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Multi control spatial history of groundwater reservoirs in Pakistan using satellite driven data

Mahmood Khalid, Basit Iqra, Faizi Fiza

Acta Geophysica

2023

Vol. 71, no. 1

423--436

Assessment of changing groundwater storage is an important factor that needs to be assessed over both time and space to understand the regional scenarios. This study has employed Geographical Temporal Weighted Regression (GTWR) along with Geographic Weighted Regression and Ordinary Least Squares to find the impact of various variables on Groundwater Storage Anomaly (GWSA). The study has made use of satellite data of gravity change, extracted using fishnet point observation to reduce processing complexity. All three methods have been compared using correlation coefficient, Akaike information criterion, and root mean squared error. Results show that GTWR, with highest R-square of 65.3 and lowest root mean square error of 0.18, is the more comprehensive option for quantifying the effect of controlling factors among its counterparts as it incorporates both spatial and temporal heterogeneity. Runoff, population density, and soil moisture are the dominant factors controlling groundwater changes with interquartile ranges of 2.35, 0.62 and 1.58 respectively, much bigger than twice the standard error. This indicates a significant effect of anthropogenic activities including rapid urbanization and increase in extraction for irrigation. Additionally, the use of GTWR led the analysis to highlight factors that influence neighboring regions. Instead of climate change and poor management of water, the alteration to the natural course of rivers has been highlighted as the biggest cause of water table decline in the region.

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 Zubairul, Singh Sudhir Kumar

Geomatics and Environmental Engineering

2021

Vol. 15, no. 4

117--127

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.