Skip to main content
ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » People » Adam Schreiner-McGraw

Adam Schreiner-Mcgraw

Research Hydrologist


Dr. Schreiner-McGraw is a Research Hydrologist for the USDA-ARS in Columbia, Missouri. He is interested in understanding how cropping practices influence water resources in the U.S. Corn Belt, as well as understanding the role of groundwater in controlling crop yield and carbon cycles.

As a research hydrologist with the USDA-ARS, his primary work is related to the Central Mississippi River Basin LTAR site (The Long-Term Agroecosystem Research Network ( He will work to evaluate the behavior of crop water use (evaporation) and growth across the business-as-usual, aspirational, and native prairie sites. His long-term projects seek to evaluate the resilience of these agro-ecosystems to drought and extreme wet periods.

 More information can be found at:


My research
As a research hydrologist, I am primarily concerned with water movement (runoff and evaporation) and storage (soil and groundwater). More specifically, I am an ‘ecohydrologist’, meaning I study how (agro)-ecosystems interact with water resources. With the USDA in Columbia, this means my primary research questions are:

Why I’m doing this research
The U.S. Corn Belt is one of the most intensively managed landscapes in the world and is crucial for supplying food for a growing population. Farm management decisions can have wide ranging consequences affecting crop yield, water quality, and flooding. I aim to evaluate management practices to maximize crop yield under changing environmental conditions, while considering the other societal impacts these practices have.

How my research is conducted
I collect data from environmental sensor networks located in long-term research fields. The primary technique that I use is called ‘eddy covariance’ and it measures evaporation as well as carbon uptake or release from fields. I use this data to test research hypotheses. Also, I use this data to improve the way plants are represented in state-of-the-art hydrologic models. Once I build these models, I can use them to test the impact of farming management at large scales.

Notable findings