the soil temperature experiences lower spatial variations at different depths. Spring and autumn seasons, as the transition period from cold to warm and warm to cold seasons, show the most spatial temperature variations in Iran. Detected trends do not have significant differences among the three observations of the day. Soil temperature Trend ANALYSIS at different depths showed positive values for two seasons of summer and winter over most of the stations throughout Iran. Extreme trends are more frequent in the summertime of Zagros and Alborz mountainous regions, while in the winter season the stations located at the southern latitudes of Iran have experienced the most positive trends. In the summer season, higher trends with 99% confidence are more frequent in the mountainous areas. These positive trends in soil temperature have occurred in all studied depths. The negative trend at different depths is a distinct feature of the autumn season, which is significantly more prevalent than other seasons throughout Iran. The ANALYSIS of soil temperature trends in different depths shows that values above 1 degree Celsius often occur in 5 to 20 cm deeps. The increasing trend of soil temperature in winter shows a greater spatial expansion, which is indicate increasing annual minimum soil temperatures and the increasing trend of Iran's soil temperature. Keywords: Soil Temperature, Spatiotemporal Variations, Man-Kendal Test, Sen's Slope, Iran

BACKGROUND AND OBJECTIVES: Understanding spatial and temporal rainfall variability is essential for effective water resource management in Indonesia, where diverse landscapes and dynamic tropical climates cause uneven precipitation that often leads to localized floods or droughts. This study aims to investigate how geomorphological and topographical differences across the Toba-Asahan, Brantas, and Larona-Malili watersheds in Indonesia influence rainfall distribution and trends, in order to support adaptive and sustainable watershed management.METHODS: This study analyzes rainfall variability in three distinct Indonesian watersheds, Toba-Asahan, Brantas, and Larona-Malili, using climate hazards group infrared precipitation with Station version 2 satellite precipitation data. The spatial and temporal patterns of rainfall are examined in relation to each watershed’s unique geomorphological and topographical characteristics. Basic statistical ANALYSIS and mapping techniques are used to identify trends and visualize distribution patterns, aiming to provide insights into how natural landscape features influence rainfall behavior and water availability at the watershed scale.FINDINGS: The results reveal a significant long-term increase in rainfall in the Larona-Malili watershed, while no statistically significant trends are observed in the Brantas and Toba-Asahan watersheds. The dominant rainfall patterns reflect the unique regional climatic characteristics of each watershed. Spectral ANALYSIS highlights the influence of El Niño Southern Oscillation and Indian Ocean Dipole, showing semi-annual rainfall patterns in Toba-Asahan and Larona-Malili, and an annual cycle in Brantas. Climatic sensitivity differs across the three watersheds, as reflected by the varying influence of the Webster-Yang Monsoon Index, El Niño Southern Oscillation, and Indian Ocean Dipole.CONCLUSION: This study comprehensively analyzes rainfall variability in three significant watersheds in Indonesia; the Brantas, the Toba-Asahan, and the Larona-Malili watersheds. Another finding from this study is that seasonal rainfall patterns in the Brantas watershed is significantly influenced by the Asian Monsoon. In contrast, the Toba-Asahan and Larona-Malili watersheds are shaped by local and regional factors, with land use changes playing a role in rainfall variability and water resource impacts. Annual patterns vary among the watershed, with Toba-Asahan experiencing year-round rainfall peaking from August to December, Brantas dominated by afternoon convection-driven rain from January to April and November to December, and Larona-Malili showing morning-to-noon rainfall from May to July due to local circulation and topographic effects. The findings provide valuable insights into managing water resources and addressing climate change and extreme weather variability in Indonesia. In conclusion, the overall results of this study may serve as a basis for water resource management in the three watersheds, especially in the face of potential climate change and extreme weather variability.

