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1

Analysis of the sugar industry and climate drought challenges in the Lower Moulouya (Ne Morocco)

El Monhim Bilal, Arabi Mourad, Bouymajjan Mohamed, Soumaa Abdelkarim, Bouchal Adil, Amirou Abdellatif, Karboub Abdelaziz, Benrbia Khadija

Economics and Environment

|

2026

|

No. 1

art. no. 1115

EN

This paper examines the impact of climate-induced drought on sugar crops in the Lower Moulouya region, where four large, irrigated plains are found: Trifa in the Berkane province, and Sabra, Garb, and Bouarg plains in the Nador province. The study focuses on a monitoring period from 2000 to 2024, utilising statistical analysis of industrial variables in relation to annual rainfall in Zaio, Bouarg, and Al Aaroui. The findings reveal a statistically significant correlation between reductions in annual rainfall and decline in sugar beet cultivation and in industrial production indicators at the SUCRAFOR factory in Zaio. To test these results, the NDVI was applied to track the values of dense vegetation cover in irrigated plains, indicative of intensive industrial crops. The maximum NDVI values shifted from 0.5 in 2000 to 1 in 2009, then dropped to 0.5 in 2016, and reached 0.6 in 2024. Through analysis of satellite imagery using this index, a reduction in industrial crop areas over time was observed, decreasing from 13,686 hectares in 2000 to 11,341 hectares in 2009, then slightly recovering to 11,515 hectares in 2016, only to reach its lowest level in 2024 at an area of 8,057 hectares. The study adopted a descriptive approach, analysing production data and rainfall patterns. Field data were collected from the sugar factory and agricultural producers, then statistically analysed using Pearson's correlation coefficient to identify relationships between variables. To reinforce these findings, the NDVI was employed to monitor vegetation cover and assess trends in intensive and industrial crop cultivation.

2

A hybrid signal decomposition-machine learning benchmarking framework for multi-station precipitation prediction in the Kebir Rhumel basin (Algeria)

Erol Aykut, Rehamnia Issam, Citakoglu Hatice

Acta Geophysica

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2026

|

vol. 74, no. 3

art. no. 159, s. 1--40

EN

Reliable multi-station precipitation forecasting is challenging due to nonstationarity, noise, and spatial heterogeneity. This paper introduces a hybrid signal decomposition-machine learning benchmarking framework that integrates four decomposition methods (TQWT, MODWT, EWT, VMD) with three learners (Bagging, LSBoost, KNN), yielding twelve hybrid models. These models were rigorously tested across twelve stations in the Kebir Rhumel Basin using eight statistical metrics and distributional diagnostics to assess accuracy, stability, and generalization. Two dominant families emerged: TQWT-based hybrids achieved localized accuracy at four stations, while MODWT-Bagging led at eight stations and delivered the most consistent cross-station performance. MODWT-Bagging achieved R2 = 0.984-0.993 and NSE = 0.981-0.993, with RMSE ranging from 2.64 to 6.34, demonstrating strong predictive skill under varying hydro-climatic conditions. In noise-rich environments, it substantially reduced errors; for example, at El Milia, RMSE dropped from 12.57 (VMD-LSBoost) to 6.03, a « 52% reduction, and improvements of up to 63% were observed at other stations. Its superiority stems from MODWT’s shift-invariance and noise robustness combined with Bagging’s variance reduction. Taylor diagrams and violin plots confirmed centered, compact error structures, while scatter plots verified accurate phase and magnitude tracking. By clarifying how decomposition structure and learner characteristics interact across heterogeneous regimes, this framework fills a key gap in signal decomposition-machine learning model selection. The findings support adaptive hybrid design for early warning, water resource management, and precipitation-driven forecasting systems. Overall, MODWT-Bagging is established as a robust default for complex precipitation modeling, and the proposed framework provides a scalable foundation for next-generation hybrid predictive tools.

