Precipitation Time Research Articles

A Reevaluation of the Timing and Temperature of Copper and Molybdenum Precipitation in Porphyry Deposits

Abstract The timing and temperature at which copper-iron and molybdenum sulfide deposition occurs in porphyry deposits remain controversial. Petrologic estimates indicate that veins and wall-rock alteration zones containing copper-iron sulfides form in a wide temperature range from ~350° to 650°C. Most sulfides are hosted in potassium(K)-silicate–altered rock and quartz A veins or in early-halo alteration selvages formed above ~450°C. In contrast, cathodoluminescence (CL) imaging of A veins indicates that copper-iron sulfides are contained within a primary lucent (bright and gray)-CL quartz and are crosscut by microfractures filled with younger dull (dark and medium-gray)-CL quartz in direct contact with copper-iron sulfides. These observations have been interpreted as supporting late copper-iron sulfide introduction together with dull-CL quartz at moderate temperatures of ~300° to 450°C, based on fluid inclusion estimates. We provide new CL, QEMSCAN, and petrographic data and images of vein quartz as well as petrologic data of altered wall rock from Haquira East (Peru), Encuentro (Chile), and Batu Hijau (Indonesia) porphyry deposits, which were formed at conditions ranging from deep to shallow (~2–10 km). At all three deposits, dull-CL quartz in microfractures is ubiquitously observed crosscutting all generations of high-temperature lucent-CL quartz veins. Each lucent-CL vein type hosts distinct sulfide populations, crosscuts the others, and coexists in space within the copper and molybdenum ore zones. Within this ore zone, the dull-CL quartz only contains copper-iron sulfides where it transects old A veins and early halos, molybdenite where it transects young molybdenite-bearing quartz veins, and both copper-iron sulfides and molybdenite in younger B veins. Furthermore, where the dull-CL quartz crosscuts igneous or barren (deep) quartz veins, it typically lacks copper and molybdenum. Therefore, dull-CL quartz has no particular spatial or genetic affinity with copper-iron sulfides or molybdenite. We propose that copper was introduced and precipitated at high temperatures in stability with K-silicate alteration. In shallow porphyry deposits, most copper was introduced with lucent-CL quartz in A veins, likely formed via adiabatic decompression from magmatic lithostatic to hydrostatic conditions at ~450° to 600°C. In deep deposits, most copper is introduced with quartz-poor early halos, likely formed at a temperature range similar to that of A veins but during an early stage of retrograde silica solubility. The inferred timing and temperature of copper precipitation are consistent with available solubility experiments for copper-bearing solutions that suggest copper precipitation may start at a high temperature of ~600°C, and ~90% precipitates before it cools down to ~400°C. Much of the molybdenum is introduced and precipitated with discrete pulses of molybdenite-bearing quartz veins that crosscut and postdate copper-bearing A veins and early halos and, to a lesser degree, with B veins that may carry both copper and molybdenum. Whereas molybdenite-bearing and barren (deep) quartz veins form at relatively high temperatures of ~550° to 650°C, copper-molybdenum–bearing B veins likely form at lower temperatures near ~500°C. Copper precipitation and local copper remobilization from older veins and halos continued during the formation of copper-iron sulfide veinlets, named C veins, and during the precipitation of dull-CL quartz following K-silicate alteration. C veins and even younger pyrite-rich D veins may have chlorite or sericite selvages and are composed of dull-CL quartz that formed at ~450° and 300° to 450°C, respectively. Microfractures form through all lucent-CL quartz veins because of the thermal contraction of high-temperature quartz at the onset of sustained cooling after K-silicate alteration has ceased. The fluid that migrated through these microfractures was initially in retrograde silica solubility, which causes dissolution and corrosion of the older lucent-CL quartz. The formation of C veins may overlap in time with the initial stage. At a later stage and temperatures below <450°C, the fluid precipitates dull-CL quartz in microfractures and dissolution zones within older lucent-CL quartz. In copper-iron sulfide-bearing A and B veins and molybdenite-bearing quartz veins, corroded lucent-CL quartz and the younger dull-CL quartz infill can often be observed in contact with older sulfides because quartz sulfide grain boundaries are preexisting discontinuities, and they are preferentially opened during volume contraction. Collectively, these observations and estimates are consistent with silicate phase petrology and numerous observations that most copper-iron sulfides precipitate in K-silicate alteration zones or in early halos with K-feldspar-muscovite-biotite assemblages.

