Abstract
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
Highlights
Groundwater governance is the commitment to provide water security in terms of quality and quantity for all citizens, making it necessary to ensure that everyone receives water with transportation methods that avoid losses, maintain quality with forms of monitoring and control that equalize the freedom, and power of all agents involved [1,2,3,4,5,6]
We propose to use the concept of geoethics to guide us in the search for ethical solutions for the use of geospatial data in groundwater governance
The membership functions established for the Mamdani’s Fuzzy Inference System (MFIS) used in this study were previous used by Manzione and Matulovic [2] in order to verify the applicability of these functions to EEcSB dataset and respective watersheds
Summary
Groundwater governance is the commitment to provide water security in terms of quality and quantity for all citizens, making it necessary to ensure that everyone receives water (equity) with transportation methods that avoid losses (efficiency), maintain quality (responsibility) with forms of monitoring and control that equalize the freedom (autonomy), and power (representativeness) of all agents involved [1,2,3,4,5,6]. A benchmarking analysis of 84 documents containing ethical guidelines for the use of artificial intelligence (considering data preparation and processing, modeling, and evaluation of results, applied to many uses such as data analytics and decision making [11,12,13]) in public and private companies identified a global convergence around five ethical principles: (1) transparency, (2) justice, (3) non-maleficence, (4) responsibility, and (5) privacy They identified a substantive divergence in how these principles are interpreted, how and why they are considered important and how they should be implemented [12]. Fjeld et al [13] consider that 32 documents converged on eight ethical principles: (1) accountability, (2) equity and non-discrimination, (3) human control of technology, (4) privacy, (5) professional responsibility, (6) promotion of human values, (7) security, and (8) transparency and the ability to be explained
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