华北南部低丘山地刺槐林土壤温度与冠层气温关系的研究

郑宁; 陆森; 张劲松; 孟平; 贾长荣; 任迎丰

华北南部低丘山地刺槐林土壤温度与冠层气温关系的研究

1.
中国林业科学研究院林业研究所, 国家林业局林木培育重点实验, 北京 100091
2.
济源市国有大沟河林场, 河南济源 454650
基金项目:
国家自然基金(40871106)
中图分类号: S792.27

Relationship between Soil and Air Temperature of Robinia pseudoacacia Plantation in North China

1.
Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation, State Forestry Administration, Beijing 100091, China
2.
Dagouhe Forest Farm, Jiyuan 454650, He’nan, China
CLC number: S792.27

- 冠层气温
- / 土壤温度
- / 刺槐人工林
- / 模型预测
Abstract: At present, field measurement is the main means of acquiring soil temperature data, which is spatially and temporally discontinuous. The prediction model of soil temperature should be built based on continuous measured data. Based on the soil temperature data of different layers (0 cm, 5 cm, 10 cm, 15 cm, and 20 cm) and the air temperature above and below the canopy, the data were measured continuously in a nearly 30-year-old Robinia pseudoacacia plantation in the hilly zone in Jiyuan City of He’nan Province in 2006 and 2007, the relationship between soil temperature and air temperature was analyzed, a mathematical model for predicting soil temperature was developed based on daily air temperature data in 2006, and the predictions were tested based on the data of 2007. The results show that:The variation trends of soil temperature of different layers and air temperature are basically the same; as soil depth increased, the impact of the soil increased, yet the correlation of soil temperature and air temperature decreased. According to the growth status of trees, a year can be divided into four phases of phenology. The correlation of soil temperature and air temperature was significant when the leaf area index was small. Therefore, the structure of forest canopy had obvious impact on the soil temperature. The model based on air temperature can provide a valuable and accurate tool for predicting temperature of shallow soil. However, to accurately predict deep soil temperature, more factors should be taken into account.
- air temperature
- / soil temperature
- / Robinia pseudoacacia plantation
- / model prediction

