Ghulam Zakir-Hassan; Jehangir F Punthakey; Ghulam Shabir; Faiz Raza Hassan

doi:10.26599/JGSE.2024.9280029

doi: 10.26599/JGSE.2024.9280029

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出版历程
- 收稿日期: 2023-10-14
- 录用日期: 2024-08-21
- 网络出版日期: 2024-12-06
- 刊出日期: 2024-12-09

Assessing the potential of underground storage of flood water: A case study from Southern Punjab Region in Pakistan

1.
School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, Albury 2640, NSW, Australia
2.
Irrigation Research Institute (IRI), Government of the Punjab, Irrigation Department, Lahore 54500, Pakistan
3.
Gulbali Institute, Charles Sturt University, Albury 2640, NSW, Australia
4.
Ecoseal Pty Ltd, Roseville, NSW, Australia

More Information

Corresponding author: zakirjg@gmail.com

摘要

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Abstract: An intensively irrigated area in southern part of Punjab Province, Pakistan, has been selected by the Punjab Irrigation Department (PID) to implement a Managed Aquifer Recharge (MAR) project. This project involves diverting floodwater from the Islam Headwork on Sutlej River into the abandoned Mailsi Canal. Utilizing various structures such as depressions, abandoned canals, flood channels, open fields, and deserts for MAR can reduce the flood intensity while recharging aquifer and wetlands. The study area, known for its fertile lands and serving as a food basket for the Punjab Province, is experiencing groundwater depletion at the rate of 0.30 m to 0.70 m per year, significantly increasing pumping costs. This study aims to evaluate the suitability of the sites for the MAR project and assess the storage capacity of the aquifer for floodwater retention. Historical groundwater level data from 25 observation wells across an area of 1,522 km² were analysed, with the study area divided in to 25 polygons using ArcMap10.6 software. Specific yield method was employed to assess the available storage capacity of the aquifer. Results indicate that the site is suitable for MAR and has the potential to store approximately 1.88 km³ of floodwater as of 2020, thereby reducing flood intensity and enhancing eco-hydrogeological conditions. MAR is identified as a Nature-Based Solution (NBS) for both flood mitigation and groundwater sustainability.
- Groundwater /
- Managed Aquifer Recharge /
- Indus River Basin /
- Aquifer /
- Vehari /
- Punjab /
- Pakistan

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Figure 1. Applications and MAR technology classification (sub-type) (IGRAC, 2014)

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Figure 2. Map of study area and Thiessen Polygons

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Figure 3. Average monthly rainfall (mm) at Multan, Sahiwal, Bahawalnagar and Bahawalpur

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Figure 4. Long-term (1967–2020) mean monthly maximum and minimum temperatures at four stations

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Figure 5. Fence diagram showing of the study area showing subsurface lithology

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Figure 6. Average water level rise/fall at different locations in study area in pre monsoon 2015–2020

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Figure 7. Average water level rise/fall at different locations in study area in post monsoon 2015–2020

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Figure 8. Depth to water table (DTWT-m) at different piezometers in Pre 2020 and Pre 2015

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Figure 9. Depth to water table (DTWT-m) at different piezometers in Post 2020 and Post 2015

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Figure 10. Increasing trend of GWRP for pre-2015 to pre-2020

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Figure 11. Increasing trend of GWRP for post-2015 to post-2020

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Figure 12. Ground water recharge potential during post-2020

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Figure 13. Ground water recharge potential in pre_2020

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Table 1. Statistics of DTWT below natural land surface from 2015–2020

Parameter	*Pre 2015	**Post 2015	Pre 2016	Post 2016	Pre 2017	Post 2017	Pre 2018	Post 2018	Pre 2019	Post 2019	Pre 2020	Post 2020
Max	23.2	22.6	23.8	22.6	23.8	22.7	24.0	22.7	24.1	22.8	24.3	22.8
Min	5.6	6.0	5.6	6.0	5.8	5.9	6.1	6.0	6.2	6.2	6.3	6.2
Avg	16.6	16.4	16.7	16.6	16.8	16.8	17.0	17.0	17.2	17.1	17.4	17.1
STDDEV	4.5	4.3	4.6	4.4	4.5	4.3	4.5	4.3	4.5	4.4	4.6	4.4
Notes: Pre monsoon; *Post monsoon

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Table 2. Statistics of DTWL during Post-Monsoon periods from 2015 to 2020

Total	Water level Rise/fall in Post monsoon in 5 years (m)	Drop/Rise in water level in Post monsoon in per year (m)
Max	3.49	0.70
Min	−1.49	−0.30
Avg	0.75	0.15
STDDEV	0.97	0.19

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Table 3. Statistics of DTWL in Pre-Monsoon periods from 2015 to 2020

Total	Water level Rise/fall in Pre monsoon in 5 years (m)	Drop/Rise in water level in Pre monsoon in per year (m)
Max	2.08	0.42
Min	−5.16	−1.03
Avg.	−0.87	−0.17
STDDEV	1.13	0.23

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Table 4. GWRP for the period of pre-2015 to pre-2020 at different locations in the study area

Parameter	Area of polygon (km²)	Natural Surface Level (NSL) (m-amsl)	GWRP (BCM)
Parameter	Area of polygon (km²)	Natural Surface Level (NSL) (m-amsl)	Pre-2020	Pre-2019	Pre-2018	Pre-2017	Pre-2016	Pre-2015
Total	1522		1.88	1.85	1.82	1.79	1.78	1.76
Max	111.83	148	0.186	0.185	0.184	0.183	0.182	0.181
Min	18.69	134	0.003	0.002	0.001	0.000	−0.001	−0.002
Avg	55.88	139	0.075	0.074	0.073	0.072	0.071	0.070
STD	26.66	4	0.047	0.047	0.046	0.046	0.045	0.045

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Table 5. GWRP for the period of post-2015 to post-2020

Parameter	Area of polygon (km²)	Natural Surface Level (NSL) (m-amsl)	GWRP (BCM)
Parameter	Area of polygon (km²)	Natural Surface Level (NSL) (m-amsl)	Post-2020	Post-2019	Post-2018	Post-2017	Post-2016	Post-2015
Total	1522		1.87	1.85	1.83	1.80	1.77	1.74
Max	111.83	148	0.176	0.175	0.174	0.173	0.172	0.172
Min	18.69	134	0.000	−0.001	−0.001	−0.001	−0.002	−0.004
Avg	55.88	139	0.075	0.074	0.073	0.072	0.071	0.069
STD	26.66	4	0.047	0.047	0.046	0.046	0.045	0.044

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