• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Ecosystem >Structural Time Series Analysis towards Modeling and Forecasting of Ground Water Fluctuations in Murshidabad District of West Bengal
【24h】

Structural Time Series Analysis towards Modeling and Forecasting of Ground Water Fluctuations in Murshidabad District of West Bengal

机译：西孟加拉邦Murshidabad区地下水波动建模和预测的结构时间序列分析

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Murshidabad district of West Bengal is well known for agriculture potential with cropping intensity of more than 200%. About 70 % of total agricultural land yields 3 crops annually and the rest single crop. It is also marked with annual population growth rate of 4 % (Khatoon and Mondal, 2012). Irrigation in this area is almost wholly groundwater based. Various reports on ground water depletion concluded that Rarh area of this district shown continuous depletion in last three decades (Mohalla and Khatoon, 2013). This research aims at forecasting ground water fluctuations using time series analysis. Groundwater table data from each station under Murshidabad district was collected and analyzed station wise according to availability. The time series water table observations collected for four months January, May, August and November during the period from 2005 to 2013. Structural time series modeling technique was applied to model and foresee behavior of groundwater table in 2014. Data from 2005 to 2012 was used for analysis and 2013 data used for validation. Residuals of developed model for each station was tested for normality and randomness. Chi-square test used to test goodness of fit of model. On the basis of significance of parameters, residual analysis and goodness of fit, models were selected and used for forecasting purpose.
机译：西孟加拉邦的穆尔什达巴德区以其农业潜力而闻名，种植强度超过200％。大约70％的农业用地每年可生产3种作物，其余的则是单种作物。人口年增长率为4％（Khatoon and Mondal，2012）。该地区的灌溉几乎全部基于地下水。关于地下水枯竭的各种报道得出的结论是，该地区的拉赫地区在过去的三十年中显示出持续的枯竭（Mohalla和Khatoon，2013年）。本研究旨在使用时间序列分析预测地下水波动。收集了Murshidabad地区下每个站点的地下水位数据，并根据可用性对站点进行了分析。在2005年至2013年期间收集了四个月的1月，5月，8月和11月的时间序列地下水位观测数据。采用结构时间序列建模技术对2014年地下水位进行了建模和预测。使用了2005年至2012年的数据用于分析，2013年数据用于验证。测试了每个站点开发模型的残差的正态性和随机性。卡方检验用于检验模型的拟合优度。根据参数的重要性，残差分析和拟合优度，选择模型并用于预测目的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号