Average Rainfall Research Articles

Identifying the pathways of extreme rainfall in South Africa using storm trajectory analysis and unsupervised machine learning techniques

Abstract This study has utilised National Oceanic and Atmospheric Administration (NOAA) NCEP/NCAR Reanalysis 1 project meteorological data and the HYSPLIT model to extract the air parcel trajectories for selected historical extreme rainfall events in South Africa. The k-means unsupervised machine learning algorithm has been used to cluster the resulting trajectories, and from this, the spatial origin of moisture for each of the rainfall events has been determined. It has been demonstrated that rainfall events on the east coast with moisture originating from the Indian Ocean have distinctly larger average maximum daily rainfall magnitudes (279 mm) compared to those that occur on the west coast with Atlantic Ocean influences (149 mm) and those events occurring in the central plateau (150 mm) where moisture has been continentally recirculated. Further, this study has suggested new metrics by which the HYSPLIT trajectories may be assessed and demonstrated the applicability of trajectory clustering in a region not previously studied. This insight may in future facilitate improved early warning systems based on monitoring of atmospheric systems, and an understanding of rainfall magnitudes and origins can be used to improve the prediction of design floods for infrastructure design.

Application of Revised Universal Soil Loss Equation (RUSLE) model for the estimation of soil erosion and prioritization of erosion-prone areas in Majuli Island, Assam, India

Soil erosion is a serious issue, causing loss of agricultural productivity, increase in sediment deposit in the riverbeds, and damage to the ecological balance of the affected areas. Proper assessment of the soil erosion rate is essential for managing natural resources. The present study employs a GIS-based RUSLE (Revised Universal Soil Loss Equation) model to estimate annual soil loss in Majuli River Island of Assam, India. Annual average rainfall, soil properties, topographic characteristics, and LULC were taken as inputs to identify the soil erosion susceptible areas. The result revealed that annual soil loss of the study area ranges between 0 to 711 t ha−1 yr−1, with a mean annual soil loss of 23.02 t ha−1 yr−1. The entire region was classified into six soil loss severity classes, around 90 % of the area was found to be very slightly affected (< 5 t ha−1 yr−1) by soil erosion, around 5 % slightly affected (5 – 10 t ha−1 yr−1), roughly 3% moderately affected (10 – 20 t ha−1 yr−1), around 1% moderate high (20 – 40 t ha−1 yr−1), nearly 0.3 % area affected severely (40 -80 t ha−1 yr−1) and very severely affected areas (> 80 t ha−1 yr−1) contributes 0.1 %. A total of six priority levels of conservation were demarcated village-wise; priority level I requires immediate attention, and so on. The research outcome can help effectively implement conservation and management practices to check soil erosion in the study area.

ON THE PERFORMANCE OF SARIMA AND SARIMAX MODEL IN FORECASTING MONTHLY AVERAGE RAINFALL IN KOGI STATE, NIGERIA

Forecasting monthly rainfall is very important in Kogi state for better approach to flood management and also plays a pivotal role in agriculture which remains a significant factor in Nigeria’s economy. Advanced time series univariate models such as Seasonal Autoregressive Integrated Moving Average (SARIMA) models are usually employed in modelling and forecasting rainfall in Nigeria due to their non-linear pattern and spatiotemporal variation. Few studies have attempted to investigate the influence of other climatic factors in modelling and prediction of rainfall pattern. This study examines the performance of a univariate seasonal ARIMA and seasonal ARIMA which uses monthly temperature and relative humidity as exogenous factors otherwise known as SARIMAX model in forecasting monthly average rainfall in Lokoja, the capital of Kogi state. The study uses monthly data on rainfall, temperature and relative humidity spanning from 2010 to 2022 obtained from Nigeria Meteorological Agency NiMet, Lokoja station. The series were appropriately differenced to attain stationarity. The plots of autocorrelation function (ACF) and partial autocorrelation function (PACF) were used to select some tentative models whose parameters would be estimated. The most suitable SARIMA model [SARIMA was chosen based on maximum Coefficient of Determination , and the minimum Akaike information criterion (AIC). However, SARIMAX model outperformed SARIMA model based on the criteria earlier highlighted. SARIMAX model was therefore recommended for modelling and forecasting monthly average rainfall in Kogi state.

