Dhruva Kathuria

Dhruva Kathuria

Educational background

Ph. D. (Pursuing)
Biological and Agricultural Engineering

M.Tech., Water Resources & Environmental Engineering
Indian Institute of Science, India (2015)

B.Tech., Civil Engineering
Punjab Engineering College, India (2012)

CV/ Resume
ResearchGategoogle scholarGithub

Research Interests

Remote sensing, Hydrology, Multi-scale data fusion, Non-stationarity, Spatio-temporal statistics for massive datasets

Current project

The global burgeoning of environmental remote sensing datasets in the past decade holds a significant potential in improving our understanding of multi-scale hydrological dynamics. The primary issues that hinder the fusion of different data platforms are

  • Massive size of datasets on a continental scale,
  • Different spatial resolutions of the data platforms,
  • Inherent spatial variability in environmental variables caused due to atmospheric and land surface controls and
  • Measurement errors caused due to imperfect retrievals of remote sensing platforms.

I have recently developed a novel data fusion scheme which takes all the above factors into account using a spatial hierarchical model (SHM). An SHM enables coherent integration of data, science and uncertainties to make optimal predictions at unobserved locations using an underlying non-stationary geostatistical model.

The applicability of the hierarchical approach, however, is severely limited by huge datasets. To account for the massive size of the datasets at a continental scale, I am currently working on a novel extension of a likelihood approximation in a multi-scale multi-platform setting and its subsequent application to fuse in-situ soil moisture observations from SCAN and USCRN with satellite-derived soil moisture products from SMOS and SMAP for Contiguous USA (CONUS). The fusion scheme will be further extended to a multivariate setting to combine different components of the water cycle such as evapotranspiration, rainfall, soil moisture, and ground-water.

Awards, scholarships, & fellowships

  • (2019) Bill and Rita Stout International Graduate Student Achievement Award

List of select publications:

  1. Kathuria, D., Mohanty, B. P. and Katzfuss, M. (2019). A nonstationary geostatistical framework for soil moisture prediction in the presence of surface heterogeneity. Water Resources Research. doi: 10.1029/2018WR023505
  2. Kathuria, D., Mohanty, B. P. and Katzfuss, M. (2018+). Multiscale data fusion for soil moisture estimation: a spatial hierarchical approach (under revision in Water Resources Research, 2018WR024581).
  3. Mao, H., Kathuria, D., Duffield, N and Mohanty, B. P. (2019+). Gap Filling of High-Resolution Soil Moisture for SMAP/Sentinel-1: A Two-layer Machine Learning-based Framework with Spatial/Temporal Transfer Learning (under revision in Water Resources Research, 2019WR024902, preprint: doi: 10.31223/osf.io/ce865)

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