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Estimation of infiltration rate from readily available soil properties (RASPs) in fallow cultivated land

机译:从休耕地的现成土壤特性(RASP)估算入渗率

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The information about water transmission rate into the ground is vital concerning the productivity of water system and seepage, advancing the accessibility of water for the plants, enhancing the yield of harvests, limiting degradation of soil and wastage of the water. Infiltration rate can successfully be measured using double ring infiltrometer. However, measurement of infiltration in the field is labour and time consuming and difficult especially in mountainous sites. As an alternative, RASP-based infiltration models can be developed. The study was carried out in the field near the NERIST campus (Nirjuli Complex), Arunachal Pradesh, India. Twenty sites were identified at the grid of 10 m interval, and the field measurement of infiltration was performed. The soil was analysed for properties, namely, soil texture, bulk density (BD), particle density (PD), moisture content (MC), and organic carbon content (OC) for each site. The basic infiltration varied from 1 to 4.84 cm/h. The Scatter plot between RASPs and infiltration rate revealed that there is a positive correlation with OC, PD, and sand, and a negative correlation with BD, MC, silt, and clay. The partial least square regression (PLSR) analysis was carried out to develop predictive models for five different groups of inputs of soil properties. The influential variable projection (VIPs) analysis revealed sand as a highly influential factor, while silt as a reluctant predictor of infiltration characteristics of the study site. It was found that to predict the soil infiltration rate based on RASPs with seven independent variables (Eq. 13) with coefficient of determination (R2) 0.92, root mean square error (RMSE) 0.378 cm/h, mean absolute error (MAE) 0.143 cm/h, and standard error (SD) 0.398 cm/h is strongly recommended for the prediction of infiltration characteristics.
机译:关于水向地下的传输速率的信息对于水系统的生产力和渗漏,提高植物的水可及性,提高收成,限制土壤退化和水的浪费至关重要。渗透率可以使用双环渗透仪成功地测量。但是,在野外测量渗透率是费力和费时的,而且困难,特别是在山区。或者,可以开发基于RASP的渗透模型。这项研究是在印度阿鲁纳恰尔邦NERIST校园(Nirjuli Complex)附近的田野中进行的。在间隔为10 m的网格上确定了20个位置,并进行了渗透的现场测量。分析土壤的属性,即每个站点的土壤质地,堆积密度(BD),颗粒密度(PD),水分含量(MC)和有机碳含量(OC)。基本渗透量为1至4.84 cm / h。 RASPs与入渗速率之间的散点图显示,与OC,PD和沙粒呈正相关,与BD,MC,粉砂和黏土呈负相关。进行了偏最小二乘回归(PLSR)分析,以开发针对五组不同土壤属性输入的预测模型。有影响力的变量投影(VIPs)分析显示,沙土是一个高度影响因素,而淤泥是研究地点渗透特征的勉强预测因子。发现基于具有七个独立变量(方程式13)的RASP预测土壤入渗速率,其测定系数(R2)为0.92,均方根误差(RMSE)为0.378 cm / h,平均绝对误差(MAE)为0.143 cm / h,强烈建议使用标准误差(SD)0.398 cm / h来预测渗透特性。

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