Precision irrigation
Plant- and soil-based sensing, crop water status, irrigation scheduling, and variable-rate management for specialty crops.
Explore theme →Advancing precision agriculture through sensing, water science, and AI.
I am an Assistant Project Scientist in the Department of Land, Air and Water Resources at UC Davis. My research connects field-scale measurements, remote sensing, hydrology, and machine learning to improve irrigation efficiency, crop productivity, and sustainable resource management.
Srinivasa Rao Peddinti, Ph.D.Assistant Project ScientistLand, Air & Water Resources • UC Davis
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Research focus
Technology that connects the field to better decisions.
I work across scales—from soil and plant sensors to aerial and satellite observations—to understand crop water use and translate measurements into practical irrigation intelligence.
Environmental sensing
Eddy covariance, sap flow, dendrometers, soil moisture and water potential sensors, and IoT-enabled monitoring.
Explore theme →Remote sensing & AI
Satellite and aerial imagery, spatial modeling, machine learning, and decision-support systems for agriculture.
Explore theme →Agrohydrology & geophysics
Electrical resistivity tomography, electromagnetic sensing, soil-water processes, and root-zone characterization.
Explore theme →Research approach
A systems approach to agricultural water management
At UC Davis, I lead and contribute to multidisciplinary projects that connect measurements from the root zone, plant, canopy, and atmosphere. These measurements are integrated with spatial observations and data-driven models to diagnose variability and support management decisions.
The work spans almonds, walnuts, pistachios, grapes, citrus, processing tomatoes, and other cropping systems, with emphasis on technologies that can move from research plots toward commercial agriculture.
FIELD INTELLIGENCE
MEASUREOBSERVEMODELDECIDE
Latest work
Recent publications
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In the field
Research systems in motion.
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