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1

Acceleration of the hydrological cycle and its impact on water availability over land: an adverse effect of climate change

Ehtasham Laraib, Sherani Sadia Hassan, Nawaz Faheem

Meteorology Hydrology and Water Management. Research and Operational Applications

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2024

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Vol. 12, Iss. 1

1--21

EN

The hydrological cycle, or water cycle, is one of the most important geochemical cycles on our planet. Normal functioning of its mechanisms (evaporation/evapotranspiration, condensation, and precipitation) is very important for the well-being of human beings. However, the acceleration of the hydrological cycle, mainly due to global warming, is increasing the frequency and intensity of extreme events (floods, droughts, and alterations in water resources) in many regions around the globe. This acceleration or intensification occurs because of rising temperature, which intensifies and speeds up evaporation (probable increase of 5.2%) and precipitation (probable increase of 6.5%); hence this scenario is escalating climate change. According to the datasets retrieved from the Global Land Data Assimilation System (GLDAS) of NASA, rain precipitation rate has shown changes in various regions of the world. Consequently, extreme and frequent events of heavy precipitation, floods, and droughts are also deteriorating the quality of water and preventing recharge of water reservoirs. Although some regions of the world will experience positive outcomes of this scenario in terms of water availability (due to frequent intense precipitation), most of the world’s regions are expected to face the daunting issue of water unavailability, as predicted by many researchers.

2

The effect of meteorological conditions on the course of development stages and yield of winter wheat in southern Poland

Skowera Barbara, Kulig Bogdan, Ziernicka-Wojtaszek Agnieszka, Grygierzec Wiesław, Ziółkowska Elżbieta, Lepiarczyk Andrzej

Journal of Water and Land Development

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2024

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no. 60

157--166

EN

Yield and the course of crop vegetation are the result of the interaction between the level of cultivation technology and the course of meteorological conditions, which are a variable production factor. The aim of the study was to quantify the effect of meteorological conditions on the course of development stages and yield of winter wheat cultivated in two technological variants (A1 - medium-intensive and A2 - intensive). The paper uses data on yield and timing of winter wheat development stages from four Experimental Stations for Variety Testing (Pol. Centralny Ośrodek Badania Odmian Roślin Uprawnych - COBORU) experimental stations from 2007-2016 located within the Upper Vistula and Upper Oder River basins. To determine the dependence of the length of development stages of winter wheat on the values of selected meteorological elements, the linear regression metod, correlation coefficient. It was found that the lengths of the selected developmental stages are positively correlated with air temperature and negatively correlated with the sum and number of days with precipitation in these stages. A 1°C increase in air temperature resulted in a shortening of the shooting - heading and heading - full maturity periods by 2.5 and 2.8 days respectively. An increase of 100 mm of precipitation in the periods sowing - full maturity and heading - full maturity resulted in an increase of these periods by 5 and 10 days. Increasing the number of days with precipitation by 10 days in the sowing - full maturity and heading - vax maturity stages resulted in extending these stages by 4.1 to 4.4 and 7 to 7.5 days for the A1 and A2 cropping technologies, respectively.

3

Characteristic of regional groundwater flow system: case modeling study in Longzici karst spring area, North China

Qiao Xiaojuan, Cheng Yu, Wang Dawei

Acta Geophysica

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2024

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Vol. 72, no. 1

323--339

EN

Karst spring water dynamic characteristics and its response to atmospheric precipitation are of great significance for water resources utilization under the background of climate change. This paper selects Longzici spring area, North China, as the study area. Based on a long series of spring water flow and precipitation data, the dynamic characteristics of spring flow were analyzed and the numerical simulation of the groundwater flow model was established. The results show that the groundwater kept the sustained decline over the past decades which is in a negative equilibrium state, with a storage variable of - 2.26 million m3/year. The sensitivity of spring flow to precipitation under different precipitation scenarios shows that the water level changes in the recharge and drainage areas are similar about (3-5 cm) and slightly larger than that in the runoff area(1.5 cm) when minimum rainfall (287.24 mm) happens. When the precipitation is at its maximum (867.66 mm), the water level change in the runoff area can reach 95 cm which is much larger than those in the recharge and discharge areas. The results indicate that Longzici karst spring has a relatively good regulation water resource capacity and the runoff area is more sensitive which plays an important role in response to climate change.

