Environmental Earth Sciences最新文献

{"title":"Integrating surface reflectance from multispectral satellite imagery and GIS-enabled LiDAR-derived techniques for sinkhole hazard detection","authors":"Ronald J. Rizzo,&nbsp;L. Sebastian Bryson","doi":"10.1007/s12665-025-12212-5","DOIUrl":"10.1007/s12665-025-12212-5","url":null,"abstract":"<div><p>Sinkhole hazard mapping using automated visual techniques is challenging because of the difficulty in distinguishing solution depressions from non-sinkhole depressions, such as streams, channels, or man-made circular structures in digital images. While past researchers have proposed semi-automated visual techniques for identifying solution depressions, these methods typically entail a manual visual processing step in which actual sinkhole formations are manually identified in a given geologic formation to establish a basic reference map that is subsequently applied to other areas in the specified geologic formation. This two-step process is lengthy and undermines the purpose of automated mapping. Using surface reflectance data from multispectral satellite imagery allows for identifying carbonate composition lithological units in a digital image. This study proposes integrating multispectral remote sensing with geological analysis to uncover crucial spectral patterns linked to surface mineralogy and environmental conditions associated with sinkhole formations. This integration aims to effectively identify the presence of sinkhole formations while excluding non-sinkhole artifacts from the analysis in a genuinely automated workflow. A crucial aspect of this study involved integrating high-resolution data from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) imagery to distinguish rock units in a predominantly karst terrain for identifying surface depressions. In addition, we incorporated attributes covering morphometric, geomorphic, and physical soil properties derived from LiDAR-based topographic depressions. Prior studies have utilized supervised learning methods within machine learning frameworks on datasets containing confirmed sinkholes and non-sinkholes to improve the accuracy of mapping predictions. We utilized three machine learning techniques—Linear Regression, Random Forest, and Gradient Boosting—on the features database to conduct a comparative analysis, aiming to assess the enhancement of the methodology’s effectiveness compared to other studies. We aimed to improve the classification of crucial features and minimize the need for an additional manual visual inspection step to distinguish non-sinkhole formations from potential sinkhole boundaries identified. Among these methods, Random Forest proved to be the most appropriate for recognizing features that directly indicate sinkholes. This approach yielded an impressive Receiver Operating Characteristic (ROC) curve of 92%, showcasing its effectiveness in mapping sinkholes.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Peak discharge amplication of debris flows in colluvial channels with varying cross-sections","authors":"Lan Ning,&nbsp;Kaiheng Hu,&nbsp;Pu Li,&nbsp;Haiguang Cheng,&nbsp;Shuang Liu,&nbsp;Qiyuan Zhang","doi":"10.1007/s12665-025-12232-1","DOIUrl":"10.1007/s12665-025-12232-1","url":null,"abstract":"<div><p>Debris flows can significantly amplify both discharge and destructive potential as they flow over a colluvial channel with non-uniform cross-sections. However, the mechanisms driving this growth remain largely unclear. In this study, we examined the influence of channel narrowing or widening on debris flow dynamics through in-situ investigations following the debris flow events in Western China, specifically in Zhouqu in 2010 and Heixiluo in 2020. By introducing two dimensionless parameters, namely the discharge amplification factor and channel narrowness, we found a significant correlation between peak discharges of the debris flows and channel widths. When the channel narrows, the increase in flow velocity leads to flow amplification, intensifying the erosive force of the debris flow and causing more severe localized failure of the bed sediments. In contrast, when the channel widens, fluid dispersion results in a decrease in flow velocity, reducing the overall scale and destructive power of the debris flow. Based on experimental measurements, an exponential relationship between the flow amplification factor and channel narrowness was determined using regression analysis. This research may aid in comprehending the dynamics of debris flow and in the evaluation and mitigation of associated disasters.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Groundwater quality assessment for irrigation in coastal region (Güzelyurt), Northern Cyprus and importance of empirical model for predicting groundwater quality (electric conductivity)","authors":"Hüseyin Gökçekuş,&nbsp;Youssef Kassem,&nbsp;Temel Rizza","doi":"10.1007/s12665-025-12190-8","DOIUrl":"10.1007/s12665-025-12190-8","url":null,"abstract":"<div><p>Variations in precipitation patterns, the exact moment of aquifer recharge, and methods of groundwater extraction and usage all contribute to variations in the quality of groundwater used for irrigation between regions. Therefore, the present study aims to evaluate the seasonal groundwater suitability for irrigation purposes in the Güzelyurt region, Northern Cyprus for the first time using indexical techniques. The results demonstrated that <span>({Na}^{+})</span> values, which ranged from 6 to 