Spatial Variability Of Rainfall Research Articles

Climate change shocks and crop production: The foodgrain bowl of India as an example

Global warming is causing climate change (CC) characterized by increased frequency of heatwaves, droughts, erratic rains, hailstorms, cloudbursts, floods, landslides etc. The CC has already adversely affected ecosystems. In spite of efforts to mitigate greenhouse gas (GHG) emissions, which lead to warming, the global temperature during 2011–20 was 1.1°C above that during pre-industrial era. The projections are that warming will continue to increase and adverse effects will intensify particularly in developing countries like India. In India a number of studies have recorded wide spatial variability in rainfall, though, many reported a general overall negative trend since mid-20th century. Further, varying pattern of rainfall has been recorded in three agroclimatic regions of Punjab state, the granary of India. Unseasonal rains followed by spiked temperature during winter (rabi) season of 2021–22 reduced wheat (Triticum aestivum L.) yield in Punjab by 651 kg/ha and by 301 kg/ha in Haryana compared to 2020–21. Further, the grain was of lower quality. During rainy (kharif) season of 2022, Southern Rice Black-streaked Dwarf Virus (SRBSDV), appeared for the first time in Punjab and Haryana. Some farmers ploughed the affected fields. Adverse weather during rabi 2022–23 also, reduced the wheat yield (143–150 kg/ha) in these states. At the national level, erratic weather during rabi 2021–22 and kharif 2022 caused losses of about 3 mt of grain of each of wheat and rice (Oryza sativa L.). The projected increased adverse effects due to intensified CC include food insecurity. Thus, there is an emergent need to accelerate implementation of adaptation and mitigation strategies in agriculture. The adaptation options include cultivar improvement, conservation agriculture altering growing seasons, crop diversification and sustainable soil, and water resource management. In the process of adaptive management of crop production, adjusting sowing dates and breeding cultivars having varying duration in consonance with CC has been one of the central aspects. Shifting sowing dates to find appropriate crop cultivation season is a low-cost measure. However, cultivar development is time and resource consuming. Novel biotechnological tools enable fast cultivar development with precision, and facilitate mobilization of genes from wild-weedy relatives, which are rich in genes conferring resistance/tolerance to biotic and biotic stresses, required to combat CC challenge. In view of CC stress on water resources, improving water-use efficiency (WUE) has gained importance. Sensor-based micro-irrigation/fertigation has great potential to enhance water and fertilizer-use efficiency. Similarly, the application of other smart technologies like nanotechnology, sensor-based pesticide application, bio-fertilizers and bio-pesticides, need to be mobilised. In view of agro-ecological diversity in India, right-sized regionspecific technology packages have to be developed implying that crop research will expand exponentially. This needs strengthening of human resources and institutional infrastructure, expanding and linking basic and applied researches, and fortifying inter-disciplinary/inter-institutional collaborations to develop and diffuse technology innovations. Enabling factors include enhanced funding and international cooperation. All-out efforts are needed to have more climate-resilient agriculture.

Spatio-Temporal Trend Analysis of Annual and Seasonal Rainfall in Ho Chi Minh City

Spatio-temporal variations and trends in climatic variables play an essential role in the adaptation and mitigation of climate change policy. This study analyzed spatial and temporal variability of annual and seasonal rainfall in Ho Chi Minh City based on non-parametric statistical trend tests and spatial interpolation techniques. In particular, Sen’s Slope Estimator and Inverse Distance Weighting (IDW) methods were applied to construct the spatial distribution of annual and seasonal rainfall over the city. The outcomes show that annual and seasonal rainfall experienced significant increasing trends. Generally, these findings draw out an overall picture of rainfall variability in terms of space and time, which makes it possible for local decision-makers to promote more promising action plans in order to respond to natural disasters in the context of climate change.