Productivity analysis and costs of wheel cable skidder during salvage logging in European beech stand

Salvage logging is increasing in Central Europe because of the growth of severe meteorological events, and timber harvesting in these conditions is challenging in terms of both productivity performances and safety of the operations. In recent years, with the increase of natural calamities, several researchers studied machinery productivity performances regarding salvage logging carried out by ground-based systems. In fact, a common post-disturbance management approach is salvage logging which consists of the widespread removal of damaged trees. In this research, system productivity and the cost of salvage logging are analysed in European beech stands affected by wet snow. The accretion of heavy wet snow poses the greatest risk to forests in the Northern Hemisphere. This type of snow attaches more effectively to tree crowns and branches when temperatures are close to freezing at the time of precipitation. As a result, trees may break or bend and may be uprooted when the soil is unfrozen. This study has been implemented to evaluate the productivity and cost-effectiveness of extraction in salvage logging deployed with a skidder in beech stands affected by two different types of wet snow damage. The results show that the productivity of the four-wheel-drive cable skidder, despite operating in salvage cutting with a removal intensity of 10%, is 14.73 m3·SMH–1, similar to skidder performances in ‘ordinary’ cuttings. Skidder’s productive time was 86% of the scheduled time, whereas the delays were due to organisational reasons, mechanical delays, and adverse weather conditions. The mean travel speed of the cable skidder obtained in this study is close to the results obtained from other studies on similar machines. The costs per unit are lower than effective cost consumptions for the other cable skidders and agricultural tractors, adapted for skidding operated in hardwood salvage logging. Therefore, under the given conditions, the operation of the fourwheel-drive cable skidder is viable from a silvicultural, technical, and economic point of view in the salvage operation logging.

Evolution of the sigma phase and its effect on the corrosion resistance of ASTM A890 3A duplex stainless steel

The sigma (σ) phase is a detrimental precipitation that affects the performance and application of duplex stainless steel (DSS). In this study, the evolution of the σ phase and its influence on the corrosion resistance of the ASTM A890 3 A DSS were analyzed quantitatively by aging at 750 °C for 3–96 h for the first time. With increasing aging time, the amount and rate of precipitation of the σ phase significantly changed. The fraction of the σ phase increased from 0.65% to 23.51%, accompanied by a decrease in ferrite content and an increase in austenite content. During the evolution of the σ phase, a combined process of nucleation and growth controlled by the eutectoid reactions in the first 3–24 h and a growth process controlled by diffusion in the subsequent 24–96 h were observed. The deteriorated corrosion resistance after aging was closely related to the fraction and distribution morphology of the σ phase. Under a precipitation fraction of the σ phase between 0% and 0.65%, the passive current density of the DSS increased, the pitting potential decreased. The width of the passivation region between 0.65% and 19.07% of the σ phase narrowed, and instability formed. The critical aging time for the transformation from passive to active DSS was between 48 h, corresponding to a content of the σ phase of 19.07%. The passivation region almost completely disappeared. In addition, the uniformity in distribution of the σ phase also influenced the corrosion resistance.

Variations in climate drive behavior and survival of small desert tortoises

In the Mojave Desert, timing and amounts of precipitation profoundly affect the availability of water and annual plant foods necessary for the threatened Agassiz’s desert tortoise (Gopherus agassizii) to survive, especially during prolonged droughts. As part of recovery actions to increase declining populations, we translocated 83 juvenile and young desert tortoises raised in head-start pens for 4–10 years to a new location 15 km away during the fall of 2013 and 2014. We tracked them for 9 years during a megadrought, during multiple years of low rainfall, and a few years when precipitation neared or exceeded long-term norms. We evaluated behaviors and how precipitation and forage availability affected survival. At the end of the study, 21.6% of tortoises were alive, and six had grown to adulthood. Annual models of survival indicated that tortoise size was the driving variable in most years, followed by the number of repeatedly used burrows during periods of temperature extremes. Other variables affecting survival in ≥1 year were vegetation, movements during the first 2 years post-translocation, and condition index, a measure of health. Tortoises moved more, expanded home ranges, and grew rapidly in years when winter rainfall approached or exceeded long-term norms and annual plants were available to eat. During dry years, movements and growth were limited. Exceptions to this pattern occurred in the last year of study, a dry year: tortoises grew and moved more, and home ranges increased. The increase in size and approaching adulthood may have stimulated greater traveling. Some left the study area, indicating a need for large release areas. We may have aided survival by offering water twice yearly when handling because some tortoises drank and increased in mass up to 40%. Prolonged droughts and hotter temperatures can limit the recovery of populations, reduce the survival of young tortoises, and increase the time to maturity.

