基于GIS和随机森林算法的宁东土壤饱和导水率分布与预测

夏子书; 白一茹; 王幼奇; 包维斌; 杨帆; 钟艳霞; 李鸣骥

doi:10.13870/j.cnki.stbcxb.2021.01.041

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基于GIS和随机森林算法的宁东土壤饱和导水率分布与预测

更新时间：2025-03-12

- 基于GIS和随机森林算法的宁东土壤饱和导水率分布与预测
- Distribution and Prediction of Soil Saturated Hydraulic Conductivity in Ningdong Based on GIS and Random Forest Algorithm
- 水土保持学报 2021年35卷第1期页码：285-293
- 作者机构：
  
  1. 宁夏大学资源环境学院,银川,750021
  2. 旱区特色资源与环境治理教育部国际合作联合实验室,银川,750021
- 作者简介：
  
  [ "夏子书(1997-),女,硕士研究生,主要从事土壤水分生态、土壤性质空间变异研究。E-mail:xzs0131@163.com" ]
- 基金信息：
  
  国家自然科学基金项目（41867003，41761049）宁夏自然科学基金项目（2018AAC03027）宁夏青年科技人才托举工程项目（2016008）宁夏重点研发计划重大项目（2018BFG02016）宁夏环境保护科学技术研究项目（2018-07）
- DOI：10.13870/j.cnki.stbcxb.2021.01.041
  中图分类号： S152.7
- 纸质出版：2021
- 稿件说明：
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夏子书, 白一茹, 王幼奇, 等. 基于GIS和随机森林算法的宁东土壤饱和导水率分布与预测[J]. 水土保持学报, 2021,35(1):285-293.

XIA Zishu, BAI Yiru, WANG Youqi, et al. Distribution and Prediction of Soil Saturated Hydraulic Conductivity in Ningdong Based on GIS and Random Forest Algorithm[J]. 2021, 35(1): 285-293.
夏子书, 白一茹, 王幼奇, 等. 基于GIS和随机森林算法的宁东土壤饱和导水率分布与预测[J]. 水土保持学报, 2021,35(1):285-293. DOI： 10.13870/j.cnki.stbcxb.2021.01.041.

XIA Zishu, BAI Yiru, WANG Youqi, et al. Distribution and Prediction of Soil Saturated Hydraulic Conductivity in Ningdong Based on GIS and Random Forest Algorithm[J]. 2021, 35(1): 285-293. DOI： 10.13870/j.cnki.stbcxb.2021.01.041.

摘要

为探明宁东土壤饱和导水率（Ks）的空间分布特征，在宁东采集136个原状土，采用经典统计和地统计方法分析土壤Ks的空间结构特征，并以地形因子、土壤属性等作为辅助变量，运用随机森林法（RF）、普通克里格法（OK）和逐步回归克里格法（RK）对区域土壤Ks进行预测并对3种方法的预测结果进行精度评价。结果表明：Ks介于0.05~7.13 mm/min，平均值为1.46 mm/min，变异系数为106.86%；Ks与容重、孔隙度、高程、坡度、坡向、平面曲率和剖面曲率在不同滞后距离下具有自相关关系和交互相关关系；土壤Ks块金值为38，表明随机因素引起的土壤Ks变异性较大，空间异质比为15.32%，在空间上呈现强变异性；RF法的预测精度最高，其平均相对误差（MRE）和均方根误差（RMSE）绝对值均为最小，相比OK和RK方法预测精度分别提高了5.53%和2.49%，且对局部细节的描述更准确、模拟效果最佳。RF法可以较为准确的预测宁东土壤Ks，为了解研究区土壤水文过程及林草植被建设提供数据参考。

Abstract

In order to find out the spatial distribution characteristics of soil saturated hydraulic conductivity (Ks)

136 undisturbed soils were collected in Ningdong. The spatial structure characteristics of Ks were analyzed by classical and geostatistical methods. Taking terrain factors and soil properties as auxiliary variables

the regional soil Ks were predicted by the random forest method (RF)

ordinary Kriging method (OK) and stepwise regression Kriging method (RK)

and the accuracy of the prediction results of the three methods were evaluated. The results showed that Ks ranged from 0.05 to 7.13 mm/min

with an average value of 1.46 mm/min and a coefficient of variation of 106.86%. Ks had autocorrelation and cross-correlation with bulk density

porosity

elevation

slope

aspect

plane curvature and section curvature under different lag distance. The nugget value of soil Ks was 38

indicating that the variability of soil Ks caused by random factor was large

and the spatial heterogeneity ratio was 15.32%

showing strong spatial variability. The prediction accuracy of RF was the highest

and the absolute values of mean relative error (MRE) and root mean square error (RMSE) were both the smallest. Compared with OK and RK

the prediction accuracy of RF was improved by 5.53% and 2.49%

respectively

and the description of local details was more accurate and the simulation effect was the best. RF could accurately predict soil Ks in Ningdong

and provide data reference for understanding soil hydrological process and forest and grass vegetation construction in the study area.

关键词

Keywords

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