4

Seasonality and long-term trends of NDVI values in different land use types in the eastern part of the Baltic Sea basin

Klimavičius Laurynas, Rimkus Egidijus, Stonevičius Edvinas, Mačiulytė Viktorija

Oceanologia

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2023

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Vol. 65 (1)

171--181

EN

This study analyses changes in Normalized Difference Vegetation Index (NDVI) values in the eastern Baltic region. The main aim of the work is to evaluate changes in growing season indicators (onset, end time, time of maximum greenness and duration) and their relationship with meteorological conditions (air temperature and precipitation) in 1982–2015. NDVI seasonality and long-term trends were analysed for different types of land use: arable land, pastures, wetlands, mixed and coniferous forests. In the southwestern part of the study area, the growing season lasts longest, while in the northeast, the growing season is shorter on average by 10 weeks than in the other parts of the analysed territory. The air temperature in February and March is the most important factor determining the start of the growing season and the air temperature in September and October determines the end date of the growing season. Precipitation has a much smaller effect, especially at the beginning of the growing season. The effect of meteorological conditions on peak greenness is weak and, in most cases, statistically insignificant. At the end of the analysed period (1982–2015), the growing season started earlier and ended later (in both cases the changes were 3–4 weeks) than at the beginning of the study period. All these changes are statistically significant. The duration of the growing season increased by 6–7 weeks.

5

Long-term precipitation events in the eastern part of the Baltic Sea region

Mačiulytė Viktorija, Rimkus Egidijus, Valiukas Donatas, Stonevičius Edvinas

Oceanologia

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2023

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Vol. 65 (1)

141--150

EN

Precipitation anomalies have a significant impact on both natural environmental and human activity. Long lasting drought analysis has received great attention on a global and regional scale while prolonged rainy periods so far have been much less studied. However, long-term precipitation events are also important and threatening. The situation around the Baltic Sea in 2017 revealed that such periods could cause significant losses in agriculture. The rainy periods of 30, 60, and 90 consecutive days in a given year during which the maximum precipitation amount was recorded in the eastern part of the Baltic Sea region were analysed in this study. Daily precipitation amount data from the E-OBS gridded dataset was used. The investigation covered a period from 1950 to 2019. The changes in magnitude and timing of such rainy periods were evaluated. It was found that the annual precipitation in the eastern part of the Baltic Sea region increased significantly during the analysed period. Positive changes were observed throughout the year except during April and September. The amounts of precipitation during rainy periods of different duration also increased in most of the investigated areas but changes were mostly insignificant. Consequently, a decrease in the ratio of precipitation amount during the rainy period to annual precipitation was observed. It was also found that the rainy periods occurred earlier, especially in the case of the rainy periods of 60- and 90-days durations. Such tendencies pose an increasing threat to agriculture.

6

Comparison and combination of interpolation methods for daily precipitation in Poland: evaluation using the correlation coefficient and correspondence ratio

Konca-Kędzierska Krystyna, Wibig Joanna, Gruszczyńska Marta

Meteorology Hydrology and Water Management. Research and Operational Applications

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2023

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Vol. 11, Iss. 2

1--27

EN

Interpolation of precipitation data is a common practice for generating continuous, spatially-distributed fields that can be used for a range of applications, including climate modeling, water resource management, and agricultural planning. To obtain the reference field, daily observation data from the measurement network of the Institute of Meteorology and Water Management – National Research Institute was used. In this study, we compared and combined six different interpolation methods for daily precipitation in Poland, including bilinear and bicubic interpolation, inverse distance weighting, distance-weighted average, nearest neighbor remapping, and thin plate spline regression. Implementations of these methods available in the R programming language (e.g., from packages akima, gstat, fields) and the Climate Data Operators (CDO) were applied. The performance of each method was evaluated using multiple metrics, including the Pearson correlation coefficient (RO) and the correspondence ratio (CR), but there was no clear optimal method. As an interpolated resulting field, a field consisting of the best interpolations for individual days was proposed. The assessment of daily fields was based on the CR and RO parameters. Our results showed that the combined approach outperformed individual methods with higher accuracy and reliability and allowed for generating more accurate and reliable precipitation fields. On a group of selected stations (data quality and no missing data), the precipitation result fields were compared with the fields obtained in other projects-CPLFD-GDPT5 (Berezowski et al. 2016) and G2DC-PLC (Piniewski et al. 2021). The variance inflation factor (VIF) was bigger for the resulting fields (~5), while for the compared fields, it was below 3. However, for the mean absolute error (MAE), the relationship was reversed - the MAE was approximately half as low for the fields obtained in this work.

