灌区尺度月灌溉用水量预报及模型敏感性分析  

Monthly Irrigation Water Amount Forecast and Model Sensitivity Analysis

作　　者：李依耘 王莹[1] 王龙 张建龙[1] 褚宏业 

机构地区：[1]云南农业大学水利学院,昆明650201

出　　处：《节水灌溉》2015年第2期85-88,共4页Water Saving Irrigation

基　　金：国家自然科学基金项目(51349010);国家重点实验室开放基金项目(2012490311);云南省教育厅基金项目(2012Y373);水利部公益项目(201201025)

摘　　要：对水量计算模型进行改进,得到灌区尺度月灌溉用水量预报模型,包含3个子模型:降雨径流子模型、河流流量子模型以及灌溉需水子模型。其中灌溉需水子模型中,灌区被分解为目标灌区与非目标灌区。将此模型在澳大利亚马兰比季灌区进行应用,并通过SUFI-2算法对模型进行参数敏感性分析。采用月径流量以及月灌溉用水量进行参数率定和模型验证。通过模拟值与实测值对比,验证阶段模型灌溉用水量相关性系数R2为0.618 4,表明灌溉用水量模拟值与实测值拟合较好,其变化趋势基本一致。通过敏感性分析表明,模型对降雨量的敏感性高于对水库库容的敏感性。因此,该模型可用于灌区灌溉用水量预报,同时不能忽视气候变化对灌溉用水量的影响。In this study,monthly Irrigation Water Forecast model（IWF）is improved based on Water Accounting Model.There are three sub-models in IWF,namely Rainfall-runoff sub-model,River-flow sub-model and Irrigation demand sub-model.In irrigation demand model,Irrigation areas in catchments are spilt into two parts,a target irrigation area and other irrigation areas.IWF is applied to Murrumbidgee Irrigation Area（MIA）.IWF sensitivity is analyzed by SUFI-2method.The model was calibrated and verified based on observed data of river discharge and irrigation water amount.The correlation coefficient R2 equals 0.618 4by comparing simulated data and observed data.The results illustrate that simulated result and observed data are matched and the trend is basically consistent.The sensitivity analysis shows that rainfall is the most sensitive factor of IWF output.Therefore,the model can be applied for IWS and the influence of climate change on irrigation water amount can not be neglected.

关 键 词：灌区尺度 月灌溉用水量 敏感性分析 

分 类 号：S274.2[农业科学—农业水土工程]