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中国农学通报

中国农学通报 ›› 2015, Vol. 31 ›› Issue (5): 164-170.doi: 10.11924/j.issn.1000-6850.2014-2332

所属专题： 玉米； 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

辽西雨养玉米农田土壤水分变化特征及其模拟

杨扬   

  1. 锦州市生态与农业气象中心
  • 收稿日期:2014-08-26 修回日期:2014-11-13 接受日期:2014-11-18 出版日期:2015-03-20 发布日期:2015-03-20
  • 通讯作者: 杨扬
  • 基金资助:
    公益性行业（气象）科研专项“东北地区土壤墒情监测预报及其对主要农作物的影响分析”(GYHY201106026)。

Variation characteristics and Simulation of rain-fed maize farmland soil moisture in the Western of Liaoning

  • Received:2014-08-26 Revised:2014-11-13 Accepted:2014-11-18 Online:2015-03-20 Published:2015-03-20

摘要： 土壤含水量是作物生长发育的关键影响因子之一，确定土壤含水量变化及预测土壤含水量变化趋势，对于雨养农业更加有效地保墒、提高作物水分利用效率和增强抗旱防灾能力有着重要的现实意义。利用2008-2011年锦州玉米生长季逢三逢八土壤湿度观测数据，日气温降水数据和2008年玉米生长发育期数据资料，结合CERES-MAIZE土壤水分模块，分析了雨养玉米农田土壤水分时空变化特征和模拟了土壤水分时空变化特征。结果表明：生长季降水并不能反映土壤水分条件的好坏，生长季中雨以下的降水量和降水频次与土壤水分条件的好坏较好的一致性；土壤水分随土层深度而增加，0-40cm土壤含水量平均值和最低值分别是田间持水量的69%-82%和49%-64%；玉米根系生物量与生长时间呈二次曲线关系，所建根系生物量模型解释率达89.7%；耦合根系生物量模型和叶面积指数模型的CERES-MAIZE中的土壤水分模块能够较好的模拟雨养玉米生态系统土壤水分的时空变化特征。

关键词: 熊岳, 熊岳

Abstract: Abstract: Soil moisture content is one of the key influence factors of crop growth. Identifying variation trends of soil water content and its precise simulation has important practical significance for keeping more effectively moisture, increasing crop water use efficiency, and enhancing the capacity of drought disaster prevention. Based on soil moisture observation data, temperatures, rainfall data and development period in maize growing season from 2008 to 2011 at Jinzhou, and combined with soil moisture module in CERES-MAIZE, the rain-fed maize farmland spatial and temporal variation characteristics of soil water was analyzed and simulated. The results showed that: the growing season precipitation did not reflect the variation trend of soil moisture conditions, the precipitation and precipitation frequency under moderate rain was correlated well with soil water content during growing season; Soil moisture was increasing with soil depth, the average value and lowest value of soil moisture from 0 cm to 40 cm of soil depth were 69%-82% and 49%-82% of field capacity, respectively. It was a quadratic curve relationship between Corn root biomass and the growth time. The explain rate of the model built was 89.7%. Coupling root biomass model and leaf area index model with soil moisture module can better simulate the soil moisture spatial and temporal variations of soil moisture in rain-fed maize ecosystem.