摘要
针对以往生态动力学模型DYRESM-CAEDYM在应用中,多采用手动方法确定参数值时较为费时费力的缺点,引入蒙特卡洛随机抽样算法对模型参数进行自动率定。以广东省大沙河水库为例,选择率定期为2011年11月至2012年2月,利用2012年7月至2012年11月实测水质数据对模型进行验证。结果表明,在率定阶段模型对水温的模拟结果非常好,表层和底层温度的均方根误差(RMSE)分别为3.53℃和2.00℃,相对误差(RE)值均小于0.15;模型对溶氧的模拟结果良好,表层和底层的RMSE值分别为1.23 mg·L·-1和1.85 mg·L·-1,RE值分别为0.08和0.20。在验证阶段,温度表层和底层的RMSE分别为2.49℃和1.67℃,RE值均小于0.1;溶氧在表层和底层的RMSE分别为2.15 mg·L·-1和0.79 mg·L·-1,RE分别为0.17和0.11。因此,经采用蒙特卡洛方法率定后得到的大沙河水库DYRESM-CAEDYM模型参数值较为可靠。
In the previous applications of hydrodynamic-ecological model (DYRESM-CAEDYM), the parameter values were arbitrarily decided by model users. In order to improve the precision of model prediction, the Monte-Carlo sampling method was introduced into auto-calibration process of DYRESM-CAEDYM. The auto-calibration was conducted with monthly water quality measurements (temperature and dissolved oxygen) during November, 2011-February, 2012 at Dashahe Reservoir in Guangdong Province. The calibrated model was validated with the water quality data measured during July, 2012-November, 2012. The model outputs of temperature showed good agreement with the observations during the autocalibriton. The RMSE values of water temperature at the surface and bottom were 3.5℃ and 2.0℃. The RE values were less than 0.15. The model was also good at simulating dissolved oxygen with RMSE values of 1.23 mg.L-1 (surface) and 1.85 mg.L-1 (bottom) and RE values of 0.08 (surface) and 0.20 (bottom). In the validation process, the RMSE values of water temperature were 2.49 "C at the surface and 1.67℃ at the bottom. The RE values were both less than 0.1. The RMSE values of dissolved oxygen were 2.15 mg.L-1 (surface) and 0.79 mg.L-1 (bottom). The RE values for dissolved oxygen were 0.17 (surface) and 0.11 (bottom). The successful calibration for DYRESM-CAEDYM at Dashahe Reservoir suggests that the model performance might be improved with automatic calibration based on Monte-Carlo sampling method and high-speed computer.
出处
《生态科学》
CSCD
北大核心
2014年第1期38-45,共8页
Ecological Science
基金
中国科学院"百人计划择优支持项目"(YOBROB045)
水体富营养化与赤潮防治广东普通高校重点实验室开放基金项目(KLGHEI KLB07007)
国家自然科学基金项目(40871095)
广东省水利科技创新项目(201102)