Masoud Bahreinimotlagh

Context: Underwater acoustic tomography (UAT) is a powerful tool for monitoring oceans, seas and inland waters. Aims: This study presents a scientometric analysis of UAT and examines future research trends. Methods: A comprehensive analysis of 449 Scopus-indexed publications across 135 journals from 1979 to 2023 was conducted to provide an in-depth examination of UAT. Results: More than 760 researchers from 18 countries have contributed to UAT research, resulting in ~40 distinct applications (e.g. four-dimensional (3-D + time) measurement of sound speed, temperature and flow velocity, as well as the localisation of autonomous underwater vehicles). The Journal of the Acoustical Society of America accounts for nearly 30% of these publications. Four major organisations have provided ~80% of the funding for the UAT research, namely, the US Office of Naval Research (31%), the National Natural Science Foundation of China (25%), the Japan Society for the Promotion of Science (13%) and the Russian Foundation for Basic Research (11%). Conclusions: Despite its unique capabilities, UAT technique still faces significant challenges to widespread adoption. Implications: Overcoming obstacles such as mass production, the development of high-frequency systems (exceeding 60 kHz) for laboratory-scale experiments and the creation of user-friendly software is essential for advancing UAT technology.

Given the changing climate, understanding the recent variability in large-scale rainfall patterns is a crucial task in order to better understand the underlying hydrological processes that occur within a watershed. This study aims to investigate how rainfall events in western Japan have changed due to climate change and how these changes have affected runoff–turbidity dynamics during the rainy season. To address the research objectives, we analyzed two decades of precipitation records in the Gōno River watershed and examined the associated runoff–turbidity dynamics during floods using turbidity–discharge (T-Q) loops, quantified using an enhanced hysteresis index. Our findings revealed a kind of intense rainfall event occurring every 3 to 4 years. Additionally, spatial pentad analysis showed varying intensities of accumulated precipitation, indicating that extreme rainfall is not confined to a specific spatial zone. Regarding turbidity–discharge behavior, we found that clockwise hysteresis patterns were caused by sediment sources from near-channel areas, while anticlockwise patterns were caused by soil erosion from nearby areas. Another notable finding was that turbidity peaks during floods may represent the earlier (or later) arrival of turbid water from distant upstream sources due to intense precipitation. One of the key challenges in quantifying hysteresis patterns is that there is no agreed-upon definition for how to determine the start and end of a flood event. This can lead to bias in the quantification of these patterns.

The Volga River, as the primary supplier of the Caspian Sea, plays a huge role in its ecosystem sustainability. In this study, we analyze its runoff predictability for different monthly forecast horizons. Additionally, the meteorological and hydrological variables affecting runoff in each month are identified. A wide range of the potential variables was first collected and the Boruta variable preprocessing method was employed to select the important ones. Then the hybrid models were created by combining the selected variables and the data-driven models [i.e., support vector regression (SVR), artificial neural network (ANN), and multiple linear regression (MLR)]. To postprocess the predicted data, the Bayesian model averaging (BMA) method was employed using the combination of the Boruta–artificial neural network (B-ANN) and the Boruta–support vector regression (B-SVR) models. Finally, the Kling-Gupta efficiency (KGE) and the continuous ranked probability skill score (CRPSS) probabilistic evaluation criteria were applied to evaluate the hybrid models. The results showed that the streamflow of the previous steps is the most crucial variable in predicting the streamflow of all next horizons, while its significance decreases as the forecast time horizon increases. Moreover, the temperature variables have the unlike effect on the streamflow prediction and the minimum temperature for winter and spring and the maximum and the average temperatures for summer and autumn are the most effective ones. Correspondingly, BMA-B-ANN-SVR presents the best performance among the hybrid models (for example, the median of 0.8 and 0.91 for CRPSS and KGE in the first horizon, respectively); the reliability of its predicted runoff for different forecast horizons is much better than other hybrid models (B-ANN and B-SVR).

This study evaluates the vulnerability of aquifers to the nitrate concentration variations. Prediction of nitrate concentration using MT3DMs modeling for a period of 10 years. The results showed that most of the wells have faced concentration increment, where it is exacerbated in the lower areas of agricultural and urban lands. The prediction of nitrate concentration zoning map obtained from the model was used to calibrate the DRASTIC vulnerability index in the aquifer. The AHP and Wilcoxon method was applied to calibrate the parameters of the DRASTIC index. The final results of the vulnerability index showed that the central aquifer parts located downstream of the agricultural lands and urban areas along the main drainage had the highest vulnerability degree. Correlation analysis showed that the correlation coefficient improved from 0.47 to 0.72, and the accuracy of the index was increased to identify the areas susceptible to development where have the least vulnerability.

Fluvial Acoustic Tomography System (FATS) as an advanced technology acquires continuous streamflow data in rivers and estuaries even during floods. However, the acoustic signals are dramatically attenuated by suspending sediments which this problem is a new field of study. In this study, we propose a new equation to estimate the maximum applicable measurement distances (MAMDs). It is based on the cross-sectional suspended sediment concentration () and the particle sizes on the 30-kHz FATS. Our study results show that MAMD might be 2,380 m in the clear water. Moreover, the streamflow monitoring can be perfectly done while is less than 12.67 kg/m3 with the particle radii of 3 μm, when the horizontal distance between two acoustic stations is 100 m. Also, the acoustic signals are not decayed if the particle radii equal to 20 mm and the maximum is 6.6 kg/m3. This study highlights the performance of FATS in the presence of high and provides a better perspective of applying FATS in different rivers with high variability of .

Acoustic Tomography (AT) technique is widely used in developed countries for water resources monitoring of the oceans, seas, and rivers. The 10-kHz Coastal Acoustic Tomography System (CATS) is previously applied to monitor coastal seas in the scale of kilometers. In this study, we evaluated the capability of the 10-kHz CAT ...

Iran has experienced a severe drought during the past two decades. Increasing water demand and decreasing available water resources have led the country to critical conflicts, particularly in shared watersheds. In these basins, the precise measurement of releasing water from upstream to downstream can be a key data for resolving water conflicts. The Iranian Ministry of Energy (MOE) makes the streamflow measurements through regional water administrative offices, mainly using the classical rating curve (RC) method. The documented measurements of runoff by adjacent offices usually present different estimations of the water resources, due to high uncertainties of the RC approach. Fluvial acoustic tomography (FAT) is a reliable technology for continuously monitoring streamflow, which can be implemented to solve this problem of shared basins. In this study, FAT is applied to the Zayanderud basin, an Iranian shared watershed and its results are compared with the RC methods. The main terms of FAT streamflow measurement uncertainty are velocity resolution component, and the selected flow angle between the stream direction and acoustic transmission path. Therefore, a new equation is proposed to carefully choose accurate angles for different river widths to decrease FAT measurement error in this paper. The obtained results show that the measured streamflow by FAT and RC are 9.89 m3/s and 10.3 m3/s, respectively, and the largest possible error of FAT is less than 15%.