3

Evaluating variogram models and kriging approaches for analyzing spatial trends in precipitation simulations from global climate models

Batool Aamina, Ahmad Sufian, Waseem Ayesha, Kartal Veysi, Ali Zulfiqar, Mohsin Muhammad

Acta Geophysica

|

2025

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Vol. 73, no. 4

3677--3697

EN

Climate change has heightened the irregularity and unpredictability of weather patterns, influencing precipitation patterns. Accurate geographical projections of precipitation and other climatic variables are critical to sustainable water resource management and disaster preparedness. Variogram models are geostatistical techniques used to examine spatial correlation. Therefore, selecting the optimum variogram model for spatial interpolation is challenging. This study used six variogram models to assess spatial trends. Leave-one-out cross-validation (LOOCV) and K-fold cross-validation approaches are used to find the best variogram model based on metrics such as mean absolute error (MAE), root mean square error (RMSE), and mean bias. In this study, correlation data of 22 GCMs within observed data are predicted over 94 locations in Pakistan from 1950 to 2014. For evaluation, ordinary kriging (OK) and universal kriging (UK) are utilized as geostatistical approaches. The study highlights the suitability of the variogram models. Pentaspherical variogram (Pen) model is suggested as suitable model due to its minimum error metrics as well as the Hol effect (Hol) model has been considered beneficial for dealing with complicated data. From the geostatistical approaches, ordinary kriging (OK) yields the best prediction. Moreover, ordinary kriging (OK) and universal kriging (UK) both yield similar outcomes across some correlation-based data of 22 GCMs within observed data. Consequently, the implication of correlation analysis, optimum variogram models, and interpolation techniques enables the precise and accurate approach in the prediction of GCM performance. The efficiency of variogram models and interpolation approaches in managing data variability helps to enhance the consistency and interpretability of climate data.

4

Evaluating climate change impacts on snow cover and karst spring discharge in a data-scarce region: a case study of Iran

Zeydalinejad Nejat, Pour-Beyranvand Ali, Reza Nassery Hamid, Ghazi Babak

Acta Geophysica

|

2025

|

Vol. 73, no. 1

831--854

EN

The incremental impacts of climate change on elements within the water cycle are a growing concern. Intricate karst aquifers have received limited attention concerning climate change, especially those with sparse data. Additionally, snow cover has been overlooked in simulating karst spring discharge rates. This study aims to assess climate change effects in a data-scarce karst anticline, specifically Khorramabad, Iran, focusing on temperature, precipitation, snow cover, and Kio spring flows. Utilizing two shared socioeconomic pathways (SSPs), namely SSP2-4.5 and SSP5-8.5, extracted from the CMIP6 dataset for the base period (1991-2018) and future periods (2021-2040 and 2041-2060), the research employs Landsat data and artificial neural networks (ANNs) for snow cover and spring discharge computation, respectively. ANNs are trained using the training and verification periods of 1991-2010 and 2011-2018, respectively. Results indicate projected increases in temperature, between + 1.21 °C (2021-2040 under SSP245) and + 2.93 °C (2041-2060 under SSP585), and precipitation, from + 2.91 mm/month (2041-2060 under SSP585) to + 4.86 mm/month (2021-2040 under SSP585). The ANN models satisfactorily simulate spring discharge and snow cover, predicting a decrease in snow cover between - 4 km2/month (2021-2040 under SSP245) and - 11.4 km2/month (2041-2060 under SSP585). Spring discharges are anticipated to increase from + 28.5 l/s (2021-2040 under SSP245) to + 57 l/s (2041-2060 under SSP585) and from + 12.1 l/s (2021-2040 under SSP585) to + 36.1 l/s (2041-2060 under SSP245), with and without snow cover as an input, respectively. These findings emphasize the importance of considering these changes for the sustainability of karst groundwater in the future.

