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🛰 Satellite(s)

MODIS, Sentinel-2, GRACE.

📊 Monitoring element

Land spectral reflectance.

🧰 Description technique

Bhanja et al. (2019) investigated the possibility of using Normalized Difference Vegetation Index (NDVI) as an indicator of groundwater storage is investigated, using . They used artificial neural network and support vector machine approaches and sand in-situ observations from groundwater wells.

📏 Accuracy / Resolution

Good correlation (r> 0.6) between NDVI and groundwater levels in natural vegetation covered areas (i.e., forest lands, shrubs, and grasslands).

🗺 Case study

India (> 15,000 wells).

Tip

Benefits

  • NDVI maybe used as a suitable indicator of groundwater storage conditions in certain areas where the water table is shallow and the vegetation is natural and where in situ groundwater observations are not available.

  • This presents a real benefit as NDVI can be measured at relatively high resolution using multiple types of remote sensing observations, while groundwater monitoring via satellite gravimetry (e.g., GRACE) provides only coarse resolution.

🧩 Also fits domain

Land.

Note

Limitations

Correlation between observed groundwater levels and NDVI is not good in agricultural regions, suggesting human influences on these parameters.

Info

Applicability for Northland

Yes, likely applicable.

A method based on Normalized Difference Vegetation Index (NDVI), as an indicator of groundwater storage, could be investigated for natural vegetation covers. Correlations would need to be confirmed in the Northland context and finer spatial resolution imagery (e.g. Sentinel-2) would be more relevant to use. GRACE-derived information would be too coarse for local applications.

Techniques applying optical data will be limited in coverage and temporal granularity by the persistent cloud cover in the region, particularly during the winter months. Mature cloud-masking techniques are directly available for open access multispectral data (e.g. Landsat and Sentinel-2). When using commercial data, care must be taken to ensure that there is sufficiently cloud free imagery available, as cloud masking is not as mature, and ordering a large volume of imagery to ensure complete cloud free coverage between multiple observations can become cost prohibitive.

Publication references

📚 Bhanja SN, Malakar P, Mukherjee A, Rodell M, Mitra P, Sarkar S. 2019. Using Satellite-Based Vegetation Cover as Indicator of Groundwater Storage in Natural Vegetation Areas. Geophysical Research Letters. 46(14):8082-8092. doi:10.1029/2019GL083015.

🔗 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL083015

Other references

📚 Abiy AZ, Melesse AM. 2017. Evaluation of watershed scale changes in groundwater and soil moisture storage with the application of GRACE satellite imagery data. CATENA. 153:50-60.

🔗 https://doi.org/10.1016/j.catena.2017.01.036


📚 Frappart F, Ramillien G. 2018. Monitoring Groundwater Storage Changes Using the Gravity Recovery and Climate Experiment (GRACE) Satellite Mission: A Review. Remote Sensing. 10(6):829.

🔗 https://www.mdpi.com/2072-4292/10/6/829

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