Average Monthly Precipitation Research Articles

Comparative Performance Evaluation of ANN and Hybrid ANN-HBA Models for Temporal and Spatial Modeling of Precipitation in East Azarbaijan Province of Iran

In this study, temporal and spatial modeling of precipitation was performed in East Azarbaijan province of Iran using 27-year (1996-2022) data by employing two neural network models, i.e., stand-alone artificial neural network (ANN) and hybrid ANNHoney badger optimization algorithm (ANN-HBA). In temporal modeling, one-month and two-month precipitation delay steps were used as input parameters, and monthly precipitation was considered as output parameter. On the other hand, in spatial modeling, longitude, latitude, and altitude were used as input parameters and average monthly precipitation was considered as output parameter. Comparative performance of both the employed models was evaluated using three statistical criteria, i.e., root mean square error (RMSE), correlation coefficient (R) and Nash- Sutcliffe efficiency (NSE). In addition, precipitation in ungauged areas was estimated based on rainfall data of the nearby rain gauges through spatial interpolation methods such as isohyet and Thiessen polygon. Results of the temporal precipitation modeling revealed better performance of the hybrid ANN-HBA model over the stand-alone ANN model. Furthermore, the hybrid ANN-HBA model, during testing phase of the temporal modeling, could resemble the precipitation most accurately at Maraghe station (with values of R as 0.95, RMSE as 1 mm, and NSE as 0.85). Similarly, the hybrid ANN-HBA model during testing phase (with values of R as 0.95, RMSE as 1 mm, and NSE as 0.96) outperformed the stand-alone ANN model in depicting the precipitation adequately at spatial scale.

Soils of xerophytic meadows of the Middle Podesen’ya: on the issues of accumulation of organic substances and biochemical activity

Relevance. Natural meadow communities, belonging to the dry meadows group, in the conditions of a decrease in floodplain of the leading water artery in the Bryansk region — the Desna River are characterized by significant changes in the mode of economic use. However, a significant part of dry meadows is used as pasture lands, so the regime of intensive exploitation of these lands significantly changes the ecological regimes of phytocenoses, reducing the carbon-depositing functions. For xerophytic (dry) meadows of natural origin, the establishment of soil carbon reserves, the identification of biochemical and microbiological activity is especially important in the light of the low stability of these communities under pasture load and wide distribution throughout the territory of the Middle Podesen’ya.Methods. The research provided for field route studies and in-house data processing using the methods of trial sites, the method of ecological and floral classification, the method of ecological scales (according to G. Ellenberg), ecological and chemical methods — determination of organic carbon, the weight method, biochemical and microbiological methods for the study of the biocompatible body.Results. For the soils of xerophytic (dry) meadows, for the first time, carbon-absorbing capacity, enzymatic activity for urease, catalase, cellulase, depending on the phytocenotic complex, has been established for the Middle Podesen’ya. A positive strong correlation has been established with organic carbon and average monthly precipitation in June, July and August. Over a two-year observation period, the amount of total organic carbon in the soil changed in a number of associations communities: Festuco ovinae-Koelerium delavignei > control > Agrimonio eupatoriae-Poetum angustifoliae > Caro carvi-Deschampsietum > Anthoxantho-Agrostietum tenuis > Hieracio pilosellae-Agrostietum tenuis > Koelerio delavignei-Festucetum rubrae > Anthyllidi-Trifolietum montani > Polygalo vulgaris-Anthoxanthoetum.

Scientific justification of Mycobacterium avium survival in natural environment of Republic of Dagestan

