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The proper planning of storage structures, waterways, irrigation schemes, water harvesting, erosion control structures, and groundwater development strategies requires accurate estimation of surface runoff. However, hydrologists in Saudi Arabia face serious challenges, specifically due to the rare availability of surface runoff data. In this study, the soil conservation service-curve number (SCS-CN) method integrated with geographic information system (GIS) and remote sensing (RS) was utilized to estimate the surface runoff in Wadi-Uranah basin, in the western region of Saudi Arabia. Different thematic maps such as slope, hydrologic soil group (HSG), land use/land cover (LULC), and daily rainfall have been created in GIS environment and processed to generate the curve number (CN) and surface runoff maps. Based on the soil classification results, the study area was categorized into two HSGs (B and C). The dominant HSG was group C, representing about 98.8% of the total area. The LULC analysis showed four main land use types in the study region: urban, rocks, barren soil, and agricultural areas. Furthermore, the finding results showed that CN values for the normal conditions (CNII) ranged between 74 and 93 in agricultural and both urban and rock areas, respectively. The CNII values were further corrected using slope data to derive slope-adjusted CNII. Moreover, the rainfall-runoff results showed an increase in the daily runoff of the study region with a minimum of 15 mm to a maximum of 74 mm. Another interesting result was rainfall-runoff linear regression analysis that showed a good correlation of 0.98. Additionally, the peak runoff hydrograph flows for 10-, 50-, and 100-year return periods obtained from the SCS-based dimensionless unit hydrograph were 828, 1353, and 1603 m3/s, respectively. Therefore, this study highlights that the SCS-CN method integrated with RS and GIS deserves further attention for estimating runoff of ungauged basins for better basins management and conservation purposes.

The current study is a field experiment set out to comprehend significance of the iron oxide (IO) nanoparticles for use as seed priming agents and their subsequent impact in alleviating water stress and improving agronomic profile of flax plants. The experimental layout consisted of a split-plot factorial design with one main plot divided into two subplots corresponding to drought and well-irrigated environment. Each of the subplots was divided into five rows of the flax plants raised from iron oxide primed seeds. The seed priming concentrations were 0, 25, 50, 75, and 100 ppm. Seed priming increased stem diameter, stem length, height, fresh weights, and dry weights of plant. The yield attributes, such as number of fruit branches, capsules, seeds per capsule, total fresh and dry stem’s fiber production, were also predominantly improved. The levels of malondialdehyde and hydrogen peroxide were found to decline by 66% and 71%, respectively, upon seed priming, and an enhancement in activity of antioxidant enzymes superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) was also observed by 28%, 56%, and 39%, respectively, documenting the potential of iron oxide particles in mitigating the water stress.