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To study the accumulation and contamination of heavy metals (i.e., Cd, Cr, Cu, Ni, and Zn) in soil, air, and water, few insect species were assayed as ecological indicators. Study area comes under industrial zone of district Gujrat of Punjab, Pakistan. Insects used as bioindicators included a libellulid dragonfly (Crocothemis servilia), an acridid grasshopper (Oxya hyla hyla), and a nymphalid butterfly (Danaus chrysippus) near industrial zone of Gujrat. Accumulation of Cd was highest in insect species followed by Cu, Cr, Zn, and Ni at p<0.05. Hierarchical cluster analysis (HACA) was carried out to study metal accumulation level in all insects. Correlation and regression analysis confirmed HACA observations and declared concentration of heavy metals above permissible limits. Metal concentrations in insects were significantly higher near industries and nallahs in Gujrat and relatively higher concentrations of metals were found in Orthoptera than Odonata and Lepidoptera. The total metal concentrations in insects were pointed significantly higher at sites S3 (Mid of HalsiNala), S9 (End of HalsiNala), and S1 (Start of HalsiNala), whereas lowest value was detected at site S6 (Kalra Khasa) located far from industrial area. HACA indicates that these insect groups are potential indicators of metal contamination and can be used in biomonitoring.

Portable hydropower turbines are turbines with a scale below 5 kW and which can be carried from one place to another easily by hand due to their light weight. This study was carried out to evaluate the potential of Archimedes Screw Turbine (AST) as an improved portable hydro-power turbine (PHPT) to address shortcomings in available portable turbines. The design of Archimedes screw hydro-power turbine is mainly concerned with screw geometry, which is determined by a variety of internal and external characteristics, including its length, external and internal diameter, Pitch of blades, and Number of the blades, which were 80 cm, 18 cm, 9.53 cm, 18 cm and two number of blades respectively. The turbine was manufactured from stainless steel material according to design parameters and installed in the laboratory. Experimental testing was performed at different discharges (Q) of 0.3, 0.4, 0.5, 0.6, and 0.7 ft 3 /s and at the angle of inclination of 22, 30, 45, and 55° of screw shaft to measure power outputs and overall efficiencies. The maximum overall efficiency obtained was 70% at a flow rate of 0.5 ft 3 /s and at an angle of inclination of 30°. The power output at maximum overall efficiency was 42 watts and hydraulic efficiency was 75.5%. At the flow rate of 0.3 ft 3 /s and an angle of inclination of 55°, the turbine produced a minimum power output of 22.8 watts and an overall efficiency of 39.4%.Experimentation revealed that the flow rate (Q) and inclination of the turbine shaft affect the turbine Power output (P o ) and overall efficiency (η o ). This study helps to manufacture small AST on a large scale, to utilize small flows of water, and to evaluate the possibilities of AST as an appropriate portable hydro-power generation turbine. Further research and experimentation are needed to assess whether 3D printing can be effectively scaled for broader implementation in low-resource areas.

Groundwater supplies approximately half of the total global domestic water demand. It also complements the seasonal and annual variabilities of surface water. Monitoring of groundwater fluctuations is mandatory to envisage the composition of terrestrial water storage. This research provides an overview of traditional techniques and detailed discussion on the modern tools and methods to monitor groundwater fluctuations along with advanced applications. The groundwater monitoring can broadly be classified into three groups. The first one is characterized by the point measurement to measure the groundwater levels using classical instruments and electronic and physical investigation techniques. The second category involves the extensive use of satellite data to ensure robust and cost-effective real-time monitoring to assess the groundwater storage variations. Many satellite data are in use to find groundwater indirectly. However, GRACE satellite data supported with other satellite products, computational tools, GIS techniques, and hydro-climate models have proven the most effective for groundwater resources management. The third category is groundwater numerical modeling, which is a very useful tool to evaluate and project groundwater resources in future. Groundwater numerical modeling also depends upon the point-based groundwater monitoring, so more research to improve point-based detection methods using latest technologies is required, as these still play the baseline role. GRACE and numerical groundwater modeling are suggested to be used conjunctively to assess the groundwater resources more efficiently.

Trash racks are usually composed of an array of bars installed in a hydropower scheme to safeguard the turbines by collecting water-borne detritus. However, current design approaches for the design of trash racks focus on structural criteria. A little attention renders the proper evaluation of hydraulic criteria, which causes a significant hydraulic head loss in low head hydropower schemes with an integral intake. This study investigates the head loss through trash racks by employing computational fluid dynamics (CFD) for several design combinations. A three-dimensional model of trash racks using fractional area/volume obstacle representation (FAVOR) method in FLOW-3D is set up to define the effects of the meshing on the geometry and several simulations are carried out considering various approach velocities and different bar spacings, inclination angles, and blockage ratios. The results indicate that head loss increases with an increase in approach velocity, the inclination angle of the rack with channel bed, and blockage ratio. It is noticed that a clear spacing between vertical bars greater than or equal to 0.075 m has a minimum head loss before it becomes significantly high for lower spacing. In addition, the head loss coefficient increases for screen angles greater than 60°, which can be considered as an optimal parameter for design purpose.

