عنوان

Utilization of Remote Sensing Data for Estimation of the Groundwater Storage Variation

Number

TL51711

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Utilization of Remote Sensing Data for Estimation of the Groundwater Storage Variation

General Material Designation

[Thesis]

First Statement of Responsibility

Mistry, Gaurang V.

Subsequent Statement of Responsibility

Ahmad, Sajjad

Name of Publisher, Distributor, etc.

University of Nevada, Las Vegas

Date of Publication, Distribution, etc.

2019

Text of Note

101 p.

Dissertation or thesis details and type of degree

M.S.E.

Body granting the degree

University of Nevada, Las Vegas

Text preceding or following the note

2019

Text of Note

Groundwater is the most extracted raw material, with an average withdrawal rate of 982 km3 per year, where 70 percent of the total groundwater withdrawn is used for agriculture globally (Margat & van der Gun, 2013). With climate change and increased water demands in recent years, monitoring the changes in the groundwater storage is of the utmost importance. This thesis presents an analysis that determines the rates, trends, and directions where groundwater storage is going in Pakistan. It also correlates fluctuations in groundwater storage with variations in precipitation and agricultural productivity in the country. The overall objectives of this thesis are to identify the long-term variations in groundwater storage, and examine the impact of precipitation and crop production on the groundwater reserves in Pakistan. In this thesis, The Gravity Recovery and Climate Experiment (GRACE) satellite data are used to estimate changes in groundwater storage for the study period of April 2002 - June 2017. By subtracting the different water subcomponents, i.e. soil moisture and snow water equivalent, derived from the Global Land Data Assimilation System (GLDAS) Noah from the GRACE data products, variations in groundwater storage are estimated. Precipitation data for this study is obtained from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) CDR system. Agricultural information, which includes the crop water requirement, is derived from CROPWAT, and yield data are obtained from the Bureau of Statistics, Punjab. The results reveal that groundwater storage in Pakistan is declining at a high rate. Over a period of 183 months, Punjab province has observed the highest loss in total volume of groundwater storage (28.2 km3), followed by Balochistan (19.57 km3), Khyber Pakhtunkhwa (9.84 km3), and lastly, Sindh (5.46 km3). The results also show that precipitation has a weak positive impact on groundwater storage and soil moisture, depending on the region. Lastly, crop cultivation has had a significant impact on the groundwater withdrawal rates, with amounts varying on a district by district basis. The contributions of this study include a better understanding of variations in the groundwater storage across different provinces in Pakistan, and an analysis of the effect of groundwater changes in relation to crop water demand and precipitation. GRACE data can be used to assess groundwater depletion in areas where groundwater monitoring is not available, as it can help with the evaluation of decreasing trends in groundwater levels. It can also provide policy makers information needed to conserve groundwater resources for future use.

Subject Term

Civil engineering

Subject Term

Water resources management

Mistry, Gaurang V.

Ahmad, Sajjad

University of Nevada, Las Vegas

Electronic name

p

[Thesis]

276903

a

Y