Papers by Abba Aliyu Kasim

Research Journal of Environmental and Earth Sciences, 2012
This research was conducted in Dambatta local government with aim of determining the influence of... more This research was conducted in Dambatta local government with aim of determining the influence of texture and organic matter content on soil water holding capacity. Three sites were chosen based on land usescultivated area (Jama'a village), uncultivated site (shantake) and Tomas irrigation site. Fifteen composite samples were randomly collected from the top (0-15 cm) in the sites. The samples were analyzed for some soil parameters such as particle size distribution, organic carbon and water holding capacity using standard routine laboratory tests. In addition, statistical graphs and tables were employed to analyze the data. Mean values of soil organic carbon was computed to compare the results with the previous findings. The mean soil organic carbon of shantake, Tomas and Jama'a fields were found to be 2.57, 1.37 and 1.27%, respectively. The textures of the soil samples were found to be Sand and Loamy sand. The soil water holding capacity ranged from 5 to 25%. The results showed that soil organic matter was found to be higher in uncultivated fields than in irrigation fields and continuous cultivation fields. It was concluded that soil organic matter and texture had influence on water holding capacity and the effect was more pronounced when fine texture was coupled with appreciable amount of soil organic matter. It was recommended that higher levels of organic matter should be incorporated to the soils with aim of improving soil water holding capacity and further research should be done in order to fully understand the moisture characteristics of different soil samples in the study area and sudano-sahelian zone at large.

Academic Research International, 2014
This research was conducted in Kadawa, Garun Mallam local government of Kano State with aim of as... more This research was conducted in Kadawa, Garun Mallam local government of Kano State with aim of assessing the fertility of soils under rice cultivation in the area. Ten (10) composite samples were randomly collected from the top (0-20cm) in the sites. The samples were analyzed for some soil fertility index parameters using standard routine laboratory tests. In addition, Mean values of soil parameter determined were computed so as to compare the results with the critical limits for interpreting levels of soil fertility. The findings indicated that the soil texture was generally sandy loam with brown colour. The soil was moderately acidic with mean pH values of 6.07 and 5.95 in water and CaCl 2 respectively. The electrical conductivity (ECE) ranged from 0.027 to 0.2 dS/m with a mean of 0.097 dS/m. The total nitrogen (TN) ranged from 0.035 to 0.053% with a mean of 0.05%. The organic matter content (OM) ranged from 0.79 to 1.87% with a mean of 2.61%. The Available phosphorus (AP) ranged from 9.63 to 87.50ppm with a mean of 54.87ppm. Furthermore, The Exchangeable K ranged from 0.11 to 0.87Cmol/kg with a mean value of 0.24Cmol/kg and Cation Exchange Capacity (CEC) ranged from 5.0 to 11.0Cmol/kg with a mean of 7.57. it was recommended that organic manure and inorganic fertilizer should be applied to the soils in order to improve nitrogen, phosphorus and potassium levels.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025
Abstract—Surface soil moisture (SSM) is essential for understanding the interactions between the... more Abstract—Surface soil moisture (SSM) is essential for understanding the interactions between the atmosphere and Earth’s surface. The rapid development of remote sensing technology in recent decades has provided feasible alternatives for SSM retrieval. The triangle model is one such method that uses the relationship between land surface temperature (LST) and vegetation index (VI) on a triangular space to estimate SSM.
However, the traditional LST-VI triangle models inherently suffer from two major drawbacks. First, the subjective requirements for a sufficient number of pixels are characterized by a wide range of vegetation and SSM under uniform atmospheric conditions. Second, this is the need for date-to-date calibration. To overcome these limitations, the present study proposed a novel scheme of the feature space, the single pixel in time-series (SPTS) triangle model. The basic assumption of this feature
space is that a given satellite pixel for cropland or grassland will undergo distinct vegetation cover and SSM status due to natural growth and soil moisture dynamics over a relatively long period. Unique triangles for 44 sites in two networks of the International Soil Moisture Network (ISMN)—the TxSon (US) dominated by grassland and REMEDHUS (Spain) dominated by cropland—were constructed based on Landsat data over a
period of ∼10 years (2013–2023). Compared to the traditional triangle model, the proposed model reveals enhanced skills for SSM retrieval, with a decrease in root-mean-square error (RMSE) by 13.5% (∼0.050 m3/m3) over the study sites.