This study, under the context of a global perspective, focuses on the Indus Basin Irrigation System (IBIS) of Pakistan specifically the Jhelum and Chenab rivers inflows. The IBIS operation relies on seasonal planning strategies, informed by forecasts of river inflows at key stations by the Indus River System Authority (IRSA). In this study, Artificial Intelligence (AI) models including Generalized Regression Neural Network (GRNN), and Multi-Layer Feedforward Neural Network (MLFN) along with the statistical model Autoregressive Integrated Moving Average (ARIMA) were used to forecast the inflows of both rivers for 5 years (2020–2024) with a lead time of 1 year. Historic flow data of 59 years (10 daily from 1966 to 2024) were collected from IRSA. The collected data from 1966 to 2014 are used for calibration/training and from 2015 to 2020 are used for validation/testing of selected models for both study locations. The results of correlation and error estimation depicted that Artificial Neural Network (ANN) models predicted better inflows than the ARIMA model. The average RMSE and R 2 of ANN models is 9.68 and 0.92 and the average RMSE and R 2 of ARIMA Model is 10.17 and 0.88, this results in improvement of average RMSE and R 2 by 4.82% and 4.35% in case of ANN Models when compared with ARIMA Model. Qualitative analysis shows that ANN techniques better predicted the high and low flows when compared with statistical methods. Specifically, the application of the ANN models has enhanced the precision of forecasted inflows assessment compared to the probabilistic inflow forecasting methods used by IRSA. The average RMSE and R 2 in case of IRSA forecast is 11.47 and 0.88 and the average RMSE and R 2 in case of ANN Models is 10.30 and 0.92, this results in improvement of average RMSE and R 2 by 10.20% and 4.35% in case of ANN Models when compared with IRSA forecast. This study highlights the need for utilization of ANN models in place of probabilistic inflow forecasting methods to improve the accuracy of time series inflow forecasts.

A spillway is the essential part of the dam body, which releases surplus flows. At higher floods, the spillway operates at high heads, which results in high flow velocities along the chute and may cause negative pressures and cavitation. Therefore, to minimize such issues, aerators are provided along the spillway's chutes. This study aims to analyze the performance of the high-head overflow spillway of Mohmand Dam, Pakistan, having a steep chute of 32° with multiple aerators. Based on Froude's law of similitude, the physical model study was carried out at Irrigation Research Institute, Nandipur, on a scale of 1:60, while FLOW-3D numerical models were used to compare different hydraulic parameters, i.e., flow depth, velocity and pressure. The numerical models were validated with the results of a physical model, which were found in an acceptable range (i.e., 4.93%), and the hydraulic performance of two aerators was evaluated at different discharges. The models indicated negative pressures inside the aerator cavity, which allowed the suction of air to the lower nappe. The maximum air entrainment at the first aerator was about 8.5%. The results also showed that air entrainment to the lower nappe decreased when discharge was increased, whereas the maximum air detrainment reached 11.3% downstream of the second aerator.

Hydraulic jump is used to dissipate excessive flow energy in stilling basins to control erosion on the downstream side. The literature review revealed that the convergence of the side walls in a USBR type II stilling basin has enhanced energy dissipation by stabilizing the hydraulic jump. Taking this into account, a Computational Fluid Dynamics (CFD) model was created using CFD code to analyze the hydraulic efficiency of a USBR type III stilling basin with varying degrees of side wall convergence. Additionally, alterations were made to the standard Impact Blocks geometry to evaluate their effect on energy dissipation. The side walls of stilling basin were converged from 0.5° to 2.5° (with an increment of 0.5°). Study results indicated an increase in hydraulic jump efficiency from 1.6 to 14.5% due to increase in wall convergence. Modified Friction Blocks also enhanced the energy dissipation up to 2%. Post-jump Froude number values were found in acceptable range of 0.6 to 0.78. The optimal hydraulic performance of stilling basin was noted when wall convergence angle of 2.5° was used along with modified Friction Blocks. Hydraulic performance of modified stilling basin may be investigated during gated operation of the model.

Measuring the extent of supraglacial debris cover (SDC) in the Karakoram region has proven to be a difficult task. Semi-automatic methodologies are often used for mapping the SDC area. However, these have limitations which lead to the overestimation or underestimation of glaciated areas. Considering these facts, this study aimed to assess the glacier's extent using a combination of satellite data and ground verification of SDC in the Hunza River Basin, Pakistan. The normalized difference snow index (NDSI) of various satellite images coupled with extensive ground survey was applied to estimate the glacier extent. Results of the glacier extents were in the range of 18–32 km2 for Gulkin, 6–18 km2 for Gulmit, and 6–17 km2 for Pissan glaciers. The ground survey indicated that satellite products are underestimating the extent of glaciers by an average of 18.018%. The comparison of on-site SDC data with Global Land Ice Measurements from Space (GLIMS) and Randolph Glacier Inventory (RGI) databases also indicates a slight variation. Overall results validate that combining satellite imagery with ground verification significantly enhances the accuracy of supraglacial extent assessment.

Dams and reservoirs trap most sediments, and clear water can cause downstream riverbed degradation or aggradation. As a result, the river adjusts its dynamics and channel geometry to regain equilibrium between sediment supply and transport capacity. This study aimed to assess the river regime of the Chenab River in the post-Chiniot Dam Project scenario using a one-dimensional numerical model. After calibration and validation using historic flows and river surveys, simulations were carried out for 5, 10, and 30 years. The sediment model was validated with Brune’s curve, which showed a Nash–Sutcliffe efficiency value of 0.734. The results showed that the river experienced continuous degradation of sediments for the first 16 years and showed a maximum erosion of 8 m at 680 m downstream of the dam. The reach experienced aggradation at 15 km downstream of the dam for the first 10 years and then became stable and showed a maximum deposition of 0.9 m. The ratio of sediments passed through the dam to sediments transported out of reach varied from 0.833 to 0.921, showing that the river reach would continue to attain equilibrium even after 30 years of reservoir operation. The study would be helpful for the prediction of possible future changes in the Chenab River.