scholarly journals ASSESSING CLIMATE RISK AND CLIMATE CHANGE USING RAINFALL DATA – A CASE STUDY FROM ZAMBIA

2011 ◽  
Vol 47 (2) ◽  
pp. 241-266 ◽  
Author(s):  
R. D. STERN ◽  
P. J. M. COOPER
Keyword(s):  
Crop Production ◽  
Markov Chain Model ◽  
Rainfall Variability ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Sub Saharan Africa ◽  
Chain Model ◽  
Wide Range ◽  
Dry Spell ◽  
Rainfall Patterns

SUMMARYRainfall variability, both within and between seasons, is reflected in highly variable crop growth and yields in rainfed agriculture in sub-Saharan Africa and results in varying degrees of weather-induced risk associated with a wide range of crop, soil and water management innovations. In addition there is both growing evidence and concern that changes in rainfall patterns associated with global warming may substantively affect the nature of such risk. Eighty-nine years of daily rainfall data from a site in southern Zambia are analysed. The analyses illustrate approaches to assessing the extent of possible trends in rainfall patterns and the calculation of weather-induced risk associated with the inter- and intra-seasonal variability of the rainfall amounts. Trend analyses use monthly rainfall totals and the number of rain days in each month. No simple trends were found. The daily data were then processed to examine important rain dependent aspects of crop production such as the date of the start of the rains and the risk of a long dry spell, both following planting and around flowering. The same approach is used to assess the risk of examples of crop disease in instances when a ‘weather trigger’ for the disease can be specified. A crop water satisfaction index is also used to compare risks from choices of crops with different maturity lengths and cropping strategies. Finally a different approach to the calculations of these risks fits a Markov chain model to the occurrence of rain, with results then derived from this model. The analyses shows the relevance of this latter approach when relatively short daily rainfall records are available and is illustrated through a comparison of the effects of El Niño, La Niña and Ordinary years on rainfall distribution patterns.

scholarly journals Fitting of a Markov chain model for daily rainfall data at Calcutta

MAUSAM ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 67-74
Author(s):  
A. N. BASU
Keyword(s):  
Markov Chain ◽  
Geometric Distribution ◽  
Markov Chain Model ◽  
Probability Model ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Actual Data ◽  
Chain Model ◽  
Daily Rainfall Data ◽  
Rainy Days

A Markov chain probability model has been fitted to the daily rainfall data recorded at Calcutta. The 'wet spell' and 'weather cycles' are found to obey geometric distribution, The distribution of the number of rainy days per week has been calculated and compared with the actual data.

scholarly journals Taluka Wise Study of Rainfall Pattern in Nanded District of Marthwada Region (Maharashtra) Using Rainfall Data

2021 ◽  
Vol 10 (9) ◽  
pp. 333-350
Author(s):  
Ramesh Bethala B. V. Asewar ◽  
M. S. Peneke K. K. Dakhore ◽  
M. G. Jadhav A. M. Khobragade
Keyword(s):  
Crop Production ◽  
Rainfall Variability ◽  
Winter Season ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Monsoon Period ◽  
Annual Basis ◽  
Rainy Days ◽  
Onset Of Monsoon

About 60 per cent of the total cultivable area of the country is rainfed. However, prolonged dry periods affect the final crop production. Monsoon is an important season for water supplies, from surface reservoir. Uneven distribution of rainfall, affect the agricultural production remarkably. The daily rainfall data was collected for each taluka of Nanded district for the period of 20 years (1998-2017) and it was to be summed up on meteorological weekly, monthly, seasonally, annual basis for each taluka of Nanded district basis for the study of rainfall characterization. The results indicated that weekly mean annual basis total rainfall was ranged between 720.0 mm in Deglur and 1009.9 mm in Mahur. The weekly highest rainfall on annual basis was recorded in Himayat Nagar (53.7 mm) in the 30th MW amongst all the taluka considering monsoon period (23 to 42 MW). The monthly mean rainfall indicated that the lowest and highest monthly mean rainfall amongst all the taluka was observed in Nanded, Kandhar, Loha, Hadgaon, Bhokar, Kinwat, Mahur, Dharmabad, Ardhapur, Naigaon talukas (0.0 mm) in the December month and in the Mahur taluka (283.1 mm) in July month. The seasonal distribution of Nanded district was obtained in winter season (6.1 mm), in summer (15.5 mm), in monsoon (578.3 mm), in post monsoon (216.6 mm). The annual rainfall data is statistical analyzed for Nanded district and within the year and taluka to taluka ranged C.V. (%) were between 25.0 to 46.9 %. The data of taluka-wise annual normal of weather parameter (i.e. rainfall and rainy days) calculated. Here, the results indicated that the onset of monsoon was observed in 23th MW and withdrawal in 43rd MW in Nanded district. It showed that average rainfall of Nanded district is 816.4 mm with 45.0 rainy days per year. The results clearly indicated the onset of monsoon in 23th MW and withdrawal of monsoon in 43rd MW for the Nanded district should be considered. The statistical analysis for rainfall variability was worked out and it was intra-annual as well as intra-taluka variation in Nanded district. It was ranged between 19.0 to 51.0 per cent with annual mean 45.0 rainy days per year.