Journal of Hydrology, 2025
Soil moisture is a critical component of the global land-surface hydrological cycle, significantl... more Soil moisture is a critical component of the global land-surface hydrological cycle, significantly impacting fields such as meteorology, agriculture, and water resource management. Understanding the spatiotemporal variability of global soil moisture and its dominant driving factors is essential for addressing global climate change and
mitigating extreme climate events. This study investigates the spatiotemporal variability of the latest version of the satellite-based global soil moisture (ESA CCI v09.1) and its dominant driving factors across different temporal scales from 2001 to 2020. The results reveal that short-term scales (8-day and monthly) show higher variability, reflecting rapid climate events and soil responses, while long-term scale (annual) demonstrates more stable patterns. On an annual scale, over 5% of the global land area experienced significant drying, while another 5%
showed increased wetness. Significant spatial differences in soil moisture were observed across various climate zones and latitudes. Using the Generalized Additive Model, the dominant factors influencing soil moisture trends were identified for each grid. On an 8-day scale, vapor pressure deficit is the primary driver factor in most regions, whileevapotranspiration plays a key role in tropical areas. At the monthly scale, vapor pressure deficit influences high latitude regions, whereas precipitation is the main factor at low latitudes. The combined effect of dominant factors on soil moisture is stronger in low latitudes and weaker in high latitudes. These findings improve our understanding of soil moisture dynamics and offer valuable insights for managing water resources and mitigating the impacts of extreme climate events.

Journal of Hydrology, 2025
The demand for accurate and reliable estimates of root zone soil moisture (RZSM) has been increas... more The demand for accurate and reliable estimates of root zone soil moisture (RZSM) has been increasing because of the growing need to address global concerns, including climate change and food security. In recent decades, significant advances have been made for inferring RZSM from remotely sensed observations, providing many methods and products that are available for Earth science fields. However, there are conflicting views in the recent literature regarding the accuracy of these methods due to regional differences in climate, soil, and vegetation conditions, as well as variations in parameterization and calibration approaches. These techniques have not been adequately discussed and documented in the literature. This article comprehensively reviews the satellite-based RZSM estimation methods (however some methods are not exclusively remote sensing-based, but in theory satellite data can be applicable to them), discusses their basic principles, and highlights their strengths, weaknesses, and potential research directions. We categorize these methods into two groups: those that estimate RZSM with knowledge of surface soil moisture (SSM) and those that estimate RZSM without SSM knowledge. Although these methods show varying levels of accuracy, periodic review required to address neglected assumptions, modify algorithms, and develop new ones in line with technological advancements of the 21st Century. In addition, we adequately describe and compare the major satellite-based global RZSM products at present to understand their global and local patterns and uncover existing problems. This review will serve as a reference for scientists in various fields to make informed decisions on the preferred methods for estimating RZSM from remote sensing measurements.

FUDMA Journal of Sciences (FJS) , 2021
The present study compared the performance of two different models for streamflow simulation name... more The present study compared the performance of two different models for streamflow simulation namely: Soil Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN). During the calibration periods, the Nash-Sutcliff (NS) and Coefficient of Determination (R2) for SWAT was 0.74 and 0.81 respectively, whereas for ANN, it was 0.99 and 0.85 respectively. The ANN performs better during the validation period as the result revealed with NS and R2 having 0.98 and 0.89 respectively, while for the SWAT model it was 0.71 and 0.74 respectively. Based on the recommended comparison of graphical and statistical evaluation performances of both models, the ANN model performed better in estimating peak flow events than the SWAT model in the Upper Betwa Basin. Furthermore, the rigorous time required and expertise for calibration of the SWAT is much less as compared with the ANN. Moreover, the results obtained from both models demonstrate the performances of the models in terms of NS and R2 and other model performance indices were satisfactory. Hence, the ANN (black-box model) might emerge as a faster model to implement on water resources management especially in data scarce basins.

The most recent groundnut varieties registered and released in Nigeria are SAMNUT 24, SAMUT 25 an... more The most recent groundnut varieties registered and released in Nigeria are SAMNUT 24, SAMUT 25 and SAMNUT 26. Using appropriate sampling procedures, a total of 224 representatives of farm-families were interviewed with 112 from administrative units where a development project is being implemented (PLGA), and 112 from administrative units where project interventions are absent (NPLGA). Results of the study reveal that improved groundnut varieties are becoming part of a multitude of groundnut varieties being cultivated by farmers in PLGA and NPLGAs. Amongst the improved groundnut varieties, SAMNUT 24 was being planted by 39% and 28% of households in PLGA and NPLGA, respectively. Similarly, amongst the varieties described as local, Ex-dakar is grown by 31% and 35% of households in PLGA and NPLGA, respectively. Five underlying factors were found to drive adoption decisions: farming experience, age, education, access to (improved seeds and extension services) and household size. Beyond the combined use of seeds of improved groundnut varieties and accompanying management practices, using the right combination of inputs to optimize financial gains remains a challenge to the households involved in the study.

