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The cluster-wise area of shallow and deep aquifer zones is used to estimate the potential of groundwater. The potential of the shallow aquifer zone is estimated at 4.61 MCM (million cubic meters) and for the deep aquifer zone at 17,509.03 MCM, while the total groundwater potential for both aquifer zones is estimated at 17,513.64 MCM. The Geographical Information System (GIS) was employed efficiently to estimate the subsurface volume of the lithological rock layers using cost-effective and time-saving techniques, while the Rockwork software integrated with GIS was successfully used to visualize the subsurface lithology and stratigraphy of the aquifer zones. The estimated potential of groundwater can be uncovered by using the alternative solar pumping system to improve the agricultural system in the study area, thereby reducing the migration rate, reducing poverty, and improving the socio-economic conditions of livelihood. In the future, too, it will be essential to design water quality studies to ensure the proper use of groundwater.

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  • The current study discovered two potential groundwater zones of the (shallow and deep) aquifer.

  • The potential of the groundwater has been estimated using GIS for future planning and development.

  • The overall groundwater potential for both aquifer zones is estimated at 17,513.64 MCM.

Graphical Abstract

Graphical Abstract
Graphical Abstract
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Graphical Abstract
Graphical Abstract
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aquifer zone, deep and shallow, groundwater potential, lithology, stratigraphy
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Agriculture is the backbone of the economy of any country and freshwater resources are essential drivers for sustainable development, especially in the world's dry regions. In contrast, the accessibility of groundwater (GW) is limited and depends on the precipitation pattern in arid regions. Increasing the population leads to water demand for food and fiber (Singh 2019).

Consequently, the domestic, agricultural, and industrial sectors increase utilization and decrease resources. In light of the above statement, GW resources are under threat globally (Varua et al. 2018; Kalhor et al. 2019; Singh 2019; Singh et al. 2019). Converting agricultural lands into dry regions is due to the quick declination of surface and GW reservoirs (Gaaloul 2014).

GW is suitable for freshwater resources and easy to extract for utilization (Panhwar et al. 2022; Solangi et al. 2022a). The quality and quantity of the GW resources vary from region to region and with their lithology. Some areas have assessed freshwater through shallow aquifers and some have done vice versa through a deep aquifer (Singh 2015). Pakistan is one of the most water-challenging countries globally and depends on the arid to semi-arid climatic region (Keerio et al. 2020). GW is one of the most valuable natural resources of drinking water (Nassiri & Mehdinejad 2022; Uc Castillo et al. 2022), supportive of human health and economic growth. MacAllister et al. (2022) studied regional post-monsoon GW accumulation at a regional scale from 1900 to 2010. They showed that Pakistan has historically enormous GW potential. The availability of GW gradually increased to 3.6 cm/year in the early 20th century due to the development of an extensive irrigation canal network that increased the yield of GW formation. While the status of the GW level was stable between 1970 and 2000 due to above and average rainfall and tubewell development for irrigation. Later, in the first decade of the 21st century, GW yield began to decrease by 2.8 cm/year due to erratic precipitation patterns and tube well development. Pakistan ranks fourth in the world for GW abstraction countries; that extract 65 BCM (billion cubic meters) annually and have 55 BCM of sustainable GW resources. (Alam et al. 2022). Currently, the GW availability is below 1,000 m3/per capita annually, which is expected to reduce up to 837 m3/per capita by December 2025 (Engelman & LeRoy 1993). Consequently, a precise assessment of GW potential is vital because water resources are serious to economic development in these areas (Leketa et al. 2019).

