scholarly journals Time-series ground-water-level and aquifer-system compaction data, Edwards Air Force Base, Antelope Valley, California, January 1991 through September 1993

1996 ◽  
Author(s):  
L.A. Freeman
Keyword(s):  
Time Series ◽  
Ground Water ◽  
Water Level ◽  
Air Force ◽  
Ground Water Level ◽  
Aquifer System ◽  
Air Force Base

REOF analysis of ground water level variation in an Urban hard rock aquifer system

2021 ◽  
Author(s):  
Vineeth Vijayan ◽  
Parthasarathy Ramachandran
Keyword(s):  
Ground Water ◽  
Water Level ◽  
Hard Rock ◽  
Ground Water Level ◽  
Level Variation ◽  
Water Level Variation ◽  
Aquifer System ◽  
Ground Water Recharge ◽  
Water Recharge ◽  
Hard Rock Aquifer

<p>Strategies for sustainable ground water management are to be planned at regional scale. Urban ground water recharge is complex and dynamic. Various factors contribute to ground water level variation. Understanding the ground water recharge components is essential in planning and management of the water resources in any city. This study attempts to understand the spatiotemporal variations of an urban hard rock aquifer system in Bengaluru, India using REOF analysis and Kriging. Bengaluru meets its needs of water supply from river Cauvery. The water supply utility has an increasing block tariff to control the water demand in the city. But it measures only the use of surface water that is being supplied by the utility. Ground water, being a free resource, bridges the demand supply gap in the city. More than half of the water demand in the city is met through ground water. Hence it is essential to understand the components of ground water level variation in this hard rock aquifer system. Rotated empirical orthogonal function (REOF) analysis of monthly piezometric heads from 153 monitoring wells measured during 2015-2017 is used to identify the primary ground water recharge components. The major components of ground water level variation in the study area was identified as rainfall and pipeline leakage. Ordinary Kriging was used to regionalize the identified significant empirical orthogonal functions.</p>

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