Herramienta diseñada en Matlab para la ordenación de redes de drenaje por las jerarquías de Horton y Hack

[EN] This work presents a new MATLAB-based tool designed for network extraction and drainage network orderings by Horton and Hack hierarchies. Most GIS software offers only topological network orderings, based on joining segments, such as Stahler or Shreve, providing segments between junctions but not entire streams. Differently, Hack and Horton orderings allow organizing a drainage network in a hierarchy, identifying the parent segment over the child segment, giving as a result a drainage network where the value of a river remains unchanged from the mouth upstream to the headwater, allowing extracting entire streams. Horton and Hack hierarchies ease the interpretation of a drainage system compared to Strahler and Shreve. To extract the drainage network, this tool uses TopoToolbox 2 functions, to compute the prior steps of the channel network extraction and channel network ordering processes, and develops new functions. To sort a network, this tool allows selecting the parameter that defines the network hierarchy. This parameter is the socalled hierarchy attribute and could be the distance upstream, which refers to the distance between a junction upstream to the headwater, or the upstream accumulation, which is the accumulation at the junction. In addition to these mandatory parameters, the tool offers a set of optional parameters which turns it into a competitive alternative to generate a highly tailored ordered drainage network. The continuous channel network provided by the tool facilitates the use of other multiple applications for landscape analysis, such as the extraction longitudinal profiles or basin analysis through geomorphic indices.[ES] Este trabajo presenta una nueva herramienta diseñada en MATLAB para la extracción y ordenación de redes de drenaje por las jerarquías de Horton y Hack. La mayoría de software GIS ofrece sólo ordenaciones topológicas de redes, basadas en la unión de segmentos, como las ordenaciones de Stahler o Shreve, que proveen segmentos entre puntos de confluencia pero no canales completos. En cambio, las ordenaciones de Hack y Horton permiten organizar una red de drenaje en una jerarquía, identificando el segmento primario sobre el segmento secundario, dando como resultado una red de drenaje donde el valor de un río permanece inalterado desde la desembocadura aguas arriba hasta la cabecera. Las ordenaciones de Horton y Hack facilitan la interpretación de un sistema de drenaje comparado con Strahler y Shreve. Para extraer la red de drenaje, esta herramienta utiliza funciones de TopoToolbox 2 para calcular los pasos previos de los procesos de extracción y ordenación de la red y además desarrolla nuevas funciones. Para ordenar la red, esta herramienta permite seleccionar el parámetro que define la jerarquía de la red. Este parámetro es el llamado atributo de jerarquía que puede ser la distancia aguas arriba, que se refiere a la distancia desde el punto de confluencia a la cabecera, o la acumulación ascendente, que es la acumulación en el punto de confluencia. Además de estos parámetros obligatorios, la herramienta ofrece un conjunto de parámetros opcionales que la convierten en una alternativa competitiva para generar una red de drenaje ordenada personalizada. Esta herramienta permite generar de una red fluvial continua que es requerida en otras múltiples aplicaciones como puede ser para la extracción perfiles longitudinales y/o el análisis de cuencas a través de índices geomórficos.This work was supported by MEC under Grant PEJ2014-A-93258; by UNED under Grant GID2016-19; and it was partially funded by MITE under Grant CGL2014- 59516-P and CARESOIL S2013/MAE-2739 projects.Pastor-Martín, C.; Antón, L.; Fernández-González, C. (2017). Matlab-based tool for drainage network ordering by Horton and Hack hierarchies. En Primer Congreso en Ingeniería Geomática. Libro de actas. Editorial Universitat Politècnica de València. 162-170. https://doi.org/10.4995/CIGeo2017.2017.6607OCS16217