FUDMA JOURNAL OF SCIENCES
Ensuring good management and sustainability of natural resources is paramount for future generati... more Ensuring good management and sustainability of natural resources is paramount for future generations to thrive and live in cleaner and safer environment. This research examines the land use/land cover changes over three decades (1990 to 2019) in Potiskum using geospatial techniques. The Land use and land cover changes of the years 2010 and 2019 showed a continuous trend of vegetation being converted to cultivated areas while cultivated areas are converted to built-up areas. The findings show significant changes in vegetation cover across the study area between 1990 and 2019. Specifically, the years 2010 and 2019 witnessed a significant reduction in vegetation cover of 38% compared to 1990 and 2000 which reveals a decrease of 14.5%. From 2000 to 2010, a decrease of 8% in the vegetation cover was found. Cumulatively, the vegetation loss in the study area was found to be 60.5% between 1990 and 2019. This is highly significant and almost irreversible due to the fragile nature of the env...

Journal of Conflict Resolution and Social Issues, Jul 27, 2021
The increasing demand for natural land resources to sustain the ever-growing human population and... more The increasing demand for natural land resources to sustain the ever-growing human population and the physio-environmental challenges associated with meeting up such demand makes studies like this necessary. This research examined the connections between the sharply undulating irregular terrains of Dutsin-Ma region and socioeconomic activities to ascertain the extent of the relationship and assess adaptation strategies for effective development. Appropriate data collection tools that deliver both qualitative and quantitative outcomes were utilized towards establishing geo-spatial trends of the study area. Data collection methods included extensive and intensive field work, review of existing documents; interviews were conducted with relevant stakeholders and questionnaires were administered in purposively selected areas. Geo-spatial techniques were used to analyse satellite images and Digital elevation Models to capture and visualize the nature of the terrain and landscape. Association and repulsion of different activities with these landscapes were also mapped. The research was able to establish that the relief of the area generally ranged between about 450m to about 650m above sea level. The eastern part of the region around areas like Kusada and Kankia have a generally higher elevation, but pockets of high, rugged undulating surfaces exist around Dutsin-Ma, Kurfi, Safana, Batsari and parts of Batagarawa. The implication of this irregular sharp terrains was observed on the field to manifest in settlement patterns, transportation networks and agricultural land uses. Settlements in Birchi village, Kurfi town, Tsaskiya village, Ummadau and even in central parts of Dutsin-Ma town have been affected. It is recommended that the Katsina State and Federal Governments should make necessary policies to cater for communities affected by rugged terrains in order to improve their conditions of living.

Journal of Toxicology and Environmental Health Sciences, 2020
The kernel of groundnut and groundnut-based products are easily contaminated by aflatoxin: a myco... more The kernel of groundnut and groundnut-based products are easily contaminated by aflatoxin: a mycotoxin produced by the fungus Aspergillus flavus and A. parasiticus. A total of 526 samples of groundnut and groundnut-based products were collected from six states in Nigeria namely Kano, Jigawa, Katsina, Kebbi, Sokoto and Benue States and analyzed for Aflatoxin B1 (AfB1) contamination using the Enzyme-linked Immunosorbent Assay (ELISA) technique. Results of the analysis revealed that both groundnut kernel and processed products had varying levels of AfB1 contamination. While AfB1 contamination levels varied between 7.82 and 12.33 µg/kg in kernels of local groundnut varieties, they ranged between 3.79 and 6.79 µg/kg in those of improved groundnut varieties. Mean AfB1 levels in groundnut-based products ranged from 12.30 to 99.37 µg/kg, with the highest recorded in kuli-kuli-a by-product of groundnut oil processing. Variability between mean AfB1 contamination levels in groundnut kernels of improved and local varieties were significant while no statistical difference was found between mean AfB1 contamination levels in groundnut kernels between/amongst the states. Outcomes of the study suggest that an integrated approach including the use of improved groundnut varieties, appropriate crop management practices and awareness creation on food safety, and notably on aflatoxin, could mitigate contamination in the groundnut value chain.

