Physics and Chemistry of the Earth最新文献

{"title":"Exploring deep learning models for roadside landslide prediction: Insights and implications from comparative analysis","authors":"Tiep Nguyen Viet ,&nbsp;Dam Duc Nguyen ,&nbsp;Manh Nguyen Duc ,&nbsp;Cong Cao Trong ,&nbsp;Mai Sy Hung ,&nbsp;Hiep Van Le ,&nbsp;Indra Prakash ,&nbsp;Binh Thai Pham","doi":"10.1016/j.pce.2024.103741","DOIUrl":"10.1016/j.pce.2024.103741","url":null,"abstract":"<div><p>This study undertakes a comparative analysis of four distinct deep learning models, i.e., Convolutional Neural Network (CNN), Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM), in the context of roadside landslide prediction, aiming to provide comprehensive insights into their strengths and weaknesses. A geospatial dataset from the Lai Châu province, Vietnam, with thirteen environmental factors (elevation, aspect, slope, curvature, topographic wetness index, stream power index, flow accumulation, geology, normalized difference vegetation index, maximum rainfall, average annual rainfall, and proximity to faults and rivers) and 284 road-along landslides was considered for analysis. Our modeling efforts yielded invaluable insights into the performance of these models during both training and validation phases. The DNN model emerged as the frontrunner in the training phase, boasting the highest area under the curve (AUC) of 0.94, accuracy of 87.47%, kappa of 0.748, and lowest RMSE of 0.125. However, during validation, the CNN model outshone others, exhibiting the highest AUC of 0.88 and overall accuracy of 80.00%. Despite variations in performance metrics across phases, CNN consistently demonstrated robust predictive prowess. The findings of this study underscore the significance of selecting appropriate machine learning models tailored to specific contexts and objectives. Moreover, they contribute valuable insights for decision-makers and researchers alike, ultimately aiming to enhance the safety and resilience of communities inhabiting landslide-prone areas. Moving forward, future research directions may explore ensemble methods, novel architectures, and interpretability techniques to further advance predictive accuracy and applicability in roadside landslide susceptibility modeling.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103741"},"PeriodicalIF":3.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How can agricultural water use efficiency be promoted in the North China Plain?","authors":"Yuping Bai ,&nbsp;Cuiling Zhang ,&nbsp;Xinyu Xie ,&nbsp;Yiwei Wang ,&nbsp;Yecui Hu","doi":"10.1016/j.pce.2024.103740","DOIUrl":"10.1016/j.pce.2024.103740","url":null,"abstract":"<div><div>Water resources are reliable guarantees for high quality development of agriculture in the North China Plain. Improving agricultural water use efficiency is one of the essential ways to solve agricultural water resources shortage. This study measured agricultural water use efficiency (AWUE) using a stochastic frontier analysis (SFA) model and estimated agricultural water-saving potential (AWP) for 74 prefecture-level cities in the North China Plain. The main factors that influenced AWUE were further identified by developing spatial econometric models. The results showed that: (1) From 2000 to 2020, the AWUE of the study area ranged from 0.701 to 0.755 and first rose then fell, and then leveled off. (2) Spatially, the best AWUE was in the central part, followed by the north, and the worst was in the south, and nearly 65% of prefectural cities had annual average AWUE below 0.8. (3) Significant gaps in AWUE and AWP were observed in different regions. Shijiazhuang, Anyang, Hebi and Xinxiang should be considered as key targets to improve AWUE. (4) The effective irrigation degree, per sown area annual precipitation, and annual average temperature had positive effect on AWUE. Increasing the corn sowing area appropriately and reducing the input of per sown area machinery power could also improve AWUE. Therefore, adopting deep plowing measures, developing semi-arid agriculture, and advancing water-saving irrigation technology were feasible ways to improve AWUE and contribute to sustainable agriculture in the North China Plain. These findings can provide a reference for the formulation of high-water efficiency agricultural management strategies in other similar major grain-producing areas.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103740"},"PeriodicalIF":3.