Daily Air Temperature Research Articles

Trends in Precipitation and Air Temperature Extremes and Their Relationship with Sea Surface Temperature in the Brazilian Midwest

The Brazilian Midwest has significant spatiotemporal variability in terms of precipitation and air temperature, making it more vulnerable to the occurrence of extreme weather events. The objective of this study is to characterize the trend of extreme climatic events regarding precipitation and air temperature in the Brazilian Midwest, and to analyze their relationship with Pacific and Atlantic Sea Surface Temperature anomalies (SSTAs). We used daily precipitation and air temperature data measured at 24 conventional weather stations. Pacific and Atlantic SSTA data were obtained from the Climate Prediction Center. The frequency of hot extremes had increased, while that of cold extremes had decreased significantly, thus highlighting the consistent warming across the Brazilian Midwest. The precipitation extremes had greater variability than the temperature extremes. Precipitation intensity increased in Amazonia, with no change in annual precipitation volume. The precipitation extremes in the Brazilian Savanna, Pantanal, and the Atlantic Forest did not have a well-defined pattern but indicated a trend towards a decrease in days with intense precipitation events. In general, the Equatorial Pacific and Atlantic Ocean (TNAI and TSAI) SSTAs were negatively correlated with precipitation extreme indices and positively correlated with air temperature extreme indices in the Amazon. However, the North Atlantic SSTAs were positively correlated with precipitation and air temperature extreme indices in the Brazilian Savanna and Pantanal. In addition, the Pacific SSTAs were positively correlated with precipitation intensity in the Atlantic Forest. Thus, the variability of the trends of precipitation and air temperature extreme indices in the Brazilian Midwest was observed, and it was surmised that this measure was significantly related to Pacific and Atlantic SSTAs.

A cold wave of winter 2021 in central South America: characteristics and impacts.

The online version contains supplementary material available at 10.1007/s00382-023-06701-1.

Multiple factors co-limit short-term in situ soil carbon dioxide emissions.

Soil respiration is a major source of atmospheric CO2. If it increases with warming, it will counteract efforts to minimize climate change. To improve understanding of environmental controls over soil CO2 emission, we applied generalized linear modeling to a large dataset of in situ measurements of short-term soil respiration rate, with associated environmental attributes, which was gathered over multiple years from four locations that varied in climate, soil type, and vegetation. Soil respiration includes many CO2-producing processes: we theorized that different environmental factors could limit each process distinctly, thereby diminishing overall CO2 emissions. A baseline model that included soil temperature, soil volumetric water content, and their interaction was effective in estimating soil respiration at all four locations (p < 0.0001). Model fits, based on model log likelihoods, improved continuously as additional covariates were added, including mean daily air temperature, enhanced vegetation index (EVI), and quadratic terms for soil temperature and water content, and their interactions. The addition of land cover and its direct interactions with environmental variables further improved model fits. Significant interactions between covariates were observed at each location and at every stage of analysis, but the interaction terms varied among sites and models, and did not consistently maintain importance in more complex models. A main-effects model was therefore tested, which included soil temperature and water content, their quadratic effects, EVI, and air temperature, but no interactions. In that case all six covariates were significant (p < 0.0001) when applied across sites. We infer that local-scale soil-CO2 emissions are commonly co-limited by EVI and air temperature, in addition to soil temperature and water content. Importantly, the quadratic soil temperature and moisture terms were significantly negative: estimated soil-CO2 emissions declined when soil temperature exceeded 22.5°C, and as soil moisture differed from the optimum of 0.27 m3 m-3.

