Showing 125 results for Index
A. Barikloo, S. Rezapour, P. Alamdari, R. Taghizadeh Mehrjardi,
Volume 27, Issue 4 (12-2023)
Abstract
Soil quality is one of the most crucial factors determining crop productivity and production stability. The soil's physical, chemical, biological, and ecological characteristics affect its quality. Numerous researchers have concentrated the evaluation on a small number of soil quality indicators because measuring all soil quality indicators would be time-consuming and expensive. This study looked at the spatial autocorrelation of soil quality in the southwest areas of the Urmia Plain to establish the minimal data set for quantitative assessment. To accomplish this, 120 composite soil samples were collected from a depth of 0 to 60 cm, and the soil quality index was then calculated using the IQI method in 4 modes: Total-Linear (IQIwL-TDS), Total-Nonlinear (IQIwNL-TDS), Minimum-Linear (IQIwL-MDS), and Minimum nonlinearity (IQIwNL-MDS). 22 physical and chemical characteristics were used to choose the data set. The characteristics of sand percentage, sodium absorption ratio, cation exchange capacity, Available phosphorus, active calcium carbonate, and nickel concentration were chosen as the minimum data set (MDS) using the decomposition method into principal components. The linear IQIMDS mode produced the greatest soil quality index result, whereas the non-linear IQIMDS mode produced the lowest. The non-linear mode of the IQI index has a greater correlation coefficient (R2=0.85) than the linear mode of the IQI index (R2=0.73), according to an analysis of the linear and non-linear correlation coefficient between the soil quality index with the total category and minimum data. The findings of computing the global Moran's index for study sets of IQI soil quality index data revealed that the soil quality data are not independent of each other and are spatially autocorrelated, distributed in clusters, and have spatial autocorrelation. Getis-ord GI statistics indicated that the eastern and southeastern parts of the research region comprise clusters with poor soil quality, salt marshes produced by Lake Urmia's drying up, and surrounding arid plains.
A. Zare Garizi, K. Shahedi, A. Matboo,
Volume 28, Issue 1 (5-2024)
Abstract
Water quality characteristics play a crucial role in water resources management, watershed health assessment, and implementing effective management strategies. The objective of this research was to present an overall assessment of the surface water quality in the Gorganrood River Basin to be utilized for developing effective watershed management plans and programs. Various physicochemical water quality data including main anions and cations, Total Dissolved Solids (TDS), Electrical Conductivity (EC), Sodium Absorption Ratio (SAR), pH, and total hardness recorded at 25 hydrometric stations across the basin were analyzed and assessed with the Canadian (CCME) Water Quality Index. The mean water quality index for drinking, agriculture, and industrial purposes indicated that headwaters and higher areas generally exhibited better water quality compared to the downstream areas of the basin. Geochemical processes and the introduction of various pollutants during water flow from the headwaters to the basin outlet contribute to a decline in water quality. The highest water quality was observed in the Kabudval and Shirabad stations, whereas the Baghesalian station exhibited the lowest. For drinking water use, hardness, bicarbonate, and chloride were identified as variables contributing to water quality decline in the headwaters and upstream areas. However, these areas predominantly maintained a moderate to good quality for drinking purposes. Conversely, downstream areas experienced a significant deterioration in water quality with higher pollutant levels such as total dissolved solids (TDS), sulfate, and sodium, resulting in relatively poor to poor conditions. Approximately 60% of the stations in the basin had excellent water quality for agricultural use, with no limiting factors. Only three stations near the basin's outlet exhibited relatively poor to poor water quality due to elevated chloride levels, sodium adsorption ratio (SAR), and electrical conductivity. only 28% of hydrometric stations demonstrated good water quality for industrial use. Hardness, pH, and TDS are the main variables contributing to water quality decline for industrial use in the upstream, while downstream areas are impacted by chloride and sulfate. The outcomes of this study hold significant implications for effective water resources management, watershed preservation, and natural resource conservation in the Gorganrood basin. From industry and especially health aspects, however, more detailed investigations are needed, taking into account some other important variables of water quality (including nitrate, total coliform, fecal coliform, etc.).