GEV Analysis of Extreme Rainfall: Comparing Different Time Intervals to Analyse Model Response in Terms of Return Levels in the Study Area of Central Italy

The extreme rainfall events of recent years in central Italy are producing an increase in hydrogeological risk, with disastrous flooding in terms of human lives and economic losses, as well as triggering landslide phenomena in correspondence with these events. A correct prediction of 100-year return levels could encourage better land planning, sizing works correctly according to the expected extreme events and managing emergencies more consciously through real-time alerts. In the recent period, it has been observed that the return levels predicted by the main forecasting methods for extreme rainfall events have turned out to be lower than observed within a few years. In this context, a model widely used in the literature, the generalised extreme value (GEV) with the “block maxima” approach, was used to assess the dependence of this model on the length of the collected precipitation time series and the possible addition of years with extreme events of great intensity. A total of 131 rainfall time series were collected from the Adriatic slope in central Italy comparing two periods: one characterised by 70 years of observations (1951–2020), the other by only 30 years (1991–2020). At the same time, a decision was made to analyse what the effect might be—in terms of the 100-year return level—of introducing an additional extreme event to the 1991–2020 historical series, in this case an event that actually occurred in the area on 15 September 2022. The results obtained were rather surprising, with a clear indication that the values of the 100-year return level calculated by GEV vary according to the length of the historical series examined. In particular, the shorter time series 1991–2020 provided higher return level values than those obtained from the 1951–2020 period; furthermore, the addition of the extreme event of 2022 generated even higher return level values. It follows that, as shown by the extreme precipitation events that have occurred in recent years, it is more appropriate to consider a rather short period because the ongoing climate change does not allow true estimates to be obtained using longer time series, which are preferred in the scientific literature, or possibly questioning the real reliability of the GEV model.

Effects of simulated extreme precipitation flooding on the degradation of anaerobic digestion effluent by algal-bacterial symbiosis system

Precipitation is directly affected by global warming among different extreme climate types. The moisture-holding capacity of the atmosphere increases by 7% with a temperature increase of 1 °C. A higher moisture content results in frequent and violent rainfall events, and the frequency and intensity of heavy rainfall and flooding events in certain countries and regions is gradually aggravated. Simulated extreme precipitation experiments with precipitation intensities of 50, 100, and 200 mm and precipitation time on 3th, 6 th, and 9 th day were set to study the effects of extreme precipitation and flooding events on the degradation performance of open algae–bacteria symbiotic (ABS) system for anaerobic digestion effluent (ADE). The experimental results showed that the precipitation time had an obvious impact on the open algae–bacteria symbiotic system. The daily COD (chemical oxygen demand) degradation rates in the algae–bacteria symbiotic system on the fourth day decreased from 12.64% (unaffected by precipitation) to 2.94, 2.38, and 1.90%, respectively, under the conditions of rainfall on the third day and precipitation intensities of 50, 100, and 200 mm. At the end of the experiments, the COD contents in the ADE increased from 355.09 mg/L (unaffected by precipitation) to 435.77, 413.67, and 403.54 mg/L, respectively. The degradation effects of COD, TN (total nitrogen), and TP (total phosphorus) in the open algae–bacteria symbiotic system were affected by extreme precipitation (200 mm) and flooding. On the third day of the heavy rainfall event, Actinobacteria, Proteobacteria, and Bacteroidetes were the most dominant phyla in the samples of the symbiotic system between algae and bacteria. Among them, the abundance of Proteobacteria and Bacteroidetes was the highest, accounting for 15.33, 21.33 and 19.97%, respectively. As the symbiotic system operated stably, their proportions decreased to 13.58, 12.13, and 17.85% on the ninth day. At the class level, the abundance of Beta-proteobacteria and Gamma-proteobacteria was relatively high in the samples of the symbiotic system. On the third day of the heavy rainfall event, they accounted for 8.99 and 7.11%, respectively. With the stable operation of the system, their proportions showed a decreasing trend, and on the sixth and ninth days, they were 7.03% and 6.01, 4.87 and 4.39%, respectively.

Emergence of Power-Law Particle Size Distribution in Microfluidic Calcium Carbonate Precipitation: An Extended Yule Process with a Ripening Effect.

