Precipitation Time Research Articles

Effect of Ru on the precipitation of the TCP phase from the γ-γʹ microstructural degradation analysis

This work investigates the effect of Ru on the precipitation of the topologically close-packed (TCP) phase from the γ-γʹ microstructural degradation analysis. The addition of Ru is found to delay the precipitation time of the TCP phase from 100 h to 1000 h after thermal exposure at 950 °C. The effect of Ru on the γ-γʹ microstructural degradation is also investigated. Adding Ru slightly decreases the coarsening rate of the γʹ size and promotes the reduction of the volume fraction of γʹ phase. The reduction of the volume fraction of γʹ phase causes the "inverse partitioning" effect and increases the solution limit of the TCP forming element in the matrix. These help inhibit the precipitation of the TCP phases in Ni-based single crystal superalloys during thermal exposure.

Effects of climate change on streamflow in the Dez Basin of Iran using the IHACRES model based on the CMIP6 model

Abstract Understanding the changes in river flow is an important prerequisite for designing hydraulic structures as well as managing surface water resources in basins. By using the LARS-WG statistical downscaling model, the outputs of the general circulation model of the sixth report, including the ACCESS-ESM1 and BCC-CSM-MR models, under the SSP5.8.5 and SSP2.4.5 release scenarios. A more accurate spatial scale and daily precipitation and temperature time series were obtained for the studied area during the period of 2015–2043. Then the IHACRES rainfall-runoff model was calibrated in the study area. Based on the fit statistics in the calibration and validation stages, the overall performance of the developed model was evaluated as satisfactory. The calibrated hydrological model was driven by rainfall data and reduced air temperature to predict the effect of climate change on the output of the studied basin. The study showed that the studied basin has more rainfall (on average, 20.8% in the ACCESS-ESM1 model and 33.2% in the BCC-CSM2-MR model). The flow rate of the main river in the ACCESS-ESM1 model will decrease by 15% compared to the base period, and in the BCC-CSM2-MR model, it will increase by 16% compared to the base period.

Formation of dolomites from the newly discovered ancient cold seep in the Middle Dongsha area of the South China Sea

Remotely operated vehicle (ROV) observations have recently revealed seep dolomite deposits covering the seafloor on Middle Dongsha of the South China Sea (SCS). Spurred by these findings, we studied the mineralogical and geochemical properties to examine the seep dolomite’s origin, precipitation mechanism, and formation environment. These carbonates mainly comprise dolomite (from 64 to 84 wt%), followed by small amounts of calcite (from 1 to 3 wt%), locally containing magnesite (∼4 wt%), and goethite (∼14 wt%). Extensively developed mineralized cells containing high Mg and Ca contents found in chimneys imply that microbially-mediated processes probably participated in the reactivation of dolomite precipitation. The moderate and concentrated δ13C values (from −36.64 to −39.16‰, V-PDB) indicated that the carbon in carbonates was mainly derived from thermogenic methane. The methane fluids most likely ascended beneath the volcaniclastic unit and inherited enriched positive Eu anomalies due to fluid–rock interactions during their seepage along tectonic faults to the seafloor. The δ18O values (4.2–4.8‰, V-PDB) of carbonate suggested that an 18O-depleted fluid was involved in carbonate precipitation. The high total Rare-Earth Element contents (ΣREE) of seep carbonates varied from 61 ppm to 92 ppm, reflecting the chemical composition of surrounding pore waters at the time of carbonate precipitation, exhibiting less mixing with seawater. It may also indicate higher alkalinity and pH of the pore water. Although the sea-like REE patterns (HREE-enriched, negative Ce anomalies) are not caused by seawater, they may be due to the complexation competition between humic acid (HA) and carbonate for REE at high pore-water alkalinity and high CO32− concentrations. This is consistent with the dolomite chimney pointing toward a formation environment in relatively deep sediments, in particular, close to the sulfate-methane interface in sediments, where the bicarbonate concentration reaches its maximum due to AOM. Moderate Mo and no U enrichments appeared in the carbonates, suggesting a relatively lower intensity of methane seepages with relatively reduced AOM rates. The wide range of (Mo/U)EF values and U–Mo covariation indicates the very dynamic AOM rate (slow to moderate) and redox conditions (mostly suboxic–anoxic, occasionally sulfidic conditions) during carbonate formation due to episodically changing seepage activity.