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatially explicit simulation and forecasting of urban growth using weights of evidence based cellular automata model in a millennium city of India","authors":"Pankaj Kumar Yadav ,&nbsp;Varun Narayan Mishra ,&nbsp;Maya Kumari ,&nbsp;Akshay Kumar ,&nbsp;Pradeep Kumar ,&nbsp;Rajeev Bhatla","doi":"10.1016/j.pce.2024.103739","DOIUrl":"10.1016/j.pce.2024.103739","url":null,"abstract":"<div><p>The present study focuses on quantifying and simulating the future urban growth based on the land use/land cover (LULC) data created from the Landsat images of the year 1999, 2011, and 2022. These LULC maps help in analysing the expansion of urban areas over the years and forecast their potential growth in the future. The spatio-temporal processes of urban growth are quantified, and future patterns are simulated and forecasted using Weights of Evidence based Cellular Automata model built in Dinamica EGO (Environment for Geoprocessing Objects) platform. The process of urban growth was manifested through prominent contributing factors of infill expansion namely, distance to built-up areas, distance to main roads, population density, and public services etc. The model's performance was evaluated using Kappa statistics and the percentage of correct prediction (PCP) based two-way comparison method. For this purpose, the simulated map was first compared with the observed information of year 2022 using Kappa indices followed by the PCP value (90.40%) exhibiting high predictive ability of the model. These findings corroborate that the model can forecast the future urban growth scenarios effectively with reasonable accuracy. Based on the outcomes, the forecasting of future urban growth scenarios for years 2033 and 2044 was accomplished. Analysis of the LULC changes displays that urban land use will experience the highest increase. Growth in the study area is predicted to increase by 23.5% and 26.7% in year 2033 and 2044 respectively where new urban settlements can appear. The results demonstrated that an integrated geospatial model provides essential information about the pattern, simulation, and prediction of urban growth associated with various driving variables.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103739"},"PeriodicalIF":3.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing streamflow simulations with gated recurrent units deep learning models in the flood prone region with low-convergence streamflow data","authors":"Aliakbar Karamvand ,&nbsp;Seyed Abbas Hosseini ,&nbsp;Seyed Ali Azizi","doi":"10.1016/j.pce.2024.103737","DOIUrl":"10.1016/j.pce.2024.103737","url":null,"abstract":"<div><p>Highly accurate streamflow simulations are essential for water resources and river management. However, there are longstanding challenges for streamflow modeling in the hydrology field. As a result, deep learning methods have been introduced as novel tools and are being used in simulation. This paper proposes a novel approach that utilizes unconventional data preprocessing techniques to improve the accuracy of daily streamflow predictions in flood-prone regions. We applied this approach to a flood-prone area in western Iran and simulated daily streamflow using a deep learning Gated Recurrent Unit (GRU) method under various data selection scenarios. These scenarios focused on identifying the optimal combination of input variables, time steps, and outlier removal techniques. The outlier removal methods investigated in this study include Mahalanobis distance, critical section removal, Z-score, and no removal. The average rainfall of the area, data driven precipitation, Normalized Difference Vegetation Index (NDVI), surface soil moisture, groundwater baseflows, and streamflow in the hydrometric station were evaluated using correlation control method, and inputs with the lowest correlation were removed. Based on the results obtained from the deep learning models produced in the research, it was found that the GRU model, with various modified inputs using Z-score removal, had the best performance. The model had an average of Root Mean Squared Error (RMSE) at 5.24 mm and R² (Coefficient of Determination) at 0.91 during training, while during validation, it had an RMSE of 7.74 mm and R² of 0.83. Considering using relatively low convergence data in streamflow simulation in this study, it can be said that the listed scenarios showed an appropriate result in dealing with the data and recognizing the complex pattern of the daily streamflow, and the future studies will show the improvement of the GRU models if higher convergence data will be used.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103737"},"PeriodicalIF":3.