地球科学进展

地球科学进展 doi: 10.11867/j.issn.1001-8166.2026.068   cstr: 32269.14.adearth.CN62-1091/P.2026.068

   

加权核优化法及其在陆面模型动态植被参数优化中的应用——以黄河流域草地类型区域为例
刘永和1，刘龙2，黄平华1，闫银1，刘思源2   
  1. （1. 河南理工大学 资源环境学院，河南 焦作 454000；2. 河南理工大学 设计学院，河南 焦作 454000）
  • 基金资助:
    河南省自然科学面上基金项目“基于人为干预太阳辐射的黄河流域草地生态水文调控研究”（编号：252300421467）；河南 省科技攻关项目“面向黄河流域数字孪生的动态植被模拟技术优化研究”（编号：252102320004）资助.

Weighted Kernel Centroid Optimization Method and Its Application in Optimizing Dynamic Vegetation Parameters of a Land Surface Model: A Case Study of Grassland Areas in the Yellow River Basin*

Liu Yonghe1， Liu Long2， Huang Pinghua1， Yan Yin1， Liu Siyuan2   

  1. (1. School of Resources and Environment, Henan Polytechnic University, Jiaozuo Henan 454000, China; 2. School of Design, Henan Polytechnic University, Jiaozuo 454000 Henan, China)

  • About author:Liu Yonghe, mainly engaged in land surface processes and hydrology research. E-mail: yonghe_hpu@163.com
  • Supported by:
    Project supported by the Natural Science Foundation of Henan Province (General Program) (Grant No. 252300421467); Henan Provincial Key Science and Technology Program (Grant No. 252102320004).
下载PDF ( 32 )
使用传统方法实施陆面过程模型参数优化时，面临收敛慢、易陷入局部最优等挑战，对具有非确定性输出的模型存在稳定性较差的问题。提出了新的全局优化算法—加权核优化法（Weighted Kernel Centroid， WKC），通过逆适应度加权计算优势解的重心，结合自适应空间收缩策略，在单峰或岭脊型且具有波动噪声的代价函数上实现探索。为验证其有效性，实施了针对多种标准数学函数的测试，并以代表黄河流域草地类型的49 个样点为基础，对NMH-CS 模型中VCMX25（25 ℃羧化速率）、MP（气孔导度斜率）、DILEFC（温度胁迫的叶片死亡系数）及QE25（25 ℃量子效率）4 个动态植被参数开展联合优化，开展与遗传算法（GA）、最速下降法（GD）和混洗复合型算法（SCE-UA）的系统对比。结果表明：①WKC具有一定全局优化能力，但更适合于非多峰性问题；②WKC具有收敛快速且稳定的优势；③参数优化使叶面积指数和总初级生产力模拟的相关系数达到0.8 左右， RMSE 和相对偏差控制良好；④优化后的参数呈现出显著空间异质性，如VCMX25 与海拔呈显著相关（r=0.89），反映了高海拔低温环境下的光合适应特征；MP 与降水量呈弱正相关，体现干旱区气孔导度减小的保水性。研究提供了一种简洁、高效与健壮的参数优化方法，通过为陆面模型参数优化揭示了黄河流域草地植被关键参数的空间分异规律及其环境适应机制。
关键词: 加权核优化法, NMH-CS, 参数优化, 黄河流域, 动态植被
Abstract：When traditional methods are used to implement parameter optimization for land surface process models, they face challenges such as slow convergence and a tendency to fall into local optima, and they also suffer from poor stability for models with non-deterministic outputs. This paper proposes a new global optimization algorithm—the Weighted Kernel Centroid (WKC) method. By calculating the centroid of superior solutions through inverse fitness weighting and combining it with an adaptive space contraction strategy, it achieves exploration on cost functions that are unimodal or ridge-type and contain fluctuating noise. To verify its effectiveness, this study conducted tests on a variety of standard mathematical functions, and, based on 49 sample points representing grassland types in the Yellow River Basin, carried out joint optimization of four dynamic vegetation parameters in the NMH-CS model, namely VCMX25 (carboxylation rate at 25 degrees C), MP (stomatal conductance slope), DILEFC (leaf death coefficient due to temperature stress), and QE25 (quantum efficiency at 25 degrees C). A systematic comparison with the genetic algorithm (GA), steepest descent method (GD), and shuffled complex evolution algorithm (SCE-UA) is conducted. The results show that: ① WKC has a certain global optimization capability, but is more suitable for non-multimodal problems; ② WKC has the advantages of fast convergence and strong stability; ③ parameter optimization brings the correlation coefficient of leaf area index and gross primary productivity simulations to around 0.8, with RMSE and relative bias well controlled; ④ the optimized parameters exhibit significant spatial heterogeneity, where VCMX25 is significantly correlated with altitude (r=0.89), reflecting photosynthetic adaptation characteristics under high-altitude lowtemperature environments; MP is weakly positively correlated with precipitation, reflecting the water conservation property of reduced stomatal conductance in arid regions. This study provides a concise, efficient, and stable parameter optimization method, and through parameter optimization for a land surface model reveals the spatial differentiation patterns of key grassland vegetation parameters in the Yellow River Basin and their environmental adaptation mechanisms.
Key words: Weighted Kernel Centroid optimization, NMH-CS, Parameter optimization, Yellow River Basin, Dynamic vegetation.
[1] 韦馨杰, 黄小倩, 管晓丹, 马婷婷, 杨坤. 水汽内外循环对黄河流域上中游夏季降水的影响[J]. 地球科学进展, 2024, 39(9): 930-944.
[2] 李得勤，段云霞，张述文. 土壤湿度观测、模拟和估算研究[J]. 地球科学进展, 2012, 27(4): 424-434.
[3] 曾燕,邱新法,潘敖大,刘昌明. 地形对黄河流域太阳辐射影响的分析研究[J]. 地球科学进展, 2008, 23(11): 1185-1193.
[4] 刘昌明. “黄河流域水资源演化规律与可再生性维持机理”研究进展[J]. 地球科学进展, 2006, 21(10): 991-998.
[5] 王浩;严登华;秦大庸;王建华. 近50年来黄河流域400 mm等雨量线空间变化研究[J]. 地球科学进展, 2005, 20(6): 649-655.
阅读次数
全文


摘要

地址：甘肃省兰州市天水中路8号
QQ：114723517
电话：0931-8762293　E-mail：adearth@lzb.ac.cn
陇ICP备2021001824号-5　 甘公网安备62010202000687