Wadi Flow Simulation Using Tank Model in Muscat, Oman

In Oman, changes in precipitation intensity and frequency have already begun to be detected, although the attributed impacts, such as, flash flooding is poorly understood. For example, the supper cyclonic storm, hurricane Gonu in 2007 led to the worst natural disaster on record in Oman, with total rainfall reached 610 mm near the cost. The cyclone and flash flood caused about $4 billion in damage (2007 USD) and 49 deaths. The objective of this study is to develop a Wadi-flow simulation model to understand precipitation-river discharge relationship in Muscat. A lumped-parameter, non-linear, rainfall-runoff model was used. The Food and Agriculture Organization (FAO-56) modified Hargreaves equation was used for estimating reference evapotranspiration (ET0). Precipitation and temperature data during 1996-2003 were obtained from the Muscat-airport meteorological station. Observed river discharges during 26-30, March 1997 were used to calibrate the model and observations during 1997-2003 were used to verify our simulations. Simulated water discharges agreed with the corresponding observations, with the Nash–Sutcliffe model efficiency coefficient equals to 0.88. This developed model will later be used with a set of General Circulation Model scenarios (GCM) to understand the Wadi-flow variations under changing climate conditions

An Assessment of Temperature and Precipitation Change Projections in Muscat, Oman from Recent Global Climate Model Simulations

Oman is vulnerable to the impacts of climate change, the most significant of which are increased temperature, less and more erratic precipitation, see level rise (SLR) and desertification. The objective of this research is to investigate the potential variation of precipitation and temperature in Muscat, the capital city of Sultanate of Oman in future. We used the MIROC general circulation model (GCM) output (maximum and minimum temperatures and precipitation) from the Representative Concentration Pathways (RCPs) 2.6, 4.5, 6.0 and 8.5 scenarios of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) for assessing changes in climate in the period of 2080-2099 compared to the baseline period of 1986-2005. The spatial mismatch between GCM grid scale and local scale was resolved by applying the LARS stochastic Weather Generator (WG) model. The results obtained for 4 scenarios indicate a significant warming in future, which ranges from 0.93ᴼC (minimum temperature by 1.1ᴼC and maximum temperature by 0.86ᴼC) for the lowest scenario, RCP 2.6, to 3.1ᴼC (minimum temperature by 3.2ᴼC and maximum temperature by 3.0ᴼC) for the highest one, RCP 8.5, relative to baseline level. The differences in the precipitation projections between the scenarios are much greater compared to consistent warming depicted in temperatures. The results reveal  -36.4% and -36.0% decreases in precipitation for the RCP 2.6 and RCP 4.5 scenarios, respectively, while, RCP 6.0 and RCP 8.5 scenarios predict increase in precipitation in a range from 9.6% to 12.5%, respectively during 2080-2099 compared to 1986-2005 period. These results need to be further improved by adopting more GCMs, which will provide potential changes in a consistent

Study of Turbulence in Open Channels Using Two-Equation Models

Prediction of the sediment transport in streams requires an accurate estimation of bed shear stress (for bed load) and eddy viscosity (for suspended load). In general, shallow water models employ empirical relationships to estimate the bottom shear stress. However, with the advancement of computing systems, the utilization of advanced turbulence models is getting common. In this paper, a number of model versions are reviewed based on their predictive abilities against the well-known bottom boundary layer properties in open channels and computational economy. Qualitative and quantitative comparisons have been made to infer that the choice of model versions should be based on the field application. For example, the bottom shear stress is very well predicted by the k-? model whereas the cross-stream velocity profile and turbulent kinetic energy are predicted more efficiently by k-? model versions. This study may be useful for researchers and practicing engineers in selecting a suitable two-equation model for calculating various bottom boundary layer properties

Numerical Simulation of Climate Change Impacts on the Coast of Oman

It is well known that there is an apparent increase in the intensity and frequency of extreme weather events, such as tropical cyclones (IPCC, 2023). This will lead to a significant effect not just on the infrastructure and the economic activities but also on the coastal environments. On the other hand, an increase in the population along the coastal areas in such a country as the Sultanate of Oman will also increase the risk and the hazard. It has been noticed extremely heavy rainfall during the most recent tropical cyclone, Shaheen (October 3 2021). It is also recorded along the Omani coast's extremely high waves during this storm event. Some other tropical cyclones in the past also indicated an essential effect on the Omani coast (Shawky et al., 2021). In this regard, the development of a fundamental understanding of the hydrodynamic behaviour along the coastal system during these events has been necessary. Moreover, the tropical cyclone track and wind speeds have been recorded only for a few temporal spans. This leads to better reliable estimations of such a kind of event. The state-of-the-art process-based numerical model will be utilized to hind cast the hydrodynamic developments from several tropical cyclone events along the Omani coast. A well-calibrated and validated flow model has been set up using Deft3D, a world leader's software (Lesser et al., 2004). Furthermore, the impact of wind-induced waves has been investigated using the SWAN wave model (Booij et al., 1999; Ris et al., 1999). In this paper, four well-known tropical cyclones in the Indian Ocean will be simulated. The four tropical cyclones were selected due to their historical significance and the amount of destruction they caused on the Omani coast. The investigation results showed significant tropical cyclones' effects on the Omani coasts due to their intensity and the cyclones' pattern. Overall, the numerical models that are showing good descriptions of climate change can be valuable tools for comprehending and predicting the influences of climate change on the Omani coast and can be employed to support in the decision-making

