Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories

Landslides are a key hazard in high-relief areas around the world and pose a risk to population and infrastructure. It is important to understand where landslides are likely to occur in the landscape to inform local analyses of exposure and potential impacts. Large triggering events such as earthquakes or major rain storms often cause hundreds or thousands of landslides, and mapping the landslide populations generated by these events can provide extensive datasets of landslide locations. Previous work has explored the characteristic locations of landslides triggered by seismic shaking, but rainfall induced landslides are likely to occur in different parts of a given landscape when compared to seismically induced failures. Here we show measurements of a range of topographic parameters associated with rainfall-induced landslides inventories, including a number of previously unpublished inventories which we also present here. We find that average upstream angle and compound topographic index are strong predictors of landslide headscarp location, while local relief and topographic position index provide a stronger sense of where landslide material may end up (and thus where hazard may be highest). By providing a large compilation of inventory data for open use by the landslide community, we suggest that this work could be useful for other regional and global landslide modelling studies and local calibration of landslide susceptibility assessment, as well as hazard mitigation studies.

Evaluation of the Compound Topographic Index (CTI) for the location of gullies in cultivated areas of Córdoba (Spain)

<p>The identification of areas susceptible to gully formation is an objective that has important consequences for erosion control. It allows for the optimization of resources by focusing on prevention and control efforts on the most susceptible areas, avoiding the frequent evolution of ephemeral to permanent gullies. The issue is of great interest in Spanish olive groves, many of which are affected by serious problems of gully erosion.</p><p>Gullies are formed in the swales, which allows the use of topography-based tools to predict their location.</p><p>The Compound Topographic Index (CTI) proposed by Thorne et al. (1986) is calculated for each pixel as an estimate of the flow capacity to cause erosion, as it includes the product of the pixel draining area and its slope. Its application requires the identification of a critical value of the CTI (CTIc), above which the potential areas of gully occurrence will be located. Using historical orthophotos, the gullies observed were digitized for 2011 in the experimental areas called Morente (11 km<sup>2</sup> of traditional olive groves on degraded and poor vertisols) and Matasanos (6 km<sup>2</sup> of intensive olive groves also on vertisols) and nearby area, with cereal crops.</p><p>The objectives of this work are: to identify CTIc values corresponding to cultivated areas in Cordoba, mainly olive groves; to develop and evaluate an application that allows a user without great technical skills to obtain the CTI; to evaluate the capacity of this CTIc to reproduce gullies observed in nearby areas or in different time periods (2005) to establish cause-effect relationships between changes in landuse in this type of phenomenon, using the aforementioned tool.</p><p>Part of the digitized gullies, representative of olive grove areas, were used to obtain the CTIc of each gully, by modifying it until the best reproduction of the gullies observed was achieved, then their average value was taken as CTIc. To calculate the CTI, a 5m resolution DEM was used, obtained from LiDAR PNOA 2014.</p><p>In the framework of the Innolivar project, a desktop GIS application has been developed in a free software environment such as QGIS, which allows the calculation of the CTI. The APET tool (AGNPS Potential Ephemeral Gully Evaluation Tool) recently implemented has helped in the development of this application.</p><p>The CTI calculation by the application, after the determination of the CTIc threshold, serves to identify critical areas from a DEM, which is free and available in many countries. A first qualitative evaluation by visual verification indicates a very good characterization of the gullies. Subsequently, the goodness of fit of the gully position between the digitized gullies and the app-calculated gullies according to the CTIc is evaluated quantitatively by obtaining a binary confusion matrix by lengths. In the Morente area, an error of omission of 29% and of commission of 16% was obtained.</p><p>It can be concluded that the application generated that allows the application of the CTI methodology makes identification of areas susceptible to gully formation possible in an efficient and relatively simple manner, helping to achieve a more sustainable agriculture.</p>

Using DEM and GIS for evaluation of groundwater resources in relation to landforms in the Maharlou-Bakhtegan watershed, Fars province, Iran

The study of groundwater resources in relation to topography is important. Clearly, in different topography, depth of the water level is different. Therefore, the aim of this study is the determination of the relationship between landform classes with compound topographic index (CTI) and depth of the water for the Maharlou-Bakhtegan watershed, Fars Province, Iran. In order to evaluate the depth of the water for the study area, CTI and geomorphology (landforms) were derived from a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM). The results of landform classes extracted using topographic position index (TPI) showed that the largest landform is open slope, while the smallest are plains. It was found that CTI and depth of the water values are high in plain classes, while they are low in local ridges. High depth of the water were found to be mostly confined to the pit regions in the plain landform, because groundwater recharge occurs in the zones where standing water remains for sufficient long period of time and has favourable condition for recharge.

