Numerical Modeling of a Complex and Data-Limited Wetland Catchment: Multi-objective Calibration and Validation

By their nature, wetlands represent an ecosystem base for many concurrent heterogeneous interactions where the mission of numerical modeling requires a wide range of consistent and reliable datasets from a variety of different sources, spatially and temporally. However, such a mission usually collides with the existence of tremendous missing in time series dataset (s), the thing that undermines the key processes of model performance evaluation, namely calibration and validation. In this context, mike she was used to construct an integrated surface subsurface flow model for the Paya Indah wetlands in Malaysia where huge gaps exist in the historical datasets of water level and flow rate. To calibrate and validate the model to a satisfactory level, a tri-criteria simulation approach was applied to overcome the occasional missing values in these datasets. This goal was accomplished by calibrating the surface water level and channel flow while simultaneously matching the steady state subsurface portion of the system wherever water table depth data allowed. Quantitatively, the integrated model scored the highest values of R (0.765-0.927) and CE (0.748-0.828) during the validation. However, large RMSE values were calculated for the flow rate during calibration at SWL2 (outlet; 0.766) and during validation at Langat river (0.780). This bias was attributed to low or occasional absence of variation in the historical time series datasets necessary for the simulation process. Furthermore, visual assessment revealed that the hydrographic dynamics characteristics (especially for surface water) were represented better by the model during the validation period than the calibration period.