Academic Publications

It is estimated that 2 billion people will move to cities in the next 30 years, many of which possess high seismic risk, underscoring the importance of reliable hazard assessments. Current ground motion models for these assessments typically rely on an extensive catalogue of events to derive empirical Ground Motion Prediction Equations (GMPEs), which are often unavailable in developing countries. Considering the challenge, we choose an alternative method utilizing physics-based (PB) ground motion simulations and develop a simplified decomposition of ground motion estimation by considering regional attenuation (Δ) and local site amplification (𝐴), thereby exploring how much of the observed variability can be explained solely by wave propagation effects. We deterministically evaluate these parameters in a virtual city named Tomorrowville, located in a 3D layered crustal velocity model containing sedimentary basins, using randomly oriented extended sources. Using these physics-based empirical parameters (Δ and 𝐴), we evaluate the intensities, particularly Peak Ground Accelerations (PGA), of hypothetical future earthquakes. The results suggest that the estimation of PGA using the deterministic Δ − 𝐴 decomposition exhibits a robust spatial correlation with the PGA obtained from simulations within Tomorrowville. This method exposes an order of magnitude spatial variability in PGA within Tomorrowville, primarily associated with the near-surface geology and largely independent of the seismic source. In conclusion, advances in PB simulations and improved crustal structure determination offer the potential to overcome the limitations of earthquake data availability to some extent, enabling prompt evaluation of ground motion intensities.

This paper investigates how variations in sediment supply, grain size distribution and climate change affect channel morphology and flood inundation in the Nakkhu River, Kathmandu, Nepal. Climate change induced extreme rainfall is expected to increase flood intensity and frequency, causing severe flooding in the Kathmandu basin. The upper reaches of the Nakkhu River are susceptible to landslides and have been impacted by large-scale sand mining. We simulate potential erosion and deposition scenarios along a 14 km reach of the Nakkhu River using the landscape evolution model CAESAR-Lisflood with a 10 m digital elevation model, field-derived sediment grain size data, daily discharge records and flood forecast models. In a series of numerical experiments, we compare riverbed profiles, cross-sections, flood extent and flow depths for three scenarios (1.2-, 85- and 1000-year return period floods). For each scenario, the model is first run without sediment transport and then with sediment transport for three grain size distributions (GSDs) (observed average, finer and coarser). In all cases, the inclusion of sediment led to predicted floods of a larger extent than estimated without sediment. The sediment grain size distribution was found to have a significant influence on predicted river morphology and flood inundation, especially for lower magnitude, higher probability flood events. The results emphasise the importance of including sediment transport in hydrological models when predicting flood inundation in sediment-rich rivers such as those in and around the Himalaya

Sediment grains are progressively rounded during their transport down a river. For more than a century, Earth scientists have used the roundness of pebbles within modern sediment, and of clasts within conglomerates, as a key metric to constrain the sediment’s transport history and source area(s). However, the current practices of assessment of pebble roundness are mainly qualitative and based on time consuming manual measurement methods. This qualitative judgement provides the transport history only in a broad sense, such as classifying distance as ’near’ or ’far’. In this study, we propose a new model
that quantifies the relationship between roundness and the transport distance.We demonstrate that this model can be applied to the clasts of multiple lithologies including modern sediment as well as conglomerates deposited by ancient river systems. We present field data from two Himalayan catchments in Nepal. We use the Normalized Isoperimetric Ratio (IRn) which relates a pebble’s area (A) to its perimeter (P), to quantify roundness. The maximum analytical value for IRn is 1, and IRn is expected to increase with transport distance. We propose a non-linear roundness model based on our field data, whereby the difference between a grain’s IRn and the maximum value of 1 decays exponentially with transport distance, mirroring Sternberg’s model of mass loss or size reduction by abrasion. This roundness model predicts an asymptotic behaviour for IRn, and the distance over which IRn approaches the asymptote is controlled by a rounding coefficient. Our field data suggest that the roundness coefficient for granite pebbles is eight times that of quartzite pebbles. Using this model, we reconstruct the transport history of a Pliocene paleo-river deposit preserved at the base of the Kathmandu intermontane Basin. These results, along with other sedimentary evidence, imply that the paleo-river was much longer than the length of the Kathmandu Basin, and that it must have lost its headwaters through drainage capture. We further explore the extreme rounding of clasts from Miocene conglomerate of the Siwaliks Zone and find evidence of sediment recycling.

