Modeling Earth Systems and Environment

Understanding drought and its multifaceted challenges is crucial for safeguarding food security, promoting environmental sustainability, and fostering socio-economic well-being across the globe. As a consequence of climate change and anthropogenic factors, the occurrence and severity of drought has risen globally. In India, droughts are regular phenomenon affecting about 16% area of country each year which leads to a loss of about 0.5–1% of country’s annual GDP. Hence, the study aims to analyse and predict the meteorological drought in northeast India during 1901 to 2015 using standardised precipitation index (SPI) and analytical techniques such as Mann–Kendall test (MK), innovative trend analysis (ITA), and wavelet approach. In addition, the periodicity of the drought was estimated using Morlet wavelet technique, while discrete wavelet transform (DWT) was applied for decomposing the time series SPI-6 & SPI-12. Study shows that the northeast India experienced moderate drought conditions (SPI-6) in short term and two significant severe droughts (SPI-12) in long term between 1901 and 2015. The trend analysis shows a significant increase in SPI-6 & SPI-12 (p-value 0.01). Further, the combination of parameters i.e. approximation and levels result in the best drought prediction model with higher correlation coefficient and lower error. By using PSO-REPTtree, this study pioneers the use of decomposed parameters to detect trends and develop a drought prediction model. The study is the first step towards establishing drought early warning system that will help decision-makers and farmers to mitigate the impact of drought at the regional level.

The current work addresses issues related to quantitative estimation of precipitation caused by convective clouds, using thermal infrared images, and adaptive regression modeling. The developed methodology has been implemented on the Indian sector during the period 22–25 October 2013. The importance of the developed methodology lies in the fact that the information obtained from it can facilitate further studies intended for the prediction of flood events. This study is the continuation of existing work of identification of convective clouds and the analysis of the Mesoscale Convective Systems (MCS). In the current work, forecast of rainfall in terms of millimeter has been proposed. The entire work has been carried out on thermal infrared (TIR) images obtained from geostationary satellites and the results have been validated by actual rainfall data measured by rain gauges. The results obtained from the developed methodology were found to be fairly close to actual values.

The aim of the research is to delineate the host rock of uranium in the semi-arid regions of Andhra Pradesh, India. Uranium is one of India's major rich resources explored in recent decades, and many parts of the country in general and Tummalapalli, Andhra Pradesh and Jadughuda, Jharkhand in particular, are established locations at present. The present study location is situated in the crescent-shaped Proterozoic Cuddapah basin. The Cuddapah basin that occurs in Andhra Pradesh is a unique middle–upper Proterozoic basin with rich minerals of economic significance along with inter-strata uranium deposits along the non-conformity. Host rocks are dolomites of the Vempalli formation of the Cuddapah Supergroup, while granites of the Archaean basement are the source rocks for uranium mineralization, especially in the Cuddapah basin. The dolomites of the composition CaMg(CO3)2 belong to the formation of Vempalli particularly in this region and phosphatic contain silica and chert mineral inclusions; hence, they are called dolostones. It occurs primarily in the area of Thummalapalli in the YSR district of Andhra Pradesh. The present research is intended to analyze by integrating geochemistry using X-Ray Fluorescence, Inductively Coupled Plasma Mass Spectrometry for major, minor, and trace elemental analyses along with the geospatial techniques of the host rock formations of uranium mineralization.

Ecological system depends on prey predator interaction. Sometimes diseases are spread among prey or predator or both species. In this paper, a disease control prey–predator model with Holling type-II functional response incorporating refuge in the susceptible prey is proposed. The impact of additional food for predator species in the system is investigated. Using some assumptions, the crisp model is formulated and it is converted into fuzzy model and defuzzified models by using basic defuzzification method. In the theoretical section, the condition of boundedness, existence of equilibrium points, global stability of interior equilibrium point and Hopf bifurcation on a refuge parameter are investigated. Theoretical results are verified in our numerical simulation section. Using MATLAB package we examined the behaviour of the species in the presence and absence of additional food in both crisp and fuzzy environments. The phase trajectories for different initial conditions in both environments and variations in population of the species are presented. Using MATCONT package, we present the bifurcation scenarios when the additional food parameter and refuge parameter vary. We compute the existence of Hopf point (H) and branch point (BP) in the model for suitable supply of additional food and intensity of refuge parameter. Finally the sensitivities of the parameters are plotted graphically. This theoretical and numerical study may be useful to control the infectious diseases in real world ecological systems.

The current study describes the use of a mathematical formula based on macro-scale balances to calculate the efflux time for gravity draining a Newtonian liquid from a large conical tank through an exit pipe at the bottom of the tank when the flow in the pipe line is turbulent. The least amount of time required to drain the tank will be calculated using the efflux time equation, which has been modified using experimental data. When the flow is mixed, that is, partially laminar and partially turbulent, gravity-driven, and once through the system, the percentage reduction in efflux time that the addition of water-soluble polyethylene oxide polymer has on drag reduction is displayed. Therefore, the efflux time equation provides the shortest amount of time needed to acquire the liquid draining from the tank.

