Rainfall analysis for rain-fed farming in the Great Rift Valley Basins of Ethiopia

Ademe, Fitih; Kibret, Kibebew; Beyene, Sheleme; Getinet, Mezgebu; Mitike, Gashaw

doi:10.2166/wcc.2019.242

Cited by 33 publications

(27 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In some other areas, bimodal rainfall pattern in which the highest rainfall is received in the months of April (long season) and October (short season) was identified. The second pattern recognized in the study area is the monomodal pattern of rainfall with a long Kiremt season that stretches from March through November (Ademe et al, 2020). The basins receive a total annual rainfall ranging from 538 mm in the northern lowlands of the Awash basin to as high as 1494 mm in south and southwestern parts of the basin.…”

Section: Results and Discussion 31 Spatial Variations Of Annual And Seasonal Precipitation In The Grvbmentioning

confidence: 92%

“…The selection ensured balanced representation of the major agroecology with data records of no more than 10% missing value (Seleshi and Zanke, 2004). Data quality have been ensured and published in Ademe et al (2020). Projected changes in rainfall and temperature were analyzed based on 8 combinations of 4 Global Climate Model (GCMs) (CNRM-CM5, EC-EARTH, HadGEM2-ES and MPI-ESM-LR), dynamically downscaled by 1 Regional Climate Models (RCM) (RCA4) and 2 Representative Concentration Pathways (RCPs) (RCP4.5 and RCP8.5).…”

Section: Climate Data Sourcesmentioning

confidence: 99%

“…Coefficient of Variation (CV) and standardized anomaly index (SAI) were used as descriptors of rainfall variability and the nature of the trend. The descriptor has been widely used in many rainfall variability studies in Ethiopia and elsewhere (example: Bewket and Conway, 2007;Kassie et al, 2015;Bekele et al, 2016;Ademe et al, 2020). Station based analysis was undertaken to investigate the variability class for annual, main and short season rainfall.…”

Section: Data Analysis 241 Climate Variability Analysismentioning

confidence: 99%

See 2 more Smart Citations

Spatial Analysis of Climate variability and Change in the Great Ethiopian Rift Valley Basins

2021

JEES

View full text Add to dashboard Cite

The generally high temporal and spatial climate variability and change in most parts of Ethiopia, where rainfed farming is the main form of crop production, has been the main cause of food insecurity in significant areas of the country. Spatial variations in selected climate variables were investigated for the great Rift Valley regions of Ethiopia during the baseline and projected (2021-2100) periods. Baseline climate data from 16 stations that represent different agroecology were obtained from National Meteorology Agency of Ethiopia (NMA) (http://www.ethiomet.gov.et). Corresponding projected data grided over 0.5ᵒ X 0.5ᵒ were retrieved from eight GCM-RCM combinations under two Representative concentration pathways (RCPs) from CORDEX database (http://www.cordex.org). First order Markov chain model was used for missing rainfall data filling. Coefficient of variation and standardized anomaly index descriptors were used in the analysis of climate data for each station. Spatial maps were then generated from station values using the ordinary kriging method of interpolation. The result indicated that rainfall of the study basins showed both spatial and temporal variabilities. The total annual rainfall showed variation in the year-to-year variability ranging from low in the southern half to high in the northern half of the basins. Seasonal rainfall showed high to very high variability which is challenging to rainfed agriculture. For the projected periods, majority of the climate models projected a decline in annual rainfall and increase in temperature. HadGEM2-ES_RCA4 model simulation suggested precipitation change varying from +4.2 to -16% and +3.8 to -18% for near period under RCP4.5 and RCP8.5 emission scenarios, respectively. Mean temperature is projected to rise from +0.7 to +1.25 ºC under RCP4.5 to +0.9 to +1.6 ºC under RCP8.5 across the GRVB in the near future and further warming was projected in the mid and end centuries. Rainfed crop production in the region, which is already impacted by the current climate variability, is likely to be further challenged with future climate change. As a consequence, specific impact -based adaptation strategies are essential to reduce the vulnerability of rainfed crop production in the area.

show abstract

Section: Results and Discussion 31 Spatial Variations Of Annual And Seasonal Precipitation In The Grvbmentioning

confidence: 92%

Section: Climate Data Sourcesmentioning

confidence: 99%

Section: Data Analysis 241 Climate Variability Analysismentioning

confidence: 99%

See 1 more Smart Citation

Spatial Analysis of Climate variability and Change in the Great Ethiopian Rift Valley Basins

2021

JEES

View full text Add to dashboard Cite

show abstract

“…and "stdry" in Kirundo and 21.5 and 20.3 days for "start" and "stdry" in Muyinga. High standard deviations of onset date of seasons lead to a misunderstanding of climate dynamics and, as a result, decisions about planting and related activities will be made at high risk (Ademe et al, 2019). The onset of the growing season may be associated with the northward/southward movement of the ITCZ and the Congo air mass which are subjected also to variability in year scale (Mugalavai et al, 2008;Ininda, 1994).…”