Precipitation of calcium carbonate in bulk solutions is well known to result in a bell-shaped or bimodal particle size distribution. However, it is unclear how the distribution behaves if precipitation occurs in a small, confined volume. In this Letter, we conduct microfluidic experiments where sodium carbonate and calcium chloride solutions are continuously injected into a microchannel to precipitate calcium carbonate particles. Results show that, regardless of the variations in reagent concentrations, mixing schemes, flow rates, and precipitation time, sizes of precipitated particles in the channel are power law distributed, with an exponent of 1.4. The data are described by an extended Yule process with the introduction of a ripening term. Since the Yule process is a general mechanism for power law generation, the extended Yule process proposed here provides a general model for systems where growth and ripening simultaneously present.

Scaling and intermittency in time of urban precipitation in Warsaw, Poland

Study regionA network of 25 rain gauges roughly covering an area of 517.2 km2 of Warsaw, in Poland. Study focusScaling and intermittency of data series of rainfall intensity are investigated for each of the network rain gauges using five multifractal framework methods: spectral density analysis, functional box-counting, trace moment, probability distribution/multiple scaling, and double trace moment. Synthetic precipitation series are then generated by means of continuous universal random cascade models. Cascade generators are defined by universal parameters calculated for selected Warsaw rain gauges, or rain gauge clusters displaying similarity of multifractal parameters. The generated synthetic precipitation time series are subject to statistical evaluation by comparing the complementary cumulative distribution function and the intermittency calculated for synthetic versus observed data. Finally, a novel filtering algorithm is proposed to correct the intermittency characteristics of synthetic precipitation time series. New hydrological insightsBased on our analyses, the temporal structure of the recorded Warsaw precipitation time series is found to be a multifractal set characterized by a scaling behaviour over a wide range of scales. Furthermore, it has been observed that most Warsaw rain gauges, have a distinct similarity of multifractal properties. It has also been demonstrated that, for the first time in Poland, the universal continuous cascades could be used in practice for the generation of synthetic rainfall series at fine (1-min) temporal resolution

Deep learning for stochastic precipitation generation – deep SPG v1.0

Abstract. We present a deep-neural-network-based single-site stochastic precipitation generator (SPG), capable of producing realistic time series of daily and hourly precipitation. The neural network outputs a wet-day probability and precipitation distributions in the form of a mixture model. The SPG was tested in four different locations in New Zealand, and we found it accurately reproduced the precipitation depth, the autocorrelations seen in the original data, the observed dry-spell lengths, and the seasonality in precipitation. We present two versions of the hourly and daily SPGs: (i) a stationary version of the SPG that assumes that the statistics of the precipitation are time independent and (ii) a non-stationary version that captures the secular drift in precipitation statistics resulting from climate change. The latter was developed to be applicable to climate change impact studies, especially studies reliant on SPG projections of future precipitation. We highlight many of the pitfalls associated with the training of a non-stationary SPG on observations alone and offer an alternative method that replicates the secular drift in precipitation seen in a large-ensemble regional climate model. The SPG runs several orders of magnitude faster than a typical regional climate model and permits the generation of very large ensembles of realistic precipitation time series under many climate change scenarios. These ensembles will also contain many extreme events not seen in the historical record.

Density-oriented deep eutectic solvent-based system for the selective separation of polysaccharides from Astragalus membranaceus var. Mongholicus under ultrasound-assisted conditions

The water extraction and ethanol precipitation method is an extraction method based on the solubility characteristics of polysaccharides that offers wide applicability in the extraction and separation of plant polysaccharides. However, this method leads to large amounts of proteins, nucleic acids, pigments, and other impurities in the polysaccharides products, which makes downstream purification complicated and time-consuming. In this study, a green, high-density natural deep eutectic solvents was used for the high-purity extraction and separation of polysaccharides from Astragalus membranaceus (Fisch) Bge. var. Mongholicus (Bge.) Hsiao roots under ultrasound-assisted conditions. In this study, 16 different natural deep eutectic solvents were designed to screen the best solvent for extracting Astragalus polysaccharides (APSs). Based on the yield and recovery of APSs, a natural deep eutectic solvents composed of choline chloride and oxalic acid with a molar ratio of 1:2 was selected. The related factors affecting polysaccharides extraction and solvent precipitation were investigated. To improve the operating methodology, single-factor trials, a Plackett-Burman design, and a Box-Behnken design were used. The optimal extraction process conditions were obtained as follows: water content of 55%, liquid–solid ratio of 24 mL/g, ultrasonic irradiation time of 54 min, ultrasonic irradiation temperature of 50 °C, ultrasonic irradiation power of 480 W, ethanol precipitation time of 24 h, and ethanol concentration of 75%. Under optimal extraction conditions, the recovery of APSs was 61.4 ± 0.6 mg/g. Considering the special matrix characteristics of A. membranaceus var. Mongholicus roots, physical-technology-based ultrasonic waves promote penetration, and the mass transfer function also solves the bottleneck of high-viscosity deep eutectic solvents in the extraction stage. In comparison with the conventional method, the proposed method based on deep eutectic solvents isolation can significantly increase APSs recovery, which is beneficial to simplifying the process of polysaccharides purification by using solvent properties to separate extracts and reduce impurities in APSs.

