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Coastal wetlands are transitional ecosystems between land and sea. Participants of citizen science programs have detected frequent floods in wetlands, as well as small pools that appear and then disappear. Considering that it is not clear whether their main hydrologic drivers are of marine or continental origin, we studied the El Culebrón wetland located in the Chilean semi-arid zone. El Culebrón is strongly influenced by extreme rain events. This wetland also experiences seasonal changes in its water stage (WS). A high mean sea level agreed with 41% of the WS rises. High intensity storm surges coincided with 53% of WS peaks. A small tsunami in 2022 impacted the WS, and another very intense tsunami flooded it in 2015. An apparent diurnal cycle in the WS was discarded due to an instrumental artifact. The combination of the aforementioned factors provided an explanation for 91% of the WS rises. The probable and novel mechanism for sea level and storm surge influence on WS is the formation of a sand barrier between the coastal lagoon and the sea. As a whole, El Culebrón receives varied influences from both the sea and the mainland, but it seems to be more dependent on freshwater sources.

This study investigates the performance of two bentonite materials, specifically MX-80 (Na-bentonite) and FEBEX (Ca-Mg-Na-bentonite), employed as engineered barriers in deep geological disposal facilities for the isolation of high-level radioactive waste, contained in metallic canisters. Experiments conducted at the laboratory scale focused on the interaction of these bentonites with FeCl2 powder, used as a soluble iron source, to observe enhanced alteration of the bentonite. The experiments were carried out under a hydrothermal gradient. A dominant Na-Cl-SO4 saline solution was put in contact with the compacted bentonites from the top, while a constant temperature of 100 °C was maintained at the bottom using a heater in contact with the layer of FeCl2. The experimental cells were examined after six months of interaction. Various changes in the physical and chemical properties of the bentonites were observed. An increase in the water content, a reduction in the specific surface area and cation exchange capacity, changes in the distribution of aqueous species, and the formation of secondary minerals were observed. Reaction products formed at the bentonite interface with FeCl2, primarily comprising akaganeite, goethite, and hematite. The smectites showed evident structural modifications, with an enrichment in iron content, and a shift in the exchangeable ion distribution in the case of MX-80 bentonite. This work provides valuable insights into the complex interactions between bentonite barriers and materials that dissolve iron, serving as proxies for deep geological disposal environments and indicating the potential long-term behavior, taking into account higher concentrations of dissolved iron than those expected in a real repository. [ABSTRACT FROM AUTHOR]

Lagtimes and times of concentration are frequently determined parameters in hydrological design and greatly aid in understanding natural watershed dynamics. In unmonitored catchments, they are usually calculated using empirical or semiempirical equations developed in other studies, without critically considering where those equations were obtained and what basic assumptions they entailed. In this study, we determined the lagtimes (LT) between the middle point of rainfall events and the discharge peaks in a watershed characterized by volcanic soils and swamp forests in southern Chile. Our results were compared with calculations from 24 equations found in the literature. The mean LT for 100 episodes was 20 hours (ranging between 0.6–58.5 hours). Most formulae that only included physiographic predictors severely underestimated the mean LT, while those including the rainfall intensity or stream velocity showed better agreement with the average value. The duration of the rainfall events related significantly and positively with LTs. Thus, we accounted for varying LTs within the same watershed by including the rainfall duration in the equations that showed the best results, consequently improving our predictions. Izzard and velocity methods are recommended, and we suggest that lagtimes and times of concentration must be locally determined with hyetograph-hydrograph analyses, in addition to explicitly considering precipitation patterns.

During hydrological research in a Chilean swamp forest, we noted a pattern of higher streamflows close to midday and lower ones close to midnight, the opposite of an evapotranspiration (Et)-driven cycle. We analyzed this diurnal streamflow signal (DSS), which appeared mid-spring (in the growing season). The end of this DSS coincided with a sustained rain event in autumn, which deeply affected stream and meteorological variables. A survey along the stream revealed that the DSS maximum and minimum values appeared 6 and 4 hours earlier, respectively, at headwaters located in the mountain forests/ plantations than at the control point in the swamp forest. Et in the swamp forest was higher in the morning and in the late afternoon, but this process could not influence the groundwater stage. Trees in the mountain headwaters reached their maximum Ets in the early morning and/or close to midday. Our results suggest that the DSS is a wave that moves from forests high in the mountains towards lowland areas, where Et is decoupled from the DSS. This signal delay seems to convert the link between streamflow and Et in an apparent, but spurious positive relationship. It also highlights the role of landscape heterogeneity in shaping hydrological processes.

