Modeling Earth Systems and Environment

A mathematical model is formulated to delve into the changes that have been produced on the natural interactive dynamics between plants and carbon dioxide when mining intervenes between them. The model is represented as a nonlinear system of ordinary differential equations comprising dynamic interactions among plants, carbon-dioxide, and mining. In the model formulation, it is assumed that mining activities enhance carbon dioxide in the atmosphere and cause plants’ ruination. The qualitative analysis of the model is executed to obtain properties like boundedness, identification of equilibrium solutions, and their stabilities. Besides qualitative investigation, the formulated model is also quantitatively analyzed from the obtained numerical solutions. The numerical values of input model parameters are estimated from global observational data of plants and carbon dioxide. However, the influential parameters towards the model outcomes are identified through a global sensitivity analysis technique that combines the evaluation of Partial Rank Correlation Coefficients (PRCCs) with Latin Hypercube Sampling (LHS). To better elucidate the role of mining over the interactive dynamics, results obtained from the proposed model are compared with the model that does not involve mining activities as one of the dynamic variables. The overall mathematical analyses reveal that the equilibrium level of carbon-dioxide concentration exhibits a significant increase, and stability of the system gets harder to achieve in the presence of mining. It is also being deduced that system outcomes are more sensitive towards mining-related parameters than plant density and carbon dioxide concentration parameters.

The utilization of geosynthetic-encased granular columns is an advantageous and environmentally friendly technique for enhancing fine-grained soil foundations, particularly for supporting footings in specific conditions. These conditions may include collapsible and porous soils, serving as a viable alternative to conventional concrete piles. This study evaluates the geomechanical behavior of GECs as an improvement technique of fine-grained soils beneath shallow foundations, with a particular emphasis on evaluating the impact of encasement length and footing diameter. The investigation involves laboratory tests using 1-g small-scale models of granular columns subjected to incremental static load stages. These models were instrumented not only to measure the applied loads and resulting settlements, but also to assess the earth pressures developed along the depth. This approach was adopted for a comprehensive understanding of the stress transfer mechanisms inherent in employing partial encasement techniques. The responses of these models contribute to the development, calibration, and validation of a numerical model, based on the finite element method, facilitating further analyses to explore the impact of encasement length and granular column diameter in relation to footing dimensions. The findings demonstrate that employing partial encasements in granular columns effectively prevents columns bulging within shallow depths, concurrently improving stress transfer mechanisms in deeper soil strata. Additionally, the study highlights the critical influence of the encasement length concerning the column height (R/L) and the ratio between footing and column diameters (D/d). These factors significantly affect column failure mechanisms, thus bearing substantial implications for the design of shallow foundations supported by columns.

The influence of interaction effects from adjacent excavations on multiple unsupported excavations could lead to the collapse of excavation walls during the construction of footings. This paper presents the predictions of the stability number of multiple unsupported excavations in cohesive-frictional soils, by using finite element limit analysis (FELA) and an artificial neural network (ANN). A numerical model which is capable of capturing the Mohr–Coulomb (MC) failure criterion is utilized, to determine the lower-bound (LB) and upper-bound (UB) solutions from finite element limit analysis (FELA). The input parameters are excavated depth ratio H/B, excavated spacing ratio S/B, and friction angle ϕ; where H is depth of excavation, S is spacing between excavations, and B is width of excavation. The paper illustrates the effects of these input parameters on the stability number N of multiple unsupported excavations in cohesive-frictional soils. The results obtained from FELA by using OptumG3 (Optum CE in OptumG3 software, Optum Computational Engineering, Copenhagen, 2020) are displayed in dimensionless charts, showing the relationships between the stability number and input parameters, which will be useful for practical applications. The FELA solutions are then employed as a necessary dataset for the ANN model of multiple unsupported excavations in cohesive-frictional soils. The ANN results show good agreement with the results obtained from FELA. Additionally, the relative importance (RI) of the input parameters is calculated using the ANN model to examine the relationship between the input parameters and the stability number. The results indicate that friction angle ϕ is the most critical parameter, followed by excavated depth ratio H/B and excavated spacing ratio S/B.

Landfill site selection is a complex multi-criteria and time consuming process. The present study aims to identify, evaluate, and prioritize the landfill site selection criteria and finally study the relationship between them, and the degree to which they affect or are affected by one another. In the first stage, experts’ opinion was sought to select the relevant criteria and fuzzy Delphi Method (FDM) was employed to obtain the critical factors for selection of landfill sites. Next, the fuzzy Analytic Hierarchy Process (FAHP) was used to make pairwise comparisons of selected criteria by domain experts for assigning weights to the decision criteria and to calculate their importance degree. Finally, by considering the interrelationships among the criteria, Decision-making Trial and Evaluation Laboratory (DEMATEL) technique was applied to deal with the importance and causal relationships among them, and to recognize the influential criteria of landfill site selection. Obtained results show that, the criteria of sensitive area and intra-municipality are revealed to be the top two significant influences in selecting landfill sites. By identifying the relevant criteria, the structures and interrelationships, this study can offer an insight for decision makers to understand cause-effect relationships and allow to select suitable sites.