Y. Neamah Abdulhasan, A. Khoshfetrat,
Volume 28, Issue 3 (10-2024)
Abstract
Piano key weirs are a type of non-linear weir that have a higher discharge coefficient than similar linear weirs. These hydraulic structures have a lightweight foundation and a simple structure is designed and installed on dams and drainage channels. Due to the high efficiency of these weirs, the investigation of downstream scour and ways to reduce it has been the focus of engineers in recent years. In the present study, a trapezoidal type C piano key weir, three discharges, and three tailwater depths were used. Two obstacles with heights of 0.02 and 0.04 meters were also used at the end of the weir exit keys. The results showed that the presence of an obstacle reduces scour at the toe of the weir. The amount of reduction in scour at the toe of the weir was greater in the weir with a larger obstacle height than in the weir with a smaller obstacle height, and in both cases was less than in the simple weir. The presence of an obstacle reduces the maximum depth of scour and moves the distance of the maximum depth of scour away from the toe of the weir. In the weir with obstacle heights of 0.02 and 0.04 meters, compared to the weir without an obstacle, the amount of maximum scour depth is approximately 16.4% and 26.9% less, and the distance of the maximum scour depth is approximately 8.7% and 19.1% more than the weir without an obstacle. The scour index in weirs with obstacles is less than in weirs without obstacles, which can reduce the risk of weir overturning. The lowest value of the scour index was observed in the weir with an obstacle height of 0.04 meters, which is approximately 41.2% less than the weir without an obstacle.
M. Tajsaeid, M. Gheysari, E. Fazel Najafabadi, R. Jafari, E. Seyfipurnaghneh,
Volume 28, Issue 3 (10-2024)
Abstract
Soil moisture is one of the important and determining factors for plant growth, the rate of evaporation and transpiration, and water management in the field. Therefore, its measurement has special importance. The surface soil has a great diversity in soil moisture and different methods were used to measure this property. Due to the problems of contact methods of soil moisture measurement, remote sensing has gained attention because of the possibility of analyzing and monitoring soil moisture on a large and global scale. In this research, satellite data and moisture measured in selected fields located in Hormoaz Abad Plain have been analyzed and compared. Sentinel-2 satellite data have been analyzed using the Google Earth Engine system. The results of this research showed that the use of triple indices in the OPTRAM model to estimate moisture is not very accurate, but the use of the EVI plant index has provided better results than the other two indices.
F. Afsharipour, M.r. Sharifi, A. Motamedi,
Volume 28, Issue 4 (12-2024)
Abstract
Drought monitoring in snowy basins requires modifications in common drought indices, called snow drought indices. The latest developed snow index is SZIsnow. The SZIsnow index calculating with special algorithm requires access to the values of 22 different climatic and physical variables, including soil moisture at a depth of 0 to 10 centimeters, soil moisture at a depth of 100 to 200 centimeters, air temperature, water equivalent to snow, runoff from snow melting, snowfall, rainfall, total precipitation rate, evaporation and transpiration, wind speed, surface runoff, groundwater runoff, potential evaporation, air pressure, relative humidity, net latent heat flux, ground heat flux, net sensible heat flux, evaporation from bare soil, evaporation from the canopy, and potential evapotranspiration. So far, the mentioned index has been calculated only on a continental scale. Drought monitoring at the basin scale is important as one of the management aspects of water resources. On the other hand, due to the lack of sufficient information to estimate the mentioned parameters, the use of information from global databases will be a solution. Therefore, in this research, while introducing the process of calculating the SZIsnow index, in the Dez catchment area, extracting the required parameters of the index in a time scale of 3, 6, and 12 months and a period of 41 years (1982 to 2023) using data GLDAS and then drought monitoring of the basin was studied. The results showed that the new SZIsnow index is a multi-variable index that provides the possibility of calculating the index due to the existence of parameters that lack ground observations and on the other hand, the availability of the reliable GLDAS database. Also, the results showed that in the time steps of 3, 6, and 12 months, July at -0.59, June at -0.45, and October at -0.35 had the highest amount of drought, respectively.
