Distance and weightage-based identification of most critical and vulnerable locations of surface water pollution in Kabul river tributaries

Sci Rep. 2023 Jul 18;13(1):11615. doi: 10.1038/s41598-023-38018-8.

Abstract

Water plays a key role in the economic growth of an agricultural country. Pakistan is a farming country that uses almost 90% of its water resources for agriculture. Khyber Pakhtunkhwa (KPK) province of Pakistan has extensive surface water resources. In addition to using groundwater resources for irrigation, large parts of its flat plains are irrigated with the Kabul River surface water. Due to large population growth and unregulated small/local scale industries in the region, surface water quality deteriorates with time, which affects people's health when polluted surface water is used for irrigation purposes. This research investigates the surface water quality of Kabul River's different tributaries. It identifies the most critical and vulnerable locations regarding water quality using the weightage-based identification method and distance-based iteration method, respectively. The Bara River exhibited the most critical location, surpassing the threshold values by a considerable margin in at least seven water quality parameters. The maximum seven critical values determined against the Bara River using the weightage-based method, i.e., 17.5, 5.95, 7.35, 27.65, 1.75, 0.35, and 10.45 for total alkalinity, sodium, total hardness, magnesium, total suspended solids, biological oxygen demand (BOD), and turbidity. The Khairabad station, where the Kabul River meets the Indus River, was identified as vulnerable due to elevated levels of total suspended solids, hardness, sulfate, sodium, and magnesium using distance-based methods. The locations, i.e. Adezai, Jindi, Pabbi, and Warsak Dam, appeared critical and vulnerable due to the prevalence of small-scale industries on their bank and high population densities. All the results are finally compared with the interpolated values over the entire region using Kriging interpolation to identify critical and vulnerable areas accurately. The results from the distance and weightage-based methods aligned with the physical reality on the ground further validate the results. The critical and vulnerable locations required immediate attention and preventive measures to address the deteriorating water quality parameters by installing monitoring stations and treatment plants to stop further contamination of the particular parameter.