Meteorological Drought Assessment and Trend Analysis in Puntland Region of Somalia

Drought assessment and trend analysis of precipitation and temperature time series are essential in the planning and management of water resources. Long-term precipitation and temperature historical records (monthly for 41 years, from 1980 to 2020) are used to investigate annual drought characteristics and trend analysis in Somalia’s northern region. Six drought indices of the normal Standardized Precipitation Index (normal-SPI), the log normal Standardized Precipitation Index (log-SPI), the Standardized Precipitation Index using the gamma distribution (Gamma-SPI), the Percent of Normal Index (PNI), the Discrepancy Precipitation Index (DPI), and the Deciles Index (DI) are used in this study for the annual drought assessment. The log-SPI, the gamma-SPI, the PNI, and the DPI could capture historical extreme and severe droughts that occurred in the early 1980s and over the last two decades. The results indicate that Somalia has gone through extended drought periods over the past quarter century, exacerbating the existing humanitarian situation. The normal-SPI, gamma-SPI, and PNI indicate less and moderate drought conditions, whereas log-SPI, DPI, and DI accurately capture historical extreme and severe drought periods; thus, these methods are recommended as annual drought assessment tools in the studied region. Not only are the PNI and DPI less correlated to each other, but their correlation coefficient (CC) with SPI-based drought indices are not as high as SPI-based indices which are close to unity. For the purpose of the trend analysis, the Mann Kendall (MK) test, the Spearman’s rho (SR) test, and the Şen test are used. Furthermore, the Pettitt test is implemented to detect the change points and the Thiel-Sen approach is used to estimate the magnitude of trend in the precipitation and temperature time series. The results indicate that there is overall warming in the region which has experienced a significant shift in trend direction since 2000. The trend analysis of annual precipitation data time series shows that Bossaso and Garowe stations have significant positive trends, while the Qardho station has no trend. In 1997 and 1998, respectively, abrupt changes in annual precipitation are detected at Qardho and Garowe stations. Due to the civil war of more than three decades in Somalia and the non-institutionalized governance to inform historical drought conditions in the country, determining the most appropriate meteorological drought index would help to develop a drought monitoring system for states and the entire country.

Precipitation timing and soil substrate drive phenology and fitness of Arabidopsis thaliana in a Mediterranean environment

Abstract In Mediterranean climates, the timing of seasonal rains determines germination, flowering phenology and fitness. As climate change alters seasonal precipitation patterns, it is important to ask how these changes will affect the phenology and fitness of plant populations. We addressed this question experimentally with the annual plant species Arabidopsis thaliana. In a first experiment, we manipulated the date of rainfall onset and recorded germination phenology on sand and soil substrates. In a second experiment, we manipulated germination date, growing season length and mid‐season drought to measure their effects on flowering time and fitness. Within each experiment, we manipulated seed dormancy and flowering time using multilocus near‐isogenic lines segregating strong and weak alleles of the seed dormancy gene DOG1 and the flowering time gene FRI. We synthesized germination phenology data from the first experiment with fitness functions from the second experiment to project population fitness under different seasonal rainfall scenarios. Germination phenology tracked rainfall onset but was slower and more variable on sand than on soil. Many seeds dispersed on sand in spring and summer delayed germination until the cooler temperatures of autumn. The high‐dormancy DOG1 allele also prevented immediate germination in spring and summer. Germination timing strongly affected plant fitness. Fecundity was highest in the October germination cohort and declined in spring germinants. The late flowering FRI allele had lower fecundity, especially in early fall and spring cohorts. Projections of population fitness revealed that: (1) Later onset of autumn rains will negatively affect population fitness. (2) Slow, variable germination on sand buffers populations against fitness impacts of variable spring and summer rainfall. (3) Seasonal selection favours high dormancy and early flowering genotypes in a Mediterranean climate with hot dry summers. The high‐dormancy DOG1 allele delayed germination of spring‐dispersed fresh seeds until more favourable early fall conditions, resulting in higher projected population fitness. These findings suggest that Mediterranean annual plant populations are vulnerable to changes in seasonal precipitation, especially in California where rainfall onset is already occurring later. The fitness advantage of highly dormant, early flowering genotypes helps explain the prevalence of this strategy in Mediterranean populations. Read the free Plain Language Summary for this article on the Journal blog.