S. Zandi, S. Borumandnasab, M. Golabi,
Volume 28, Issue 4 (12-2024)
Abstract
Quinoa, a nutritionally rich crop with remarkable adaptability to unfavorable environments, exhibits a high tolerance to salinity. Reusing agricultural drainage water is a natural and important method in drainage management that increases farmers' income, sustainable production, and food security. The objective of this study was to investigate the effects of irrigation with agricultural drainage water, salinity stress, and water deficit on the yield and yield components of quinoa (Titicaca) under salinity levels of 2, 10, 15, and 20 dS/m and irrigation levels of full irrigation, 80%, and 60% of the crop water requirements. The experiment was conducted with three replications using a split-plot design with a randomized complete block design (RCBD) at the experimental farm of the Faculty of Water and Environmental Engineering at Shahid Chamran University of Ahvaz, during the fall and spring seasons of the years 2022 and 2023. The water requirement of Qinoa was determined gravimetrically by measuring soil moisture before each irrigation and increasing it to field capacity. The experimental treatments were imposed after seed germination and from the start of cultivation. The plants were harvested and transported to the laboratory for drying and yield component analysis upon physiological maturity. The results revealed that salinity stress had a more pronounced impact on reducing quinoa yield and yield components compared to water stress. The highest and lowest grain yields were observed in the autumn season, reaching 5.45 and 1.8 t/ha under the treatments of S1I1 and S4I3, respectively. Similarly, in the spring season, the highest and lowest grain yields were 3.87 and 0.73 t/ha under the same treatments, respectively.
M. Naderi Khorasgani, R. Amiri, A. Karimi, J. Mohammadi,
Volume 29, Issue 1 (4-2025)
Abstract
The soils of the Shahrekord plain, part of the Beheshtabad watershed subbasin in Shahrekord County, Chaharmahal va Bakhtiari province, have been used for crop production and domestic animal feeding for centuries, yet the soil quality of this plain has been overlooked. Therefore, assessing the quality of Shahrekord plain soil is essential. This research aimed to evaluate the physical soil quality of the plain using soil quality indices such as the Integrated Quality Index (IQI) and Nemoro Quality Index (NQI). A randomized compound sampling strategy was employed, and 106 surficial (0-25 cm) soil samples were collected during intensive fieldwork. Following pretreatments of the soil samples, several key soil characteristics were measured using standard methods, which were compiled into a Total Data Set (TDS) and used to calculate IQITDS and NQITDS. The minimum effective data set (MDS) was selected, and weights for the quality indices were determined using TDS and Principal Component Analysis (PCA). The minimum data set included the soil sand percentage, soil organic matter percentage, mean weighted diameter of aggregates, soil moisture at field capacity, bulk density, soil reaction, and electrical conductivity. The soil quality at each sample site was assessed using the indices and data sets, TDS and MDS. Geostatistical techniques and ordinary kriging methods were utilized to map soil quality. Results indicated that the soil quality of rangelands was significantly higher than that of cultivated soils (irrigated and drylands). Additionally, approximately 71% of the soils were classified as very low, low, and medium quality, highlighting the need for monitoring and managing such soils.
J. Karimi Shiasi, F. Fotouhi Firoozabad, A. Fathzadeh, M. Hayatzadeh, M. Shirmardi,
Volume 29, Issue 1 (4-2025)
Abstract
One of the main factors contributing to water erosion is the inherent characteristic of soil erodibility. Erodibility depends on particle size distribution, organic matter, structure, and soil permeability. This research aimed to investigate changes in the soil erodibility factor across geomorphological facies. The soil erodibility index was estimated by sampling 58 points within the geomorphological facies of the Dorahan watershed, using the Wischmeyer and Smith method. In the laboratory, soil granularity distribution, organic matter, soil structure, the amount of gravel, lime, salinity, acidity, and sodium absorption ratio were measured. Results indicated that soil erodibility across the entire area ranges from 0.0148 to 0.0661 (t.hr/Mj.mm). The soil erodibility index (K) for the hro-p1 and hro-p2 facies is higher than for others and exhibits the widest range of variations compared to the other facies. The lowest range of changes within geomorphological facies is associated with the hrc facies. The erodibility index decreases from the east to the west of the basin due to the presence of exposed rock faces, which protect the soil as a cover layer.
