• ▶ 2008-2024年被中国情报信息研究所评价中心评为“中国科技核心期刊”
  • ▶ 2019-2024年连续三届被中国科学院文献情报中心中国科学引文数据库CSCD(核心库)收录
  • ▶ 2021、2023年入编北京大学图书馆《中文核心期刊要目总览》
  • ▶ 2020-2024连续四年入选《科技期刊世界影响力指数(WJCI)报告》
杜明成, 张建云, 王振龙, 刘翠善, 王国庆.皖北杨楼流域玉米农田土壤水变化特征及驱动因子研究水资源与水工程学报[J].,2022,33(1):206-214
皖北杨楼流域玉米农田土壤水变化特征及驱动因子研究
Soil moisture content change characteristics and driving factors of maize farmland in the Yanglou Watershed, northern Anhui Province
  
DOI:10.11705/j.issn.1672-643X.2022.01.29
中文关键词:  土壤水  黄潮土  增强回归树  夏玉米  生长期
英文关键词:soil moisture content  yellow fluvo-aquic soil  boosted regression tree  summer maize  growing period
基金项目:国家自然科学基金项目(41830863、52121006); 国家重点研发计划项目(2017YFA0605002、2017YFC0404602); 水文水资源与水利工程科学国家重点实验室“一带一路”水与可持续发展科技基金项目(2019nkzd02、2020nkzd01)
作者单位
杜明成1,2,3, 张建云1,2,3, 王振龙4, 刘翠善2,3, 王国庆2,3 (1.天津大学 水利工程仿真与安全国家重点实验室 天津300072
2.南京水利科学研究院水文水资源与水利工程科学国家重点实验室江苏 南京 210029
3.长江保护与绿色发展研究院江苏 南京 210098
4.安徽省(水利部淮河水利委员会)水利科学研究院 安徽 蚌埠 233000) 
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中文摘要:
      为研究皖北平原北部黄潮土在玉米不同生长期内土壤水分变化特征,选取杨楼流域为研究对象,利用2010-2018年0~50 cm深度土壤水数据,结合同期地下水埋深、前期无降雨日数、水面蒸发和降雨量进行相关性分析,利用增强回归分析算法确定不同驱动因子对土壤水变化的相对贡献。结果表明:在玉米整个生长期内,随着土层深度的增加,土壤含水率减小。按变异系数可划分为2个典型土层,即活跃层(深度0~10 cm)和次活跃层(深度10~50 cm)。土壤水与水面蒸发、地下水埋深和前期无降雨日数呈显著负相关,与降雨量呈显著正相关关系。前期无降雨日数对土壤含水率的相对贡献率最大,为42.6%,其次是地下水埋深,为20.9%,作物生长期对土壤含水率的相对贡献率最小,为7.3%。该研究对了解土壤水分变化、农业水管理及水分利用率等有重要意义。
英文摘要:
      To study the characteristics of soil moisture changes of yellow fluvo-aquic soils in the northern Anhui North Plain during different growing periods of maize, the Yanglou Watershed was selected as the study object, and correlation analysis of groundwater table, the number of days without rainfall in the previous period, evaporation from water surface and rainfall was conducted using 0~50 cm soil water content data from 2010-2018, and the relative contribution of different driving factors to soil water content were calculated using boosted regression tree algorithm. The results showed that the soil water content decreased with the increase of the soil depth throughout the maize growing season. Two typical soil layers could be classified according to the coefficient of variation, with 0~10 cm as the active layer and 10~50 cm as the less active layer. Soil water content showed a significant negative correlation with water surface evaporation, groundwater table and the number of days without rainfall in the previous period, but a significant positive correlation with the rainfall. The relative contribution of the number of days without rainfall in the previous period to soil water content was the largest, which accounted for 42.6%, followed by the groundwater table, which was 20.9%, and the crop growing period only contributed 7.3%, which was the smallest. This study can shed some light on the understanding of soil moisture changes, agricultural water management and water utilization.
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