In the present study, an ArcSWAT model was utilized to simulate the hydrological responses due to land use and climatic changes in the Omo-Gibe river basin, Ethiopia. The performance of the model was evaluated through sensitivity, uncertainty analysis, calibration and validation. The most sensitive parameters were identified which are governing on surface runoff generation processes in the selected basin. The calibration and validation of the model was done using SWAT-2005. Also, the sensitivity and uncertainty analysis was performed using the SUFI-2 and SWAT-CUP algorithm. The model results revealed that a good performance during the calibration (R2 = 72.4%, NSE = 62.6% and D = 14.37%) and validation (R2 = 68.1%, NSE = 68% and D = 4.57%). SUFI-2 algorithm gave good results in minimizing the differences between observed and simulated flow in the Great Gibe sub-basin. The studies show that there is an overall increasing trend in future annual temperature and significant variation of monthly and seasonal precipitation from the base period 1985–2005. Also, the annual potential evapotranspiration shown increasing trend for future climate change scenarios. Similarly, the surface water decreases in terms of mean monthly discharge in the dry season and increases in the wet season. The percentage change in future seasonal and annual hydrological variables was shown increasing trends. Therefore, this study found that SWAT can be effectively used for assessing the water balance components of a river basin in Omo-Gibe basin, Ethiopia.

Agent-based modelling (ABM) is a form of simulation that is phenomenal in understanding and exploring various types of spatial and non-spatial problems. The goal of this research is to study agent-based modeling in an urban context. ArcGIS was used to develop cost raster. In the second part, NetLogo was used to create agents for the purpose of stochastic simulation of urban sprawl in Waterloo Region. The cost rasters were generated using the Cost Distance Tool in ArcGIS with two inputs: source raster and time raster. The simulating model in NetLogo was created using three raster layers: proximity to University of Waterloo campus, proximity to grocery stores and proximity to the LRT stops. The use of ABM has helped in understanding the urban dynamics and to model the settlement pattern of students in Waterloo region.

This study tried to investigate the effect of Co/SiO2 NPs on CO2 absorption in a single raising bubble column (20 °C and 1 atm). Co-doped SiO2 nanoparticles were first synthesized through the chemical vapor deposition (CVD) method, then several nanofluids, including different weight percentages of the synthesized NPs (0.001, 0.01, 0.02, 0.05, and 0.1 wt%) were prepared. Comprehensive experimental studies examined the effect of NPs concentration and nanofluid volume on CO2 absorption rate. The stability of nanofluids, as an affecting factor on nanofluid efficiency, was investigated over 10 days. It was tried to obtain mass transfer parameters, including Sherwood (Sh), and Schmidt (Sc) numbers, incorporating the CO2 diffusivity into the Co/SiO2 nanofluid. Results showed that increasing NPs concentration from 0.001 to 0.02 caused the CO2 absorption rate to reach a maximum point followed by a downward trend. Increasing nanofluid volume was not beneficial for increasing gas absorption, which is attributed to the fact that the predominant mechanism of CO2 absorption was the Brownian motion of NPs. Results confirmed that the prepared nanofluids had acceptable stability over 10 days, and the nanofluid (80 mL), including 0.02 wt% of NPs, had the maximum CO2 absorption, which was 28% more than the base fluid. Findings indicated that the magnitude of the CO2 mass transfer coefficient in the nanofluid was 1.953 * 10− 4 (m.s− 1), which was 1.89 times more than that for the base fluid. Finally, a comprehensive correlation (R2 = 0.99) was introduced to predict the CO2 mass transfer coefficient in the Co/SiO2 nanofluid.

Groundwater is a major natural resource for drinking and irrigation purpose. The overexploited of groundwater is increase year by year and quality of groundwater simultaneously decreases. Groundwater quality is the main issue because water is linked with our metabolism. In order to know the groundwater pollution and controlling factors of groundwater quality in the upper Manimuktha sub basin, Vellar river, Tamil Nadu, India. Forty eight groundwater samples were collected from entire study area on January 2014 and analysed for physicochemical properties. Major ions were as abundance of Na > Ca > Mg > K, and HCO3 > Cl > SO4 > NO3 respectively. Multivariate statistical analyses display the good correlation between all the physicochemical parameters except pH and F. The dendrogram reveals cluster 3 (EC and TDS), cluster 2 (alkalinity, TH, HCO3) and cluster 1 (F, K, NO3, Ca, Mg, Na, SO4, Cl). The hydrochemical processes reveal rock-weathering interactions and ion-exchange processes play an important role in groundwater quality of the study area. The WQI indicates 50.03% of the samples fall in excellent to good for drinking in the center of the study area. Remaining samples fall poor to very poor categories, signifying northern and southern side mainly polluted. Maximum of lakes located in the northern side also indicate poor quality, because of the contamination of wastewater at or near the lakes, migrate in the groundwater. This study has shown the great combination of GIS, statistical analysis and WQI in assessing groundwater quality give a clear view for decision makers can plan better for the operation and maintenance of groundwater resources.