International Journal of Multidisciplinary Research and Development, 2015
Abstract
Total heavy metals concentrations for Cu, Pb, Zn, Mn, Ni and Fe were evaluated in soil... more Abstract
Total heavy metals concentrations for Cu, Pb, Zn, Mn, Ni and Fe were evaluated in soils and surface water. Samples collected from two different mine sites A (old mines) and B (new mines) analyzed using Atomic Absorption Spectrophotometer. From the
analysis, it was observed that except for Cu and Fe, at 50-100m from source, total trace metal concentrations were higher at the mines location B than in the mines location A. Cd was not detected, except in surface water samples after extraction with
APDC/MIBK. Based on the findings, concentrations of these metals were above the limits specified for agricultural soils, except Cu, which was within the limits. The results also revealed that the concentrations of these metals in surface water samples were
above the recommendation limits of World Health Organization (WHO) for drinking water.

International Journal of Scientific & Engineering Research, 2015
Surface soil water content (surface moisture availability) is the principal indicator of soil phy... more Surface soil water content (surface moisture availability) is the principal indicator of soil physical fertility. A simplified geometric method is presented for estimating surface soil water content in Allahabad district using remotely sensed multispectral satellite data (Landsat 7ETM+). Surface radiant temperature and Normalized Difference Vegetation Index (NDVI)/Fractional vegetation cover were derived from optical/thermal satellite imagery. The method utilizes the relationship between these satellite measurements to infer surface soil water content. The derived surface soil water content values were correlated with ground measured volumetric soil water content. A poor correlation coefficient was found to exist (R2 < 0.2) on all the dates under study, presumably indicating that soil surface water content has become decoupled from the soil water content at deeper layers. Surface soil water content maps were created to show spatial and temporal variability in surface soil water c...

Net Journal of Agricultural Science
The most recent improved groundnut varieties with farmers in Nigeria are SAMNUT 23, SAMNUT 24, SA... more The most recent improved groundnut varieties with farmers in Nigeria are SAMNUT 23, SAMNUT 24, SAMNUT 25 and SAMNUT 26. Amongst other things, this paper summarises outcomes of an adoption survey of these varieties in Sokoto and Kebbi States of Northwestern Nigeria. A total of 110 respondents were selected from administrative units where a donor funded project is being executed (coded herein as PLGA) and 110 from administrative units where project actions are absent (coded herein as NPLGA). The survey reveals that improved groundnut varieties are being grown amidst several other varieties designated as local. While SAMNUT 24 is being grown by 39% of respondents in PLGA and 19% of those in NPLGA, Kampala (a local groundnut variety) is being planted by 35 and 40% of respondents in PLGA and NPLGA, respectively. Farming experience, level of education and household size were found to influence household decisions to adopt groundnut varietal technologies and accompanying crop management practices at 1, 5 and 10% levels of significance. Gross Profit Margins in PLGA and NPLGA were 66,854 Naira (or $219) and 23,744 Naira (or $78), respectively, indicating that smallholder farmers could make nearly 64% additional cash incomes by adopting improved groundnut technologies.

Remote Sensing, 2020
We assess the validity of the surface moisture availability parameter (Mo) derived from satellite... more We assess the validity of the surface moisture availability parameter (Mo) derived from satellite-based optical/thermal measurements using the simplified triangle method. First, we show that Mo values obtained from the simplified triangle method agree closely with those generated from a soil/vegetation/atmosphere/transfer (SVAT) model for scenes over a field site at the Allahabad district, India. Next, we compared Mo values from the simplified triangle method for these same overpass scenes with surface soil water content measured at depths of 5 and 15 cm at this field site. Although a very weak correlation exists between remotely sensed values of Mo for the full scenes and measured soil water content measured at both depths, correlations increasingly improve for the 5 cm samples (but not for the 15 cm samples) as pixels were limited to increasingly smaller vegetation fractions. We conclude that the simplified triangle method would yield reasonable values of Mo and demonstrate good a...