Analyzing the contribution of gully erosion to land degradation in the upper Blue Nile basin, Ethiopia

Soil erosion has become a worldwide problem that threatens the environment and the future of economic and social development. The purpose of this study is to investigate the contribution of steep slopes and gullies to erosion in high precipitation tropical areas of the Ethiopian highlands. A trapezoidal weir was installed at the head and tail of the gully to monitor the discharge and sediment concentration from 2017 to 2020. Sediment yield and runoff are heavily influenced by the amount and timing of precipitation. The coefficients of variation for total sediment loads ranged from 65.1 to 96.1% at the head and 17.1–78.1% at the tail; the lowest coefficients were found in 2018 and the highest in 2020. Furthermore, 85% of the sediment at the tail comes from the gully, according to the four-year sediment budget. Further, a hysteretic analysis of suspended sediment concentration and runoff revealed that hilly sediment sources are limited (clockwise), then sediment can be transported through the gully via bank failures (counterclockwise). Study findings contributed to a classification of runoff patterns and an investigation of suspended sediment dynamics. In the gully tail, sediment yield was higher than in the head, suggesting gully sediment contributed more to sediment yield than large upland catchments. As a result of the study, we have been able to develop practical recommendations for managing gully erosion in the future.

Study on NDVI Periodic Change Characteristics of Inner Mongolia Grassland Based on Variational Mode Decomposition Algorithm

Based on the NDVI data of vegetation in Inner Mongolia from 1982 to 2015, the variational mode decomposition (VMD) method, which has been well applied in the field of signal decomposition, is introduced to study the periodicity of vegetation index in Inner Mongolia. The VMD method is used to extract the monthly and annual NDVI and the long time series cycle characteristics of temperature and precipitation in the same period from April 1982 to October 2015 in Inner Mongolia. The results show that temperature and precipitation are important factors affecting the growth of vegetation, and there are 6.99 and 3.49 months of the same oscillation cycle for monthly NDVI and temperature and precipitation time series; when the central frequency is the same, the amplitude of the monthly temperature and precipitation time series increases with the increase of the lag period. The annual scale NDVI has the same period of 16.95, 6.8a, and 4.85a with precipitation, and the same period of 6.8a and 4.85a with temperature. The Residue component shows that the overall NDVI and temperature in Inner Mongolia have shown a significant slow growth trend in the past 30 years. Although the precipitation has shown a significant slow decline trend in the same time period (p = 0.000), the grassland is still in the process of continuous improvement.

Seasonal controls override forest harvesting effects on the composition of dissolved organic matter mobilized from boreal forest soil organic horizons