Renewable Energy Potential Estimation Using Climatic-Weather-Forecasting Machine Learning Algorithms

The major challenge facing renewable energy systems in Nigeria is the lack of appropriate, affordable, and available meteorological stations that can accurately provide present and future trends in weather data and solar PV performance. It is crucial to find a solution to this because information on present and future solar PV performance is important to renewable energy investors so that they can assess the potential of renewable energy systems in various locations across the country. Although Nigerian weather provides favorable weather conditions for clean power generation, there is little penetration of renewable energy systems in the region, since over 95% of the power is fossil-fuel-generated. This is because there has been no detailed report showing the potential of clean power generation systems due to the dysfunctional meteorological stations in the country. This paper sought to fill this knowledge gap by providing a machine-learning-inspired forecasting of environmental weather parameters that can be used by manufacturing companies in evaluating the profitability of siting renewable energy systems in the region. Crucial weather parameters such as daily air temperature, relative humidity, atmospheric pressure, wind speed, and rainfall were obtained from NASA for a period of 19 years (viz. 2004–2022), resulting in the collection of 6664 high-resolution data points. These data were used to build diverse regressive neural networks with varying hyperparameters to find the best network arrangement. In summary, a low mean-squared error of 7 × 10−3 and high regression correlations of 96% were obtained during the training.

Effects of Temperatures and Heatwaves on Occupational Injuries in the Agricultural Sector in Italy.

The effects of heat on health have been well documented, while less is known about the effects among agricultural workers. Our aim is to estimate the effects and impacts of heat on occupational injuries in the agricultural sector in Italy. Occupational injuries in the agricultural sector from the Italian national workers' compensation authority (INAIL) and daily mean air temperatures from Copernicus ERA5-land for a five-year period (2014-2018) were considered. Distributed lag non-linear models (DLNM) were used to estimate the relative risk and attributable injuries for increases in daily mean air temperatures between the 75th and 99th percentile and during heatwaves. Analyses were stratified by age, professional qualification, and severity of injury. A total of 150,422 agricultural injuries were considered and the overall relative risk of injury for exposure to high temperatures was 1.13 (95% CI: 1.08; 1.18). A higher risk was observed among younger workers (15-34 years) (1.23 95% CI: 1.14; 1.34) and occasional workers (1.25 95% CI: 1.03; 1.52). A total of 2050 heat-attributable injuries were estimated in the study period. Workers engaged in outdoor and labour-intensive activities in the agricultural sector are at greater risk of injury and these results can help target prevention actions for climate change adaptation.

Streamflow Composition and the Contradicting Impacts of Anthropogenic Activities and Climatic Change on Streamflow in the Amu Darya Basin, Central Asia

Abstract Transboundary rivers are often the cause of water-related international disputes. One example is the Amu Darya River, with a catchment area of 470 000 km2, which passes through five countries and provides water resources for 89 million people. Intensified human activities and climate change in this region have altered hydrological processes and led to water-related conflicts and ecosystem degradation. Understanding streamflow composition and quantifying the change impacts on streamflow in the Amu Darya basin (ADB) are imperative to water resources management. Here, a degree-day glacier-melt scheme coupled offline with the Variable Infiltration Capacity hydrological model (VIC-glacier), forced by daily precipitation, maximum and minimum air temperature, and wind speed, is used to examine streamflow composition and changes during 1953–2019. Results show large differences in streamflow composition among the tributaries. There is a decrease in the snowmelt component (−260.8 m3 s−1) and rainfall component (−30.1 m3 s−1) at Kerki but an increase in the glacier melt component (160.0 m3 s−1) during drought years. In contrast, there is an increase in the snowmelt component (378.6 m3 s−1) and rainfall component (12.0 m3 s−1) but a decrease in the glacier melt component (−201.8 m3 s−1) during wet years. Using the VIC-glacier and climate elasticity approach, impacts of human activities and climate change on streamflow at Kerki and Kiziljar during 1956–2015 are quantified. Both methods agree and show a dominant role played by human activities in streamflow reduction, with contributions ranging 103.2%–122.1%; however, the contribution of climate change ranges from −22.1% to −3.2%.

