Groundwater Contamination and Risk Assessment in Greater Palm Springs DOI Open Access

Warda Khalid,

Muhammad Yousuf Jat Baloch, Asmat Ali

et al.

Water, Journal Year: 2023, Volume and Issue: 15(17), P. 3099 - 3099

Published: Aug. 29, 2023

Groundwater is an essential resource for drinking water, but its contamination with potentially toxic elements and arsenic (As) a global issue. To evaluate As levels in the Coachella Valley, US Geological Survey (USGS) collected 17 groundwater samples. This study looked into distribution, enrichment, hydrogeochemical behavior, health risks associated The comparative analysis between Greater Palm Springs similar regions, could provide valuable insights regional differences common challenges. facies showed dominance of calcium magnesium-bicarbonate-carbonate, indicating permanent hardness salt deposits residual carbonate. Gibbs plot demonstrated that chemical weathering rock-forming minerals evaporation are primary forces impacting chemistry. Geochemical modeling revealed saturation calcite dolomite, under-saturation halite. Principal component identified potential contributory sources groundwater. carcinogenic non-carcinogenic potentials arsenic, cadmium, chromium (VI), lead were calculated using human risk assessment model. For both adults children, highest mean value was observed (8.52 × 10−1), lowest cadmium (1.32 10−3). Children had cumulative from elements. Our research offers crucial baseline data assessing at level, which important reduction remediation programs. show preventative action must be taken to reduce area groundwater, particularly children.

Language: Английский

Comparison of Three Machine Learning Algorithms Using Google Earth Engine for Land Use Land Cover Classification DOI Open Access
Zhewen Zhao, Fakhrul Islam, Liaqat Ali Waseem

et al.

Rangeland Ecology & Management, Journal Year: 2023, Volume and Issue: 92, P. 129 - 137

Published: Nov. 22, 2023

Language: Английский

Citations

98
Delineation of groundwater potential zonation using geoinformatics and AHP techniques with remote sensing data DOI Creative Commons
Dechasa Diriba, Shankar Karuppannan, Tariku Takele

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(3), P. e25532 - e25532

Published: Feb. 1, 2024

Among all other valuable natural resources, groundwater is crucial for global economic growth and food security. This study aimed to delineate potential zones (GWPZ) in the Gidabo watershed of Main Ethiopian Rift. The demand supplies various applications has risen recently due rapid population upsurge. An integrated Geographical Information System, Remote Sensing, Analytical Hierarchy Process (AHP) been utilized. Eight regulating factors, including rainfall, elevation, drainage density, soil types, lineament slope, lithology, land use/land cover, have taken analysis. To assign suitable weights each factor, AHP was employed, as element contributes differently occurrence. weighted overlay analysis (WOA) technique then used ArcGIS environment integrate thematic layers generate a GWPZ map. delineated classified into five categories. poor covered 18.7 %, low 33.8 moderate 23.4 high 18.1 very 5.8 % area. Well spring data were validate model, ROC (Receiver Operating Characteristic) curve method applied. results showed good accuracy 76.8 %. result this research can be planning managing resources watershed.

Language: Английский

Citations

25
Assessing terrestrial water storage variations in Afghanistan using GRACE and FLDAS-Central Asia data DOI Creative Commons
Son K., Fazlullah Akhtar, Benjamin D. Goffin

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 55, P. 101906 - 101906

Published: July 30, 2024

Afghanistan, Central Asia. In this study, we evaluated the terrestrial water storage dynamics in Afghanistan and its five major river basins using anomalies (TWSA) from three Gravity Recovery Climate Experiment (GRACE) mascons observations JPL, CSR, GSFC processing centers, Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System – Asia (FLDAS-CA) simulation. Since 2008, due to intense prolonged drought conditions groundwater overexploitation, TWS has been decreasing at an alarming rate. The average slopes of TWSA trend for GRACE period (2003–2016) products range between − 3.6 4.8 mm/year. decrease is further exacerbated during GRACE-FO (2019–2022), ranging 20.4 30 Because heavily relied on country but human-induced change (i.e., extraction) not simulated FLDAS-CA, a significant difference could be observed FLDAS-CA results, especially following after each severe event (e.g., 2018) when substantial extraction occurred. assimilation into framework will undoubtedly have positive impact decision-makers local stakeholders preparing mitigating impacts overexploitation

Language: Английский

Citations

22
Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone DOI Creative Commons
Pingheng Li, Aqil Tariq, Qingting Li

et al.

International Journal of Digital Earth, Journal Year: 2023, Volume and Issue: 16(1), P. 3105 - 3124

Published: Aug. 10, 2023

In this research, we used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) to predict annual rate of soil loss in District Chakwal Pakistan. The parameters RUSLE model were estimated using remote sensing data, erosion probability zones determined GIS. length slope (LS), crop management (C), rainfall erosivity (R), erodibility (K), support practice (P) range from 0–68,227, 0–66.61%, 0–0.58, 495.99–648.68 MJ/mm.t.ha−1.year−1, 0.15–0.25 1 respectively. results indicate that total potential approximately 4,67,064.25 t.ha−1.year−1 is comparable with measured sediment 11,631 during water year 2020. predicted due an increase agricultural area 164,249.31 t.ha−1.year−1. study, also Landsat imagery rapidly achieve actual land use classification. Meanwhile, 38.13% region was threatened by very high erosion, where quantity ranged 365487.35 Integrating GIS helped researchers their final objectives. Land-use planners decision-makers result's spatial distribution for conservation planning.

