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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

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2023

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Vol. 71, no. 1

423--436

EN

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.

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Geospatial indices as an alternative for environmental impact assessment of dumped waste

Mahmood Khalid, Iftikhar Wajiha, Faizi Fiza

Acta Geophysica

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2023

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Vol. 71, no. 1

309--322

EN

Urban municipalities throughout the world are facing grave challenge on the environmental front due to generation and mismanagement of massive amounts of municipal solid waste. This study focuses on the ecological damage caused by Municipal Solid Waste Open Dumps (MSWOD) in their vicinity. To study the adverse ecological impacts, satellite-based vegetation health indices and thermal measurements have been used as bio-thermal indicators to assess the deterioration of vegetation health and thermal heterogeneity around Mehmood Booti Municipal Solid Waste Open Dump in Lahore, Pakistan. Freely available satellite data and appropriate GIS techniques have been utilized to form basis of geospatial proximity analysis, making the approach efficient and economical. Zonal statistics and curve smoothing functions have been combined to prepare distance-dependent profiles that were subject to curve flattening technique for determination of impact range and severity in different seasonal conditions. Varying trends of high and low ranges for both indicators provide insight into factors other than main source of hazardous emissions, controlling bio-thermal conditions in the area as minor influencers. Similarly, role of meteorological variables in influencing waste decomposition and supporting vegetation health has also been distinguished. It has been discovered that the hazardous bio- and thermal influence zones around the study site have undergone expansion up to 761 m and 694 m, respectively, as compared to 650 m reported previously. Overall, the study supports the use of geospatial indicators to monitor and study environmental variables with a particular focus on emissions from MSWOD resulting from waste decomposition.

3

Synergic use of neural networks model and remote sensing algorithms to estimate water clarity indicators in Khanpur reservoir, Pakistan

Faizi Fiza, Mahmood Khalid

Acta Geophysica

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2022

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Vol. 70, no 3

1433--1443

EN

Freshwater reservoirs are limited and facing issues of over-exploitation, climate change effects and poor maintenance which have serious consequences for water quality. Developing countries face the challenge of collecting in situ information on ecological status and water quality of these reservoirs due to constraints of cost, time and infrastructure. In this study, a practical method of retrieval of two water clarity indicators, total suspended matter and secchi disk depth, using Sentinel-2 satellite data is adopted for preliminary assessment of water quality and trophic conditions in Khanpur reservoir, Pakistan. The study explores the synergy of utilizing two independent models, i.e., case 2 regional coast color analytical neural network model and semiempirical remote sensing algorithms to understand the spatiotemporal dynamics of water clarity patterns in the dammed reservoir, in the absence of ground measurements. The drinking water quality and trophic state of the reservoir water is determined based purely on satellite measurements. Out of the five months studied, the reservoir water has high turbidity and poor eutrophic status in three months. The results from both computational models are compared, which exhibit a high degree of statistical agreement. The study demonstrates the effective utilization of relevant analytical and semiempirical methods on satellite data to map water clarity indicators and understand their dynamics in both space and time. This solution is particularly useful for regions where routine ground sampling and observation of environmental variables are absent.