M. Zarinibahador,
Volume 29, Issue 1 (4-2025)
Abstract
The calcium carbonate equivalent (CCE) in soil is one of the most important soil properties. Predicting the amount of calcium carbonate equivalent in soil is essential for sustainable soil fertility management. The present study aimed to digitally map calcium carbonate equivalent using auxiliary environmental variables, Landsat 8 satellite images, and predictive models and to present the best models in the Badr watershed in the south of Qorveh district. In the first phase, a geomorphologic map was created using a geologic map and based on the ZINC method in a geographic information system environment. In the second phase, the location of 125 survey profiles was determined using the Latin hypercube technique, and the calcium carbonate equivalent of the soil horizons was measured by acid titration. The auxiliary variables included derivatives of the digital elevation model, remote sensing indices from the Landsat 8 satellite, and a geopedological map. The principal component analysis (PCA) method was used to select suitable auxiliary variables. In the third phase, the modeling was carried out, digital maps of the soil classes and properties were created, and the models were evaluated. Two different cases were investigated in this study to estimate the calcium carbonate equivalent of the soil. In the first case, artificial neural network models, decision tree analysis, random forest, and the K-nearest neighbor model were used for prediction. The multiple linear regression model was also used to combine the results of the models. Among the models used to predict the equivalent amount of calcium carbonate using the 10-fold cross-validation method, the multiple linear regression (MLR) model had the highest prediction accuracy with a coefficient of determination of 0.796 and a mean square error of 6.514. In the 5-fold cross-validation method, the K-nearest neighbor (KNN) model had the highest predictive accuracy with a coefficient of determination of 0.9845 and a root mean square error of 2.1258. Due to the spatial nature of the 10-fold cross-validation method, the use of this method is preferable to the 5-fold cross-validation method. In addition, the most important auxiliary variables in order of importance to predict the calcium carbonate equivalent in soil were the carbonate index, slope direction, geomorphology, the base level of the catchment network, and the slope of the catchment.
H. Ramezani Etedali, S. Koohi,
Volume 29, Issue 1 (4-2025)
Abstract
Agriculture, as a crucial economic and social sector in Iran, has always been significantly influenced by weather conditions, water availability, and farm management practices. Enhancing productivity and optimizing resource management in crop production are essential to achieving sustainable agricultural development and ensuring food security. This research aimed to investigate how much wheat, barley, and corn production, separately from irrigated and rainfed crops, will be affected by the severity of climatic drought (based on the CMIP6) in Iran. This research was carried out using the amount of wheat, barley, and corn production in all the provinces, which was provided by the Agricultural Jihad Organization during the years 1371 to 1402. Climate data was obtained from the NEX-GDDP database, and the De Martonne aridity index was calculated to investigate changes in aridity under climate scenarios. The results indicated that during the baseline period, the production of rainfed wheat, barley, and corn under semi-arid to very arid climatic conditions was approximately 2,076, 434, and 15 thousand tons per year, respectively. With the intensification of arid conditions across the country, these production levels are projected to increase to 3,333, 693, and 16 thousand tons under the SSP2 scenario and further rise to 3,558, 842, and 16 thousand tons under the SSP5 scenario. Additionally, the production of irrigated wheat, barley, and corn in semi-arid to very arid climatic conditions during the baseline period stands at approximately 6,240, 1,683, and 5,842 thousand tons, respectively. Under the SSP2 climate scenario, the production is expected to reach about 7,126, 1,757, and 6,253 thousand tons, while in the SSP5 scenario, the estimated production is approximately 7,348, 1,780, and 6,324 thousand tons. The findings revealed notable spatial differences in crop production across the country, highlighting that the climatic conditions, particularly in the central, southern, southeastern, and southwestern regions, are becoming increasingly arid. It is crucial to implement smart planning and policies, adopt advanced technologies, and improve the management of water and soil resources to mitigate the adverse impacts of these changes and better adapt to evolving conditions. Addressing these challenges and implementing effective measures are essential steps toward achieving sustainability in the agriculture and natural resources sectors.