The risk of fires in natural areas is one of the most important climatic hazards in Lorestan Province. The current study aims to analyze the temporal series trend of wildfire events in natural areas and to reveal the spatial-temporal pattern of wildfire related to the type of land cover. In this regard, the data of MODIS fire product as well as land cover and vegetation product of MODIS during the 2000-2020 were used. Cross-tabulation matrix ANALYSIS and spatial correlation matrix were used to reveal the relationship between wildfire events and land cover. The findings showed that more than 70% of the total frequency of wildfire in natural resources (wildfire code 2) in Lorestan Province is related to June and then July. The results of cross-tabulation matrix ANALYSIS revealed that 3 uses of rangelands with medium canopy, low density forest lands and rainfed agricultural lands accounted for 0. 75 of wildfires. More than 70% of the annual frequency of fire events in the two forest land cover classes was in June and July (June and July), which is significantly correlated with the density of vegetation in these classes two months ago (April and May). While the frequency of fires in rainfed agricultural lands was generally concentrated in August and September, it did not show a significant correlation with vegetation of any month. Practically, it can be said that the presence of vegetation density during April and May in the forest floors is one of the most important factors related to wildfire in following two months, June and July. Therefore, focusing on management over a 62-day period, from May 15 to July 16, 55% of fire incidents can be controlled in the area of pastures and forest floors.

Drought as one of the natural disasters has a major impact on parts of an ecosystem. Although it cannot be prevented, its negative effects can be mitigated by some measures. Considering the high importance of groundwater resources in the country, the study of hydrogeological droughts and factors affecting groundwater drawdown is essential for the management of these vital resources. In order to investigate the impact of droughts on each other, the groundwater level variations and evaluation of the groundwater drought in Karun watershed were analyzed using GRI and SDI drought indices over a ten-year statistical period (2008-2018). The results showed a correlation between GRI and SDI indices in most regions of the study areas. Although in some cases, the impact of hydrological drought on groundwater is delayed by 6 months to one year. Low correlation between two hydrological and groundwater drought indices and the high correlation between GRI and groundwater abstraction indicated that drawdown in the aquifers cannot be the sole cause of drought, rather, in some cases, excessive abstraction is more effective. Overall, the GRI indices are more obvious in the southeast and west of the Karun watershed during the ten-year statistical period. In the final years of this period the northern side of the basin has also been affected by more severe droughts, which also has a correlation with the values of the SDI indices.

Background and Objectives: One of the applications of population attributable risk percent (PAR%) is to estimate the disease burden in a population exposed to several risk factors. Therefore, this study was conducted to estimates the PAR% of the space-time clusters of pulmonary tuberculosis.Methods: In this study, the data of pulmonary TB cases were obtained from the health department of Hamadan University of Medical Sciences. After detecting significant clusters using the spatiotemporal scan statistic, PAR% was used to analyze the clusters and to detect the location of clusters more accurately.Results: Four primary space-time clusters and three secondary spatiotemporal clusters were detected for patients with pulmonary tuberculosis and 92% of the patients who did not have a clear state in term of HIV infection. Despite differences in the location of clusters and PAR% attributed to them, the second primary cluster of pulmonary tuberculosis cases (consisting of the cities of Razan, Famenain and Kabudrahang) had the highest amount of PAR% that needs more attention.Conclusion: The presence of significance spatiotemporal clusters in Hamadan highlights the necessity of the use of PAR% to distinguish cluster areas and to implement prevention and control policy. However, more analytical studies are needed to detect the on the determinants of the occurrence of pulmonary TB.