5

Evaluation of Hydro-Meteorological Conditions at the Water Reservoir for Supply of Drinking Water in the Period Since its Commissioning

Velísková Yvetta, Bara Márta Koczka, Sokáč Marek, Sočuvka Valentin, Okhravi Saeid

Inżynieria Mineralna

|

2024

|

Vol. 1, no. 2

art. no. 34

EN

Safe drinking water and its abundance include into among the basic attributes of a healthy environment and the basic human rights. As climate change progresses, ensuring a supply of drinking water to the population will pose increasing challenges. In this context, apart from exploiting groundwater sources, water reservoirs will assume a pivotal role in addressing this issue. On the territory of the Slovakia, there are currently 8 water reservoirs, which are used to collect water for the production of drinking water. One of them is the Turček reservoir, which was completed in May 1996 and has been in full operation since 1997. In this contribution, the hydro-meteorological data from the Turček water reservoir location, which were provided by the operator of this reservoir, are evaluated. These data contain information on daily values of basic characteristics. The period 1997-2021 was analyzed, especially the development and trends of precipitation, air temperature, occurrence of a given type of weather during this period and ice cover thickness and duration. The analysis of hydro-meteorological data showed that the average annual air temperature is rising slightly, for the period 1997-2021 it rose by 0,03 °C. The ice cover thickness (both maximum and average value) shows a decreasing trend and decreased by 7,3 cm during the observed period. The same trend is shown by the duration of the ice cover on the reservoir surface. The frequency of precipitation events has been decreasing for a long time, the annual total depth of precipitation also has a decreasing trend. Recently, this reservoir also had a problem with the occurrence of cryophilic cyanobacteria, the occurrence of which is not desirable in such types of water bodies. The performed analysis of the development of hydro-meteorological conditions is an important basis for the evaluation and understanding of processes related to water quality in this reservoir.

6

Prediction of Temperature and Precipitation Changes for Serbia Using Time Series Models with Machine Learning

Tomić Miroslav, Đukić Marija, Kordić Slavica, Dimitrieski Vladimir, Luković Ivan

Annals of Computer Science and Information Systems

|

2024

|

Vol. 41

177--184

EN

In the past few decades, there has been an evident change in climatic conditions worldwide as well as on the territory of Serbia. Extremely high temperatures, heavy floods, and sudden changes in the weather are increasingly frequent occurrences that bring great social and material damage. Climate change affects many economic sectors, like tourism and agriculture, which are potentially at risk. In Serbia, one of the vital economic sectors is agriculture. In order to act preventive, the main goal of this research was to predict the mean monthly temperature and precipitation for Serbia for periods 2021-2050 and 2071-2100. We collected a dataset titled ERA5 monthly averaged data on single levels from 1940 to present from the Climate Data Store. The dataset was analyzed and prepared to be used with SARIMA(X) and ARIMA(X) methods, which are utilized for prediction. The results that we identified are presented in this paper.

7

Spatiotemporal relationship of temperature and precipitation over southern coasts of the Caspian Sea based on quantile regression methods

Solaimani Karim, Ahmadi Sedigheh Bararkhanpour

Acta Geophysica

|

2024

|

Vol. 72, no. 2

1127--1142

EN

Temperature and precipitation are significant environmental variables that can lead to catastrophic climatic disasters. The intensity of precipitation increases with increasing temperature under humid conditions. As a result, investigating the trend and relationship between precipitation and temperature is important in a wide range of industries such as trade, agriculture, and ecological analysis. Quantile regression techniques were used in this study to determine the effect of temperature variables on different amounts of precipitation during a 36-year duration (1984-2019) in Mazandaran Province of Iran. According to the findings, heavy rainfall increased significantly in February and April while decreasing in May, June, and September. All minimum and maximum temperature measurements, however, increased significantly. Moreover, the positive and negative effects of temperature variables were higher in the upper quantiles of precipitation, so the most negative effect of the minimum temperature were identified in the northwestern regions and in the warm and cold months of the year, but the most positive effect were detected in the north. In contrast, it was revealed that the north and northwest regions, respectively, were most negatively impacted by maximum temperature and most positively impacted by heavy rainfall. Finally, in a long period, high temperatures have not shown a positive effect on precipitation, and it is different according to spatial and temporal changes.

