Vinit Sehgal

Louisiana State University;LSUAgCenter | Assistant Professor

Subject Areas: Hydrology, Remote sensing, soil moisture, Soil physics

 Recent Activity

ABSTRACT:

This resource contains the parameters of terrestrial water-energy coupling derived using SMAP and MODIS datasets.

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ABSTRACT:

This resource contains seasonal estimates of global characteristics of surface soil moisture preferential hydrologic states using SMAP observations from March 2015- September 2022. Three tipping characteristics are defined to estimate the intensity (Mean Tipping Depth, epsilon_bar), frequency (Tipping Count, eta), and duration (Mean Tipped Time, tau_bar) of the excursion of SMAP soil moisture from wet− to dry−average conditions.
For details, please refer to our affiliated paper here: https://doi.org/10.22541/essoar.167840001.13313960/v1

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ABSTRACT:

We provide the pathways and parameters of surface soil moisture (SM) drydown using global observations from NASA's Soil Moisture Active Passive (SMAP) at 36 KM spatial resolution. Globally dominant canonical shapes of SM drydowns are identified using a non-parametric approach. A pixel-wise fitting of the selected canonical forms using a non-linear least-squares approach provide the pathways and parameters of SM drydown. The data generated from this study can be used for diverse applications including (and not limited to) identification of dominant soil hydrologic regimes, understanding land-surface coupling strength, and estimating effective soil water retention parameters at remote-sensing footprint scale etc.
Details can be found in our paper: Sehgal, V., Gaur, N., & Mohanty, B. P. (2020). Global Surface Soil Moisture Drydown Patterns. Water Resources Research, 56, e2020WR027588. https://doi.org/10.1029/2020WR027588

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ABSTRACT:

We provide the pathways and parameters of surface soil moisture (SM) drydown using global observations from NASA's Soil Moisture Active Passive (SMAP) at 36 KM spatial resolution. Globally dominant canonical shapes of SM drydowns are identified using a non-parametric approach. A pixel-wise fitting of the selected canonical forms using a non-linear least-squares approach provide the pathways and parameters of SM drydown. The data generated from this study can be used for diverse applications including (and not limited to) identification of dominant soil hydrologic regimes, understanding land-surface coupling strength, and estimating effective soil water retention parameters at remote-sensing footprint scale etc.
Details can be found in our paper: Sehgal, V., Gaur, N., & Mohanty, B. P. (2020). Global Surface Soil Moisture Drydown Patterns. Water Resources Research, 56, e2020WR027588. https://doi.org/10.1029/2020WR027588

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Resource Resource

ABSTRACT:

This resource contains seasonal estimates of global characteristics of surface soil moisture preferential hydrologic states using SMAP observations from March 2015- September 2022. Three tipping characteristics are defined to estimate the intensity (Mean Tipping Depth, epsilon_bar), frequency (Tipping Count, eta), and duration (Mean Tipped Time, tau_bar) of the excursion of SMAP soil moisture from wet− to dry−average conditions.
For details, please refer to our affiliated paper here: https://doi.org/10.22541/essoar.167840001.13313960/v1

Show More
Resource Resource

ABSTRACT:

This resource contains the parameters of terrestrial water-energy coupling derived using SMAP and MODIS datasets.

Show More