Climatic conditions of the Urals and Western Siberia post-virgin regions and field crops productivity

The purpose of these studies was to determine the current trends in the change in the meteorological conditions of the growing season of field crops in the post-virgin regions of the Urals and Western Siberia and to identify their regional characteristics and influence on the yield of spring wheat. The research object was information on the average daily air temperatures, precipitation, and spring wheat yield. When processing the digital material, the generally accepted methods of statistical analysis were used. It has been established that current trends in an increase in climate aridity are accompanied by a significant change in the growing conditions of field crops, especially in the post-virgin areas of the Orenburg region. The steppe natural and climatic zone of the Omsk region, with all the humidification conditions’ intensity, is characterized by more favorable hydrothermal indicators and their temporary stability. The most significant dependence (r = 0.75 – 0.79) of the yield of spring wheat on hydrothermal conditions was found in the Svetlinsky district of the Orenburg region, which is characterized by the least amount of precipitation (139 mm) of the active growing season. The results obtained indicate the feasibility of developing and implementing adaptive moisture-saving agricultural technologies and techniques focused on the rational use of water resources in a changing climate.

Temperature-dependent modal analysis of the InSight lander on Mars

The first high-performance seismometer on Mars, deployed by InSight, has been working for nearly two Martian years. However, the recorded seismic data are substantially affected by the natural frequencies of the lander. To analyze the effect of the natural frequencies of the lander on specific components of the seismic data, we have built a simplified finite-element model of the lander to conduct modal analyses. Three natural frequencies are modeled by comparing them with those identified from the observed data. These natural frequencies are nonconstant and temperature dependent, which can be explained as an elastic modulus reduction of the solar panels (35% at most) and/or the property changes of the ground media beneath the lander due to a daily air temperature variation of approximately 100 K on Mars. Compared with the previous studies based on the empirical models before the launch, our results can quantitatively evaluate natural modes and their temperature dependency. Thus, these analyses are helpful in avoiding the potential interference of natural frequencies and improving the reliability of seismic data applications.

Environmental pollution in North-Eastern Italy and its influence on chronic obstructive pulmonary disease: time series modelling and analysis using visibility graphs

The impact on human health from environmental pollution is receiving increasing attention. In the case of respiratory diseases such as chronic obstructive pulmonary disease (COPD), the relationship is now well documented. However, few studies have been carried out in areas with low population density and low industrial production, such as the province of Belluno (North-Eastern Italy). The aim of the study was to analyze the effect of exposure to certain pollutants on the temporal dynamics of hospital admissions for COPD in the province of Belluno. Daily air pollution concentration, humidity, precipitations, and temperature were collected from the air monitoring stations in Belluno. Generalized additive mixed models (GAMM) and visibility graphs were used to determine the effects of the short-term exposure to environmental agents on hospital admissions associated to COPD. In the case of the city of Belluno, the GAMM showed that hospital admissions were associated with NO2, PM10, date, and temperature, while for the city of Feltre, GAMM produced no associated variables. Several visibility graph indices (average edge overlap and interlayer mutual information) showed a significant overlap between environmental agents and hospital admission for both cities. Our study has shown that visibility graphs can be useful in establishing associations between environmental agents and COPD hospitalization in sparsely populated areas.

Optimization of sowing date for spring maize in China's loess plateau based on presowing temperature and soil water content.

The sowing date of spring maize in China's Loess Plateau is often restricted by the presowing temperature and soil water content (SWC). The effective measurement of the effects of presowing temperature and SWC on the sowing date is a major concern for agricultural production in this region. In this paper, we considered the average daily air temperature of ˃10 °C in the 7 days before sowing. The Decision Support System for Agrotechnology Transfer (DSSAT) model was used to simulate a spring maize yield under distinct combinations of SWC and sowing date for 51 years (1970-2020). Subsequently, through the cumulative probability distribution function, the contribution of presowing SWC to the spring maize yield was quantified, and the optimal sowing date of spring maize in each production location was determined. The results revealed that the daily average temperature of ˃10 °C for 7 days consecutively can be used effectively as the basis for the simulation of spring maize sowing date. The presowing SWC affected the spring maize yield but did not change the optimal sowing date. When the SWC of each study site is about 70% of the field capacity, Wenshui and Yuanping can properly delay sowing, and Lin county can sow early to obtain a higher yield. This study provides an effective approach for optimizing presowing soil moisture management and the sowing date of spring maize in the semiarid regions of the Loess Plateau. © 2023 Society of Chemical Industry.

