Early warning systems and climate resilience

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Moderator of this session: Jan Peter van der Hoek (Waternet)

This session will include the speakers: Juliette Kool (Department of Water Resources, Delft University of Technology,) Maitreyi Koduganti (Indian Institute for Human Settlements, Bengaluru, India) and Roni Deitz (Community & Urban Resilience Planning Practice Lead for Arcadis).

Take a look at the abstracts below:

Unveiling the seasonal inundation dynamics and water-balance of the Mara Wetland, Tanzania through multi-temporal Random Forests classification of Sentinel-2 satellite imagery

Presenting author: Juliette Kool

The Mara Wetland in Tanzania has an important role in regulating the quality, timing and magnitude of the flow of water into Lake Victoria. In addition, the wetland provides natural resources for local communities and habitat for a variety of species. The planned dam construction upstream of the wetland and projected changes in the local climate could affect the physical and ecological equilibrium of the system. Baseline information on seasonal inundation dynamics is necessary to sustainably manage these potential threats. The wetland is sparsely instrumented, which has hampered a thorough temporal and spatial understanding of the local water balance. In addition, the highly vegetated nature of the wetland, and relatively frequent cloud-coverage, motivates multi-source integration of remotely sensed data to capture flood patterns at a high resolution.

In this study, the spatiotemporal inundation pattern of the Mara Wetland in Tanzania is reconstructed using optical remote sensing data. The annual fluctuations in aerial wetland extent are analysed in parallel to the fluctuations of local water balance components: downstream water level of Lake Victoria, upstream discharge, direct precipitation and evaporation. The analysis aims to shed light on the underlying mechanisms and hydrological processes that control the hydric status of the wetland. Comparing the temporal changes in extent with surrounding physical processes provides insight on the responsiveness of the wetland to specific water balance components.

The intra- and inter-annual trends in inundation of the Mara Wetland are reproduced for the years 2017, 2018, 2019. The Random Forests (RF) algorithm is trained bi-seasonally (using bands and derived water and vegetation indices from Sentinel-2 data and a Digital Elevation Model (DEM) as input variables), and used to classify the land-covers of the wetland region in a semi-automated way for a total of 73 Sentinel-2 scenes. The scenes are classified into 7 individual land-cover classes; 3 wetland classes (open water, flooded vegetation, wet floodplain) and 4 dryland classes (dry floodplain, wet agriculture, dry agriculture, bare land). The overall classification accuracy achieved (based on an independent validation set, not used to train the classification algorithm) is 98.6 %. The spatiotemporal variability of the inundated area is used in combination with available hydrological field-data to reproduce the local water balance.

The seasonal expansion and contraction of the wetland follows a consistent bi-modal regime, and the results from the water-balance affirm the importance of local precipitation in the seasonal expansion and contraction of the wetland. The base-flow supplied by the Mara River, together with the backwater from Lake Victoria appear to be at equilibrium at the extent of the permanent swamp during the dry season, insinuating the importance of the river flow during these low-rainfall months. The occasional yet extreme flood events induced by high discharge rates are expected to play a specific ecological role in the wetland, and should be accounted for during future dam operations upstream.

Early Warning Systems in the Digital Age: Investigating the role of social media in disaster communications in Uttarakhand, India.

