Xin'anjiang Model Parameter Calibration

The Xin'anjiang model, as a hydrologic watershed model independently developed in China, has been widely applied in flood forecasting and water resources management. Parameter calibration serves as a critical step in model application, directly influencing simulation accuracy.

Core methodology for parameter calibration: Parameter sensitivity analysis is typically conducted first to identify key parameters significantly affecting output results, thereby reducing calibration workload Objective function selection is crucial, with common comprehensive metrics including Nash-Sutcliffe efficiency coefficient and relative error of runoff depth For optimization algorithms, specialized hydrological optimization methods like SCE-UA can be employed, or intelligent algorithms such as particle swarm optimization may be implemented Attention must be paid to correlation constraints between parameters to avoid obtaining mathematically feasible but physically unreasonable parameter sets

A complete calibration procedure should include parameter boundary setting, optimization process control, and result validation modules. Implementationwise, multi-event flood cross-validation is recommended during calibration to prevent overfitting issues. In code implementation, this typically involves partitioning hydrological datasets into training and validation subsets, with calibration performed on training data and verified against independent validation events.