A Multi-Criteria Decision-Making Approach for Selection of Wave Energy Converter Optimal Site

Ocean wave energy is an essential source of renewable power for coastal communities. Choosing the optimal site for the wave energy converter (WEC) deployment depends on a number of criteria. The characteristics of the WEC must be taken into account in the prediction power supply, whereas the local sea state is connected to elements like wave condition (as a representation of construction budget) and energy output as well as the influence of the exploitable storage of wave energy and its trend. As a result, this research provides a multi-criteria decision-making (MCDM) strategy for considering several factors simultaneously to choose the best possible site. The suggested MCDM technique incorporates two primary factors, i.e., exploitable storage of wave energy and energy production, into a single metric that takes into account both WEC efficiency of a particular type, WEPTOS, and sea state to aid decision-makers in the development of a pilot project. The method was then used to analyse the waves at two locations that had been identified as promising sites for harvesting wave energy along the coast of Oman. To further assess a site's potential upcoming pilot project and select the most efficient WEC, we compared the MCDM results at the stations with certain WEC types. In conclusion, optimal sites for placement of the WEPTOS WEC along the coast of Oman were identified considering the highest annual energy production and exploitable energy storage. Through solving the MCDM technique, 17 sites were pinpointed, and only 6 points were picked up

Flash flood modelling in Oman Wadis

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Satellite-Based Water and Energy Balance Model for the Arid Region to Determine Evapotranspiration: Development and Application

Actual evapotranspiration (ETa) plays an important role in irrigation planning and supervision. Traditionally, the estimation of ETa was approximated using different in situ techniques, having high initial and maintenance costs with low spatial resolution. In this context, satellite imagery models play an effective role in water management practices by estimating ETa in small and large-scale areas. All existing models have been widely used for the estimation of ETa around the globe, but there is no definite conclusion on which approach is best for the hot and hyper-arid region of Oman. Our study introduces an innovative approach that uses in situ, meteorological, and satellite imagery (Landsat-OLI/TIRS) datasets to estimate ETa. The satellite-based water and energy balance model for the arid region to determine evapotranspiration (SMARET) was developed under the hot and hyper-arid region conditions of Oman by incorporating soil temperature in the sensible heat flux. The performance of SMARET ran through accuracy assessment against in situ measurements via sap flow sensors and lysimeters. The SMARET was also evaluated against three existing models, including the surface energy balance algorithm for land (SEBAL), mapping evapotranspiration at high-resolution with internalized calibration (METRIC), and the Penman–Monteith (PM) model. The study resulted in a significant correlation between SMARET (R2 = 0.73), as well as the PM model (R2 = 0.72), and the ETa values calculated from Lysimeter. The SMARET model also showed a significant correlation (R2 = 0.66) with the ETa values recorded using the sap flow meter. The strong relationship between SMARET, sap flow measurement, and lysimeter observation suggests that SMARET has application capability in hot and hyper-arid regions

A Multi-Objective Optimal Allocation of Treated Wastewater in Urban Areas Using Leader-Follower Game

This study proposes a new method for optimal allocation of Treated Wastewater (TW), in which different stakeholders, their social position in decision-making, and priority of objectives were attended using the leader-follower game theory. The suggested methodology was applied in a case study in the eastern part of Tehran province in Iran, where the Water and Sewage Department is considered the leader and four TW dependent districts are the followers in the game model. The leader appropriates a certain TW quantity to the system, and the followers compete for the allocated resources in the face of various physical and sociopolitical constraints. The Nash-Harsanyi production function was applied to model the non-cooperative relationships among the followers (i.e., their competition for limited resources) and find a compromise solution. Considering different limitations, such as the location and quantity of the TW allocation, 1569 different allocation scenarios were considered in four districts. Then, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based multi-objective optimization model was developed to optimize the main objectives of the leader, including i) minimizing the TW transfer costs, and ii) minimizing the supplied demand deficiency in all districts. A multi-criteria decision-making model was utilized to find the best solution on the achieved Pareto-front space. Nine different weighting scenarios were adopted to assess the model sensitivity to the importance of the selected criteria. Results point to the sensitivity of the framework to weighting scenarios, but provide effective compromise solutions to a complex system that can only partially supply water demands

Pressure Sensor Placement in Water Distribution Networks for Leak Detection Using a Hybrid Information-Entropy Approach

This study proposes an optimization framework based on a hybrid information-entropy approach to identify leakage events in water distribution networks (WDN). Optimization-based methods are widely employed in the literature for such purposes; however, they are constrained by time-consuming procedures. Hence, researchers eliminate parts of the decision space to curtail the computational burden. Here, we propose an information theory-based approach, using Value of Information (VOI) and Transinformation Entropy (TE) methods, in conjunction with an optimization model to explore the entire decision space. VOI allows for the entire feasible space search through intelligent sampling, which in turn ensures robust solutions. TE minimizes redundant information and helps maximize the spatial distribution of sensors. The herein proposed model is developed within a multi-objective optimization framework that renders a set of Pareto-optimal solutions. ELimination and Choice Expressing the REality (ELECTRE) multi-criteria decision-making model is then used to select the best compromise solution given several weighting scenarios. The results of this study show that the information-entropy based scheme can improve the precision of leak detection by enhancing the decision space, and can reduce the computational burden