Abstract: Systems and methods for coagulation optimization may include a control system deployed at the water treatment plant operating with a computing system executing various control model(s). The computing system may receive data including one or more water quality metrics and a settled turbidity setpoint of output water. The computing system may also receive a manual input corresponding to a dose of coagulant received during a manual override (e.g., at a first time instance). The control model(s) may determine the recommended dose of coagulant, while accounting for the manual input and the one or more metrics. When the control system has a handover from manual mode to automatic mode, the computing system may determine a recommended dose of coagulant based on the input data and the manual input. The computing system may transmit data corresponding to the recommended dose of coagulant to the control system of the water treatment plant.

Abstract: A computer-based graphical user interface for graphically controlling processing of hydrological data, comprising a display menu interface listing executable tools from the group comprising one or more of: hydrological data input, hydrological data validity checking and correction, and hydrological modeling, a GUI for selecting and arranging tools from the display menu in a graphical display area to construct a hydrological process, the selected tools each being represented by icons on the graphical display, and for establishing a connection between at least one output of a first tool and an input of a second tool said tools by graphically displaying the connection between said tools representative icon and input means for receiving user input to arrange and execute said constructed hydrological data processing process.

Abstract: A method for identifying anomalies in time series data, the method comprising the steps of computing parity vectors for one or more data points in a predetermined sample of data points in the time series, the parity vector representing redundancy between an estimated true value and an error term for each of the said one or more data points, evaluating the parity vectors to determine a set of the parity vectors in a selected direction; and evaluating a statistical distribution of the set according to a predetermined criterion to determine a data point to be corrected whose parity vectors satisfy the criterion in the distribution.