An investigation into the role of crowdsourcing in generating information for flood risk management

Flooding is a major global hazard whose management relies on an accurate understanding of its risks. Crowdsourcing represents a major opportunity for supporting flood risk management as members of the public are highly capable of producing useful flood information. This thesis explores a wide range of issues related to flood crowdsourcing using an interdisciplinary approach. Through an examination of 31 different projects a flood crowdsourcing typology was developed. This identified five key types of flood crowdsourcing: i) Incident Reporting, ii) Media Engagement, iii) Collaborative Mapping, iv) Online Volunteering and v) Passive VGI. These represent a wide range of initiatives with radically different aims, objectives, datasets and relationships with volunteers. Online Volunteering was explored in greater detail using Tomnod as a case study. This is a micro-tasking platform in which volunteers analyse satellite imagery to support disaster response. Volunteer motivations for participating on Tomnod were found to be largely altruistic. Demographics of participants were significant, with retirement, disability or long-term health problems identified as major drivers for participation. Many participants emphasised that effective communication between volunteers and the site owner is strongly linked to their appreciation of the platform. In addition, the feedback on the quality and impact of their contributions was found to be crucial in maintaining interest. Through an examination of their contributions, volunteers were found to be able to ascertain with a higher degree of accuracy, many features in satellite imagery which supervised image classification struggled to identify. This was more pronounced in poorer quality imagery where image classification had a very low accuracy. However, supervised classification was found to be far more systematic and succeeded in identifying impacts in many regions which were missed by volunteers. The efficacy of using crowdsourcing for flood risk management was explored further through the iterative development of a Collaborative Mapping web-platform called Floodcrowd. Through interviews and focus groups, stakeholders from the public and private sector expressed an interest in crowdsourcing as a tool for supporting flood risk management. Types of data which stakeholders are particularly interested in with regards to crowdsourcing differ between organisations. Yet, they typically include flood depths, photos, timeframes of events and historical background information. Through engagement activities, many citizens were found to be able and motivated to share such observations. Yet, motivations were strongly affected by the level of attention their contributions receive from authorities. This presents many opportunities as well as challenges for ensuring that the future of flood crowdsourcing improves flood risk management and does not damage stakeholder relationships with participants

The motivations, enablers and barriers for voluntary participation in an online crowdsourcing platform

This paper examines the phenomena of online crowdsourcing from the perspectives of both volunteers and the campaign coordinator of Tomnod – an online mapping project that uses crowdsourcing to identify objects and places in satellite images. A mixed-methods approach was used to study the enablers and barriers to participation, taking into consideration the whole spectrum of volunteers. The results show broad diversity in online volunteers, both in their demographics and the factors affecting their voluntary participation. The majority are older than 50 years and many – particularly the most active volunteers – have disabilities or long term health problems. The personal circumstances of participants are highlighted as a major factor affecting involvement in campaigns. Like many other platforms, altruism is a key motivator, yet many participants are more interested in the quality of their data and the impact it has on the ground. For many participants of online crowdsourcing campaigns, their involvement is strongly linked to the level of contact they have with campaign coordinators, both in the design of the platform and in providing feedback on the impact of their contributions

Micro and Macroscale Drivers of Nutrient Concentrations in Urban Streams in South, Central and North America.

Global metrics of land cover and land use provide a fundamental basis to examine the spatial variability of human-induced impacts on freshwater ecosystems. However, microscale processes and site specific conditions related to bank vegetation, pollution sources, adjacent land use and water uses can have important influences on ecosystem conditions, in particular in smaller tributary rivers. Compared to larger order rivers, these low-order streams and rivers are more numerous, yet often under-monitored. The present study explored the relationship of nutrient concentrations in 150 streams in 57 hydrological basins in South, Central and North America (Buenos Aires, Curitiba, São Paulo, Rio de Janeiro, Mexico City and Vancouver) with macroscale information available from global datasets and microscale data acquired by trained citizen scientists. Average sub-basin phosphate (P-PO4) concentrations were found to be well correlated with sub-basin attributes on both macro and microscales, while the relationships between sub-basin attributes and nitrate (N-NO3) concentrations were limited. A phosphate threshold for eutrophic conditions (>0.1 mg L-1 P-PO4) was exceeded in basins where microscale point source discharge points (eg. residential, industrial, urban/road) were identified in more than 86% of stream reaches monitored by citizen scientists. The presence of bankside vegetation covaried (rho = -0.53) with lower phosphate concentrations in the ecosystems studied. Macroscale information on nutrient loading allowed for a strong separation between basins with and without eutrophic conditions. Most importantly, the combination of macroscale and microscale information acquired increased our ability to explain sub-basin variability of P-PO4 concentrations. The identification of microscale point sources and bank vegetation conditions by citizen scientists provided important information that local authorities could use to improve their management of lower order river ecosystems

Correlating surface water flood damages in three Indonesia cities [Abstract]

Despite a high growth rate of over 5%, the insurance penetration rate in Indonesia is low, at roughly 2.77 percent and is one of the least developed insurance market among ASEAN economies. A primary explanation for the lack of motivation for taking up insurance is due to the lack of understanding of the multitude of risks from natural hazards the Indonesian market faces, principally of flooding. The purpose of this research is to assess the flood correlation between three of the major cities (Jakarta, Semarang, and Solo) on the island of Java. These highly populated and financial centres of Indonesia are most prone to the rainfall extremes during the Monsoon Season (November – March), many of which causes flooding. All the historical rainfall events were extracted from ECMWF’s ERA-5 hourly rainfall dataset (1979 – 2018). The top 10 events for each city were selected based on peak rainfall intensity. For the selected events in a city, rainfall records of the same period were extracted for the other two cities. This results in 30 simulations per city. Using a 2D hydraulic modelling tool (FloodMap), surface water flood footprints were generated for the events. In the absence of depth-damage curves, the number of buildings flooded under each event were used as an approximation to building damages. Damage to buildings due to surface water flooding in Solo and Semarang were found to be most correlated, with a significant number of buildings flooded in both cities in 15 out of the 20 paired events. Solo and Jakarta show some correlation (7 out of 20) whilst flooding in Semarang and Jakarta are least correlated (4 out of 20). This study is an initial analysis relevant to the modelling of catastrophes in a relatively data sparse environment, providing an approximation of the correlation of flooding between three Indonesian cities. Further studies are required to develop pragmatic approaches to complement catastrophe modelling that integrate the spatial correlation between flood damages in cities.</p

Spearman’s rho between sub-basin averaged phosphate and nitrate concentrations (n = 57) and microscale and macroscale variables.

<p>*AHWS refers to the Adjusted Human Water Security, [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0162684#pone.0162684.ref029" target="_blank">29</a>]. **Significant p-values, considering multiple hypotheses are below 0.002 (Bonferroni correction).</p

a) Global location of study areas, b) Sub-basins and sampling sites examined by citizen scientists in Buenos Aires, c) Curitiba, d) São Paulo, e) Rio de Janeiro, f) Mexico City and g) Vancouver.

<p>Basemap image reprinted from Esri under a CC BY license with permission from Esri and its licensors, original copyright June 2009.</p

Average concentrations of phosphate (a) and nitrate (b) measured in each sampled sub-basins (Level 10 HydroBasins on y axis) in Buenos Aires, Curitiba, Mexico City, Rio de Janeiro, São Paulo and Vancouver.

<p>Bars indicate 2 standard errors (SE).</p