8

Groundwater-level prediction in Visakhapatnam district, Andhra Pradesh, India, using Bayesian Neural Networks

Rajesh Rekapalli, Mathews Gathala Vinod, Rao N. Purnachandra, Begum Shaik Kareemunisa

Acta Geophysica

|

2024

|

Vol. 72, no. 4

2759--2772

EN

Groundwater-level and rainfall measurements from 37 borewells in the Visakhapatnam district, Andhra Pradesh, India, from 2002 to 2021 were analyzed using Bayesian Neural Networks (BNNs) to comprehend the predictability of groundwater levels. We found chaotic dynamics in the groundwater and rainfall data, but a dominant trend component was seen in the groundwaterlevel data from phase plots. Dynamics suggest the presence of self-organized criticality/chaos in the groundwater dynamics over decadal time scales. We used BNN prediction models, (i) nonlinear autoregressive (NAR), (ii) nonlinear input-output (NIO) and (iii) nonlinear autoregressive exogenic Input (NARX), to predict the groundwater levels with rainfall and temperature as exogenic inputs. We noticed ~ 94 to 95% prediction accuracy with the NAR model with optimal inputs and ~ 1% improvement with added exogenic input. Interestingly, the study indicates that (i) the dynamics of the groundwater differ significantly from rainfall and temperature in the region, (ii) the nonlinear autoregressive model based on the self-organized dynamics of groundwater-level changes is robust in providing prediction accuracy up to ~ 95%, and (iii) the dynamics of remaining ~ 5% groundwater-level changes may be due to the presence of randomly varying extreme weather events and man-made/anthropogenic changes.

9

Enhancing the TRMM precipitation product in diverse regions of Iran through an intelligent-based post-processing approach

Shahbazdashti Reza, Sharafati Ahmad, Kheyruri Yusef, Ghasemzadeh Firouz, Mohajeri Seyed Hossein

Acta Geophysica

|

2024

|

Vol. 72, no. 4

2925--2940

EN

The significant role of remote-sensed precipitation data lies in alleviating the absence of readily accessible daily precipitation data, particularly in developing nations. The TMPA 3B42 V7 precipitation data, with (0.25° X 0.25°) spatial resolution, widely used in satellite precipitation products, requires evaluation and correction at local scales. The aim of this study was to examine the reliability of the TMPA 3B42 V7 precipitation data in various climate regions in Iran. To achieve this, the data were compared with that of 103 synoptic stations from 2012 to 2017 using agreement indices, including the correlation coefficient. The findings reveal a notable association between the two datasets in terms of monthly and annual timeframes while displaying limited coherence on a daily level. In consideration of the disparity between satellite- and ground-based precipitation data, linear regression model (LRM) and artificial neural network (ANN) (specifically, a three-layer cascadeforward neural network (CFN)) were utilized to adjust the satellite precipitation data. The results demonstrate favorable performance for both in LRM and ANN models. The RMSE decreases to 20.8 and 20.7, while the NSE increases to 0.639 and 0.643, respectively. Specifically, the performance of the LRM model in correcting annual precipitation and the ANN model in correcting monthly precipitation surpasses that of other models. Additionally, the artificial neural network (ANN) displays inadequate performance in arid and semi-arid highlands located in the central region of Iran, as well as in the rectification of monthly and annual precipitation in the western vicinity of the Caspian Sea.

10

Characterizing spatiotemporal properties of precipitation in the middle Mahanadi subdivision, India during 1901-2017

Sahu Ramgopal Tilakram, Verma Shashikant, Verma Mani Kant, Ahmad Ishtiyaq

Acta Geophysica

|

2024

|

Vol. 72, no. 2

1143--1158

EN

Long-term historical data and their interpretation are crucial aspects of understanding any kind of variation that exists as a result of changing environmental behaviour. The focus of the study is to characterize precipitation properties in the middle subdivision of the Mahanadi River basin (MRB). An eigen-based technique, also known as the maximum loading value approach, and gridded precipitation data with a resolution of 0.25° X 0.25° are presented to analyze the spatiotemporal properties of precipitation at different timeslot intervals. The meteorological data (gridded precipitation for 117 years from 1901 to 2017) has a special “k” field for spatial and temporal modes of spatial pattern analysis, which aids in the recognition of precipitation properties. The identified characteristics of the exclusive timeslot periods have been assessed for any dispersion as a function of annual precipitation. To cross-validate the identified patterns for distinctness and pairwise comparison, the Kolmogorov-Smirnov’s D test was used. Southwest Mahanadi does not experience much variation in pattern size (± 3-5%), with a maximum variance of 39.09% during timeslot 2 (1940-1978). Similarly, the southeast Mahanadi observed a continuous increase in pattern size and was above 10% with a maximum variance of 28.53% during timeslot 3 (1979-2 017). While north-eastern Mahanadi experienced a continuous and significant decrease of > 14% of the total variance, with a maximum (42.48%) during timeslot 1 (1901-1939) and a minimum (28.14%) during timeslot 3 (1979-2017). There is no spatial pattern variability from summer to any of the timeslot intervals.

