Waqas Ahmad

Mr. Waqas Ahmad


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2014 in Global and Planetary Change
Verified
Journal Article
Closed access
WAWaqas Ahmad
Waqas Ahmad
AFAamira Fatima
Aamira Fatima
UAUsman Khalid Awan
Usman Khalid Awan
AAArif Anwar
Arif Anwar

14 May 2016 in Irrigation Science
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Journal Article
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PDF file
AAArif Anwar
Arif Anwar
WAWaqas Ahmad
Waqas Ahmad
Muhammad Tousif BhattiMuhammad Tousif Bhatti
Muhammad Tousif Bhatti
ZHZia Ul Haq
Zia Ul Haq

24 June 2013 in Irrigation and Drainage
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Journal Article
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PDF file
AQAsad Sarwar Qureshi
Asad Sarwar Qureshi
WAWaqas Ahmad
Waqas Ahmad
AAAl‐Falahi A. Ahmad
Al‐Falahi A. Ahmad

24 February 2016 in Environmental Earth Sciences
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Journal Article
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UAUsman Khalid Awan
Usman Khalid Awan
AAArif Anwar
Arif Anwar
WAWaqas Ahmad
Waqas Ahmad
MHMohsin Hafeez
Mohsin Hafeez

1 November 2019 in International Journal of Applied Earth Observation and Geoinformation
Verified
Journal Article
Closed access
WAWaqas Ahmad
Waqas Ahmad
DKDongkyun Kim
Dongkyun Kim

25 June 2019 in International Journal of Remote Sensing
Verified
Journal Article
Closed access
WAWaqas Ahmad
Waqas Ahmad
MCMinha Choi
Minha Choi
SKSoohyun Kim
Soohyun Kim
DKDongkyun Kim
Dongkyun Kim
This paper presents the analysis of land subsidence as a result of excessive groundwater abstraction for irrigation and domestic supply in Quetta valley, Pakistan. The European Space Agency (ESA) Sentinel–1 and Sentinel–2 satellite data is used to identify and categorize the spatial distribution of land subsidence. The aquifer geology and observed groundwater table are used to establish the relationship between land subsidence and groundwater abstraction. For this, we performed Persistent Scattering Interferometry (PSIn) analysis using the Sentinel–1 Synthetic Aperture Radar (SAR) imagery to develop 28 maps of land subsidence covering a period of 16 October 2014 to 22 November 2016. The interferometry results matched well with the land subsidence values measured at the Global Positioning System (GPS) ground station with a mean absolute error of 5.7 mm and coefficient of determination of 0.94. The land subsidence values at each pixel of the map were classified according to the land cover types of the study area. Here, the map of land cover types was developed using the multispectral image of Sentinel–2A satellite. The results revealed that, during the 2–year period, the entire study area has suffered from varying degree of accumulated land subsidence ranging between 10 and 280 mm in magnitude, which was linearly proportional to the depth and drawdown of groundwater table observed at four piezometers located in the study area. The magnitude of land subsidence across the study area showed a strong correlation with land covers. The urban area and orchard vegetation with a large amount of groundwater abstraction showed an excessive amount of cumulative land subsidence, while the seasonally cultivated and barren land are slightly affected by land subsidence.