CHALLENGES ON DAM SAFETY UNDER CHANGING CLIMATE IN INDIA MANOHAR ARORA NATIONAL INSTITUTE OF HYDROLOGY, ROORKEE
• The most common causes of failure of large dams over the world are overtopping accounting for 32% failures followed by internal erosion accounting for 27% failures. • Of the world wide dam failures caused by overtopping, 73% are due to inadequate spillway capacity and 27% due to spillway gate failure.
There are currently about 4839 completed large dams in India, with another 348 under construction (CWC, 2013). The total storage capacity of these dams, 76% of which are more than 20 years old, is about 283 billion cubic meters.
Temperatures increase significant changes in seasonal and annual rainfall patterns and other factors affecting streamflow. M ost of the world's dams have not been built to allow for the erratic hydrological patterns that climate change is bringing. M ore extreme storms and increasingly severe floods will have major implications for dam safety.
FLOOD ESTIMATION/DESIGN FLOOD CALCULATIONS IN INDIA The Bureau of Indian standard guidelines IS: 5477 (Part IV) recommends that the Inflow Design Flood (IDF) of a structure, depending on its importance or risk involved, may be chosen from either one of the following: Probable M aximum Flood (PM F) Standard Project Flood (SPF) Flood of a Specific Return Period
SEASONAL AND REGIONAL FLOOD CHARACTERISTICS / PROCESS TYPES PROPOSED Process Type Long Rain Floods Short- Rain Flash Floods Rain- On-Snow Snowmelt Floods Floods Floods Timings of No pronounced No pronounced Floods and Often occur during Floods in spring to floods seasonality seasonality extreme rainfall transition between summer mainly in summer cold and warm or late summer periods Storm duration Long duration (> 1- Duration of Short duration (< Moderate rainfall Rainfall day) several hours to 1 90 min), high events can cause unimportant day intensities large floods Rainfall depths, Substantial rainfall Moderate to Small to moderate Snow melt and Snowmelt, no or snow melt depths Substantial rainfall depths rainfall minor rainfall rainfall Catchment state Wet due to persistent Wet for large Any Wet , snow Wet , snow (SWE, soil rainfall flood event covered covered moisture) Runoff response Slow response Fast response Flashy response Responses range Medium or slow dynamics from fast to slow response Spatial Large spatial extent Local or regional Limited spatial Limited to areas of Medium spatial coherence of storms and floods extent extent of storms snow cover extent of floods ( >10 4 km 2 ) and floods (< 30 km 2 )
NEW CLIMATE CHANGE PROJECTIONS FOR INDIA • Replacing the old SRES scenarios RCP scenarios based climate projections are now available. • Currently about 40 climate models provide climate projections at global scale • CMIP5 ESMs are available on better resolution (1-2.8 ° ) than the previous CMIP3 models
AN INTRODUCTION TO THE RCP SCENARIOS GtC/Yr 936 30 ppm 25 RCP 8.5 20 RCP 6.0 670 15 ppm RCP 4.5 10 538 RCP 2.6 5 ppm 421 0 ppm -5
LIST OF CMIP 5 GCMs Resolution (lat) - Resolution (lon) S. . Model Modeling Center (or Group) deg - deg No. 1 CCSM4 National Center for Atmospheric Research, USA 0.942 1.250 Commonwealth Scientific and Industrial Research Organization in CSIRO-Mk3.6 collaboration with Queensland Climate Change Centre of Excellence, 2 1.895 1.875 Australia 3 GISS-E2-R NASA Goddard Institute for Space Studies, USA 2.022 2.517 4 HadGEM2-ES Met Office Hadley Centre, UK 1.250 1.875 5 IPSL-CM5A-LR Institut Pierre-Simon Laplace, France 1.895 3.750 Japan Agency for Marine-Earth Science and Technology, The 6 MIROC-ESM University of Tokyo), and National Institute for Environmental 2.857 2.813 Studies Japan Agency for Marine-Earth Science and Technology, The MIROC-ESM-CHEM University of Tokyo), and National Institute for Environmental 7 2.857 2.813 Studies The University of Tokyo, National Institute for Environmental MIROC5 Studies, and Japan Agency for Marine-Earth Science and 8 1.417 1.406 Technology 9 MRI-CGCM3 Meteorological Research Institute, Japan 1.132 1.125 10 NorESM1-M Norwegian Climate Centre 1.895 2.500 11 BCC-CSM1.1 Beijing Climate Center, China Meteorological Administration 2.812 2.812 12 CESM1(CAM5) Community Earth System Model Contributors 0.937 1.250 13 FIO-ESM The First Institute of Oceanography, SOA, China 2.812 2.812 14 GFDL-CM3 NOAA Geophysical Fluid Dynamics Laboratory 2.000 2.500 15 GFDL-ESM2G NOAA Geophysical Fluid Dynamics Laboratory 2.000 2.500 16 GFDL-ESM2M NOAA Geophysical Fluid Dynamics Laboratory 2.000 2.500 17 HadGEM2-AO Met Office Hadley Centre, UK 1.241 1.875 18 NorESM1-ME Norwegian Climate Centre 1.875 2.500
MULTI-MODEL APPROACH TO CAPTURE UNCERTAINTIES IN TEMPERATURE AND PRECIPITATION PROJECTIONS OVER INDIA Baseline = 1961-1990 Chaturvedi et al., (2012)
CMIP5 model ensemble mean temperature change ( ° C) relative to the pre-industrial period Chaturvedi et al., 2012
CMIP5 model ensemble mean precipitation change (%) relative to the pre-industrial period Chaturvedi et al., 2012
LIMITATIONS OF THE CMIP5 BASED CLIMATE PROJECTIONS
For the whole India, the projections of maximum temperature from all the six models showed an increase within the range 2.5°C to 4.4°C by end of the century with respect to the present day climate simulations. The annual rainfall projections from all the six models indicated a general increase in rainfall being within the range 15-24%.
