A Systematic Review of Ontology-Based River Streamflow and Flood Data Management Challenges

Abstract

The management of the riverine water has always remained an open challenge. The variation of water flow creates hurdles to determine the exact time and the quantity of water flow caused by the spatio-temporal complex streamflow and flood risk reduction domain. From a management perspective, irregular flow patterns generate various challenges and the development of irrigation water distribution schemes without contextual knowledge integration adversely affect the relevant community. The river streamflow and flood mitigation domains are interdisciplinary that require coordination from the various stakeholders. Coordination limiting factors includes native data acquisition methodology of each stakeholder for their specific needs, the complexity of the domain involving a heterogeneous group of managers, spatio-temporal context, region-specific terminologies, data sharing, and reusability support. Earlier proposed research and developed ontologies by the esteemed researchers focused to address these challenges in a domain-specific context. In this research, we review the challenges of a large scale spatio-temporal system for streamflow of watersheds and flood disaster management based on the ontological semantic models. This research also examines the proposed ontological models for streamflow and/or flood domain, and how they address such challenges. Furthermore, a systematic review of the last two decades’ research articles is conducted and the findings are presented to assess the mappings of the challenges to proposed solutions through ontological modeling for streamflow and flood domain.