Utilizing the HEC-HMS Model for Hydrological Modelling of the Rambiara Watershed: Rainfall and Runoff Estimation

Abstract: Hydrological modelling and flood prediction are essential components of the Rambiara watershed's water resource management. To improve disaster preparedness and reduce the danger of flooding in the area, the effectiveness of the HEC HMS model in flood forecasting must be assessed. In this study, various techniques for estimating rainfall are examined, and a customized hydrological model tailored to the hydrological complexities of the Rambiara watershed is developed. The goal of this project is to provide practical insights for better flood risk reduction and water resource management through the integration of cutting-edge modelling tools and rigorous analysis. This work advances our knowledge of watershed dynamics and provides guidance for sustainable water resource planning projects in the Rambiara watershed and beyond by thoroughly examining precipitation patterns and hydrological processes. In addition, the research takes into account a number of factors related to flood behaviour, such as determining places that are vulnerable to flooding, analysing the size of floods, and estimating how frequently they occur. By taking a holistic approach, it is possible to gain a thorough understanding of the dynamics of flooding in the Rambiara watershed, which paves the way for the development of efficient flood risk management techniques. This study looks into the temporal and spatial variability of rainfall in the Rambiara watershed in addition to research on floods. Through the comparison of several methods for estimating rainfall, including deterministic and geostatistical approaches, the study offers valuable insights into the precision and dependability of rainfall data, which are essential for hydrological modelling and flood forecasting. The hydrological processes of the Rambiara watershed can be more accurately represented by creating a bespoke hydrological model with the HEC HMS program. Informed decision-making and proactive flood risk reduction strategies are made possible by the study's model calibration and validation, which guarantee the model's dependability in simulating runoff and forecasting flood events. Overall, this study advances our knowledge of flood dynamics in the Rambiara watershed and advances hydrological modelling tools. The goal of this study is to promote sustainability and resilience in the face of hydrological hazards by offering practical insights for managing water resources and reducing the danger of flooding.

Variability of temperature, rainfall and reference evaporation of catolé do Rocha-PB municipality, semi-arid region of Brazil

The state of Paraíba, specifically in the alto sertão of Paraíba, is characterized by the spatial and temporal variability of rainfall, of temperature and evapotranspiration, coming from the semi-arid climate that is inserted in the region, and yet, the performance of different meteorological systems. The objective was to quantify the rainfall, temperature and reference evaporation (mm/ month and mm/year) comprised in the experimental period between 2016 to 2020, in the municipality of Catolé do Rocha-PB, in order to determine the history of the rainy and dry season, and thus, minimize agricultural production losses due to environmental factors. The daily rainfall, temperature and reference evaporation data were obtained by means of a rain gauge and the indirect method of the class A tank, respectively. The rainfall (mm year-1) was analyzed by the nonparametric Friedman test, the Conover test and reference evaporation (mm year-1) applied the parametric test of the ANAVA and the test of Tukey HSD. Both parametric and non-parametric tests were analyzed by Real Statistics. Temperature data was compiled from the website (www.inmet.gov.br) in order to control, statically collecting and decision-making in the process of building scientific knowledge regarding meteorological data (climate - Temperature). Were also analyzed pearson's correlation matrices and elementary principal components analysis for the rainfall variables, Eto and Temperature in the studied experimental period. Were also studied the principal component analysis between the years 2016 to 2020 and its significance by the t test. The average reference evaporation between 2016 and 2020 was 2.1 times greater than rainfall. Mean rainfall and reference evaporation in Catolé do Rocha-PB between 2016 and 2020 were 827 mm ano-1 and 1704 mm year-1 and are compatible with historical averages of 800 mm year-1 and 1700 mm year-1, respectively. Inglesa.

Validation of CORDEX Regional climate models to simulate climate trends and variability across various agro-ecological zones of North Shewa, Ethiopia

Climate variability significantly affects the overall agricultural production and productivity over space and time. To quantify the effect of climate variability on natural systems on Earth in the future, the use of regional climate models (RCMs) as a tool is mandatory. Thus, the use of well-validated RCM provides efficient climate data; and predicts future climate variability over agroecological zones (AEZs). Eleven RCMs from CORDEX-Ethiopia were evaluated to simulate maximum temperature (Tmax), minimum temperature (Tmin) and rainfall variability over space and time, to validate their performance and to select the best-fit models. The temporal variability Tmax and rainfall was smaller with a CV of 10 %, indicating uniform distribution over stations. However, CV for Tmin over stations shows satisfactory distributions. Most of the evaluated RCMs have a better capability to capture the spatial variability of rainfall,Tmax, and Tmin in some stations. However, some of the RCMs can handle the spatial variability of Tmax while others are not. None of the RCMs can handle the spatial variability of Tmin in Debre Birhan, Majete, and Kewat AEZs. In general, most RCMs can capture the spatial and temporal variability of rainfall and temperature. It might be better to use the ensemble average of the output from these RCMs for precise estimation of data than specific RCMs. Therefore, this work could suggest the use of high-resolution RCMs for the projection of temperature and rainfall over different AEZs.