7

Assessing the impact of climate change on discharge in the Horyn River basin by analyzing precipitation and temperature data

Lobodzinskyi Oleksandr, Vasylenko Yevheniia, Koshkina Olha, Nabyvanets Yurii

Meteorology Hydrology and Water Management. Research and Operational Applications

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2023

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Vol. 11, Iss. 1

93--106

EN

It is important to investigate the hydrological consequences of current climate change. Hydrological responses to climate warming and wetter conditions include changes in discharge (frequency, amplitude, and volume). This paper describes current climate change and its impact on hydrological flow within the Horyn River basin. Daily air temperature and precipitation data obtained from the 17 meteorological stations located in and nearby the Horyn River basin, in combination with hydrological data (such as daily water discharges obtained from 9 water gauges), were used for the analysis of climate variability and its hydrological consequences. Analyses of meteorological variables and water discharges are crucial for the assessment of long-term changes in the river regime. Thiessen polygons were used to determine the area of influence of assigned specific meteorological stations, which affect the river’s catchments within the Horyn River basin. As a result of the trend analysis, it was observed that discharge within the Horyn River basin decreased over time. These results were congruent with the trends of precipitation data and air temperature data of the stations determined by the Thiessen polygons and basin boundaries. To understand current changes in the daily flow in the basin, changes in air temperature and precipitation for the period 1991-2020 were compared with the period of the climatic norm (1961-1990). A similar analysis was done for daily water discharges. Increasing air temperature and decreasing precipitation in the current period led to a significant decrease in discharges in the Horyn River basin, especially during the spring flood period.

8

Machine learning for supporting irrigation decisions based on climatic water balance

Treder Waldemar, Klamkowski Krzysztof, Wójcik Katarzyna, Tryngiel-Gać Anna

Journal of Water and Land Development

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2023

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no. 58

25--30

EN

A machine learning model was developed to support irrigation decisions. The field research was conducted on ‘Gala’ apple trees. For each week during the growing seasons (2009-2013), the following parameters were determined: precipitation, evapotranspiration (Penman-Monteith formula), crop (apple) evapotranspiration, climatic water balance, crop (apple) water balance (AWB), cumulative climatic water balance (determined weekly, ∑CWB), cumulative apple water balance (∑AWB), week number from full bloom, and nominal classification variable: irrigation, no irrigation. Statistical analyses were performed with the use of the WEKA 3.9 application software. The attribute evaluator was performed using Correlation Attribute Eval with the Ranker Search Method. Due to its highest accuracy, the final analyses were performed using the WEKA classifier package with the J48graft algorithm. For each of the analysed growing seasons, different correlations were found between the water balance determined for apple trees and the actual water balance of the soil layer (10-30 cm). The model made correct decisions in 76.7% of the instances when watering was needed and in 87.7% of the instances when watering was not needed. The root of the classification tree was the AWB determined for individual weeks of the growing season. The high places in the tree hierarchy were occupied by the nodes defining the elapsed time of the growing season, the values of ∑CWB and ∑AWB.