Flood and Food Security in the Benue Valley: Stylized Facts

The scientific consensus is that global climatic change is caused by human activities. Global climate variation has altered the pattern of annual rainfall in most parts of the world, resulting in annual flooding with devastating effects on humanity. With many rivers that crisscross the Nigerian landscape, the country has experienced a number of flood incidents along the river basins (valleys) with varying degrees of devastation. This paper, thus, focuses on the effects of flood on food security in the Benue Valley. The specific objectives of the study include: to examine the effects of flood on food supply; prices of agricultural output; and the level of public and private aids to flood victims within the study area. A sample of households and market leaders were interviewed for the purpose of data collection. Data was equally sourced from Non-governmental Organizations, State Emergency Management Agencies, and other written sources. The data was analyzed and presented using simple bar charts. Findings revealed that there is always a gross inadequacy of food supply during the years of devastating floods compared to years of normal annual rainfall. Prices of agricultural products increased by almost 200% and household income declined significantly during the flood disaster years. Findings also revealed that private organizations sometimes render more aids to flood victims than the public sector. To arrest the danger of annual devastating floods in the Benue Valley, the paper recommends better water infrastructure management strategies like the construction of more dams and dredging of River Benue.

The empirical analysis of cereal production under the climate exchange and examining the effects of banks’ domestic credit on cereal production: Evidence from Turkey

In this study, it aims to examine the linkage among climate change, banks’ domestic credit and cereal production such as Turkey's CO2 emissions, average rainfall and average temperature in the period 1980-2019. In the study, firstly, the stationarity properties of the variables are examined by KPSS, ADF and Ng-Perron tests, and the presence of cointegration between the variables is investigated through the ARDL boundary test. Then, the long-run elasticities of the independent series are estimated by applying the ARDL model and the causality linkage among the series is detected through VECM method. Empirical findings show that there is cointegration among the variables and that in Turkey, banks’ domestic credit, CO2 emissions, average rainfall and increase in cereal production area increase cereal production, while average temperature increase reduces cereal production. At the same time, it is determined that there is a bidirectional causality between banks’ domestic credit, CO2 emissions, average rainfall and average temperature and grain production, while there exists a uni-directional causality extending from the grain production area to the grain production. Finally, as a result of the examinations, it is detected that there exists a mutual linkage between the financial sector and cereal production.

Analisis Faktor-Faktor yang Mempengaruhi Volume Produksi Padi Provinsi Aceh

The agricultural sector has a very significant contribution to the achievement of the Sustainable Development Goals (SDG's) and is also the second largest contributor to Gross Domestic Product (GDP). Aceh's agricultural sector excels in various commodities such as rice, corn, soybeans, and chili. One of the main commodities in Aceh's agricultural sector is rice. Rice is a staple food commodity for the Indonesian people whose needs continue to increase along with the increase in population and also as a source of income for the farming community in meeting their needs. The volume of rice production from year to year fluctuates greatly, experiencing a decrease or increase. the realization of the rice harvest from January to December 2022 amounted to 271.75 thousand hectares, or decreased by around 25.31 thousand hectares (8.52 percent) compared to 2021 which reached 297.06 thousand hectares. The purpose of this study is to analyze the factors that affect the volume of rice production in Aceh Province. The results of the study obtained a regression model Y = 556505,224 + 3,081 X1-1376,14 X2 + 139,57 X3 + 92,797 X4-1,019 X5. The results of the simultaneous test show that the harvest area, rainfall, irrigation area, seed use, and labor together or simultaneously have a significant effect on rice production at a significance level of 0.05. Partially, the variable that has a positive and significant effect on rice production is the variable of harvest area. In addition, the variable area of irrigation and the use of seeds also have a positive effect on rice production but not significant. Meanwhile, the variables of average rainfall and labor have a negative effect on rice paddy production.