scholarly journals Climatology of dry and wet spell over Vidarbha region during monsoon months

MAUSAM ◽  
2021 ◽  
Vol 52 (2) ◽  
pp. 365-370
Author(s):  
JAYANTA SARKAR ◽  
K. SEETHARAM ◽  
S. K. SHAHA
Keyword(s):  
Markov Chain Model ◽  
Monsoon Season ◽  
Daily Rainfall ◽  
Chain Model ◽  
Stationary Probability ◽  
South West ◽  
South West Monsoon ◽  
Dry Spell ◽  
West Monsoon ◽  
Wet Spells

In this investigation 10-day period-wise simple probability, 10-day period-wise  probability of consecutive dry and wet spells of different lengths, and month-wise different parameters, and properties of Markov Chain Model over Vidarbha region during south-west monsoon months have been studied.   For this purpose, daily rainfall data (1 June – 30 September) of 11 stations covering all the districts of Vidarbha for the period 1960-90 have been utilized.   The study reveals that over Vidarbha during monsoon season (June - September) probability of a day being wet and probability of consecutive wet spell of different lengths are by and large high during the last and first 10-day periods of July and August respectively when the monsoon is at its peak. During the first two 10-day periods in June and last two 10-day periods in September, the probabilities of a dry day and that of consecutive dry spell of different lengths and quite high. During July and August a maximum of 12-14 wet days are expected and wet spell, on an average, lasts for 2 days. Stationary probability of the occurrence of wet day (pi2) is found to be maximum during July making it the most humid month in the monsoon season.

scholarly journals Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
M. Oscar Kisaka ◽  
M. Mucheru-Muna ◽  
F. K. Ngetich ◽  
J. N. Mugwe ◽  
D. Mugendi ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Kriging Interpolation ◽  
Study Region ◽  
Daily Rainfall Data ◽  
Kriging Interpolation Method ◽  
Dry Spell ◽  
Interpolation Techniques ◽  
Mean Square Errors

This study examined the extent of seasonal rainfall variability, drought occurrence, and the efficacy of interpolation techniques in eastern Kenya. Analyses of rainfall variability utilized rainfall anomaly index, coefficients of variance, and probability analyses. Spline, Kriging, and inverse distance weighting interpolation techniques were assessed using daily rainfall data and digital elevation model using ArcGIS. Validation of these interpolation methods was evaluated by comparing the modelled/generated rainfall values and the observed daily rainfall data using root mean square errors and mean absolute errors statistics. Results showed 90% chance of below cropping threshold rainfall (500 mm) exceeding 258.1 mm during short rains in Embu for one year return period. Rainfall variability was found to be high in seasonal amounts (CV = 0.56, 0.47, and 0.59) and in number of rainy days (CV = 0.88, 0.49, and 0.53) in Machang’a, Kiritiri, and Kindaruma, respectively. Monthly rainfall variability was found to be equally high during April and November (CV = 0.48, 0.49, and 0.76) with high probabilities (0.67) of droughts exceeding 15 days in Machang’a and Kindaruma. Dry-spell probabilities within growing months were high, (91%, 93%, 81%, and 60%) in Kiambere, Kindaruma, Machang’a, and Embu, respectively. Kriging interpolation method emerged as the most appropriate geostatistical interpolation technique suitable for spatial rainfall maps generation for the study region.

scholarly journals Spatial and Temporal Analysis of Dry and Wet Spells in Upper Awash River Basin, Ethiopia

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3051
Author(s):  
Girma Berhe Adane ◽  
Birtukan Abebe Hirpa ◽  
Chul-Hee Lim ◽  
Woo-Kyun Lee
Keyword(s):  
River Basin ◽  
Management Practices ◽  
Markov Chain Model ◽  
Temporal Analysis ◽  
Chain Model ◽  
Rainfall Analysis ◽  
Dry Spells ◽  
Dry Spell ◽  
Awash River Basin ◽  
Wet Spells

This study aimed to analyze the probability of the occurrence of dry/wet spell rainfall using the Markov chain model in the Upper Awash River Basin, Ethiopia. The rainfall analysis was conducted in the short rainy (Belg) and long rainy (Kiremt) seasons on a dekadal (10–day) scale over a 30-year period. In the Belg season, continuous, three-dekad dry spells were prevalent at all stations. Persistent dry spells might result in meteorological, hydrological, and socio-economic drought (in that order) and merge with the Kiremt season. The consecutive wet dekads of the Kiremt season indicate a higher probability of wet dekads at all stations, except Metehara. This station experienced a short duration (dekads 20–23) of wet spells, in which precipitation is more than 50% likely. Nevertheless, surplus rainwater may be recorded at Debrezeit and Wonji only in the Kiremt season because of a higher probability of wet spells in most dekads (dekads 19–24). At these stations, rainfall can be harvested for better water management practices to supply irrigation during the dry season, to conserve moisture, and to reduce erosion. This reduces the vulnerability of the farmers around the river basin, particularly in areas where dry spell dekads are dominant.

