Multi-decadal groundwater variability analysis using geostatistical method for groundwater sustainability

Islam, Zubairul; Ranganathan, Muthukumarasamy; Bagyaraj, Murugesan; Singh, Sudhir Kumar; Gautam, Sanjay K.

doi:10.1007/s10668-021-01563-1

Cited by 17 publications

(4 citation statements)

References 32 publications

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“…A cold spot region means a cluster area with low efficiency of tourism development. A hot spot region means a cluster area with high efficiency of tourism development [50]. In addition, the spatial statistics module of ArcGIS is used to calculate the local spatial correlation index of OE in 2014 and 2019 and thus reveals the spatial characteristics of OE in tourism development (Figure 1).…”

Section: Analysis Of Empirical Resultsmentioning

confidence: 99%

Empirical Study on the Sustainable Development of Mountain Tourism in the Early Stage of High-Speed Railways—Taking the Southwest Mountainous Region of China as an Example

Liu

Pérez-Sánchez

et al. 2022

Sustainability

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This study focuses on the early stage of high-speed railways (HSRs) and corrects problems in a timely manner and integrates the direction for tourism development. Its aim is to realize the sustainable development of mountain tourism in the southwest region of China. Based on the panel data from 2010 to 2019 of 39 cities in Guizhou, Guangxi, and Yunnan provinces, which are in the southwest mountainous region of China, and using data envelope analyses, the Malmquist productivity index, the Tobit model, and the intermediary effect, this study verifies the impact of core factors on the development efficiency of mountain tourism in the early stage of an HSR to find the problems existing in tourism development at present and in future stages. Results show the following: (1) In its early stage, an HSR is not yet the key factor to improve the efficiency of tourism development in the mountainous region. (2) The promotion effect of an HSR on the efficiency of tourism development is delayed. (3) In its early stage, an HSR breaks the balance of resource investment and wastes resources. (4) Taking HSRs is born out of the rigid demand of residents in the mountainous region rather than of their income levels. (5) Accessibility in mountain tourism plays a positive role between HSRs and the efficiency of tourism development.

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Section: Analysis Of Empirical Resultsmentioning

confidence: 99%

Empirical Study on the Sustainable Development of Mountain Tourism in the Early Stage of High-Speed Railways—Taking the Southwest Mountainous Region of China as an Example

Liu

Pérez-Sánchez

et al. 2022

Sustainability

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“…Step 4: Geographically weighted regression (GWR) analysis helps to explore spatially varying relationships [17,18]. To measure the impact of flood and drought hazards on human migration, geographically weighted regression was used; it is a local form of linear regression which is used to model spatially varying relationships.…”

Section: Discussionmentioning

confidence: 99%

Geospatial Analysis of the Impact of Flood and Drought Hazards on Crop Land and Its Relationship with Human Migration at the District Level in Uttar Pradesh, India

Islam

Singh

2021

GaEE

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The main objective was to explore the connection between flood and drought hazards and their impact on crop land and human migration. The Flood and Drought effect on Cropland Index (FDCI), hot spot analysis and the Global Regression Analysis method was applied for the identification of the relationship between human migration and flood and drought hazards. The spatial pattern and hot and cold spots of FDCI, spatial autocorrelation and Getis-OrdGi* statistic techniques were used respectively. The FDCI was taken as an explanatory variable and human migration was taken as a dependent variable in the environment of the geographically weighted regression (GWR) model which was applied to measure the impact of flood and drought hazards on human migration. FDCI suggests a z-score of 4.9, which shows that the impact of flood and drought frequency on crop land is highly clustered. In the case of the hot spots analysis, out of seventy districts in Uttar Pradesh twenty-one were classified as hot spot and eight were classified as cold spots with a confidence level of 90 to 99%. Hot spot indicate maximum and cold spots show minimum impact of flood and drought hazards on crop land. The impact of flood and drought hazards on human migration show that there are fourteen districts where migration out is far more than predicted while there are ten districts where migration out is far lower.

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“…Spatial Autocorrelation (Moran's I) Tool was used to identify the spatial pattern of the residuals (Islam et al 2021).…”

Section: Discussionmentioning

confidence: 99%

Change In Nitrogen Dioxide (No2 ) Concentration Due To The Lockdown Amid The Covid-19 Pandemic In India

Islam

Singh

Ahirwar

2021

GES

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The study aimed to examine the change in the concentration of nitrogen dioxide due to the lockdown amid the COVID-19 pandemic in India at the district level using Sentinel-5P TROPOMI. The spatio-temporal characteristics of the tropospheric column NO2 concentration during 45 days of the lockdown were compared with the same days of 2019. Further, to model spatially varying relationships of NO2 during the lockdown period, it was given as a dependent variable whereas NO2 during the pre-lockdown period was considered as an independent variable. Results show that the mean NO2 concentration was reduced from 0.00406 mol/m2 before the lockdown (2019-03-25 to 2019-05-10) to 0.0036 mol/m2 during the lockdown period (2020-03-25 to 2020-05-10). The maximum decline of NO2 concentration was observed in Gautam Buddha Nagar and Delhi. This indicates the high level of atmospheric pollution due to the excess use of fuel in human activities. The results of the Ordinary Least Squares (OLS) method show a strong positive relationship between both variables. Positive standard residuals indicate that the concentration of NO2 has reduced more than expected as per the OLS model. The z-score (24.11) was obtained from spatial autocorrelation. It indicates that residuals are highly clustered and there is less than a 1% likelihood that this clustered pattern could be a result of a random chance. The highest decrease was observed in districts/urban agglomerations of Gautam Buddha Nagar (-40%), Delhi (-37%), Greater Bombay (-31%), Hyderabad (-29%), Faridabad (-29%), Bangalore Urban (-28%), Gandhinagar (-27%), Chennai (-27%) and Gurgaon (-26%) respectively.

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Multi-decadal groundwater variability analysis using geostatistical method for groundwater sustainability

Cited by 17 publications

References 32 publications

Empirical Study on the Sustainable Development of Mountain Tourism in the Early Stage of High-Speed Railways—Taking the Southwest Mountainous Region of China as an Example

Empirical Study on the Sustainable Development of Mountain Tourism in the Early Stage of High-Speed Railways—Taking the Southwest Mountainous Region of China as an Example

Geospatial Analysis of the Impact of Flood and Drought Hazards on Crop Land and Its Relationship with Human Migration at the District Level in Uttar Pradesh, India

Change In Nitrogen Dioxide (No2 ) Concentration Due To The Lockdown Amid The Covid-19 Pandemic In India

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