Impacts of wintertime meteorological variables on decomposition of Phragmites australis and Solidago canadensis in the Balaton System

A field experiment was carried out in plant litter decomposition at three sites of the Balaton System (Balaton — Kis Balaton wetland — Zala Mouth) differing in their environment type during winter 2019/2020. The largest freshwater shallow lake in Central Europe (Carpathian Basin) is the Balaton, with a surface area of about 600 km2 and an average depth of 3.25 m. Right around the lake, a nutrient filtering system, the Kis-Balaton wetland, is functioning to avoid water deterioration and eutrophication. The aim of the study was to investigate crop-weather relations in two sample species, the widely distributed native P. australis and the allied S. canadensis incubated beneath the water using leaf-bag technique to characterise plant organ decomposition. Based on our results, the most consistent meteorological variable regarding decomposition process was global radiation (r = − 0.62* to − 0.91**; r: correlation coefficient; * and ** mean that correlations are significant at the 0.05 and 0.01 levels), in each treatment. In modelling the decomposition process, out of eight meteorological variables, only the daily mean air temperatures and humidity were excluded from regression equations. On dominatingly windy days, with the increase in water temperature of the Zala Mouth, the sensitivity of the decomposition of S. canadensis litter tended to decrease as compared to P. australis. The remaining litter masses were in a Kis-Balaton > Balaton > Zala order, contrasting the water temperature gradient that decreased from the Zala to the Kis-Balaton wetland under wind-dominated conditions. Considering all sampling places in three aquatic ecosystems, there was a 2.2 and a 2.7% daily mean detritus mass loss in P. australis and S. canadensis, respectively. We concluded that the invasive S. canadensis litter decomposed more quickly than those of native P. australis, irrespective to sampling site. Increase in winter water temperature significantly promoted the litter decomposition of both plant species. The originality of the study is that it quantifies the litter decomposition for an Eastern European wetland, during wintertime.

Disaster event-based spring frost damage identification indicator for tea plants and its applications over the region north of the Yangtze River, China

Spring frost damage (SFD) is the main meteorological disaster limiting the tea industry in the region of the north of the Yangtze River (NYR) in China. Research regarding an SFD indicator for tea plants is of great significance for prevention and control of spring frosts, as well as for timely monitoring and early warning. Based on daily minimum air temperatures (Tmin) and spring frost disaster records in NYR from 1961 to 2020, the Receiver Operating Characteristic curve (ROC) was used to evaluate the accuracy of frost identification, and the critical temperature threshold for SFD to tea plants was determined by jointly comparing Overall Accuracy and the Youden Index. The results showed that the area under the ROC curve was 0.977, indicating that Tmin performed well in identifying frost events. The critical temperature threshold for spring frost in NYR was determined as Tmin of 3.7 °C, and 93 % of frost occurrences were correctly identified. Based on the determined critical threshold of SFD, the number of spring frost days, first frost date (FFD), and last frost date (LFD) in NYR from 1961 to 2020 were analyzed. The results showed that the number of spring frost days in NYR decreased from north to south. FFD appeared earlier and LFD ended later in northern NYR than in southern NYR. These results provide theoretical and technical support for the monitoring and evaluation of spring frosts in NYR, and also for implementing SFD prevention and control measurements for tea plants by use of a critical temperature threshold.