11

Assessing the variability of satellite and reanalysis rainfall products over a semiarid catchment in Tunisia

Gharnouki Ines, Aouissi Jalel, Benabdallah Sihem, Tramblay Yves

Acta Geophysica

|

2024

|

Vol. 72, no. 2

1257--1273

EN

Precipitation is a key component in hydrologic processes. It plays an important role in hydrological modeling and water resource management. However, many regions suffer from limited and data scarcity due to the lack of ground-based rain gauge networks. The main objective of this study is to evaluate other source of rainfall data such as remote sensing data (three different satellite-based precipitation products (CHIRPS, PERSIANN, and GPM) and a reanalysis (ERA5) against groundbased data, which could provide complementary rainfall information in semiarid catchment of Tunisia (Haffouz catchment), for the period between September 2000 and August 2018. These remotely sensed-data are compared for the first time with observations in a semiarid catchment in Tunisia. Twelve rain gauges and two different interpolation methods (inverse distance weight and ordinary kriging) were used to compute a set of interpolated precipitation reference fields. The evaluation was performed at daily, monthly, and yearly time scales and at different spatial scales, using several statistical metrics. The results showed that the two interpolation methods give similar precipitation estimates at the catchment scale. According to the different statistical metrics, CHIRPS showed the most satisfactory results followed by PERSIANN which performed well in terms of correlation but overestimated precipitations spatially over the catchment. GPM underestimates the precipitation considerably, but it gives a satisfactory performance temporally. ERA5 shows a very good performance at daily, monthly, and yearly timescale, but it is unable to represent the spatial variability distribution of precipitation for this catchment. This study concluded that satellite-based precipitation products or reanalysis data can be useful in semiarid regions and data-scarce catchments, and it may provide less costly alternatives for data-poor regions.

12

Application of hierarchical cluster analysis to spatiotemporal variability of monthly precipitation over Khyber Pakhtunkhwa, Pakistan

Tajbar Sapna, Tajbar Asfandiyar, Pashaie Zahra, Khorshiddoust Ali Mohammad, Rafiq Lubna

Acta Geophysica

|

2024

|

Vol. 72, no. 2

1159--1174

EN

Understanding the long-term spatiotemporal variability of precipitation at the regional scale is critical for developing flood and drought control strategies and water resource management. This study assessed the spatiotemporal variability of monthly precipitation over the Khyber Pakhtunkhwa province of Pakistan for 1998-2019 using hierarchical cluster analysis to cluster 156 Tropical Rainfall Measuring Mission grids. Statistical properties of clusters were calculated and the relationship of geographical features such as latitude, longitude, and altitude and statistical variables including standard deviation, maximum and minimum precipitation, and coefficient of variation (CV) with average precipitation was assessed. Findings showed that northeast parts received maximum precipitation while north and southern regions received less precipitation. Temporal analysis showed two clusters of rainy months (February, March, April, May, July, and August) and dry months (January, June, September, October, November, and December). The region was divided into two homogeneous precipitation regions. From January to April and November to December, cluster 1 occupied northern parts with maximum average precipitation while cluster 2 southern parts. From June to September, cluster 2 covered the northeast and southern parts with the highest average precipitation. During May, cluster 2 received the highest average precipitation in the northeast and southeast parts, whereas cluster 1 covered the northwest and southwest. In October, cluster 2 received maximum average precipitation covering the northeast. CV suggested higher temporal variability in cluster 2 (67.75-102.36)% than cluster 1 (65.82-99.55)%. Precipitation correlation showed that CV opposed the longitude and averages, whereas latitude and altitude demonstrated minimal correlations. These insights can assist decision-makers in devising suitable strategies to plan and control unexpected volumes of precipitation.