L. Babakhah, A. Khoshfetrat, E. Delavari,
Volume 29, Issue 1 (4-2025)
Abstract
Piano key weirs are a new form of labyrinth weirs and exhibit nonlinear characteristics. Due to their high efficiency regarding flow capacity, it is crucial to investigate local scour and identify solutions to mitigate it. Local scour was examined downstream of a trapezoidal piano key weir type B for the first time in this study. The weir was installed 5.50 m from the start of the channel and has a height of 0.20 m, featuring three cycles (three outlet keys, two inlet keys, and two inlet half keys). Three tailwater depths and three different flow rates were also utilized. The maximum scour depth increases with a higher densimetric Froude number and flow rate while decreasing with tailwater depth. The range of the dimensionless parameter for the densimetric Froude number in this study varies between 1 and 2. Additionally, sand and gravel were employed as two types of bed materials. As the diameter of the bed material increases, the maximum scour depth decreases. The scour index for gravel bed material is significantly lower than that for sand material, indicating that the risk of weir overturning is much lower in gravel bed material.
F. Zolfaghari, S. Eslamian, A.r. Gohari, M.m. Matinzadeh, S. Azadi,
Volume 29, Issue 2 (7-2025)
Abstract
Drought represents one of the most critical natural disasters, exerting profound impacts on agriculture, society, the economy, and water resources. Various indices are used to monitor drought and its effects. This study aims to monitor drought in the Zayandeh-Rud Basin using the Standardized Precipitation Index (SPI), the Standardized Precipitation-Evapotranspiration Index (SPEI), the Evaporative Demand Drought Index (EDDI), the Palmer Drought Severity Index (PDSI), and the Reconnaissance Drought Index (RDI). All these indices are based on potential evapotranspiration, incorporating parameters such as precipitation, temperature, relative humidity, wind speed, and sunshine duration. These five indices were calculated and evaluated during the statistical period of 1993–2023 for meteorological stations in Isfahan, East Isfahan, Kabootarabad, Daran, Shahreza, Najafabad, and Mobarakeh. After calculating the indices and using spatial zoning maps, the studied stations were compared in terms of these indices. The continuity of dry and wet periods, as well as the intensity of droughts and wet spells, was analyzed. Subsequently, drought intensities during different years in these stations were ranked using the TOPSIS model based on factors such as precipitation, potential evapotranspiration, and station elevation. The results showed that in stations with a dry climate (such as Isfahan, East Isfahan, and Shahreza), drought occurrences (as indicated by higher rankings) have been consecutive over multiple years. Comparing the performance of the indices in the studied stations using spatial zoning maps revealed that the intensity of droughts and wet spells in regions with dry and semi-dry climates was not very significant. However, in areas with humid climates, the fluctuations in drought and wet spell intensities were quite substantial. The findings indicate that the PDSI and EDDI indices are more suitable for evaluating drought in dry climates.
M. Khoshoei,
Volume 29, Issue 2 (7-2025)
Abstract
The issue of water scarcity or the limited availability of water resources, including concepts such as water stress, water shortage, and water crisis, is investigated in this study. Water stress refers to problems related to access to freshwater resources, particularly due to the excessive withdrawal of surface and groundwater. A water crisis describes a situation where the available clean and safe drinking water in a specific region is insufficient to meet demand. Factors like drought, reduced rainfall, and pollution can exacerbate water stress. Water shortage arises from reasons such as the inability to meet demand, economic competition over water quality and quantity, conflicts among users, the irreversible depletion of groundwater resources, and negative environmental impacts. This study provides an index to assess water stress for spatial analysis in the study area and analyzes relevant data by collecting information from various sources. This index utilizes both static and dynamic parameters to estimate drought and better depict water stress conditions. Static parameters include land use, slope, and soil type. Dynamic parameters include precipitation, temperature, and groundwater level. Kashan County was selected as the case study due to the continuous reduction in water resources. The results showed that in the water years 2005, 2014, 2020, and 2021, Kashan experienced the highest level of water stress, while in the water years 2002, 2004, 2010, 2012, 2013, and 2015, it experienced the lowest level of water stress.
