Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)techniques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model’s result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.

COVID-19 strict lockdown impact on urban air quality and atmospheric temperature in four megacities of India

COVID-19 pandemic has forced to lockdown entire India starting from 24th March 2020 to 14th April 2020(first phase), extended up to 3rd May 2020(second phase), and further extended up to 17th May 2020(third phase) with limited relaxation in non-hotspot areas. This strict lockdown has severely curtailed human activity across India. Here, aerosol concentrations of particular matters(PM) i.e., PM,PM, carbon monoxide(CO), nitrogen dioxide(NO), sulphur dioxide(SO), ammonia(NH) and ozone(O), and associated temperature fluctuation in four megacities(Delhi, Mumbai, Kolkata, and Chennai)from different regions of India were investigated. In this pandemic period, air temperature of Delhi,Kolkata, Mumbai and Chennai has decreased about 3 ℃, 2.5 ℃, 2 ℃ and 2 ℃ respectively. Compared to previous years and pre-lockdown period, air pollutants level and aerosol concentration(-41.91%,-37.13%,-54.94% and-46.79% respectively for Delhi, Mumbai, Kolkata and Chennai) in these four megacities has improved drastically during this lockdown period. Emission of PMhas experienced the highest decrease in these megacities, which directly shows the positive impact of restricted vehicular movement. Restricted emissions produce encouraging results in terms of urban air quality and temperature, which may encourage policymakers to consider it in terms of environmental sustainability.

Extreme exposure of fluoride and arsenic contamination in shallow coastal aquifers of the Ganges delta,transboundary of the Indo-Bangladesh region

Globally,shallow aquifer groundwater(GW)has been severely affected in recent decades for both geogenic and anthropogenic reasons.The hydro-geochemical characteristics of the GW change inconsistently with the addition of unwanted inorganic trace elements into the GW aquifer of the Indo-Bangladesh delta region(IBDR),such as arsenic(As)along with fluoride(F-)contamination.Contaminated GW can have a negative impact on drinking water supplies and agricultural output.GW pollution can have serious adverse effects on the environment and human health.Thus,the GW quality of this region is deteriorating progressively,and human health threatening by various life-threatening disorders.Hence,the current study concentrated on the GW quality evaluation and prediction of possible health issues in the IBDR due to elevated contamination of As along with F-within GW aquifers by considering sixteen causative.Field survey-based statistical methods such as entropy quality index(EWQI)combined with health risk index(HRI)was implemented for evaluating the As and F-sensitivity with the help of correlation testing and principal component analysis.The study's outcome explains that a substantial portion of the IBDR has been vastly experiencing inferior GW quality,environmental issues,and health-related problems in dry and wet seasons,correspondingly for As and F-exposure.Piper diagram verified the suitability of water that almost 55%of GW across the study area’s aquifers are unfit for drinking as well as cultivation of crops.Sensitivity analysis and the Monte Carlo simulation method were also applied to assess the contaminant's concentration level and probable health risk appraisal.The present study concludes that the elevated exposure of As and F-pollution has to be monitored regularly and prevent unwanted GW contamination through implementing sustainable approaches and policies to fulfil the sustainable development goal 6(SDG-6)till 2030,ensuring the most basic human right of clean,safe,and hygienic water.