Natural Flow Reconstruction Using Kalman Filter and Water Balance–Based Methods I: Theory

Abstract

Because natural flow (NF) values are either not directly measured or have the potential to contain considerable error, when deemed necessary, the reconstruction of a reliable NF series is ostensibly important. Selecting the appropriate method depends on available data. For a time period before reservoir construction (pre-reservoir construction period), the only available data for ungauged basins came from the neighboring basins and simulated flow used in a rainfall-runoff model. A new Kalman-based method developed in this paper looks to reconstruct the NF series using the state fusion technique, which is then compared with the area ratio method, the maintenance of variance (Move) type III method, and the multivariable regression method using different quality indexes (QIs). In the perspective of the post-reservoir construction period, when hydrometric data (i.e., turbine flow, water level in the reservoir, and discharged flow) is collected in an ungauged basin (with no flow measurements), a new water balance equation (WBE)-based method is recommended for reconstructing and filtering the NF data using an optimization technique that would then be compared with the classic WBE that implements different QIs.