Language: Английский

Citations

30
The analysis on groundwater storage variations from GRACE/GRACE-FO in recent 20 years driven by influencing factors and prediction in Shandong Province, China DOI Creative Commons
Wanqiu Li, Lifeng Bao, Guobiao Yao

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 9, 2024

Monitoring and predicting the regional groundwater storage (GWS) fluctuation is an essential support for effectively managing water resources. Therefore, taking Shandong Province as example, data from Gravity Recovery Climate Experiment (GRACE) GRACE Follow-On (GRACE-FO) used to invert GWS January 2003 December 2022 together with Watergap Global Hydrological Model (WGHM), in-situ volume level data. The spatio-temporal characteristics are decomposed using Independent Components Analysis (ICA), impact factors, such precipitation human activities, which also analyzed. To predict short-time changes of GWS, Support Vector Machines (SVM) adopted three commonly methods Long Short-Term Memory (LSTM), Singular Spectrum (SSA), Auto-Regressive Moving Average (ARMA), comparison. results show that: (1) loss intensity western significantly greater than those in coastal areas. From 2006, increased sharply; during 2007 2014, there exists a rate - 5.80 ± 2.28 mm/a GWS; linear trend change 5.39 3.65 2015 2022, may be mainly due effect South-to-North Water Diversion Project. correlation coefficient between WGHM 0.67, consistent level. (2) has higher positive monthly Precipitation Climatology Project (GPCP) considering time delay after moving average, similar energy spectrum depending on Continuous Wavelet Transform (CWT) method. In addition, influencing facotrs annual analyzed, including consumption mining, farmland irrigation 0.80, 0.71, respectively. (3) For prediction, SVM method analyze, training samples 180, 204 228 months established goodness-of-fit all 0.97. coefficients 0.56, 0.75, 0.68; RMSE 5.26, 4.42, 5.65 mm; NSE 0.28, 0.43, 0.36, performance model better other short-term prediction.

Language: Английский

Citations

9
Insight into land cover dynamics and water challenges under anthropogenic and climatic changes in the eastern Nile Delta: Inference from remote sensing and GIS data DOI
Youssef M. Youssef, Khaled S. Gemail,

Hafsa M. Atia

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 913, P. 169690 - 169690

Published: Dec. 30, 2023

Language: Английский

Citations

21
The use of Multispectral Radio-Meter (MSR5) data for wheat crop genotypes identification using machine learning models DOI Creative Commons
Mutiullah Jamil,

Hafeezur Rehman,

Muhammad Saqlain Zaheer

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Nov. 14, 2023

Satellite remote sensing is widely being used by the researchers and geospatial scientists due to its free data access for land observation agricultural activities monitoring. The world suffering from food shortages dramatic increase in population climate change. Various crop genotypes can survive harsh climatic conditions give more production with less disease infection. Remote play an essential role genotype identification using computer vision. In many studies, different objects, crops, cover classification done successfully, while still a gray area. Despite importance of planning, significant method has yet be developed detect varieties yield multispectral radiometer data. this study, three wheat (Aas-'2011', 'Miraj-'08', 'Punjnad-1) fields are prepared investigation radio meter band properties. Temporal (every 15 days height 10 feet covering 5 circle one scan) collected efficient Radio Meter (MSR5 five bands). Two hundred samples each acquired manually labeled accordingly training supervised machine learning models. To find strength features (five bands), Principle Component Analysis (PCA), Linear Discriminant (LDA), Nonlinear Discernment (NDA) performed besides models Extra Tree Classifier (ETC), Random Forest (RF), Support Vector Machine (SVM), Decision (DT), Logistic Regression (LR), k Nearest Neighbor (KNN) Artificial Neural Network (ANN) detailed configuration settings. ANN random forest algorithm have achieved approximately maximum accuracy 97% 96% on test dataset. It recommended that digital policymakers agriculture department use RF identify at farmer's research centers. These findings precision management specific optimized resource efficiency.

Language: Английский

Citations

20
Assessment of heavy metal accumulation in dust and leaves of Conocarpus erectus in urban areas: Implications for phytoremediation DOI
Atta Ur Rehman, Kousar Yasmeen, Fakhrul Islam

et al.

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2023, Volume and Issue: 132, P. 103481 - 103481

Published: Aug. 25, 2023

Language: Английский

Citations

18
Spatio-Temporal Analysis of Hydrometeorological Variables for Terrestrial and Groundwater Storage Assessment DOI
Muhammad Shareef Shazil, Sheharyar Ahmad, Syed Amer Mahmood

et al.

Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: 27, P. 101333 - 101333

Published: Sept. 4, 2024

Language: Английский

Citations

8
Soil erosion susceptibility mapping of Hangu Region, Kohat Plateau of Pakistan using GIS and RS-based models DOI
Fakhrul Islam, Liaqat Ali Waseem, Tehmina Bibi

et al.

Journal of Mountain Science, Journal Year: 2024, Volume and Issue: 21(8), P. 2547 - 2561

Published: Aug. 1, 2024

Language: Английский

Citations

7