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HYDROLOGICAL PROPAGATION OF ENSO IMPACTS ON DROUGHT RISK ACROSS SUB-SAHARAN AFRICA JOSIE BAULCH, JUSTIN SHEFFIELD, JADU DASH Department of Geography & Environmental Sciences, University of Southampton [email protected] ABSTRACT OBJECTIVES RESULTS DATA & METHODS Giannini, A., Biasutti, M., Held, I. M., & Sobel, A. H. (2008). A global perspective on African climate. Climatic Change, 90(4), 359–383. https ://doi.org/10.1007/s10584-008-9396-y Kotir, J. H. (2011). Climate change and variability in Sub-Saharan Africa: a review of current and future trends and impacts on agriculture and food security. Environ Dev Sustain, 13, 587–605. https ://doi.org/10.1007/s10668-010-9278-0 Rippke, U., Ramirez-Villegas, J., Jarvis, A., Vermeulen, S. J., Parker, L., Mer, F., ... & Howden, M. (2016). Timescales of transformational climate change adaptation in sub-Saharan African agriculture. Nature Climate Change. Sheffield, J., and Wood, E., (2011), Drought: past problems and future scenarios. Earthscan: London, UK Sheffield, J., Wood, E. F., Chaney, N., Guan, K., Sadri, S., Yuan, X., ... & Ogallo, L. (2014). A drought monitoring and forecasting system for sub-Sahara African water resources and food security. Bulletin of the American Meteorological Society, 95(6), 861-882 DISCUSSION FUTURE WORK Sub-Saharan Africa is particularly susceptible to the effects of hydrological extremes, such as drought, due to the high dependency of much of the population, and national economies, on agriculture. Increased precipitation variability, as a result of climate change, has made the need for better and more reliable forecasts even more necessary. Furthermore, drought risk is generally quantified in terms of meteorological anomalies due to better availability of information on precipitation, yet drought impacts are most aligned with soil moisture and hydrological drought, which are more difficult to monitor and forecast. Initial results have shown that the positive and negative phases of ENSO have a strong impact on regional meteorological drought risk across the continent. As these trends propagate through the hydrological system, they manifest in other biophysical variables (such as soil moisture, stream flow and NDVI), with various time lags and differing spatial patterns. The aim of this paper is to quantify the enhanced risk of growing season drought in SSA due to ENSO events. This has been achieved by: 1) Quantifying the spatial and temporal variability and trends in growing season drought events over the past 67 years 2) Estimating the risk of drought and how it changes with the ENSO climate oscillation 3) Analysing how drought risk propagates through the hydrological cycle, from meteorological, to agricultural to hydrological drought 4) Identifying which staple crops are most at risk from drought in regions with high agricultural dependency REFERENCES Climatic and hydrological data - African Flood and Drought Monitor [Sheffield et al., 2014] ENSO data - Multivariate ENSO Index (MEI) [NOAA] Growing season data - Crop Calendar [Centre for Sustainability and the Global Environment] 1. Determine growing season start and end date for maize s for each grid cell 2. Define a drought year as a year with 2 or more months within the growing season that fall below the drought threshold 3. Calculate drought statistics (duration, magnitude etc…) 4. Repeat analysis for El Nino and La Nina years only 5. Repeat analysis with growing season data for other staple crops (cassava, sorghum and millet) MAIZE Relative Risk and Average Duration of Growing Season Drought Across SSA Major Crop Harvest Locations in SSA >500Ha Quantitative time lag analysis to further understand how drought propagates through the hydrological system Analyse drought risk variance for other staple crops to asses which regions are most sensitive to drought events depending on the growing season of the most densely grown crop Regional patterns between growing season drought risk and ENSO phases across SSA are clearly present In El Niño years, drought risk increases in areas of southern Africa, the western Sahel and the Horn of Africa In La Niña years, the risk of drought decreases across much of SSA, particularly in central Africa, but increases even further in the Horn of Africa These regional variations can be seen propagating through, from meteorological drought, to agricultural drought, with a minimal time lag For most of SSA, fewer years experienced hydrological drought, than meteorological and agricultural drought. SPI1 SMPCT RUN Average Duration of Growing Season Drought (24°E, 22°S)

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Page 1: HYDROLOGICAL PROPAGATION OF ENSO IMPACTS ON …eoscience.esa.int/landtraining2018/files/posters/baulch.pdf · 2018. 9. 19. · HYDROLOGICAL PROPAGATION OF ENSO IMPACTS ON DROUGHT