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the influence of hydrogeochemical characteristics and microbial communities on monsoon dynamics in groundwater quality in north Chennai city, India","authors":"S. Syed Ahamudul Rafeek ,&nbsp;N. Mohamed Basith ,&nbsp;M. Mohamed Hanipha ,&nbsp;Meera Moydeen Abdul Hameed ,&nbsp;S. Senthilkumar","doi":"10.1016/j.pce.2024.103735","DOIUrl":"10.1016/j.pce.2024.103735","url":null,"abstract":"<div><p>The current study evaluated the physicochemical, statistical, hydrogeochemical and biological characteristics of fifty groundwater samples that were taken from bore wells and tube wells in North Chennai, Tamil Nadu, India, in the monsoon seasons of November 2021 and November 2022. For the purposes of analysis and result interpretation, APHA standard procedures were used. The mean values of Total dissolved solids (TDS), Electrical conductivity (EC), Total hardness (TH), sodium and chloride (Cl⁻) surpassed the desired threshold specified by the World Health Organization (WHO). The Pearson coefficient of interaction showed that calcium hardness and TDS (0.940), as well as sodium and TDS (0.968), have high positive correlations. The strong correlation existed between Mg-Cl, Ca-Cl, Na-Cl, Na-SO₄, Na-Mg, Na-Ca and Mg-Ca ions with reference to both monsoon periods. While Gibb's plots indicated that evaporation and rock dominance were the main types, the sodium-chloride (Na-Cl) type was primarily shown in the Piper and Chadha models. Principal Component Analysis (PCA) identified Eigenvalues with 79.09% and 80.81% of the total variance during the monsoon periods of 2021 and 2022 respectively, which indicated seawater seepage into the coastal groundwater, soil-water interaction and anthropogenic activities. Pollution reasons were also evaluated for optimal management planning to safeguard the aquifer system. Based on the study of groundwater quality carried out in the research area, the concentration of Standard Plate Count (SPC), Total Coliforms (TC) bacterial influence have exceeded the permitted criteria in the majority of the sample locations (WHO).</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103735"},"PeriodicalIF":3.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calibration and evaluation of various reference evapotranspiration estimation methods in a humid subtropical climate: A case study in Samsun Province, Türkiye","authors":"Amin Gharehbaghi ,&nbsp;Ehsan Afaridegan ,&nbsp;Birol Kaya ,&nbsp;Maryam Adhami","doi":"10.1016/j.pce.2024.103734","DOIUrl":"10.1016/j.pce.2024.103734","url":null,"abstract":"<div><p>Reference evapotranspiration is crucial for estimating plant water needs and managing resources. Simplifying the Penman-Monteith model by reducing input parameters and local calibration can enhance efficiency and reliability. In this study, three empirical formulas—Hargreaves and Samani (HS, 1985), Priestley and Taylor (PT, 1972), and the World Meteorological Organization (WMO, 1966)—representing temperature-, solar radiation-, and mass-transfer-based approaches, respectively, were evaluated. To achieve this objective, meteorological data from five synoptic stations situated in the Samsun province in the Black Sea region of Türkiye, were utilized. Three methods, namely the traditional method, regression analysis, and genetic algorithm, were employed to estimate the local calibration coefficients of empirical equations based on the Penman-Monteith 56 equation. Finally, the outcomes were evaluated based on four criteria: root-mean-square error, coefficient of determination, mean bias error, and percentage error of estimate. The results of empirical formulas both before and after calibration were analyzed. Prior to calibration, HS and PT exhibited greater accuracy for the case study. This accuracy trend was also observed in the calibrated results. Additionally, among the three employed calibration methods, regression analysis and traditional methods demonstrated a higher level of accuracy.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103734"},"PeriodicalIF":3.