Section: Onset Cessation and Length Of Growing Periodmentioning

confidence: 99%

Response of Seasonal Vegetation Dynamics to Climatic Constraints in Northeastern Burundi

Batungwanayo¹,

Vanclooster²,

Koropitan³

2020

GEP

View full text Add to dashboard Cite

The climate crises in East Africa (EA), particularly in Burundi, have affected vegetation which, in turn, plays a key role in the climate system by modifying the terrestrial water and energy balance. Consequently, it is vital to understand vegetation dynamics and its response to current and projected climate conditions to support the design of climate resilient land management strategies. The objective of this study was to study the dynamics of vegetation cover over the Northeastern Burundi (NEB) in response to climatic constraints. The methodology used consisted of the interpretation of satellite images along with the analysis of data collected through rain-gauge stations. The data sets used include time series composite moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data collected between February 2000 and December 2017; long term (1986-2017) rainfall data acquired from two meteorological stations throughout the Northeastern provinces in Burundi and precipitation and mean temperature data (1986-2017) from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and ERA5 Daily aggregates for the study area. The study provides an assessment of the vegetation trends in NEB using the NDVI time series. In addition, regression analysis is applied to assess the relations between NDVI and precipitation, air temperature, potential evapotranspiration, as well as with growing season characteristics (onset, cessation, and length). Results show that the rate in vegetation productivity is persistently gradual between 2000 and 2011 despite fluctuations from the mean position, followed by a lower growth rate over the period 2011-2017. There has been trend variation in precipitation, neither the temperature was constant. The temperature over the region has increased while the precipitation has decreased. The onset of the growing season and air temperature also show a significant influence

show abstract

“…Trend and variability analysis of rainfall and temperature series is necessary for agriculture production, energy production, drinking water supply, and management and utilization of resources (Bekele et al, 2016). Trend and variability analysis in precipitation and temperature series have been investigated by many researchers in Ethiopia, Ademe et al(2019) for the Great Rift Valley Basins of Ethiopia, Bekele et al(2016) for Keleta watershed of Awash River Basin, Muluneh and Biazin(2015) in the Central Rift Valley of Ethiopia, Mengistu et al(2014) in the Upper Blue Nile River Basin of Ethiopia, Tekle and Tadele(2014) in Bilate watershed of Ethiopian rift valley, Kassie et al(2013) in the Central Rift Valley of Ethiopia, Setegn et al(2011) in Lake Tana Basin and Abdo et al(2009) in Gilgel Abay Catchment of Abay Basin, The reports agree that, temperature showed an increasing trend and except for few stations, no significant trend in the annual rainfall pattern was observed for the majority of stations studied and most of the studies indicated there is a variability in rainfall. Tibebe et al (2019) indicated that there is a variability of rainfall and streamflow whereas an increasing trend of streamflow was observed in most of the stations within Awash river basin.…”

Section: Introductionmentioning

confidence: 99%

Hydro-climatic Variability and Trend Analysis of Modjo River Watershed, Awash River Basin of Ethiopia

2021

JEES

View full text Add to dashboard Cite

Climate change and variability is expected to trigger changes in temperature and precipitation series. This study aimed at assessing variability and trend of hydro-climatic variables at Modjo River watershed. Long-term climate data of 5 representative stations with in the watershed and streamflow data of Modjo gauging station (1983 -2010) were used. Rainfall variability was analyzed using Coefficient of variation (CV), Precipitation concentration index (PCI) and Standardized anomaly index (SAI). Climate trends were evaluated using Sen's slope estimator and Mann-Kendall trend test methods. The study revealed Most of the stations showed low variation in annual rainfall (CV% <20) while the main (Kiremt) and short (Belg) season rainfall exhibited CV ranging from low to high. Both annual and seasonal rainfall showed a non-significant trend at all stations for the past 30 years. However, majority of stations showed an increasing trend in annual daily average temperature ranging from 0.2 to 0.6ºC per decade. Following increases in temperature and the subsequent rise in evapotranspiration, streamflow has shown a high significant declining trend. The temporal decline in streamflow at Modjo watershed could likely affect downstream Koka dam water reserve. Thus, any watershed management strategy that can optimize water conservation for sustainable crop production and option that can improve flow to the reserve is vital.

show abstract

Rainfall analysis for rain-fed farming in the Great Rift Valley Basins of Ethiopia

Cited by 33 publications

References 15 publications

Spatial Analysis of Climate variability and Change in the Great Ethiopian Rift Valley Basins

Spatial Analysis of Climate variability and Change in the Great Ethiopian Rift Valley Basins

Response of Seasonal Vegetation Dynamics to Climatic Constraints in Northeastern Burundi

Hydro-climatic Variability and Trend Analysis of Modjo River Watershed, Awash River Basin of Ethiopia

Contact Info

Product

Resources

About