Nafiseh Haghtalab

  • Ph.D.

  • Email: haghtala@msu.edu
  • Geography Building
    673 Auditorium Rd, Room 116
    East Lansing, MI 48824
  • Areas of interest: Land use/land cover change, Remote Sensing, Climate Change, Crop modeling, Quantitative modeling
Ph.D.

Research Synopsis:

As a geographer who is doing interdisciplinary research, my research area is very diverse. It mostly focuses on land use/land cover change detection, climate change, climate modeling, and human-environment interactions. In my research, I extensively use remote sensing products and software such as ArcGIS and Erdas Imagine. I work with Python and R programs to process and analyze the data. Also, the climate model that I am working with is WRF (weather research and forecast model) which is dynamical climate model. Beside these, I am familiar with DSSAT (Decision Support System for Agrotechnology Transfer).

My primary research focuses on land use/land cover change interactions with climate. In one of my research, I work on east Africa since the region is very vulnerable to any changes in climate and most people rely on rain-fed agriculture for feeding. When there is a slight change in precipitation amount, intensity, distribution, or timing, they may lose their yield. Actually, there is a strong coupling loop between atmosphere and land, in which any changes in any part of the loop can propagate throughout the whole system. As soil moisture and precipitation are two essential factors in success or failure of the farming season, any perturbation in any of them will change the productivity. Considering food security in Africa, having productive agriculture would assure that. Therefore, in my research, I am going to investigate the land-atmosphere coupling and interactions in east Africa to address food security in that region. I am doing this research under supervision of Dr. Nathan Moore who is an associate professor in the Department of Geography, Environment, and Spatial Science.

In one of our papers entitled “Precipitation Pattern Analysis and Rainy Season Change Detection over Malawi,” we analyzed inter-annual variability of rainy season indices over Malawi. All previous studies found no significant changes in rainfall season using station data. However, using high resolution gridded dataset (CHIRPS), we found that there is a robust change in the onset, cessation, and length of growing season, as well as drought and flood events, which is consistent with the farmers’ claim of changing the climate.

Another research that I am engaged with is about “precipitation recycling analysis” in the Amazon basin. In this research, I am working on land cover change-precipitation pattern change interactions over the basin during the time to depict the spatio-temporal relationship between precipitation and land cover parameters. Ultimately, my goal is to find out if we change the disturbed land cover let say farm land or savannah to forest, can we change the precipitation pattern? To do this, I use WRF (weather research and forecast model) to model the land-atmosphere-human interactions.