9

A data-driven approach to predict hydrometeorological variability and fluctuations in lake water levels

Tan Kesgin Remziye I., Demir Ibrahim, Kesgin Erdal, Abdelkader Mohamed, Agaccioglu Hayrullah

Journal of Water and Land Development

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2023

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no. 58

158--170

EN

Beyşehir Lake is the largest freshwater lake in the Mediterranean region of Turkey that is used for drinking and irrigation purposes. The aim of this paper is to examine the potential for data-driven methods to predict long-term lake levels. The surface water level variability was forecast using conventional machine learning models, including autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA), and seasonal autoregressive integrated moving average (SARIMA). Based on the monthly water levels of Beyşehir Lake from 1992 to 2016, future water levels were predicted up to 24 months in advance. Water level predictions were obtained using conventional time series stochastic models, including autoregressive moving average, autoregressive integrated moving average, and seasonal autoregressive integrated moving average. Using historical records from the same period, prediction models for precipitation and evaporation were also developed. In order to assess the model’s accuracy, statistical performance metrics were applied. The results indicated that the seasonal autoregressive integrated moving average model outperformed all other models for lake level, precipitation, and evaporation prediction. The obtained results suggested the importance of incorporating the seasonality component for climate predictions in the region. The findings of this study demonstrated that simple stochastic models are effective in predicting the temporal evolution of hydrometeorological variables and fluctuations in lake water levels.

10

The Influence of the Gray Forest Soil Moisture Level on the Accumulation of Pb, Cd, Zn, Cu in Spring Barley Grain

Razanov Serhii, Husak Oksana, Hnativ Petro, Dydiv Andrii, Bakhmat Oleh, Stepanchenko Vitalii, Pryshchepa Alla, Shcherbachuk Victor, Mazurak Oksana

Journal of Ecological Engineering

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2023

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Vol. 24, nr 7

285--292

EN

Among a number of climate-related factors, moisture has the greatest impact on crop productivity. In recent years, certain changes have been observed under conditions of the Forest-Steppe of Ukraine with regard to precipitation – from low to in some cases – abnormally high, which requires the study of their impact on the yield and safety of cereal grain for its forecasted production. The article examined the effect of a high level of soil moisture (256.2–272.5 mm) and a low level (47.4–52.3 mm) during the growing season (germination→earing) of spring barley grain on the accumulation of heavy metals in it and its productivity under the conditions of gray forest soils of the Right Bank Forest Steppe of Ukraine. Spring barley varieties Helios and Caesar were selected for the research. A decrease in the accumulation coefficient at a high level of soil moisture (256.6–272.5 mm) in spring barley grain Pb from 8.3% to 11.3%, Cd – from 35.0% to 35.5%, Zn was established – by 15% and Cu – from 11.2% to 16.6% compared to the low level of soil moisture (47.1 mm – 53.3 mm). At the same time, it was found that with a high level of soil moisture, there is a decrease in the yield of Helios and Caesar spring barley by 18.0% and 14.1%, respectively.

11

Accumulation of Lead and Cadmium by Vegetables at Different Levels of Gray Forest Soil Moistening in the Conditions of the Right Bank Forest Steppe of Ukraine

Dydiv Andrii, Piddubna Antonina, Gucol Galina, Vradii Oksana, Zhylishchych Yustyna, Titarenko Olga, Razanova Alla, Odnosum Hanna, Postoienko Dmytro, Kerek Stepan

Journal of Ecological Engineering

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2023

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Vol. 24, nr 10

198--204

EN

Providing a sufficient level of moisture while growing vegetables is the key to a high yield, its excessive or insufficient amount can lead to negative phenomena – disrupt the normal functioning of plants, deteriorate their chemical composition, etc. Every year, in certain areas of Ukraine, in particular, the Right Bank Forest Steppe, one can observe unevenness of the amount in precipitation (from a very low level to an abnormally high level in a short period of time). During heavy rainfall, the plant nutrition system is disrupted due to the movement of chemicals into deeper layers of the soil, which may become inaccessible to the root system of plants, thereby changing the quantitative and qualitative indicators of their production. The purpose and main direction of the research was aimed at studying the influence of different levels of gray forest soil moisture in the conditions of the Right Bank Forest Steppe of Ukraine on the content, accumulation coefficients and danger of lead (Pb) and cadmium (Cd) in the leaf mass of parsley, dill and spinach grown in the zone of man-made influence (from mobile sources of pollution). According to research results, it was established that vegetable plants (parsley, dill, spinach) can accumulate several times more Pb and Cd per unit mass compared to the content of these toxicants in the same mass of soil. At a high level of soil moisture (98–134 mm) during the formation of the leaf mass of vegetables, a lower content and coefficient of accumulation of Pb and Cd in the leaf mass of parsley, dill, and spinach was observed, compared to moderate soil moisture (30–37 mm). The results of the research indicate that when growing parsley, dill, and spinach on gray forest soils under man-made conditions with a high (98–134 mm) level of moisture during the formation of their leaf mass, a decrease in the content of Pb and Cd in the leaf mass of these plants is observed.