15 mg/l, were within allowable limits. Besides, the concentrations of <span>({Ca}^{2+})</span> and <span>({Cl}^{-})</span> that ranged from 2 to 7 mg/l and 4 to 12 mg/l, respectively, were appropriate for irrigation. However, <span>({Mg}^{2+})</span> concentrations between 4 and 9 mg/l exceed FAO requirements. The <span>({N{O}_{3}}^{-})</span> levels of 20–80 mg/l raised concerns about pollution and salinity. Furthermore, <span>({HC{O}_{3}}^{-})</span> and <span>({S{O}_{4}}^{2-})</span> concentrations fell between 3 and 8 mg/l and 2 and 5 mg/l, respectively, within safe limits. Additionally, the results showed that most of the samples are in the “suitable” or “excellent” category, which means that the water quality is generally appropriate for irrigation, according to the IWQI. However, there are observable declines in water quality after the monsoon season, especially in sodicity and sodium levels, which can negatively impact soil quality and crop production. This highlights the significance it is to maintaining irrigation systems and ensuring agricultural yield over time by effectively controlling water quality. Moreover, hydrogeological features, irrigation return water, maritime invasion, and aquifer communication can all be connected to the region’s groundwater salinity as identified by Electric Conductivity (EC). Therefore, a novel method based on Multi-Layer Perceptron Neural Network (MLP), K-Nearest Neighbor Algorithm (KNN), Support Vector Regression (SVR), and Non-Linear Neural Network Ensemble (NL-NNE) models optimized by Whale Optimization Algorithm (WOA) is proposed in this work for determining seasonally EC as a function of groundwater quality, groundwater depth, and weather parameters. The results demonstrated that the NL-NNE may increase the average performance of a single model during the verification phase. This showed that NNE’s potential ability to solve nonlinear processes supported its resilience and reliability in modeling EC.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12665-025-12190-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of hillslope positions and soil properties on soil micronutrient availability in steep terraced croplands of north-western Himalayas","authors":"K. R. Sooryamol,&nbsp;Sankar Mariappan,&nbsp;Suresh Kumar,&nbsp;Anu David Raj","doi":"10.1007/s12665-025-12222-3","DOIUrl":"10.1007/s12665-025-12222-3","url":null,"abstract":"<div><p>Soil micronutrients are critical for plant growth and reproductive processes to complete their key functionality of the life cycle. The availability of micronutrients in hilly and mountainous regions is influenced by topography-controlled soil processes at various hillslope positions. However, the ruggedness of terrains makes it challenging to gather comprehensive data on soil micronutrient status, which in turn limits effective micronutrient management. This issue is particularly significant to the acidic soils of the North-western Himalayas, where agriculture is the primary source of livelihood. Therefore, this study was designed to explore the availability and variability of major micronutrients (Zn, Cu, Fe, and Mn) in the soils of hilly and mountainous landscapes across five different hillslope positions and various cropping systems, and to examine their relationship with physico-chemical properties of soils. The study revealed that all micronutrients were present in sufficient quantities across the hillslope positions. However, a slight tendency toward zinc deficiency was observed at some hillslope positions. Principal component analysis (PCA) highlighted the importance of micronutrients Fe, Mn, Zn, and Cu to pH, organic matter, sand and silt contents in the landscape. It revealed that pH and organic matter were critical factors influencing micronutrient availability, with higher levels of organic matter generally enhancing the availability of these micronutrients. The study further concluded that a complex interplay of topography, soil management practices, and cropping systems influence soil micronutrient availability. The variability observed at the hillslope scale highlights the need for site-specific management approaches. Understanding these factors is crucial for optimizing soil micronutrient management and ensuring sustainable agricultural productivity in the soil erosion-prone fragile Himalayan region.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recovery of trace elements in sediments from the alpine mountain stream affected by a severe flash flood in the Tatra Mountains","authors":"Zacher Šimon,&nbsp;Solár Jaroslav","doi":"10.1007/s12665-025-12215-2","DOIUrl":"10.1007/s12665-025-12215-2","url":null,"abstract":"<div><p>Sediments in mountain streams are an essential component of aquatic ecosystems, providing nutrients and life space for many organisms. In this study, we focused on one alpine—mountain stream (in the Tatra Mountains, Slovakia) affected by a huge summer flash flood in 2018. We analyzed the content of trace elements (Hg, K, Ca, Ti, Cr, Mn, Fe, Zn, Rb, Sr, Zr, Mo, Ba and Pb) in sand-sized sediments, which were collected regularly in monthly intervals at five different sites determined by vegetation zones over a period of four years. Because we hypothesized that flash floods are one of the essential factor in long-term maintained of oligotrophic profile of mountain streams, we tried to find out if contents of trace elements in sediments from temporal aspect will increase after flood, and which season or part of the stream support recharge of trace elements in sediments. The results pointed to a main environmental factor (from PCA) which explains the gradual restoration of trace element accumulation in sediments after the flood. The seasonal pattern of this factor shows that the stream flow in spring and precipitation in autumn significantly influenced this increase. In addition, it was discovered that minerals present in granite probably support a higher enrichment of sediments with trace elements than minerals present in various Mesozoic sediments. This indicated that unstable bare land (rocks, debris and screes) and sparsely vegetated areas in higher elevations are crucial for the supply and release of trace elements to lowlands.