To assess Mars’ potential for both harboring life and providing useable resources for future human exploration, it is of paramount importance to comprehend the water situation on the planet. Therefore, studies have been conducted to determine any evidence of past or present water existence on Mars. While the presence of abundant water on Mars very early in its history is widely accepted, on its modern form, only a fraction of this water can be found, as either ice or locked into the structure of Mars’ plentiful water-rich materials. Water on the planet is evaluated through various evidence such as rocks and minerals, Martian achondrites, low volume transient briny outflows (e.g., dune flows, reactivated gullies, slope streaks, etc.), diurnal shallow soil moisture (e.g., measurements by Curiosity and Phoenix Lander), geomorphic representation (possibly from lakes and river valleys), and groundwater, along with further evidence obtained by probe and rover discoveries. One of the most significant lines of evidence is for an ancient streambed in Gale Crater, implying ancient amounts of “vigorous” water on Mars. Long ago, hospitable conditions for microbial life existed on the surface of Mars, as it was likely periodically wet. However, its current dry surface makes it almost impossible as an appropriate environment for living organisms; therefore, scientists have recognized the planet’s subsurface environments as the best potential locations for exploring life on Mars. As a result, modern research has aimed towards discovering underground water, leading to the discovery of a large amount of underground ice in 2016 by NASA, and a subglacial lake in 2018 by Italian scientists. Nevertheless, the presence of life in Mars’ history is still an open question. In this unifying context, the current review summarizes results from a wide variety of studies and reports related to the history of water on Mars, as well as any related discussions on the possibility of living organism existence on the planet.

The total phosphorus (TP) concentration, as the primary limiting eutrophication factor in the Mahabad Dam reservoir in Iran, was studied, considering the combined impacts of climate change, as well as the scenarios on changes in upstream TP loadings and downstream dam water allocations. Downscaled daily projected climate data were obtained from the Beijing Normal University Earth System Model (BNU-ESM) under moderate (RCP4.5) and extreme (RCP8.5) scenarios. These data were used as inputs of a calibrated Soil and Water Assessment Tool (SWAT) model of the watershed in order to determine the effects of climate change on runoff yields in the watershed from 2020 to 2050. The SWAT model was calibrated/validated using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). Moreover, to model TP concentration in the reservoir and to investigate the effects of upstream/downstream scenarios, along with forecasted climate-induced changes in streamflow and evaporation rates, the System Dynamics (SD) model was implemented. The scenarios covered a combination of changes in population, agricultural and livestock farming activities, industrialization, water conservation, and pollution control. Relative to the year 2011 in which the water quality data were available, the SD results showed the highest TP concentrations in the reservoir under scenarios in which the inflow to the reservoir had decreased, while the upstream TP loadings and downstream dam water allocations had increased (+29.9%). On the other hand, the lowest TP concentration was observed under scenarios in which upstream TP loadings and dam water allocations had decreased (−18.5%).

This study investigates the impact of different digital elevation model (DEM) resolutions on the topological attributes and simulated runoff, as well as the sensitivity of runoff parameters in the Mahabad Dam watershed in Iran. The watershed and streamlines were delineated in ArcGIS, and the hydrologic analyses were performed using the Soil and Water Assessment Tool (SWAT). The sensitivity analysis on runoff parameters was performed, using the Sequential Uncertainties FItting Ver. 2 algorithm, in the SWAT Calibration and Uncertainty Procedures (SWAT-CUP) program. The results indicated that the sensitivity of runoff parameters, watershed surface area, and elevations changed under different DEM resolutions. As the distribution of slopes changed using different DEMs, surface parameters were most affected. Furthermore, higher amounts of runoff were generated when DEMs with finer resolutions were implemented. In comparison with the observed value of 8 m³/s at the watershed outlet, the 12.5 m DEM showed more realistic results (6.77 m³/s). Comparatively, the 12.5 m DEM generated 0.74% and 2.73% more runoff compared with the 30 and 90 m DEMs, respectively. The findings of this study indicate that in order to reduce computation time, researchers may use DEMs with coarser resolutions at the expense of minor decreases in accuracy.