Precipitation behavior of calcium sulfate in leach solution of ion-adsorption rare earth ore after reverse osmosis

Ion-adsorption rare earth ore (IAREO) is a crucial source of mid-heavy rare earths elements (M-HRE). Reverse osmosis technology is a promising technique for the pre-concentration of the leach solution from in-situ leaching of IAREO. However, calcium sulfate scaling is inevitably formed in sulfate system, causing decreases in the flux and life time of membrane. Herein, to simulate the precipitation behavior of calcium sulfate in the leach solution of IAREO during reverse osmosis, a series of experiments was conducted in binary and quaternary supersaturated calcium sulfate solution systems. Experimental data show that the concentration of Ca2+ decreases with the increase of the concentration of Mg2+, and increases with the increase of the concentration of RE3+ in both binary and quaternary systems. Whereas, the influence of Al3+ on the concentration of Ca2+ is different. This variation of the Ca2+ concentration is explained by thermodynamic analysis. The difference of association concentration for Mg2+, Al3+ and RE3+ with SO42− in binary or quaternary system is the main reason. Finally, the influence and mechanisms of antiscalant on the precipitation behavior of calcium sulfate are discussed. X-ray diffraction (XRD), Zeta potential and scanning electron microscopy (SEM) analyses reveal that polyacrylic acid (PAA) effectively inhibits the crystal growth of calcium sulfate, and the precipitation time of calcium sulfate is prolonged, indicating that PPA is a potential inhibitor for calcium sulfate scaling during the process of reverse osmosis.

Hierarchical and Non- Hierarchical Cluster Classification of Precipitation Time Series Data in Nigeria

Precipitation is highly unpredictable over space and time, and is an indicator for climate change. The present work classified average yearly precipitation over the 36 states and the Federal Capital Territory (FCT) in Nigeria into various groups. The hierarchical and non- hierarchical (k-means) cluster method was used in the classification of 37- years precipitation data (1984-2020). The results showed that six major clusters were formed. The Precipitation across the 36 states and the FCT in Nigeria can be classified as Light precipitation for Sokoto, Borno, Kastina, Yobe and Kano States; Moderate precipitation for Kebbi, Zamfara, Dutse, Yola, Gombe and Bauchi States; Heavy precipitation for Kaduna, Plateau, Kwara, Taraba, Nassarawa, Benue and Kogi States; Very Heavy precipitation for Osun, Ogun, FCT, Ekiti, Niger and Lagos States; Shower for Edo, Abia, Delta, Anambra, Ebonyi, Enugu, Ondo and Oyo States and lastly, Heavy Shower for Akwaibom, Imo, Rivers, Bayelsa and Cross River States.. The rangs of precipitation based on the six classification are 1.5-1.8mm (Light precipitation), 1.9-2.7mm (Moderate precipitation), 2.8-3.6mm (Heavy precipitation), 3.7-4.3mm (Very Heavy precipitation), 4.4-5.4mm (Shower) and greater than 5.5mm (Heavy Shower). The hierarchical cluster method performed better than the non- hierarchical (k-means) cluster method in structuring the precipitation data and shaping it into groups (clusters) such that observations within the same group are more similar than those in different groups. The results of this study can contribute to a better understanding of the climate condition of the36 States and the FCT in Nigeria.

