Environmental sustainability of grey water footprints in Peshawar Basin: Current and future reduced flow scenarios for Kabul River

Khan, Taous; Khan, Hizbullah

doi:10.25165/j.ijabe.20191204.4804

Cited by 4 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Grey water footprint is an indicator to weigh the water pollution level within a region [50]. By establishing the relationship between grey water footprint and water resources, the value of the regional water pollution level can be obtained.…”

Section: Grey Water Footprint Sustainabilitymentioning

confidence: 99%

Quantification and Evaluation of Grey Water Footprint in Yantai

Xue

Lü

et al. 2022

Water

View full text Add to dashboard Cite

Problems such as water scarcity and pollution frequently occur in coastal zones. This study investigated the grey water footprint and the sustainability and intensity of grey water footprint in Yantai between 2014 and 2019 by taking both surface water and groundwater into consideration. The research results indicated that the Yantai grey water footprint firstly increased and then decreased between 2014 and 2019. The lowest grey water footprint in 2019 was 744 million m3. The agricultural grey water footprint accounted for a large proportion of the total grey water footprint. Although the sustainability of grey water footprint fluctuates in Yantai, it maintains well. The Yantai grey footprint intensity gradually decreased to <10 m3/10,000 CNY. The economic benefit of grey water footprint and utilization efficiency of water resources have been improved yearly. The quality of the water environment in Yantai has also been improved. The research of this paper provides some useful information for water resources protection and sustainable utilization in coastal cities.

show abstract

Section: Grey Water Footprint Sustainabilitymentioning

confidence: 99%

Quantification and Evaluation of Grey Water Footprint in Yantai

Xue

Lü

et al. 2022

Water

View full text Add to dashboard Cite

show abstract

“…Almost all these industries have no treatment facilities for effluents. Nitrites from agricultural fertilizers and untreated effluents like ammonia, chromium, and nickel from industries influence the water quality in these areas 38 .…”

Section: Introductionmentioning

confidence: 99%

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

Irfan

Alam

Khan

et al. 2023

Sci Rep

View full text Add to dashboard Cite

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.

show abstract

Distance and Weightage-based Identification of Most Critical and Vulnerable locations of Surface Water Pollution in Kabul River Tributaries

Irfan¹,

Alam²,

Khan³

et al. 2022

Preprint

View full text Add to dashboard Cite

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 agricultural purposes. Khyber Pakhtunkhwa (KPK) province of Pakistan is blessed with 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 deteriorated with time. Which impacts 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 and identifies the most critical locations in terms of water quality. Various physical, chemical, and biological parameters at ten sites on as many Kabul River tributaries are examined to investigate surface water quality. The distance and weightage-based identification method is used to identify the most critical and vulnerable locations for each parameter. 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, BOD, and turbidity. In comparison, the distance-based iteration method is used to identify the most vulnerable location against the specific parameter. All the results are finally compared with the interpolated values over the entire region using Kriging interpolation. The areas are mostly the same identified through the distance and weightage-based method. The results will guide the competent authority to install the monitoring station and treatment plants for specific parameters responsible for the critical location and to stop further contamination of the particular parameter near the threshold.

show abstract

Environmental sustainability of grey water footprints in Peshawar Basin: Current and future reduced flow scenarios for Kabul River

Cited by 4 publications

References 22 publications

Quantification and Evaluation of Grey Water Footprint in Yantai

Quantification and Evaluation of Grey Water Footprint in Yantai

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

Distance and Weightage-based Identification of Most Critical and Vulnerable locations of Surface Water Pollution in Kabul River Tributaries

Contact Info

Product

Resources

About