COVID-19 Coronavirus is now one of the most contagious diseases of the recently discovered and spread across the China in 2019 and has received global attention. In most COVID-19-infected individuals, respiratory symptoms should be mild to moderate and improve without the need for medical care. The risk of serious disease is higher for senior citizens and people with serious health problems, such as heart disease, diabetes, severe respiratory disease, and cancer. The World Health Organization (WHO) has formally declared the outbreak of COVID-19 to be a global pandemic. As on 11th April 2020 in India the largest number of persons testing positive for COVID-19 since the outbreak earlier month with samples of people, mostly contacts of already confirmed patients, rendering positive. In India total confirmed cases 7364, 633 are cured/discharged, with 240 deaths had been reported by the Ministry of Health and Family Welfare Government of India. The aim of the research is to analyze the spatial distribution of COVID-19 and its trends with the help of GIS software. At this time, there are no precise antibiotics or treatment options for COVID-19. Besides, several ongoing clinical studies are assessing effective treatments. The best way to protect and sluggish transmission should be well advised about the current COVID-19 virus, the disease it triggers and also how it continues to spread. Therefore, monitoring active ties using GIS spatial analysis is very important to control such as a COVID-19 virus spreading problem.

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The aim of this present study was to evaluate groundwater quality in the lower part of Nagapattinam district, Tamil Nadu, Southern India. A detailed geochemical study of groundwater region is described, and the origin of the chemical composition of groundwater has been qualitatively evaluated, using observations over a period of two seasons premonsoon (June) and monsoon (November) in the year of 2010. To attempt this goal, samples were analysed for various physico-chemical parameters such as temperature, pH, salinity, Na ? , Ca 2? , K ? , Mg 2? , Cl-, HCO 3 and SO 4 2-. The abundance of major cations concentration in groundwater is as Na [ Ca [ Mg [ K, while that of anions is Cl [ SO 4 [ HCO 3. The Piper trilinear diagram indicates Ca-Cl 2 facies, and according to USSL diagram, most of the sample exhibits high salinity hazard (C3S1) type in both seasons. It indicates that high salinity (C3) and low sodium (S1) are moderately suitable for irrigation purposes. Gibbs boomerang exhibits most of the samples mainly controlled by evaporation and weathering process sector in both seasons. Irrigation status of the groundwater samples indicates that it was moderately suitable for agricultural purpose. ArcGIS 9.3 software was used for the generation of various thematic maps and the final groundwater quality map. An interpolation technique inverse distance weighting was used to obtain the spatial distribution of groundwater quality parameters. The final map classified the ground quality in the study area. The results of this research show that the development of the management strategies for the aquifer system is vitally necessary.

Terrain characteristics of the land and meteorological properties of the region are the main natural factors for flood. The recent flood in Chennai was unexpected and not triggered by the above factors. Sometimes floods occur when the watershed size is considerably small which leads to the over flow of water inland may due to the encroachment and the urban development of the city. Temporarily used backwater effects in sewers and local drainage channels and creation of unsanitary conditions may cause flooding. Chennai flood was basically claimed to occur due to improper drainage system and underlying strata which was found to be landfill over the ponds and lakes. The Coouam River which flows through the centre of main city was found silting due to the improper drainage facilities and encroachment by the local peoples who causes flood. For the analysis of potentially affected areas Geographical Information System (GIS) integrated with Multicriteria Decision Analysis (MCDA) were employed. Ranking and displaying the potentially risky areas, the spatial Multicriteria analysis was used. It has been revealed that all most all the area's having populations are likely to be exposed to flood hazard. At the end of study, a map of flood risk areas was generated and studied with a view to assisting decision makers on the consequences posed by the disaster.

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The present research datasets provide a different potential sector of groundwater accessibility in Debre Berhan, Amhara region represented by GIS and remote sensing techniques. Groundwater potential factors such as geology, slope, geomorphology, landuse/landcover, drainage density, and lineament density thematic layers were prepared from the SRTM 30m and LANDSAT multispectral satellite data. Weightage and scores were assigned to all thematic layers based on their groundwater holding capacity. The Inverse Distance Weighted (IDW) method was applied to integrate all the thematic layers to appraise the groundwater potential sector. From this method, the total data site is classified as very good - 6.5%; good - 22.1%; moderate - 51.2%; low - 18.4%; and very low - 1.8% of the groundwater potential sector. This analysis of data demonstrates the fact that the implication of GIS and remote sensing techniques in groundwater potential sector mapping at the regional scale and suggests that similar techniques could be applied to other regions of this country.

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