Understanding the Mississippi River Delta as a Coupled Natural-Human System: Research Methods, Challenges, and Prospects Academic Article uri icon


  • A pressing question facing the Mississippi River Delta (MRD), like many deltaic communities around the world, is: Will the system be sustainable in the future given the threats of sea level rise, land loss, natural disasters, and depleting natural resources? An integrated coastal modeling framework that incorporates both the natural and human components of these communities, and their interactions with both pulse and press stressors, is needed to help improve our understanding of coastal resilience. However, studying the coastal communities using a coupled natural-human system (CNH) approach is difficult. This paper presents a CNH modeling framework to analyze coastal resilience. We first describe such a CNH modeling framework through a case study of the Lower Mississippi River Delta in coastal Louisiana, USA. Persistent land loss and associated population decrease in the study region, a result of interplays between human and natural factors, are a serious threat to the sustainability of the region. Then, the paper describes the methods and findings of three studies on how community resilience of the MRD system is measured, how land loss is modeled using an artificial neural network-cellular automata approach, and how a system dynamic modeling approach is used to simulate population change in the region. The paper concludes by highlighting lessons learned from these studies and suggesting the path forward for analysis of coupled natural-human systems.

published proceedings


altmetric score

  • 0.5

author list (cited authors)

  • Lam, N., Xu, Y. J., Liu, K., Dismukes, D. E., Reams, M., Pace, R. K., ... Mihunov, V.

citation count

  • 19

complete list of authors

  • Lam, Nina S-N||Xu, Y Jun||Liu, Kam-biu||Dismukes, David E||Reams, Margaret||Pace, R Kelley||Qiang, Yi||Narra, Siddhartha||Li, Kenan||Bianchette, Thomas A||Cai, Heng||Zou, Lei||Mihunov, Volodymyr

publication date

  • January 2018