Valuation methodology of laminar erosion potential using fuzzy inference systems in a Brazilian savanna

Souza, José Carlos de; Sales, Jomil Costa Abreu; Lopes, Elfany Reis do Nascimento; Roveda, José Arnaldo Frutuoso; Roveda, Sandra Regina Monteiro Masalskiene; Lourenço, Roberto Wágner

doi:10.1007/s10661-019-7789-1

Cited by 6 publications

(1 citation statement)

References 44 publications

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“…It was identified that the fuzzy application avoided the attenuation that variables classified in "critical conditions" suffer under the influence of other variables classified in "good conditions." Similar results were obtained analyzing fuzzy application in Water Quality Index [91] and Soil Quality Index [92].…”

Section: How Does the Feedback Between The Stages Of The Open-minded Roadmap Support The Decision Making Process?supporting

confidence: 82%

New dilemmas, old problems: advances in data analysis and its geoethical implications in groundwater management

Silva¹,

Matulovic

Manzione

2021

SN Appl. Sci.

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Groundwater governance uses modeling to support decision making. Therefore, data science techniques are essential. Specific difficulties arise because variables must be used that cannot be directly measured, such as aquifer recharge and groundwater flow. However, such techniques involve dealing with (often not very explicitly stated) ethical questions. To support groundwater governance, these ethical questions cannot be solved straightforward. In this study, we propose an approach called “open-minded roadmap” to guide data analytics and modeling for groundwater governance decision making. To frame the ethical questions, we use the concept of geoethical thinking, a method to combine geoscience-expertise and societal responsibility of the geoscientist. We present a case study in groundwater monitoring modeling experiment using data analytics methods in southeast Brazil. A model based on fuzzy logic (with high expert intervention) and three data-driven models (with low expert intervention) are tested and evaluated for aquifer recharge in watersheds. The roadmap approach consists of three issues: (a) data acquisition, (b) modeling and (c) the open-minded (geo)ethical attitude. The level of expert intervention in the modeling stage and model validation are discussed. A search for gaps in the model use is made, anticipating issues through the development of application scenarios, to reach a final decision. When the model is validated in one watershed and then extrapolated to neighboring watersheds, we found large asymmetries in the recharge estimatives. Hence, we can show that more information (data, expertise etc.) is needed to improve the models’ predictability-skill. In the resulting iterative approach, new questions will arise (as new information comes available), and therefore, steady recourse to the open-minded roadmap is recommended. Graphic abstract

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Section: How Does the Feedback Between The Stages Of The Open-minded Roadmap Support The Decision Making Process?supporting

confidence: 82%

New dilemmas, old problems: advances in data analysis and its geoethical implications in groundwater management

Silva¹,

Matulovic

Manzione

2021

SN Appl. Sci.

View full text Add to dashboard Cite

show abstract

The concentration of potentially toxic elements (PTEs) in sausages: a systematic review and meta-analysis study

Nematollahi

Abdi

Abdi-Moghadam

et al. 2021

Environ Sci Pollut Res

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Anthropic Exposure Indicator for River Basins Based on Landscape Characterization and Fuzzy Inference

et al. 2021

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Valuation methodology of laminar erosion potential using fuzzy inference systems in a Brazilian savanna

Cited by 6 publications

References 44 publications

New dilemmas, old problems: advances in data analysis and its geoethical implications in groundwater management

New dilemmas, old problems: advances in data analysis and its geoethical implications in groundwater management

The concentration of potentially toxic elements (PTEs) in sausages: a systematic review and meta-analysis study

Anthropic Exposure Indicator for River Basins Based on Landscape Characterization and Fuzzy Inference

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