Multi-objective Allocation Optimization of Soil Conservation Measures Under Data Uncertainty.
Many regions worldwide face soil loss rates that endanger future food supply. Constructing soil and water conservation measures reduces soil loss but comes with high labor costs. Multi-objective optimization allows considering both soil loss rates and labor costs, however, required spatial data cont...
| Published in: | Environmental Management Vol. 72; no. 5; pp. 959 - 978 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Published: |
Springer Nature
Nov2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=172020444&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 172020444 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0364152X O5H jtl: Environmental Management issn: 0364152X maglogo: N pubinfo: dt: Nov2023 vid: 72 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 172020444 163962398 10.1007/s00267-023-01837-6 172020444 ppf: 959 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Multi-objective Allocation Optimization of Soil Conservation Measures Under Data Uncertainty. aug: au: Hildemann, Moritz Pebesma, Edzer Verstegen, Judith Anne affil: https://ror.org/00pd74e08 Institute for Geoinformatics, University of Münster, Heisenbergstraße 2, 48149, Münster, Germany sug: ab: Many regions worldwide face soil loss rates that endanger future food supply. Constructing soil and water conservation measures reduces soil loss but comes with high labor costs. Multi-objective optimization allows considering both soil loss rates and labor costs, however, required spatial data contain uncertainties. Spatial data uncertainty has not been considered for allocating soil and water conservation measures. We propose a multi-objective genetic algorithm with stochastic objective functions considering uncertain soil and precipitation variables to overcome this gap. We conducted the study in three rural areas in Ethiopia. Uncertain precipitation and soil properties propagate to uncertain soil loss rates with values that range up to 14%. Uncertain soil properties complicate the classification into stable or unstable soil, which affects estimating labor requirements. The obtained labor requirement estimates range up to 15 labor days per hectare. Upon further analysis of common patterns in optimal solutions, we conclude that the results can help determine optimal final and intermediate construction stages and that the modeling and the consideration of spatial data uncertainty play a crucial role in identifying optimal solutions. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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