地理研究 ›› 2017, Vol. 36 ›› Issue (5): 837-849.doi: 10.11821/dlyj201705003

• 研究论文 • 上一篇    下一篇

土壤相对湿度在东北地区农业干旱监测中的适用性分析

安雪丽1,2,3(), 武建军1,2,3(), 周洪奎1,2,3, 李小涵1,2,3, 刘雷震1,2,3, 杨建华1,2,3   

  1. 1. 北京师范大学民政部/教育部减灾与应急管理研究院,北京 100875
    2. 北京师范大学地表过程与资源生态国家重点实验室,北京 100875
    3. 北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875
  • 收稿日期:2016-12-04 修回日期:2017-03-09 出版日期:2017-05-20 发布日期:2017-05-20
  • 作者简介:

    作者简介:安雪丽(1991- ),女,河南濮阳人,硕士,研究方向为农业干旱监测、评估。E-mail:xlan1992@163.com

  • 基金资助:
    国家国际科技合作专项(2013DFG21010);中央高校基本科研业务费专项资金和教育部创新团队资助项目(IRT1108)

Assessing the relative soil moisture for agricultural drought monitoring in Northeast China

Xueli AN1,2,3(), Jianjun WU1,2,3(), Hongkui ZHOU1,2,3, Xiaohan LI1,2,3, Leizhen LIU1,2,3, Jianhua YANG1,2,3   

  1. 1. Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs & Ministry of Education, Beijing Normal University, Beijing 100875, China
    2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    3. Key Laboratory of Environment Change and Natural Disaster, Ministry of Education (MOE), Beijing Normal University, Beijing 100875, China
  • Received:2016-12-04 Revised:2017-03-09 Online:2017-05-20 Published:2017-05-20

摘要:

分析土壤相对湿度(RSM)与标准化植被指数(SVI)、站点农气灾情数据及产量数据的关系,探究土壤相对湿度对东北地区农业干旱的监测能力。结果表明:① 土壤相对湿度与SVI有较好的相关关系,76%的站点能够通过0.05的检验;水分胁迫下,作物生长状态对土壤湿度的滞后时间为10天。② 土壤相对湿度低于60时,超过58%的作物生长状态受到影响;土壤相对湿度低于35时,超过92%的作物生长状态受到影响。③ 土壤相对湿度对农气灾情数据记录的不同等级干旱的正确检测概率都超过了50%。④ 7月上旬土壤相对湿度和产量的相关关系最好。土壤相对湿度在东北地区农业干旱监测中具有较好的适用性,本文可为农业干旱监测提供理论支持。

关键词: 农业干旱, 土壤相对湿度, 标准化植被指数, 作物产量

Abstract:

Soil moisture is an important factor affecting crop growth, development and production. Currently, the presence of a growing number of long-term soil moisture networks allowed users to obtain precise soil moisture data. Therefore, it is reasonable to consider soil moisture observation data as a potential approach for monitoring agricultural drought. In Northeast China, the soil moisture dataset at agro-meteorological stations is relatively complete. In order to study the ability of Relative Soil Moisture (RSM) monitoring agricultural drought, we firstly analyzed the correlation and lag time between relative soil moisture and Standardized Vegetation Index (SVI), and investigated the response of crop growth state to soil moisture. Secondly, by the comparison between relative soil moisture and the drought disaster data recorded by the national agro-meteorological stations, we analyzed the probability of detection of relative soil moisture to drought disaster record data. Finally, the relationship between relative soil moisture and crop yield was analyzed. The results are as follows: (1) The RSM has good correlations with SVI in the growing season, 76% of the stations can pass the 0.05 test. Under water stress, SVI and RSM have the best correlation at 10-day lag. (2) Through the analysis of corresponding relationship between RSM and the 10-day lagged SVI, we point out that the RSM is able to depict the influence of different drought intensities on crop growth status. With the decrease of RSM, the effect on both the crop growth status and the probability are increasing. When RSM is below 60, more than 58% of the crop growth status was affected; When RSM is below 35, more than 92% of the crop growth status was affected. (3) The probabilities of detection of RSM on the different drought grades recorded by the national agro-meteorological stations are all more than 50%. But if we do not classify the RSM into drought grades, the probability of detection of RSM on moderate drought recorded by the national agro-meteorological stations reaches 73%. (4) The impacts of RSM on crop yield during the main growing season were also explored using 10-day RSM data. The result shows that the key period was the first dekad in July. RSM has a good applicability in agricultural drought monitoring in Northeast China, and this study can provide theoretical support for agricultural drought monitoring.

Key words: agricultural drought, relative soil moisture, standardized vegetation index, crop yield