Influence of Data Length on the Determination of Data Adjustment Parameters in Conceptual Hydrological Modeling: A Case Study Using the Xinanjiang Model

Minimum data length is vital to guarantee accuracy in hydrological analysis. In practice, it sometimes determined by the experiences of hydrologists, leading selection acceptable minimum an arguable issue among hydrologists. Therefore, this study aims investigate impact on parameter estimation and model performance, especially for data-scarce regions. Using four primary datasets from river basins Japan USA, subsets were generated a 28-year dataset used estimate adjustment parameters based aridity index approach improve estimation. The influence their analysis evaluated using Xinanjiang (XAJ) model; also, effectiveness outlier removal checked regression Here, we present most assessing XAJ removing outliers observed datasets. results show that between 10-year 13-year are generally sufficient robust model. Moreover, can all basins.