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Coastal zones are highly dynamic and constantly influenced by geomorphological and physical properties. Thus, estimating coastal vulnerability around the world is necessary for coastal zone management. Makran region, in the southeast of Iran, with a 133 km coastline, is considered a case study for vulnerability analysis and estimating its potential for further economic developments. The coastal vulnerability index (CVI) was considered with five parameters: geomorphology, regional elevation, coastal slope, shoreline changes and mean significant wave height. Significant wave height is an additional variable we added to CVI estimation compared to previous works. MIKE 21 software was used to extract this variable. Seven images from the Landsat satellite were employed to provide shoreline transformation. According to our results 52% of the coastline is ranked as high-vulnerability index, and 15% as very-high vulnerability index. We detected some anthropogenic areas with considerable accretion along the shoreline, while these areas were not considered vulnerable areas according to CVI. Thus, we reckon a sort of shortcoming in calculating CVI for not giving weight to the variables involved. This aim to be achieved necessitates organized historical research over the area, which was out of the scope of this sole research. Research highlights: Inclusive employment of geomorphic and hydrodynamic parameters is suggested for calculating CVI. However, a shortcoming in this calculation is the lack of information to give weight to the variables involved. More than half of Makran shoreline (67%) is ranked as high to very high-vulnerable area, which means specific concern is needed for any further anthropogenic activities around this area. Accretion can be counted as an issue on CZM, specifically on the area with anthropogenic activities, such as ports. [ABSTRACT FROM AUTHOR]

Understanding the effects of extreme floods on critical infrastructures such as bridges is paramount for ensuring safety and resilient design in the face of climate change and extreme events. This study develops robust computational and predictive modeling tools for assessing the impacts of extreme floods on the hydraulic response and structural resilience of bridges. A computational fluid dynamic (CFD) model utilizing RANS equations and k-ω Shear Stress Transport (SST) for simulating supercritical flows is adopted to compute hydrodynamic pressures and the water levels on bridge piers of cylindrical and rectangular shapes during a flood event. The CFD model is validated based on the case study data obtained from the Haj Omran Bridge, built on the Khorramabad River in Iran. The numerical simulations consider hydrological conditions and exclude geotechnical parameters and abutment damages. The numerical results are evaluated based on well-established design guidelines. Machine learning techniques, including Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Regression (SVR), optimized with Grid Search Cross-Validation (GSCV), are adopted to enhance the accuracy of hydrodynamic pressure forecasting at bridge piers. The XGBoost model exhibits superior performance (R2 = 0.908, RMSE = 0.0279, and E = 3.41%) compared to the RF and SVR models. All the estimated pressure data by XGBoost falls within ±6 percent error lines, highlighting the model's robustness for out-of-range hydrodynamic pressure prediction. Additionally, an optimized Long Short-Term Memory (LSTM) model is adopted to effectively predict free surface flow profiles (i.e. flood depth) over the bridge (R2 = 0.937 and RMSE = 0.083), demonstrating its potential for practical applications of flood depth predictions over bridge infrastructures. The proposed methodological framework outlined in this study can facilitate modeling the impacts of extreme floods on bridges, enabling robust climate resilience assessment of critical infrastructures. [Display omitted] • Impacts of extreme flood on bridges are investigated. • Optimized LSTM robustly predicts water surface profiles over bridges. • XGBoost outperform RF and SVR in forecasting hydrodynamic pressure at piers. • Performance of design codes in estimating hydrodynamic pressure on piers is compared. [ABSTRACT FROM AUTHOR]

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• Andarokh-Kardeh region provides dominant part of Mashhad city potable water. • Rock weathering and ion exchange dominantly controls water resources quality. • Depleted δ18O and δ2H were observed in KR and groundwater, and enriched values in KDR. • δ13C and DIC demonstrate dominant role of carbonate mineral dissolution. • Hydrogeological model demonstrates various conditions in dry and wet periods. Andarokh-Kardeh region is located northeast of Iran and provides notable part of potable water of Mashhad, the second most populated city of Iran with over 3 million inhabitants. Stable isotopes (18O, 2H and 13C), hydrodynamic, and hydrochemical indicators have been applied to evaluate water resources quality comprehensively and to present a hydrogeological conceptual model for the Andarokh-Kardeh region. Hydrochemical studies indicate that chemical rock weathering and ion exchange are the main factors controlling the quality of water in the region, while atmospheric (precipitation) as well as anthropogenic sources have no notable effect. Stable isotopes (18O and 2H) studies in surface and groundwater samples demonstrate enriched values in Kardeh Dam Reservoir (KDR) due to evaporation and also demonstrate that the interaction between KDR and downstream groundwater resources is negligible. The δ13C isotope and DIC and DOC concentrations indicate role of carbonate mineral dissolution from Mozdooran Formation, atmospheric and soil CO 2 and also the domination of C3 vegetation coverage in the study region. The developed conceptual model for Andarokh-Kardeh demonstrates different hydrogeological conditions during wet and dry periods, and highlights the main process which affect hydrogeology of the region. Water quality studies and the developed conceptual model demonstrate the main factors controlling water quality and the main hydrogeological characteristic of Andarokh-Kardeh region which can be used by water resources scientists for the future water management programmes. [ABSTRACT FROM AUTHOR]