The RS (Remote Sensing) and Geographical Information System (GIS) techniques have been important to estimate the GW potential since the mid-1990s (Jasrotia et al. 2013; Solangi et al. 2022b). The integrating approach of the RS/GIS overcomes the most critical problems and provides quick information on broader utilization (Rather et al. 2022), a time-saving and cost-benefit practice, with applicable processing results through productive outcomes. A GIS method might be applied efficiently to associate unexpected hydrogeological themes observed in the GW perspective on a particular regional scale (Shahid et al. 2000), it is also a convenient method to identify the GW potential (Ombasa et al. 2022). RS and GIS are the leading systems for the ecological growth of essential GW resources, primarily in countries with a deficiency of data. In previous surveys, the depiction of GW potential has been researched by utilizing GIS innovation with lithological layer data. Evaluated the GW potential creating different layers of each stone and the information on porosity has been interpreted with the thickness of each rock layer (Shahid et al. 2000). However, it is essential to determine the potential of GW resources to combat the challenging situations of the increasing population and climate change vulnerabilities. The current study is aimed to assess the potential GW zones for agricultural sustainability in the remote area of district Dadu Sindh, Pakistan. Some basic information about the proposed study area is as follows:

Climate

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The study area is climatically arid in the semi-arid region and depends on precipitation as a primary source. The average annual rainfall is about 120 mm, while the monsoon falls from July–September.

The study area experienced several devastating floods and droughts over the past 81 years (1933–2013). Droughts and floods have been extensive in the current periods. The recent drought from 1996 to 2002 severely affected the study area, reducing water resources, water table levels and water quality and increasing mortality rates, migration rates, and poverty (Soomro A. et al., 2019; Bisharat 2016). In 2010, significant flooding occurred in the study area, increasing the death toll, causing land degradation, destroying infrastructure, devastating the agricultural system, and damaging shallow wells (Soomro, A. et al. 2019; Soomro et al. 2019a, 2019b). In the normal precipitation cycle, the runoff is diverted to the arid lands for farming practices, subsequently, GW is used to supplement irrigation and livelihood practices. The study area falls in climatically arid to semi-arid regions. The hottest month is June with a temperature of about 45 °C and the coldest month is January where the temperature varies below 14 °C.

Agriculture

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Agriculture is the backbone for sustainable development in the study area. Rabi and Kharif are two cropping seasons in the study area that depend on the GW resources. The primary precipitation months are the monsoon from July to September each year. The rest of the year's agriculture and livelihood activities depend on the precipitation and GW resource. Precipitation creates runoff which is diverted by the local people for the agricultural purpose. Soomro et al. (2020) researched the same area using RS and a hydrological modeling approach. They showed that 86.25% of the settlements in the study area, followed by 83.85% of the land, used runoff water for agricultural purposes. Likewise, 65% of the area was used for agriculture. Due to the elevation compared to the Indus River, farmers have captured 39.50% of the runoff in the farmland and ditches in the form of wetlands. Consequently, the stored water is used for supplemental irrigation and replenishment of the shallow aquifer. Cotton, wheat, cluster beans, pulses, sesame, and vegetables are the major crops in the study area. During the drought seasons, local people migrate to the agricultural and industrial regions and return during the wet seasons. In this situation, the sustainability and planning of the GW may play a vital role in sustainable development in the region.

Hydrology

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The study area consists of a hilly tract and most of the settlements are situated in the foothills. Rainfall is the main source of torrential runoff. Most of the floods are generated in hilly areas that move to the foothill area and collect fresh floods. To reduce the velocity of the floods, the farmers divert one-third quantity of the floods to their agricultural lands by raising periphery bunds around the lands, and the rest of the runoff wastes into the Arabian Sea through the Indus River without use. In the study area, the floods are collected in the natural depression ponds, manmade constructed ponds/reservoirs, and periphery bunds (Varua et al. 2018). The torrential runoff spreads in the study area through numerous sub-torrents. The ‘Nai Gaj’ is the mighty torrential source of runoff and other average torrents Mirani, Naing, and Angai Nai are prominent in the study area.

Groundwater

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The study area depends on two aquifer zones, i.e. shallow (dug wells) and deep (tube wells) aquifers. The primary source for recharging aquifers is precipitation. The GW is extracted for agriculture and livelihood cores (Frenken 2012). The GW level fluctuates with seasonal variations.