Contamination of the environment with the infectious animal disease agents is still a pressing problem for the poultry farms. Mycobacterium avium can grow and replicate in organic wastes from the poultry farms for a long time thus contaminating vast adjacent areas and being the source of infection not only for wild and domestic animals but also for humans. The studies were aimed at the examination of the duration of Mycobacterium avium survival in the natural environment in two geographical regions of the Republic of Dagestan characterized by different soil and climate. Samples of Mycobacterium avium-contaminated feces and soil collected from pastures and farmyards (on the surface and from 5 cm depth) were tested. The experiments demonstrated that pathogenic for chickens mycobacteria survived for up to 30 days in the samples collected in the sub-mountainous areas in summertime, when the air temperature ranged from 15.1 to 30 °С, land surface temperature – from 17 to 38 °С, air humidity – from 44 to 94% and average monthly precipitation amounted to 1.5 mm. From September to May, with the air temperature ranging from –10.8 to +25 °C, land surface temperature from –14 to +30 °C, air humidity 26–100% and average precipitation 0.39 mm, the bacteria survived for up to 213 days on the soil surface on the pastures and farmyards, and for up to 243 days at the depth of 5 cm and in the feces. In the plain area, in the same time period in the slightly saline soil with high humus content and at air temperature from –11.9 to +27.3 °C, soil temperature from –13 to +45 °C, air humidity from 37 to 100% and average precipitation 20.4 mm, Mycobacterium avium survived just like in the sub-mountainous area, i.e. for 213 and 243 days, respectively. The post-mortem lesions in the internal organs of the poultry corresponded to the tuberculosis clinical signs in 86 of 171 birds (50.3%). The study results will allow for the development of the optimal algorithm for animal health and management measures aimed at tuberculosis eradication on the poultry farms.

Analysis of environmental factors influencing lumpy skin disease outbreak seasonality and assessment of its spread risk in the Saratovskaya oblast of Russia.

Lumpy skin disease (LSD) is a transboundary viral disease of cattle that causes serious economic losses due to a significant decrease in meat and milk productivity. This study analyzed the influence of natural and anthropogenic environmental factors on LSD spread seasonality and assessed the risk of LSD outbreaks in the Saratovskaya oblast of the Russian Federation. Data on LSD outbreaks and environmental factors during different seasons were collected for the period 2011-2020 in the Balkan Peninsula, Middle East, and Russia. Risk assessment was performed using mathematical modeling with generalized linear regression and maximum entropy. Fourteen statistically significant environmental factors influencing LSD spread were identified. The analysis of MaxEnt models built using the selected factors showed that the presence of the pathogen is mostly exerted by: the density of susceptible cattle (an increased risk is observed at a density above 10 and 20 heads/10 km2 in winter and autumn, with a permanent risk in spring and summer), the density of water bodies (the risk is increased at any density in winter and autumn, in the range of 13-23.5 m2/km2 in spring, in the ranges of 0-8 and over 14.5 m2/km2 in summer), and average monthly precipitation rate (the most risky are 105-185 mm/month in winter, 35 mm in spring, 15-105 mm in summer, and above 50 mm in autumn). LSD tends to spread during the warm season. Compared with other test zones, the Saratovskaya oblast has a negligible risk of disease spread (in winter), low risk (in spring), or medium risk (in summer and autumn). The annual risk is low to medium.

Evaluation of climate change impact on plants and hydrology

Climate change (CC) is the menace of the hour impacting every facet of human existence. Regional CC and its impact studies are crucial in that they contribute to global change. The current study aims to investigate the prevalence of CC in Charsadda, Pakistan and its impact on vegetation and hydrology of the region to understand microclimate variability contribution to global CC. Utilizing local climate data for 20 years (2001–2020), Modified Mann-Kendall and Sen’s Slope statistics were employed to determine monthly and seasonal trends in climate variables. Significant changing climate variables were regressed on Moderate resolution Imaging Spectroradiometer (MODIS) satellite dataset viz. normalized difference vegetation index (NDVI). Due to the prominent climate factor impacting vegetation, NDVI was further correlated to MODIS land surface temperature (LST). Floods being the conspicuous climate calamity were mapped for 2005 and 2010 using satellites Landsat 5 and 7 dataset viz. normalized difference water index (NDWI) with flood risk assessment by watershed delineation. The findings revealed significant (p < 0.05) variability in climate variables (average monthly and summer maximum temperature, and average monthly and summer precipitation) that are driving CC and impacting vegetation and hydrology in the region. Temperature and solar radiation affect NDVI adversely while precipitation and relative humidity has positive impact on vegetation. NDVI varied greatly spatiotemporally, often increasing but worsening in some areas (Shabqadar, Abazai, Palai and Charsadda city with NDVI = 0.1–0.3) of the study region as a result of extreme weather events. Temporally, NDVI improved with an overall positive trend with a stage (2007–2016) of noticeable zigzag fluctuation. Spatial grids with higher LST (>40°C) were either devoid of or with sparse NDVI (<0.3) presenting global warming as peril to vegetation. NDWI maps (2005, 2010 floods) indicate that after floods wreaked havoc on the region altering the vegetation pattern revealing heavy irregular precipitation as the next to temperature in jeopardizing vegetation of the region. Lower elevation regions along the Swat and Kabul Rivers with a greater risk of flooding were identified by watershed delineation. The study suggests that local governments and stakeholders implement CC mitigation strategies and plans for vegetation restoration, flood alerts with post-flood management for regional sustainable development.