Long-term trends and spatial variability in rainfall in the southeast region of Bangladesh: implication for sustainable water resources management

Long-term trends and spatial variability in rainfall in the southeast region of Bangladesh: implication for sustainable water resources management

Temporal rainfall variability and drought characterization in Cheleka Watershed, Awash River Basin, Ethiopia

Study regionCheleka Watershed, lower Awash River Basin, Ethiopia. Study focusThe lower part of Awash River (Cheleka Watershed) with an area of 1744.48 km2 has limited rainfall temporal variability and drought incidence data. So, the study analyzed the temporal rainfall variability and drought incidence from five meteorological station starting from1988 up to 2017. Coefficient of variation, precipitation concentration index, mean and standard deviation were computed to analysis the temporal variations of rainfall; frequency and severity of droughts were characterized through rainfall anomalies indexes (RAI) and standardized precipitation indexes (SPI). New hydrological insights for the regionThe study found that, mean annual rainfall with a range value of 908.90 mm - 1181.48 mm in Batie and Majetie station respectively. Kiremt rainfall total with the highest coefficient of variation (22.93–29.12%) next to Belg rainfall total (39.31–52.43%) and the lowest variations of annual rainfall total (15–22.59%). Frequency of drought in 12 month’s interval indicates severely dry droughts, most frequently next to moderately dry drought. The maximum frequency for severely dry (8.61%) and moderately dry (11.39%) drought were occurred in Kemisse station. The longest duration and the highest magnitude drought were occurred in Kombolcha station next to Kemisse. As recommendation, since, this study was focused only temporal rainfall variability and drought characteristic, it is better that, future research will be conducted to evaluate the spatial rainfall variability and hydrological drought severity nature and its impact on socio-economic and human well-beings in the area.

Mapeando a Variabilidade das Chuvas na Bacia do Rio São Francisco: Insights para a Gestão de Recursos Hídricos

Abstract The São Francisco River Basin (SFRB) is extremely important for both the local rural and urban population, running through several states and municipalities in Brazil. Thus, the study of the spatial distribution of rainfall in the SFRB, supported by the application of geostatistics, offers valuable insights for water management and planning. In this study, data from 341 rainfall stations were used, corresponding to the period between 1989 and 2018, and monthly accumulated rainfall analyzed. About the trends, positive estimates for latitude, except for April, highlight that the accumulated precipitation decreases from south to north each month. In December, 85.10% of the spatial variability of rainfall was explained by the trend of rainfall concerning geographical coordinates. Concerning spatial dependence, the analyzed data predominantly exhibited the exponential variogram model. The conducted analyses offered a holistic view of rainfall in the region, facilitating the understanding of spatial patterns and shedding light on challenges in the face of climate change. Our research limited on the spatial modeling of rainfall in the SFRB, and future work should include modeling socio-economic and environmental impacts in the region concerning the spatial irregularity of rainfall.

Spatial Variability of Rainfall and Classification of Peninsular Indian Catchments

The strength and success of hydrological analysis depend upon the quantity and quality of observed data. In the recent past, the availability of advanced computing facilities and measurement techniques had a great impact on the field of hydrology, especially in hydrologic analysis and hydrologic modeling. In spite of such growth, the present hydrologic modeling has certain challenges: complexity (involving a large number of parameters), applicability to a specific region (difficult to generalize for other regions), and lack of understanding of the connection between model theories and the actual system. The general solution of simplifying the models in terms of developing a classification framework has been discussed and focused on in the present study. It will greatly help to overcome the hydrologic modeling challenges and provides a better understanding of the hydrologic process. In general, classification is a way of grouping entities which has similar characteristics. The importance of applying nonlinear dynamics and chaos methods for classification has been realized in the recent past; since such studies provide exclusive information on hidden characteristics such as complexity, nonlinearity, dimensionality, etc. Of hydrological processes. The hydrologic processes are complex. In this study, information regarding the complexity is extracted by statistical analysis and linear methods such as Autocorrelation Function, and Average Mutual Information. 367 gridded rainfall stations over Peninsular Indian basins are used to investigate the applicability of different methods used in the study.