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12665-025-12215-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-temporal evaluation of ionospheric disturbances before, during and after earthquakes using differential rate of TEC (DROT) from GPS measurements","authors":"Secil Karatay,&nbsp;Feza Arikan,&nbsp;Atinc Pirti","doi":"10.1007/s12665-025-12216-1","DOIUrl":"10.1007/s12665-025-12216-1","url":null,"abstract":"<div><p>This study presents a comprehensive spatio-temporal analysis of ionospheric disturbances associated with seismic activity by applying the Differential Rate Of TEC (DROT) algorithm to GPS-based Total Electron Content (TEC) data. The investigation covers ten major earthquakes (Mw 9.0–5.6), examining ionospheric variability across pre-seismic, co-seismic, and post-seismic periods, alongside geomagnetically quiet and disturbed days. Results reveal that ionospheric perturbations are not confined to the pre-earthquake phase; significant anomalies are also observed during and up to six days after the seismic events. On earthquake days, DROT values predominantly cluster between 60 and 70%, indicating large-scale disturbances, while medium-scale disturbances (50–60%) are prevalent in the days leading up to and following the earthquakes. Spatial analysis shows stronger disturbances within 500 km of epicenters, diminishing with distance. The findings support the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model, highlighting the sustained influence of seismic processes on the ionosphere. By distinguishing between seismically and geomagnetically induced disturbances, this study underscores the potential of DROT as a tool for real-time ionospheric monitoring and contributes to efforts in earthquake precursor detection and early warning systems.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12665-025-12216-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting thermal conductivity of granite subjected to high temperature using machine learning techniques","authors":"Mohua Bu,&nbsp;Cheng Fang,&nbsp;Pingye Guo,&nbsp;Xin Jin,&nbsp;Jiamin Wang","doi":"10.1007/s12665-025-12224-1","DOIUrl":"10.1007/s12665-025-12224-1","url":null,"abstract":"<div><p>The evolution and accurate prediction of thermal conductivity (TC) of granite subjected to high temperature is of great significance for many geological and underground engineering. In this study, the relationship between TC and temperature, mineral composition, porosity and density after high temperature was studied experimentally. Subsequently, totally 229 measurements containing four input variables (i.e., temperature, porosity, density and quartz content) were collected, and a new prediction model for granite TC was proposed using back propagation neural network (BPNN-TCPM). The results indicate that the TC of granite is strongly dependent on temperature and decreases with the increase of temperature. The TC is inversely proportional to porosity and positively related to density, the effect of temperature on the mineral content can be ignored, but the damage of mineral structure can significantly affect the heat conduction capacity of granite, which also demonstrate that the initiation and propagation of thermally-induced cracks in granite during thermal treatment is the main reason for the deterioration of TC. More importantly, machine learning (ML) techniques could prove to be highly accurate and efficient new methods for predicting the TC of granite. The prediction results on the testing data set show that the average absolute error (<i>MAE</i>), root mean square error (<i>RMSE</i>), and coefficient of determination (<i>R</i>²) of the BPNN-TCPM are 0.0286, 0.0765 and 0.9785, respectively, and the prediction accuracy is better than the other 7 ML models and 8 temperature-dependent empirical models of rock TC. This also means that considering the coupled effects of multiple factors can help improve the accuracy of granite TC prediction. In addition, a graphical user interface (GUI) is developed for practical application, which can obtain single or batch TC data by directly inputting variables.