Rock formation

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The lithological survey area includes the Khirthar formation area (Figure 1). The formation consists of alluvial soil, gravel, clay, sand, and limestone, as collected from drill log lithology, etc. The excess amount of sand, silt, as clay deposited in the flood plains is called, alluvial soil. Mostly identified in the river springs. They can also be found in the higher areas of the floodplains. It is the first upper layer below the surface of the earth with fairly deposited nutrient levels (Hakeem et al. 2014). The Gaj Formation includes limestone, sandstone, shale, and light aggregates. In the middle Miocene-age, a large part of the freshwater aquifer closed the mountain streams, mostly at shallow depths (Soomro et al. 2022).
Figure 1
Khirthar formation.
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Khirthar formation.

Figure 1
Khirthar formation.
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Khirthar formation.

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Study area

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The study area is situated in the hilly southwestern portion of the lower Indus River, covering an area of 1,442.13 km2 of district Dadu, Sindh, Pakistan, and lies between longitudes from 67.167735'E to 67.682658 (dd)'E and latitudes from 26.136681'N to 26.593051 (dd)'N with uneven topography (Figure 2). The study area is well known as the ‘KAACHO,’ one of the leading dry regions and rich in flora and fauna. The study area is administratively divided into various small union councils with a population of 250,339.
Figure 2
Layout map of the study area and locations of existing groundwater.
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Layout map of the study area and locations of existing groundwater.

Figure 2
Layout map of the study area and locations of existing groundwater.
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Layout map of the study area and locations of existing groundwater.

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Data collection

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The data on GW extraction, daily pumping, seasonal basis pumping, and land use cover under various cropping patterns have been collected using the questionnaires filled out by the stakeholder through interviews. The 14 deep wells and four dug wells data have been collected (Figure 2). The hydraulic data of GW sources were measured through the measuring tape and monitored from October 2016 to April 2019, the aquifer level was on a seasonal basis for the dry and wet seasons to monitor how the regional climate affects the GW aquifer. The coordinates of all the GW resources have been recorded through the GPS (Global Positioning System) and confirmed by Google Earth Pro. ArcGIS was employed to change point shapefiles into KML format. The database has been recorded in Table 1. The lithological information regarding the study area has been collected through the literature citation, collected through the revenue, irrigation, and soil survey departments. The lithological logs of the GW resources have been received from the Mining and Industrial Consultants, who worked on the installation of a dug well and a deep well in 1990 for a project under the Government of Sindh.

Table 1

Database of tube wells and dug wells information and water levels in the study area