Analysis of Extreme Rainfall in the Mt. Merapi Area

The slopes of Mount Merapi (Mt. Merapi) are an area prone to hydrological disasters due to elevation and orography. Hydrological disasters that have the potential to occur include floods, erosion, landslides, and drought which are closely related to extreme rainfall. Spatial and temporal variability of rainfall in mountainous areas requires rainfall data that can represent rainfall events. Therefore, this research aims to obtain the reliability of satellite rainfall data in the extreme rainfall indices. The CHIRPS, GPM-IMERG FINAL (IMERG-F) and GPM-IMERG LATE (IMERG-L) will be used in the reliability analysis of satellite-based rainfall compared to observed rainfall station. To validate satellite rain data, statistical criteria are utilized with parameters such as Correlation Coefficient (R), Root Mean Squared Error (RMSE), and Relative Bias (RB). Satellite-based rainfall estimates have a weak to moderate correlation (0.19 – 0.55), the RMSE value is relatively good (12.18 – 31.35 mm) and the observed bias tends to underestimate the estimated values. The capabilities of the IMERG-F, IMERG-L and CHIRPS satellites as alternative rainfall data in the Mt. Merapi area are quite good where IMERG-L has the best performance in capturing rainfall above 50 mm (R50mm), Consecutive Dry Days (CDD) indices, max 1–day and 5-day precipitation (Rx1day and Rx5day). The potential for extreme rainfall that is most prone to trigger lava floods occurs in the western region of Mt. Merapi at Ngandong Station (Sta. Ngandong). In this region, there is a high occurrence of extreme rainfall events. For instance, there were 501 instances of R50mm with an intensity of 77 mm day-1, Total Precipitation (PRCPTOT) reaches 3385 mm, Rx5day reaches 393 mm, and Consecutive Wet Days (CWD) lasts for 30 days. The results of this analysis can assist in climate understanding and modeling of extreme rainfall relevant to the region and support water resource management and disaster risk mitigation.

Unexpected contribution of cloud seeding to NPP increase during drought

Abstract Cloud seeding is generally used to secure additional water resources, which is not an easy goal to achieve, as the spatial variability of rainfall is high. Instead, the increased rain may moisten the neighboring forest. This study focuses on this situation and estimates the possible increase in the net primary production (NPP) due to cloud seeding. This study considers the Boryeong Dam basin in Korea as a study area and uses the Carnegie–Ames–Stanford Approach (CASA) model to estimate the NPP at 8-day intervals. As a result, first, the increase of the current 8-day NPP is greater when the rainfall amount during the last 16-day period is 50 mm or more. The mean increase of the 8-day NPP is estimated at about 1.873 g/m2 of carbon. Second, the increase of the NPP with the target 16-day rainfall of 50 mm is estimated at about 3%, which is about 4% with the target 16-day rainfall of 100 mm. Simply extrapolating the derived result to the entire forest in Korea, the increased carbon accumulation can be extended to about 0.6 and 0.8% of the total carbon emission in 2018, respectively. These amounts correspond to about 1.2 and 1.5% of the target amount of carbon reduction by 2030 in Korea.

Gauging the ungauged: estimating rainfall in a West African urbanized river basin using ground-based and spaceborne sensors

ABSTRACT Accurate precipitation observations are crucial for hydrological forecasts, notably over rapidly responding urban areas. This study evaluated the accuracy of three gridded spaceborne rainfall products (Integrated Multi-satellitE Retrievals for GPM (IMERG), Meteosat Second Generation Visible (MSG-VIS), and MSG-Infrared (MSG-IR)) and the non-governmental Trans-African Hydro-Meteorological Observatory (TAHMO) gauges across the Odaw catchment (Accra, Ghana) from January 2020-July 2022. IMERG is hardly able to capture the strong spatial variability of rainfall required for flood forecasting, but agrees in annual sums with TAHMO and MSG-IR. MSG-IR has difficulties during the wet season. MSG-VIS, only available during daylight, shows limited accuracy and gives high estimates while other products do not detect rain. TAHMO gauges effectively record high-intensity events and their strong spatial variability, although some (daily) accumulations are doubtful and data gaps exist due to technical issues. These findings assist hydrological modelers in selecting appropriate datasets at suitable spatiotemporal resolutions for their research.