Intraseasonal Oscillation Features of the Two Types of Persistent High Temperature Events over Jiangnan Region

In order to find potential low-frequency signals and provide new ideas for extended-range forecasting, the intraseasonal oscillation (ISO) characteristics of persistent high temperature events (PHTEs) in the extended summer in Jiangnan area are explored by using daily maximum air temperature (Tmax) data from the China Meteorological Data Network and daily reanalysis data provided by NCEP/DOE. The results show that the low-frequency PHTEs can be classified into three types according to the position variation of the Western Pacific subtropical high (WPSH). For the first two types of PHTEs, a southwestward migrating mid-latitude wave train from the North American coast to the central and eastern China can be clearly seen in the whole troposphere. Whereas the two types of PHTEs show different features in the low-latitude. It is found that a significantly westward extension of the WPSH during the first type of PHTEs, with the low-frequency anticyclone moving westward in the mid-lower troposphere. For the second type of PHTEs, the WPSH is mainly located in the southeastern China with slightly movement. Analysis of the low-frequency vertical circulation and the thermodynamic equation further reveal that the increase of temperature in Jiangnan region is primarily attributed to the descending airflow.

Characteristics of Ozone Pollution and High-impact Meteorological Factors in Urban Cities: A Case of Suzhou

The problem of urban ozone (O3) pollution has become prominent in recent years. However, the meteorological factors associated with O3 pollution remain unclear. Analyzing the characteristics of O3 pollution in Suzhou, as a typical urban city, and exploring the high-impact meteorological factors with O3 pollution are crucial to the prevention and control of air pollution in this region. This study used correlation analysis and machine learning methods to analyze the variation in O3 concentration and the relationship between meteorological driving factors in Suzhou based on the O3 concentration data provided by Suzhou Environmental Monitoring Center and the contemporaneous meteorological observation data in Suzhou from April to September in 2015 to 2020. The results showed that: ① O3 pollution exceeding the standard rate was more than 20% in ozone seasons during the past six years; further, pollution days of O3 and the number of pollution days of O3 as the primary pollutant increased yearly. Evidently, the problem of O3 pollution has become increasingly prominent. ② The diurnal variations in O3 were unimodal with the valley point at 07:00 and the highest peak between 15:00 and 16:00. Similar trends were found in diurnal variations of both air temperature and solar radiation, but the daily highest peak came earlier than that of O3. The results also showed an apparent weekend effect of O3 concentration in 2017 and 2019 and a significant correlation between O3 concentration and solar irradiance during the week. In addition, the monthly variation in O3 concentration and pollution exceeding the standard rate was bimodal. ③The occurrence of ozone pollution was affected by various meteorological conditions. The maximum number of days appeared when daily sunshine hours lasted longer than 7 hours, with a daily maximum air temperature around 30℃, solar irradiance ranging from 350 to 440 kW·m-2, and relative humidity ranging from 50% to 75%, at which time the intensity of pollution was the strongest. When the wind speed of easterly wind was less than 1.5 m·s-1, or the wind speed of southwest wind was less than 3.5 m·s-1, moderate ozone pollution occurred. ④ An optimal prediction model of O3 concentration was established based on machine learning, which had good predictive ability for O3 concentration in April, May, July, and September but did not perform well when O3 concentration exceeded 200 μg·m-3. Meanwhile, it was found that solar radiation had the most obvious effect on O3 concentration, followed by relative humidity, whereas the temperature and wind were less important than the former two factors.

Unfolding unique features of precipitation-temperature scaling across India

Warming of the climate is now unequivocal. However, probable dynamics of changes in the precipitation regimes remains disputable under potential future warming. Theoretically, increasing atmospheric heat translates to increase the atmospheric moisture holding capacity at the Clausius-Clapeyron (C-C) scaling rate in the absence of moisture limitation, which in turn raises the possibilities of more intense precipitation events. Here we investigated the scaling relationship between observed and reanalysis precipitation with surface air temperature and dew point temperature at daily and sub-daily time scales on annual and season-wise basis. To reach a robust conclusion, entire Indian mainland is considered as the study area that spans across a vast climatic characteristics. More influential temperature dependence is found for heavier precipitation events than the lighter ones on annual basis as well as for different seasons. Negative and peak type scaling patterns between the daily surface air temperature (SAT) and precipitation is noticed across the different climatic regimes of the study region. In contrast, positive dependence between dew point temperature (DPT) and precipitation is obtained to be dominant across the study region. Negative sensitivity noticed for the daily surface temperature is mainly the consequence of the local cooling effect due to the occurrence of precipitation and the moisture limitation at higher end of the local temperature. In general, the scaling relation varies from season to season, which tend towards a negative scaling in hotter seasons, but a positive scaling in colder seasons. Extreme precipitation can be better portrayed by sub-daily temperature conditions prior to the start of the storm events. Scaling relationship obtained between the sub-daily precipitation and surface air and dew point temperature exhibits greater consistency in the relationship across the regions. The Western Ghats region is consistently noticed to exhibit a positive scaling relation, whereas rest of the country exhibits mostly a peak type relation. The SAT considered up to 6-h prior to the precipitation might not reflect the actual response of precipitation towards the temperature increase, possibly due to the prevailing cloudy conditions preceding the precipitation event. Findings of this study provides a better understanding related to the anticipated changes in precipitation regimes under future climate with a warming condition across different climatic regimes.

