Quantifying reservoir water balance is an essential process for the efficient management of water resources. Water level records are often the only data available for reservoir analysis, which causes an ill‐posed problem in water resource system planning. This study proposes an analytical framework to estimate reservoir inflow and outflow from water level observations using hydrological models and reasoning carefully derived from expert knowledge and soft data. Partial reservoir inflow hydrographs were constructed from water level observations using a continuity equation and knowledge‐based constraints developed for periods of no spillway discharge. A bucket‐type rainfall‐runoff model was then calibrated to the partial inflow hydrographs. Finally, a complete reservoir inflow hydrograph was constructed using the calibrated models, which were then employed to estimate detailed reservoir outflow components under a full water balance relationship between inflow, outflow, water levels, and reservoir operation rules. The proposed solution for the ill‐posed water balance equation outperformed conventional (benchmark) approaches in accuracy and uncertainty in its application to agricultural reservoirs. This study demonstrates how hydrological modeling and reasoning, which are discreetly designed based on expert knowledge, can help to solve the ill‐posed water balance equation by creating supplementary information regarding the problem. The proposed framework is expected to assist in reconstructing reservoir routing processes using water level observations for hydrological analysis and water resource management planning.

The purpose of this study was to determine the accuracy of three-dimensional coronary angiography obtained with electron beam CT in the assessment of the patency of coronary artery bypass grafts.