Block-level long-term rainfall variability using trend analysis in a state of central India

Abstract Rainfall is the key weather element which regulates the hydrological cycle, availability of water resources and crop production. In this study, spatial and temporal variability of rainfall has been investigated on seasonal and annual time scales of the 149 blocks of Chhattisgarh State using 120 years (1901–2020) of rainfall data. Non-parametric, and Theil and Sen's slope estimator were used to identify possible trends and ascertain the variability in the magnitude. The results revealed that there exists a well-marked spatial variability in rainfall over Chhattisgarh on annual and seasonal time scales. Out of 149 blocks, a significant negative rainfall was noticed in 105 blocks. Annual rainfall showed a significant positive trend in a few blocks like Bhopalpattnam, Bijapur, Usur, and Konta. A similar pattern of trend was noticed in the monsoon season. The results of the study demand the urgent need to formulate policies and strategies for water resource management and planning. The blocks which showed the positive rainfall trends can be identified to intensify the cultivation of more water-requiring crops based on the suitability for that region. The findings of this study can be used as valuable information for crop planning, policy-making and preparation of contingency plans.

Controls on topography and erosion of the north-central Andes

Abstract We present 17 new 10Be erosion rates from southern Peru sampled across an extreme orographic rainfall gradient. Using a rainfall-weighted variant of the normalized channel steepness index, ksnQ, we show that channel steepness values, and thus topography, are adjusted to spatially varying rainfall. Rocks with similar physical characteristics define distinct relationships between ksnQ and erosion rate (E), suggesting ksnQ is also resolving lithologic variations in erodibility. However, substantial uncertainty exists in parameters describing these relationships. By combining our new data with 38 published erosion rates from Peru and Bolivia, we collapse the range of compatible parameter values and resolve robust, nonlinear ksnQ–E relationships suggestive of important influences of erosional thresholds, rock properties, sediment characteristics, and temporal runoff variability. In contrast, neither climatic nor lithologic effects are clear using the traditional channel steepness metric, ksn. Our results highlight that accounting for spatial rainfall variations is essential for disentangling the multiple influences of climate, lithology, and tectonics common in mountain landscapes, which is a necessary first step toward greater understanding of how these landscapes evolve.

Land Cover Trajectories and Their Impacts on Rainfall-Triggered Landslide Occurrence in a Cultivated Mountainous Region of Western Japan

Land cover changes in mountainous regions are potential precursors to landslide disasters. However, the effects of past long-term land cover changes on the characteristics of recent landslides remains underexplored. We studied land cover evolution over a 56-year period on Omishima Island in western Japan to examine the spatial relations of landslides in the July 2018 storm event based on rainfall, land cover trajectories, and topography. We generated land cover maps for 1962, 1981, and 2018 by aerial photo interpretation. We also identified 512 new landslides. Based on 47-year precipitation records, we estimated the return periods of 1- to 264-h rainfalls during the storm using the generalised extreme value (GEV) distributions. Return periods showed wide variation when the derived GEV distributions were applied to 1-km grid rainfall distributions. Despite such pronounced spatial variations in rainfall, we did not observe a clear correlation between rainfall intensity and landslide distribution. In contrast, land cover trajectories had a pronounced effect on landslide occurrence. Landslides were more concentrated on slopes that experienced land cover changes after 1962. A comparison of slopes on farmland developed between 1962 and 1981 (mainly citrus orchards) indicated that landslide density and area ratio were significantly lower on slopes that had reverted to forests than on those remaining as farmland. However, the values of the reforested slopes exceeded those of forests and farmlands that remained since before 1962. Our geospatial analysis revealed that even if the field had shifted to forests, the effects of reduced slope stability due to orchard development had remained for at least 37 years. This suggested that the impacts of converting forests to orchards last longer than harvesting in managed plantation forests.

