Berkeley Lab — Lawrence Berkeley National Laboratory

Point to Landscape-Scale: Traits in Agroecology

What to Expect

The shift in the paradigm of point to landscape-scale in agroecology had a tremendous effect on management practices. The advances in computational capabilities and increased efficiency had transformed our thought processes in these areas. Some of the examples of these efforts are to monitor vegetation indices, surface temperature, and soil moisture far from the sky using remote sensing based techniques that had been widely used in agroecology; there are still gaps in these traits either to integrate these processes or in the prediction accuracy. With the help of supercomputers and intelligent algorithms, the data from manned or unmanned aerial vehicles, drones, and lidar technology will further complement the remote sensing techniques in the coming decades. The transfer of knowledge of these landscape-scale advances in agroecology to the end-users is vital for increasing crop productivity and reducing the impacts of climate extremes. This presentation will discuss the benefits and challenges of the effort to develop and utilize the landscape-scale integrated analytic crop water productivity tool supporting multi-year water management decisions. Some real-world examples of solving the compelling problems of agroecology will also be discussed.

Speaker Bio

Ramesh Dhungel is a postdoc on assignment at the Department of Agronomy, Kansas State University. He earned his Ph.D. in civil engineering at the University of Idaho; and later working at the University of California, Merced and Desert Research Institute, Reno, NV. His research focuses on water resources management topics including surface and groundwater interactions, bio-micrometeorology, and modeling atmospheric and environmental processes using remote sensing and geospatial tools. He developed the Backward-averaged iterative two-source surface temperature and energy balance solution (BAITSSS), a biophysical high-resolution (spatial and temporal) land surface model quantifying evapotranspiration.

In the News

Mother Earth News

An integrated analytic framework for water and crop production in agroecosystems (AGU 2019)

Abstract

Globally, drought and water scarcity threaten food security for current and growing populations. This study applies the surface energy balance equation (SEBE) to the agricultural landscape, explicitly linking food, energy and water systems. We synthesize our understanding of accurate accounting for water and corresponding crop production in irrigated and dryland agroecosystems, from point to landscape scale in the semi-arid environment. Our approach includes the flux measurements from lysimeter, eddy covariance systems and farm irrigation records compared against landscape-scale SEBE simulation, utilizing large scale gridded weather data from NLDAS and remote sensing data from satellite and unmanned aerial vehicle platforms. An integrated modeling environment was developed and implemented using the detailed biophysical model, BAITSSS, to quantify evaporation and transpiration fluxes (hourly time resolution; 30 m x 30 m spatial resolution) during the growing season for regional water management districts in the Central High Plains of Kansas and Texas. BAITSSS utilizes continuous vegetation indices and weather variables as boundary conditions required to simulate fluxes in energy and soil water balance. The carbon-water transpiration ratio is used to explicitly link transpiration and primary productivity. Field evidence indicates that this kind of integrated modeling is feasible for a reasonable representation of fluxes, water, and crop production in crops like corn and sorghum. We collaborate with regional groundwater management districts to support effective water management by quantifying crop water consumption at seasonal and regional scales.

2018 Governor's Water Conference

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Open Access Government, 2018

2018 ASA and CSSA Meeting, Baltimore

2017 Ogallala Aquifer Project Workshop