A Geospatial Liquefaction Model for Rapid Response and Loss Estimation

We describe an approach to model liquefaction extent that focuses on identifying broadly available geospatial variables (e.g., derived from digital elevation models) and earthquake-specific parameters (e.g., peak ground acceleration, PGA). A key step is database development: We focus on the 1995 Kobe and 2010–2011 Christchurch earthquakes because the presence/absence of liquefaction has been mapped so that the database is unbiased with respect to the areal extent of liquefaction. We derive two liquefaction models with explanatory variables that include PGA, shear-wave velocity, compound topographic index, and a newly defined normalized distance parameter (distance to coast divided by the sum of distance to coast and distance to the basin inland edge). To check the portability/reliability of these models, we apply them to the 2010 Haiti earthquake. We conclude that these models provide first-order approximations of the extent of liquefaction, appropriate for use in rapid response, loss estimation, and simulations.

High-resolution global topographic index values for use in large-scale hydrological modelling

Modelling land surface water flow is of critical importance for simulating land surface fluxes, predicting runoff and water table dynamics and for many other applications of Land Surface Models. Many approaches are based on the popular hydrology model TOPMODEL (TOPography-based hydrological MODEL), and the most important parameter of this model is the well-known topographic index. Here we present new, high-resolution parameter maps of the topographic index for all ice-free land pixels calculated from hydrologically conditioned HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) data using the GA2 algorithm (GRIDATB 2). At 15 arcsec resolution, these layers are 4 times finer than the resolution of the previously best-available topographic index layers, the compound topographic index of HYDRO1k (CTI). For the largest river catchments occurring on each continent we found that, in comparison with CTI our revised values were up to 20% lower in, e.g. the Amazon. We found the highest catchment means were for the Murray–Darling and Nelson–Saskatchewan rather than for the Amazon and St. Lawrence as found from the CTI. For the majority of large catchments, however, the spread of our new GA2 index values is very similar to those of CTI, yet with more spatial variability apparent at fine scale. We believe these new index layers represent greatly improved global-scale topographic index values and hope that they will be widely used in land surface modelling applications in the future.

A high-resolution global dataset of topographic index values for use in large-scale hydrological modelling

Modelling land surface water flow is of critical importance for simulating land-surface fluxes, predicting runoff and water table dynamics and for many other applications of Land Surface Models. Many approaches are based on the popular hydrology model TOPMODEL, and the most important parameter of this model is the well-knowntopographic index. Here we present new, high-resolution parameter maps of the topographic index for all ice-free land pixels calculated from hydrologically-conditioned HydroSHEDS data sets using the GA2 algorithm. At 15 arcsec resolution, these layers are 4× finer than the resolution of the previously best-available topographic index layers, the Compound Topographic Index of HYDRO1k (CTI). In terms of the largest river catchments occurring on each continent, we found that in comparison to our revised values, CTI values were up to 20% higher in e.g. the Amazon. We found the highest catchment means were for the Murray-Darling and Nelson-Saskatchewan rather than for the Amazon and St. Lawrence as found from the CTI. We believe these new index layers represent the most robust existing global-scale topographic index values and hope that they will be widely used in land surface modelling applications in the future.

Delineating soil landscape facets from digital elevation models using compound topographic index in a geographic information system

Soil landscapes and their component facets (or sub-units) are fundamental information for land capability assessment and land use planning. The aim of the study was to delineate soil landscape facets from readily available digital elevation models (DEM) to assist soil constraint assessment for urban and regional planning in the coastal areas of New South Wales (NSW), Australia. The Compound Topographic Index (CTI) surfaces were computed from 25 m DEM using a D-infinity algorithm. The cumulative frequency distribution of CTI values within each soil landscape was examined to identify the values corresponding to the area specified for each unmapped facet within the soil landscape map unit. Then these threshold values and CTI surfaces were used to generate soil landscape facet maps for the entire coastal areas of NSW. Specific programs were developed for the above processes in a geographic information system so that they are automated, fast, and repeatable. The modelled facets were assessed by field validation and the overall accuracy reached 93%. The methodology developed in this study has been proven to be efficient in delineating soil landscape facets, and allowing for the identification of land constraints at levels of unprecedented detail for the coast of NSW.