HYDROLOGICAL PROPAGATION OF ENSO IMPACTS ON DROUGHT RISK ACROSS SUB-SAHARAN AFRICA

JOSIE BAULCH, JUSTIN SHEFFIELD, JADU DASHDepartment of Geography & Environmental Sciences, University of Southampton

[email protected]

ABSTRACT

OBJECTIVES

RESULTS

DATA & METHODS

Giannini, A., Biasutti, M., Held, I. M., & Sobel, A. H. (2008). A global perspective on African climate. Climatic Change, 90(4), 359–383.https://doi.org/10.1007/s10584-008-9396-y

Kotir, J. H. (2011). Climate change and variability in Sub-Saharan Africa: a review of current and future trends and impacts on agriculture and food security.Environ Dev Sustain, 13, 587–605. https://doi.org/10.1007/s10668-010-9278-0

Rippke, U., Ramirez-Villegas, J., Jarvis, A., Vermeulen, S. J., Parker, L., Mer, F., ... & Howden, M. (2016). Timescales of transformational climate change adaptationin sub-Saharan African agriculture. Nature Climate Change.Sheffield, J., and Wood, E., (2011), Drought: past problems and future scenarios. Earthscan: London, UKSheffield, J., Wood, E. F., Chaney, N., Guan, K., Sadri, S., Yuan, X., ... & Ogallo, L. (2014). A drought monitoring and forecasting system for sub-Sahara Africanwater resources and food security. Bulletin of the American Meteorological Society, 95(6), 861-882

DISCUSSION

FUTURE WORK

Sub-Saharan Africa is particularly susceptible to the effects of hydrological extremes, such as drought,due to the high dependency of much of the population, and national economies, on agriculture.Increased precipitation variability, as a result of climate change, has made the need for better and morereliable forecasts even more necessary. Furthermore, drought risk is generally quantified in terms ofmeteorological anomalies due to better availability of information on precipitation, yet drought impactsare most aligned with soil moisture and hydrological drought, which are more difficult to monitor andforecast. Initial results have shown that the positive and negative phases of ENSO have a strong impacton regional meteorological drought risk across the continent. As these trends propagate through thehydrological system, they manifest in other biophysical variables (such as soil moisture, stream flow andNDVI), with various time lags and differing spatial patterns.

The aim of this paper is to quantify the enhanced risk of growing season drought in SSA dueto ENSO events. This has been achieved by:

1) Quantifying the spatial and temporal variability and trends in growing season droughtevents over the past 67 years

2) Estimating the risk of drought and how it changes with the ENSO climate oscillation3) Analysing how drought risk propagates through the hydrological cycle, from meteorological,

to agricultural to hydrological drought4) Identifying which staple crops are most at risk from drought in regions with high agricultural

dependency

REFERENCES

Climatic and hydrological data -African Flood and DroughtMonitor [Sheffield et al., 2014]

ENSO data - Multivariate ENSOIndex (MEI) [NOAA]

Growing season data - CropCalendar [Centre for Sustainabilityand the Global Environment]

1. Determine growing seasonstart and end date for maize sfor each grid cell

2. Define a drought year as ayear with 2 or more monthswithin the growing seasonthat fall below the droughtthreshold

3. Calculate drought statistics(duration, magnitude etc…)

4. Repeat analysis for El Ninoand La Nina years only

5. Repeat analysis with growingseason data for other staplecrops (cassava, sorghum andmillet)

MAIZE

Relative Risk and Average Duration of Growing Season Drought Across SSA

Major Crop Harvest Locations in SSA>500Ha

• Quantitative time lag analysis to further understand how drought propagates through the hydrological system

• Analyse drought risk variance for otherstaple crops to asses which regions aremost sensitive to drought eventsdepending on the growing season of themost densely grown crop

• Regional patterns between growing season drought risk and ENSO phases across SSA are clearly present

• In El Niño years, drought risk increases in areas of southern Africa, the western Sahel and the Horn of Africa

• In La Niña years, the risk of droughtdecreases across much of SSA,particularly in central Africa, butincreases even further in the Hornof Africa

• These regional variations can beseen propagating through, frommeteorological drought, toagricultural drought, with a minimaltime lag

• For most of SSA, fewer yearsexperienced hydrological drought,than meteorological and agriculturaldrought.

SPI1SMPCTRUN

Average Duration of Growing Season Drought (24°E, 22°S)