双参数冻融新模型在新疆喀什地区土壤水预测中的应用研究
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摘要
土壤水的准确预测对区域旱情评估及水量分析计算十分重要。传统模式大都基于土壤水观测数据构建线性回归方程进行预测。本次研究结合一种新的双参数冻融模型,以新疆喀什为研究区域,综合考虑土壤物理特性和参数的非线性,对区域内的土壤水进行非线性预测,结果显示:喀什地区的土壤水预测结果和实测土壤水数据相比,新模型预测计算误差在6%～10%之间,明显优于传统自动监测仪器的误差值,预测精度大大提高,具有重要的参考和实用价值。
Accurate prediction of soil water is important for regional drought assessment and water volume analysis.Traditional modeare mostly based on soil water observation data to construct linear regression equations for prediction. Combined with a new two-parameter freeze-thaw model, Xinjiang Kashgar is used as the research area, and the soil physical properties and nonlinearly parameters are considered. The soil water in the region is predicted nonlinearly. The results show that the prediction results of soil water in the Kashgar area are compared with the water data in the measured soil, the new model predicts the calculation error between 6% to 10%, which is obviously superior to the error value of the traditional automatic monitoring instrument, and the prediction accuracy is greatly improved, which has important reference and practical value.
Accurate prediction of soil water is important for regional drought assessment and water volume analysis.Traditional modeare mostly based on soil water observation data to construct linear regression equations for prediction. Combined with a new two-parameter freeze-thaw model, Xinjiang Kashgar is used as the research area, and the soil physical properties and nonlinearly parameters are considered. The soil water in the region is predicted nonlinearly. The results show that the prediction results of soil water in the Kashgar area are compared with the water data in the measured soil, the new model predicts the calculation error between 6% to 10%, which is obviously superior to the error value of the traditional automatic monitoring instrument, and the prediction accuracy is greatly improved, which has important reference and practical value.
引文
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[2]武建虎.农田土壤水分动态及其影响因素分析[J].地下水.2011.33(04):13-14+18.
[3]肖建英,李永涛,王丽.利用Van Genuchten模型拟合土壤水分特征曲线[J].地下水.2007(05):46-47.
[4]王壮.双参数冻融入渗模型在辽西冬季冻土期土壤水非线性预测的适用性分析[J].水土保持应用技术.2018(01):7-9.
[5]王宏宇,马娟娟,孙西欢,等.基于BP神经网络的土壤水热动态预测模型研究[J].节水灌溉.2017(07):11-15+27.
[6]孙玥,关明皓.改进的PSO-RBF模型在土壤水入渗参数非线性预测中的应用研究[J].水利技术监督.2017.25(02):117-120.
[7]唐田.基于AMSR-E和RBF神经网络的川中丘陵区土壤水分反演[D].四川农业大学.2013.
[8]李彦.节水灌溉条件下河套灌区土壤水盐动态的SWAP模型分布式模拟预测[D].内蒙古农业大学.2012.
[9]任尚岗.土壤水动力参数测算方法及其空间变异性研究[D].鲁东大学.2011.