Journal of Geoscience and Environment Protection, 2016
Soil surface wetness is indispensable land surface parameter in agriculture, hydrology and enviro... more Soil surface wetness is indispensable land surface parameter in agriculture, hydrology and environmental engineering. This paper explores the relationship between surface radiant temperature and fractional vegetation cover derived from satellite imagery to estimate soil surface wetness (triangle method) in Allahabad district. The pixel distributions create triangular shapes because the range of surface radiant temperature decreases as the amount of vegetation cover increases and sufficient number of pixels exists. A very weak correlation is found between the simulated soil surface wetness and ground measured soil moisture at deeper soil layers (R 2 < 0.15) on all the dates under investigation. This is because the drying rates at the surface discontinue to be linearly correlated to that at lower levels (depths). The standing water pixels distort the shape of the triangle especially at lower left edge of the triangle. This distortion is removable. The spatial and temporal inhomogeneity of soil surface wetness is examined.

International Journal for Scientific and Engineering Research, 2017
The Urban Heat Island (UHI) effect is a phenomenon of higher atmospheric and surface temperatures... more The Urban Heat Island (UHI) effect is a phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in surrounding rural areas happening majorly as a result of urbanisation and industrialisation. The effect of urbanisation on the occurrence of UHI in Kano metropolis was investigated. Landsat images of the study area for the years of 1986, 1998, 2006 and 2016 sourced from the archives of the United States Geological Survey (USGS) were utilised in this study. Land Surface Temperature (LST) and Land Use/Land Cover (LULC) maps for the years of 1986, 1996, 2006 and 2016 were estimated using Model Maker in Earth Resource Development Assessment System (ERDAS) Imaging 14 software. The urban city centre exhibit higher surface temperatures compared to its suburban counterparts thus, indicating the presence of the Surface UHI over Kano Metropolis. Urbanisation accounted for 80.5% increment in the LST of Kano Metropolis, thus indicating a very strong positive relationship between urbanisation and UHI. Conclusively, urbanisation is identified as the major factor that leads to the occurrence of surface UHI in Kano Metropolis. Recommendations include afforestation programmes, adoption of green and cool roofing technologies, proper spacing between houses, and accommodation of green areas and open spaces and continuous monitoring of weather events.
Conference Presentations by Abba Aliyu Kasim

