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Spatially Targeting the Expansion of Agricultural Land in a Mountainous Catchment for Maximal Sediment Export Avoidance: Heuristic Optimization Considering Spatial Interaction

  • Pablo Vanegas-Peralta
  • , René Estrella
  • , Geovanny García
  • , Marcelo Peñafiel
  • , Patricia Cazorla
  • , Elina Ávila-Ordóñez
  • , Grethell Castillo-Reyes
  • , Gerdys Jiménez-Moya
  • , Dirk Roose
  • , Jos Van Orshoven
  • Universidad de Cuenca
  • Escuela Superior Politécnica de Chimborazo
  • Universidad de las Ciencias Informáticas
  • KU Leuven

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Vegetation cover has a large impact on the soil loss dynamics of non-sealed, natural surfaces. Forests have meaningful effects on avoiding the production and transport of sediment. In this study, a combination of methods was applied to locate areas within a river catchment in the southern Andes of Ecuador that would produce a maximal or minimal impact on the sediment yield when deforested. RUSLE was applied to compute the amount of local sediment production within the study region. Then CAMF-MFD was used to simulate sediment flow throughout the catchment and to select cells with maximal/minimal impact on sediment yield at the catchment outlet and/or the urban border of the populated area within the catchment. Six scenarios were devised taking all possible combinations of two factors: reference areas (outlet, urban border, or the combination of both), and type of optimization (maximal- or minimal-impact afforested areas that would be converted to agriculture). The outcomes showed the results of CAMF-MFD are in the same order of magnitude as the sediment values obtained by related studies. Additionally, this work provides a means, based on scientifically sound methods, to discriminate between afforested areas that may be converted, in case it is required, to agriculture with a minimum impact on sediment yield, and afforested areas that must not, under any circumstances, be converted to land use types that are less protective to the soil.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2026 Workshops - Proceedings
EditorsOsvaldo Gervasi, M. Noelia Faginas Lago, Beniamino Murgante, Chiara Garau, Ana Maria A. C. Rocha, David Taniar, Yeliz Karaca
PublisherSpringer Science and Business Media Deutschland GmbH
Pages568-585
Number of pages18
ISBN (Print)9783032305268
DOIs
StatePublished - 2027
EventWorkshops of 26th International Conference on Computational Science and its Applications, ICCSA 2026 - Braga, Portugal
Duration: 30 Jun 20263 Jul 2026

Publication series

NameLecture Notes in Computer Science
Volume16761 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceWorkshops of 26th International Conference on Computational Science and its Applications, ICCSA 2026
Country/TerritoryPortugal
CityBraga
Period30/06/263/07/26

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • CAMF
  • deforestation
  • flow and yield
  • heuristic optimization
  • RUSLE
  • sediment production
  • spatial interaction

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