Muhammad Ali

Global climate change, increasing water demand, and rapid urbanization pose significant threats to groundwater sustainability in arid and semi-arid regions. Globally, approximately four billion people face water scarcity, with many developing countries, including Pakistan, struggling to ensure access to clean water. This study employs a comprehensive approach integrating surface and subsurface geophysical methods (electrical resistivity survey and borehole logs) with GIS-based Multi-Influencing Factor (MIF) analysis and hydrochemical assessment to evaluate groundwater potential and quality in the semi-arid Bannu Basin, Pezu Darra, Lakki Marwat District, northern Pakistan. Within a GIS framework, parameters such as slope, lineament density, drainage density, elevation, distance from rivers, topographic wetness index (TWI), land use/land cover, lithology, and rainfall were incorporated to assess groundwater potential. Additionally, 20 Vertical Electrical Sounding (VES) stations and borehole geophysical logs from two tube wells were analyzed to reveal the subsurface aquifer system and groundwater potential zones. Furthermore, nine water samples were analyzed for ten physicochemical parameters. The results indicate that 3.1% of the study area falls within a very low groundwater potential zone, while 11.83%, 63.81%, and 21.26% correspond to low, moderate, and high potential zones, respectively. In the western part of the study area, high-potential aquifers occur at depths of approximately 170 m, whereas in the eastern part, which represents a very low potential zone, aquifers occur at depths of about 235 m. Hydraulic properties of the layers overlying the aquifer were calculated from VES data to evaluate protective capacity. The longitudinal conductance ranges from 0.5 to 2.9 mhos, and the transverse resistance varies from 13,711 to 101,622 Ω·m², indicating heterogeneous aquifer protection. Overall, the findings demonstrate the effectiveness of integrating geospatial and geophysical techniques with hydrochemical analysis to provide a comprehensive understanding of groundwater potential and quality. These insights are crucial for sustainable water resource management, informed groundwater development, and climate-resilient planning in semi-arid regions.

A healthy ecosystem that supports all living forms depends on water, which is the most magnificent natural resource. Considering the acute global water scarcity, it is critical to investigate rainwater gathering techniques that incorporate practical drought mitigation strategies. In addition to providing a selection of the best sites for natural aquifer recharge, the ultimate objective of this work is to determine where rainwater harvesting structures can be built for efficient and successful rainwater harvesting management in the research region. The current work also focuses on identifying possible locations for natural aquifer recharging utilizing RS and GIS methodologies because the water table is rapidly declining. Land use/land cover, slope, soil, runoff, drainage density, and road limitations were the five criteria used to identify RWH locations using GIS-based MCEs. Using the soil and water assessment tool approach, the observed runoff depth varied from 0 to 900 CMS, and the RWH unit's appropriateness ranged from highly suitable to least suitable. The Panjkora River Basin's total area of 1128.395 km2 is the most suitable for building farm ponds, whereas 954.756 km2 is moderately suitable. The suitable area for check dam building is 350.58 km2, while the moderate area is 245.31 km2. According to the results, 1572.518 km2 are the most suitable areas to build gully plug structures in order to prevent soil erosion and store rainwater, while 3742.38 km2 are of moderate appropriateness. In the current study seven local influencing factors, e.g., land use and land cover (LULC), drainage density, slope, population density, water table, elevation, and soil types, were used to accomplish the objective of natural aquifer recharge sites. More than 72% of the basin has been classified as having moderate to very high potential for artificial recharge. The land area is categorized as highly suitable in 30.19% of cases and very high suitability in 1.01% of situations. In terms of hydrology, this spatial correlation is quite important. Highly or very highly suitable locations for recharge are found in many sections of the moderate and poor groundwater zones. Particularly in areas where traditional groundwater extraction is no longer technically or economically feasible, these interventions would encourage vertical infiltration, lessen runoff, and aid in the restoration of dwindling aquifers. Water managers can implement location-specific, data-driven methods to increase climate resilience and long-term water security in the Panjkora Basin by coordinating recharge planning with natural recharge potential and current groundwater stress.