12

Technologia wykonywania fundamentów

Łupieżowiec Marian

Inżynier Budownictwa

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2023

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nr 12

78--81

13

Tendencje zmian klimatycznych wskaźników potrzeb nawadniania roślin w Polsce w latach 1991-2020

Żarski Jacek, Kuśmierek-Tomaszewska Renata

Infrastruktura i Ekologia Terenów Wiejskich

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2023

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nr I/1

88--103

PL

Przeprowadzono ocenę zmienności czterech klimatycznych wskaźników potrzeb nawadniania roślin w I strefie celowości stosowania tego zabiegu w Polsce (temperatura powietrza, opady atmosferyczne, częstość susz atmosferycznych, niedobory opadów). Analiza dotyczyła czterech miejscowości (Szczecin, Poznań, Kalisz, Toruń), wielolecia referencyjnego 1991-2020 oraz fragmentów i całego okresu aktywnego wzrostu roślin (V-VIII). Badania wykazały dość jednoznaczny wzrost potrzeb nawadniania pod względem kryterium klimatycznego. Wynika on przede wszystkim z istotnego wzrostu temperatury powietrza, skutkującego zwiększeniem się potrzeb wodnych roślin. Wykazano tendencję do pogłębiania się niedoborów opadowych w wieloleciu 1991-2020 na Nizinie Szczecińskiej i w Wielkopolsce oraz zidentyfikowano dużą liczbę susz atmosferycznych o zwiększonej intensywności w latach 2015-2020.

EN

An assessment of the variability of four climatic indicators of plant irrigation needs (air temperature, precipitation, frequency of atmospheric droughts, rainfall shortages) in the 1st zone of irrigation application in Poland was carried out. The analysis concerned four localities (Szczecin, Poznań, Kalisz, Toruń) during the reference multiyear period 1991-2020, in the entire period of active plant growth (V-VIII) as well as the parts of it. Results of the analysis have shown a fairly clear increase in irrigation needs in terms of the climatic criterion. It results primarily from a significant increase in air temperature, resulting in an increase in the water needs of plants. For the period 1991-2020 tendency to deepening rainfall shortages in the Szczecin Lowland and in Wielkopolska was demonstrated. The large numbers of atmospheric droughts with higher level of intensity were identified in the second part of the analysed period in the years 2015-2020.

14

Characterization of Climatic Drought Sequences in the Upper Moulouya Watershed, Morocco

Hachem Abdelaaziz, Mili El-Mostafa, Benbella Bouchra, El Ouardi Hmidou, Mehdaoui Radouan