Climate and disease in historical urban space: evidence from 19th century Poznań, Poland

Abstract. This study examines the relationship between temperature levels and precipitation amounts as explanatory variables for the probability of death due to waterborne and airborne diseases in historical urban space. To date, the literature has not focused on the climatological epidemiology of 19th century Polish urban areas. We used individual mortality data from Poznań parish death registers between 1850 and 1900. Each deceased individual was assigned average monthly temperature values and precipitation amounts in the month of death, LAG1 (1-month-lagged) temperature and LAG1 rainfall, and place of residence. We studied the relationship between weather conditions and mortality using formalized statistical models reflecting the discrete nature of the response data (via multinomial logistic regression). Lagged monthly average temperature levels and lagged monthly average precipitation amounts were better predictors of airborne and waterborne disease mortality than the concurrent (non-lagged) monthly averages. The lagged effects of temperature and precipitation on waterborne and airborne diseases were significant (except for the smooth lagged average monthly temperature effect for airborne diseases). There was also significant spatial heterogeneity (differences among city quarters) in the prevalence of deaths due to waterborne and airborne diseases.

Changes in the hydrological regime and Climatic variability assessment within the Belaya River catchment, Russia

The trends of changes in the indicators of the hydrological regime and climatic variability in the catchment area of the Belaya River were assessed. Mann-Kendall test and Sen's slope estimator at 8 out of 10 (80%) in the considered posts showed the presence of a positive trend in changes in the average monthly values of streamflow. At the same time, meteorological data sets at 19 of 34 (56%) observation stations have a positive trend of changes in the average monthly precipitation and temperature.

Long Memory in Average Monthly Temperatures and Precipitations in Guatemala

Abstract In this paper, we perform a fractional integration analysis of the average monthly temperature and precipitation data in 17 departments of Guatemala. Two analyses are performed, the first with the original data and the second with the anomalies based on the period January 1994–December 1999. The results indicate that there is a significant positive time trend in temperatures in the departments of Guatemala (0.0045°C month−1), Quetzaltenango (0.0040°C month−1), Escuintla (0.0034°C month−1), and Huehuetenango (0.0047°C month−1), whereas in the case of precipitation no time trend was observed. An important relevant result is that the departments of El Progreso, Baja Verapaz, and Guatemala occupy the second, third and fourth highest levels of persistence for both temperatures and precipitation, with Sacatepéquez and Quiché displaying the first places for temperature and precipitation, respectively, thus making these five departments the ones that are most vulnerable to climate change since a shock would take a long time to disappear.

Response of Metabolites in Cymbopogon distans Leaves to Water Addition in Karst Areas during Different Seasons

Climate change could influence the plant response to drought stress in karst environments. However, fewer related studies have been reported. This study examined the impact of artificial water addition on the accumulation of metabolites of Cymbopogon distans with a non-targeted metabolomics approach during both the dry and wet seasons. Three water treatment gradients (CK, T1, and T2, indicating 0%, +20%, and +40% relative to the average monthly precipitation, respectively) were chosen. The findings of our study indicate that the levels of primary metabolites were higher in the leaves of C. distans during the dry season compared to the rainy season. In addition, the presence of water did not have a substantial impact on the composition and functionality of metabolites between the wet and drought seasons. The contents of some lipids were greater during the dry season, while others were greater during the wet season. During the dry season, the contents of FA, DG, MGDG, SQDG, TG, and PR decreased with water addition. Our findings demonstrated that artificial water addition might have a greater impact on metabolite accumulation during the dry season in drought-tolerant species in karst areas. Due to the buildup of certain metabolites, they exhibit clear drought resistance. At the same time, water addition during the dry season will also cause a certain stress, affecting the adaptability of plants. These findings have significant ramifications for the management and choice of species in various sea seasons in karst regions.