Rise, fall and hope for the Sicilian endemic plant Muscari gussonei: A story of survival in the face of narrow germination optimum, climate changes, desertification and habitat fragmentation

Muscari gussonei is an endangered endemic plant growing on fragmented Mediterranean coastal dunes. This study focused on the germination performance of M. gussonei at two fixed temperatures, 10 and 15 °C, and at an alternating one, 10/20 °C, and on the multi-temporal trends of temperature and rainfall during 1931–2020, as well as on the patterns of desertification and land-cover changes over the last 60 years. High and similar germinability was found for different populations of M. gussonei, in particular, the final germination percentage (FGP) was ≥95 % for the three treatments. The general pattern was the lower the temperature the higher and faster the germination. However, germination speed varied significantly among populations. This intraspecific variability of germination behavior may suggest a certain level of ecophysiological plasticity in M. gussonei, thus raising hopes on the capacity of M. gussonei to respond better to the ongoing severe environmental changes. In the period 1931–2020, indeed, the average temperature rose by 1.5 °C, from 16.8 to 18.3 °C, which is equivalent to the enormous increase of 0.17 °C per decade. Similarly, the average rainfall declined by 100 mm, from 600 to 500 mm. Another serious stressor was desertification, which affects >90 % of the distributional area of M. gussonei. A further factor of ecological degradation is a considerably altered landscape, where the agricultural component accounts for c. 85 %, whereas natural and seminatural areas were only c. 10 %. Increasing temperature and dryness will inevitably reduce the germinability of M. gussonei, characterized by a narrow germination optimum of 10–15 °C. The future of M. gussonei looks even more dramatic if we consider its small and scattered populations distributed in an agricultural matrix affected by high levels of desertification. Only multivariate information at different space-time scales can provide an exhaustive picture for implementing effective conservation strategies.

ASSESSING THE RELATION BETWEEN LAND USE / LAND COVER CHANGES AND ENVIRONMENTAL PARAMETERS FOR CHENNAI CITY, TAMIL NADU: A REMOTE SENSING AND GIS APPROACH

Abstract. Land use land cover changes in coastal regions are prone to many factors like rapid urbanization and industrialization, tourism, and tideline changes etc. Chennai city, a coastal city of TamilNadu, India has witnessed tremendous changes in land use land cover over the past two decades due to rapid urbanization and industrialization. Remote sensing and GIS technologies can efficiently help in analyzing these changes. In this study, changes in land use land cover patterns of Chennai city from 2005 to 2016 were assessed using IRS P6 LISS III remotely sensed satellite images. Post classification comparison-based change detection method was used to identify the changes in LU/LC. The study shows an increase in compact built-up and industrial areas by 15.36 % and 7.22 % respectively and a decrease in agricultural land, wetlands, and water bodies by 3.66%, 1.73%, and 5.24% respectively over the past decade. The obtained LU/LC changes were correlated with environmental parameters like Land surface temperature (LST), annual average rainfall and average groundwater level to establish a relation. Observations have shown that the temperature in Chennai metropolitan city has increased by 6̊c from 2005 to 2016 and the rainfall has reduced by 100mm from 2005 to 2016. This study demonstrated the relation between LU/LC changes over the past decade and the variations in environmental parameters like increased LST, reduced rainfall and groundwater.

