Deriving high-resolution sediment load data using a nonlinear deterministic approach

Accurate estimation of sediment load at high resolutions is crucial for river related activities. The existing methods for high‐resolution load estimation involve either extrapolation and interpolation schemes using high‐resolution water discharge and sediment concentration measurements or direct measurements using load movement detectors. The present study introduces a new (disaggregation) approach, which is based on scaling properties of the sediment load transformation process itself. The load transformation process between different scales is assumed as nonlinear deterministic. The disaggregation approach follows: (1) reconstruction of the scalar (sediment load) series in a multidimensional phase‐space for representing the transformation dynamics; and (2) use of a local approximation (nearest neighbor) method for disaggregation. The effectiveness of the approach is demonstrated by employing it to suspended sediment load data observed in the Mississippi River basin. Data of successively doubled resolutions between daily and 16 days (i.e., daily, 2‐day, 4‐day, 8‐day, and 16‐day) are studied, and disaggregations are attempted between successive resolutions (i.e., 2‐day to daily, 4‐day to 2‐day, 8‐day to 4‐day, and 16‐day to 8‐day). Comparison between the disaggregated values and the actual values (through statistical indicators, time series and scatterplots) reveal excellent agreements for all the cases studied, indicating the suitability of the nonlinear deterministic approach for sediment load disaggregation. The possible nonlinear deterministic nature of the sediment load transformation process between different scales is also evident from the best disaggregation results achieved for low phase‐space dimensions (less than 4) and small number of neighbors (less than 100).