Acta Geophysica

The Zambezi watershed is essential for water supply, irrigation, fishing activities, and river transport of the populations of Southern Africa. The importance and variability of these water resources make it necessary to develop studies that may help understand and manage them. Despite this need, water resources studies for this region are still scarce. Therefore, the present work aims to present a strategy for forecasting the daily water flow of the Zambezi River in the Cahora Bassa dam, located in Mozambique, an important energy producer in the country and the fourth largest dam in Africa. Historical rainfall, evaporation, and humidity records collected from 2003 to 2011 are used for training and testing a model that forecasts water flow using the Group Method of Data Handling algorithm. The results achieved were compared, through error metrics, with those of other models to prove the effectiveness of the assembled model. They revealed that the proposed model achieves a satisfactory performance for the forecast horizon and could become a helpful tool in monitoring hydrographic basins and forecasting their daily streamflow values.

In recent years, seismic time series has been used to construct complex network models in order to describe the seismic complexity. The effect of the factor focal depth has been elided in some of these models. In this paper, we aim to construct a new complex network model for seismicity by considering depth factor from the earthquake catalog and investigate the statistical properties of the network. Since the networks have been proved to be scale-free and small-world properties, the new network models should be studied whether the properties have changed. The results show that the new network model by considering depth factor is still scale-free and small-world. However, it is found that its average degree is smaller than the original network. The clustering coefficient increases at the year including mainshocks. The assortativity coefficient, which demonstrates preferential attachment of nodes, is positive and shows consistent pattern when main shocks occur.

Malkara coals are located in the Oligocene-aged Danişmen Formation in the Thrace Tertiary coal basin. The Danişmen Formation consists of limestone, sandstone, tuffite, siltstone, claystone and intercalated coal. Elemental and specific natural radionuclide concentrations of lignites collected from Tekirdağ–Malkara coalfield were determined, and the associated radiological risk was assessed. In order to examine the depth-dependent radionuclide concentration changes, samples were taken from top, middle and bottom parts of the boreholes. Gamma spectrometric measurements of radionuclide activities were performed with HPGe detector. The calculated mean 226Ra, 232Th and 40K concentrations were 27.0 ± 3.57, 18.9 ± 3.28 and 155 ± 36.1 Bq kg−1, and the measured U, Th, Pb and K concentrations were 4.04, 6.27, 10.6 ppm and 0.82%, respectively. Findings were comparable with the reported literature for Turkey and other countries from the world. The dose due to the radionuclide content of lignites was not very high to pose a serious health risk.

Soil erosion and its impact on the land and surface water resources are posing both ecological and socioeconomic threats around the world. In South India, tank systems are quite ancient, supporting rural livelihood including their agricultural needs. But, in recent decades they have lost their significance. The aggravated catchment erosion and resultant siltation have significantly reduced their storage capacity and thereby their functionality. Ambuliyar sub-basin, encompassing 809 irrigation tanks, has once satisfied multifunctional needs of people but now becomes degraded due to siltation. Though desilting of tanks and feeder channels is practiced, the tanks often get silted owing to aggravate soil erosion. Hence, to sustain their life span, it is essential to minimize the erosion in the catchment. Thus, the present study intends to estimate the rate of erosion, analyze their spatial variation through a time series analysis, and ascertain the causative factor. Accordingly, the annual soil loss estimated using Revised Universal Soil Loss Equation method has shown an increase in the rate of erosion from 4084.40 (1996) to 4922.47 t ha−1 y−1 (2016). However, spatially, a non-uniform pattern is inferred, and hence based on the variations, the sub-basin is divided into five zones. In zones I, II, and V, there is an increase in erosion, and in zones III and IV, a decrease is witnessed. Variations studied in conjunction with RUSLE parameters reveal that the improper land use practice has modified the erosion rate and pattern. Further, it is presumed that the silted watercourses might have increased the overland flow, which in turn increased the erosion. Remedial measures such as afforestation, promotion of coconut plantation, and reduction in overland flow by desilting tanks are suggested; thereby, the surface and groundwater resources will be enhanced and in turn the agricultural productivity.

EULAG is a computational model for simulating flows across a wide range of scales and physical scenarios. A standard option employs an anelastic approximation to capture nonhydrostatic effects and simultaneously filter sound waves from the solution. In this study, we examine a localized gravity wave packet generated by instabilities in Held-Suarez climates. Although still simplified versus the Earth’s atmosphere, a rich set of planetary wave instabilities and ensuing radiated gravity waves can arise. Wave packets are observed that have lifetimes ≤ 2 days, are negligibly impacted by Coriolis force, and do not show the rotational effects of differential jet advection typical of inertia-gravity waves. Linear modal analysis shows that wavelength, period, and phase speed fit the dispersion equation to within a mean difference of ∼ 4%, suggesting an excellent fit. However, the group velocities match poorly even though a propagation of uncertainty analysis indicates that they should be predicted as well as the phase velocities. Theoretical arguments suggest the discrepancy is due to nonlinearity — a strong southerly flow leads to a critical surface forming to the southwest of the wave packet that prevents the expected propagation.