The role of drylines in thunderstorm initiation and record rainfall during an anomalously convective early summer season in South Africa

An average of 12 drylines are associated with thunderstorm development (convective drylines) during December in the western plateau of subtropical southern Africa. During December 2021, 20 convective drylines occurred. This was the highest number since the record began in 2010. December 2021 was also unusually wet over a large part of the summer rainfall region in South Africa. Monthly rainfall records were broken in the Northern Cape, Northwest and Free State provinces. Above-average rainfall had dire consequences for the maize industry over the central interior. The large-scale circulation during December 2021 was very conducive to dryline formation over the western plateau with a deeper than usual surface trough and strong low-level northeasterly moisture flux towards the climatologically dry western plateau region. Above normal wind speeds of mid-tropospheric northwesterlies and large-scale uplift contributed to a favorable environment for strong thunderstorms, as seen during a 6-day convective dryline event. Thunderstorms which were triggered along the dryline travelled east and contributed to the above normal rainfall observed during December 2021. Dryline and rainfall frequencies show large inter-annual variability. However, a positive Pearson correlation (r = 0.45; p < 0.05) between the number of dryline days and rainfall amounts were found between 1979 and 2021. This correlation increased (r = 0.53; p < 0.05) when rainfall amounts immediately east of the western plateau domain were also included, suggesting that dryline-related convection can have a significant influence on rainfall over the western plateau and further downstream.

ANALISIS KARAKTERISTIK IKLIM DAN HUJAN PADA LAHAN PERTANIAN DI KECAMATAN KEDIRI KABUPATEN LOMBOK BARAT

The availability of water on Earth's surface is influenced by rainfall and climate in a particular region. Water is a basic necessity for human beings and is used for various daily life purposes. One of these purposes is irrigation in agricultural lands. The agricultural sector has traditionally relied on the availability of water from rainfall and the suitability of the climate. Climate factors include air temperature, humidity, sunlight intensity, and wind speed. This research aims to determine the impact of rainfall and climate conditions on agricultural lands. The study utilizes descriptive analysis of climate data and its influence on agricultural lands. The research findings reveal that the average monthly rainfall in Kediri district, West Lombok Regency, is approximately 222.75 mm. The average temperature is 26.7 degrees Celsius, with an average humidity of 84.5%, average sunlight intensity of 65.9%, and an average wind speed of 3.1 knots. These rainfall and climate conditions can affect water availability, soil microbe growth, plant photosynthesis processes, and plant pollination processes in agricultural lands.

Spatial Association between Socioeconomic Factors, Physical Geographic Factors, and Suicide in Thailand

Background: Suicide is a significant cause of death in many countries worldwide. In Thailand, it ranks second in unnatural deaths, following accidents, with an increasing trend. This study aims to 1) describe the spatial distribution of suicide rates and 2) identify the spatial relationships among socioeconomic status, physical geography and suicide rates during the years 2012–2021. Methods: This study sought to explain the spatial distribution of suicide rates across provinces in Thailand from 2012 to 2021. The spatial relationships were analyzed using LISA and spatial regression. Results: The result obtained from univariate LISA indicated a concentration of suicide rates in the northern region of Thailand for the period from 2012 to 2021. Spatial regression analysis using OLS, SLM and SEM demonstrated the relationships between suicide rates and various variables, such as divorce rates, poverty rates, elderly proportions and NDWI. These factors exhibited a positive correlation with suicide rates and were statistically significant. Conversely, the NTL density and average rainfall displayed a negative correlation with suicide rates. Conclusion: Our study observed that the distribution of divorce rates, poverty population proportion, elderly population proportion and the normalized difference water index were likely to be associated with enhancing the suicide rate. However, the intensity of average Night-Time-Light (NTL) was observed to reduce the suicidal rate. Therefore, these present findings can be utilised in the development of policy as well as strategies concerning surveillance, control and prevention of suicide in Thailand.

