Physics and Chemistry of the Earth最新文献

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).

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.

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 (Ro), runoff coefficient (RoC), and soil loss (SL) responses of teff (Eragrostis tef), maize (Zea mays), and wheat (Triticum aestivum) 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 Ro is recorded from teff land use (700 mm) followed by wheat (651.2 mm), and maize (570 mm) land uses. The Ro generated from the teff crop land use exceeds 18.5% and 6.9% compared to maize and wheat crop land uses (P < 0.05). The lower proportion of the rainfall was converted to runoff (RoC = 38%) under the maize crop land use, however, nearly half of the rainfall (RoC = 46.6%) became runoff in the teff crop. The average (three slope gradients) rate of SL in teff, 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 teff crop in general and on steep slopes in particular leads to a high Ro and SL. Therefore, sustainable land management practice and setting land use policy are recommended, particularly for teff cultivation.

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.

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 (p < 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.

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.

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 ($\rho =-0.83$; $p-value<{0.05}^{**}$) 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.

Hydrocarbon impacts on subsurface environmental systems occur due to leaked buried pipelines, petroleum facilities sabotage and oil spills during exploration, production, and transportation. 2D geoelectric investigation was carried out on soils of hydrocarbon impacted site in Alode community, Eleme Local Government Area of Rivers State, Central Niger Delta, Nigeria. This was imperative due to the right-of-way spill along a sabotaged petroleum flow line that has been identified for remediation. This study employed a PASI 16 GL earth resistivity meter for Electrical Resistivity Tomography (ERT) with established 5 Wenner-4 electrode array survey lines consisting of 290 horizontal electrical profiles (HEP) probes. The survey was done in a grid format over 100 m lines at 1.5 m, 3 m, 6 m, 9 m, 12 m, and 15 m constant spacing to acquire high-resolution 2D geoelectric data. ERT data inversion was performed using GS RES2DINV and AGI Earth Imager software's to generate 2D resistivity subsurface imageries to map and delineate the hydrocarbon contaminations. The results showed resistivity values from 600 Ω-m to above 3500 Ω-m denoted impacted areas, extending beyond the maximum target depth of 6 m, as pertinent for soil excavation procedure during ex-situ remediation within the locality. ERT profiles displayed evident spill geometries at lines 1, 2 and 3 with only significant presence from below 2 m at lines 4 and 5. The result confirms the horizontal direction and vertical trajectory of the spill through a porous medium-grained sandy layer, providing information for impacted area zoning, conducting risk assessments, and designing and implementing appropriate remediation actions.

Simulation models are useful tools for estimating plant response and contributing to the development of management strategies and yield predictions in crops. This study aimed to calibrate and evaluate the AquaCrop-FAO model for the forage cactus imposed on different cropping systems in the semi-arid region of Brazil. Four experiments were conducted: cactus-sorghum intercropping system with five spacings between plants (0.10, 0.20, 0.30, 0.40 and 0.50 m); cactus-sorghum intercropping system with five spacings between rows (1.00, 1.25, 1.50 and 1.75 m); single cactus with four levels of mulch (0, 5, 10 and 15 Mg ha⁻¹); and single forage cactus with four levels of nitrogen fertilisation (50, 150, 300 and 450 kg of N ha⁻¹). The performance of the model was evaluated using the following parameters: root mean squared error (RMSE); normalised RMSE (NRMSE), coefficients of determination (R²), Nash-Sutcliffe model efficiency coefficient (ME) and the Willmott index of agreement (d). During the calibration stage, the statistical indices pointed to the good performance of the AquaCrop model in estimating dry biomass in most of the cropping systems, with 10 < NRMSE <20; R² > 0.96 and ME > 0.95. The AquaCrop model showed the best performance simulating systems under different levels of nitrogen fertilisation. Among the intercropping systems, the denser arrangements showed the highest values for simulated biomass.

Drought, a recurrent natural hazard, significantly impacts agricultural productivity, water resources, and socio-economic development, especially in semi-arid regions like Bundelkhand in India. Here, frequent droughts challenge the livelihoods of its predominantly agrarian population. These challenges, compounded by poverty, land degradation, and resource conflicts, have profound implications for local communities and the attainment of Sustainable Development Goals (SDGs). Understanding the spatiotemporal conditions of drought is crucial for effective planning and management. This study evaluates meteorological and hydrological drought attributes at a high resolution within the region, using the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) across a range of temporal scales. Findings indicate moderate droughts are more probable than severe or extreme droughts, with SPI-12 showing up to 20% probability over some grids, implying drought occurrence once in five years. Trend analysis reveals decreasing SPI trends in certain northern districts during monsoon months, suggesting more frequent droughts in vulnerable areas. The study also finds higher drought probabilities with longer SPI durations, highlighting significant temporal and spatial variability. Additionally, the applicability of SDI using GloFAS discharge data is evaluated, offering an alternative in the absence of gauge data. The combined SPI and SDI analysis underscores higher and more extensive drought probabilities for longer periods, emphasizing the need for multi-temporal scale assessment for effective drought management. This study enhances understanding of drought characteristics in the region, aiding policymaking for drought management and supporting evidence-based strategies to achieve SDGs, particularly those related to water security, climate resilience, and sustainable development.

Improving environmental resilience performance (ERP) is a significant support for achieving sustainable development goals. This study introduces the three-dimensional analysis framework of "object-process-actor", capable of addressing multidimensional and multilevel issues. This framework systematically addresses the "three key questions" of what, how, and who to improve ERP. Results indicate that from 2011 to 2020, the ERP of the Yangtze River Delta Urban Agglomeration (YRDUA) was between 0.42 and 3.30. The violin plot and visualization analysis showed that its probability density and distribution status were stable, with significant regional differences. The ERP of economically developed cities such as Hangzhou and Shanghai is high, while the ERP of cities in the Yancheng-Chuzhou line is low, and the number of high-performing cities increases to 40.7% in 2020, which is a constantly improving development trend. Factors related to market actors have the greatest impact on ERP, with the explanatory power of FDI, green invention patents, and population concentration all exceeding 0.6, and the importance of government and social actors is also supported. The explanatory power of factor interactions was stronger than that of single factors, and land development degree ranked third in terms of its interaction power with other factors and was also a key factor influencing ERP. These findings provide new explanations and knowledge for improving ERP, which can provide references for policymakers and urban planners.