A5032118977- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Tropical and Extratropical Cyclones Research
- Cryospheric studies and observations
- Hydrology and Sediment Transport Processes
- Hydrology and Drought Analysis
- Climate change impacts on agriculture
- Disaster Management and Resilience
- Landslides and related hazards
- Hydrological Forecasting Using AI
- Groundwater and Watershed Analysis
- Soil erosion and sediment transport
- Precipitation Measurement and Analysis
- Climate variability and models
- Remote Sensing and LiDAR Applications
- Geophysics and Gravity Measurements
- Meteorological Phenomena and Simulations
- Climate Change, Adaptation, Migration
- Environmental and Agricultural Sciences
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Fish Ecology and Management Studies
- Clinical Nutrition and Gastroenterology
- Computational Physics and Python Applications
- Climate change and permafrost
- demographic modeling and climate adaptation
University of Bristol
2016-2025
Cabot (United States)
2020
Abstract Elevation data are fundamental to many applications, especially in geosciences. The latest global elevation contains forest and building artifacts that limit its usefulness for applications require precise terrain heights, particular flood simulation. Here, we use machine learning remove buildings forests from the Copernicus Digital Model produce, first time, a map of with removed at 1 arc second (∼30 m) grid spacing. We train our correction algorithm on unique set reference 12...
Open-access global Digital Elevation Models (DEM) have been crucial in enabling flood studies data-sparse areas. Poor resolution (>30m), significant vertical errors and the fact that these DEMs are over a decade old continue to hamper our ability accurately estimate hazard. The limited availability of high-accuracy dictate dated open-access still used extensively models, particularly Nevertheless, found give better estimations, thus can be considered 'must-have' for any model. A DEM is not...
Freely available Global Digital Elevation Models (GDEMs) are essential for many scientific and humanitarian applications. Recently, TanDEM-X 90 has been released with a global coverage at 3 arc sec resolution. Its release is sure to generate keen interest as it provides an alternative the widely used Shuttle Radar Topography Mission (SRTM) DEM, especially flood risk management low slope floodplains height errors can become particularly significant. Here, we provide first accuracy assessment...
Digital elevation models (DEMs) provide fundamental depictions of the three-dimensional shape Earth’s surface and are useful to a wide range disciplines. Ideally, DEMs record interface between atmosphere lithosphere using discrete two-dimensional grid, with complexities introduced by intervening hydrosphere, cryosphere, biosphere, anthroposphere. The treatment DEM surfaces, affected these spheres, depends on their intended use, characteristics sensors that were used create them. is general...
We present a practical approach to inter-compare range of candidate digital elevation models (DEMs) based on pre-defined criteria and statistically sound ranking approach. The presented integrates the randomized complete block design (RCBD) into novel framework for DEMs comparison. method provides flexible, customizable tool evaluating quality any raster - in this case DEM by means approach, which takes account confidence level, can use both quantitative qualitative criteria. users their own...
Humanitarian disasters such as Typhoon Haiyan (SE Asia, 2013) and the Horn of Africa drought (2011–2012) are examples natural hazards that were predicted, but where forecasts not sufficiently acted upon, leading to considerable loss life. These events, alongside international adoption Sendai Framework for Disaster Risk Reduction, have motivated efforts enable early action from warnings. Through initiatives Forecast-based Financing (FbF) Science Emergencies Resilience (SHEAR) programme,...
Abstract Flood inundation modeling across large data sparse areas has been increasing in recent years, driven by a desire to provide hazard information for wider range of locations. The sophistication these models steadily advanced over the past decade due improvements remote sensing and capability. There are now several global flood (GFMs) that seek simulate water surface dynamics all rivers floodplains regardless scarcity. However, lack river bathymetry because this cannot be observed...
A large number of historical simulations and future climate projections are available from Global Climate Models, but these typically coarse resolution, which limits their effectiveness for assessing local scale changes in attendant impacts. Here, we use a novel statistical downscaling model capable replicating extreme events, the Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ), to downscale daily precipitation, air-temperature, maximum minimum temperature,...
High-resolution global flood risk maps are increasingly used to inform disaster planning and response, particularly in lower income countries with limited data or capacity. However, current approaches do not adequately account for spatial variation social vulnerability, which is a key determinant of outcomes exposed populations. Here we integrate annual average exceedance probability estimates from high-resolution fluvial model gridded population poverty create vulnerability-adjusted index...
Abstract The Shuttle Radar Topography Mission has long been used as a source topographic information for flood hazard models, especially in data‐sparse areas. Error corrected versions have produced, culminating the latest global error reduced digital elevation model (DEM)—the Multi‐Error‐Removed‐Improved‐Terrain (MERIT) DEM. This study investigates spatial structure of MERIT and Mission, before simulating plausible DEMs using fitted semivariograms. By multiple DEMs, we allow modelers to...
