Dr. Nada Jumaa is interested in applying hydrological and water quality modeling to study environmental change in wetlands and agricultural watersheds. Her current research focuses on large-scale modeling, utilizing process-based models (e.g., SWAT+, APEX) and machine learning approaches to evaluate the effectiveness of conservation practices. Her research experience encompasses the integration of satellite remote sensing, digital image processing, environmental economics, GIS and Python-based geospatial analysis, and the analysis of future climate scenarios and land-use change impacts on water quality. She has contributed to projects involving basin-scale pollutant load modeling, HRU-based machine learning predictions, and the assessment of land management scenarios' impacts on water resources. Currently, her research involves large-scale modeling of future climate across the continental USA, employing process-based models and machine learning to evaluate conservation practice effectiveness within the framework of the CEAP and REAP projects, funded by NRCS and ERS. Dr. Jumaa obtained her doctoral degree from Erciyes University, Faculty of Engineering, Department of Environmental Engineering (Turkey), and held a postdoctoral position at Kansas University, where she worked on using machine learning to emulate SWAT+ model outputs to evaluate the effectiveness of agricultural conservation practices on water quality and quantity across the U.S.

Undergraduate Education

B.E. in Civil Engineering - Damascus University

Graduate Education

M.S. in Environmental Economics. Damascus University

Ph.D. in Environmental Engineering. Erciyes University