Apps for Smart Groundwater Monitoring and Assessments: A Case Study of Regideso Catchment in Kimbanseke

Abstract

There are various groundwater data bases and scanty/sketchy groundwater monitoring and information systems. Groundwater monitoring has been difficult in the Southern African region, particularly, the Democratic Republic of Congo (DRC), for the water administrative authorities. Water clients do not submit the required compulsory critical data for effective monitoring of water use. This, combined with the absence of limits to boreholes dug by permit holders to the water authorities, has led to challenges in decision-making and groundwater conservation. In this mixed method research, using an Android telephone, well data (water levels) and climatic related information such as precipitation were assembled and sent to a composed store through a sort code/USSD/Instrument free line in texts (SMS). This is proficient through a 3G/GSM/GPRS module that is part of the sensor equipment to be used for this procedure. Once in the store, requests were used to recuperate data in the required design. Additionally, a cloud framework at the point where a long-lasting file was followed up. Although the experimentation is still on-going for the case of the Kimbanseke catchment in DRC, the preliminary findings are that the Kimbanseke catchment has a fluctuating abstraction rate resulting from no clear monitoring mechanism, and that research on the development of an application and/or MS Excel© monitoring spreadsheet, using the scores, and ranking of the factors, is necessary. Therefore, a study was carried out with the aim of creating an analysis application for groundwater sustainability in the Kimbanseke catchment. An application for monitoring and evaluation of the groundwater level should be considered so that the sustainable yield is routinely adjusted for the Kimbanseke catchment.

Keywords

• apps
• artificial intelligence
• groundwater
• monitoring system
• yield