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

Nina Lam,Margaret Reams,Yi Qiang,Lei Zou,David Dismukes,Volodymyr Mihunov,Kam-Biu Liu,Kenan Li,Y Xu,Siddhartha Narra,R Pace,Heng Cai,Thomas Bianchette

doi:10.3390/w10081054

Abstract

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.

Highlights

Coastal communities around the world, such as those in the Mississippi River Delta, are vulnerable to natural resource losses and unsustainability due to multiple hazards that interact with climate change [1]
In an effort to translate thereal results from discriminant into a simpler formand to enable the validated through the use of data of hazard threatanalysis level, economic damage, recovery resilience assessment model serve as a useful planning tool in a real-world setting, we developed a
We show that the black-box data mining approach, such as artificial neural network (ANN), can represent non-linear complex relationships which are common in coupled natural-human system (CNH)

Summary

Introduction

Coastal communities around the world, such as those in the Mississippi River Delta, are vulnerable to natural resource losses and unsustainability due to multiple hazards that interact with climate change [1]. These communities are vital in providing valuable resources and ecosystem services to the region and the world. Water 2018, 10, x FOR PEER REVIEW in other parts of the world (e.g., Nile and Mekong), the region has endured multiple natural and human landscape-level disturbances suchregion as flooding, land loss, subsidence, rise, hurricanes, the world (e.g., Nile and Mekong), the has endured multiple natural sea-level and human landscapeand oil disturbances spills [12,13,14,23,24,25,26,27]. Thousands miles of canalsnatural cut across coastal[31]

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