Evaluating river cross section geometry for a hydraulic river routing model : Guadalupe and San Antonio river basins

textA new methodology is presented to construct reliable river channel cross section approximations. These approximations are based on the idea of downstream hydraulic geometry as well as supported by the information collected by the USGS streamflow measurement stations across the study area. A hydraulic river routing model (SPRNT) is run with the newly constructed cross section approximations. Initial conditions for the simulation are estimated based on the steady state solution for the model. Boundary conditions or lateral inflows for the river network are estimated based on the outputs of a Land Surface model: Noah, which provides surface and sub-surface runoff for every catchment area in the San Antonio and Guadalupe river basins. Simulations are compared with observed measurements from the USGS stations.Civil, Architectural, and Environmental Engineerin

New data structure and process model for automated watershed delineation

DEM analysis to delineate the stream network and its associated subwatersheds are the primary steps in the raster-based parameterization of watersheds. There are two widely used methods for delineating subwatersheds. One of these is the Upstream Catchment Area (UCA) method. The UCA method employs a user specified threshold value of upstream catchment area to delineate subwatersheds from the extracted network of streams. The other common technique is the nodal method. In this approach, subwatersheds are initiated at stream network nodes, where nodes occur at the upstream starting point of streams and at the point of intersection of streams in the network. The UCA approach and the Nodal approach do not permit watershed initiation at points of specific interests. They also fail to explicitly recognize drainage features other than single channel reaches. That is, they exclude water bodies, wetlands, braided channels and other important hydrologic features. TOPAZ (TOpographic PArameteriZation) [Garbrecht and Martz, 1992], is a typical program for raster based, automated drainage analysis. It initiates subwatersheds at source points and at points of intersection of drainage channels. TOPAZ treats lakes as spurious depressions arising out of errors in DEM, and removes them. This research addresses one important limitation of the currently used modeling techniques and tools. It adds the capability to initiate watershed delineation at points of specific interest other than junction and source points in the delineated networks from the Digital Elevation Models (DEMs). The research project evaluates qualitative and quantitative aspects of a new Object Oriented data structure and process model for raster format data analysis in spatial hydrology. The concept of incorporating a user-specified analysis in extraction and parameterization of watersheds is based on the need to have a tool to allow for studies specific to certain points in the stream network including gauging stations. It is also based on the need for an improved delineation of hydrologic features (water bodies) in hydrologic modeling. The research project developed an interface module for TOPAZ [Garbrecht and Martz, 1992] to offset the aforementioned disadvantages of the subwatershed delineation techniques. The research developed an internal hybrid, raster-based, Object Oriented data structure and processing model similar to that of vector data type. The new internal data structure permits further augmentation of the software tool. This internal data structure and algorithms provide an improved framework for discretization of the important hydrologic entities (water bodies) and the capability of extracting homogenous hydrological subwatersheds

An objective approach for feature extraction: distribution analysis and statistical descriptors for scale choice and channel network identification

A statistical approach to LiDAR derived topographic attributes for the automatic extraction of channel network and for the choice of the scale to apply for parameter evaluation is presented in this paper. The basis of this approach is to use distribution analysis and statistical descriptors to identify channels where terrain geometry denotes significant convergences. Two case study areas with different morphology and degree of organization are used with their 1 m LiDAR Digital Terrain Models (DTMs). Topographic attribute maps (curvature and openness) for various window sizes are derived from the DTMs in order to detect surface convergences. A statistical analysis on value distributions considering each window size is carried out for the choice of the optimum kernel. We propose a three-step method to extract the network based (a) on the normalization and overlapping of openness and minimum curvature to highlight the more likely surface convergences, (b) a weighting of the upslope area according to these normalized maps to identify drainage flow paths and flow accumulation consistent with terrain geometry, (c) the standard score normalization of the weighted upslope area and the use of standard score values as non subjective threshold for channel network identification. As a final step for optimal definition and representation of the whole network, a noise-filtering and connection procedure is applied. The advantage of the proposed methodology, and the efficiency and accurate localization of extracted features are demonstrated using LiDAR data of two different areas and comparing both extractions with field surveyed networks