Large-scale atmospheric teleconnections and spatiotemporal variability of extreme rainfall indices across India

Identifying trends in hydrometeorological time series during extreme weather events and their interactions with large-scale atmospheric teleconnections is crucial for climate change research. This study evaluates 14 precipitation-based indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) across seven climatic zones of India using gridded daily rainfall data from the India Meteorological Department (IMD) for 120 years (1902–2021) utilised. Trend analysis was carried out using the Mann-Kendall (MK) test, Theil-slope Sen's estimator, Innovative Trend Analysis (ITA), and other statistical tools. Change point detection is established using the Pettitte test and Cumulative Sum algorithm. The relationships between large-scale atmospheric teleconnections and ETCCDI indices are also found, and Multiple Linear Regression (MLR) models are developed between them.The results show significant increasing trends in extreme rainfall indices in India's Ladakh region, located in the arid desert-cold climatic zone. The annual, Southwest Monsoon (SW-Monsoon), Northeast Monsoon (NE-Monsoon), and summer rainfall trends were positive, while winter rainfall had a negative trend across most climatic zones. Significant associations between large-scale atmospheric teleconnections, including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Global Temperature Anomaly (GTA), Southern Oscillation Index (SOI), SST of Niño 3.4 region, Oceanic Niño Index (ONI), and Dipole Mode Index (IOD) and ETCCDI indices were established across multiple climatic zones. Using MLR analysis, this study attempts to establish, for the first time, the relationship between teleconnections and ETCCDI indices across India. Extreme rainfall indices are influenced by climate change during the SW-Monsoon across most of the climatic zones of India. During the previous El Niño event (2014–2016), average annual rainfall decreased by 19.5%, SW-Monsoon rainfall decreased by 25.2%, and NE-Monsoon rainfall decreased by 64.1% in India. The findings may provide valuable insights into mitigation strategies to sustain the adverse effects of extreme weather conditions and enhance climate resilience.

Post-harvest management and characteristics of melon cultivars fruits and their prospects in the Roraima savannah: a review

The melon (Cucumis melo L.) holds significant economic importance on the global stage, with Brazil standing out as a strong exporter. Climatic conditions such as high temperatures, low relative humidity, and extended periods of sunlight are beneficial for the fruit's production and quality. The Northeast region of Roraima, particularly the municipalities of Bonfim and Normandia, close to the border with Guyana, has a semi-arid climate with an average annual rainfall between 1,200 and 1,400 mm. After harvesting, horticultural products begin to respire, a process that compromises post-harvest quality, leading to a decrease in organoleptic characteristics, firmness, sugar content, and loss of mass. The Cantaloupensis and Reticulatus melons, which are climacteric, have a high synthesis of ethylene and high respiratory rates in the fruit, resulting in flavor deterioration, firmness loss, and a shorter post-harvest shelf life. In contrast, non-climacteric melons, such as the inodorus group, display reduced ethylene synthesis, white flesh, subtle aroma, no pronounced ripening, and a longer post-harvest lifespan. It's worth noting that the melon market offers a variety of significant cultivars, resistant to pests, with high productivity and excellent post-harvest quality. This study aimed to address a literature review on the management of melon cultivation, development conditions of the crop, and post-harvest of melon cultivars in the Roraima Savanna."

Spatiotemporal Analysis of Extreme Rainfall and Meteorological Drought Events over the Angat Watershed, Philippines

Understanding the spatiotemporal distribution of extreme rainfall and meteorological drought on a watershed scale could be beneficial for local management of any water resources system that supports dam operation and river conservation. This study considered the watershed of Angat as a case, given its economic importance in the Philippines. A series of homogeneity tests were initially conducted on each rainfall dataset from monitoring stations in and near the watershed, followed by trend analysis to determine the rate and direction of change in the annual and seasonal rainfall extreme indices in terms of intensity, duration, and frequency. Three indices, using the rainfall deviation method (%DEV), percent of normal rainfall index (PNRI), and Standardized Precipitation Index (SPI), were also used to identify meteorological drought events. Generally, rainfall in the watershed has an increasing annual PCPTOT (4–32 mm/year), with increasing frequency and intensity in heavy rainfall and wet days. A significant increasing trend (α = 5%) in the seasonal PCPTOT (7–65 mm/year) and R10mm (1.7–10.0 days/decade) was particularly observed in all stations during the Amihan Monsoon Season (Dec–Feb). The observed increasing rainfall intensity and frequency, if it continues in the future, could have an implication both for the water resources operation to satisfy the multiple objectives of Angat Reservoir and for the flood operation that prevents damage in the downstream areas. The effect of each ENSO (El Niño- Southern Oscillation) phase on the rainfall is unique in magnitude, intensity, and duration. The seasonal reversal of the ENSO in the extreme rainfall and meteorological drought signals in Angat Watershed was also evident. The identified meteorological drought events in the watershed based on SPI-12 persisted up to 12–33 months, could reduce more than 60% (PNRI &lt; 40%) of the normal rainfall. Insights from the study have implications for the hydrology of the watershed that should be considered for the water resources management of the Angat Reservoir.

