1. Introduction
The population of Pakistan is increasing exponentially, accompanied by a rapid increase in the proposed study area of Peshawar [
1,
2]. The economy of Pakistan is based on agriculture, and this is the main reason for extensive research in the area of water preservation [
3], even though every year a large quantity of rainfall as well as surface and sub-surface water sources convert into floods and destroy all agriculture products [
4,
5]. Still, the soft cover of vegetation provides an excellent means for infiltration [
6,
7]. However, the rate of infiltration for settled (covered) areas is different. Most rainfall received by the settled/covered area hardly penetrates, and most of this water becomes running water. Calculation of the total area covered by settlement within the basin boundaries along with rainfall data will help in quantifying the total volume of running water. The running water from settled areas is the actual contribution to the Kabul River, which ultimately contributes to the Indus at Attock [
8].
The human-induced change in the activities on the surface of the earth is known as land-use/land-cover (LULC) change. In the past few decades, the rate of LULC change has excessively increased. Regional and global changes in the environment are directly affected by the LULC change. Studying LULC changes is very important to predict and mitigate the various ecological and environmental changes on regional and global levels [
9,
10,
11,
12]. It is useful in various applications like agriculture, forestry, geology, hydrology, etc. The focus in these applications is mainly on issues like loss of cropland, degradation of soil, urban expansion, the variation in the quality of water, etc. Various techniques have been used by the researchers to monitor changes in the natural resources and the urban expansion. These techniques quantitatively analyze the particular distributions of the population of interest [
13].
In order to mitigate the global environmental issues, it is essential to have the most reliable and latest LULC change information [
14]. The LULC changes are commonly detected and mapped using satellite remote sensing and GIS techniques because these techniques employ a reliable geo-referencing methodology, and their digital format is more suitable for computer processing [
15]. The digital change detection methodology, based on the multi-temporal remotely sensed data, can also be used for the detection of the LULC changes. This methodology allows the identification of change between two or more dates [
16]. In a study by Gao and Liu [
17], two Landsat images were digitally analyzed for detecting the land degradation trends in northeast China due to the salinization of soil over a period of 10 years. Various techniques, such as post-classification comparison (PCC), vegetation index differencing, principal components analysis (PCA), etc., have been used in the literature for monitoring the LULC changes. Of these techniques, many studies in the literature have mentioned the PCC technique as a more accurate procedure for representing the nature of the changes by comparing the classifications of images on different dates [
18].
The majority of freshwater research is conducted worldwide to assess and quantify the groundwater resource. The amount of water retained inside aquifers is used to quantify the volume of water. The stored water in aquifers results from more precipitation, low evaporation, and gentile slop that will facilitate the infiltration process, and ultimately, fresh surface water becomes part of the groundwater. The unmanaged and unplanned use of groundwater (GW) by the public as well as private industry, e.g., marble, and lack of adequate infrastructure will cause water scarcity in the region. Rapid population growth causes urbanization and industrialization, which causes the depletion of the GW table worldwide and in the study area. GW is considered a major source of fresh water in the study area (the Peshawar basin). The storage of GW will ultimately affect the daily life of the settled population. The research area is a densely populated and economic hub, and most of the rural population of Khyber Pakhtunkhwa has migrated to Peshawar city [
19,
20].
The shortage of GW occurs during dry periods due to the drawdown of the water table, which increases the pumping cost. In addition, previous studies and electronic media reports indicate that in Khyber Pakhtunkhwa, untreated waste and garbage mix with the Kabul River. Over-pumping, which induces recharging in the Kabul River catchment area’s shallow aquifers, is the main reason for reduced water quality [
19,
21]. Along the Kabul River, the waterlogging problem in Mardan, Charsadda, and sections of the Peshawar district prompted regional groundwater studies in the early 1960s. As a result, the Water and Power Development Authority (WAPDA) launched a detailed investigation to cater to the water logging issue and a hydrogeological investigation to evaluate GW. This study analyzed borehole data of drilled water wells for agriculture and domestic applications. This report is very informative, as it describes different groundwater levels, different water storage volumes, and the per annum recharge of the particular area. Malik [
23] thoroughly examined the groundwater level records for the entire Peshawar valley, including the study area.
GIS plays a significant role in modeling and identification of optimum locations for water garnering or recharging structures. GIS can also be used for hydrological modeling as well as for estimating underground and running water [
24,
25,
26,
27]. Earlier research studies have been carried out by applying GIS and remote sensing to rainwater collection and storage [
28,
29]. Rainwater flows and drains in a specific area via a surface channel after nourishing the surface and sub-surface losses [
30]. Rainwater in arid and semi-arid areas acts as a water source for miscellaneous purposes once the auxiliary sources such as wells, springs, and stream flow water dry up [
28,
31]. The ability of GIS to process large amounts of spatial and attribute data makes it an important tool for hydrological modeling. Certain functions (such as map overlay and analysis) can extract and add hydrological parameters from various sources (such as soil, land-cover, and precipitation data) [
25]. The Digital Elevation Model (DEM) is also one of the tools used for the digital representation of the land surface elevation with respect to any reference datum. The DEM is frequently used to refer to any digital representation of a topographic surface [
32]. In a study by Abdulwahd et al. [
33], analysis of the spatial data and DEM data was conducted using GIS to estimate the hydrological properties for the watershed valley with a 158.5 km
2 surface area. Alcaras et al. [
34] analyzed the possibility of rapidly producing smart maps from remotely sensed image classification. Amano and Iwasaki [
35] used GIS data and SPOT 6/7 satellite images to classify the Kumamoto area into nine categories. A land-cover map was developed using GIS to estimate the groundwater recharge in the Kumamoto area in Japan.
Odekunle et al. [
36] used the GIS technique to examine the impacts of the change in rainfall quantity on the availability of water for maize yield. It was concluded that the maize yield changes with the change in the water availability caused by the variations in the rainfall quantity. A flood hazard map was prepared by Bandi et al. [
37] for the Telangana State, India, and various factors like surface slope and roughness, rainfall variability, density of drainage, soil type, and LULC were discussed in their study. Schumann et al. [
38] presented a hydrological model with feedback components between the flow from surface and the rate of infiltration. Dewan et al. [
39] assessed the flood hazard in Dhaka using the Synthetic Aperture Radar (SAR) data with GIS data. The hydrologic parameters used in their study were the flood frequency and flood depth. Liu et al. [
40] used a diffusive transport approach based on GIS for calculating the rainfall runoff response and routing of floods. The watershed was represented by a grid cell mesh, and for the routing of the runoff from the grid cells to the basin outlet the first passage time response function was used. A sensitivity study was also performed that concluded that the threshold of drainage area is highly dependent on the flood frequency and the channel roughness coefficient. In another study by Kumar et al. [
41], both the SCS-CN and GIS techniques were used to estimate the surface runoff estimation of the Sind River basin. The excessive emission of CO
2 has caused global climatic changes like global warming. The excessive CO
2 should be captured from the point sources and should be converted to useful products or stored for long time period in underground sedimentary reservoirs. GIS is a useful tool for analyzing the CO
2 capture sites and its storage possibilities [
42,
43,
44,
45].
The main objective of the current study is to estimate the total volume of running water by applying GIS in Peshawar basin, which will eventually contribute to the Indus River. In particular, we aim to calculate the area covered by settlements, water bodies, range land, and agriculture area to find the total runoff water volume in the Peshawar basin and finally to estimate the total recharge to the Peshawar basin aquifer.