Basin Analysis and Modelling

Human land use land cover changes (LULCCs) can cause impacts on watershed lands and on water resources. The regions with land use conflict suffer more intense erosion processes due to their high slope and drainage density. The study intends to evaluate scenarios with an absence of land use conflict and verify if it can contribute to reductions in surface runoff, avoiding the carriage of tailings to river channels. In the study, the SWAT model was used in the hydrological modeling of the Paraopeba River watershed affected by the rupture. The results show that the SWAT model was able to reproduce the flow data with good and very good performances. The quality indicators in the calibration step were NSE = 0.66, R² = 0.69, PBIAS = 5.2%, and RSR = 0.59, and in the validation, step were NSE = 0.74, R² = 0.77, PBIAS = 13.5%, and RSR = 0.51. The LULCC from 2000 to 2019 led to a 70% increase in lateral runoff (LATQ) and a 74% decrease in aquifer groundwater. The scenario of land use capability and no conflict can reduce lateral runoff by 37% and increase water infiltration by 265%, minimizing the point and diffuse contamination of the tailings in the Paraopeba river channel. Full article

In order to understand the hydrological impacts of the nature-based solutions in the Cantareira Water Supply System, this study evaluates six different land cover and land use change scenarios. The first and second consider the restoration of native vegetation in riparian areas, the third prioritizes restoration sites using biophysical characteristics (optimized restoration scenario derived from Resource Investment Optimization System—RIOS), the fourth considers best management practices and the fifth and sixth are hypothetical extreme scenarios converting all pasture to forest and vice versa. Two hydrological models were developed to represent the distributions of water and yields in the study watershed: HEC-HMS and SWAT. Simulation results indicate that when nature-based solutions are implemented, surface runoff is reduced and ambient storage increases during the rainy season (December–March); while the overall flow increases during the dry season (June–September). The combination of specific hydrologic components of RIOS-customized intervention scenario simulation outputs—namely surface flows and groundwater contribution to stream flows—indicate on average 33% increase in the overall water yield, or 206 hm³/year, across the study watershed when comparing against the baseline conditions. In the same modeling scenario, the water storage in the sub-watersheds adjacent to the reservoirs showed an increase of 58% (or 341 hm³/year). The results indicate that adopting NbS in the source watershed can mitigate the impacts of extreme drought conditions and contribute toward building long-term water security. Full article

Monthly hydrological models are useful tools for runoff simulation and prediction. This study proposes a three-parameter monthly hydrological model based on the proportionality hypothesis (TMPH) and applies to the Upper Hanjiang River Basin (UHRB) in China. Two major modules are involved in the TMPH: the actual evapotranspiration and runoff, in which the coupled water–energy balance equation and the proportionality hypothesis are used for calculation, respectively. It is worth mentioning that the proportionality hypothesis was extended to the partitioning of the available water into water loss and runoff at the monthly scale, which demonstrates that the ratio of runoff to its potential value is equal to the ratio of continuing water loss to its potential value. Results demonstrate that the TMPH model performs well when the NSE values are 0.79 and 0.83, and the KGE values are 0.86 and 0.78 for calibration period and validation period, respectively. The widely used two-parameter monthly water balance (TWBM) model and ABCD model are compared with the proposed model. Results show that TMPH performs better than TWBM model with NSE increased by 0.07 and 0.11, and KGE increased by 0.02 and 0.16, respectively, whereas the TMPH performs similarly as the ABCD model in the calibration period, and performs slightly better in the validation period, with NSE increased by 0.02, and KGE increased by 0.03. Sensitivity analysis show that the simulation result is most sensitive to parameter n, followed by SC and $\lambda$. In summary, the proposed model has strong applicability to the study area. Full article