In Press

In Quito, Ecuador, landslides present a significant threat to communities settled on hillsides and ravine slopes, and geotechnical data is needed to assess slope stability. Saturated hydraulic conductivity is a key input parameter for mechanistic modelling of rainfall infiltration and the pore water pressure conditions that can trigger landslides. This paper presents field data of in-situ saturated hydraulic conductivity by working with communities to conduct field measurements on the cemented volcanoclastic soils found in Quito. The new field data is then compared with predictions from recently established geodatabases of hydraulic conductivity obtained from laboratory tests on fine-grained and granular soil.

The utilization of big data has emerged as a critical instrument for land use classification and decision-making processes due to its high spatiotemporal accuracy and ability to diminish manual data collection. However, the reliability and feasibility of big data are still controversial, the most important of which is whether it can represent the whole population with justice. The present study incorporates multiple data sources to facilitate land use classification while proving the existence of data bias caused digital injustice. Using Nairobi, Kenya, as a case study and employing a random forest classifier as a benchmark, this research combines satellite imagery, nighttime light images, building footprint, Twitter posts, and street view images. The findings of the land use classification also disclose the presence of data bias resulting from the inadequate coverage of social media and street view data, potentially contributing to injustice in big data-informed decision-making. Strategies to mitigate such digital injustice situations are briefly discussed here, and more in-depth exploration remains for future work.

This paper examines the impact of rapid urbanisation on the production of unequal disaster risk in Khokana, peri-urban town in the Kathmandu Valley (KV), Nepal. It brings together scholarships in disaster risk creation and urban political ecology (UPE), asking: (1) what are the roots of Khokana’s specific urbanisation trajectory; (2) how is this trajectory altering geographies of hazard risks in Khokana; and (3) how is this risk unevenly distributed between social groups. The data reveal overlapping forms of risk and precarity affecting residents’ (long-standing and migrants) everyday lives, in ways that disproportionately impact already-disadvantaged and marginalised groups. These unequal risk geographies are related to the specific forms and processes of urban growth occurring in Khokana, fuelled by three powerful, interconnected pressures: neoliberal capitalist expansion, internal migration, and a strong developmental state. We characterise the resulting form of urbanisation as ‘haphazard’: a patchwork of planned and unplanned developments, with inadequate attention to hazard risk, livelihood stability and essential services. The paper advances understanding of the place- and historically-specific ways that hazard risk intersects with social, political and economic forces to produce disaster risk in rapidly-urbanising centres. We extend calls for more situated UPE analysis and call for greater, more granular attention to forms of haphazard urbanisation and their uneven risk-producing qualities. We conclude an urgent need to reimagine urban development as a political and economic project, and for future urban planning to pay deliberate and deliberative attention to risk factors, both in KV and in other rapidly urbanising areas of the global South.

This paper argues for normative visioning as an underdeveloped component of adaptation planning.
Multi-stakeholder and normative approaches to future visioning offer generative moments when
creativity can meet the power to act required for critical, including transformative, adaptation.
Including normative methods with community and city actors in adaptation planning allows for
alternative narratives of development to arise as a basis for deeper conversation and potential action
on the root causes of vulnerability and risk. A specific visioning approach is tested for four megacities
– Istanbul, Kathmandu, Nairobi and Quito. Relations between current and future states of
development and resilience are found to be both aligned (congruent or contingent) and in opposition
(countervailing or constrained) shaping strategy for policy setting. These data are combined with
additional work from London, Kolkata, New York and Lagos to pilot a City Resilience Challenge Index
(CRCI), indicating to policy-makers whether and how cities are currently moving away from, rather
than towards, envisioned trajectories of vulnerability reduction and adaptation. In the future, the CRCI
might provide a global tool to track the progress of cities towards climate resilient development and,
by doing so, to increase ambition and galvanize action.