Climate Change Impacts on Shallow Landslide Events and on the Performance of the Regional Shallow Landslide Early Warning System of Piemonte (Northwestern Italy)

Shallow landslides are one of the most dangerous gravitational phenomena. They are responsible for more than 50% of causalities due to landslides in northwestern Italy in the last century. The aim of the research study presented here is focused on understanding if and how climate change influences the occurrence and behavior of this landslide type. A total of 120 widespread shallow landslide events have been analyzed from 1960 to 2019, taking into account the spatial and time distribution in association with related rainfall historical data elaborated by the Optimal Interpolation (OI) model. Results underline that shallow landslide events’ number (aggregated per five-year intervals) is characterized by a weak trend consisting of a slight increase in the Alps and a more pronounced decrease in the hilly and Apennines environments. In addition, the trend of the annual accumulated rainfall average shows a weak drop in the winter season of about 9 mm in ten years. Moreover, the rainy days have generally decreased over the hills and Apennines, while in the Alps, only in the summer season, with a decreasing rate of about 1.5 days every ten years. The rainfall trends are in accordance with those of shallow landslide events, pointing out the close and direct dependence of the shallow landslide events on the rainfall regime variations. The results obtained were also used to validate the robustness of the performance of the Regional Shallow Landslide Early Warning System adopted in Piemonte over the investigated period, confirming the effectiveness of the trigger thresholds used for the entire historical series and for different geographical areas.

Climate variability, rainwater-harvesting structures and groundwater levels in Odisha, India: an empirical analysis

ABSTRACT To examine the driver of groundwater depletion, this paper estimates a dynamic panel regression model using district-level secondary data from 1995 to 2017. Results show that the number of rainwater-harvesting structures, annual average rainfall, forest cover and net sown area improve groundwater levels. Tube well irrigation and rice cultivation can adversely affect groundwater levels. The positive relationship between surface water and improved groundwater level is consistent in all the estimated models. Hence, efficient use and management of surface and groundwater are crucial for the long-term sustainability of water resources.

Impact of different water penetration criteria and cavity ventilation rates on the risk of mold growth in timber frame walls with brick veneer cladding

The present paper investigates the impact of different water penetration criteria on the risk for damage in a common type of building envelope in Nordic countries, timber frame walls with brick masonry veneer. The studied walls are evaluated based on one damage criterion, the risk of mold growth. The study investigates several parameters: water penetration criterion, type of moisture source (uniformly distributed or point source) and its position in the wall assembly, air change rate (ACR) (representing different workmanship scenarios), wind-driven rain (WDR) coefficient, and locations (Gothenburg and Rensjön, with different average annual rainfall and temperature). Two criteria on how to implement water penetration are compared: a) a commonly accepted reference model that assumes one percent of all wind-driven rain deposited on the façade to penetrate the clay brick cladding, and b) a new criterion stating that 3.8% of WDR penetrates when the water content of the brick veneer cladding is above 90% of its saturation capacity. The simulation is done for a thirteen-year period with WUFI Pro and WUFI 2D. The results indicate the greater importance of implementing water penetration compared to ventilation in cavities. Further, the findings suggest that the moisture source’s location significantly impacts the mold growth risk. The results also show that the choice of the WDR coefficient affects the risks, which suggests that this factor needs accurate quantification for hygrothermal analyses. The results in this study suggest that an effective measure for the design/maintenance of such walls should incorporate: a) limiting the amount of water penetrating through the cladding, particularly stopping water from reaching the sensitive elements, i.e., timber studs, b) removing extruded mortar stemming from poor workmanship, if any, which may act as a capillary bridge.