Spatial and temporal variability of rainfall in Western Bahia

Western Bahia is a region widely recognized for its significance in large-scale agricultural production, being one of the mainstays of the local economy. However, agricultural activities in this area are often challenged by extended periods of low precipitation, posing a constant threat to the productivity of major crops. Deep concerns are raised by unpredictability of rainfall, especially in February during the critical period of crops, which encompasses the flowering and/or grain filling stages of most crops in the region. In this scenario, this study assumes a central role in search for answers. Thus, this paper aimed to analyze the behavior of spatial and temporal variability of rainfall in the Western region of Bahia. The research focused on the month of February due to its critical relevance to the life cycle of local crops and its direct influence in agricultural productivity. Rainfall data were obtained from the stations network of the National Water Agency (ANA) through the Hydroweb platform for the period from 1986 to 2015. The Rain Anomaly Index (RAI) for the month of February was then calculated using equations developed by Rooy (1965). To analyze the space-time variability of drought events in their different intensities, RAI maps were generated containing eight categories ranging from extremely wet to extremely dry, for the measurement and classification of rainfall anomalies in relation to the historical average. The results revealed that throughout the analyzed period, approximately 53.33% of the February months exhibited negative anomalies, denoting drought events ranging from mild to extreme, while approximately 30% of the months displayed positive anomalies, indicating moisture levels ranging from low to extremely wet. Notably, in the years with the most significant negative anomalies (drought events), there was a predominance of spatial variability from east to west, with the lowest negative anomalies on the western side and the highest on the eastern side of the region. On the other hand, positive anomalies (wet events) exhibited a predominance of spatial variability from south to north in the region. This study provides valuable insights for the agricultural sector, water resource planning, and environmental management. It underscores the importance of adaptive strategies to address climatic fluctuations and ensure the sustainability of agricultural production in the Western Region of Bahia.

ASSESSMENT OF TEMPORAL VARIABILITY OF TEMPERATURE AND PRECIPITATION TRENDS IN KARGI, MAIKONA, DAKABARICHA AND SOLOLO WARDS OF MARSABIT COUNTY, KENYA

<p><strong>Background.</strong> Climate change is a global phenomenon, with varying indicators and impacts from one region to another. The impacts of the changing climate are high in developing countries that are mainly dependent on climate-driven economic sectors such as pastoral and agro-pastoral livelihoods. <strong>Objective.</strong> Analyze the temporal trend, the variability in temperature and precipitation, and the relationship between both parameters to determine the influence of the El Niño phenomenon in Marsabit County, Kenya, from 1981 to 2021. <strong>Methodology.</strong> Daily rainfall and temperature data for the four study locations (Maikona, Kargi, Dakabaricha, and Sololo) were obtained. The analysis of extremes was the main method used in the analysis of the temporal and spatial variability of rainfall and temperature to establish the frequency and magnitude of climate variability in the study area. The seasonal mean plus or minus 1 Standard deviation for the entire period of study was used in the analysis of extremes. <strong>Results.</strong> Findings from trend analysis showed that rainfall trends have significantly increased in Marsabit County. Further, results on seasonal trends and variability of rainfall showed that March-April-May rainfall has been decreasing over the years. Below average rainfall has been experienced in Maikona in 2000 and 2011 with a magnitude of -42.9 mm, and -39.3 mm, respectively, while below average rainfall has been experienced in Kargi in 2000, 2009, 2011, and 2012 with a magnitude of -41.7 mm, -24.2 mm, -35.3 mm, and -34.3 mm, respectively. Analysis of the temperature trends and variability showed that both night and day temperatures have significantly increased over the years in Marsabit County. The magnitude of warming was found to be double that of cooling. The regression analysis further showed that there exists a negative correlation between temperatures and rainfall, implying that generally, rainfall decreases with increasing temperatures. <strong>Implications.</strong> This finding is important because it could help policymakers and people working on development in Marsabit County see what temperature and precipitation changes are happening locally. This could help them plan for climate change better. Both pastoral and agro-pastoral areas have been affected by both El Niño and La Niña activities, with the El Niño years recording the highest amounts of rainfall while the La Niña years recording the lowest amounts. <strong>Conclusion</strong><strong>s</strong><strong>.</strong> This study recommends the use of rainwater harvesting during the October to December Season to take advantage of the increasing Trends and flood episodes associated with high magnitudes and frequencies of above average rainfall and use the same to cope with reduced rainfall in the March to May season. </p>

Spatio-Temporal Variability of Rainfall Over Kathmandu Valley of Nepal

The present study used and analyzed rainfall data from 18 meteorological stations from 1971 to 2013 to examine the spatial and temporal variability of seasonal and annual rainfall based on rain gauge measurements. The monthly to annual rainfall analysis was carried out for each site of Kathmandu Valley. Rainfall amounts in Kathmandu Valley vary considerably in space and time. The minimum mean monthly rainfall is observed in November which is 6.5 mm and maximums of 447.8 mm in July. Monsoon is the main contributor of the rainfall which is 80% followed by pre-monsoon with 13.6%, post-monsoon with 3.6% and winter with 2.8%. Spatial interpolation was used to explore spatial variability of seasonal and annual rainfall over Kathmandu Valley. There is large spatial variability of monsoon rainfall; generally, the upper parts of the Kathmandu Valley received the heavy monsoon rainfall than the lower parts of the Valley floor. The rainfall of Kathmandu has marked decreasing in recent a couple of decades. Annual rainfall has decreased by 0.96 mm/year observed in Kathmandu Valley.