Clouds cover major portion of the earth’s surface and play an important role in climatic system. Clouds affect the radiation energy balance of the earth’s climate system by absorbing or scattering solar radiation and long wave radiation and emitting thermal radiation. Cloud properties are closely related to cloud cover patterns, a shift in cloud regime would result in changes in cloud fraction and the cloud microphysical properties and both of these (cloud fraction and cloud microphysics) influence the radiation forcing (Rapp, 2015). Clouds have a strong effect on precipitation distribution, tropospheric temperature profile, climate change, radiation budget, global hydrology budget. Thus, they have an important influence on global climate. The purpose of this research is the study of this variety of cloud fraction in Iran during all months over 2001-2015 with respect to the latitude, topographic forcing, and vegetation cover. Latitude, altitude, slope, aspect and vegetation are geographic characteristics in an area which determine and control many climatic parameters such as temperature, precipitation and etc. ANALYSIS of spatiotemporal variations of cloud fraction based on the characteristics in a vast country like Iran has not been considered by researcher. Satellite imagery is one of the most efficient data source to monitor cloudiness. The spatial and temporal variation of cloud type Ping as deep cloud (Ping et al., 2014), stratospheric clouds (Pitt et al., 2007) and different cloud type (Halladay et al., 2012) have been studied by researchers over the world. Some researchers consider relation between cloud fraction and climate and geographic parameters e.g. Sato et al., 2007. Some other researchers reviewed cloudiness studies e.g. Bromwich et al., 2012. Iran is located between 24.5 to 39.5 north latitude and has topographic range between -28 to 5595m. NDVI value reaches a maximum value in June (0.897) during 2001-2015 time period. This research uses DEM 30 meter and Normalized Difference Vegetation Index in order to analyzie the effets of geographic parameters on cloud fraction. Monthly mean values of cloud fraction are extracted from MOD08/MYD08 MODIS products. We have then validated accuracy of MODIS mean monthly of cloud fraction aboard the Terra and Aqua using ERA-Interim and station data.Results show that there is a good agreement between them but the data is more accurate in cold month, and in the mornings, so that, polynomial coefficients of determination are higher against the stations data and in the morning times due to hourly stations weather data which corresponded to the satellites overpass. The geographic characteristics results showed that cloud fraction increases with increase in latitude except summer seasons due to monsoon system. In order to showing topographic forcing on cloud fraction, this parameter is divided into intervals of 15% for each months and then altitude, slope and aspect that were extracted for each interval. Topographic forcing presents the interesting role of slopped convection in mountain area in average elevation (500-1500 meter) over spring and autumn. Vegetation also has nearly direct relation with cloud fraction. Investigation of temporal variations of cloud fraction showed that the maximum value of STD is obtained in autumn for both satellites.Furthermore, significant trend was not observed in many months, but month of December showed decreasing trend by 2 to 3 annually. This research is the first attempt in the field of cloud climatology in recent decades and further ANALYSIS are needed to show the ongoing climate change effects on cloud climatology in this region. Study of cloud vertical profiles can be the next research in this field.

Maroon River is a valuable aquatic ecosystem in Iran. The purpose of this research was to investigate the lasting impacts of the Maroon dam on river water quality (RWQ), particularly downstream, and determine those factors affecting the optimal management of the RWQ. The modified Mann-Kendall and Sen's slope estimator tests were employed to investigate the variation trend of qualitative parameters. Then, multivariate statistical analyses, including correlation assessment, cluster ANALYSIS, T-test, and factor ANALYSIS of spatiotemporal pattern, are applied to recognize factors affecting the effects of dam construction. Results showed that the total hardness and the calcium, chlorine, and sulfate concentrations significantly increased in downstream at a level of 5% confidence. The cluster ANALYSIS indicated that dam construction probably did not affect the upstream; however, the increased dissolution rates of calcium and sulfates downstream illustrated the presence of the Gachsaran formation in the river path and the dissolution of rock gypsum in the water. The factor ANALYSIS determined three and two main components before and after dam construction with 84.8% and 71.6% variances, respectively. These components and the correlation between chloride-sodium and calcium-sulfate ions could show the Sodium Chloride  dissolution and the effects of the dissolution of gypsum mid-layers from the Gachsaran formation after the dam construction. The strong relationship between the magnesium and chlorine contents in the Cham Nezam station might result from the salt/detergent-contained household and urban wastes entering the river. According to the results of various tests, the dam has changed the quality of the river downstream. Still, Wilcox and Schoeller's indices demonstrated that dam construction did not significantly affect the RWQ used for drinking and agriculture.