THE HEAT STRESS INFLUENCE REDUCTION ON MILK PRODUCTIVITY

The article presents the results of research on the reduction of the negative influence of heat stress on the milk productivity of cows in the second half of lactation due to the use of a protein feed additive with protected protein and starch. One of the factors of effective milk production with intensive management of the industry is the creation of comfortable conditions for keeping animals on the farm. Highly productive cows are quite demanding on the conditions of maintenance and microclimate. The study of the productive action of the complex drug Bypass protein + passable starch under the influence of temperature stress was carried out by us for the first time. The influence of the thermal factor of the environment on the productivity of cows is well described in the literature and the mechanisms of such an effect are described. The main consequence of the reaction of cows to temperature stress is a decrease in the consumption of dry matter of feed. This factor becomes the main factor in reducing productivity due to energy and protein deficiency. The same reaction was observed in our studies, both in the control and experimental groups. But we confirmed for the first time that the actions of compensation of temperature stress can be controlled due to the configurations of protein and energy entering the body by bypassing the scar. In our research, it has been proven for the first time that even in the conditions of reduced feed consumption, this way of providing cows with protein and energy is a reliable way of managing the productivity of cows and stabilizing their homeostasis during the period of temperature conditions that are dangerous for the existence of animals. It was established that the decrease in daily milk yield by 1.3 kg is a consequence of the negative influence of the temperature factor, when the daily air temperature in the summer period was at the level of +24.5-36.4 oС. The proof of this is the decrease in the rate of decline in the level of milk productivity of the cows of the experimental groups in August, when the average daily air temperature dropped to +24-26 °C. Modernization of the feeding ration of high-yielding cows by increasing the content of non-degradable protein in the rumen to the norm during temperature stress contributed to better adaptation of animals to productivity and quality indicators of milk. Keywords: protected protein, cows, milk productivity, protein supplement, heat stress.

A 40-Year 1-km Daily Seamless Near-Surface Air Temperature Product Over Yellow River Basin of China

A 40-Year 1-km Daily Seamless Near-Surface Air Temperature Product Over Yellow River Basin of China

Long-term changes in surface air temperature over the Chinese mainland during 1901-2020

The magnitude of long-term surface climate warming over some regions, such as the Chinese mainland, is still uncertain due to the lack of observational data early in the 20th century. In this study, the monthly data series of the average, maximum, and minimum temperatures in the Chinese mainland during 1901-2020 were constructed based on the daily surface air temperature observations from 60 stations across the country, and the characteristics of the average, maximum, and minimum temperature, and diurnal temperature range (DTR) changes were analyzed. Results show that (1) regional average annual mean temperature in the Chinese mainland rose by 0.14°C per decade, maximum temperature rose by 0.07°C per decade, minimum temperature rose by 0.19°C per decade, and DTR decreased by 0.13°C per decade. All these trends are statistically significant (p &lt; 0.01); (2) the largest annual mean maximum temperature increase occurred in spring, followed by winter and autumn/summer, and the largest annual mean minimum temperature increase was in winter and spring, followed by autumn and summer; (3) annual mean DTR decreased significantly at a rate of -0.08, -0.12, -0.12, and -0.13°C per decade (p &lt; 0.01) in spring, summer, autumn, and winter, respectively; (4) the stations with drops in maximum temperature were mainly in Central China, southern North China, the southeastern coastal areas, and the middle and lower reaches of the Yangtze River, and the stations with significant increases in minimum temperature were located in North China, Northeast China, and Northwest China; (5) the areas with the fastest dropping DTR were mainly located in Northeast China and North China. The maximum and minimum temperature series for China based on climate anomalies are comparable to those based on other currently available datasets.

