A high-resolution global flood hazard model Sampson, Christopher C.; Smith, Andrew M.; Bates, Paul D. ...
Water resources research,
September 2015, Volume:
51, Issue:
9
Journal Article
Peer reviewed
Open access
Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and ...economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data‐scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross‐disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ∼90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high‐resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ∼1 km, mean absolute error in flooded fraction falls to ∼5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2‐D only variant and an independently developed pan‐European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next‐generation global terrain data sets will offer the best prospect for a step‐change improvement in model performance.
Key Points:
High‐resolution flood hazard model that employs globally available data sets
Quantitative assessment of model performance relative to benchmark local data
Performance adequate for certain real world applications in data‐scarce regions
High‐resolution raster hydrography maps are a fundamental data source for many geoscience applications. Here we introduce MERIT Hydro, a new global flow direction map at 3‐arc sec resolution (~90 m ...at the equator) derived from the latest elevation data (MERIT DEM) and water body data sets (G1WBM, Global Surface Water Occurrence, and OpenStreetMap). We developed a new algorithm to extract river networks near automatically by separating actual inland basins from dummy depressions caused by the errors in input elevation data. After a minimum amount of hand editing, the constructed hydrography map shows good agreement with existing quality‐controlled river network data sets in terms of flow accumulation area and river basin shape. The location of river streamlines was realistically aligned with existing satellite‐based global river channel data. Relative error in the drainage area was <0.05 for 90% of Global Runoff Data Center (GRDC) gauges, confirming the accuracy of the delineated global river networks. Discrepancies in flow accumulation area were found mostly in arid river basins containing depressions that are occasionally connected at high water levels and thus resulting in uncertain watershed boundaries. MERIT Hydro improves on existing global hydrography data sets in terms of spatial coverage (between N90 and S60) and representation of small streams, mainly due to increased availability of high‐quality baseline geospatial data sets. The new flow direction and flow accumulation maps, along with accompanying supplementary layers on hydrologically adjusted elevation and channel width, will advance geoscience studies related to river hydrology at both global and local scales.
Plain Language Summary
Rivers play important roles in global hydrological and biogeochemical cycles, and many socioeconomic activities also depend on water resources in river basins. Global‐scale frontier studies of river networks and surface waters require that all rivers on the Earth are precisely mapped at high resolution, but until now, no such map has been produced. Here we present “MERIT Hydro,” the first high‐resolution, global map of river networks developed by combining the latest global map of land surface elevation with the latest maps of water bodies that were built using satellites and open databases. Surface flow direction of each 3‐arc sec pixel (~90‐m size at the equator) is mapped across the entire globe except Antarctica, and many supplemental maps (such as flow accumulation area, river width, and a vectorized river network) are generated. MERIT Hydro thus represents a major advance in our ability to represent the global river network and is a data set that is anticipated to enhance a wide range of geoscience applications including flood risk assessment, aquatic carbon emissions, and climate modeling.
Key Points
A global hydrography map was generated using the latest topography dataset
Near‐automatic algorithm applicable for global hydrography delineation was developed
Adjusted elevation and river width layers consistent with flow direction map are provided
Since 1996, there have been several case reports of autochthonous visceral leishmaniasis in Thailand. Here we report a case in a 52-year-old Thai male from northern Thailand, who presented with ...subacute fever, huge splenomegaly and pancytopenia. Bone marrow aspiration revealed numerous amastigotes within macrophages. Isolation of Leishmania LSCM1 into culture and DNA sequence analysis (ribosomal RNA ITS-1 and large subunit of RNA polymerase II) revealed the parasites to be members of the Leishmania enriettii complex, and apparently identical to L. martiniquensis previously reported from the Caribbean island of Martinique. This is the first report of visceral leishmaniasis caused by L. martiniquensis from the region. Moreover, the majority of parasites previously identified as "L. siamensis" also appear to be L. martiniquensis.
Spaceborne digital elevation models (DEMs) are a fundamental input for many geoscience studies, but they still include nonnegligible height errors. Here we introduce a high‐accuracy global DEM at 3″ ...resolution (~90 m at the equator) by eliminating major error components from existing DEMs. We separated absolute bias, stripe noise, speckle noise, and tree height bias using multiple satellite data sets and filtering techniques. After the error removal, land areas mapped with ±2 m or better vertical accuracy were increased from 39% to 58%. Significant improvements were found in flat regions where height errors larger than topography variability, and landscapes such as river networks and hill‐valley structures, became clearly represented. We found the topography slope of previous DEMs was largely distorted in most of world major floodplains (e.g., Ganges, Nile, Niger, and Mekong) and swamp forests (e.g., Amazon, Congo, and Vasyugan). The newly developed DEM will enhance many geoscience applications which are terrain dependent.