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142172051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil erosion responses of cropland uses in contrasting slope in the Abay basin, Ethiopia","authors":"Mengie Belayneh","doi":"10.1016/j.pce.2024.103732","DOIUrl":"10.1016/j.pce.2024.103732","url":null,"abstract":"<div><p>Cultivated land is the primary source of runoff and soil loss in a watershed. Quantifying the soil erosion response of dominant cereal crops at different slope gradients is vital to sustainable land use, crop management, and conservation options. This study evaluated the runoff loss (<em>Ro</em>), runoff coefficient (<em>RoC</em>), and soil loss (<em>SL</em>) responses of <em>teff</em> (<em>Eragrostis tef</em>), maize (<em>Zea mays</em>), and wheat (<em>Triticum aestivum</em>) cropland use under different slope conditions. During 2020 and 2021, 18 experimental erosion plots (3 m × 10 m) having 3 crops × 3 slope gradients (8%, 18%, and 32%) with two replicates were installed. Soil loss and runoff analysis were made and the significance variation among land uses and slopes was tested using ANOVA. On average, the highest <em>Ro</em> is recorded from <em>teff</em> land use (700 mm) followed by wheat (651.2 mm), and maize (570 mm) land uses. The <em>Ro</em> generated from the <em>teff</em> crop land use exceeds 18.5% and 6.9% compared to maize and wheat crop land uses (<em>P &lt;</em> 0.05). The lower proportion of the rainfall was converted to runoff (<em>RoC</em> = 38%) under the maize crop land use, however, nearly half of the rainfall (<em>RoC</em> = 46.6%) became runoff in the <em>teff</em> crop. The average (three slope gradients) rate of <em>SL</em> in <em>teff</em>, wheat, and maize crop land uses was found to be 54.86, 45.61, and 38.27 t ha⁻¹ year⁻¹, respectively. Although the result shows high soil erosion in all cereal crops, cultivation of the <em>teff</em> crop in general and on <em>s</em>teep slopes in particular leads to a high <em>Ro</em> and <em>SL</em>. Therefore, sustainable land management practice and setting land use policy are recommended, particularly for <em>teff</em> cultivation.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103732"},"PeriodicalIF":3.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the drivers of the catchment hydrological cycle of the Jonkershoek Valley catchment, South Africa","authors":"Retang Anna Mokua ,&nbsp;Julia Glenday ,&nbsp;Dominic Mazvimavi","doi":"10.1016/j.pce.2024.103731","DOIUrl":"10.1016/j.pce.2024.103731","url":null,"abstract":"<div><p>Understanding trends in hydro-climate variables and the impacts of land use on the streamflow is crucial for the development of appropriate catchment water management strategies. Jonkershoek (146 km²) is an important headwater catchment in the Table Mountain Group (TMG) geological region, contributing flow to the Cape Winelands District Municipality in the Western Cape. This study analyses hydro-climate variables at annual, monthly, and seasonal scales using an integrated approach composed of statistical homogeneity testing for abrupt changes, Mann-Kendall tests for trend analysis, and the Indicators of Hydrological Alteration (IHA) tool for streamflow alterations. Analyses were conducted for three headwater sub-catchments within the Jonkershoek value, each with different land use history.</p><p>Homogeneity test of rainfall and streamflow data spanning from 1946 to 2019 identified gradual downwards change points for annual rainfall and streamflow across the sub-catchments. Moreover, the change points for streamflow were inconsistent with those of rainfall. The identified change points in streamflow were consistent with the timing of afforestation activities in Tierkloof, whereas in Bosboukloof and Langrivier they could be attributed to earlier climatic variability. Furthermore, Mann-Kendall test detected significant <em>(p</em> &lt; 0.05) decreasing trends for both annual and seasonal rainfall which coincided with most of the streamflow trends. Trends were strongest for the winter season suggesting a possible shift in climate patterns which influence winter rainfall. Winter streamflows declined by 15.5%–39.5%. Analysis of hydrological flow indices indicated significant decrease in 1-,7- and 30-day annual maximum extremes during afforestation which were attributed to high evapotranspiration rates of pines. The opposite was observed during clearfelling period in Bosboukloof. The median monthly flow also showed a decrease for winter months. This shows that climate variability and land-use change by afforestation have major impacts on streamflow. The findings of this study are important to inform policymakers on the impacts of climate change and land use, allowing pro-active mitigation and adaptation.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103731"},"PeriodicalIF":3.