基于自回归综合移动平均(Arima)模型的拉丘尔地区Devasuguru Nala流域地下水位模拟

Anandakumar U, Sathishkumar GV, Srinivasa Reddy, B Maheshwara Babu
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摘要

地下水是印度重要的水源,大约65-70%的灌溉和85-90%的农村生活用水依赖于地下水。印度是世界上最大的地下水使用者之一,估计每年抽取的地下水超过230立方公里(km³)。如此高的采掘率引发了人们对许多地区过度开采的担忧。为了有效地管理地下水,对地下水位的波动进行建模和预测是非常重要的。时间序列分析中使用最广泛的技术是Box Jenkins的自回归综合移动平均(ARIMA)模型。结果表明:1999年1月至2017年3月,地下水水位明显下降;结果表明:观测井地下水位季节性下降0.034 m/年,年平均下降0.7424 m/年。ARIMA候选模型[3,0,2]被认为是Devasuguru nala流域地下水位时间序列建模和预测的最佳拟合模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autoregressive integrated moving average (Arima) model for simulation of groundwater level at Devasuguru Nala watershed, Raichur district
Groundwater is a significant source of water in India, with approximately 65-70% of irrigation and 85-90% of the rural domestic water supply dependent on groundwater. India is one of the world's largest groundwater users, with an estimated annual groundwater extraction of over 230 cubic kilometers (km³). This high rate of extraction raises concerns about over-exploitation in many regions. For the effective management of groundwater, it is important to model and predict fluctuations in groundwater levels. The most widely used technique for time series analysis is, the Box Jenkins’ Autoregressive Integrated Moving Average (ARIMA) model is adopted for the study. Results showed that the groundwater levels had significantly declined from January 1999 to March 2017. The results indicated that seasonal decline in groundwater level for the observation well was 0.034 m/year and average annual decline was 0.7424 m/yr. The ARIMA candidate model [3, 0, 2] was identified as the best fit model for groundwater level time series modelling and forecasting in Devasuguru nala watershed region.
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