Selection of representative near-future climate simulations by minimizing bias in average monthly temperature and precipitation

Selection of representative near-future climate simulations by minimizing bias in average monthly temperature and precipitation

Changes in the Urban Hydrological Cycle of the Future Using Low-Impact Development Based on Shared Socioeconomic Pathway Scenarios

Representative Concentration Pathway (RCP) scenarios have been used for various studies in the field of climate change. In this regard, the Shared Socioeconomic Pathway (SSP) scenario has been newly introduced to examine climate change impacts, but relevant research is still insufficient. For this reason, new SSP scenarios with a combination of Low-Impact Development (LID) techniques are applied to predict rainfall-runoff efficiency and hydrological variation. The inter-model variability in the monthly average precipitation for each GCM according to new SSP scenarios under future climate was investigated. Based on the RCP 4.5 and RCP 8.5 scenarios, the results show precipitation changes with an increase of 4.8% and 12.3%, respectively. Furthermore, precipitation projections under SSP2-4.5 and SSP5-8.5 scenarios are predicted to increase by 13.9% and 20.6%, respectively, indicating that the magnitude of precipitation increases with new climate change scenarios. The Storm Water Management Model (SWMM) during the future period indicated that LID applications will reduce runoff compared with scenarios with no LID application. In particular, the introduction of permeable pavement and infiltration trenches revealed the best runoff reduction performance among the combinations of LID techniques considered. In addition, this study projected changes in the urban hydrological cycle for the climate over the next 30 years to reflect the implementation of urban hydrological cycle plans, which take approximately 10 years. Overall, it was found that, in the future, LID applications will contribute to improving the sustainability of the urban hydrological cycle of the study area. The results of our study can provide future directions for water management strategies in Korea.

Balneability of the Municipality of São Luis – MA and the Influence of Rainfall Occurrences as an Externality Factor

Objective: To analyze the bathing conditions, that is, the quality of the water intended for primary contact recreation on the beaches of Ponta D’areia, São Marcos, Calhau and Olho d’água located in the municipality of São Luís- Maranhão. Theoretical framework: This study was conducted based on theoretical reflections on environmental issues, the relationship between society and nature. Issues of water use for recreation, environmental policies regarding bathing and externalities that interfere with the quality of water for bathing and their impacts on the health of the population were analyzed. Method: To select beaches and water collection sites, the most intense flow of bathers and the risks of interference with water quality were taken into account. Data on bathing ability and average monthly precipitation were obtained to verify bathing conditions, in addition to information on effluent release points and urban drainage. Results and conclusion: It was observed that the main influence on the incidence of thermotolerant coliforms is the presence of sanitary effluents on beaches, this factor becomes visible in the rainy season and with the lack of sanitary infrastructure. Implications of the research: This research will contribute to public policy measures, helping decision-making to improve public and environmental health in the city of São Luís- MA. Originality/value: This study has socio-environmental and scientific value, as it relates bathing ability to externalities such as the lack of environmental sanitation and high rainfall in the region.

Drought Assessment and Monitoring for Rajshahi District Using Meteorological Drought Indices

An analysis for drought condition has been made in the Rajshahi district of Bangladesh. The assessment of drought for the country has become an urgent need. The agriculture of the country is dependent on the amount of precipitation. As drought and precipitation are inversely related so it is desired to know the condition of Rajshahi. The main characteristics that define drought are the absence of precipitation for a lengthy period and a low distribution of rainfall in contrast to the normal climatic condition. The monthly maximum average temperature data, monthly minimum average temperature data and total monthly precipitation data for the last 48 years (1971-2019) from Bangladesh Meteorological Department (BMD) are utilized for the analysis process. An online software named DrinC is preferred due to its open-source platform and its user-friendly interface. The meteorological data serve as inputs for the software. The Deciles Index (DI), the Standardized Precipitation Index (SPI) and the Reconnaissance Drought Index (RDI) have been used to identify the drought condition of Rajshahi. The values of the DI and SPI are generated from the precipitation data. However, for the generation of the RDI, the precipitation data as well as the potential evapo-transpiration (PET) data, which is an intermediate data that is generated from the two different types of temperature data via DrinC software are used. The values of SPI, RDI and DI values are presented in a tabular as well as in graphical form. From the comparison of these data and from the study of the recurrence interval the state and the repetition of drought in Rajshahi district can be determined.

