Ammar Ashraf

Dams play a pivotal role in water resource management by storing and supplying water for a multitude of purposes. However, the looming threat of dam breach floods necessitates meticulous research and the simulation of potential failure scenarios. These endeavors are essential not only for comprehending the gravity of dam break floods but also for identifying vulnerable regions and informing emergency response strategies and land-use planning initiatives. This study employs a two-dimensional hydraulic model within the HEC-RAS (Hydrologic Engineering Center and River Analysis System) software to conduct an extensive dam breach analysis specifically focusing on the Mangla Dam located in Azad Kashmir, Pakistan. The analysis encompasses the prediction of various breach parameters, including the hydrograph of the breach flood, peak flow rates, arrival times of the flood, and the creation of inundation maps. Of primary concern is the Probable Maximum Floo, which drives the dam collapse model under unsteady flow conditions, accounting for both piping and overtopping failure scenarios. This study discerns the breach outflow hydrograph through the utility of HEC-RAS tools and evaluates hydraulic conditions at critical downstream locations. To dynamically route flood waves, the breach outflow hydrographs are harnessed. Furthermore, the HEC-RAS model is executed with breach parameters derived from five distinct empirical approaches, with ensuing outcomes subjected to rigorous comparative analysis. A comprehensive sensitivity study pertaining to breach parameters is also carried out to ascertain the sensitivity of peak flow and maximum stage. The results reveal peak flow rates of 174,850 m³/s and 177,850 m³/s in the downstream vicinity adjacent to the dam, translating into corresponding flooded areas of 379 km² and 394 km² attributable to piping and overtopping failures, respectively. The analysis of Land Use Land Cover data demonstrates that in the event of piping failure, 217 km² of agricultural land and 56 km² of urban areas would be completely submerged. Conversely, overtopping failure would inundate 220 km² of agricultural land and 59 km² of urban areas. The utilization of advanced remote sensing data, combined with flood modeling insights, equips engineers and stakeholders with invaluable knowledge. This knowledge, in turn, underpins strategic planning and well-informed decision-making processes, essential for addressing the potential global repercussions of similar catastrophes.

The present study aimed to assess the relationship of soil properties in salt-affected soils. The soil samples were collected from 14 districts of Pakistan. Soil salinity and sodicity are the common features of the arid and semiarid regions. The effects of the salt’s interactions with soil micronutrients have not been well studied. Therefore, saline and non-saline soil samples were collected from different locations. The microelements (Fe, Cu, Mn, and Zn) were fractionated into water-soluble, exchangeable, carbonate, Fe + Mn oxide, organic, and residual fractions. Univariate and multivariate analysis (PCA) was carried out to determine the linear relationship between soil properties and micronutrients fractions. Results showed that the magnitude of micronutrients appeared to be affected by the salinity in soils. In saline soil, the Fe fractions differed in the order of residual > organic bound > Fe + Mn bound > carbonate bound > exchangeable > water soluble. Iron fractions varied in the non-saline soils as residual > Fe + Mn bound > organic bound > exchangeable > carbonate bound > water soluble. Copper concentration was higher in the residual and carbonate forms, and the amount was lower in the exchangeable and water-soluble forms under both saline and non-saline conditions. The water-soluble Mn fraction was lower, and the residual Mn fraction was proportionately higher than other forms of Mn in soils. Zinc was found mostly in the residual fraction in both saline and non-saline soils. The mobility factor of micronutrients in non-saline soil was greater than in saline soil. PCA revealed that organic matter (OM) and pH directly affected the fractionation of Cu, Mn, Zn, and Fe in soil. Thus, it could be inferred that salts can bring changes to the composition of micronutrients depending on the nature of the soil and the magnitude of salts.