Rainfall-triggered landslides are increasingly a concern in rapidly urbanising areas around the globe. Assessing the stability of slopes is important for geotechnical engineers and planners working in these regions. Saturated hydraulic conductivity is key parameter for assessing the hydrological drivers of slope instability. This paper presents a recent citizen-science case study in Quito, Ecuador, in which saturated hydraulic conductivity measurements were taken in the field on a fine-grained volcanic sediment, often referred to as cangahua, were obtained as part of the Tomorrow’s Cities project on urban multi-hazards and disaster risk management. These data are then used along with a recent soil database of Quito soils (Quito/GEO-299) and other locally obtained soil data and the Combined Hydrology And Stability Model (CHASM) to assess the stability of slopes in a hillside community in South Quito. The paper focuses on the variability of key slope stability parameters, including saturated hydraulic conductivity to assess the plausible ranges of behaviour for slopes in this area.

Atificial light at night (ALAN) has positive and negative effects on social, economic, environmental, and ecological systems, and will increase with urban expansion. In this study, we used a multi-spectral 1.5 m resolution night-time acquisition from a Jilin-1 satellite over the city of Quito, Ecuador, to evaluate spatial lighting patterns in an expanding and topography complex built environment. We demonstrated a requirement for robust georeferencing and orthorectification due to the complex topography, with errors on the order of 4–6 pixels (5.8–8.4  m CE95). We also quantified differences in observed brightness due to the image acquisition and local geometry. Street light type was distinguishable between high-pressure sodium (HPS) and light emitting diode (LED) sources (F1-score = 0.72–0.83) using a shark random forest decision tree approach. Additionally, street lights could be located within 10 m (F1- score = 0.71) with balanced omissions and commissions. Spatial trends revealed that the road network was the dominant source of illumination, accounting for 45% of illuminated pixels, whereas built-up areas accounted for 23%. Overall, 68% of all illuminated pixels were on or within 10 m of the road. Higher socio-economic development was associated with higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. The broad impacts of ALAN mean that addressing the causes and consequences of lighting inequalities is a complex issue. Nonetheless, Jilin-1 night time imagery offers a low-cost way to map and monitor light sources at high-resolution that will be beneficial to city-planners and progressing Sustainable Development Goals.

Disaster risk is the result of complex interactions between the drivers of vulnerability such as poverty and lack of access to resources and the impacts from multiple hazards (with differing intensities and recurrence intervals). These risks are difficult to understand, quantify or convey. Historical hazard events have important potential in generating understanding of multiple potential risks. They provide historical and near-historical records of the real-life experience of relevant hazardous events and their physical, political and social consequences in physically familiar terrain. In this paper, we explore the use of historical research, memory, and emotion in developing conversations around the complexities of multi-hazard risk in urban settings through co-produced interdisciplinary museum exhibits and an educational transmedia platform in Quito, Ecuador. We argue that the opportunity for impact in Disaster Risk Reduction (DRR) arrives by targeting DRR education from an interdisciplinary perspective, with a narrative that draws on history and memory, and that uses art to address emotions and to communicate and visualise two sometimes overlooked but essential dimensions in DRR education: 1) understanding the risk drivers that turn hazardous events into disasters, and 2) building the capacity of communities to imagine future scenarios that reduce risk and create open and participatory processes of risk sensitive urban planning as proposed by the Tomorrow’s Cities Decision Support Environment (TCDSE).