Abstract. Dissolved organic matter (DOM) mobilized from the organic (O) horizons of forest soils is a temporally dynamic flux of carbon (C) and nutrients, and the fate of this DOM in downstream pools is dependent on the rate and pathways of water flow as well as its chemical composition. Here, we present observations of the composition of DOM mobilized weekly to monthly from O horizons in mature forest and adjacent harvested treatment plots. The study site was experimentally harvested, without replanting, 10-years prior to this study. Thus, the treatments differ significantly in terms of forest stand and soil properties, and they interact differently with the regional hydrometeorological conditions. This presented an opportunity to investigate the role of forest structure relative to environmental variation on soil DOM mobilization. On an annual basis, fluxes of total dissolved nitrogen (TDN) and dissolved organic nitrogen (DON) were largest from the warmer and thinner O horizons of the harvested (H) treatment compared to the forest (F) treatment; however, neither phosphate nor ammonium fluxes differed by treatment type. On a short-term basis in both H and F treatments, all fluxes were positively correlated to water input, and all concentrations were positively correlated to soil temperature and negatively correlated to water input. Soil moisture was negatively correlated to the C : N of DOM. These results suggest common seasonal controls on DOM mobilization regardless of harvesting treatment. Optical characterization of seasonally representative samples additionally supported a stronger control of season over harvesting. The chemical character of DOM mobilized during winter and snowmelt: lower C : N, higher specific ultraviolet absorbance and lower molecular weight of chromophoric DOM (CDOM; higher spectral slope ratio) were representative of relatively more decomposed DOM compared to that mobilized in summer and autumn. This shows that the decomposition of soil organic matter underneath a consistently deep snowpack is a key determinant of the composition of DOM mobilized from O horizons during winter and the hydrologically significant snowmelt period regardless of harvesting impact. Despite the higher proportion of aromatic DOM in the snowmelt samples, its lower molecular weight and rapid delivery from O to mineral horizons suggests that the snowmelt period is not likely to be a significant period of DOM sequestration by mineral soil. Rather, the higher-molecular-weight, high-C : N DOM mobilized during slow and relatively infrequent delivery during summer and rapid, frequent delivery during autumn are more likely to support periods of mineral soil sequestration and increased export of fresher terrestrial DOM, respectively. These observed seasonal dynamics in O horizon DOM suggest the predicted decreases in winter and spring snowfall and increasing autumn and winter rainfall with climate warming in this region will enhance mobilization of DOM that is more reactive to mineral interactions in deeper soil, but also more biological and photoreactive in the aquatic environment. Understanding the downstream consequences of this mobilized DOM in response to these shifts in precipitation timing and form can improve our ability to predict and manage forest C balance but requires understanding the response of landscape hydrology to these changing precipitation regimes.

Evaluating the Simulation of CONUS Precipitation by Storm Type in E3SM

AbstractConventional low‐resolution (LR) climate models, including the Energy Exascale Earth System Model (E3SMv1), have well‐known biases in simulating the frequency, intensity, and timing of precipitation. Approaches to next‐generation E3SM, whether the high‐resolution (HR) or multiscale modeling framework (MMF) configuration, improve the simulation of the intensity and frequency of precipitation, but regional and seasonal deficiencies still exist. Here we apply a methodology to assess the contribution of tropical cyclones (TCs), extratropical cyclones (ETCs), and mesoscale convective systems (MCSs) to simulated precipitation in E3SMv1‐HR and E3SMv1‐MMF relative to E3SMv1‐LR. Across the United States, E3SMv1‐MMF provides the best simulation in terms of precipitation accumulation, frequency and intensity from MCSs and TCs compared to E3SMv1‐LR and E3SMv1‐HR. All E3SMv1 configurations overestimate precipitation amounts from and the frequency of ETCs over CONUS, with conventional E3SMv1‐LR providing the best simulation compared to observations despite limitations in precipitation intensity within these events.

The removal of heavy metals from refinery effluents by sulfide precipitation

This study investigated the selective precipitation of copper (Cu2+), nickel (Ni2+) and zinc (Zn2+) ions from industrial wastewater by using sodium sulfide (Na2S). The effects of pH, time and free sulfide concentration on the selective precipitation were systematically investigated using synthetically prepared solutions and gold refinery wastewater. First, the optimum precipitation pH values of metals, the amount of Na2S and time were determined by using synthetic solutions containing Cu, Ni and Zn single metal ions. The highest precipitation efficiencies were obtained at a pH of 4, 5.3 and 5.3 for Cu, Ni and Zn, respectively. Based on these results, the effects of Na2S stoichiometry and time of precipitation were investigated with synthetically prepared solutions containing mixed metal ions (100 mg/L Cu2+, 90 mg/L Ni2+ and 100 mg/L Zn2+). Metal sulfide precipitation efficiencies increased with increasing amounts of Na2S and reached a maximum at a ratio of 1:1.75 (Metal ion: Na2S molar ratio). Lastly, the results obtained from the experiments performed with synthetic solutions were used for the metal sulfide precipitation from industrial wastewater. The precipitation from refining wastewater containing 10 g/L Cu2+, 0.3 g/L Ni2+ and 3 g/L Zn2+ ions was achieved at pH values from 2.3 to 5.3. At a pH of 2.3, Cu2+ precipitated as CuS (Cu2S) at 100% efficiency. While the Ni2+ concentration in the solution decreased by only 44% at a pH of 2.3, the Zn2+ concentration decreased by 52%. At a pH of 5.3, Cu2+ and Zn2+ precipitated together at 100%.

