Traditional irrigation practices, low crop productivity, unlevelled fields, water losses taking place during conveyance and application phases, as well as low irrigation efficiencies are the main problems of the common farmers in Pakistan. These problems are more noticeable in the command area of Lower Chenab Canal (LCC), which is the main portion of the Indus Basin Project in Pakistan. To overcome these problems, different water management technologies such as precision land levelling (PLL), bed planting, drip irrigation systems, and watercourse improvement were introduced to farmers to increase water savings and crop yields in the area of five distributaries—Khurrianwala, Shahkot, Mungi, Khikhi, Killianwala and Dijkot—during the cropping seasons of 2008 to 2015. The use of drip irrigation resulted in savings of water and fertilizer and increased the crop yields by 30–40%. Three watercourses, one on each site of 1200 m in length, were lined, which resulted in improved conveyance efficiency of 15–20%. If wheat, rice and cotton in the command area of LCC are sown on precisely levelled fields and on beds, then about 2768.1 million m³ and 3699.3 million m³ of irrigation water can be saved. These results show the potential of water-efficient technologies for saving water as well as increasing crop yields.

The source region of the Indus River (SRIR), which is located in the Hindukush, Karakoram and Himalayan (HKH) mountainous range and on the Third Pole (TP), is very sensitive to climate change, especially precipitation changes, because of its multifarious orography and fragile ecosystem. Climate changes in the SRIR also have important impacts on social and economic development, as well as on the ecosystems of the downstream irrigation areas in Pakistan. This paper investigates the changes in precipitation characteristics by dividing the daily precipitation rate into different classes, such as light (0–10 mm), moderate (10.1–25 mm) and heavy precipitation (>25 mm). Daily precipitation data from gauging and non-gauging stations from 1961–2015 are used. The results of the analysis of the annual precipitation and rainy day trends show significant (p < 0.05) increases and decreases, respectively, while light and heavy precipitation show significant decreasing and increasing trends, respectively. The analysis of the precipitation characteristics shows that light precipitation has the highest number of rainy days compared to moderate or heavy precipitation. The analysis of the seasonal precipitation trends shows that only 18 stations have significant increasing trends in winter precipitation, while 27 stations have significant increasing trends in summer precipitation. Both short and long droughts exhibit increasing trends, which indicates that the Indus Basin will suffer from water shortages for agriculture. The results of this study could help policymakers cope with floods and droughts and sustain eco-environmental resources in the study area.

Effective wastewater management is a critical environmental challenge, particularly in industrial regions like Faisalabad, where untreated textile effluents contribute to severe water pollution. This study evaluates the potential of phytoremediation using floating aquatic plants—Eichhornia crassipes (water hyacinth), Pistia stratiotes (water lettuce), and Lemna minor (common duckweed)—for the treatment of industrial textile wastewater. A controlled laboratory-scale experiment was conducted to assess pollutant removal efficiency over a 10-day retention period. The initial effluent concentrations of key parameters were measured before treatment to establish baseline conditions. The results demonstrated that Eichhornia crassipes exhibited the highest removal efficiency, achieving reductions of 36.12% (TDS), 36.14% (EC), 36.30% (salinity), 6.12% (pH), 34.30% (total hardness), and 44.52% (chloride). Furthermore, Pistia stratiotes and Lemna minor were particularly effective in removing nitrate (99.76%), ammonium (52.11%), and sodium adsorption ratio (46.29%), indicating species-specific phytoremediation potential. These findings highlight the viability of a low-cost, eco-friendly, and sustainable nature-based solution for wastewater treatment in industrial clusters, offering a practical alternative to conventional treatment technologies.

Groundwater depletion is among the most critical hydrological threats to sustainable agriculture and water security in semi-arid regions. This study presents a high-resolution, multi-sensor assessment of groundwater storage (GWS) dynamics across the Lower Chenab Canal (LCC) command area in Punjab, Pakistan—an intensively irrigated agro-hydrological system within the Indus Basin. We integrated downscaled GRACE/GRACE-FO-derived total water storage anomalies with CHIRPS precipitation, MODIS evapotranspiration (ET) and vegetation indices, TerraClimate soil moisture, land surface temperature (LST), land use/land cover (LULC), and population density using the Google Earth Engine (GEE) platform to reconstruct spatiotemporal GWS changes from 2002 to 2020. The results reveal a persistent and accelerating decline in groundwater levels, averaging 0.52 m yr⁻¹, which intensified to 0.73 m yr⁻¹ after 2014. Cumulative GWS losses exceeded 320 mm yr⁻¹, with severe depletion (up to −3800 mm) in northern districts such as Sheikhupura, Gujranwala, and Narowal. Validation with borewell data (R² = 0.87; NSE = 0.85) confirms the reliability of the remote sensing estimates. Statistical analysis indicates that anthropogenic drivers (population growth, urban expansion, and intensive irrigation) explain over two-thirds of the observed variability (R² = 0.67), whereas precipitation contributes only marginally (R² = 0.28), underscoring the dominance of human-induced stress over climatic variability. The synergistic rise in evapotranspiration, land surface temperature, and cultivation of high-water-demand crops such as rice and sugarcane has further amplified hydrological imbalance. This study establishes an operational framework for integrating satellite and ground-based observations to monitor aquifer stress at basin scale and highlights the urgent need for adaptive, data-driven groundwater governance in the Indus Basin. The approach is transferable to other data-scarce semi-arid regions facing rapid aquifer depletion, aligning with the global targets of Sustainable Development Goal 6 on water sustainability.

Oat is an essential Rabi crop commonly used as green fodder. The nutritional requirements of oats are higher than those of other Rabi fodder crops. Higher doses of inorganic fertilizers are required to meet this demand, which is not economical for fodder production. This study evaluates the best economical dose of integrated nutrient management for attaining higher yield and better nutritional quality of oat. The experiment was conducted on the Agronomy Research Farm, University of Agriculture, Faisalabad, Punjab, Pakistan. The seed varieties used in this experiment were Oat-2011 Sargodha and Oat-F-411 (2021) Faisalabad. The experimental treatments were organized in factorial Randomized Complete Block Design (RCBD) arrangements, with each treatment replicated three times. The results revealed that treatment (T4) 50% RDF + 5 t/ha. Farmyard Manure + seed inoculation azotobacter was found to be the most appropriate than all other treatments.