Spatial and Temporal Variability of Rainfall in South-central Senegal: Example of the Fatick and Kaolack Regions

One of the manifestations of climate change in the Sahel is a decrease in rainfall, which has led to a sharp decline in water potential in the south-central Senegal. The objective of this study is to understand the changes in rainfall through time and space, in the south-central Senegal (Fatick and Kaolack regions), to better plan water management for sustainable development. The rainfall data used ranges from 1961 to 2020 for the sites of Gossas, Foundiougne, Guinguineo and Nioro, and from 1951 to 2020 for the sites of Fatick and Kaolack. Pettitt and Buishand break tests were used to detect changes in rainfall patterns, Hubert segmentation was used to highlight sub-periods within the time series, and Standardized Precipitation Indices (SPI) were used to highlight deficits and surpluses. The results of break tests and Hubert segmentation show a decrease in average rainfall between the 1960s and 1970s, and an increase between the 1990s and 2000s, for some of the sites. The decrease in the 1960s and 1970s was early in sites in the Fatick region (Gossas, Fatick and Foundiougne) and late or absent in the Kaolack region (Guinguineo, Kaolack and Nioro). As for the increase in the 1990s and 2000s, it was first observed in the south and center of the study area in the 1990s (Nioro and Kaolack). In the 2000s, the increase was observed further north (Fatick and Gossas). The Standardized Precipitation Index shows reduced rainfall for 1971-2000 compared to the surrounding periods. Coefficient of variation values show that dispersion is lowest in the wetter years 1950 for two sites (Fatick and Kaolack), 1990 and 2000 for four sites (Gossas, Foundiougne, Guinguineo and Nioro). The highest coefficients of variation were detected in the drought years 1960, 1970 and 1980 for these four sites (Gossas, Foundiougne, Guinguineo and Nioro). This is not the case at the Fatick site, where the coefficients of variation for the 1970s, 1980s and 1990s are higher than those for 2000 and 2010. Coefficients of variation increase in the 2010s at five sites (Kaolack, Gossas, Foundiougne, Guinguineo and Nioro). The highest coefficients of variation were recorded in 2010 in Gossas, Guinguineo and Nioro. The decrease in average rainfall from the 1960s to the 1990s, and the increase in the 1990s and 2000s detected in most of the study sites, corroborates results of other studies from West and Central Africa.

Analysis Of The Spatial And Temporal Variability Of Rainfall In The Kayanga-Anambé Hydrological Complex (Republic Of Guinea And Senegal)

The high rainfall variability observed especially from the 1970s has intensified the vulnerability of water resources in tropical watersheds. It resulted in the recurrence of extreme hydrological events – combined with the increase in temperature which increases evapotranspiration causing considerable water losses – but also in the "Sahelization" of Sudanian areas resulting in the migration of isohyets towards the south.This article studies recent spatial and temporal changes in rainfall in the Kayanga-Anambé complex, as well as their potential hydrological implications. The methodological approach is based on (i) checking the quality of data and filling gaps using the method of rainfall indices with the Regional Vector Method (RVM); and on (ii) the analysis of spatial and temporal variability of rainfall using PETITT stationarity test and Standardized Precipitation Index (SPI).The evolution of rainfall in the basin is reflected in a fact specific to the intertropical zone, namely the variability of rainfall. This is marked by several sequences: a wet period between 1940 and 1967, followed by a long dry sequence which extends between the beginning of the 70s until the end of the 90s, and finally a slight resumption of the rainfall over the period 1993-2020. However, according to the outputs of global climate models ("Multi-model Ensemble"), the resumption of rainfall in the Kayanga basin will only be effective from 2060. This variability noted in the rains will induce a similar variability in the flows and agricultural production since they are largely dependent on it.