Ecological Engineering & Environmental Technology

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2023

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Vol. 24, iss. 2

162--179

EN

Like most of the countries of the African continent and the MENA, Morocco has experienced alternating wet and dry periods for several decades and is still confronted with the effects of unstable climate change due to the specificities conferred by its geographical position and the diversity of its ecosystems. It is one of the countries most affected by desertification, with an arid and semi-arid climate covering more than 93% of its territory. Indeed, the Upper Moulouya watershed has been exposed to severe droughts several times in recent decades. The spatial and temporal distribution of drought episodes in this watershed is studied over a 91-year period between 1931 and 2022. In order to characterize and evaluate the severity and sustainability of drought in this watershed, four indices were used and applied in this study, as they have advantages in terms of statistical consistency and have the capacity to describe, through different time scales (short, medium and long) the impacts of the climatic drought in question. These are the Standardized Precipitation Index SPI, RDI, RI and DI. The annual rainfall series at the eight meteorological stations of the said watershed show irregularities and very marked spatial and temporal variability with a generally decreasing trend. The SPI calculation results obtained show a heterogeneous distribution of SPI values throughout the watershed area. The analysis of the graphical illustrations of this index allowed to highlight an important fluctuation of the dry and wet periods with a strong dominance and tendency to drought with the order of 51% in the stations of Midelt, and Ansegmir, 52% in the station of Zaida, 59% in the stations of Tabouazant, Barrage (Dam) Enjil and El Aouia, 58% in the station of Louggagh, 47% in the station of Anzar Oufounes. The analysis of the results of the of the drought indices RDI, RI and DI at the level of this watershed also made it possible to highlight the existence of numerous drought sequences alternating with other wet sequences and indicates a dominance of dry years, perfectly remarkable during the period 1976-93. The most important dry episode, in number of successive years, was recorded at the Ansegmir station from 1976-89 and the most important rainy episode was recorded at the Midelt station from 1966-76. The years of the 2015-2022 series show an overall persistent decrease in rainfall, thus allowing the installation of a severe drought episode. The trend in the entire watershed is a decrease in rainfall and the installation of mild, moderate and severe drought episodes of varying length and duration.

15

Precipitation of Sigma and Chi Phases in Cast Standard Duplex Stainless Steel

Myška Martin, Bořil Petr, Krutiš Vladimír, Kaňa Václav, Zádĕra Antonin

Archives of Foundry Engineering

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2023

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Vol. 23, iss. 2

29--34

EN

This work deals with the problem of intermetallic phases in cast standard duplex steel ASTM A890 Gr 4A (generally known as 2205). The investigated steel was subjected to isothermal heat treatment in the range from 595 °C to 900 °C and in the duration from 15 minutes to 245 hours, and was also investigated in terms of anisothermal (natural) cooling after casting into the mould. The precipitation starts at grain boundaries with a consistent ferrite transformation. The work is focused on the precipitation of the sigma phase (σ) and the chi phase (χ). Examination of the microstructure was conducted using light and scanning electron microscopy. Their statistical analysis was carried out using the results of the investigations of precipitation processes in the microstructure, both within the grains and at the grain boundaries. To illustrate this impact, the surface area of precipitates was evaluated. The percentage of these intermetallic phases was calculated by measuring their area using a computer image analysis system. Based on their observations, a combined time-temperature transformation (TTT) diagram with continuous cooling transformation (CCT) curves was created.

16

Evolution of the microstructure and mechanical properties of Sanicro 25 austenitic stainless steel after long-term ageing

Sroka M., Zieliński A., Golański G., Pawlyta M., Purzyńska H., Novy F.

Archives of Civil and Mechanical Engineering

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2023

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Vol. 23, no. 3

art. no. e149, 2023

EN

A newly developed heat-resistant austenitic steel, Sanicro 25 is currently considered the leading candidate material for an advanced ultra-supercritical installation. The test material was subjected to long-term ageing (up to 30,000 h) at 700 and 750 °C, after which investigations into the microstructure, identification of precipitates, and testing of mechanical properties were conducted. Sanicro 25 had an austenitic microstructure with annealed twins and numerous large primary NbX and Z-phase precipitates in the as-received condition. It was found that the long-term ageing of the steel resulted in numerous precipitation processes. For example, M23C6 carbides, Laves, σ and G phases occurred at the grain boundaries. However, Z-phase precipitates, ε_Cu particles, and Laves phase were observed inside the grains. At the same time, compound complexes of precipitates based on the primary Z-phase precipitates were revealed in the microstructure. The ageing process increased the particle size of M23C6 carbides and the σ phase. After longer ageing times, a precipitate-free zone (PFZ) near the grain boundaries was observed. The precipitation processes initially lead to an increase in the strength properties of the steel. However, after 5000 h, an over-ageing effect was observed at 750 °C, which was not observed at 700 °C.