Association of Nigerian Geographers 60th Annual Conference, 2019
The potentials of vegetation cover in reducing the Urban Heat Island over Kano metropolis and its... more The potentials of vegetation cover in reducing the Urban Heat Island over Kano metropolis and its environs, Nigeria was investigated. Satellite images of the study area for the years of 2016 and 2018 sourced from the archives of the United States Geological Survey (USGS) were utilised in this study. Land Surface Temperature (LST) for both years were estimated from thermal bands of Landsat 8 using Model Maker in Earth Resource Development Assessment System (ERDAS) Imagine 14 software. Land Use/Land Cover (LULC) maps were derived from optical bands of Sentinel 2A. The LST over Kano State in 2018 has declined as compared to what it was in 2016 by about 4.84°C. Vegetation cover has increased from 451.74km2 in 2016 to 549.78km2 in 2018, indicating a positive change of 98.04km2, with an annual increment rate of 49.02km2. Findings revealed that increased vegetation cover is one of the major factor accounting for a drop in the LST. Vegetation cover has thus been identified to possess enormous potentials for city cooling. Recommendations include sustained afforestation activities, harnessing the potentials of urban agriculture, green and cool roofing technologies, and adequate house spacing as some of the strategies to be synergised and adopted into city planning and management, in order to effectively reduce and mitigate the Urban Heat Island effects in urban areas.
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Papers by Abba Aliyu Kasim
However, the traditional LST-VI triangle models inherently suffer from two major drawbacks. First, the subjective requirements for a sufficient number of pixels are characterized by a wide range of vegetation and SSM under uniform atmospheric conditions. Second, this is the need for date-to-date calibration. To overcome these limitations, the present study proposed a novel scheme of the feature space, the single pixel in time-series (SPTS) triangle model. The basic assumption of this feature
space is that a given satellite pixel for cropland or grassland will undergo distinct vegetation cover and SSM status due to natural growth and soil moisture dynamics over a relatively long period. Unique triangles for 44 sites in two networks of the International Soil Moisture Network (ISMN)—the TxSon (US) dominated by grassland and REMEDHUS (Spain) dominated by cropland—were constructed based on Landsat data over a
period of ∼10 years (2013–2023). Compared to the traditional triangle model, the proposed model reveals enhanced skills for SSM retrieval, with a decrease in root-mean-square error (RMSE) by 13.5% (∼0.050 m3/m3) over the study sites.
mitigating extreme climate events. This study investigates the spatiotemporal variability of the latest version of the satellite-based global soil moisture (ESA CCI v09.1) and its dominant driving factors across different temporal scales from 2001 to 2020. The results reveal that short-term scales (8-day and monthly) show higher variability, reflecting rapid climate events and soil responses, while long-term scale (annual) demonstrates more stable patterns. On an annual scale, over 5% of the global land area experienced significant drying, while another 5%
showed increased wetness. Significant spatial differences in soil moisture were observed across various climate zones and latitudes. Using the Generalized Additive Model, the dominant factors influencing soil moisture trends were identified for each grid. On an 8-day scale, vapor pressure deficit is the primary driver factor in most regions, whileevapotranspiration plays a key role in tropical areas. At the monthly scale, vapor pressure deficit influences high latitude regions, whereas precipitation is the main factor at low latitudes. The combined effect of dominant factors on soil moisture is stronger in low latitudes and weaker in high latitudes. These findings improve our understanding of soil moisture dynamics and offer valuable insights for managing water resources and mitigating the impacts of extreme climate events.
Total heavy metals concentrations for Cu, Pb, Zn, Mn, Ni and Fe were evaluated in soils and surface water. Samples collected from two different mine sites A (old mines) and B (new mines) analyzed using Atomic Absorption Spectrophotometer. From the
analysis, it was observed that except for Cu and Fe, at 50-100m from source, total trace metal concentrations were higher at the mines location B than in the mines location A. Cd was not detected, except in surface water samples after extraction with
APDC/MIBK. Based on the findings, concentrations of these metals were above the limits specified for agricultural soils, except Cu, which was within the limits. The results also revealed that the concentrations of these metals in surface water samples were
above the recommendation limits of World Health Organization (WHO) for drinking water.
Conference Presentations by Abba Aliyu Kasim
However, the traditional LST-VI triangle models inherently suffer from two major drawbacks. First, the subjective requirements for a sufficient number of pixels are characterized by a wide range of vegetation and SSM under uniform atmospheric conditions. Second, this is the need for date-to-date calibration. To overcome these limitations, the present study proposed a novel scheme of the feature space, the single pixel in time-series (SPTS) triangle model. The basic assumption of this feature
space is that a given satellite pixel for cropland or grassland will undergo distinct vegetation cover and SSM status due to natural growth and soil moisture dynamics over a relatively long period. Unique triangles for 44 sites in two networks of the International Soil Moisture Network (ISMN)—the TxSon (US) dominated by grassland and REMEDHUS (Spain) dominated by cropland—were constructed based on Landsat data over a
period of ∼10 years (2013–2023). Compared to the traditional triangle model, the proposed model reveals enhanced skills for SSM retrieval, with a decrease in root-mean-square error (RMSE) by 13.5% (∼0.050 m3/m3) over the study sites.
mitigating extreme climate events. This study investigates the spatiotemporal variability of the latest version of the satellite-based global soil moisture (ESA CCI v09.1) and its dominant driving factors across different temporal scales from 2001 to 2020. The results reveal that short-term scales (8-day and monthly) show higher variability, reflecting rapid climate events and soil responses, while long-term scale (annual) demonstrates more stable patterns. On an annual scale, over 5% of the global land area experienced significant drying, while another 5%
showed increased wetness. Significant spatial differences in soil moisture were observed across various climate zones and latitudes. Using the Generalized Additive Model, the dominant factors influencing soil moisture trends were identified for each grid. On an 8-day scale, vapor pressure deficit is the primary driver factor in most regions, whileevapotranspiration plays a key role in tropical areas. At the monthly scale, vapor pressure deficit influences high latitude regions, whereas precipitation is the main factor at low latitudes. The combined effect of dominant factors on soil moisture is stronger in low latitudes and weaker in high latitudes. These findings improve our understanding of soil moisture dynamics and offer valuable insights for managing water resources and mitigating the impacts of extreme climate events.
Total heavy metals concentrations for Cu, Pb, Zn, Mn, Ni and Fe were evaluated in soils and surface water. Samples collected from two different mine sites A (old mines) and B (new mines) analyzed using Atomic Absorption Spectrophotometer. From the
analysis, it was observed that except for Cu and Fe, at 50-100m from source, total trace metal concentrations were higher at the mines location B than in the mines location A. Cd was not detected, except in surface water samples after extraction with
APDC/MIBK. Based on the findings, concentrations of these metals were above the limits specified for agricultural soils, except Cu, which was within the limits. The results also revealed that the concentrations of these metals in surface water samples were
above the recommendation limits of World Health Organization (WHO) for drinking water.