Flood Prediction in Small Dams through in-situ Sensing Technologies
There is convincing research available that demand-based irrigation system in Pakistan can successfully lead to efficient agricultural water consumption. However, these studies lack implementation. Center for Water Informatics and Technology (WIT) at Lahore University of Management Sciences (LUMS) boasts an extensive experience in the development and deployment of smart water sensors all over Pakistan, for the purpose of efficient water resource management. A moderate scale experimental setup was deployed at Namal Valley located in Mianwali district which hosts socio-ecological-economic importance. The Namal Lake lies in the heart of this valley and serves as a reservoir for the Dane Dam, constructed to feed the Namal canal system which is responsible for irrigating an area of 5,897 acres. The scope of this project is to install the required sensors and gather enough data to develop and test a hydrological model of Namal Lake. The developed model held the capability of predicting the future reservoir level, given a certain climatic event (such as rainfall) occurring in the catchment area, or the opening of the gates on the dam spillway. Furthermore, the developed data-driven hydrological models are to assist in predicting and calculating the risk of floods which have been the cause of infrastructure damage in the past and to prepare suitable plans of actions to mitigate those risks. The sensor network, is also planned to be extended beyond the spillway and towards the outlets of the canal in order to develop a demand-based irrigation system. The project consists of three partners: Namal College, with expertise in developing smart web-based applications and easy access to the lake and local government bodies; SEECS, NUST (NUST's School of Electrical Engineering and Computer Science) with expertise in system identification for open-channel hydraulics; and LUMS with extensive experience in developing ICT Solutions for efficient water resources management for Pakistan.