No.Name of farmerWell IDElevation (m)Min. level (m)Max. level (m)Base of well (m)LongitudeLatitudeThe total depth of well (m)
1 Moosa Khan Baazmaad Village, Johi DTW 1 51 23.80 22.10 −71.00 67.50645 26.74077 122 
2 Aashiq Ali khoso, Johi DTW 2 45 26.80 26.40 −46.50 67.52888 26.7322 91.5 
3 Mohammad Moosa Leghari, Wahi Paandhi DTW 3 54 −13.87 −14.22 −83.20 67.36399 26.65488 137.2 
4 Ghulam Asghar Leghari DTW 4 55 −15.12 −16.09 −67.00 67.36392 26.64442 122 
5 Pyar Ali Rustmani DTW 5 55 −15.01 −16.08 −67.00 67.52666 26.64422 122 
6 Bhoora Khan Rustmani,Wahi Pandhi DTW 6 55 14.5 13.45 −51.4 67.36246 26.65466 109.4 
7 Abdul Aziz Rustmani, Wahi Paandhi DTW 7 53 3.9 3.1 −103.4 67.40432 26.65701 152.4 
8 Zulfiqar Ali Rustmani, Wahi Pandhi DTW 8 49 3.92 3.01 −103.4 67.40422 26.65711 152.4 
9 Deedar Ali Rustmani, Gaj Nai DTW 9 49 5.92 4.91 −104.4 67.41022 26.65802 152.4 
10 Raees Ali Ghulam Leghari, Near Gaj Nai DTW 10 50 7.91 6.78 −69 67.36343 26.65905 122 
11 Jhangar Bajara, Dadu DTW 11 50 40.5 38.8 −41.5 67.57109 26.308899 91.5 
12 Bajara, Dadu DTW 12 46 36.8 35.8 −45.5 67.572269 26.308351 91.5 
13 Bajara, Dadu DTW 13 46 36.95 36.2 −60.8 67.5743 26.308121 106.8 
14 Jhangar Bajara, Dadu DTW 14 49 37.8 36.5 −73 67.577608 26.309821 122 
15 Jhagara Bajara, Dadu DDW 1 45 40.08 39.75 5.5 67.516881 26.230153 39.5 
16 Jhagara Bajara, Dadu DDW 2 49 39.5 37.91 3.27 67.513276 26.23187 45.73 
17 Jhagara Bajara. Dadu DDW 3 50 40.75 40.35 11.5 67.515293 26.23579 38.5 
18 Bajara, Dadu DDW 4 49 39.35 38.5 18.52 67.525456 26.249538 30.48 
No.Name of farmerWell IDElevation (m)Min. level (m)Max. level (m)Base of well (m)LongitudeLatitudeThe total depth of well (m)
1 Moosa Khan Baazmaad Village, Johi DTW 1 51 23.80 22.10 −71.00 67.50645 26.74077 122 
2 Aashiq Ali khoso, Johi DTW 2 45 26.80 26.40 −46.50 67.52888 26.7322 91.5 
3 Mohammad Moosa Leghari, Wahi Paandhi DTW 3 54 −13.87 −14.22 −83.20 67.36399 26.65488 137.2 
4 Ghulam Asghar Leghari DTW 4 55 −15.12 −16.09 −67.00 67.36392 26.64442 122 
5 Pyar Ali Rustmani DTW 5 55 −15.01 −16.08 −67.00 67.52666 26.64422 122 
6 Bhoora Khan Rustmani,Wahi Pandhi DTW 6 55 14.5 13.45 −51.4 67.36246 26.65466 109.4 
7 Abdul Aziz Rustmani, Wahi Paandhi DTW 7 53 3.9 3.1 −103.4 67.40432 26.65701 152.4 
8 Zulfiqar Ali Rustmani, Wahi Pandhi DTW 8 49 3.92 3.01 −103.4 67.40422 26.65711 152.4 
9 Deedar Ali Rustmani, Gaj Nai DTW 9 49 5.92 4.91 −104.4 67.41022 26.65802 152.4 
10 Raees Ali Ghulam Leghari, Near Gaj Nai DTW 10 50 7.91 6.78 −69 67.36343 26.65905 122 
11 Jhangar Bajara, Dadu DTW 11 50 40.5 38.8 −41.5 67.57109 26.308899 91.5 
12 Bajara, Dadu DTW 12 46 36.8 35.8 −45.5 67.572269 26.308351 91.5 
13 Bajara, Dadu DTW 13 46 36.95 36.2 −60.8 67.5743 26.308121 106.8 
14 Jhangar Bajara, Dadu DTW 14 49 37.8 36.5 −73 67.577608 26.309821 122 
15 Jhagara Bajara, Dadu DDW 1 45 40.08 39.75 5.5 67.516881 26.230153 39.5 
16 Jhagara Bajara, Dadu DDW 2 49 39.5 37.91 3.27 67.513276 26.23187 45.73 
17 Jhagara Bajara. Dadu DDW 3 50 40.75 40.35 11.5 67.515293 26.23579 38.5 
18 Bajara, Dadu DDW 4 49 39.35 38.5 18.52 67.525456 26.249538 30.48 
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Estimation of rock volume using GIS application

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The dataset has been developed into an Excel sheet and converted into a CSV (Comma-Separated Values) format. The bore log data has been used to visualize the actual underground situation of the rock layers employing the Rockwork 15 version. The lithology setup was converted into the stratigraphy and developed in the 3D (Three-Dimensional) thematic map to represent the rock layers (Figure 3) of the GW resources in the study area. The database of bore logs for each dug well and deep well has been shown through coordinate systems in ArcGIS version 10.5.1 and developed the thematic layers of the deep and shallow aquifers. Each thickness of lithology is converted into a volume using the raster calculator in GIS and the porosity data of the layer is multiplied by volume to estimate the specific yield GW potential. The highlighted portions of Table 2 (Khokhar et al. 2016) indicated the porosity values used to convert into water potential for the particular layers. The detailed methodology is described in Figure 4.
Table 2

