Identifying homogeneous precipitation zones is essential for regional water resource management and climate zone adaptation. However, previous studies have been limited by relatively short temporal datasets and/or adopting inconsistent clustering approaches. This study develops a statistical modeling framework that integrates Principal Component Analysis (PCA) with unsupervised clustering algorithms to distinguish precipitation regimes across Iran. Using a 40-year precipitation dataset (1980–2020) from 93 synoptic stations, the model incorporates both monthly and seasonal temporal scales. PCA was used for dimensionality reduction, capturing 87.8
This study investigates the changes in scouring depth and location at the outlet of a culvert under various flow conditions, using numerical simulation to model flow and sediment interactions. Ansys Fluent was employed in this study to simulate various flow rates, inlet blockages (0% and 40%), and sediment sizes (0.85 mm and 2 mm). The numerical results were validated by comparing them with experimental data and numerical simulations from Flow-3D, utilizing two turbulence models, Renormalization Group (RNG) and k-epsilon. The findings indicate that the RNG model more closely matched observational data, particularly under the 40% blockage condition, while both models agreed well under the 0% blockage condition. Increased flow rates and higher inlet blockage led to greater scour depths. In the 40% blockage condition, the maximum scour depth in the RNG model was 200% and 150% greater than the Fluent model, respectively. Additionally, the study found a 30% increase in maximum scour depth when sediment particle size increased from 0.85 mm to 2 mm. This research highlights the importance of selecting the appropriate turbulence model for accurate scour predictions and offers valuable insights that can inform the design and maintenance of culverts and related infrastructure.
Soil moisture plays a crucial role in agriculture, hydrology, and erosion control, especially in semi-arid regions. Direct measurement of soil moisture is costly and time-consuming, prompting the use of pedotransfer functions (PTFs) for predicting field capacity (FC) and permanent wilting point (PWP). This study aimed to advance new PTFs, which are models used to estimate soil moisture properties from easily measured soil data, for predicting FC and PWP soil properties and remote sensing data coupled with regression. 100 soil samples from four land uses were analysed for bulk density (BD), texture, organic matter (OM), and calcium carbonate (CaCO3). A GIS was used to extract five spectral indices from Landsat 8 satellite data to improve model predictions. Three scenarios were tested using soil properties (Scenario I), using spectral indices (Scenario II), and combining both soil properties and spectral indices (Scenario III). Strong correlations were found between %clay and FC (r = 0.57) and PWP (r = 0.62), while BD negatively correlated with FC (r =-0.66) and PWP (r =-0.54). FC and PWP were also significantly correlated with SAVI (r = 0.46) and NDVI (r = 0.45). Scenario III, integrating soil properties and spectral indices, yielded the most accurate predictions, with R2 of 0.85 for FC and 0.77 for PWP, compared to Scenario I (R2 of 0.82 for FC and 0.70 for PWP) and Scenario II(R2 of 0.54 for FC and 0.63 for PWP). This combined approach enhances soil moisture prediction, aiding sustainable agriculture and land-use planning in semi-arid regions.
A shoreline management plan (SMP) implies thematic actions to conserve natural resources and sustainable development. The research aimed to achieve optimized spatial zoning of the SMP along the Bushehr Province, Persian Gulf, Iran. The research method includes computing sea flood level combining elevations of the high astronomic tide (HAT), the storm set-up, the wave set-up, and the climate change-induced sea-level rise, and the depth of closure (DoC) to set upper and lower boundaries of SMP spatial zoning. The SMP longitudinal limits divide based on sedimentary cells, sub-cells, and shore sections considering governing littoral drifts, the possibility of sediment bypassing, and natural and artificial trap restrictions. Results imply spatial zoning of a 2,854,250-ha area of the Boushehr coastal watersheds, including three sedimentary cells, 16 sub-cells, and 36 shore sections. The maximum and minimum sea flood levels (100-year return period) as the hazard line for precaution and management considerations in the northern Persian Gulf vary between 4.25 m and 3.11 m, introduced sea flood zones of 80,379.38 ha and 61,013.25 ha spatially in sediment cell-1 and sediment cell-2. Seaside the SMP management units introduced to DoC of 48,280.51 ha, 67,190.17 ha, and 442 ha in sediment cell-1, sediment cell-2, and sediment cell-3, which vary depths between 5.27 m and 3.03 m. The research method is a guideline for sea-oriented development, especially for coastal watershed management, optimal placement of prosperity and population loading, and prevention of environmental hazards.
The Karun River, the longest and highest water flow river in Iran, has experienced heavy and trace metal pollution in recent years. While previous studies have evaluated the water quality of the river, not all sections from north to south have been examined for all metals. To address this gap, a study was conducted between March and June 2022 to evaluate the concentration of 15 heavy and rare metals in the river. Geoaccumulation index (Igeo), Potential Ecological Risk (RI), Enrichment Factor (EF), and the Contamination Factor (CF) were used to assess water quality. The results showed that despite some metals exceeding the Iranian standard, all metals had negative Igeo values, indicating an uncontaminated condition. The contamination levels of all metals were low, with a CF value less than one, and RI values were generally below 0.01, except for vanadium and mercury. The Karun River was categorized as moderate and significant enrichment for all metals except for aluminum, lead, and cobalt, with chromium and copper having particularly high EF values at some stations. Zinc, manganese, nickel, arsenic, molybdenum, and cadmium were also in the moderate enrichment category, while antimony, vanadium, and mercury were in the very high and extremely high enrichment categories, respectively. The study concludes that the concentrations of metals in the Karun River are within permissible limits, indicating low risk of metal pollution. However, continuous monitoring is necessary to maintain the permissible limits and identify potential sources of metal pollution in the future to prevent contamination of these essential water resources.