13

Funkcjonowanie zbiorników retencyjnych Regionalnego Zarządu Gospodarki Wodnej w Poznaniu w kontekście zmian klimatycznych i potrzeb wodnych - wyzwania i problemy eksploatacyjne na przykładzie wybranych obiektów

Wierzbicki Michał, Andrzejak Anna, Piniarska Dorota, Sobczyk Bartłomiej, Nowak Bogumił

Gospodarka Wodna

|

2023

|

Nr 9

32--38

PL

Zmiany klimatyczne stawiają przed gospodarką wodną nowe wyzwania. Funkcjonowanie obiektów, służących jej celom, musi uwzględniać zarówno zmiany warunków hydrologicznych, jak i zmiany potrzeb wodnych użytkowników wód i środowiska naturalnego oraz rosnącej presji ich zaspokojenia. Kiedy szczególnego znaczenia nabiera racjonalne gospodarowanie wodą, niejednokrotnie istnieje konieczność przedefiniowania celów i zadań, jakie mają one spełniać, oraz określenia nowych zasad ich funkcjonowania. W referacie przedstawiono - na wybranych przykładach - nowe wyzwania i problemy eksploatacji obiektów hydrotechnicznych RZGW w Poznaniu w zmieniających się warunkach hydrologiczno-meteorologicznych. Wykorzystano dane hydrometeorologiczne, dane dotyczące obiektów hydrotechnicznych, ich funkcjonowania oraz potrzeb wodnych. Opisano zmiany zasilania zbiorników wodnych, m.in. coraz częściej występujące niżówki hydrologiczne, skutkujące trudnościami w realizacji założonej gospodarki wodnej, oraz możliwości zaspokojenia potrzeb wodnych. Wskazano na konieczność dostosowania zbiorników do zmieniających się warunków klimatycznych. Przedstawiono również wzajemne zależności pomiędzy obiektami hydrotechnicznymi i wskazano na konieczność ich uwzględnienia w określaniu zasad gospodarowania wodą. Części wspólne tych zasad są niezwykle istotne w kontekście szerszego spojrzenia na zasoby wodne i możliwości zaspokojenia potrzeb wodnych regionu.

EN

Climate change brings new challenges for the water management to face. Functioning of the facilities it uses needs to take into account changing hydrological conditions as well as the evolution of the water users” and natural environment needs and the growing pressure to meet them. When rational water management becomes of particular importance, it sometimes gives rise to the necessity to redefine the goals and tasks it should fulfill and determine new principles of it functioning. The article, using selected examples, presents new challenges and operational problems of hydro-technical structures of the Regional Water Management Authority in Poznań in the evolving hydrological and meteorological conditions. It uses hydro-meteorological data, data on hydro-technical strictures, their functioning and water needs. The authors describe the change in water reservoir supply, increasingly frequent low water periods among them, resulting in difficulties to meet the assumed water management goals and impacting the ability to satisfy water needs. They point out to the necessity to adapt reservoirs to the changing climate conditions. They also present interdependencies between hydro-technical structures and the necessity to take them into account while determining water management principles. Common parts of these principles are of significant importance in the context of having a broader view of water resources and the possibility to satisfy water needs of the region.

14

The Effect of Microalloying (Nb, V) and Interstitial (C, N) Elements on Mechanical Properties of Microalloyed Steels

Marynowski Przemysław, Hojny Marcin, Dębiński Tomasz

Archives of Foundry Engineering

|

2023

|

Vol. 23, iss. 4

127--136

EN

The microalloying elements such as Nb, V are added to control the microstructure and mechanical properties of microalloyed (HSLA) steels. High chemical affinity of these elements for interstitials (N, C) results in precipitation of binary compound, nitrides and carbides and products of their mutual solubility – carbonitrides. The chemical composition of austenite, as well as the content and geometric parameters of undissolved precipitates inhibiting the growth of austenite grains is important for predicting the microstructure, and thus the mechanical properties of the material. Proper selection of the chemical composition of the steel makes it possible to achieve the required properties of the steel at the lowest possible manufacturing cost. The developed numerical model of carbonitrides precipitation process was used to simulate and predict the mechanical properties of HSLA steels. The effect of Nb and V content to change the yield strength of these steels was described. Some comparison with literature was done.