O- and H-isotope record of Cape Town rainfall from 1996 to 2022: the effect of increasing temperature, and the ‘water crisis’ of 2015 to 2018

Abstract The O- and H-isotope composition of rainfall collected monthly at the University of Cape Town (UCT) between 2009 and 2022 has been added to a previously published data set from 1996 to 2008 to make a continuous 27 year record. Monthly rainfall over the 27 year period has a range in δD and δ18O values from -57 to +21‰ and -8.1 to +3.5‰, respectively, and shows limited but discernible temperature and amount effects. The 27 year rainfall record defines a Local Meteoric Water Line (LMWL) whose equation is δD = 5.96*δ18O + 7.00 (r = 0.88), a slight change from the LMWL of 1996 to 2009 (6.41*δ18O + 8.89). Annual rainfall at UCT has varied from ~992 mm (2017) to 1996 mm (2013), with no systematic change in annual rainfall amount (r = −0.16). However, from 2015 to 2022, the average annual rainfall of 1 145 mm has been below the 27 year average of 1 313 mm. Mean monthly temperature has increased from 1996 to 2022 (r = 0.53), and the weighted mean annual δD and δ18O values have increased by ~4‰ (r = 0.53) and ~0.5‰ (r = 0.64), respectively, over the 27 years. The UCT data and the data for 1961 to 1974 from Cape Town International Airport plot around the same LMWL, with an average deuterium excess (d-excess) of 13.78 and 12.95, respectively. Natural springs in the area plot close to the LMWL with an average d-excess of 14.15, whereas local well-point and borehole water samples generally plot below the LMWL with an average d-excess of 10.65. These differences can be explained by relatively rapid recharge of springs and slower recharge of groundwater, with the latter containing an additional component, that could either be rainwater that fell during a period of hotter drier climate or, more probably, municipal mains water. Long-term monitoring of groundwater and spring water as well as rainwater would be of great help in assessing the sustainability of groundwater use, among other important questions.

Evaluating climate Change's impact on hydroelectricity in the Zambezi river basin

This study investigates the effects of climate change on energy security in Africa, specifically focusing on the Upper and Lower Zambezi Basin. Data from the Kariba River basin sub-catchments, annual reports, the Climate Data Store, and Teal Tool Earth's country-by-country climate data were analysed through quantitative and qualitative data analysis techniques. The Mann-Kendal Trend Analysis was used to analyse time series and test the significance of changes to the climate. The historical climate and hydrological data analysis showed evidence of a slight increase in average rainfall amounts in the Zambezi River Basin but with high rainfall variability in some areas. Despite droughts increasing in frequency, there is a general increase in hydrological annual average water flow in the Zambezi River at two of the three sample sites. The increased water flow through the region could be attributed to population growth-induced land clearance and the degradation of wetlands in Angola's highlands. Although there is an increase in hydrological water flow into Kariba, there are water shortages for hydroelectricity generation due to increased generation capacity, resulting in increased demand for more water than in previous years. The unsustainable water abstraction to meet growing energy demands contributes to low water levels in the lake. The study recommends energy diversification and new hydroelectricity where the potential exists in the basin to reduce over-reliance on Lake Kariba with care not to disrupt the basin's hydrology and other economic activities. The study results provide insight into the potential effects of climate change on energy security in Africa.

Seasonal Average Rainfall forecasting in Tamil Nadu - Bootstrap SARIMA Model

Seasonal Average Rainfall forecasting in Tamil Nadu - Bootstrap SARIMA Model