[1]	张慧智,史学正,于东升,等.中国土壤温度的空间预测研究[J]. 土壤学报, 2009, 46(1):1-8
[2]	Meikle R W, Treadway T R. A mathematical method for estimating soil temperatures in Canada[J]. Soil Science, 1981, 131(5):320-326
[3]	史学正, 邓西海. 我国土壤温度状况[M].北京:科学出版社, 1993:353-360
[4]	关德新, 吴家兵, 金昌杰, 等. 用气象站资料推算附近森林浅层地温和气温[J]. 林业科学, 2006, 42(11):132-137
[5]	冯学民, 蔡德利. 土壤温度与气温及纬度和海拔关系的研究[J]. 土壤学报, 2004, 41(3):489-491
[6]	Tabari H, Sabziparvar A-A, Ahmadi M. Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region[J]. Meteorology and Atmospheric Physics, 2011, 110(3-4):135-142
[7]	姚付启, 张振华, 钱为君. 烟台果园土壤温度影响因素及其预测模型研究[J]. 农业系统科学与综合研究, 2008, 24(2):201-204
[8]	邹平, 杨劲松, 姚荣江. 土壤温度时间序列预测的BP神经网络模型研究[J]. 中国生态农业学报,2008, 16(4):835-838
[9]	王选耀. 烟台地区土壤温度变化特征及预测模型研究[J]. 农业系统科学与综合研究,2010, 26(4):487-492
[10]	Bilgili M. Prediction of soil temperature using regression and artificial neural network models[J]. Meteorology and Atmospheric Physics, 2010, 110(1-2):59-70
[11]	Ozturk M, Salman O, Koc M. Artificial neural network model for estimating the soil temperature[J]. Canadian Journal of Soil Science, 2011, 91(4):551-562
[12]	Mihalakakou G. On estimating soil surface temperature profiles [J]. Energy and Buil, 2002, 34(3):251-259
[13]	Grant R F, Izaurralde R C, Chanasyk D S. Soil temperature under different surface managements:testing a simulation model[J]. Agricultural and Forest Meteorology, 1995, 73(1-2):89-113
[14]	Paul K I, Polglase P J, Smethurst P J. Soil temperature under forests:a simple model for predicting soil temperature under a range of forest types[J]. Agricultural and Forest Meteorology, 2004, 121(3-4):167-182
[15]	Veltena K, Pascholdb P-J, Stahelc A. Optimization of cultivation measures affecting soil temperature [J]. Scientia horticulturae, 2003, 97(2):163-184
[16]	Gao Z, Bian L, Hu Y, et al. Determination of soil temperature in an arid region[J]. Journal of Arid Environments, 2007, 71(2):157-168
[17]	Gao Z, Horton R, Wang L, et al. An improved force-restore method for soil temperature prediction[J]. European Journal of Soil Science, 2008, 59(5):972-981
[18]	Zheng D, Hunt Jr E R, Running S W. A daily soil temperature model based on air temperature and precipitation for continental applications[J]. Climate Research, 1993, 2:183-191
[19]	Elias E A, Cichota R, Torriani H H, et al. Analytical soil–temperature model correction for temporal variation of daily amplitude[J]. Soil Science Society of America journal, 2004, 68(3):784-788
[20]	Conway K E, Pickett L S. Solar Heating (Solarization) of Soil in Garden Plots for Control of Soilborne Plant Diseases[J]. Oklahoma Cooperative Extension Service, 1999, EPP-7640:1-2
[21]	Harris R N. Variations in air and ground temperature and the POM-SAT model:results from the Northern Hemisphere [J]. Climate of the Past, 2007, 3(4):611-621
[22]	Dardo G O, Pousa J L, Pilan L. Predicting temperature and heat flow in a sandy soil by electrical modeling [J]. Soil Science Society of America journal, 2001, 65(4):1074-1080
[23]	Droulia F, Lykoudis S, Tsiros I, et al. Ground temperature estimations using simplified analytical and semi-empirical approaches [J]. Solar Energy, 2009, 83(2):211-219