Lithological formation and its porosity in the study area

The porosity of the soil layer
LithologyPorosity (%)Porosity
Alluvial 30.2 0.30 
Silt 53.2 0.53 
Sand 30.0 0.30 
Gravel 40.0 0.40 
Clay 42.4 0.42 
Shale 17.0 0.17 
Limestone 15.0 0.15 
The porosity of the soil layer
LithologyPorosity (%)Porosity
Alluvial 30.2 0.30 
Silt 53.2 0.53 
Sand 30.0 0.30 
Gravel 40.0 0.40 
Clay 42.4 0.42 
Shale 17.0 0.17 
Limestone 15.0 0.15 
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Figure 3
Flowchart of elaborating the visualization procedure of lithology and stratigraphic of the wells in 3D using Rockwork 15.
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Flowchart of elaborating the visualization procedure of lithology and stratigraphic of the wells in 3D using Rockwork 15.

Figure 3
Flowchart of elaborating the visualization procedure of lithology and stratigraphic of the wells in 3D using Rockwork 15.
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Flowchart of elaborating the visualization procedure of lithology and stratigraphic of the wells in 3D using Rockwork 15.

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Figure 4
Flowchart of methodology.
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Flowchart of methodology.

Figure 4
Flowchart of methodology.
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Flowchart of methodology.

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Visualization of lithology and stratigraphy

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Figure 4 shows the detailed visualization and investigation of both shallow and deep aquifer zones in 3D views. The 3D survey identified the structures of the subsurface soil layer and the spatial distribution of the existing GW resources in both clusters, with the visualization showing the extent of the aquifers and the soil layers in different colors (Figure 5).
Figure 5
Rockwork 3D model visualization of lithology and stratigraphy.
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Rockwork 3D model visualization of lithology and stratigraphy.

Figure 5
Rockwork 3D model visualization of lithology and stratigraphy.
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Rockwork 3D model visualization of lithology and stratigraphy.

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GW potential district Dadu

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Table 3 shows that the study area covers 1,442.13 km2, while the cluster area of shallow aquifer zone 2.65 km2 and deep aquifer zone 1,008.28 km2 covers the study area. The four dug wells in the shallow aquifer zone and 14 tube wells in the deep aquifer zone were selected and monitored for study purposes. A limited area under a dug well has been chosen due to some limitations of the hilly mountainous region and its physiographic conditions. The total area of 1,010.93 km2 was monitored under both clusters of aquifer zones.

Table 3

The area under different aquifer zones

DistrictStudy area (km2)Aquifer zoneNumber of wellsCluster-wise area (km2)
Dadu 1,442.13 Shallow 04 2.65 
Deep 14 1,008.28 
Total 18 1,010.93 
DistrictStudy area (km2)Aquifer zoneNumber of wellsCluster-wise area (km2)
Dadu 1,442.13 Shallow 04 2.65 
Deep 14 1,008.28 
Total 18 1,010.93 
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Table 4 depicts the GW potential of the shallow aquifer (dug wells) zone in the study area. Table 4 represents two parts of the figure and tabular formations. The figure formation showed sub-divided portions of the subsurface lithology and straitigraphical rock layer representations of shallow aquifers. The table discloses that the slice of A-Horizon containing the soil layers of alluvial, silt, and sand consists of the volumetric capacity of rock 6,186,266.20 m3. Spergen Fm has a rock layer of gravel with a volume of 7,089,070.00 m3. Leadville Ls leads the soil layer of clay and shale with a volume of 4,363,068.30 m3. Potosi Fm is rich with sand soil containing a volume of 4,707,350.87 m3 and the basement is full of limestone rock with 2,428,706.98 m3. The lithological rock layers of gravel, sand, and limestone contain a porosity of 0.4, 0.3, and 0.15% and the potential of GW is 2.84, 1.41, and 0.36 MCM (million cubic meters), respectively. The total GW potential is estimated at 4.61 MCM in the shallow aquifer zone.