Automated Upscaling of River Networks for Macroscale Hydrological Modeling

We developed a hierarchical dominant river tracing (DRT) algorithm for automated extraction and spatial upscaling of basin flow directions and river networks using fine-scale hydrography inputs (e. g., flow direction, river networks, and flow accumulation). In contrast with previous upscaling methods, the DRT algorithm utilizes information on global and local drainage patterns from baseline fine-scale hydrography to determine upscaled flow directions and other critical variables including upscaled basin area, basin shape, and river lengths. The DRT algorithm preserves the original baseline hierarchical drainage structure by tracing each entire flow path from headwater to river mouth at fine scale while prioritizing successively higher order basins and rivers for tracing. We applied the algorithm to produce a series of global hydrography data sets from 1/16 degrees to 2 degrees spatial scales in two geographic projections (WGS84 and Lambert azimuthal equal area). The DRT results were evaluated against other alternative upscaling methods and hydrography data sets for continental U. S. and global domains. These results show favorable DRT upscaling performance in preserving baseline fine-scale river network information including: (1) improved, automated extraction of flow directions and river networks at any spatial scale without the need for manual correction; (2) consistency of river network, basin shape, basin area, river length, and basin internal drainage structure between upscaled and baseline fine-scale hydrography; and (3) performance largely independent of spatial scale, geographic region, and projection. The results of this study include an initial set of DRT upscaled global hydrography maps derived from HYDRO1K baseline fine-scale hydrography inputs; these digital data are available online for public access at ftp://ftp.ntsg.umt.edu/pub/data/DRT/

Assessment of neotectonic landscape deformation in Evia Island, Greece, using GIS-based multi-criteria analysis

This study deals with the assessment and mapping of neotectonic landscape deformation in the northern part of the Evia Island (Central Greece). Multi-Criteria Decision Analysis (MCDA) utilizing Analytic Hierarchy Process (AHP) andWeighted Linear Combination (WLC) procedures were conducted for the calculation of the Neotectonic Landscape Deformation Index (NLDI). The study is based on the combination of morphotectonic, geomorphological and geological parameters. The GIS-based spatial MCDA led to the classification of the study area into five classes of neotectonic deformation (from very low to very high) and to a neotectonic deformation map. The results were compared with the outputs of a relative tectonic activity classification approach based on quantitative geomorphic analysis at a regional scale, including site-specific field observations. Areas of high and very high deformation are related to the major active faults of Dirfis, Kandili and Gregolimano- Telethrio. Other minor active normal faults of medium to high seismic risk level, affecting the northern and northeastern parts of the island, are also associated with areas of intense landscape neotectonic deformation

Giving gully detection a HAND:Testing the scalability and transferability of a semi-automated object-orientated approach to map permanent gullies

Gully erosion can incur on- and off-site impacts with severe environmental and socio-economic consequences. Semi-automated mapping provides a means to map gullies systematically and without bias, providing information on their location and extent. If used temporally, semi-automated mapping can be used to quantify soil loss and identify soil loss source areas. The information can be used to identify mitigation strategies and test the efficacy thereof. We develop, describe, and test a novel semi-automated mapping workflow, gHAND, based on the distinct topographic landform features of a gully to enhance transferability to different climatic regions. Firstly, topographic heights of a Digital Elevation Model are normalised with reference to the gully channel thalweg to extract gully floor elements, and secondly, slope are calculated along the direction of flow to determine gully wall elements. As the gHAND workflow eliminates the need to define kernel thresholds that are sensitive towards gully size, it is more scalable than kernel-based methods. The workflow is rigorously tested at different gully geomorphic scales, in contrasting geo-environments, and compared to benchmark methods explicitly developed for region-specific gullies. Performance is similar to benchmark methods (variance between 1.4 % and 14.8 %). Regarding scalability, gHAND produced under- and over-estimation errors below 30.6 % and 16.1 % for gullies with planimetric areas varying between 1421.6 m2 and 355403.7 m2, without editing the workflow. Although the gHAND workflow has limitations, most markedly the requirement of manually digitising gully headcuts, it shows potential to be further developed to reliably map gullies of small- to large-scales in different geo-environments