Added value of an atmospheric circulation pattern‐based statistical downscaling approach for daily precipitation distributions in complex terrain

AbstractReliable prediction of heavy precipitation events causing floods in a world of changing climate is crucial for the development of appropriate adaption strategies. Many attempts to provide such predictions have already been conducted but there is still much potential for improvement left. This is particularly true for statistical downscaling of heavy precipitation due to changes present in the corresponding atmospheric drivers. In this study, a circulation pattern (CP) conditional downscaling to the station level is proposed which considers occurring frequency changes of CPs. Following a strict circulation‐to‐environment approach we use atmospheric predictors to derive CPs. Subsequently, precipitation observations are used to derive CP conditional cumulative distribution functions (CDFs) of daily precipitation. Raw precipitation time series are sampled from these CDFs. Bias correction is applied to the sampled time series with quantile mapping (QM) and parametric transfer functions (PTFs) as methods being tested. The added value of this CP conditional downscaling approach is evaluated against the corresponding common non‐CP conditional approach. The performance evaluation is conducted by using Kling–Gupta Efficiency (KGE), root mean squared error (RMSE), and mean absolute error (MAE) metrics. In both cases the applied bias correction is identical. Potential added value can therefore only be attributed to the CP conditioning. It can be shown that the proposed CP conditional downscaling approach is capable of yielding more reliable and accurate downscaled daily precipitation time series in comparison to a non‐CP conditional approach. This can be seen in particular for the extreme parts of the distribution. Above the 95th percentile, an average performance gain of +0.24 and a maximum gain of +0.6 in terms of KGE is observed. These findings support the assumption of conserving and utilizing atmospheric information through CPs can be beneficial for more reliable statistical precipitation downscaling. Due to the availability of these atmospheric predictors in climate model output, the presented method is potentially suitable for downscaling precipitation projections.

A novel framework for spatiotemporal groundwater pumping process estimation based on data-driven approaches

Understanding the spatial and temporal distribution of pumping activities is crucial for effective water resource management. However, obtaining accurate pumping records is often challenging, particularly in areas without efficient groundwater withdrawal permit systems. In this study, we propose a novel approach for identifying pumping activities and estimating their associated pumping rates across space and time. Our data-driven approach integrates empirical orthogonal function (EOF) and Hilbert-Huang transform (HHT) analyses on first-differenced head data to extract high-frequency head variations that are closely related to pumping activities. The identified pumping-associated head variations are used to estimate the on-and-off times of local pumping stations and their associated pumping-rate time series. We test our approach using a hypothetical aquifer with designed pumping and real precipitation time series. Our results show that the EOF analysis is able to distinguish pumping locations where distinct temporal head variabilities are present. HHT analysis is then able to effectively remove noise from the EOF-identified pumping-associated head variations. Compared to the designed pumping data, our results demonstrate that our proposed method is able to produce accurate pumping estimates in terms of both spatial and temporal distribution and total amounts. While our approach does have limitations, such as delayed and boundary effects, our results suggest that it can be an effective tool for pumping estimation in areas with relatively abundant head observations across space and time, which is a common scenario in Taiwan.

Physical Metallurgy Guided Machine Learning for Strain‐Induced Precipitation of Nb (C, N) Based on the Orthogonalized Small Data

Strain‐induced precipitation (SIP) plays an important role in controlling the microstructure and properties of micro‐alloyed steels during hot rolling. However, due to lack of systematic experiments, the existing precipitation data are scarce and insufficient for accurate modeling of SIP behavior with good extrapolation. Herein, the data space of Niobium Carbonitride (Nb(C,N)) SIP kinetics is analyzed based on principle of orthogonal design, and the missing points in the orthogonal space are identified and supplemented in addition to the available data. The parameters in models for precipitation start and finish times are optimized by using the precipitation–time–temperature curves through genetic algorithm, and their relationships with compositions and processing conditions are established by support vector machine. Based on the orthogonally modified dataset, the machine learning (ML) models outperform the classical and ML models with the original data in terms of accuracy and are in good agreement with theoretical expectations. By using the new ML modeling, the evolution behavior of Nb (C, N) during hot deformation is predicted and verified with transmission electron microscope, and the influences of Nb content in steel, strain, strain rate, and the sensitivity of compositions and processing conditions on precipitation kinetics are quantitatively analyzed.