摘要
将LH-OAT方法与农业水文模型SWAP-EPIC相结合,构建了模型参数的全局敏感性分析方法。以黑河中游盈科灌区2012年春玉米田间试验为验证实例,选取了SWAP-EPIC模型中26个参数进行了全局敏感性分析。计算获得参数敏感性排序,并将其敏感度划归为极敏感、敏感、次敏感和不敏感4类。结果表明,参数针对不同输出变量的敏感性强度呈明显差异,土壤水力参数多数呈极敏感性,水分胁迫参数则呈现次敏感性或不敏感;选取敏感性较强的10个参数进行校正,进而高效地完成了模型率定且效果良好,所构建的全局参数敏感性分析方法可有效提高SWAP-EPIC模型率定效率,并具有较强的田间适用性。
Sensitivity analysis is of great importance to identify the key parameters and to increase the calibration efficiency of ag‐ro‐hydrological model .In this study ,a sensitivity analysis method ,based on LH‐OAT sampling approach ,was developed and applied for sensitivity analysis of parameters in SWAP‐EPIC model .A case modeling was conducted using SWAP‐EPIC ,with field experiment of spring maize in Yingke Irrigation District in the middle Heihe River basin in 2012 .Twenty‐six parameters in SWAP‐EPIC were chosen for sensitivity analysis .The ranks of parameter sensitivity were obtained and classified as four different levels :highly sensitive ,sensitive ,less sensitive and insensitive .Results showed that the degree of sensitivity were obviously dif‐ferent relative to different output variables .Most of soil hydraulic parameters showed high sensitivity while the water stress pa‐rameters were less sensitive .Ten highly sensitive parameters were selected for calibration and the model was well calibrated .O‐verall ,the proposed LH‐OAT method for global parameter sensitivity analysis can greatly increase the efficiency of model calibra‐tion .It was also beneficial to the field application of agro‐hydrological model .
出处
《中国科技论文》
CAS
北大核心
2016年第7期739-745,共7页
China Sciencepaper
基金
高等学校博士学科点专项科研基金资助项目(20120008120011)