Với tư cách là sinh vật cố định, thực vật phải đối mặt với các căng thẳng môi trường như tấn công của sâu bệnh, cạnh tranh với các thực vật lân cận theo những cách khác nhau. Các hợp chất bay hơi được sản xuất bởi thực vật đóng vai trò quan trọng trong việc phòng vệ của chúng. Sau khi bị tấn công bởi sâu bệnh, thực vật sẽ phát ra các hợp chất bay hơi kích thích để thu hút kẻ thù tự nhiên của sâu bệnh. Như vậy, kẻ thù tự nhiên sẽ tham gia vào hệ thống thực vật - sâu bệnh. Có nhiều nghiên cứu về sự phát triển và phòng vệ của từng cây riêng lẻ, trong khi đó, việc phân tích sự đánh đổi giữa phát triển và phòng vệ trong bối cảnh thực vật như là một thành viên của cộng đồng thực vật là rất cần thiết. Trong bài viết này, chúng tôi đề cập đến tác động của sự cạnh tranh giữa các cây và các hợp chất bay hơi được kích thích bởi sâu bệnh trong hệ thống bốn loài thực vật - sâu bệnh - động vật ăn thịt. Chúng tôi phác thảo vai trò đa dạng của các hợp chất bay hơi trong sự cạnh tranh và phòng vệ của thực vật. Ngoài sự ổn định cục bộ, chúng tôi cũng nghiên cứu hành vi toàn cầu tại các mật độ của tất cả các quần thể tại điểm cân bằng. Chúng tôi thảo luận về các điều kiện cho sự sống sót lâu dài của tất cả các quần thể. Chúng tôi phân tích các loại phân nhánh khác nhau tại các trạng thái ổn định khác nhau. Cuối cùng, xử lý số được thực hiện để minh họa cho các kết quả thu được của chúng tôi.

This investigation was carried out with the objective to understand the impacts of landfill leachate on groundwater quality. This study also explained the movement of trace metals in groundwater by using Visual MODFLOW/MT3D. It also delineates the various factors controlling the suitability of groundwater for domestic, agriculture and drinking purpose. The statistical assessment shows ~ 60.09% groundwater are in good condition, ~ 35.38% in poor condition and 4.53% in very poor condition. The spatial distributions of water quality index (LWQI) around landfills indicate landfills are in depleted condition. Hydrogeochemical classification indicates ~ 90.91% groundwater shows Ca–Na water-type cation facies and Cl− water-type anion facies. While 9.09% groundwater shows Ca–Na water-type cation facies and Cl−–SO42−–HCO3− anion hydrogeochemical facies. The mineral equilibrium diagram of groundwater has revealed that it is in equilibrium with silicate minerals and favors kaolinite formation. The saturation index indicates chrysotile (Mg3Si2O5(OH)4) (2.84), dolomite (CaMg(CO3)2) (0.45), ferric hydroxide (Fe(OH)3) (1.97–3.58), goethite (FeOOH) (7.86–9.47), hematite (Fe2O3) (17.73–20.95), hydroxyapatite (Ca5(PO4)3OH) (2.38–4.62), jarosite-K (KFe3(SO4)2(OH)6) (0.22–1.92), cerussite (PbCO3) (0.39), vivianite (Fe3(PO4)2·8H2O) (0.39) and willemite (Zn2SiO4) (0.35) are reactive mineral in groundwater aquifer of study area. The seasonal and temporal variation indicates anthropogenic influence. The calibration and validation of model show > 90% models correct with 95% confidence. The contaminant transport simulated in groundwater aquifer with the high accuracy (estimated standard error 0.049 m) for the large area (~ 300 km2). The trends of contour lines of trace metals concentration indicate; it will contaminate study area within few years of its release through the landfill.