Investigating climatic and human effects on the decline in the groundwater level (a case study of the Kuhdasht plain)

Abstract This study has been investigated using the new criterion measuring complexity Hilbert-Huang entropy (HHE), changes, and fluctuations in groundwater levels under the influence of climate change factors and humans. In this regard, the 120-month time series of groundwater level, precipitation, temperature, and runoff parameters (period 2009–2018) are first divided into five 24-month periods, then by applying the Hilbert-Huang transform. Eachperiod is decomposed down into smaller periods, and finally, the HHE criterion measures the complexity of the time series. The examination of changes in the HHE complexity criterion shows a decrease of 2.02, 2.93, and 29.58% in the groundwater level in the second, third, and fourth periods. Also, according to the results of changes in the complexity of precipitation and temperature time series as climate change factors, these two parameters have decreased in the third and fourth periods, with the rate of decrease for the temperature time series being 18.8 and 8.3%, respectively, and for the precipitation time series is obtained by 30.6 and 4.4%, respectively. Hence, according to the results, the discharge parameter, as a human factor in the second and fourth periods, shows a decrease of 8.6 and 39.1%, respectively.

Ground deformation monitoring via PS-InSAR time series: An industrial zone in Sacco River Valley, central Italy

Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is an advanced technique enabling effective ground deformation monitoring. In this study, PS-InSAR time series of Sentinel-1 ascending and descending orbits for period 2015–2022 are utilized for an industrial zone in Sacco River Valley, Central Italy. The Sequential Turning Point Detection (STPD) is applied to estimate the trend turning points and their directions in PS-InSAR time series. In addition, river flow and climate time series for Sacco River near the industrial zone are analyzed using the coefficient of determination and the Least-Squares Cross-Wavelet Analysis (LSCWA) to investigate their potential impact on ground deformation. A significant land subsidence was observed prior to Fall 2016 likely as the result of drought and excessive water extraction followed by land uplift after Fall 2017 likely due to groundwater rebound. The LSCWA showed statistically significant seasonal coherency between precipitation and streamflow in 2018 when relatively much higher precipitation and streamflow were observed in this year compared to 2016 and 2017, potentially contributing to the land uplift in the study zone during 2018. These results not only highlight the capabilities of STPD for detecting trend turning points and LSCWA for analyzing streamflow and precipitation time series but also can help policymakers and stakeholders for developing a sustainable city and environment.

Relationships between current climate and deforestation on citrus productivity in Northeastern Pará (Eastern Amazon)

This study analyzed the temporal and spatial patterns of the precipitation (PRP) and maximum temperature (TMAX) time series of 37 municipalities proportionally distributed in the northeastern part of Pará (Eastern Amazon), from 1981 to 2018 (37 years). Environmental data on citrus productivity-PROD (oranges and lime) (IBGE), evapotranspiration (ET) and deforestation (PRODES) were used for the last 15 years to identify the impacts of climate change. The non-parametric approach, specifically the Mann-Kendall (MK) test and delta variation in the period 1989-2003 and 2004-2018 (15 years), were applied to estimate annual and seasonal trends and detect variations after using heatmap and boxplots. To compose the climate change study, Principal Component Analysis (PCA) was applied to environmental variables and Principal Component Regression (PCR) was used to test the hypothesis. The results showed an increasing positive trend in the annual and seasonal TMAX time series over 37 years, with the most significant trends in the dry season. The trend results in PRP, on the other hand, showed regions with both negative and positive trend significance. On annual and seasonal scales, regions such as R5 in northeastern Pará showed positive trends. On the other hand, negative trends of decreasing PRP were observed in the coastal areas of Pará (R1 and R3). Based on PCA and PCR results, deforestation data are associated with higher maximum temperatures and orange productivity follows correlated with PRP and ET. In contrast, PRP and ET are considered limiting factors for lime productivity.