Key Points
A high‐accuracy global digital elevation model (DEM) was developed by removing multiple height error components from existing DEMs
Landscape representation was improved, especially in flat regions where height error magnitude was larger than actual topography variation
The improved‐terrain DEM is helpful for any geoscience applications which are terrain dependent, such as flood inundation modelling
Plain Language Summary
Terrain elevation maps are fundamental input data for many geoscience studies. While very precise Digital Elevation Models (DEMs) based on airborne measurements are available in developed regions of the world, most areas of the globe rely on spaceborne DEMs which still include non‐negligible height errors for geoscience applications. Here we developed a new high accuracy map of global terrain elevations at 3" resolution (~90m at the equator) by eliminating multiple error components from existing spaceborne DEMs. The height errors included in the original DEMs were separated from actual topography signals and removed using a combination of multiple satellite datasets and filtering techniques. After error removal, global land areas mapped with ±2m or better accuracy increased from 39% to 58%. Significant improvements were found, especially in flat regions such as river floodplains. Here detected height errors were larger than actual topography variability, and following error removal landscapes features such as river networks and hill‐valley structures at last became clearly represented. The developed high accuracy topography map will expand the possibility of geoscience applications that require high accuracy elevation data such as terrain landscape analysis, flood inundation modelling, soil erosion analysis, and wetland carbon cycle studies.
Significant uncertainties remain of how global change impacts on species richness, relative abundance and species composition. Recently, a discussion emerged on the importance of detecting and ...understanding long-term fluctuations in species composition and relative abundance and whether deterministic or non-deterministic factors can explain any temporal change. However, currently, one of the main impediments to providing answers to these questions is the relatively short time series of species diversity datasets. Many datasets are limited to 2 years and it is rare for a few decades of data to be available. In addition, long-term data typically has standardization issues from the past and/or the methods are not comparable. We address several of these uncertainties by investigating bird diversity in a globally important mountain ecosystem of the Hkakabo Razi Landscape in northern Myanmar. The study compares bird communities in two periods (pre-1940: 1900-1939 vs. post-2000: 2001-2006). Land-cover classes have been included to provide understanding of their potential role as drivers. While species richness did not change, species composition and relative abundance differed, indicating a significant species turn over and hence temporal change. Only 19.2% of bird species occurred during both periods. Land-cover model predictors explained part of the species richness variability but not relative abundance nor species composition changes. The temporal change is likely caused by minimal methodological differences and partially by land-cover.
PCR-based methods to amplify the 3' untranslated region (3'-UTR) of the heat shock protein 70 (type I) gene (HSP70-I) have previously been used for typing of Leishmania but not with Leishmania ...(Mundinia) martiniquensis and L. (Mundinia) orientalis, newly identified human pathogens. Here, the 3'-UTRs of HSP70-I of L. martiniquensis, L. orientalis, and 10 other species were sequenced and analyzed. PCR-Restriction Fragment Length Polymorphism (RFLP) analysis targeting the 3'-UTR of HSP70-I was developed. Also, the detection limit of HSP70-I-3'-UTR PCR methods was compared with two other commonly used targets: the 18S small subunit ribosomal RNA (SSU-rRNA) gene and the internal transcribed spacer 1 region of the rRNA (ITS1-rRNA) gene. Results showed that HSP70-I-3'-UTR PCR methods could be used to identify and differentiate between L. martiniquensis (480-2 bp) and L. orientalis (674 bp) and distinguished them from parasites of the subgenus Viannia and of the subgenus Leishmania. PCR-RFLP patterns of the 3'-UTR of HSP70-I fragments digested with BsuRI restriction enzyme successfully differentiated L. martiniquensis, L. orientalis, L. braziliensis, L. guyanensis = L. panamensis, L. mexicana = L. aethiopica = L. tropica, L. amazonensis, L. major, and L. donovani = L. infantum. For the detection limit, the HSP70-I-3'-UTR PCR method could detect the DNA of L. martiniquensis and L. orientalis at the same concentration, 1 pg/μL, at a similar level to the SSU-rRNA PCR. The PCR that amplified ITS1-rRNA was more sensitive (0.01 pg/μL) than that of the HSP70-I-3'-UTR PCR. However, the sizes of both SSU-rRNA and ITS1-rRNA PCR amplicons could not differentiate between L. martiniquensis and L. orientalis. This is the first report of using HSP70-I-3'-UTR PCR based methods to identify the parasites causing leishmaniasis in Thailand. Also, the BsuRI-PCR-RFLP method can be used for differentiating some species within other subgenera.
