drought risk in changing climate - unescap.org
TRANSCRIPT
Central Asia is expected to become warmer in the coming
decades and increasingly arid, especially in the western
parts of Turkmenistan, Uzbekistan, and Kazakhstan
(Lioubimtseva and Henebry, 2009). Some parts of the
region could be winners (cereal production in northern and
eastern Kazakhstan could benefit from the longer growing
season, warmer winters, and a slight increase in winter
precipitation), while others could be losers (particularly
western Turkmenistan and Uzbekistan, where frequent
droughts could negatively affect cotton production,
increase already extremely high water demands for
irrigation, and exacerbate the already existing water crisis
and human-induced desertification).
IPCC AR5 WG2 on drought in Central Asia
Volga-Kama Cascade of dams
The total mean electric-power generation is 38,270
GW
Ongoing renovation should further increase power
generation
Multiple users on water resources
• Hydropower
• Agriculture
• Industry
• River transport
• Drinking water
DSS for Volga River Hydropower cascade
Water levels
monitoring and prediction
DSS for cascade regulation
Drought causing cascading effects
Warm
(May-Sep)
Cold
(Nov – Mar)Winter
1978-2006
1946-1977
Mean precipitation anomalies
in Volga region
Volga River Hydropower cascade: role of climate
Regime shift of 1976: Temperature
NH temperature trends
Trend length
Fir
st y
ear
Annual temperature in Russia
Daily RR, mm 𝜏, distribution
𝜋, distribution
BeforeAfter
𝛾2 − 𝛾1
𝑐ℎ𝑎𝑛𝑔𝑒s 𝑖𝑛𝑑𝑖𝑠𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 𝑠ℎ𝑎𝑝𝑒
Daily rainfall R follows Zero Inflated Gamma distribution 𝜸𝑹~𝜸 𝜶, 𝜷, 𝝅 [1]
Where
𝜶 - shape
𝜷 – rate or inverse scale
𝝅 – probability of zero (no rainfall)
Regime shift creates inconsistency in model parameters –
𝜶, 𝜷, 𝝅 = ቊ𝜶𝟏, 𝜷𝟏, 𝝅𝟏 𝑖𝑓 𝒕 < 𝝉𝜶𝟐, 𝜷𝟐, 𝝅𝟐 𝑖𝑓 𝒕 ≥ 𝝉
[2]
𝝉 – time of regime shift
t – observation time
We assume following priory values –
𝜶𝟏 = 𝜶𝟐 = 𝑵𝒐𝒓𝒎𝒂𝒍(𝝁 = 𝟏, 𝝈 = 𝟏. 𝟓)[3]
𝜷𝟏 = 𝜷𝟐 = 𝑵𝒐𝒓𝒎𝒂𝒍(𝝁 = 𝟎. 𝟏, 𝝈 = 𝟎. 𝟓) [4]
𝝅𝟏 = 𝝅𝟐 = 𝑼𝒏𝒊𝒇𝒐𝒓𝒎(𝟎, 𝟏) [5]
𝝉 = 𝑼𝒏𝒊𝒇𝒐𝒓𝒎(𝒕𝟎 + 𝟑𝟔𝟓 ∗ 𝟓, 𝒕𝒏 − 𝟑𝟔𝟓 ∗ 𝟓) [6]
Example of precipitation regime shift detection
Probability of no rain
Regime shift of 1976: Physical mechanismW type E type C type
January
July
Amplitude
• Long period oscillation in the Pacific ocean, specifically PDO-ENSO interactions, cause rapid changes in global circulation
• Change in global circulation affect frequency of different circulation types in Central Asia leading to precipitation regime shift
• The effect is most pronounced in the Pacific but detectable in most of the Northern Hemisphere
Regime shift of 1976: Physical mechanism
PDONino 3.4
Regime shift of 1976: Physical mechanism
We are currently in a stable regime,
however,
based on a historical data we can expect
another rapid regime shift somewhere in
2025-2035
Regime shift have a strong effect on a
drought frequencies and magnitude
Additional research is necessary to
estimate local impacts
National scale multihazard risk assessment: Example -UNDP Tajikistan project
Goals:
• Update the methodology for The District Disaster Risk Assessment
• Conduct Risk assessment for all the districts of Tajikistan
• Develop District Risk Profiles.
• Build the capacity of the local stakeholders on the process of the risk assessment.
MULTI-HAZARD RISK ASSESSMENT
Diagram by Cees van Westen
• Collecting data
• Modelling and hazard assessment
• Engaging local experts
• Training seminars and capacity building
ACTIVITIES
• Understanding changing climate important for a long-term planning
• Decision making systems often tuned to fit current situation
• Climate change is not always gradual but often happens as a rapid regime shift
IMPACT OF CLIMATE CHANGE
Final thoughts
• There are gap between state of the art methods of hazard risk
assessment and local expertise. In my opinion capacity building projects
have more direct impact compare to research projects.
• A lot of value can be extracted on a local level from global freely
available datasets given sufficient expertise of the local experts
Thank you!
Vasily Kokorev
Researcher
KNMI and ITC (University of Twente)