M. Asadi, M. Noshadi, A.r. Noshadi,
Volume 29, Issue 2 (7-2025)
Abstract
In this research, drinking water quality was investigated using acceptability, health, and nutrition-based indicators from 2010 to 2022 in Shiraz City (Fars province). Magnesium, fluoride, and calcium play a significant role in the contribution of drinking water in Shiraz City to the intake of dietary minerals. The acceptability water quality index (AWQI), health-based water quality index (HWQI), and drinking water quality index (DWQI) rankings in Shiraz City are excellent, but the average drinking water nutritional quality index (DWNQI) of Shiraz City is 77.52 ± 5.47, which falls within the good ranking. Therefore, while the conventional water quality indices (AWQI, HWQI, and DWQI) are excellent, the DWNQI index does not achieve an excellent rating, due to the inclusion of the nutritional value of water in the DWNQI index. In general, the trend of AWQI, HWQI, DWQI, and DWNQI over thirteen years in Shiraz City shows that the conventional drinking water quality indices (AWQI, HWQI, and DWQI) do not provide an accurate picture of the assessment of drinking water quality in many cases, as they do not consider the nutritional role of water. For this reason, water is sometimes treated more than necessary. Therefore, it is essential to revise the interpretation of drinking water quality using the DWNQI index to gain a comprehensive picture of drinking water quality.
Hossein Rezazadeh, Parisa Alamdari, Salar Rezapour, Mohammad Sadegh Askari,
Volume 29, Issue 3 (10-2025)
Abstract
Soil quality assessment plays a crucial role in sustainable land management, particularly in degraded areas such as saline and sodic soils. This study aimed to determine the spatial distribution of the Soil Quality Index (SQI) in saline and sodic soils around Lake Urmia using two geostatistical interpolation methods: Kriging and Inverse Distance Weighting (IDW). A total of 82 soil samples were collected from a depth of 0–30 cm, and 24 physical, chemical, and heavy metal properties were analyzed. The Soil Quality Index was calculated based on both linear and non-linear approaches. Principal Component Analysis (PCA) was used to identify a Minimum Data Set (MDS), including: calcium carbonate equivalent, EC, clay percentage, BD, silt percentage, organic carbon, Pb, and cadmium, which explained more than 78% of the total variance. The results indicated that the SQI showed moderate spatial variability across the study area, with a decreasing trend from west to east. Comparison of the interpolation methods revealed that Kriging performed better in the linear model, while IDW showed higher accuracy in the non-linear approach. The best-fitted theoretical model was spherical, with a range of influence varying between 6,130 and 20,610 meters. Overall, integrating the Soil Quality Index with geostatistical methods provides a powerful tool for understanding spatial variability and supporting effective planning in saline and sodic soils.