The characterization of flood behavior in data poor regions has been receiving considerable attention in recent years. In this context, we present the results of regional flood frequency analyses ...(RFFA) conducted using a global database of discharge data. A hybrid‐clustering approach is used in conjunction with a flood‐index methodology to provide a regionalized discharge estimates with global coverage. The procedures are implemented with varying complexity, with results indicating that catchment area and average annual rainfall explain the bulk of variability in flood frequency; a split‐sample validation procedure revealed median errors in the estimation of the 100 year flood to be around 56%. However, far larger errors were also found, with performance varying between climate regions and estimation of the index‐flood found to be the dominant source of uncertainty. Moreover, the RFFA procedure is utilized to provide insights on the statistical characteristics of floods across different climates and catchments.
Key Points:
Regional flood frequency analysis applied at the global scale
Distinct patterns in flood behavior between different climates and catchments
Validation of RFFA at the global scale
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 to the widely used Shuttle Radar Topography Mission (SRTM) DEM, especially for flood risk management as for low slope floodplains height errors can become particularly significant. Here, we provide a first accuracy assessment of TanDEM-X 90 for selected floodplain sites and compare it to other popular global DEMs – the Shuttle Radar Topography Mission (SRTM) and the error-reduced version of SRTM called Multi-Error-Removed-Improved-Terrain (MERIT) DEM. We characterize vertical height errors by comparing against high resolution LiDAR DEMs for 32 floodplain locations in 6 continents. Results indicate that the average vertical accuracy of TanDEM-X 90 and MERIT are similar and are both a significant improvement on SRTM. We further our analysis by assessing vertical accuracy by landcover, with our results suggesting that TanDEM-X 90 is the most accurate global DEM in all landcover categories tested except short vegetation and tree-covered areas where MERIT is demonstrably more accurate. Lastly, we present the first characterization of the spatial error structure of any TanDEM-X DEM product, and find the spatial error structure is similar to MERIT, with MERIT generally having lower sill values and larger ranges than TanDEM-X 90 and SRTM. Our findings suggest that TanDEM-X 90 has the potential to become the benchmark global DEM in floodplains with careful removal of errors from vegetation, and at this stage should be used alongside MERIT in any flood risk application.
Display omitted
•First vertical accuracy assessment of TanDEM-X 90 for floodplain areas•Comparison to other freely available global DEMs•TanDEM-X 90 accuracy correlated to landcover type•First spatial error structure assessment of TanDEM-X 90•TanDEM-X 90 has the potential to be the benchmark global DEM for floodplains.
Improvements in modelling power and input data have vastly improved the precision of physical flood models, but translation into economic outputs requires depth-damage functions that are inadequately ...verified. In particular, flood damage is widely assumed to increase monotonically with water depth. Here, we assess flood vulnerability in the US using >2 million claims from the National Flood Insurance Program (NFIP). NFIP claims data are messy, but the size of the dataset provides powerful empirical tests of damage patterns and modelling approaches. We show that current depth-damage functions consist of disparate relationships that match poorly with observations. Observed flood losses are not monotonic functions of depth, but instead better follow a beta function, with bimodal distributions for different water depths. Uncertainty in flood losses has been called the main bottleneck in flood risk studies, an obstacle that may be remedied using large-scale empirical flood damage data.
Current estimates of global flood exposure are made using datasets that distribute population counts homogenously across large lowland floodplain areas. When intersected with simulated water depths, ...this results in a significant mis-estimation. Here, we use new highly resolved population information to show that, in reality, humans make more rational decisions about flood risk than current demographic data suggest. In the new data, populations are correctly represented as risk-averse, largely avoiding obvious flood zones. The results also show that existing demographic datasets struggle to represent concentrations of exposure, with the total exposed population being spread over larger areas. In this analysis we use flood hazard data from a ~90 m resolution hydrodynamic inundation model to demonstrate the impact of different population distributions on flood exposure calculations for 18 developing countries spread across Africa, Asia and Latin America. The results suggest that many published large-scale flood exposure estimates may require significant revision.
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