[1]	潘勇军 , 王兵 , 陈步峰 , 陈进 , 史欣 , 李汉强 . 短轮伐期桉树人工林土壤温度特征分析. 林业科学研究, 2011, 24(3): 404-409.
[2]	张岗岗 , 刘伟霞 , 王洋 , 范定臣 , 王晶 , 刘艳萍 . 黄河故道刺槐人工林空间和大小结构特征. 林业科学研究, 2022, 35(3): 185-192. doi: 10.13275/j.cnki.lykxyj.2022.03.021
[3]	雷蕾 , 肖文发 , 曾立雄 , 黄志霖 , 高尚坤 , 谭本旺 . 不同营林措施对马尾松林土壤呼吸影响. 林业科学研究, 2015, 28(5): 713-719.
[4]	田超 , 孟平 , 张劲松 , 孙守家 , 黄辉 , 贾长荣 , 李建中 . 降雨对华北石质山地侧柏林土壤温湿度及水分运移的影响. 林业科学研究, 2015, 28(3): 365-373.
[5]	段文标 , 王金铃 , 陈立新 , 景鑫 , 张玉双 , 魏全帅 , 杜珊 , 赵莹 , 秦必达 . 云冷杉林风倒区坑丘微立地微气候因子时空变化及其与土温的关系. 林业科学研究, 2015, 28(4): 508-517.
[6]	张蓝霄 , 李雅婧 , 胡晓创 , 孙守家 , 张劲松 , 蔡金峰 , 孟平 . 基于Biome-BGC模型的刺槐人工林生产力和内在水分利用效率研究. 林业科学研究, 2023, 36(3): 1-10. doi: 10.12403/j.1001-1498.20230015
[7]	巩大鹏 , 毕华兴 , 王劲峰 , 赵丹阳 , 黄靖涵 , 宋艺琳 . 晋西黄土区不同密度刺槐人工林叶片-枯落物-土壤化学计量特征. 林业科学研究, 2024, 37(2): 156-164. doi: 10.12403/j.1001-1498.20230299
[8]	王风芹 , 田丽青 , 桑玉强 , 宋安东 , 张劲松 . 华北土石山区刺槐和栓皮栎人工林土壤微生物数量和微生物量碳、氮研究. 林业科学研究, 2016, 29(6): 956-961.
[9]	郝佳 , 熊伟 , 王彦辉 , 于澎涛 , 刘延惠 , 徐丽宏 , 王轶浩 , 张晓蓓 . 华北落叶松人工林叶面积指数实测值与冠层分析仪读数值的比较和动态校正. 林业科学研究, 2012, 25(2): 231-235.
[10]	陈绘画 , 朱寿燕 , 崔相富 . 基于人工神经网络的马尾松毛虫发生量预测模型的研究. 林业科学研究, 2003, 16(2): 159-165.
[11]	惠刚盈 , 盛纬彤 , Gadow K. V. , 罗云伍 , 张校林 , 黄冬青 . 杉木人工林收获模型系统的研究*. 林业科学研究, 1994, 7(4): 353-358.
[12]	. 人工幼龄印度黄檀木材解剖性质和结晶度的径向变异及预测模型. 林业科学研究, 2009, 22(4): -.
[13]	盛炜彤 , 杨承栋 , 范少辉 . 杉木人工林的土壤性质变化. 林业科学研究, 2003, 16(4): 377-385.
[14]	佟金权 , 盛炜彤 . 杉木人工林广义干形模型的研究. 林业科学研究, 2000, 13(3): 239-248.
[15]	徐德应 , 盛炜彤 . 杉木人工林经营的计算机模型-CHIFIR. 林业科学研究, 1988, 1(4): 390-396.
[16]	孙晓梅 , 李凤日 , 牛屾 , 张阳武 . 长白落叶松人工林生长模型的研究. 林业科学研究, 1998, 11(3): 306-312.
[17]	杨锦昌 , 江希钿 , 许煌灿 , 王素萍 , 尹光天 . 马尾松人工林直径分布收获模型及其应用研究. 林业科学研究, 2003, 16(5): 581-587.
[18]	陈永富 . 短周期桉树人工林直径分布模型研究. 林业科学研究, 2008, 21(Z1): 50-54.
[19]	张雄清 , 张建国 , 段爱国 . 杉木人工林林分断面积生长模型的贝叶斯法估计. 林业科学研究, 2015, 28(4): 538-542.
[20]	何潇 , 徐奇刚 , 雷相东 . 气候敏感的落叶松人工林林分生物量模型研究. 林业科学研究, 2021, 34(6): 20-27. doi: 10.13275/j.cnki.lykxyj.2021.06.003

点击查看大图

计量

文章访问数: 3239
HTML全文浏览量: 214
PDF下载量: 1284
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

华北南部低丘山地刺槐林土壤温度与冠层气温关系的研究

Relationship between Soil and Air Temperature of Robinia pseudoacacia Plantation in North China

计量

华北南部低丘山地刺槐林土壤温度与冠层气温关系的研究

English Abstract

Relationship between Soil and Air Temperature of Robinia pseudoacacia Plantation in North China

全文HTML

目录

留言板

华北南部低丘山地刺槐林土壤温度与冠层气温关系的研究

Relationship between Soil and Air Temperature of Robinia pseudoacacia Plantation in North China

计量

出版历程

华北南部低丘山地刺槐林土壤温度与冠层气温关系的研究

English Abstract

Relationship between Soil and Air Temperature of Robinia pseudoacacia Plantation in North China

全文HTML

目录