Can Vegetation Greenness Reliably Predict Stream Drying?
Additional Funding Sources
The project described was supported by the National Science Foundation under Award No. 1653998.
Abstract
Predicting streamflow drying patterns in water-limited regions is important for managing both water quality and quantity. Riparian satellite-derived Normalized Difference Vegetation Index (NDVI) values correlate with short periods of drying in Australian evergreen forests. However, because evergreen vegetation is deep-rooted and tolerates large changes in soil moisture, it may not be affected by the absence of water in nearby streams. Deciduous vegetation may be more sensitive to nearby streamflow, although there is global isotopic evidence that streams and vegetation derive water from two separate sources. We test whether riparian deciduous NDVI predicts stream drying using spectral reflectance sensors to measure top-of-canopy NDVI in riparian zones in Murphy Creek, an intermittent, discontinuous stream in semi-arid southern Idaho. We compare measured NDVI to water level along the stream network over the seasonal stream recession and also compare ground-based and satellite-based NDVI at varying resolutions. Preliminary results show a moderate correlation between stream dryness and NDVI values in summer, and a weaker correlation in late spring; this relationship is obscured by low-resolution satellite imagery. If the seasonal NDVI-drying pattern strengthens as the stream network contracts and disconnects, vegetation greenness may help predict dynamic surface water availability throughout headwater networks in semi-arid regions.
Can Vegetation Greenness Reliably Predict Stream Drying?
Predicting streamflow drying patterns in water-limited regions is important for managing both water quality and quantity. Riparian satellite-derived Normalized Difference Vegetation Index (NDVI) values correlate with short periods of drying in Australian evergreen forests. However, because evergreen vegetation is deep-rooted and tolerates large changes in soil moisture, it may not be affected by the absence of water in nearby streams. Deciduous vegetation may be more sensitive to nearby streamflow, although there is global isotopic evidence that streams and vegetation derive water from two separate sources. We test whether riparian deciduous NDVI predicts stream drying using spectral reflectance sensors to measure top-of-canopy NDVI in riparian zones in Murphy Creek, an intermittent, discontinuous stream in semi-arid southern Idaho. We compare measured NDVI to water level along the stream network over the seasonal stream recession and also compare ground-based and satellite-based NDVI at varying resolutions. Preliminary results show a moderate correlation between stream dryness and NDVI values in summer, and a weaker correlation in late spring; this relationship is obscured by low-resolution satellite imagery. If the seasonal NDVI-drying pattern strengthens as the stream network contracts and disconnects, vegetation greenness may help predict dynamic surface water availability throughout headwater networks in semi-arid regions.
Comments
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