The Spatio-Temporal Dynamics of Water Resources (Rainfall and Snow) in the Sierra Nevada Mountain Range (Southern Spain)

This paper describes the use of a unique spatio-temporally resolved precipitation and temperature dataset to assess the spatio-temporal dynamics of water resources over a period of almost seven decades across the Sierra Nevada mountain range, which is the most southern Alpine environment in Europe. The altitude and geographical location of this isolated alpine environment makes it a good detector of climate change. The data were generated by applying geostatistical co-kriging to significant instrumental precipitation and temperature (minimum, maximum and mean) datasets. The correlation between precipitation and altitude was not particularly high and the statistical analysis yielded some surprising results in the form of mean annual precipitation maps and yearly precipitation time series. These results confirm the importance of orographic precipitation in the Sierra Nevada mountain range and show a decrease in mean annual precipitation of 33 mm per decade. Seasonality, however, has remained constant throughout the period of the study. The results show that previous studies have overestimated the altitudinal precipitation gradient in the Sierra Nevada and reveal its complex spatial variability. In addition, the results show a clear correspondence between the mean annual precipitation and the NAO index and, to a much lesser extent, the WeMO index. With respect to temperature, there is a high correlation between minimum temperature and altitude (coefficient of correlation = −0.84) and between maximum temperature and altitude (coefficient of correlation = −0.9). Thus, our spatial temperature maps were very similar to topographic maps, but the temporal trend was complex, with negative (decreasing) and positive (increasing) trends. A dynamic model of snowfall can be obtained by using the degree-day methodology. These results should be considered when checking the local performance of climatological models.

Influence of Spring Water Residence Time on the Irrigation Water Stability in the Hani Rice Terraces

The stability of irrigation water is critical for the sustainability of alpine agriculture. Based on monthly precipitation and terraced field water and spring water samples obtained between 2015 and 2016, the study used the mean residence time and isotope mixing model to analyze the influence of spring water residence time on irrigation water stability in the Hani Rice Terraces. The results indicate that: (1) The mean residence time of precipitation and terraced field water in spring water was 2.46 years and 1.55 years, respectively, implying that the terraced field’s irrigation water source could be refilled by spring water recharged 1.5–2.5 years ago. (2) The mean residence time of precipitation in ascending and descending springs was 2.73 years and 1.95 years, respectively. The mean residence time of terraced field water in ascending and descending springs was 1.54 years and 1.04 years, respectively. The ascending spring’s recharge water residence time is 0.5–0.8 years longer than that of the descending spring, indicating that the spring water exhibits intra-seasonal and inter-seasonal staggered peak recharging. At the same time, the total recharge period of the ascending–descending spring is extended to 1–3 years, which means the terraced fields have a drought resistance of three years. (3) The mean residence time of precipitation and terraced field water at higher altitudes in the ascending spring is 2.52 times and 3.73 times, respectively, while in the descending spring, it is 3.36 times and 6.49 times to the lower altitude region. This means that the mean residence time of the recharge water source in the lower terraced fields was shorter, and the elevation difference between ascending and descending springs was smaller, thereby regulating the spatial homogeneous distribution of recharge water sources in the terraced fields.

Improving precipitation estimates for Turkey with multimodel ensemble: a comparison of nonlinear artificial neural network method with linear methods

AbstractEnsemble analysis is proven to provide advantages in climate change impact assessment based on outputs from climate models. Ensembled series are shown to outperform single-model assessments through increased consistency and stability. This study aims to test the improvement of precipitation estimates through the use of ensemble analysis for south and southwestern Turkey which is known to have complex climatic features due to varying topography and interacting climate forcings. The analysis covers an evaluation of the performance of eight regional climate models (RCMs) from the EUR-11 domain available from the CORDEX database. The historical outputs are evaluated for their representativeness of the current climate of the Mediterranean region and its surroundings in Turkey through a comparison with long-term monthly precipitation time series obtained from ground-based precipitation observations by the use of statistical performance indicators and Taylor diagrams. This is followed by a comparative evaluation of three ensemble methodologies, simple average of the models, multiple linear regression for superensemble, and artificial neural networks (ANN). The analysis results show that the overall performance of ensembled time series is better compared to individual RCMs. ANN generally provided the best performance when all RCMs are used as inputs. Improvement in the performance of ensembling due to the use of nonlinear models is further confirmed by fuzzy inference systems (FIS). Both ANN and FIS generated monthly precipitation time series with higher correlations with those of observations. However, extreme events are poorly represented in the ensembled time series, and this may result in inefficiency in the design of various water structures such as spillways and storm water drainage systems that are based on high return period events.