This research centers on the implementation of photovoltaic systems in residential applications, coupled with battery-based energy storage, and evaluates their efficiency in generating energy, specifically for lighting in buildings. The methodology hinges on detecting interharmonic signals to characterize potentially disruptive frequencies and identify the origins of various failures. Multiple case studies are presented to validate the method's efficacy, including one involving fluorescent lamp circuits and another examining variations in solar radiation during the summer season. Real-world experiments are conducted in a residential setting, and the results are thoroughly analyzed. Various types of interharmonic generation behaviors are demonstrated, which are influenced by fluctuations in solar radiation and the appropriate installation of solar panels. The findings reveal that the absence of solar radiation below 300 W/m2 in a photovoltaic system relying on energy storage adversely affects interharmonics in luminaires installed within a residential space. [ABSTRACT FROM AUTHOR]

Wheat is a major crop worldwide, mainly cultivated for human consumption and animal feed. Grain quality is paramount in determining its value and downstream use. While we know that climate change threatens global crop yields, a better understanding of impacts on wheat end‐use quality is also critical. Combining quantitative genetics with climate model outputs, we investigated UK‐wide trends in genotypic adaptation for wheat quality traits. In our approach, we augmented genomic prediction models with environmental characterisation of field trials to predict trait values and climate effects in historical field trial data between 2001 and 2020. Addition of environmental covariates, such as temperature and rainfall, successfully enabled prediction of genotype by environment interactions (G × E), and increased prediction accuracy of most traits for new genotypes in new year cross validation. We then extended predictions from these models to much larger numbers of simulated environments using climate scenarios projected under Representative Concentration Pathways 8.5 for 2050–2069. We found geographically varying climate change impacts on wheat quality due to contrasting associations between specific weather covariables and quality traits across the UK. Notably, negative impacts on quality traits were predicted in the East of the UK due to increased summer temperatures while the climate in the North and South‐west may become more favourable with increased summer temperatures. Furthermore, by projecting 167,040 simulated future genotype–environment combinations, we found only limited potential for breeding to exploit predictable G × E to mitigate year‐to‐year environmental variability for most traits except Hagberg falling number. This suggests low adaptability of current UK wheat germplasm across future UK climates. More generally, approaches demonstrated here will be critical to enable adaptation of global crops to near‐term climate change. [ABSTRACT FROM AUTHOR]

In this study, we extend research on genomic prediction (GP) to polysomic polyploid plant species with the main objective to investigate single-trait (ST) and multitrait (MT) multienvironment (ME) models using field trial data from 3 locations in Sweden [Helgegården (HEL), Mosslunda (MOS), Umeå (UM)] over 2 years (2020, 2021) of 253 potato cultivars and breeding clones for 5 tuber weight traits and 2 tuber flesh quality characteristics. This research investigated the GP of 4 genome-based prediction models with genotype × environment interactions (GEs): (1) ST reaction norm model (M1), (2) ST model considering covariances between environments (M2), (3) ST M2 extended to include a random vector that utilizes the environmental covariances (M3), and (4) MT model with GE (M4). Several prediction problems were analyzed for each of the GP accuracy of the 4 models. Results of the prediction of traits in HEL, the high yield potential testing site in 2021, show that the best-predicted traits were tuber flesh starch (%), weight of tuber above 60 or below 40 mm in size, and the total tuber weight. In terms of GP, accuracy model M4 gave the best prediction accuracy in 3 traits, namely tuber weight of 40-50 or above 60 mm in size, and total tuber weight, and very similar in the starch trait. For MOS in 2021, the best predictive traits were starch, weight of tubers above 60, 50-60, or below 40 mm in size, and the total tuber weight. MT model M4 was the best GP model based on its accuracy when some cultivars are observed in some traits. For the GP accuracy of traits in UM in 2021, the best predictive traits were the weight of tubers above 60, 50-60, or below 40 mm in size, and the best model was MT M4, followed by models ST M3 and M2. [ABSTRACT FROM AUTHOR]