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conceptual modelling on water-rock reaction and genesis of high pH fluids in a typical granitoid geothermal reservoir: A case from Indus-Tsangpo Suture Zone, India","authors":"Parashar Mishra ,&nbsp;Archisman Dutta ,&nbsp;Vivek Prakash Malviya ,&nbsp;Ayodhya Prasad Thapliyal ,&nbsp;Pankaj Saini ,&nbsp;Sayandeep Banerjee ,&nbsp;Vishal Vasantrao Sakhare","doi":"10.1016/j.pce.2024.103736","DOIUrl":"10.1016/j.pce.2024.103736","url":null,"abstract":"<div><p>Two novel thermal springs are investigated along ITSZ of north-west Himalayas in Demchok geothermal belt. The area consists of deep-seated faults in LGB; despite being situated in ITSZ, fluid chemistry of these low-temperature springs differs significantly, specifically in terms of low TDS (161–168 mg/l) and high alkalinity, with neighbouring springs in Puga and Chumathang (∼2100 mg/l). Thermal waters are mixed type (Na–Cl–HCO₃–SO₄) with elemental composition influenced through silicate rock weathering and partial carbonate dissolution. Variable temperature speciation (25 °C–200 °C) indicates that in reservoir fluid, Na⁺ precedes over other cations, while sulfate and carbonate complexes being prominent for Mg and Ca, respectively. Aquifer boiling modelling suggests calcite scaling and silica mineral equilibration in reservoir. Environmental stable isotopes (δ¹⁸O and δD) suggest high-altitude recharge from Jamlung La (6156 m), with altitude-effect of 0.43 ‰ isotopic depletion per 100 m elevation in altitude. As only silica minerals equilibrate with thermal waters, silica, and gas geothermometers give most conservative estimate of reservoir temperature (125°−135 °C). The steep topography enables extensive lateral flow of hot fluids in outflow zone, leading to high mixing and a high water-rock ratio, which contribute to lower TDS. Conceptual modelling reveals that geothermal system is a low-enthalpic hydrothermal system controlled by joints and permeable fractures, having deep fluid circulation of meteoric waters of ∼1275 m at sub-surface, with anomalous geothermal gradient and steam migration as reservoir heat sources. These fluids closely resemble springs of Guerrero state, Mexico, exhibiting similarities in low-TDS, high-pH, and high concentration of dissolved silica.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103736"},"PeriodicalIF":3.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the effects of Water hyacinth proliferation on biochemical oxygen demand with operational land imager data","authors":"Yeison Alberto Garcés-Gómez ,&nbsp;Diego Fernando Cabezas-Alzate ,&nbsp;Vladimir Henao-Céspedes ,&nbsp;Eduardo Javid Corpas-Iguarán","doi":"10.1016/j.pce.2024.103733","DOIUrl":"10.1016/j.pce.2024.103733","url":null,"abstract":"<div><p>The rapid proliferation of water hyacinth (Eichhornia crassipes) in water bodies poses a significant threat to ecosystems and communities that rely on these resources. While this plant can offer certain benefits, its excessive growth can lead to detrimental ecological and social impacts. This study aimed to assess the relationship between water hyacinth coverage and Biochemical Oxygen Demand (BOD) levels in the Sonso Lagoon, Colombia, using Landsat 8 satellite imagery and in-situ measurements. Water hyacinth coverage was classified and quantified from Landsat 8 images. These data were then correlated with BOD levels obtained through periodic monitoring of the lagoon. The analysis revealed a strong negative correlation (<span><math><mrow><mi>ρ</mi><mo>=</mo><mo>−</mo><mn>0.83</mn></mrow></math></span>; <span><math><mrow><mi>p</mi><mo>−</mo><mi>v</mi><mi>a</mi><mi>l</mi><mi>u</mi><mi>e</mi><mspace></mspace><mo>&lt;</mo><mspace></mspace><msup><mn>0.05</mn><mrow><mo>*</mo><mo>*</mo></mrow></msup></mrow></math></span>) between water hyacinth coverage and BOD, demonstrating the plant's impact on water quality. A predictive model was developed to estimate BOD levels based on satellite-derived water hyacinth data. The integration of remote sensing and in-situ measurements offers an effective strategy for monitoring water hyacinth proliferation and its ecological consequences. The proposed approach enables rapid assessment of water quality parameters, facilitating timely implementation of mitigation and control measures. This methodology can be extended to quantify other invasive aquatic plant species and their impacts on aquatic ecosystems.</p></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"136 ","pages":"Article 103733"},"PeriodicalIF":3.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1474706524001918/pdfft?md5=4a2e3e5ab98892393988fabba36b3d05&pid=1-s2.0-S1474706524001918-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142162597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}