Timing and Mechanism of Ore Precipitation in Porphyry Cu Systems: Insight from LA-ICP-MS Analysis of Fluid Inclusions and In Situ Oxygen Isotope Analysis of Hydrothermal Quartz at Zhunuo Porphyry Cu Deposit, China

Abstract The timing and mechanism of ore precipitation in porphyry copper systems are hot topics and remain controversial. The large Miocene collision-related Zhunuo porphyry Cu deposit in the Gangdese belt of southern Tibet, China, was produced by multistage quartz veining and hydrothermal alteration, accompanied by Cu sulfide precipitation. In this study, we have combined cathodoluminescence (CL) petrography with in situ oxygen isotope analysis and fluid inclusion microthermometry and laser ablation-inductively coupled plasma-mass spectrometer microanalysis to constrain the growth history of individual quartz veins, the source and evolution of the hydrothermal fluids, and the timing and mechanism of ore precipitation at Zhunuo. Early quartz A veins associated with potassic alteration are composed of quartz, K-feldspar, biotite, Cu-Fe sulfides, and pyrite. Quartz B veins are composed of quartz, Cu-Fe sulfides, molybdenite, and pyrite. CL imaging shows that quartz grains in the A and B veins consist of abundant early generation of bright-luminescent quartz (QA and QB) with volumetrically minor later generation of dull-luminescent quartz (QA-crack and QB-crack) occurring in the voids or at the margins of the QA and QB veins with embayed contacts. Cu-Fe sulfides are generally in contact with the dull-luminescent quartz and locally in contact with the bright-luminescent quartz and K-feldspar in the A and B veins or occur as disseminations in the potassic-altered porphyries that have been overprinted by chlorite ± muscovite alteration. QA and QB contain single-phase intermediate-density inclusions and abundant brine and vapor-rich inclusions. A boiling assemblage in QA has a homogenization temperature of ~560°C and trapping pressure of ~530 bar. Two boiling assemblages in QB have homogenization temperatures of ~440°C with trapping pressures of ~230 and ~250 bar, indicating a transition from lithostatic to hydrostatic conditions at a paleodepth of ~2.0 to 2.5 km. QA-crack and QB-crack contain aqueous inclusions with lower homogenization temperatures of 340° to 400°C and salinities of 6 to 12 wt % NaCl equiv. In situ oxygen isotopes indicate that QA and QB have δ18O values of 7.6 to 11.4‰, whereas QA-crack and QB-crack have δ18O values of –7.2 to 6.7‰. Combined with fluid inclusion compositions, we propose that condensation of vapors into brines and mixing with 25 to 60% meteoric water can produce the salinity and oxygen isotopes of fluids that caused the dissolution of the early bright-luminescent quartz and the precipitation of the later dull-luminescent quartz. Zhunuo Cu-Fe sulfides are in contact with the bright-luminescent quartz and cut the growth bands. The dull-luminescent quartz in contact with the Cu-Fe sulfides has oscillatory growth banding. In addition, Cu-Fe sulfides in the A and B veins or in the potassic-altered rocks coexist with chlorite ± muscovite alteration minerals. These geologic observations, together with evidence that there is an abrupt drop in the Cu/(Na + K) ratio by more than one order of magnitude in the aqueous fluids within the dull-luminescent quartz compared to the brines within the bright-luminescent quartz, indicate that precipitation of Cu-Fe sulfides occurred after the potassic alteration stage and during the chlorite ± muscovite alteration stage. Ore precipitation was associated with mixing of magmatic fluids (brines + vapors) with meteoric water, accompanied by fluid cooling, salinity decrease, and retrograde quartz solubility as the rocks transitioned from lithostatic to hydrostatic conditions. During continued cooling in the latest stage, the hydrothermal fluids precipitated D veins that contain abundant pyrite with minor quartz. Quartz in the D veins (QD) contains aqueous inclusions with much lower temperatures and Cu/(Na + K) ratios, indicating that most of the Cu-Fe sulfides have been precipitated during this stage.

