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Effective management of water resources in arid and semi-arid areas demands studies that cross over the disciplinaries of
natural and social sciences. An integrated Hydrological, Ecological and Economical (HEE) modeling system at regional
scale has been developed to assess water resources use and ecosystem production in arid and semi-arid areas. As a
physically-based distributed modeling system, the HEE modeling system requires various input parameters including
those for soil, vegetation, topography, groundwater, and water and agricultural management at different spatial levels. A
successful implementation of the modeling system highly depends on how well it is calibrated. This paper presented an
automatic calibration procedure for the HEE modeling system and its test in the upper and middle parts of the Yellow
River basin. Previous to calibration, comprehensive literature investigation and sensitivity analysis were performed to
identify important parameters for calibration. The automatic calibration procedure was base on conventional Monte
Carlo sampling method together with a multi-objective criterion for calibration over multi-site and multi-output. The
multi-objective function consisted of optimizing statistics of mean absolute relative error (MARE), Nash-Sutcliffe model
efficiency coefficient (ENS), and coefficient of determination (R2). The modeling system was calibrated against
streamflow and harvest yield data from multiple sites/provinces within the basin over 2001 by using the proposed
automatic procedure, and validated over 1993-1995. Over the calibration period, the mean absolute relative error of
simulated daily streamflow was within 7% while the statistics R2 and ENS of daily streamflow were 0.61 and 0.49
respectively. Average simulated harvest yield over the calibration period was about 9.2% less than that of observations.
Overall calibration results have indicated that the calibration procedures developed in this study can efficiently calibrate
the modeling system in the study area. Annual validation results for average streamflow and harvest yield showed
relative large errors which were associated with irrigation water use and reservoir impact. The validation results of
streamflow for sites in upper reaches have shown close relationship with observations which indicated the liability of
calibrated parameter values in predicting watershed responses. The information and results provided by the study will be
helpful to watershed modelers and model users in calibrating complex watershed models and contribute knowledge to
interdisciplinary modeling for water resources management in the study area.
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