Rainfall Characteristics in Ahmednagar District of Maharashtra State

Rainfall is one of the vital form of precipitation which affects not only agricultural activity but also entire ecology in any region. Hence rainfall distribution and its trends in district is important to understand water availability and to take decisions for the agricultural activities in area. This research paper is an effort to assess the spatial and temporal rainfall variability of Ahmednagar district of Maharashtra State. Ahmednagar is popularly known as the largest district of Maharashtra with fourteen Talukas. The average annual rainfall of this district is 621 mm with an average of 46 rainy days. In this study the spatial and temporal rainfall distribution of this district is taken in to account. Short-term annual rainfall data are considered from 1998 to 2014. The daily rainfalls of monsoon months of all the fourteen Taluka are analyzed for the year 2015.It was found that spatial and temporal variability is high in the District.

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ARENIZAÇÃO NO BRASIL:

Revista de Geografia - PPGEO - UFJF ◽

10.34019/2236-837x.2018.v8.25982 ◽

2019 ◽

Vol 8 (2) ◽

pp. 01-11

Author(s):

Ivamauro Ailton de Sousa Silva ◽

Dirce Maria Antunes Suertegaray

Keyword(s):

Meteorological Data ◽

Rainfall Variability ◽

Annual Rainfall ◽

Distribution Characteristics ◽

Thematic Maps ◽

Rainfall Distribution ◽

Study Results ◽

Average Annual Rainfall ◽

Different Climates ◽

Meteorological Institute

A finalidade desta pesquisa é caracterizar e comparar a dinâmica pluviométrica das áreas de ocorrência do processo de arenização no território brasileiro. Os estudos sobre arenização aqui registrados, situam-se nos munícipios de Quaraí (RS), Paranavaí (PR), Itirapina (SP), Buritizeiro (MG), Serranópolis (GO), Gilbués (PI), Reserva do Cabaçal (MT) e Manaus (AM). Na perspectiva climática, o artigo realiza um comparativo dessas áreas, evidenciando as características acerca do regime e distribuição pluvial. Para isso, a pesquisa foi constituída através de revisão bibliográfica, elaboração de mapas temáticos, coleta e análise de dados meteorológicos disponibilizados pelo Instituto Nacional de Meteorologia, para 8 estações representativas das diferentes localidades com ocorrência de arenização. Como resultados, o trabalho revela as seguintes asserções: a) considerando a tipologia climática brasileira, o processo de arenização pode ocorrer sob diferentes climas; subtropical, tropical subúmido e equatorial; b) a pluviometria é variável durante o ano para as diferentes localidades; c) a pluviosidade média anual, em todas as áreas analisadas, é superior a 1.100 mm; d) períodos de estiagem são comuns nas áreas com clima tropical subúmido. Palavras-chave: Arenização, Variabilidade Pluviométrica, Espacialização. Abstract The aim of the present study is to characterize and compare the rainfall dynamics of occurrence areas concerning arenization processes throughout the Brazilian territory. Arenization studies registered in the country are located in the municipalities of Quaraí (RS), Paranavaí (PR), Itirapina (SP), Buritizeiro (MG), Serranópolis (GO), Gilbués (PI), Cabaçal Manaus (AM). Concerning a climatic perspective, this study carried out comparisons between these areas, evidencing regime and rainfall distribution characteristics. The research comprised a bibliographical revision, the elaboration of thematic maps and the collection and analysis of meteorological data made available by the National Meteorological Institute, for 8 representative stations of the different localities where arenization is detected. The study results reveal the following investigations: a) considering Brazilian climatic typology, arenization processes can occur under different climates, subtropical, tropical subhumid and equatorial; b) rainfall is variable throughout the year for the different localities; c) the average annual rainfall in all analyzed areas is over 1,100 mm; d) drought periods are common in areas presenting a subhumid tropical climate. Keywords: Arenization, Rainfall Variability, Comparisons.

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Evaluation and Application of Multi-Source Satellite Rainfall Product CHIRPS to Assess Spatio-Temporal Rainfall Variability on Data-Sparse Western Margins of Ethiopian Highlands

Remote Sensing ◽

10.3390/rs11222688 ◽

2019 ◽

Vol 11 (22) ◽

pp. 2688 ◽

Cited By ~ 4

Author(s):

Ashebir Sewale Belay ◽

Ayele Almaw Fenta ◽

Alemu Yenehun ◽

Fenta Nigate ◽

Seifu A. Tilahun ◽

...