The Role of Temperature, Wind Speed, and Precipitation on the Abundance of Culex Species and West Nile Virus Infection Rate in Rural West-Central Illinois.

While most research on West Nile virus (WNV) and its main vector, the Culex mosquito, has been conducted in laboratory or urban settings, studies with field-caught mosquitoes in rural areas, such as west-central Illinois, are lacking. The objective of this research was to investigate key abiotic factors using macroclimate data, including temperature, precipitation, and wind speed, to determine their influence on field-caught mosquito abundance in 4 rural counties in Illinois from 2014 to 2016. Additionally, the relationship between minimum infection rate (MIR) and thermal time was examined. Using gravid traps at 15 sites, Culex mosquitoes were collected twice a week. A total of 5,255 adult female Culex mosquitoes (Cx. pipiens, Cx. quinquefasciatus, and Cx. restuans) were collected in 2014; 9,138 in 2015; and 5,702 in 2016. Regression models were developed based on outcomes of relationships between field-caught mosquitoes and abiotic factors. Precipitation and thermal time had the most significant relationship with mosquito abundance (r2 = 0.993 and r2 = 0.993, respectively), while wind speed was less (r2 = 0.714). The greatest number of Culex and the highest annual MIR were observed in 2015, which was also the driest of the 3 sampling seasons. Mosquito abundance was observed to increase with warmer degree days and MIR was found to increase with abundance in mosquitoes. These models can be used for other mosquito surveillance and monitoring studies in various climate types and environments.

Elastic deformation as a tool to investigate watershed storage connectivity

Storage-discharge relationships and dynamic changes in storage connectivity remain key unknowns in understanding and predicting watershed behavior. In this study, we use Global Positioning System measurements of load-induced Earth surface displacement as a proxy for total water storage change in four climatologically diverse mountain watersheds in the western United States. Comparing total water storage estimates with stream-connected storage derived from hydrograph analysis, we find that each of the investigated watersheds exhibits a characteristic seasonal pattern of connection and disconnection between total and stream-connected storage. We investigate how the degree and timing of watershed-scale connectivity is related to the timing of precipitation and seasonal changes in dominant hydrologic processes. Our results show that elastic deformation of the Earth due to water loading is a powerful new tool for elucidating dynamic storage connectivity and watershed discharge response across scales in space and time.

Validation of global precipitation time series products against tree ring records and remotely sensed vegetation greenness.

Global interpolated climate products are widely used in ecological research to investigate biosphere-climate interactions and to track ecological response to climate variability and climate change. In turn, biological data could also be used for an independent validation of one aspect of climate data quality. All else being equal, more variance explained in biological data identifies the better climate data product. Here, we compare seven global precipitation time series products, including gauge-based datasets (CRU-TS, UDEL-TS, GPCC), re-analysis products (ERA5, CHELSA), a satellite-based dataset (PERSIANN) and a multi-source product that draws on gauge, re-analysis, and satellite data (MSWEP). We focus on precipitation variables, because they are more difficult to interpolate than temperature, and show larger divergence among gridded data products. Our validation is based on 20 years of remotely sensed vegetation greenness (MODIS-EVI) and 120 years of tree ring records from the International Tree Ring Data Bank (ITRDB). The results for the 20-year EVI based validation shows that all gauge and re-analysis data products performed similarly, but were outperformed by the multi-source MSWEP product, especially in regions with low weather station coverage, such as Africa. For analyzing long 120-year time-series, UDEL-TS showed superior performance prior to the 1940s, with especially large margins for northern Asia and the Himalayas region. For other regions, CRU-TS and GPCC could be recommended. We provide maps that can guide the best regional choice of climate product for research involving time series of biological response to historic climate variability and climate change.

The impact of tropical cyclones and water conservancy projects on island's flash floods.