17

Spatiotemporal detection of abrupt change in trends of rainfall and dry and wet periods at different time scales: The case of the Medjerda basin in northeast Algeria

Berhail Sabri, Katipoğlu Okan Mert

Acta Geophysica

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2023

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Vol. 71, no. 5

2497--2516

EN

This study investigates possible rainfall and drought trends using data from 38 rainfall stations in the Medjerda basin (northeast of Algeria) over 54 years (1965–2018). Drought-related data were calculated with the Standardized precipitation index (SPI). The Mann–Kendall test was used to find positive or negative precipitation trends. The magnitude of these trends was calculated using Sen’s slope method. According to the analysis, a decrease during the spring precipitation season was observed. Furthermore, the authors found the maximum increasing (decreasing) precipitation magnitude to be 2.14 mm/season (− 4.41 mm/season) in winter (spring). In addition, the magnitude of the precipitation trend per year ranged from − 6.26 to 2.54 mm/year, with an average reduction of 39% for the entire basin. From the outcomes of drought trend analysis, it can be inferred that for a short-time scale, the innovative trend analysis method exhibited a negative trend for the minimum and maximum SPI values. Drought severity was found to have increased during severe and extreme wet episodes, directly affecting Algeria’s frequently drought-affected agricultural regions, such as the Merdja plain and the irrigated perimeters of Sedrata and Zouabi. Considering the long-time scales, an increase was detected in drought severity and a decline during severe and extreme wet episodes. These findings show that the southeastern and central parts of the Medjerda basin’s long-term water resources have been severely affected, which negatively impacts the newly-constructed Ouldjet Mellegue dam in Tébessa province.

18

Global gridded products efficiency in closing water balance models: various modeling scenarios for behavioral assessments

Mousavi Rahimeh, Nasseri Mohsen, Abbasi Saeed, Taheri Mercedeh, Anboohi Milad Shamsi

Acta Geophysica

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2023

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Vol. 71, no. 5

2401--2422

EN

Global gridded products efficiency in closing water balance models: various modeling scenarios for behavioral assessments

19

Evaluation of the performance of data-driven approaches for filling monthly precipitation gaps in a semi-arid climate conditions

Katipoğlu Okan Mert

Acta Geophysica

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2023

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Vol. 71, no. 5

2265--2285

EN

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

20

Comparison of different ensemble precipitation forecast system evaluation, integration and hydrological applications

Tang Yehai, Wu Qiang, Soomro Shan-e-hyder, Li Xiang, Sun Yue, Hu Caihong

Acta Geophysica

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2023

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Vol. 71, no. 1

405--421

EN

The examination and integration of numerical forecast products are essential for using and developing numerical forecasts and hydrological forecasts. In this paper, the control forecast products from 2010 to 2014 of four model data (China Meteorological Administration (CMA), the National Centers for Environmental Prediction (NCEP), the European Centre for Medium-Range Weather Forecasts (ECMWF), and the United Kingdom Meteorological Office (UKMO)) from The Interactive Grand Global Ensemble (TIGGE) data center were evaluated comprehensively. On this basis, a study of runoff forecasting based on multi-model (multiple regression (MR), random forest (RF), and convolutional neural network-gradient boosting decision tree (CNN-GBDT)) precipitation integration is carried out. The results show that the CMA model performs the worst, while the other models have their advantages and disadvantages in different evaluation indexes. Compared with the single-index optimal model, CMA model had a higher root-mean-square error (RMSE) of 18.4%, and a lower determination coefficient (R2 ) of 14.7%, respectively. The integration of multiple numerical forecast information is better than that of a single model, and CNN-GBDT method is superior to the multiple regression method and random forest method in improving the precision of rainfall forecast. Compared with the original model, the RMSE decreases by 13.1 ~27.9%, PO decreases to 0.538 at heavy rainfall, and the R2 increases by 4~15.2%, but the degree of improvement decreases gradually with the increase in rainfall order. The method of multi-model ensemble rainfall forecasting based on a machine learning model is feasible and can improve the accuracy of short-term rainfall forecasting. The runoff forecast based on multi-model precipitation integration has been improved, and NSE increases from 0.88 to 0.935, but there is still great uncertainty about food peaks during the food season.