The Hindukush and Himalaya regions of Pakistan are chronically prone to several geological hazards such as landslides. Studying landslides in these regions is crucial for risk assessment and disaster management, as well as for determining the effects of adverse climatic conditions, infrastructure management, and increasing anthropogenic activities. High-relief mountains in these regions face severe challenges because of frequently occurring landslides and other natural hazards, especially during intensive rainfall seasons and seismic activity, which destroy infrastructure and cause injuries and deaths. Landslides in the Alpuri Valley (Hindukush) and the Neelum Valley (Himalaya) have been activated through high magnitude earthquakes, intensive rainfalls, snowfall, floods, and man-made activities. Landslide susceptibility mapping in these areas is essential for sustainable development as it enables proactive risk management, up-to-date decision-making, and effective responses to landslide hazards, ultimately safeguarding human lives, property, and the environment. In this study, the relative effect method was applied for landslide susceptibility modeling in both study areas to determine the capability to reduce the effects of landslides, and to improve the prediction accuracy of the method. The relative effect is a statistical model that has only been used for very limited time for landslide susceptibility with effective results. A total of 368 (Neelum Valley) and 89 (Alpuri Valley) landslide locations were identified, which were utilized to prepare the reliable landslide inventory using GIS. In order to evaluate the areas at risk for future landslides activities and determine their spatial relationship with landslide occurrences, the landslide inventory was developed with 17 landslide causative factors. These factors include slope gradient, slope aspect, geology, plan curvature, general curvature, profile curvature, elevation, stream power index, drainage density, terrain roughness index, distance from the roads, distance from the streams, distance from fault lines, normalized difference wetness index, land-use/land-cover, rainfall, and normalized difference vegetation index. Finally, the performance of the relative effect method was validated using the success and prediction curve rate. The AUC-validated result of the success rate curve in the Alpuri Valley is 74.75%, and 82.15% in the Neelum Valley, whereas, the AUC-validated result of the prediction rate curve of the model is 87.87% in the Alpuri Valley and 82.73% in the Neelum Valley. These results indicate the reliability of the model to produce a landslide susceptibility map, and apply it to other landslide areas. The model demonstrated a more effective result in the Alpuri Valley, having a smaller area. However, the results are also desirable and favorable in Neelum Valley, with it being a large area. It will assist in general landslide hazard management and mitigation, and further research studies related to future landslide susceptibility assessments in other parts of the region.

In this article, a new lifetime model, referred to as modified Frechet–Rayleigh distribution (MFRD), is developed by accommodating an additional parameter in Rayleigh distribution on the basis of the modified Frechet method. Numerous statistical properties of the suggested model are derived and discussed. The technique of maximum likelihood (ML) estimation is adopted to get estimates of the parameters. The suggested model is very flexible and has the capability to model datasets having both monotonic and nonmonotonic failure rates. The proposed model is applied on two real datasets for checking its performance in comparison with available well-known models. The suggested model has shown outclass performance in comparison with the available versions of the Rayleigh distribution used in the literature.

Groundwater is a precious source of fresh water and a major component of the entire water supply. Both water quality and quantity could be satisfied by evaluating the groundwater potential sites (GWPS). This paper analyzes the ground-water potentials in a semi-arid region of Khyber Pakhtunkhwa, Pakistan. It describes a standard methodology to identify and map GWPS using integrated Geographical Information System (GIS) and remote sensing (RS) methods. Eight parameters including elevation, slope, drainage density, lineaments density, soil, geology, land use/land cover and rainfall were integrated to explore areas with groundwater holding capability. GWPS were delineated through subjective weights assigned after coupling various thematic layers using Saaty’s Analytical Hierarchical Process (AHP). The modelled GWPS were cross-checked with tube wells data. The result indicates that the central part of the study area has good potential for groundwater reserves/exploitation, where the factors i.e. moderate to high drainage density, sedimentary sequence of alluvial plain, low elevation etc. discern the central portion of the study area as a suitable site for groundwater. This study suggests that the applied method proves to be very significant and reliable tool for timely assessment of quality assured evaluation of groundwater resources. This study could be a systematic guide for future investigations for water related explorations, especially in semi-arid environments.