Seepage control is critically essential for dams, slopes, and the stability of many engineering structures, developing over many years using different methods. This study presents a novel approach for seepage control using the photopolymerization technique to form an impermeable crust at the soil surface. Effects of exposure duration (5, 10, 15, and 30 min) and light intensities (140, 550, 710, and 1000 W/m2) on the seepage control effectiveness of four different sand soils were investigated by using the photopolymerization technique. The three-point bending, permeability and acid rain simulation tests were performed to illustrate the effect of photopolymerization on the seepage control of sand soils. Furthermore, the influence of photopolymerization on the microstructure of soils was examined with the aid of SEM analysis. The results indicated that the photopolymerization technique could improve the crust strength, acid rain durability, and permeability of sand soils. The crusts at the surface layer of soils were formed after the photopolymer was applied to the sand surface and then exposed to UV light. These crusts of different soils have bending strengths and thicknesses in the range of 34.57 and 68.07 MPa, 2.13 and 6.18 mm, respectively. The increase in exposure duration and light intensity, resulted in the gradual increment of soil crust thickness. On the other hand, the increase in light intensities have more effective on the crust thickness. The formed soil crust has been provided an impermeable surface that prevents the weight loose from the surface of the soil under acid rain conditions. The SEM analysis indicated that the photopolymerized gels were homogeneously distributed between the grains in all samples, although the grain distribution of soils were different. Since the photopolymerization method has a short treatment duration and is easier to apply on the sand surface, the occurrence of the crust at the soil surface by this technique may open a new and improvable path for seepage control. The obtained results showed that the photopolymerization method is promising for repairing, restoring, and strengthening the construction materials in different engineering areas, as well as seepage control.

In the original version of this article, the reference list for the kinematic source inversion algorithm provided us by Yuji Yagi is incomplete.

Missing data cause problems in meteorological, hydrological, and climate analysis. The observation data should be complete and cover long periods to make the research more accurate and reliable. Artificial intelligence techniques have attracted interest for completing incomplete meteorological data in recent years. In this study the abilities of machine learning models, artificial neural networks, the nonlinear autoregressive with exogenous input (NARX) model, support vector regression, Gaussian processes regression, boosted tree, bagged tree (BAT), and linear regression to fill in missing precipitation data were investigated. In developing the machine learning model, 70% of the dataset was used for training, 15% for testing, and 15% for validation. The Bayburt, Tercan, and Zara precipitation stations, which are closest to the Erzincan station and have the highest correlation coefficients, were used to fill the data gaps. The accuracy of the constructed models was tested using various statistical criteria, such as root-mean-square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe model efficiency coefficient (NSE), and determination coefficient (R2) and graphical approaches such as scattering, box plots, violin plots, and Taylor diagrams. Based on the comparison of model results, it was concluded that the BAT model with R2: 0.79 and NSE: 0.79 and error (RMSE: 11.42, and MAE: 7.93) was the most successful in the completion of missing monthly precipitation data. The contribution of this research is assist in the choice of the best and most accurate method for estimating precipitation data in semi-arid regions like Erzincan.

This study presents a comparison of data acquisition, processing and interpretation between passive seismic interferometry (SI) and active multichannel analysis of surface waves (MASW) methods, both using surface waves for estimation S-wave velocity field. Measurements have been taken in the same geological engineering conditions on Just-Tegoborze landslide on the south of Poland. This comparison study has an important meaning from landslide hazard evaluation point of view. The landslide is located in Magura Nappe in Outer (Flysch) Carpathians. SI was based on registration of local seismic noise generated by high traffic on the state road which intersects the landslide. The main processing step was cross-correlation of seismic noise between every pair of receivers. It led to obtain series of empirical Green’s functions for Rayleigh surface wave. However, in MASW method, seismic energy was released by an impact of 5 kg sledgehammer in a metal plate. Both methods included analysis of dispersion curves of Rayleigh surface wave. The inversion of picked fundamental modes was applied using genetic algorithm and resulted in 1D S-wave velocity models. The last step of interpretation included model visualization as the 2D S-wave velocity sections for studied profiles. Both MASW and SI methods allowed to estimate S-wave velocity field in Just-Tegoborze landslide subsurface. Dispersion images obtained from both methods provided similar phase velocity and frequency ranges. On S-wave velocity sections, the greater depth range was observed for SI method; however, lateral resolution was better for MASW. Slip surfaces in colluvial layer were not observed on either SI or MASW S-wave velocity sections. Only results obtained from SI allowed to distinguish probable slip surface located deeper, i.e. on the contact with less weathered flysch bedrock.