Table 4

Cluster-wise GW of a dug well in the Khirthar formation of the district Dadu

 
 
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Table 5 portrays the GW potential of the deep aquifer (tube wells) zone. The table is sub-divided into figural and tabular portions. The lithology and straitigraphical layers disclosed that the slice of A-Horizon contains alluvial and clay soil layers and occupies the rock volume of 26,040,684,328.58 m3. Spurgeon Fm covered only the rock layer of gravel with a volume of 18,176,894,977.77 m3, having a porosity of 0.4% and estimated the potential of GW at 7,270.76 MCM. Leadville Ls clay contains a limestone rock layer with a volume of 10,330,789,857.39 m3. Potosi Fm includes a sand layer volume of 27,488,333,542 m3, having 0.30% of porosity and a potential for GW of 8,246.50 MCM. The basement cover layer of limestone with a volume of 13,278,503,609.64 m3, having 0.15% of the porosity the potential of GW 1,991.78 MCM, however the total GW potential in the deep aquifer zone has an estimated 17,509.03 MCM. Though, the clusters of both aquifer zones (shallow and deep) in the study area, determined 17,513.64 MCM.

Table 5

Cluster-wise GW of a tube well in the Khirthar formation of the district Dadu

 
 
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The alluvial and the upper layer of soil: just below the surface contain the surficial deposition of the rock layer, which has porosity but does not contribute to the groundwater. The other soil layers shale, clay, and silt react as aquitards that restrict the flow of GW because of squat penetrability, that is not measured for potential GW zone (soil quality).

Regional agriculture sustainability

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The current agricultural scenario is unsustainable due to negative impacts on natural resources and the global environment. About  one-third of agricultural land has been degraded by waterlogging, salts are affected, up to 75% of cultural genetic diversity has been lost through the replacement of hybrid seed, 22% of animal breeds are endangered, about 13 million hectares of forest have been converted to other land uses every year. Most of the agricultural land is urbanized due to the high-income yield. The sustainability of agriculture is the greatest challenge facing humanity worldwide. The gradually growing population of 9.0 billion people needs food security and will demand 60% more basic foodstuffs by 2050. At the same time, around 793 million people worldwide suffer from hunger, as reported by Ursu & Petre (2022).

To meet these challenges, it is important to protect the existing natural resources, which could be used with smart techniques at the regional scale to conserve the natural resources and agricultural system to improve food security (Laurett et al. 2021). The results of sustainable agriculture are reflected in sustainable production – ecological, economical, and social. Likewise, the exposed GW potential can be used sensibly for sustainable agriculture with innovative techniques, which improves the socio-economic conditions at the regional level of the study area.

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The study has conducted cores in the arid mountainous region of the Dadu district depending on rainfall as the main source of agriculture and livelihood. The study area has historical experience with massive flooding and prolonged periods of drought. The GW source is often used in the study area to cover the food and fiber requirements. The current scenario of GW resources is severe in the study area. The current study identified two shallow and deep aquifer zones consisting of the Khirthar formation in the study area. The lithological soil strata contain potential aquifers in the gravel, sand, and limestone and allow for lithological and stratigraphically visualized analysis and investigation through the 3D view. The present study has estimated the total GW potential for the Dadu district for a dense cluster of shallow and deep zones. GW potential results include 4.61 and 17,509.03 MCM, respectively. Total GW potential was estimated at 17,513.64 MCM in shallow and deep clusters of the study area. The GIS was used to determine GW potential and a reliable data set for numerical GW modeling, integration, demonstration of image processing, and modeling results was developed. The current study supported GIS and Rockwork, which helped achieve the goals of the current GW potential reviews.

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The current study shows the groundwater potential zones in the study area, which was possible due to the collaborative help of Mr Muhammad Hassan Soomro, Senior Geologist, who facilitate the field visits and provide guidelines. Last but not least the authors of the current manuscript have used their expertise to investigate and developed through the interest of untired hard work.

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None.

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All relevant data are included in the paper or its Supplementary Information.

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The authors declare there is no conflict.

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