Presenting author: Maitreyi Koduganti

Access to information and knowledge of natural hazards is critical in all stages of disaster management -mitigation, preparedness, and response and recovery. During the onset of disasters and other extreme events, conventional communication channels fail to function accurately. This leads to increased unrest amidst local populations who need information and guidance, not only for themselves but also to ensure the safety of their loved ones. Hence,having effective early warning systems is of extreme importance.Situated in an ecologically sensitive mountainous region, the state of Uttarakhand in northern India has witnessed a four-fold increase in frequency of floods coupled with a loss of more than thousands of livelihoods and over 50,000 acres of forest cover. To prevent such extensive damage to livelihoods and ecosystems, it is imperative to communicate timely predictions and disaster warnings to all communities living there. Through the present study, we examined how social media, especially Facebook and Twitter, played a key role in early warning messages for disasters between 2019 and 2021 in the state. For this purpose, we engaged in gathering and analysing existing disaster warning data from the two chosen social media platforms using aset of predetermined keywords to develop an analysis framework. These helped us analyse the theme of messaging (seeking assistance; offeringassistance; government/factual info) on the social media platforms; types ofimages posted; and effectiveness of the content during the natural hazards in Uttarakhand.Our analysis revealed that the use of Facebook and Twitter by the public increased several folds between 2019 and 2021 for communicating timely updates and issuing alerts regarding the disaster. In addition, the social media platforms were constantly updating and enhancing their ‘Crisis Response’ features, which enabled faster and efficient communication of hazard related information. Therefore, through our study, we reinforce that social media, including several web-based and mobile technologies such as Twitter Earthquake Detection and other SOS tools,play a critical role in all stages of disaster management, especially in middle-income countries such as India, which are experiencing the greatest risk for disasters with each passing year. Furthermore, we suggest that an increase in social media users across the rural-urban spectrum presents a key opportunity for developing countries to make social media technologies an integral part of early warningdisaster systems.

Building a Climate Resilience Strategy for Lower Manhattan in a Post-Covid Landscape

Presenting author: Roni Deitz

For over 400 years, the historic identity of New York City has been rooted in Lower Manhattan. In October 2012, Hurricane Sandy hit New York City and exposed Lower Manhattan’s vulnerabilities to climate change.  

To reduce both acute and chronic flood risk to the Financial District and Seaport, NYC Economic Development Corporation retained the Arcadis-led consultant Team to study climate adaptation strategies for both neighborhoods. Given the unique convergence of climate risk and physical constraints, it is critical to examine both on-land and in-water solutions (i.e., extending the shoreline of Lower Manhattan via land reclamation) to implement a comprehensive flood risk reduction strategy while maintaining public access to the waterfront and critical maritime functions that serve the region.  

To develop a comprehensive flood risk reduction strategy, the following workstreams were developed and methods are being employed: 

  • Hydrodynamic Modeling – the East River is a highly dynamic environment with fast tidally driven currents, waves, and vessel activity. To study the potential impacts of extending the shoreline, the Arcadis Team leveraged its existing ADvanced CIRculation (ADCIRC) model for the New York Harbor to initially screen options. The Arcadis Team also developed a higher resolution numerical model (e.g., Delft3D), to examine scour and sedimentation concerns across the study area. 
  • Drainage Modeling – regardless of any shoreline modifications to protect against storm surge, sea level rise and more intense storm events will stress the aging and undersized combined sewer system under even future sunny day conditions. To manage interior drainage, the Arcadis Team is working closely with city partners to develop blue-grey solutions to store and pump stormwater.  
  • Urban Programming – while once defined by tall skyscrapers and new residential and commercial real estate, the urban program of the shoreline extension needed to be re-envisioned in response to the COVID-19 pandemic. The Arcadis Team reimagined the shoreline leveraging three key principles: (1) re-connecting people and the water, (2) creating a flexible maritime edge that can respond to future ferry demand and provide space for resilient ferry terminals, and (3) replace existing programming on-site and provide much needed uses and amenities to the area, including improved open space and civic amenities.  
  • Community Outreach – The Arcadis Team is supporting and participating in the City’s effort to conduct a robust and intensive community engagement process, acknowledging a necessary reliance on immersive and interactive digital tools considering COVID-19 and limitations on gatherings. Public engagement tools include: Augmented and virtual reality, online platforms and virtual meeting spaces; as well as non-digital materials such as canvassing the waterfront in multi-lingual materials.  

Our presentation will explore: 

  • The process to develop a set of project alternatives to reduce flood risk – including sea level rise, coastal storms, and precipitation; 
  • Key project challenges and solutions, including siting coastal defense and blue-green drainage infrastructure, as well as protecting complex transportation and low-lying maritime infrastructure all while providing waterfront access and egress; and,  
  • The shift in project vision and reconceptualizing the urban waterfront and landscape for a resilient Lower Manhattan in response to the COVID-19 pandemic.   
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