Applications of remote sensing to groundwater hydrology

Waters, Pauline; Greenbaum, D.; Smart, Peter L.; Osmaston, Henry

doi:10.1080/02757259009532107

Cited by 72 publications

(42 citation statements)

References 23 publications

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“…Harnessing remote sensing technologies for interpreting groundwater dynamics is a cost-efficient approach to capture phenomena at a greater extent more quickly than possible on the ground (Waters et al, 1990, Fernandez, 2013. There are, however, many constraints in remote sensing and GIS applications due to limited understanding of how to interpret groundwater hydrology (Jha et al, 2007).…”

Section: Subsurface: Groundwater Monitoringmentioning

confidence: 99%

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

Rodriguez

Ustin

Sandoval-Solís

et al. 2016

Science of The Total Environment

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Earthquakes often cause destructive and unpredictable changes that can affect local hydrology (e.g. groundwater elevation or reduction) and thus disrupt land uses and human activities. Prolific agricultural regions overlie seismically active areas, emphasizing the importance to improve our understanding and monitoring of hydrologic and agricultural systems following a seismic event. A thorough data collection is necessary for adequate postearthquake crop management response; however, the large spatial extent of earthquake's impact makes challenging the collection of robust data sets for identifying locations and magnitude of these impacts. Observing hydrologic responses to earthquakes is not a novel concept, yet there is a lack of methods and tools for assessing earthquake's impacts upon the regional hydrology and agricultural systems. The objective of this paper is to describe how remote sensing imagery, methods and tools allow detecting crop responses and damage incurred after earthquakes because a change in the regional hydrology. Many remote sensing datasets are long archived with extensive coverage and with well-documented methods to assess plant-water relations. We thus connect remote sensing of plant water relations to its utility in agriculture using a post-earthquake agrohydrologic remote sensing (PEARS) framework; specifically in agro-hydrologic relationships associated with recent earthquake events that will lead to improved water management.© 2016 Elsevier B.V. All rights reserved. Keywords:Agro-hydrology Disaster management Monitoring Plant-water relations Post-earthquake agrohydrologic remote sensing (PEARS) Remote sensing Background, scope & needEarthquake events threaten food security, resource management and human life, and are observed to be steadily increasing (Ellsworth, 2013). As observed earthquake events continue to increase, it is important to explore and improve response and recovery strategies. Infrastructural damages, especially in urban environments, are at the forefront of research in remote sensing of earthquake-associated damage. Agricultural environments also face catastrophic impacts, often due to adverse hydrologic behavior following the event. The earthquake-water linkage poses particular threats to agricultural productivity, yet difficulty lies in predicting the location, destructiveness, and extent of damage. While effects of earthquake-induced hydrologic changes on crops remain largely unexplored, remote sensing of crop water relations provide a suite of tools to monitor responses and to mitigate crop loss. Remote sensing can address these challenges with archived imagery that has extensive spatial coverage. There are conceptual models that explicitly walk through remote sensing in disaster management (Joyce et al., 2009b) and remote sensing of post-earthquake urban damage (Eguchi et al., 2003) -leaving a gap at the interface of post-earthquake remote sensing of agricultural impacts. We therefore draw attention to current research in understanding earthquake impacts on agric...

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Section: Subsurface: Groundwater Monitoringmentioning

confidence: 99%

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

Rodriguez

Ustin

Sandoval-Solís

et al. 2016

Science of The Total Environment

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“…Lineaments captured from imagery often provide a crucial clue on the interpretation and analysis of fractured rocks and associated groundwater flow regimes. The main assumption that underlies all lineament analyses is that the linear features, when properly identified, represent the surface manifestations of the transmissive fracture framework of low-permeability rocks (O'Leary et al, 1976;Waters et al, 1990;Degnan et al, 2002). Lineaments are usually characterised by azimuth and length distributions, length density (total length of lineaments per unit area), frequency (total number of lineaments per unit area), and intersection point density (total number of lineament intersection points per unit area).…”

Section: Application Of Remotely-sensed Datamentioning

confidence: 99%

Characterisation of fracture network and groundwater preferential flow path in the Table Mountain Group (TMG) sandstones, South Africa

Li¹,

Lin²,

Xu³

2014

WSA

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Characterisation of fractured rocks and evaluation of fracture connectivity are essential for the study of subsurface flow and transport in fractured rock aquifers. In this study, we use a new method to present fracture networks and analyse the connectivity of the fractures, based on the technique of randomly-generated realisations. The application of the method aims to provide more detailed insights into the flow path and dynamics for sustainable utilisation of groundwater in the Table Mountain Group (TMG) aquifers, South Africa. Focusing on a representative wellfield in the TMG, the interpretation and integration of fracture data derived from field measurements, existing geological maps and remotely-sensed imagery, and observed responses of hydraulic tests, led to the development of a conceptual model for fracture network characterisation, which forms the basis of fracture connectivity analysis. The result shows that the a dominant number of the interconnected fractures are in the form of separated fracture clusters (networks) which is considered to be a common connectivity pattern in the TMG rocks and alike. The result also suggests that the connectivity pattern is collectively dependent on such factors as orientation, length, and density of fractures and implies that in a study domain only a small part of the fractures are responsible for flow circulation.

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“…It is important to note that groundwater mapping is an unusual application for Earth-observing sensors, since the target-of-interest is not directly observable from the sky [12,13]. As a result, various methods have been developed aimed at proxy measures of groundwater in peatlands, such as plant water stress, vegetation composition and density, soil-moisture content, topographic features, and other indirect indicators.…”

Section: Introductionmentioning

confidence: 99%

A New Method to Map Groundwater Table in Peatlands Using Unmanned Aerial Vehicles

et al. 2017

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Groundwater level (GWL) and depth to water (DTW) are related metrics aimed at characterizing groundwater-table positions in peatlands, and two of the most common variables collected by researchers working in these ecosystems. While well-established field techniques exist for measuring GWL and DTW, they are generally difficult to scale. In this study, we present a novel workflow for mapping groundwater using orthophotography and photogrammetric point clouds acquired from unmanned aerial vehicles. Our approach takes advantage of the fact that pockets of surface water are normally abundant in peatlands, which we assume to be reflective of GWL in these porous, gently sloping environments. By first classifying surface water and then extracting a sample of water elevations, we can generate continuous models of GWL through interpolation. Estimates of DTW can then be obtained through additional efforts to characterize terrain. We demonstrate our methodology across a complex, 61-ha treed bog in northern Alberta, Canada. An independent accuracy assessment using 31 temporally coincident water-well measurements revealed accuracies (root mean square error) in the 20-cm range, though errors were concentrated in small upland pockets in the study area, and areas of dense tree covers. Model estimates in the open peatland areas were considerably better.

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Applications of remote sensing to groundwater hydrology

Cited by 72 publications

References 23 publications

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

Characterisation of fracture network and groundwater preferential flow path in the Table Mountain Group (TMG) sandstones, South Africa

A New Method to Map Groundwater Table in Peatlands Using Unmanned Aerial Vehicles

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