Сохранение клона дерева Закхея (Ficus sycomorus L.) В Ставропольском ботаническом саду

The purpose of the study is to preserve the plant-clone of the Fig tree Zacchaeus in the greenhouse of the Stavropol Botanical Garden. The current changed ecological situation and a large anthropogenic load have led to the deplorable state of the plant. To preserve it, the current members of the IOPS (Imperial Orthodox Palestine Society) and Russian scientists were tasked with preserving and reproducing Ficussycomorus L. The age of Ficussycomorus was determined – about 2000 years, the plant needs special therapeutic and preventive measures for its further preservation. Agrotechnical measures aimed at activating growth processes in the fig tree were carried out. For preservation, the evergreen biennial fig tree plant Zacchaeus was transferred to the Stavropol Botanical Garden named after V.V. Skripchinsky in 2016. The object was a clone of Ficussycomorus L. Phenological observations were carried out according to the generally accepted method. The plant is kept in the greenhouse of the Stavropol Botanical Garden with an average annual air temperature of plus 24.3°C. The highest average daily air temperatures of more than plus 27 to 30°C are observed from May to August, the lowest – in October, November plus 16 … 21°C. For the period 2016-2022 it increased its size from 30 cm to 82 cm, the number of lateral trunk branches from 3 to 20 pcs. A distinctive feature of the plant is a slowdown in growth in the autumn-winter period, partial fall of leaves and a decrease in their length (about 10% of the leaf mass remains on the tree), but syconia are constantly formed, regardless of the length of daylight hours.

Роль и динамика инфильтрации в структуре влагообмена зоны аэрации орошаемого поля

Purpose: scientific and technical substantiation of the water balance components of an irrigated field in the particular case of connecting an aquifer and an aeration zone through a capillary fringe. Materials and methods. The research was carried out at Pobeda LLC, Bagaevsky district, Elkin farmstead, in 2018 and 2019. When organizing the research, an integrated approach was used: stationary and experimental sites were used. The climatic conditions of the research objects correspond to the semi-arid steppe zone, the soils are southern chernozems. Results. As a result of processing data from field experience, it was determined that with infiltration varying from 0.183 to 1.915 mm: the average daily water supply ranged from 0.8 to 7.33 mm/day; relative moisture reserves – from 0.61 to 1.20; average daily air temperature – from 8.0 to 23.0 °C; average daily air humidity deficit – from 2.1 to 12.0 mbar; average daily evaporation – from 1.3 to 7.34 mm/day. The correlation analysis determined that, according to the correlation coefficient, the infiltration value has the greatest correlation – 0.86 and 0.63 with water supply (M + P) and relative moisture reserves (W0), respectively; the smallest – 0.28; 0.38 and 0.37 with temperature (t), air humidity deficit (dφ) and evaporation (Eω), respectively. In turn, the multifactor correlation analysis determined that the formation of the infiltration runoff volume in the system of vertical moisture exchange of an irrigated field has the greatest connection with a paired change in the values of water supply and relative moisture reserves. Conclusions: infiltration of irrigation water and atmospheric precipitation beyond the root layer is determined by the obtained empirical dependence, is observed when the moisture reserves of this layer exceed the moisture reserves corresponding to the minimum moisture capacity and water supply, and has the greatest close relationship according to the coefficient of multiple determination (R²) 81 % (multiple correlation coefficient R = 0.899) with changes in these two factors.