文章摘要
景 明, 程献国, 王军涛, 姜晗琳.黄河下游灌区引黄灌溉需水预测关键技术分析Journal of Water Resources and Water Engineering[J].,2013,24(6):60-63
黄河下游灌区引黄灌溉需水预测关键技术分析
Analysis of key technology of irrigation water demand forecast in downstream area of Yellow river
  
DOI:10.11705/j.issn.1672-643X.2013.06.014
中文关键词: 灌溉需水量预测  作物需水量  引黄灌区
英文关键词: forecast of irrigation water demand  crop water demand  irrigation district of Yellow River
基金项目:中央级科研院所基本科研业务费专项资金资助项目(HKY-JBYW-2011-05); 水利部公益性行业专项(200901021); 农业科技成果转化资金项目(2011GB23320008)
Author NameAffiliation
JING Ming1,2, CHENG Xianguo1,3, WANG Juntao1,2, JIANG Hanlin4 (1.黄河水利科学研究院 河南 郑州 453000 2.黄河流域农村水利研究中心 河南 新乡 4530033.黄河水利委员会农村水利局 河南 郑州 453000 4.西北农林科技大学 陕西 杨凌 712100) 
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中文摘要:
      根据水量平衡原理,建立了黄河下游灌区引黄灌溉需水量中期预测方法。分析了引黄灌溉需水预测基本原理,阐述了作物需水量、有效降水量、斗渠以下灌溉水利用系数、引黄灌溉需水量分离等引黄灌溉需水预测的关键参数和方法。作物需水量可采用修订的Valiantzas方程进行预测;有效降水量预测可采用美国垦务局推荐方法;斗渠以下灌溉水利用系数可采用该系数与末级渠道灌溉控制单元至支渠分水口的距离、渠道衬砌率等的线性方程估算;引黄灌溉需水量的分离可采用高精度遥感技术确定引黄灌溉面积,并通过本文提出的计算方法,从灌区供水水源中分离出引黄供水需求量。上述关键技术问题的研究可以为黄河下游农业用水需求预测提供技术支持。
英文摘要:
      According to water balance principle, the paper established medium and long-term forecast method of Yellow River irrigation water demand. It analyzed the fundamental of irrigation water demand forecast and reviewed the main forecast parameters such as crop water demand, effective precipitation, irrigation water efficiency of sub irrigation system, and Yellow River irrigation water demand separation from the irrigation district water requirement. Crop water demand forecast could apply Valiantzas equation; effective precipitation prediction could use U.S. Bureau of Reclamation recommended method; and irrigation water efficiency of sub irrigation system could be calculated by some factors such as distance between final canal irrigation control unit to lateral canal division and channel lining rate; Yellow River irrigation water demand separation could be computed with irrigation area defined by remote sensing technique and the paper's method. Through the above research, it can provide technical support to the Yellow River agricultural water demand forecastion.
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