Best Management Practices (BMPs) are commonly used to control pollution in the river basins. Prioritization of BMPs helps improve the efficiency and effectiveness of pollution reduction, especially in Critical Source Areas (CSAs) that produce the highest pollution loads. Recently, the Dez River in Khuzestan, Iran, has become highly eutrophic from the overuse of fertilizers and pesticides. In this basin, dry and irrigated farming produce 77.34% and 6.3% of the Total Nitrogen (TN) load, and 83.56% and 4.3% of the Total Phosphorus (TP) load, respectively. In addition, residential, pasture, and forest land uses together account for 16.36% of the TN and 12.14% of the TP load in this area. The Soil and Water Assessment Tool (SWAT) was implemented to model the Dez River basin and evaluate the applicability of several BMPs, including point source elimination, filter strips, livestock grazing, and river channel management, in reducing the entry of pollution loads to the river. Sensitivity analysis and calibration/validation of the model was performed using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). The CSAs were identified using individual (sediment, TN, TP) and combined indices, based on the amount of pollution produced. Among the BMPs implemented, the 10 m filter strip was most effective in reducing TN load (42.61%), and TP load (39.57%).

Scour is defined as the erosive action of flowing water, as well as the excavating and carrying away materials from beds and banks of streams, and from the vicinity of bridge foundations, which is one of the main causes of river bridge failures. In the present study, implementing a numerical approach, and using the FLOW-3D model that works based on the finite volume method (FVM), the applicability of using sacrificial piles in different configurations in front of a bridge pier as countermeasures against scouring is investigated. In this regard, the numerical model was calibrated based on an experimental study on scouring around an unprotected circular river bridge pier. In simulations, the bridge pier and sacrificial piles were circular, and the riverbed was sandy. In all scenarios, the flow rate was constant and equal to 45 L/s. Furthermore, one to five sacrificial piles were placed in front of the pier in different locations for each scenario. Implementation of the sacrificial piles proved to be effective in substantially reducing the scour depths. The results showed that although scouring occurred in the entire area around the pier, the maximum and minimum scour depths were observed on the sides (using three sacrificial piles located upstream, at three and five times the pier diameter) and in the back (using five sacrificial piles located upstream, at four, six, and eight times the pier diameter) of the pier. Moreover, among scenarios where single piles were installed in front of the pier, installing them at a distance of five times the pier diameter was more effective in reducing scour depths. For other scenarios, in which three piles and five piles were installed, distances of six and four times the pier diameter for the three piles scenario, and four, six, and eight times the pier diameter for the five piles scenario were most effective.

Golestan Province is one of the most vulnerable areas to catastrophic flood events in Iran. The flood severity in this region has grown dramatically during the last decades, demanding a major investigation. Accordingly, an authentic map providing detailed information on floods is required to reduce future flood disasters. Three ensemble models produced by the combination of Evaluation Based on Distance from Average Solution (EDAS) and Multilayer Perceptron Neural Network (MLP) with Frequency Ratio (FR), and Weights of Evidence (WOE) are used to quantify the map flood susceptibility in Golestan Province, in the north of Iran. Ten flood effective criteria, namely altitude, slope degree, slope aspect, plan curvature, distance from rivers, Topographic Wetness Index (TWI), rainfall, soil type, geology, and land use, are considered for the modeling process. The flood zonation maps are validated by the receiver operating curve (ROC). The results show that the most precise model is MLP-FR (AUROC = 0.912), followed by EDAS-FR-AHP (AUROC = 0.875), and EDAS-WOE-AHP (AUROC = 0.845). The high accuracies of all methods applied to illustrate their capability in predicting flood susceptibility in future studies.