scholarly journals Impact of Climate Change on Rainfall Pattern in Upper Kumaon Himalaya Region

2021 ◽  
Author(s):  
A. Singh ◽  
R. B. Singh ◽  
S. Anand ◽  
A. Mohanty ◽  
S. S. Dash
Keyword(s):  
Climate Change ◽  
High Altitude ◽  
Human Life ◽  
Rainfall Variability ◽  
Parametric Method ◽  
Daily Rainfall ◽  
Research Area ◽  
Rainfall Data ◽  
Rainfall Pattern ◽  
Kumaon Himalaya

Abstract Every single aspect of environment is affected by climate change. Change in rainfall pattern is an immense important research area in climate-change based study. Rainfall pattern has direct impacts on food production and frequencies natural disasters (landslide, cloudburst, flood, drought etc.). Consequently, that appropriate and systemic consideration since it distresses the most of the human life. Situation in Himalayan region is worst. High altitude, less agricultural area, harsh climate with high fragility makes mountain region more vulnerable in term of climate change. The objective of this study is to identify yearly, seasonal, and monthly rainfall trends in the Upper Kumaon region (UKR). Long-term gridded daily rainfall data (1950–2018) were used. Rainfall data was processed and analyzed for a period of 68 years (1950–2018) at four places (four in each Kumaon division) in the surrounding area of Almora, Bageshwar, Pithoragarh, and Champawat. The regression analysis (parametric) method and variability analysis were used to examine historical trends in daily rainfall. The rising and falling trends in rainfall, as well as anomalies, have been studied using regression.The result shows that rainfall demonstrate statistically significant changes occurred in last 34 years. Rainfall variability is higher in low altitude region than high altitude region of Upper Kumaon region.

scholarly journals Analysis of Genesis Rain in Spring Transition in Makassar

2020 ◽  
Vol 6 (2) ◽  
pp. 177
Author(s):  
Candra Febryanto Patandean
Keyword(s):  
Daily Rainfall ◽  
Secondary Data ◽  
Gumbel Distribution ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Analysis Method ◽  
Descriptive Research ◽  
Transition Season ◽  
Rainfall Patterns ◽  
The City

Extreme weather in this case heavy rains is common in the city of Makassar, both of which resulted in a flood or no flood.  This type of research is descriptive research that aims to describe the incidence of rain in the transition season in Makassar. The source of data used in obtaining data on research in Makassar is secondary data. His research methods such as analysis method is based on monthly rainfall data to determine the monthly rainfall pattern using the Log Pearson III distribution methods and daily rainfall data duration of 3 hours early to analyze the frequency of rain by using Gumbel distribution methods. Based on the results in a graph of monthly rainfall patterns in the city of Makassar in the year (1985-2014) for 30 years and chart the frequency of daily rainfall duration 3 hours late in the year (2005 to 2014) for 10 years in the transition season in the city of Makassar, we can conclude that monthly rainfall patterns in Makassar is a monsoonal pattern with the second-largest peak intensity of rainfall occurs in January and December and the smallest intensity of rainfall occurs in August.

scholarly journals Impact of Rainfall Variability on Crop Production within the Worobong Ecological Area of Fanteakwa District, Ghana

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Conrad Kyei-Mensah ◽  
Rosina Kyerematen ◽  
Samuel Adu-Acheampong
Keyword(s):  
Crop Production ◽  
Rainfall Variability ◽  
Potential Effect ◽  
Rainfall Data ◽  
Rainfall Pattern ◽  
Rainfall Distribution ◽  
District Office ◽  
Precipitation Concentration Index ◽  
The Face ◽  
Established Relationship

Crop production in the Fanteakwa District is predominantly rainfed, exposing this major livelihood activity to the variability or change in rainfall pattern. The net potential effect of severe changes in rainfall pattern is the disruption in crop production leading to food insecurity, joblessness, and poverty. As a major concern to food production in Ghana, this study seeks to show the relationship between the production of major crops and rainfall distribution pattern in the Worobong Agroecological Area (WAA) relative to food security in the face of climate change. The study analysed the variability in local rainfall data, examining the interseasonal (main and minor) rainfall distribution using the precipitation concentration index (PCI), and determined the pattern, availability of water, and the strength of correlation with crop production in the WAA. Data from the Ghana Meteorological Agency (GMet) spanning a 30-year period and grouped into 3 decades of 10 years each was used. Selected crop data for 1993-2014 was also obtained from the Ministry of Food and Agriculture’s District office and analyzed for trends in crop yield over the period and established relationship between the crop data and the rainfall data. Part of the result revealed that rainfall variability within the major seasons in the 3 groups was lower than the minor seasons. It further showed that yields of three crops have declined over the period. Among the strategies to sustain crop production is to make the findings serve as useful reference to inform discussions and policy on adaptive agricultural production methodologies for the area in the face of changing climate.

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