The analysis of the influencing factors of flash floods, one of the most destructive natural disasters, is the basis of scientific disaster prevention and mitigation. There is little research considering the influence of tropical cyclones (TCs) and water conservancy projects on flash floods, which cannot be ignored in the island areas where flash floods often occur due to the complex influence of various factors. In this study, under the pressure-state-response framework (PSR framework), the factors affecting the distribution of flash floods on Hainan Island, China, from 1970 to 2010 were quantitatively analyzed by using the geographical detector method. By dividing the time period, give full play to the advantages of the PSR framework and show the evolution process of various factors. Different from inland areas, extreme precipitation and tropical cyclones play a major role in the spatial distribution of flash floods on Hainan Island, China, and the driving force of tropical cyclones is 1.1 times that of extreme precipitation on average. Medium-sized reservoirs play the greatest role in the prevention of flash floods on Hainan Island, and their driving forces reach 0.38 times of extreme precipitation on average, followed by large-sized reservoirs and small-sized reservoirs. Large-sized reservoirs are limited in quantity and have limited effectiveness in preventing flash floods on Hainan Island. Therefore, in the forecasting and risk management of flash flood in the island area, more attention should be paid to the impact of extreme precipitation and TCs, and the role of medium-sized reservoir should be fully exerted.

Study of the influence of crystallisation companions on the oxidation - precipitation of Fe2+ applied to the synthetic water of Dan Daji -Illela (Tahoua -Niger)

The elimination of iron by the oxidation-precipitation technique applied to Dan Daji water requires the study of the influence of certain parameters that frequently coexist with iron in water, such as Ca2+, Mg2+, Na+ , K+, SO42-, HCO3-, CO32- and NO3-. The use of natural water does not make this study possible. To overcome this limitation, synthetic water was adopted to study the influence of these parameters on iron precipitation. For the needs of this study, the physico-chemical characteristics of the synthetic groundwater are identical to those of the Dan Daji drilling. All the experiments were carried out in a 1000 mL beaker with stirring to allow contact with atmospheric oxygen for a precipitation time of 60 minutes. Among the ions that accompany Fe2+ precipitation, certain ions such as HCO3-, Ca2+, K+ and Mn2+ promote the precipitation of iron to Fe(OH)3. On the contrary, other ions such as Mg2+, SO42- and NO3- inhibit the formation of Fe(OH)3.

Assessment of the Spraying System Impact at the Preparation Stage of Iron Ore Concentrate Products

Introduction. Harmful components of ore dust, formed during the unloading of products in the preparation of iron ore concentrate (PPIOC) at the mixing stage, cause damage to both workers and equipment. To address this issue, liquid aerosol spraying using nozzles with large diameters (>20 μm) is used. However, this method proves ineffective in capturing fine-dust particles. Therefore, enhancing the efficiency of the dust deposition method through PPIOC dust spraying becomes a pressing challenge. The aim of this study is to investigate the impact of the Dry Fog technology, generating liquid droplets up to 20 μm in size, during the unloading stage of PPIOC at a mining and metallurgical enterprise in the precipitation of suspended fine-dust particles. The primary goal of this research was to assess the effectiveness and potential advantages of applying the Dry Fog technology for dust spraying with subsequent precipitation, as this technology has not been previously applied to PPIOC dust.Materials and Methods. The experiment on the PPIOC dust deposition was conducted in a specially designed laboratory setup. Through physical modeling in the laboratory setup, parameters of the precipitation process were obtained. Subsequently, the results were analyzed to understand the dependence of dust precipitation over time, taking into account the influence of the Dry Fog technology. An experiment program was developed for physical modeling. According to the devised program, dust was uniformly loaded into the interior of the laboratory setup (from the top), distributed in the air stream throughout the volume of the setup by a fan, and an instrument located at the bottom recorded changes in concentration over time. Experiments on dust precipitation were then conducted using liquid spraying (filtered water as the liquid) introduced into the setup through nozzles generating droplets with sizes of 10 and 15 μm, concurrently with the loading of dust into the laboratory setup. The effectiveness of the Dry Fog technology in the deposition of PPIOC dust was determined visually and further analyzed based on a comparison of graphs. The dynamics of changes in the average dust concentrations depending on time was studied both during precipitation without spraying and using the Dry Fog technology. During the experiment, the characteristics of the microclimate inside the laboratory setup (humidity, temperature and air velocity) and the parameters of two nozzles — their operating pressure and the supplied liquid spraying time — were recorded.Results. The comparison of the results showed a reduction in the dust precipitation time by 40 % and 75 % when using nozzles with sizes of 10 μm and 15 μm, respectively.Discussion and Conclusion. The experiment results confirm the effectiveness of the Dry Fog technology for PPIOC dust precipitation during unloading at the mixing stage. Fundamental findings have been obtained, providing a basis for further assessment of the efficiency of dust precipitation with the additional application of pulsating ventilation. In such a combination, an additional 20–25 % increase in precipitation efficiency is anticipated compared to the results presented in this article. The obtained results will support the justification of rational parameters and the implementation of the described method in production to enhance dust precipitation efficiency. Additionally, they will aid in developing a methodology to accelerate the PPIOC dust precipitation using the pulsating ventilation method.