Simulation of the Potential Impacts of Projected Climate and Land Use Change on Runoff under CMIP6 Scenarios

Assessing the impacts of climate change and land use/land cover changes on water resources within a catchment is essential because it helps us understand how these dynamic factors affect the quantity, quality, and availability of freshwater. This knowledge is crucial for making informed decisions about water management, conservation, and adaptation strategies, especially in regions facing increasing environmental uncertainties and challenges to water resource sustainability. In Pakistan’s Kunhar River Basin (KRB), this investigation explores the potential effects of shifting land use/land cover (LULC), and climate on stream flows. The SWAT (Soil and Water Assessment Tool), a semi-distributed hydrological model, and the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) dataset from multiple global climate models (GCMs) were used to evaluate these effects. The temperature and precipitation data were downscaled using the CMhyd software; for both shared socioeconomic pathways (SSP2 and SSP5), the top-performing GCM out of four was required to produce downscaled precipitation and temperature predictions while taking future land use characteristics into account. The output from the chosen GCM indicated that by the conclusion of the 21st century, relative to the reference period (1985–2014), the study area’s average monthly precipitation, highest temperature, and lowest temperature will be increasing. Precipitation is anticipated to increase between 2015 and 2100 by 20.5% and 29.1% according to the SSP2 and SSP5 scenarios, respectively. This study’s findings, which emphasize the need for project planners and managers taking into account the effects of climate and land cover changes in their management techniques, show that climate change can have a significant impact on the changing seasons of flows in the Kunhar River basin.

INFLUENCE OF DIGITAL ELEVATION MODEL RESOLUTION ON MAPPING TERRITORY SUSCEPTIBILITY TO LANDSLIDE DEVELOPMENT

Link for citation: Van B. Duong, Fomenko I.K., Duc T. Ta, Trung K. Nguyen, Zerkal O.V., Gorobtsov D.N., Hong D. Vu. Influence of digital elevation model resolution on mapping territory susceptibility to landslide development. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 8, рр. 164-181. In Rus. The relevance. Landslides are one of the most hazardous natural disasters in the world, causing significant economic damage and human deaths. For 20 years (1995–2014), 3876 landslides killed 163658 people and injured 11689 people, as reported by the U. Haque study (2019), based on the data from 128 countries. Excluding events triggered by earthquakes, the total number of fatal landslides from 2004 to 2016 was 4862, and most landslides (75 %) occurred in Asia. In Vietnam, particularly in the northern mountainous regions, landslides frequently caused considerable losses of life and property. The systematic evaluation of landslide hazards is a crucial component of Vietnam's disaster prevention strategy. The main aim of this study is to assess the landslide susceptibility of the Batxat district, Laocai province (Vietnam), using four digital elevation model resolutions (10, 30, 40, and 60 m) and nine landslide causative factors: slope aspect, elevation, slope, distance to roads, distance to faults, distance to drainage, average monthly precipitation, land use, and weathering crust. Object of the study is the landslide susceptibility in Batxat district, Laocai province, Vietnam. Methods: Certainty Factor method, fractal method. Results. The performed analyses indicated a statistically significant relationship between the distribution of landslides and the landslide causative factors in the study area. As a result, the territory was divided into five zones according to its susceptibility to the landslide process: very low, low, moderate, high, and very high. The very low landslide susceptibility zone is less than 10 % of the study area, while the very high susceptibility zone varies from 14,95 to 18,32 %, depending on the digital elevation model spatial resolution. Analysis of the Receiver Operating Characteristics curve revealed that all models, independent of digital elevation model resolution, have good prediction efficiency, with the area under the receiver operating characteristic curve over 70 %. In addition, the Receiver operating characteristic and fractal analysis results indicated that the model with a digital elevation model spatial resolution of 60 m has the highest accuracy. This significant conclusion may be explained by the fact that the accuracy of the landslide susceptibility assessment result is dependent not only on the digital elevation model resolution but also on the ratio of the digital elevation model resolution and the average area of landslides in the study area. This conclusion proves that it is necessary to depict landslide locations and their detailed morphological characteristics on the landslide inventory maps.