Mehdi Feyzolahpour, Behrouz Mohamady Yeganeh, Maryam Amri,
Volume 29, Issue 4 (12-2025)
Abstract
By utilizing land surface temperature (LST), valuable insights can be gained regarding the impact of land use on energy balance processes. Therefore, this study aimed to investigate the trend of LST changes due to land use changes in the Gorab rural district. Four land use types, including water bodies, bare land, Agricultural area, and forest, were determined from 2013 to 2024 for the maximum likelihood classification (MLC) and support vector machine (SVM) models. The surveys showed that the area of water in the dry period decreased from 0.9 km2 in 2013 to 0.4 km2 in 2024, a decrease of 0.5 km2. In contrast, the area of forest areas increased from 136.1 km2 in the dry period of 2013 to 147.2 km2 in 2024. The Kappa coefficient values for the SVM and MLC models during the wet season of 2021 were 53.94 and 68.7, respectively. Based on this, it was found that the MLC model has higher accuracy. To match spectral indices with LST values, NDVI, NDSI, and NDWI were calculated. Land use changes during the 2013-2024 period affected land surface temperatures, causing fluctuations from 11.5°C to 21.18°C in the wet season and from 13.81°C to 31.45°C in the dry season. The highest LST values were associated with barren land, while water bodies and vegetation cover had the lowest LST values. Among the spectral indices, the highest positive correlation was observed with NDWI, with a value of 0.64 in 2024. The highest negative correlation, -0.66, was observed with NDVI in the same year. Over the 11 years, the area of forest cover increased by 8.15%, while agricultural land decreased by 33.5%. The most significant change occurred in agricultural lands, which declined in area from 35.5 km² to 23.6 km².
Laleh Divband Hafshejani, Mohammad Mirnaseri, Abd Ali Naseri,
Volume 29, Issue 4 (12-2025)
Abstract
Soil, as one of the vital natural resources, plays a fundamental role in ecosystem sustainability and global food security; however, degradation caused by unsustainable management, intensive agriculture, and pollution threatens its capacity. The use of organic amendments such as hydrochar is considered an innovative approach to improve soil physicochemical properties and enhance the Soil Quality Index (SQI). This study aimed to investigate the effects of different levels of hydrochar on soil properties and evaluate SQI. The treatments included control and three hydrochar levels (H10, H20, and H50). Soil properties such as pH, porosity, bulk density, electrical conductivity, organic carbon, total nitrogen, and available phosphorus were measured and normalized, and parameter weighting was conducted using entropy and principal component analysis (PCA). Results showed that nitrogen and organic carbon had the greatest importance in soil quality. The H50 treatment recorded the highest SQI (0.815), significantly greater than other treatments, while H20 (0.546) and H10 (0.336) also showed positive effects compared to the control (0.159). Hydrochar application improved organic carbon, nitrogen, and phosphorus and reduced bulk density. Although an increase in electrical conductivity was observed in H50. Overall, hydrochar application had a positive and gradual effect on SQI, with H20 recommended as an optimal level to improve fertility and reduce long-term salinity risks.
Homa Chegini, Chooghi Bairam Komaki, Majid Owneq, Hamidreza Asgari, Khalil Ghorbani,
Volume 30, Issue 1 (3-2026)
Abstract
This study aimed to analyze the spatial–temporal correlation between the Vegetation Health Index (VHI) and climatic variables, including precipitation, potential evapotranspiration (PET), and mean temperature, in Golestan Province during the period 2000–2024. MODIS satellite products were used for vegetation and land surface temperature data, while the TerraClimate dataset provided precipitation and PET variables. After spatial–temporal alignment, the Cross-Correlation Function (CCF) was applied to identify optimal time lags, and the Random Forest model was employed to assess the relative importance of the climatic drivers. Turning to the results, increasing trends in mean temperature and PET were observed, alongside a significant decrease in precipitation, which led to intensified climatic stress and reduced VHI across the province, especially during summer in croplands and rangelands. The relationship between VHI and precipitation was positive (maximum correlation of 0.299 in croplands), negative with PET (−0.287), and non-linear with temperature (0.275). Notably, VHI responded to precipitation with short-term lags (0–1 month), whereas PET and temperature effects emerged with longer lags (2–4 months). The Random Forest analysis highlighted precipitation as the most influential factor on VHI, followed by PET and temperature, achieving strong predictive performance (R² = 0.78, RMSE = 0.09). Overall, these findings emphasize precipitation as the immediate driver of vegetation health, while PET and temperature act as secondary, cumulative stressors. The results provide valuable insights for developing climate adaptation and sustainable resource management strategies in agriculture and natural ecosystems of Golestan Province.