15

Jakość wód opadowych przeznaczonych do dalszego wykorzystania

Ryńska Joanna

Rynek Instalacyjny

|

2022

|

Nr 12

94--98

PL

W artykule przedstawiono dotychczas stosowane sposoby podczyszczania wód opadowych przeznaczonych do retencji i dalszego zastosowania. Omówiono nowe kierunki w oczyszczaniu wód opadowych, związane z wynikami badań naukowych w Polsce i na świecie oraz z praktycznymi doświadczeniami eksploatatorów.

EN

The paper presents the methods used currently for re-treatment of stormwater intended for retention and further use. The new approach to stormwater treatment, related to both the results of scientific research in Poland and in the world, and operational practice, were discussed.

16

Wpływ ujemnej temperatury i opadów podczas procesów technologicznych na właściwości nawierzchni asfaltowej

Czyż Magdalena, Lis Maciej, Szafranko Elżbieta

Materiały Budowlane

|

2022

|

nr 4

82--85

PL

W artykule przedstawiono wpływ ujemnej temperatury i opadów reprezentujących warunki zimowe na właściwości nawierzchni wykonywanej podczas ich występowania. W celu uchwycenia granicznych warunków atmosferycznych, po przekroczeniu których właściwości nawierzchni znacznie odbiegają od wymaganych, wyodrębniono cztery odcinki, na których wykonywano podbudowę z betonu asfaltowego AC22P oraz warstwę wiążącą z betonu asfaltowego AC16W, w różnych warunkach atmosferycznych. W artykule opisano wady nawierzchni powstałe na skutek wykonywania robót w nieodpowiednich warunkach pogodowych.

EN

The article presents the impact of adverse weather conditions occurring in winter on the properties of the pavement performed during such winter conditions. In order to try to capture the boundary atmospheric conditions, beyond which the properties of the pavement significantly differ from the required ones, four sections were distinguished on which the AC22P asphalt concrete foundation and the AC16W asphalt concrete binding layer were made, in various weather conditions. The article the surface defects caused by the execution of works in inappropriate weather conditions were demonstrated.

17

Responses of Physiological Characteristics of Annual C4 Herbs to Precipitation and Wind Changes in Semi-Arid Sandy Grassland, Northern China

Sun Shanshan, Liu Xinping, He Yuhui, Lv Peng, Chelmeg, Zhang Lamei, Wei Shuilian

Polish Journal of Ecology

|

2020

|

Vol. 68, nr 2

121--131

EN

The effects of changing precipitation and wind regimes on plant physiology are increasingly drawing attention of eco-physiologists. In the manipulative experiment we studied the physiological mechanisms of annual C4 herbs in the semi-arid sandy land to understand the functional significance of their traits and responses to the changing environment, grass Setaria viridis, characterized by the moderate stem water content and low leaf water content, more effectively absorbed light energy and utilized water resources than two dominant dicot plants, Salsola collina and Bassia dasyphylla. Precipitation increase and wind reduction promoted photosynthesis of the three C4 herbaceous plants, and their photosynthetic rates were higher in the end of July than that in August. Precipitation increase and the 20% reduction in wind velocity could also enhance their stomatal conductance and transpiration rate. The transpiration rate was consistent with the change in stomatal conductance, exhibiting highly positive correlation. The interactive effects of precipitation increase and wind velocity reduction made great changes in photosynthetic rate of the S. collina, lifted the photosynthetic rate and water use efficiency of the S. viridis. Our results suggest that the C4 herbs have shown some degree of stress resistance, and they are able to acclimate better to frangible environment of semi-arid sandy land. Furthermore, the changing environments heighten photosynthesis of the C4 herbs, which is pretty important to strength the arid plant stress resistance, then contributed to the ecosystem community production and dry matter accumulation.

