Sustainability 2022, 14, 148. https://doi.org/10.3390/su14010148 www.mdpi.com/journal/sustainability Review A Review of Groundwater Management Models with a Focus on IoT-Based Systems Banjo Ayoade Aderemi 1, *, Thomas Otieno Olwal 1 , Julius Musyoka Ndambuki 2 and Sophia Sudi Rwanga 3 1 Department of Electrical Engineering, Tshwane University of Technology, Pretoria 0183, South Africa; OlwalTO@tut.ac.za 2 Department of Civil Engineering, Tshwane University of Technology, Pretoria 0183, South Africa; NdambukiJM@tut.ac.za 3 Department of Civil Engineering, Vaal University of Technology, Vanderbijlpark 1900, South Africa; sophiar@vut.ac.za * Correspondence: ayoadebanjo93@hotmail.com; Tel.: +27-78-354-2284 Abstract: Globally, groundwater is the largest distributed storage of freshwater and plays an im- portant role in an ecosystem’s sustainability in addition to aiding human adaptation to both climatic change and variability. However, groundwater resources are dynamic and often change as a result of land usage, abstraction, as well as variation in climate. To solve these challenges, many conven- tional solutions, such as certain numerical techniques, have been proffered for groundwater mod- elling. The global evolution of the Internet of Things (IoT) has enhanced the culture of data gathering for the management of groundwater resources. In addition, efficient data-driven groundwater re- source management relies hugely on information relating to changes in groundwater resources as well as their availability. At the moment, some studies in the literature reveal that groundwater managers lack an efficient and real-time groundwater management system which is needed to gather the required data. Additionally, the literature reveals that the existing methods of collecting data lack the required efficiency to meet computational model requirements and meet management objectives. Unlike previous surveys, which solely focussed on particular groundwater issues related to simulation and optimisation management methods, this paper seeks to highlight the current groundwater management models as well as the IoT contributions. Keywords: Internet of Things (IoT); groundwater level; groundwater resource; groundwater management models; groundwater monitoring system; wireless sensor network 1. Introduction About approximately one-third of global freshwater consumption depends on groundwater resources; thus, it has become an important source of freshwater globally [1]. In the water cycle, the freshwater resource accounts for approximately 4% of the total water available on earth, while the remaining 96% is salty, found within seas and oceans [2]. Meanwhile, only about 0.001% of water is available as a groundwater resource that is hidden underground, while 75% is ice and about 25% is liquid water [3]. Therefore, groundwater resources constitute approximately 98% of all fresh liquid water available on earth [4]. Since both plants and animals depend on water, the interaction between sur- face water systems and groundwater resources is essential for basic life on the earth. This makes groundwater the largest distributable storage of freshwater which plays an im- portant role in an ecosystem’s sustainability as well as in aiding human adaptation to both climatic change and variability [5]. Human beings largely depend on groundwater re- sources as a major supply of their drinking water. Thus, the efficient measurement, mon- itoring, and management of groundwater resources are crucial to ensure future sustaina- bility. Nonetheless, human activities and a lack of planning for these activities have led to Citation: Aderemi, B.A.; Olwal, T.O.; Ndambuki, J.M.; Rwanga, S.S. A Review of Groundwater Management Models with a Focus on IoT-Based Systems. Sustainability 2022, 14, 148. https://doi.org/10.3390/ su14010148 Academic Editor: Shervin Hashemi Received: 17 November 2021 Accepted: 21 December 2021 Published: 23 December 2021 Publisher’s Note: MDPI stays neu- tral with regard to jurisdictional claims in published maps and institu- tional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and con- ditions of the Creative Commons At- tribution (CC BY) license (https://cre- ativecommons.org/licenses/by/4.0/).