Genetic diversity and Agro-climatic conditions contribute significantly to the agronomic and morphological features of the food plant species, and their nutraceutical potential. The present study was intended to evaluate the impact of growing conditions on total phenolic and total flavonoid contents, and in vitro antioxidant potential in the bulbs and leaves of onion varieties planted under diverse environmental conditions. Standard analytical methods were used to quantify total phenolic content (TPC), total flavonoid content (TFC), and free radicals’ scavenging/antioxidant capacity. The impact of climatic and soil conditions was assessed using statistical tools. In general, onion varieties cultivated at three different locations viz. Kalar Kahar, Lahore and Swabi exhibited significant variations in TPC and TFC, and antioxidant activities. The bulbs and leaves of Mustang (V1) variety planted at Lahore and Swabi had significantly (p < 0.05), high levels of TPC (659.5 ± 6.59, and 631.1 ± 8.58 mg GAE/100 g, respectively). However, leaves of Red Orb (V2) and bulbs of Mustang (V1), and Golden Orb (V6), harvested from Kalar Kahar depicted the highest concentration of TFC (432.5 ± 10.3, 303.0 ± 6.67, and 303.0 ± 2.52 mg QE/100 g DW, respectively). Likewise, bulbs of V1 planted at Kalar Kahar, Lahore and Swabi exhibited maximum inhibition of DPPH, ABTS, and H₂O₂ radicals (79.01 ± 1.49, 65.38 ± 0.99, and 59.76 ± 0.90%, respectively). Golden Orb (V6) harvested from Lahore had the highest scavenging of OH radical (67.40 ± 0.09%). Likewise, bulbs of V1 variety planted at KalarKahar and Swabi had significant capacity to scavenge ferric ions (415.1 ± 10.6 mg GAE/100 g DW), and molybdate ions (213.7 ± 0.00 mg AAE/100 g DW). Conversely, leaves of Amazon (V8), planted at Lahore and Swabi depicted significant levels of DPPH, ABTS, H₂O₂ radical scavenging (90.69 ± 0.26, 63.55 ± 1.06, 51.86 ± 0.43%, respectively), and reduction of ferric ions (184.2 ± 6.75 mg GAE/100 g DW). V6 leaves harvested from Lahore and that of Super Sarhad (V3) from Swabi showed the highest inhibition of OH radical (61.21 ± 0.79%), and molybdate ions (623.6 ± 0.12 mg AAE/100 g DW), respectively. Pearson correlation and principal component analysis revealed strong relationships of climatic conditions, soil properties and elevation with TPC, TFC and free radicals’ scavenging potential in the bulbs and leaves of onion varieties. The variations in the total phenolic and flavonoid contents, and antioxidant potential of different varieties, and their associations with climatic and soil factors revealed the complexity of the growing conditions and genetic makeup that imposed significant impacts on the synthesis of secondary metabolites and nutraceutical potential of food and medicinal plant species.

This study proposes a modelling framework of integrated one-dimensional (1D) and two-dimensional (2D) hydrodynamic modelling to evaluate the effectiveness of sponge city construction at community scale. Through a case study in Zhuhai, we integrate Stormwater Management Model (SWMM) and Cellular Automata Dual-DraInagE Simulation (CADDIES) 2D model to analyze the rainfall-runoff process involving green infrastructures. SWMM is applied to analyze the change of surface runoff control effects before and after the implementation of sponge city low impact development (LID) facilities, and CADDIES is adopted to simulate the propagation of excess runoff on the surface. The results show that the LID facilities can effectively reduce the runoff volume of small and medium-sized rainfall events since the maximum runoff reduction rate is 94.4%. For long-term operation, the LID can capture 52.9% of annual rainfall volume and reduce annual runoff by 28.0%. However, the CADDIES 2D model simulations indicate that LID facilities have little effect on flood alleviation in specific regions under extreme rainfall conditions. In addition, we compared the modelling performance using four different terrain Digital Elevation Model (DEM) resolutions and found that 1 m terrain DEM resolution can produce comparable results to 0.25 m DEM with a fraction of computational time. We also find that the MIKE FLOOD model and the integrated model of SWMM and CADDIES 2D can obtain similar simulation results, the p-value = 0.09 which is >0.05, but SWMM-CADDIES integrated model is more suitable for small-scale simulation.

In many parts of the world, including the Hindukush-Karakoram-Himalayan (HKH) region, the population depends on snow and glaciers-melt waters to grow food, generate electricity and store water for their use throughout the year. The annual and seasonal variation in the snow cover area (SCA) due to its response to the climatic variables directly influences the water supplies. The aim of current study is to evaluate the spatio-temporal trends in the annual and seasonal snow cover at basin-wide scale. Impact of topography on the SCA is analyzed by revealing the trends in SCA in different elevation bands. It also investigates the trends in hydro-climatic factors (temperature, precipitation and river flows) in the Chitral River basin (Hindukush region) and their linkage to the SCA variations. Snow cover is estimated using cloud-free 8-day MODIS snow products on 17-year time-period (2000‒2016). Hydro-climatic data of the river flow (1989–2014), temperature, and precipitation (1965–2013) were obtained from Water and Power Development Authority (WAPDA), and Pakistan Meteorological Department (PMD). Trend analysis of the SCA and hydro-climatic variables was carried out using Mann-Kendall’s trend test and Sen’s slope. The results reveal: 1) a significant increasing trend in the SCA at basin-wide scale and at all elevation zones i.e. A to E (1471‒7708 m ASL), except zone B (2500‒3500 m ASL), 2) decreasing and constant trends in the mean temperature and total precipitation, respectively, over the same time-period as SCA indicating possible reasons for increasing SCA, 3) a slight decrease in the mean annual and summer flow (1989–2014) possibly due to the summer cooling, reduced snowmelt and slightly decreasing summer precipitation over this time-period, and 4) strong dependency of the Chitral River flow on snowmelt, driven by the temperature seasonality. Modeling snowmelt runoff under future climate projections in the study area may help to manage the water resources properly.