Abstract. Precipitation is the most important driver of hydrological cycle, but it challenging to estimate over large scales from satellites and models. Here, we assessed performance six global quasi-global high-resolution precipitation datasets (European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5), Climate Hazards group Infrared with Stations 2.0 (CHIRPS), Multi-Source Weighted-Ensemble 2.80 (MSWEP), TerraClimate (TERRA), Prediction Unified 1.0 (CPCU),...
At least 10 global digital elevation models (DEMs) at one-arc-second resolution now cover Earth. Comparing derived grids, like slope or curvature, preserves surface spatial relationships, and can be more important than just values. Such comparisons provide nuanced DEM rankings root mean square error (RMSE) for a small number of points. We present three new comparison categories: fraction unexplained variance (FUV) grids with continuous floating point values; accuracy metrics integer code...
<title>Abstract</title> Over a billion people globally are already exposed to the risk of flooding, but by 2050 this number is expected double due human-induced climate change, population growth, and encroachment into at-risk areas. Global Flood Models (GFMs) vital tools for producing flood hazard maps supporting impact estimates policy interventions. These GFMs represent river channels typically assuming that bankfull flow-carrying capacity equates flow with specified return period (RP)...
Coastlines are increasingly vulnerable to the compound effects of high sea levels, intense rainfall, and extreme river discharge from tropical cyclones. Accurate flood modelling is critical for assessing risks informing forecasts under current future climate scenarios. However, in data-sparse regions like southeastern Africa, such faces significant challenges due lack bathymetry data, which cannot be obtained remotely, limited or absent situ gauge data required model calibration. The...
Digital Elevation Models (DEMs) describe the earth surface&#8217;s topography and are an important source of information for applications physical modelling, engineering many others. Flood inundation where water flows determined by terrain slope, is also highly dependent on DEM quality. The most accurate DEMs currently available sourced from airborne LiDAR, however these only cover a small fraction globe, leaving majority globe satellite imagery. Satellite based have limitations...
The estimation, attribution or projection of hydro-meteorological extremes in individual locations is constrained by the limited number observations extreme events. Recent advances large-sample machine learning (ML) models, however, have demonstrated significant potential to mitigate impact data scarcity on quantification hydrological risks. These models integrate hundreds thousands time-series records alongside local descriptors climate and catchment characteristics, enabling them learn...
The increasing frequency and intensity of climate hazards, as emphasized by the IPCC&#8217;s Sixth Assessment Report, underscore urgent need for effective disaster risk reduction strategies. Using devastating floods September 2024 in Nepal&#8217;s Kathmandu Valley, April Kenya&#8217;s Nairobi, this study examines persisting gaps flood resilience despite early warnings using forensics techniques. floods, which were triggered an extreme rainfall event resulting from convergence a...
Global flood models (GFMs) and earth observation (EO) play a crucial role in characterising flooding, especially data-sparse, under-resourced regions of the world. However, validation studies are often limited to handful historic events do not directly assess ability these products simulate hazard—the probability that flooding will occur given location. As result, it is difficult for stakeholders decipher either or observations identify hazard make decisions mitigate flooding. Here, we...
Abstract Kenya and the wider East African region suffer from significant flood risk, as illustrated by major losses of lives, livelihoods assets in most recent years. This is likely to increase future exposure rises rainfall intensifies under climate change. Accordingly, risk management a priority action area Kenya's national change adaptation planning. Here, we outline opportunities challenges improve end‐to‐end early warning systems, considering scientific, technical...
Abstract Southern Asia experiences some of the most damaging climate events in world, with loss life from cyclones hundreds thousands. Despite this, research on extremes region is substantially lacking compared to other parts world. To understand narrative how an extreme event may change future, we consider Super Cyclone Amphan, which made landfall May 2020, bringing storm surges 2–4 m coastlines India and Bangladesh. Using latest CMIP6 model projections, coupled surge, hydrological,...
We present a practical approach to inter-compare range of candidate digital elevation models (DEMs) based on pre-defined criteria and statistically sound ranking approach. The presented integrates the randomized complete block design (RCBD) into novel framework for DEMs comparison. method provides flexible, customizable tool evaluating quality any raster - in this case DEM by means approach, which takes account confidence level, can use both quantitative qualitative criteria. users their own...
In the sparsely investigated region of Congo Basin (CB), flood seasonality and regime shift are established through relative frequency, cluster analysis, directional statistics, non-overlapping block methods based on maxima peak over threshold (POT) series. Two months significantly rich floods observed at all gauging stations. The spatial distribution presents three patterns: north northwest pattern, south southeast west/east pattern. It is that unimodal coherent in northern southern parts,...