Keyword(s):

Rainfall Variability ◽

Daily Rainfall ◽

Annual Rainfall ◽

Integration Time ◽

Spatial And Temporal Variability ◽

Rainfall Events ◽

Rainfall Characteristics ◽

Mean Annual Rainfall ◽

Time Space ◽

Spatio Temporal

The spatio-temporal characteristic of rainfall in the Beles Basin of Ethiopia is poorly understood, mainly due to lack of data. With recent advances in remote sensing, satellite derived rainfall products have become alternative sources of rainfall data for such poorly gauged areas. The objectives of this study were: (i) to evaluate a multi-source rainfall product (Climate Hazards Group Infrared Precipitation with Stations: CHIRPS) for the Beles Basin using gauge measurements and (ii) to assess the spatial and temporal variability of rainfall across the basin using validated CHIRPS data for the period 1981–2017. Categorical and continuous validation statistics were used to evaluate the performance, and time-space variability of rainfall was analyzed using GIS operations and statistical methods. Results showed a slight overestimation of rainfall occurrence by CHIRPS for the lowland region and underestimation for the highland region. CHIRPS underestimated the proportion of light daily rainfall events and overestimated the proportion of high intensity daily rainfall events. CHIRPS rainfall amount estimates were better in highland regions than in lowland regions, and became more accurate as the duration of the integration time increases from days to months. The annual spatio-temporal analysis result using CHIRPS revealed: a mean annual rainfall of the basin is 1490 mm (1050–2090 mm), a 50 mm increase of mean annual rainfall per 100 m elevation rise, periodical and persistent drought occurrence every 8 to 10 years, a significant increasing trend of rainfall (~5 mm year−1), high rainfall variability observed at the lowland and drier parts of the basin and high coefficient of variation of monthly rainfall in March and April (revealing occurrence of bimodal rainfall characteristics). This study shows that the performance of CHIRPS product can vary spatially within a small basin level, and CHIRPS can help for better decision making in poorly gauged areas by giving an option to understand the space-time variability of rainfall characteristics.

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Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

Hydrology and Earth System Sciences ◽

10.5194/hess-21-3859-2017 ◽

2017 ◽

Vol 21 (7) ◽

pp. 3859-3878 ◽

Cited By ~ 69

Author(s):

Elena Cristiano ◽

Marie-Claire ten Veldhuis ◽

Nick van de Giesen

Keyword(s):

Temporal Variability ◽

Urban Areas ◽

Rainfall Variability ◽

Urban Environments ◽

Hydrological Processes ◽

Small Scale ◽

Spatial And Temporal Variability ◽

Hydrological Response ◽

Weather Radars ◽

New Instruments

Abstract. In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

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THE INFLUENCE OF THE BRAZILIAN CERRADO DEFORESTATION IN GRAIN CULTURE AND ITS CONSEQUENCES TO LOSSES THE SOIL IN THE CACHOEIRA DOURADA RESERVOIR REGION – CENTRAL - WESTERN BRAZIL

Geoambiente on-line ◽

10.5216/revgeoamb.v0i14.26001 ◽

2013 ◽

pp. 01

Author(s):

João Batista Pereira Cabral ◽

Valter Antonio Becegato ◽

Francismário Ferreira dos Santos

Keyword(s):

Annual Cycle ◽

Annual Rainfall ◽

Brazilian Cerrado ◽

Rainfall Distribution ◽

Rainfall Variation ◽

Influence Area ◽

Average Annual Rainfall ◽

Average Rainfall ◽

Soil Preparation ◽

Erosivity Index

The erosivity index (EI30) and its spatialization were determined for the contribution basins of the Cachoeira Dourada hydroelectric system reservoir, located between the states of Goiás and Minas Gerais and limited by coordinates 640000-760000 m W and 7910000-7975000 m N. Average monthly and annual rainfall data corresponding to eight localities and to a 30-year period were treated. It was observed that in this period the average annual rainfall was 1441 mm, the highest and lowest indexes having occurred respectively in January and July (7.5 mm). EI30 varied from 7100 to 8500 MJ mm (ha h)-1. The most representative period was October to March, corresponding to 7880.3 MJ mm (ha h)-1and 94% of the average annual EI30. The average rainfall variation coefficient for all stations was 82.73%. There is an irregular rainfall distribution in the region and consequently a non-uniform spatialization of the erosivity indexes within the influence area of the reservoir. The highest rainfall values coincide with the period of soil preparation and development of annual-cycle plants, mainly soybean and corn.