In a previous paper, the authors implemented a machine learning k-nearest neighbors (KNN) algorithm and Python libraries to create two 3D interactive models of the stratigraphic architecture of the Quaternary onshore Llobregat River Delta (NE Spain) for groundwater exploration purposes. The main limitation of this previous paper was its lack of routines for evaluating the confidence of the 3D models. Building from the previous paper, this paper refines the programming code and introduces an additional algorithm to evaluate the confidence of the KNN predictions. A variant of the Similarity Ratio method was used to quantify the KNN prediction confidence. This variant used weights that were inversely proportional to the distance between each grain-size class and the inferred point to work out a value that played the role of similarity. While the KNN algorithm and Python libraries demonstrated their efficacy for obtaining 3D models of the stratigraphic arrangement of sedimentary porous media, the KNN prediction confidence verified the certainty of the 3D models. In the Llobregat River Delta, the KNN prediction confidence at each prospecting depth was a function of the available data density at that depth. As expected, the KNN prediction confidence decreased according to the decreasing data density at lower depths. The obtained average-weighted confidence was in the 0.44−0.53 range for gravel bodies at prospecting depths in the 12.7−72.4 m b.s.l. range and was in the 0.42−0.55 range for coarse sand bodies at prospecting depths in the 4.6−83.9 m b.s.l. range. In a couple of cases, spurious average-weighted confidences of 0.29 in one gravel body and 0.30 in one coarse sand body were obtained. These figures were interpreted as the result of the quite different weights of neighbors from different grain-size classes at short distances. The KNN algorithm confidence has proven its suitability for identifying these anomalous results in the supposedly well-depurated grain-size database used in this study. The introduced KNN algorithm confidence quantifies the reliability of the 3D interactive models, which is a necessary stage to make decisions in economic and environmental geology. In the Llobregat River Delta, this quantification clearly improves groundwater exploration predictability. Full article

To promote oil and gas exploration of the Carboniferous formation in the Shibei sag, the northeastern margin of Junggar Basin, recently drilled rocks from Well ZB6 with typical seismics were characterized. Through systematic core observation, the identification marks of seismites were described, a vertical sequence of seismites was established, and its oil and gas geological significance was analyzed. The results show that the seismites have typical identification marks, such as soft-sediment deformation structures (including five typical marks: liquefied stone vein, liquefied crinkled deformation structure, ball–pillow structure, flame structure and load cast, water release structure and liquefied breccia), brittle fracture structures (including three typical marks: seismic fractures, synsedimentary microfractures and seismic fracture rock) and special rock types, such as seismic grain-supported conglomerates. The stratigraphic succession reconstructed in Well ZB6 was characterized, from base to top, by (1) a basal non-seismic interval; (2) a seismic interval made up of a grain-supported conglomerate level, brittle fracture level, soft-sediment deformation level; and (3) a non-seismic interval. The discovery of seismites has oil and gas geological significance for improving reservoir performance and forming favorable source–reservoir–cap assemblages. The research describes the new reservoir genetic type and exploration direction of the Carboniferous formation in the Shibei sag (China), which has important guiding significance for the next step of oil and gas exploration. Full article

In the course of attempting to date the host rocks of Viburnum metal deposits from the US state of Missouri, the purpose was here a detailed examination and contribution of the constitutive minerals of glauconite-rich pellets to the isotopic dating of these deposits. The glauconite pellets of Cambrian sediments hosting metal concentrates were dated here by the K-Ar method to complement earlier published Rb-Sr data. The study confirmed that the preparation and purification step of such glauconite pellets is especially critical with the need for a specific cleaning step to not only remove the detrital counterparts but also all Sr-rich components occurring as accessory minerals such as the carbonates, sulfates and oxides that apparently “contaminated” the Rb-Sr results. The K-Ar data and the previously released Rb-Sr results obtained on strictly the same glauconite-rich separates outline clear age discrepancies that can be summarized by higher, “older” K-Ar age data at about 440, 415 and 390 Ma, and lower, “younger” Rb-Sr data at about 400 and 370 Ma. The glauconite separates of most samples being apparently not contaminated by various detrital K-rich crystals, the two dating methods should have been affected similarly. The analytical dispersion seems, then, to result from a diagenetic event that affected the Rb-Sr system more than the K-Ar system by a plausible addition/subtraction of one or several Sr-rich and Rb-poor and, therefore, K-poor minerals. In turn, the studied pellets were apparently impregnated after deposition by flowing metal-rich fluids in a low-temperature environment not affected by a significant thermal impact. The Bonneterre Formation acted apparently as a regional drain for metal-rich fluids that percolated throughout the region at a probable burial depth of less than 2000 m. Full article