18

Wpływ plam słonecznych na opady w Polsce

Chmielewska Iwona, Dołżyk-Szypcio Katarzyna, Szypcio Zenon

Magazyn Autostrady

|

2020

|

Nr 3

58--64

PL

W artykule pokazano, że na znacznym obszarze Polski sumaryczny opad roczny zależy od liczby plam słonecznych. Wystąpienie powodzi i intensywnych opadów jest bardziej prawdopodobne w okresach małej aktywności słońca niż dużej. Fakt ten może być wykorzystany przy planowaniu budowy dróg i mostów.

EN

The article demonstrates that in a significant area in Poland the total annual precipitation depends on the number of sunspots. Floods and heavy rainfall are more likely during the periods of low rather than high sun activity. This fact can be used when planning the construction of roads and bridges.

19

On the go-and-stop motion of the discontinuous precipitation front

Chronowski M., Zięba P.

Archives of Civil and Mechanical Engineering

|

2020

|

Vol. 20, no. 2

73--79

EN

The growth of lamellar structure during discontinuous precipitation occurs frequently by so-called go-and-stop fashion. The results of simulation combined with the changes of Cahn’s parameter C revealed two types of such motion. The process takes place in the successive stages which can be distinguished judging from the value of C parameter. For lower values of linear growth rate (v = 10÷20 nm/s) and smaller α lamella thickness (100÷200 nm), the full cycle with relaxation takes 4–6 s. The faster movement of the reaction front (v = 30 nm/s) resulted in dramatic decrease of the full cycle to τtotal = 0.8 s. The same behavior is observed if the α lamella thickness increases beyond 200 nm at constant v equal to 10 nm/s. Both predicted types of go-and-stop motion can experimentally be observed during growth or dissolution of discontinuous precipitates. What is the reason that particular type prevails is unknown, and this is invitation for further studies especially using high-resolution transmission electron microscope operating in in situ mode.

20

Analysis of distribution of precipitation duration and amounts in Legnica in the period of 1966–2015

Jakubczyk Teresa

Journal of Water and Land Development

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2019

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no. 41

69--76

EN

The paper presents the results of analysis of duration of precipitation sequences and the amounts of precipitation in individual sequences in Legnica. The study was aimed at an analysis of potential trends and regularities in atmospheric precipitations over the period of 1966–2015. On their basis a prediction attempt was made for trends in subsequent years. The analysis was made by fitting data to suitable distributions – the Weibull distribution for diurnal sums in sequences and the Pascal distribution for sequence durations, and then by analysing the variation of the particular indices such the mean value, variance and quartiles. The analysis was performed for five six-week periods in a year, from spring to late autumn, analysed in consecutive five-year periods. The trends of the analysed indices, observed over the fifty-year period, are not statistically significant, which indicates stability of precipitation conditions over the last half-century.

PL

W pracy przedstawiono wyniki analiz rozkładów długości trwania sekwencji opadowych oraz wielkości opadów w poszczególnych sekwencjach w Legnicy. Badania miały na celu przeprowadzenie analizy ewentualnych tendencji i regularności w opadach atmosferycznych w okresie 1966–2015. Na ich podstawie podjęto próbę predykcji dla tendencji w kolejnych latach. Analizę wykonano przez dopasowanie do danych odpowiednich rozkładów – rozkładu Weibulla do sum dobowych w sekwencjach oraz rozkładu Pascala do długości sekwencji, a następnie przez zbadanie zmienności poszczególnych wskaźników, takich jak średnia, wariancja i kwartyle. Analiza została przeprowadzona w odniesieniu do pięciu sześciotygodniowych okresów w ciągu roku od wczesnej wiosny do późnej jesieni, rozpatrywanych w kolejnych pięcioleciach. Tendencje badanych wskaźników zaobserwowane na przestrzeni pięćdziesięciolecia nie są istotne statystycznie, co świadczy o stabilności zjawiska opadów w ostatnim pięćdziesięcioleciu.