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Spatio-Temporal Variability and Trend of Rainfall and Its Association with Pacific Ocean Sea Surface Temperature in West Harerge Zone, Eastern Ethiopia

10.21203/rs.3.rs-104059/v1 ◽

2020 ◽

Author(s):

Getachew Bayable Tiruneh ◽

Gedamu Amare ◽

Getnet Alemu ◽

Temesgen Gashaw

Keyword(s):

Pacific Ocean ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Temporal Variability ◽

Rainfall Variability ◽

Sea Surface ◽

Annual Rainfall ◽

Eastern Ethiopia ◽

Spatio Temporal ◽

Annual Time

Abstract Background: Rainfall variability is a common characteristic in Ethiopia and it exceedingly affects agriculture particularly in the eastern parts of the country where rainfall is relatively scarce. Hence, understanding the spatio-temporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatio-temporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia.Method: The coefficient of variation (CV) and standardized anomaly index (SAI) was employed to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by the Pearson correlation coefficient (r).Results: The annual rainfall CV ranges from 12-19.36% while the seasonal rainfall CV extends from 15-28.49%, 24-35.58%, and 38-75.9% for average Kiremt (June-September), Belg (February-May), and Bega (October-January) seasons, respectively (1983-2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends of rainfall were not statistically significant (α = 0.05), unlike November. The annual rainfall trends showed a non-significant decreasing trend. On a seasonal basis, the trend of mean Kiremt and Belg seasons rainfall was decreased. But, it increased in Bega season although it was not statistically significant. Moreover, the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, the correlation between rainfall and Pacific Ocean SST was negative at annual time scales.Conclusions: High spatial and temporal rainfall variability on monthly, seasonal, and annual time scales was observed in the study area. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall was increased annually and in the Bega season rather than other seasons. Generally, the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

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A Note on Rainfall Variability and Trends in Nigeria: Implications for Agricultural Production*

Studies in Microeconomics ◽

10.1177/23210222211051472 ◽

2021 ◽

pp. 232102222110514

Author(s):

Kolawole Ogundari ◽

Adebola Abimbola Ademuwagun ◽

Ogechukwu Appah

Keyword(s):

Food Security ◽

Coefficient Of Variation ◽

Agricultural Production ◽

Hypothesis Test ◽

Rainfall Variability ◽

Climatic Variability ◽

Least Square ◽

Annual Rainfall ◽

Average Annual Rainfall ◽

Over Time

The climatic change crisis has led to a renewed interest in understanding the dynamic of climatic variability over time. This is because rainfall variability in response to climate change poses a severe threat to global food security and agricultural production in general. As a result of this, the study investigates the convergence of rainfall variability in Nigeria. We use historical climate data on annual rainfall collected from meteorological stations across 12 states and covering 1992–2013. This gives rise to a balanced panel data of 12 states and 20 periods, which yields 240 observations. The study used a sigma convergence hypothesis test estimated using ordinary least square, fixed-effect and feasible generalized least square models. The coefficient of variation is taken as a measure of rainfall variability in the study. The results showed a negative (declining) linear correlation between rainfall’s coefficient of variation and data year. This means that rainfall variability decreased over time. This indicates evidence of convergence of rainfall, which means states with lower average annual rainfall are catching up on states with higher average annual rainfall over time. And, from the agricultural production standpoint, this result shows that the potential threat of rainfall variability to food security is not severe. In addition, it indicates a decrease in risk and uncertainty in food crop production associated with rainfall variability. JEL Classifications: O13, O55, Q10, Q54

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Modeling Short-Term Spatial and Temporal Variability of Groundwater Level Using Geostatistics and GIS

Natural Resources Research ◽

10.1007/s11053-011-9167-8 ◽

2012 ◽

Vol 21 (1) ◽

pp. 117-136 ◽

Cited By ~ 25

Author(s):

Deepesh Machiwal ◽

Amit Mishra ◽

Madan K. Jha ◽

Arun Sharma ◽

S. S. Sisodia

Keyword(s):

Groundwater Level ◽

Temporal Variability ◽

Spatial And Temporal Variability ◽

Short Term

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Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)

Climate ◽

10.3390/cli6030075 ◽

2018 ◽

Vol 6 (3) ◽

pp. 75 ◽

Cited By ~ 2

Author(s):

Stefanos Stefanidis ◽

Dimitrios Stathis

Keyword(s):

Multiple Regression ◽

Rainfall Variability ◽

Multiple Regression Model ◽

Rainfall Data ◽

Annual Rainfall ◽

Spatial And Temporal Variability ◽

Mountain Range ◽

Rainfall Time Series ◽

Distribution Maps ◽

Mountainous Catchment

In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann–Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen’s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately −1.9%, −3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area.

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