Zoning of groundwater level using innovative trend analysis: Case study at Rechna Doab, Pakistan

Authors

  • Muhammad Abbas Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Punjab, Pakistan
  • Muhammad Arshad Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Punjab, Pakistan
  • Muhammad Adnan Shahid Agricultural Remote Sensing Lab (ARSL), National Center of GIS and Space Applications (NCGSA), Faisalabad, Punjab, Pakistan

DOI:

https://doi.org/10.19149/wrim.v12i1-3.3155

Keywords:

Groundwater level, time series, Sen’s estimator, pre-monsoon, pro-monson

Abstract

Groundwater plays a pivotal role in the economy from several country due to the scarcity of surface freshwater. In Pakistan it is the second largest water source which is used for irrigation, drinking and domestic uses. To monitor the groundwater availability and variation in country, the trend needs to be observed over time period; therefore, a study was conducted at Rechna Doab (Punjab province, Pakistan) to analyze the groundwater level trends over (period 2006-2019) using innovative trend analysis (ITA). 134 tube wells data was collected from Punjab Irrigation Department in pre-monsoon (June) and post-monsoon seasons (October), which were subsequently segregated at tehsils. In ITA, the data was divided in two equal parts and arranged in ascending order, first half (2006-2012) placed on the horizontal axis (X-axis) and second half (2013-2019) placed on the vertical axis (Y-axis) in a two-dimensional Cartesian coordinate system. After distribution of data, the points which are above the triage line show positive trend (increasing trend), similarly the data points which are scattered below the trend line represent negative trend (decreasing trend), while the data points which are scattered at the 1:1 line indicates  no trend. For both seasons (pre-monsoon and post-monsoon), the results of the groundwater level trends for tehsil (representing point in each tehsil) were spatially interpolated using interpolation method of the Inverse Distance Weighted (IDW). A division with three classes was adopted, namely: low, moderate, and high-water levels. For pre-monsoon season it was observed that 32% groundwater wells were showing no trend, 62% with decreasing trend, and 7% with increasing trend. For post-monsoon season, 43% groundwater wells were showing no trend, 50% with decreasing trend, and 7% with increasing trend.

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Published

2023-03-15

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