The Impact of ENSO on the Precipitation in Iraq Regions

Abstract Precipitation is considered one of the important weather variables in determining the climate of any region in the world, and perhaps the precipitation in Iraq is witnessing an incomprehensible seasonal fluctuation. The work tries to identify the reasons for this fluctuation, from one season to another. The monthly average precipitation data in Iraq was obtained by Global Precipitation Climatology Project GPCP. Also, data for sea surface temperature anomalies (SST) for the four El Nino regions, as well as relative humidity and zonal wind speed were obtained from the National Centres for Environmental Prediction NCEP and National Centre for Atmospheric Research NCAR. The study period extended from 1980 to 2022, where the correlation of monthly precipitation average in Iraq with El Nino and La Niña events was tested, and it was found that there was a positive proportional effect of the El Nino event on the increase in rainfall rates in Iraq, the correlation coefficient R about 0.8 in North and Northern-East of Iraq. To explain this, the correlation between El Niño events, relative humidity, and zonal wind speed was tested. It was found that there is a proportional effect of El Nino on the relative humidity and an inverse effect on the zonal wind speed. Central and southern Iraq is less affected by El Niño and La Niña events, as the correlation coefficient of monthly precipitation average with El Niño phenomenon is approximately 0.5 to 0.6.

Environmental Adaptability and Energy Investment Strategy of Different Cunninghamia lanceolata Clones Based on Leaf Calorific Value and Construction Cost Characteristics.

The calorific value and construction cost of leaves reflect the utilization strategy of plants for environmental resources. Their genetic characteristics and leaf functional traits as well as climate change affect the calorific values. This study explores the differences in energy investment strategies and the response characteristics of energy utilization in leaves to climate change among nine clones of Chinese fir (Cunninghamia lanceolata). Considering the objectives, the differences in the energy utilization strategies were analyzed by determining the leaf nutrients, specific leaf area, and leaf calorific value and by calculating the construction cost. The results showed a significant difference in the ash-free calorific value and construction cost of leaves among different Chinese fir clones (p < 0.05). There were also significant differences in leaf carbon (C) content, leaf nitrogen (N) content, specific leaf area, and ash content. The correlation analysis showed that leaves' ash-free calorific value and construction cost were positively correlated with the C content. Principal component analysis (PCA) showed that P2 is inclined to the "fast investment return" energy investment strategy, while L27 is inclined to the "slow investment return" energy investment strategy. Redundancy analysis (RDA) indicates that the monthly average temperature strongly correlates positively with leaf construction cost, N content, and specific leaf area. The monthly average precipitation positively impacts the ash-free calorific value and construction cost of leaves. In conclusion, there are obvious differences in energy investment strategies among different Chinese fir clones. When temperature and precipitation change, Chinese fir leaves can adjust their energy investment to adapt to environmental changes. In the future, attention should be paid to the impact of climate change-related aspects on the growth and development of Chinese fir plantations.

Trends in climate change observed under tropical wet and tropical montane climates; A case study from Sri Lanka

Climate change-related changes in temperature and precipitation trends must be investigated at local, regional and global levels. Temperature and precipitation trends in two selected regions having tropical wet and tropical montane climates (i.e., Colombo and Nuwara Eliya respectively) in Sri Lanka were studied for a 30 year period from 1989 to 2019, to evaluate the temporal dynamics of climate change. Precipitation trends were analyzed on annual, monthly, and seasonal scales, while the trends in mean, minimum, and maximum temperatures were examined on annual and monthly scales. Decadal time series plots were used to study decadal variations in average temperature and precipitation. The trends in extreme temperature and precipitation events were also evaluated. In addition, the trends in diurnal temperature range (DTR), cool and warm nights, and heat index (HI) were studied. The significance of trends was evaluated using the Mann-Kendall test, while the magnitude of the slope was assessed by Sen’s slope estimator. Clear statistically significant increasing trends were observed for the mean annual temperatures under the tropical wet and tropical montane climates, and no clear trends were observed in annual precipitation in both districts. There were decreasing trends in south-west monsoon rainfall, with a significant decrease in Nuwara Eliya under the tropical montane climate. Increasing trends were observed for the average monthly precipitation in November (i.e., during the inter-monsoonal rains) and average monthly temperature in April (i.e., the hottest month) over the last decade (i.e., 2010-2019) in Colombo. The DTR has significantly decreased over the last three decades in Colombo. A significant upward trend was observed for HI values during the last decade in Colombo. Colombo also showed a statistically significant decreasing trend in the number of cool nights and a statistically significant decreasing trend in the number of warm nights over the last decade.