Lesser Himalayan watersheds are most susceptible to conservational deprivation, that needs to accurate management and planning of available natural resources such as soil and water which are pre-requisites for sustainable growth of the watershed in the mountains regions. The analysis of watershed through morphometric together with geomorphic maps i.e., soil distribution, land cover, and slope map can play a role in forecasting to understand the behavior of hydrological processes in a Himalayan watershed. An attempt has been made to quantify the geo-morphometric parameters and their characteristics for watershed prioritization using remote sensing (RS) and geographical information system (GIS) approach and linked the geomorphologic parameters with the hydrological characteristics of the watershed. The sub-catchment Aglar UP (SC-1), Paligaad (SC-2), and Balganga (SC-3), located in the lesser Himalayas in Jaunpur block of Uttarakhand state having elevation between (670–2975 m). The sub-watershed (SC-1) and (SC-2) are third order and (SC-3) is a 1st order stream, having a dendritic drainage pattern with low drainage density < 0.5 km per km2, indicates the impact of lithology and topography on drainage pattern. The average bifurcation ratio of (SC-1) is combatively less than (SC-2) which shows a high infiltration rate with low overland flow and presence of strong structural control on the drainage pattern. Lower values of circularity ratio and elongation ratio of < 0.5 advocated elongated shape of the watershed with lesser peak flows for an extended time. The less value of the form factor in the elongated type of watershed suggested about flatter peak flow. Based on the obtained morphometry parameters of linear and shape, watershed prioritization has been carried out for erosion risk. Based on weight and ranking, (SC-2) got the highest priority, is the most susceptible to erosion, whereas (SC-1) receives the least priority which means the least erosion. The results from this study helps to understand the hydrological behavior and soil erosion factors of lesser Himalayan watersheds that would be useful to water resource conservation to the planners, policy makers and agriculturists. The study gets the attentions from the scientists, researchers, involved in their respective fields.

Land use maps are widely using all over the world for monitoring the usage of lands over a while when urbanization booms. The urban development of the city environment parallelly involves the quick change of landcover in a short time. This work aims to review the land cover changes in Miami which areone of a highly urbanized county in the USA in the twentieth century. The color patterns of land use maps were reviewed with a uniform temporal rate (5 years once) from 2001 to 2016. Based on the color code of the image, land use maps were visually interpreted and it was extended to the Statistical analysis. Unique formulas are derived from the linear statistical model for the changing rate of the land use type in 15 years. Urban built-up gave expeditious increment in land use (9.5%). In the meantime, agricultural land (5.97%) and water (4.21%) decreased at a rapid rate. At the end of the study, the regression model projects the land use change in the year 2021 in Miami Dade County. This study distinctly exhibits how urbanization affects the vegetation cover, water areas, and wetlands, in which land use classes playing a vital role in the ecosystem. This experiment gives a basic understanding of Miami Dade county development and its environmental impact.

The sensitivity analysis of calibrated erosion models holds significant promise for improving the performance of simulations and the understanding of the dynamics of runoff and soil loss. The aim of this study was to perform the calibration and sensitivity analyses of the OpenLISEM model for an unpaved rural road in Southern Brazil, where the quantitative understanding of the impact of precipitation on water and soil loss is limited, and the improvement of the use of the method is crucial for determination of the hydrosedimentological dynamic. Nash-Sutcliffe model efficiency coefficients (NSE) were used to compare measured and simulated data series of discharge and sediment production. “One-factor-at-a-time” (OAT) and relative sensitivity coefficients were derived relative to changes of total discharge (Q), average soil loss (Qs), infiltration (I), runoff erosion (Er), splash erosion (Es), and deposition (D) against relative changes of the Manning coefficient (n), random roughness (rr), saturated hydraulic conductivity (Ksat), suction at the wetting front (ψsoil), aggregate stability (aggrstab), soil cohesion (coh), mean aggregate diameter (d50), and initial soil moisture content (θi). The model calibration produced NSE coefficients of 0.97 and 0.90 for discharge and sediment production data series, respectively. Q and Qs were mostly sensitive to random roughness and saturated hydraulic conductivity. Our results also showed the high relevance of Ksat for I, and aggrstab for D and Es. The sensitivity analysis of the model revealed significant variations of sensitivity, depending on the magnitude of the values adopted in the calibration and the used methodology.

Groundwater is the main water source in arid and semi-arid regions. Monitoring water quality and quantity is essential as the groundwater is the most important drinkable and agricultural water source in Iran. Traditional groundwater evaluation methods are expensive and time consuming. Newly developed spatial interpolation method is an accurate and non-expensive method which needs fewer samples comparing to tradition methods. The main goal of this study is to choose the best spatial interpolation methods from geostatistical and deterministic interpolation for zoning (locating) of some water quality parameters in Najafabad plain. Several Spatial methods such as… were applied to study TDS, SAR, pH, cl and hco3. The accuracy and efficiency of studied methods were evaluated applying RMSE and MBE. Results showed that simple kiriging is suitable for zoning cl, hco3, TDS and Ec, IDW is more suitable for pH and ordinary kiriging is best method for zoning SAR. Finally the best spatial interpolation method was applied to develop quality parameter zoning maps.