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of homogeneous rainfall regions and spatial-temporal variability in the Teesta River Basin","authors":"Prasanya Sarkar,&nbsp;Shasanka Kumar Gayen","doi":"10.1007/s12665-025-12219-y","DOIUrl":"10.1007/s12665-025-12219-y","url":null,"abstract":"<div><p>This study explores rainfall regionalization to understand spatial and temporal variations in the Teesta River Basin using 122 years (1901–2022) of monthly precipitation data from the Indian Meteorological Department (IMD) with 23 rain-gauge stations. The seasonality index (SI), the precipitation concentration index (PCI), the innovative trend analysis (ITA), the Mann-Kendall test (MK) family, and the cluster analysis (K-means and fuzzy) were used to the annual precipitation data to compare and visualize temporal patterns. Spatial variability was discovered by trend analysis using the ITA and MK tests. Results indicate spatial variability in trends, with significant positive trends in annual rainfall observed at stations G4, G7, G9, and G13, while stations G6 and G10 show negative trends. According to the MK family test, 8 out of 23 rain gauge sites in the Teesta River Basin displayed a monotonic trend in rainfall. The ITA indicates that at a significance level of 99%, 13 stations exhibit increasing trends in historical annual rainfall, whereas eight stations demonstrate decreasing trends. Additionally, trends in rainfall at two stations are deemed not significant. By employing rainfall regionalization techniques like clustering (fuzzy C-means or K-means), study area stations are grouped into two clusters with similar characteristics. Stations in the upper basin are included in Cluster 1, while stations in the lower basin are covered by Cluster 2. Silhouette width analysis was used to validate the clustering results. Researchers and policymakers can benefit from rainfall regionalisation by better understanding the variability of precipitation within river basins.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the propagation law of acid fracturing in cave carbonate rock","authors":"Haifeng Zhao,&nbsp;Zhiyuan Liu,&nbsp;Chaojun Yu,&nbsp;Guipeng Gan","doi":"10.1007/s12665-025-12208-1","DOIUrl":"10.1007/s12665-025-12208-1","url":null,"abstract":"<div><p>Acid fracturing technology is the main reservoir modification method of cavity carbonate rock in Tahe oilfield. However, the conditions of cavity carbonate reservoir are complicated, the mechanism of fracture and cave interaction is not clear, and the effect of acid fracturing on stimulation is not obvious. Therefore, in this paper, the interaction between acid fractures and caves under different distribution angles of different acid systems is discussed through the physical simulation experiment of true triaxial acid fracturing. The results show that: (1) The initial propagation stage of the fracture is mainly controlled by the horizontal stress difference. When the acid fracture spreads to the far well area, the acid fracture is attracted by the cave. (2) The distribution angle of acid fracture increases with the increase of the distribution angle of cave. (3) When the acid concentration increases, the acid fracture is easy to continue to propagation directly through the cave. Compared with self-generated acid and solid acid, gelling acid is easier to pass directly through the cave and has a larger propagation area when the injection conditions are fixed.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of water quality for irrigation purpose: a case study of three states in Nigeria","authors":"Samuel Dare Oluwagbayide,&nbsp;Akinyinka Akinnusotu,&nbsp;Kikelomo Mabinuola Arifalo,&nbsp;Ademola Adamu,&nbsp;Francis Olawale Abulude,&nbsp;Samson Olatunde Mabayoje,&nbsp;Amoke Monisola Kenni","doi":"10.1007/s12665-025-12221-4","DOIUrl":"10.1007/s12665-025-12221-4","url":null,"abstract":"<div><p>Both humans and animals use water for a variety of functions. However, access to drinking water and agricultural water continues to be a major problem in many areas, especially Southwest Nigeria. Based on sodium adsorption ratio (SAR), soluble sodium percentage (SSP), magnesium adsorption ratio (MAR), and exchangeable sodium percentage (ESP), this study is unique because it offers a thorough evaluation of the metal (Na, Ca, K, Mg, Cr, Mn, Cu, Pb, Cd, and Fe) levels in water samples from thirty-five (35) sites in Osun, Ondo, and Ekiti States with a range of socioeconomic activities and environmental conditions. This study’s main goal is to evaluate the metal concentrations in the water samples and decide whether or not they are suitable for irrigation. Water samples were taken from rivers and streams (10), boreholes (8), wells (15), and rain (2). Atomic Absorption Spectroscopy (AAS) was used to determine the metal content of the samples. The mean concentration of the metals showed the following results: Ca &gt; K &gt; Na &gt; Mg &gt; Fe &gt; Mn &gt; Cr &gt; Cu &gt; Pb &gt; Cd. The irrigation assessments yielded the following results: ESP (10.32), KR (0.50), MAR (17.84), SAR (8.69), and SSP (22.85). Comparing the findings of this investigation, it was found that K, Mg, Na, Ca, Pb, and Cr were below the national limit, while Cu, Cd, and Fe were marginally above the National Environmental Standards and Regulations Enforcement Agency (NESREA) limits. Similarly, it was found that the acceptable limits were exceeded by Mn, Pb, Cd, and Cr, but the limits for Na and Cu were below the World Health Organization (WHO) level. The different activities that took place in the studied locations maybe the causes of the higher levels. The irrigation water samples are safe and of high quality. According to the study’s findings, heavy metal contamination of water samples is a widespread problem in Southwest Nigeria that poses major dangers to public health. In order to guarantee safe irrigation and drinking water, the results highlight the necessity of frequent water quality monitoring, public awareness initiatives, and the adoption of stronger laws.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}