A variance-upscaling quantile mapping method for gridded precipitation bias correction

Accurate estimation of precipitation in mountainous regions remains a challenge. Quantile Mapping (QM) is a method used extensively to correct gridded precipitation from numerical models or satellite remote sensing. The method can match the intensity histogram of a given gridded precipitation to that of the observation. However, the widely existing oversmoothed effect, a precipitation time series variability representativeness error, in observational gridded datasets may be inherited in the corrected results, impacting the assessment of extreme precipitation events. To address this issue, this study introduces a variance-upscaling QM method (VUQM). Unlike previous methods that obtain frequency parameters by interpolating rain gauge data, the new method creates a model to transform the precipitation time series variance at the rain gauge point level to the model's grid level. When compared to correct ERA5-Land reanalysis precipitation, the results show that the variance using the VUQM is 1.6 times larger than that obtained using QM alone, and it is 2 times larger in the 95th percentile. This indicates that the new method significantly reduces the oversmoothed effect and preserves precipitation variation. Random simulations show that low station density only introduces uncertainty, not theoretical bias in VUQM. In contrast, the variance biases in gridded datasets constructed from areal average or interpolation cannot be avoided, particularly in regions with significant spatial heterogeneity. This suggests that VUQM is well-suited for use in the Qinghai-Tibetan Plateau (QTP) compared with the old methods. Overall, this method sheds some light on mountainous precipitation bias correction.

What controls the tail behaviour of flood series: rainfall or runoff generation?

Abstract. Many observed time series of precipitation and streamflow show heavy-tail behaviour. For heavy-tailed distributions, the occurrence of extreme events has a higher probability than for distributions with an exponentially receding tail. If we neglect heavy-tail behaviour we might underestimate the magnitude of rarely observed, high-impact events. Robust estimation of upper-tail behaviour is often hindered by the limited length of observational records. Using long time series and a better understanding of the relevant process controls can help with achieving more robust tail estimations. Here, a simulation-based approach is used to analyse the effect of precipitation and runoff generation characteristics on the upper tail of flood peak distributions. Long, synthetic precipitation time series with different tail behaviour are produced by a stochastic weather generator. These are used to force a conceptual rainfall–runoff model. In addition, catchment characteristics linked to a threshold process in the runoff generation are varied between model runs. We characterize the upper-tail behaviour of the simulated precipitation and discharge time series with the shape parameter of the generalized extreme value (GEV) distribution. Our analysis shows that runoff generation can strongly modulate the tail behaviour of flood peak distributions. In particular, threshold processes in the runoff generation lead to heavier tails. Beyond a certain return period, the influence of catchment processes decreases and the tail of the rainfall distribution asymptotically governs the tail of the flood peak distribution. Beyond which return period this is the case depends on the catchment storage in relation to the mean annual rainfall amount.