Analysis of the dynamics and precipitation regime in the cross-border region Poland-Belarus- Ukraine (2010-2018)

&#x0D; &#x0D; &#x0D; The work analyzes the dynamics and regime of atmospheric precipitation in the cross-border region of Poland-Belarus-Ukraine during the period 2010-2018. This time period was chosen, in particular, due to the need to find the prerequisites for the strong shallowing of lake complexes and the depletion of groundwater in the Polish region in 2019, which caused significant social and scientific resonance. The source data for the statistical part of the work were archival information from 17 weather stations in the specified region for this period. The main results of the study: 1) the dynamics of the average monthly precipitation amounts for each meteorological station were calculated and analyzed (Lutsk, Svityaz, Manevychi, Kovel, Liubeshiv, Volodymyr, Rivne, Dubno, Sarny, Brody, Rava-Ruska, Kamianka-Buzka, Pinsk, Pruzhany, Terespol, Wlodawa, Zamosc), the average amounts of precipitation that fell during the warm season of the year (IV-X months) and the cold season of the year (XI-III months), average annual precipitation amounts and precipitation amounts for the entire period, which was investigated (2010-2018). All calculated indicators were compared with the data of the climatic norm of 1961-1990). The annual number of days with precipitation, the warm and cold periods of the year, and the average values of this indicator were also determined. Based on the results of the statistical analysis, charts, cartograms, and several diagrams were developed that visually represent the peculiarities of the dynamics of atmospheric precipitation in the studied region during the analyzed period (2010-2018). 2) on the basis of the calculated indicators, maps of the geographical distribution of precipitation amounts on the territory of the cross-border region Poland-Belarus-Ukraine during the studied period (annual amounts, cold and warm season amounts) were constructed. When comparing them with maps of the period of the 20th century. Changes in the geography of distribution and trends of modern growth of precipitation amounts in the study region were revealed. After the analysis, a number of conclusions and generalizations were made: 1. During the period 2010-2018 in the territory of the cross-border region Poland-Belarus- Ukraine, the average annual amounts of precipitation increased by 20-45 mm compared to the climatic standard, while the average annual number of days with precipitation decreased by 25-30%. 2. Annual amounts of precipitation exceeded 600 mm at almost all (16 out of 17) meteorological stations whose data were analyzed. 3. The distribution of days with atmospheric precipitation during the seasons of the year has changed. The ratio between the amounts of precipitation that fell in the warm and cold periods of the year changed from 75/25 to 60/40 on average. In general, in the studied region, there are trends towards a slight increase in annual precipitation amounts, a redistribution of precipitation amounts in liquid and solid state in favor of rains, and a reduction in the total number of days with precipitation during the year and a more even distribution of them during the warm and cold seasons, compared to the climatic norm.&#x0D; &#x0D; &#x0D;

THE APPLIED OF FUNCTIONAL DATA ANALYSIS TO COMPARISON 100 TIMES SIMULATED MONTHLY RAINFALL USING SOME TWO PARAMETERS DISTRIBUTION

Three probability models of mothly rainfall such as Gamma, Weibull and Log Normal distribution are evaluated in terms of their ability to reproduce the mean statistics derived from 100 times simulation of monthly rainfall in the Pekanbaru City, Indonesia. One of the important studies is to investigate and understand the simulate mean monthly rainfall patterns that occur throughout the year. To identify the pattern, it requires a rainfall curve to represent monthly observation of rainfall received during the year. Functional data analysis (FDA) methods are capable to convert discrete data into a function that can represent the rainfall curve and as a result, try to describe the hidden patterns of the rainfall. This study is focused on investigating 100 curve average monthly rainfall simulatated by three different quantile functions using the FDA. The mean and standard deviation of FDA for average monthly precipitation are obtained. Through these two statistics a the confidence interval curves of the mean curve are presented represent 95% pointwise confidence intervals. In this study, most of the monthly average rainfall from the actual data were around the FDA mean and the monthly average rainfall was within the FDA confidence interval. In this study, 100 times monthly rainfall simulations using the quantile function of the gamma and log normal distributions found that the mean FDA can capture most of the mean monthly rainfall from historical data, and within the FDA interval. The contradictory results shown by the monthly rainfall simulations using the Weibull distribution, most of the monthly average rainfall historical data cannot be captured by the FDA mean and are outside the FDA confidence interval. Based on the Mean Absolute Error (MAE) value of the average monthly rainfall of historical data and the monthly average of the FDA, it can be concluded that the gamma distribution can produce simulated rain better than the log normal distribution.