• Under the business-as-usual (between RCP6.0 and RCP8.5) scenario, mean warming in India is likely to be in the range 1.7-2 degrees C by 2030s and 3.3 - 4.8 degrees C by 2080s relative to pre-industrial times; • All-India precipitation under the business-as-usual scenario is projected to increase from 4% to 5% by 2030s and from 6% to 14% towards the end of the century (2080s) compared to the 1961-1990 baseline; • There is a consistent positive trend in frequency of extreme precipitation days (e.g. > 40 mm/ day) for decades 2060s and beyond.
Pyramid of uncertainties in climate models (GCM ’s) Conclusions for water management M odels (e.g. climate scenarios) Assumptions Theory Data Result: • GCM ’s are good in predicting temperature • GCM ’s are very poor in predicting rainfall • ‘bias correction’ of 600% in some cases
How certain are the changes ? “ Climate is changing, the risk is unacceptable! “ Water manager Scientist (Hans M iddelkoop, ~1995)
“ How much.. ? “ 0,7 0,5 (Pscenario-Ppresent)/Ppresent 0,3 0,1 -0,1 jan feb mar apr may jun jul aug sep oct nov dec CSIRO-Mk2 CGCM1 -0,3 ECHAM4 HadCM2 Gga1 HadCM2 Gga2 HadCM2 Gga3 -0,5 HadCM2 Gga4 CCSR-98 HADCM2 GSa1 -0,7 Water manager Scientist Hans M iddelkoop, ~1995)
‘ Short List’ of potential vulnerability of reservoir function to climate change Dam function Climate variable Potential impact Flood detention High rainfall Increased flow into reservoirs increases flood risk: increased storage requirements or less well managed floods. Increase in sedimentation during flood events could lead to reduction in flood storage capacity and/ or blockage of spillways due to increased mobilisation of vegetation in flood flows High temperature Increase in vegetation growth - potential reduction in reservoir capacity and/ or blocking of spillways
Dam function Climate variable Potential impact Storage for seasonal High rainfall High rainfall events leading to use increased peak flows into impounding reservoirs can lead to overtopping. Dams may need to be operated at lower or more variable levels to mitigate against this risk, potentially reducing available storage. Increase in sedimentation during flood events could lead to a reduction in water storage capacity. Increase in turbidity during flood events could lead to water clarity & quality issues with resultant increased treatment requirements. Water may no longer be suitable for some uses at certain times of year
Dam function Climate variable Potential impact Storage for Low rainfall Lower rainfall will lead to lower flows, seasonal use decreasing reservoir levels and less water will be available for use. Reduced yields. Low rainfall will increase demand for water for irrigation and environmental uses. For reservoirs with secondary purposes, management conflicts can occur when draw down is required for primary function (e.g. recreational use of water supply reservoirs; environmental flow releases). Lower water levels leading to increased concentration of pollutants, lower water quality and higher treatment requirements.
Dam function Climate variable Potential impact Storage for High temperature Increase in water temperature leading seasonal use to increased vegetation growth and eutrophic conditions. Increased duration and frequency of Algal blooms. Reduction in water quality and increase in treatment requirements. Water may not be suitable for some purposes (e.g. environmental releases). Increase in evaporation of stored water, and transpiration from vegetation and soils - lower water levels in reservoirs and less available for use.
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