Eisa Solgi, Mahdiyeh Dorjdar,
Volume 30, Issue 2 (7-2026)
Abstract
Soil contamination by metals is a major problem in terrestrial ecosystems, particularly in and around industrial areas, and can pose a threat to human health in various ways. Therefore, in the present study, the bioaccumulation of heavy metals in the earthworm (Eisenia fetida) in soil around the Abik Cement Factory in Alborz Province was evaluated. Sixty soil samples were collected at depths of 0-20 cm at distances of 500, 1000, and 2000, in the directions of north, south, east, and west. Earthworm samples were also randomly collected from these distances and directions. The wet digestion method was employed to determine heavy metal concentrations in soil and earthworms, and Zn, Cu, Pb, Cr, and Ni were measured using an atomic absorption spectrometer. One- way ANOVA and Kruskal- Wallis statistical methods were used to examine the effects of distance and direction. The bioaccumulation factor (BAF) was used to evaluate the ability of earthworms as a biological indicator. According to the results, the average concentrations of heavy metals in the soil around the lands of the Abik Cement Factory for Cr, Pb, Cu, Zn, and Ni were 22. 20, 10. 19, 6. 34, 7. 63, and 135. 75 (mg/kg), respectively. The average concentrations of heavy metals in earthworms in this region for Cr, Pb, Cu, Zn, and Ni were 51.57. 57, 9. 66, 5. 18, 5. 45, and 106. 17 (mg/kg), respectively. The results indicated that the distance effect was significant only for Ni (p< 0. 05), and the direction effect was significant for all heavy metals except Zn (p> 0. 05). A decreasing trend in the concentrations of Cu, Zn, and Pb was observed with increasing distance from the cement factory, indicating the impact of the Abik Cement Factory on heavy metal pollution in the agricultural soil of the surrounding lands. The highest bioaccumulation factor (BAF) was calculated for zinc and was greater than 1, indicating bioaccumulation of Zn in earthworms. It can be concluded that earthworms can be used as a suitable biological indicator species for monitoring soil contamination with heavy metals, especially for Zn.
Omolbani Mohammadrezapour, Hadi Siasar, Mohammad Javad Zeinali, Mohammad Nazeri Tahroodi,
Volume 30, Issue 2 (7-2026)
Abstract
Accurate monitoring of water surface dynamics in semi-arid regions poses challenges due to uncertainties regarding the optimal spectral index and sensor selection for effective water resource management. This study assessed the comparative performance of nine spectral water indices across the Landsat-8 and Sentinel-2 platforms to identify the best index-sensor combinations for monitoring semi-arid reservoirs. Utilizing the Google Earth Engine cloud computing platform, 181 satellite images were processed for Golestan Dam in northeastern Iran, comprising 107 Landsat-8 scenes from 2013 to 2023 and 74 Sentinel-2 scenes from 2018 to 2024. After applying atmospheric corrections using the LEDAPS and Sen2Cor algorithms, nine spectral indices (NDWI, MNDWI, ANDWI, AWEI, WI2015, WI1, WI2, LSWI, and NDTI) were calculated and evaluated against the WI2 reference through RMSE, R², and Nash-Sutcliffe efficiency metrics. MNDWI showed superior performance for Sentinel-2 (RMSE=21.42 ha, R²=0.998, NS=0.996), while ANDWI was optimal for Landsat-8 (RMSE=54.54 ha, R²=0.977, NS=0.976). Time-series analysis revealed a 35% reduction in mean annual reservoir area, decreasing from 7.28 km² in 2014 to 4.72 km² in 2021. Consistent seasonal patterns were observed, with spring maxima (9.33 km² in March) and autumn minima (3.35 km² in September) evident across both sensors. A high inter-sensor correlation (r = 0.933) supports the potential for multi-sensor integration in comprehensive monitoring efforts. The LSWI and NDTI indices displayed systematic overestimation due to interference from soil moisture and vegetation, making them unsuitable for quantifying water area. These findings highlight the sensor-dependent nature of optimal index selection, recommending MNDWI-Sentinel-2 pairing for short-term monitoring and ANDWI-Landsat-8 for long-term trend analysis in the management of semi-arid reservoirs.
