Including the human factor in adaptive actions to face climate change

Transcription

1 Including the human factor in adaptive actions to face climate change M.J. Polo, M.A. Losada Andalusian Institute for Earth System Research University of Cordoba University of Granada, Spain 2 nd International Conference Science for the Environment Aarhus University 3-4 October, 2013

2 Justification Assessing uncertainty and risk in integrated river coastal basin management Many and different processes interaction Uncertainty Risk Probability of occurrence Damage and opportunity loss Unit value 2

3 Objective To highlight the importance of including the call effect when assessing adaptation actions to cope with climate change. Need for providing technicians and managers with criteria to include the human factor in decision making Examples: Coastal areas occupation and protection Irrigated areas increase and high water efficiency Increasing potential risk after adaptative actions 3

4 Overview 1. Conceptual framework Uncertainty assessment and risk analysis The call effect of protection actions 2. Some examples in Southern Spain Water regulation and coastal protection The call effect on coastal occupation and irrigated area 3. Conclusions and prospective 4

5 Introduction (i) Quantifying uncertainty Different uncertainty sources in watershed modelling Input data quality and availability (climate, soil type and use, demands, terrain, policies ) Model structure and equations (scales) Time evolution of boundary conditions Uncertainty analysis: Probabilistic approach, e.g. Monte Carlo simulation techniques Usually, some simplifying hypothesis are assumed Climatic agents occurence < > Main source of uncertainty 5

6 Introduction (ii) Quantifying risk Risk = Probability of occurrence x costs of associated consequences Costs = damage x unit value For a given uncertainly level (probability), risk can be minimized on the costs term The extent of damage depends on the current level of territory occupation/use Some damages cannot be valued when compared to other Minimum risk < > Decreasing damage What about the call effect following protection actions? 6

7 1 Conceptual framework Uncertainty assessment and risk analysis: Risk = probability of occurrence x associated costs damage x unit value Protection actions reduce the frequency of small medium size events up to a threshold Hazard is decreased, and man memory changes perception of risk Extreme events remain unaffected over the threshold, but what about their damage? The call effect : Damage associated to extreme events is increased by enhanced soil occupation/use/exploitation Risk may be dramatically increased after protection actions 7

8 1 Conceptual framework Uncertainty analysis : Available multivariate data series of events and non- events = V years Probability distribution functions of the input variables This single sample is replicated N times by resampling using a Weather Generator oriented to local conditions validated at the study site (Polo and Losada, 2009; HydroPredict) Empirical/analytical pdfs of the input variables Weather Generator (Monte Carlo simulation of multivariate variables) N samples of V years of meteorological sequences Validation of pdfs and extreme variables in V years pdfs 8

9 Uncertainty analysis : Soil use distribution, water demands, system operation Resampling: 1 event, v events, season, year, V years by the Weather Generator GIS definition of the environment, and parameter values in the governing equations Watershed distributed physical/ global models (WiMMed software, 2010) Results: N groups made up by1 event, or v events, or 1 season, or 1 year, or V years N groups of results for the A state variables previously selected Probability distribution functions for each A variable and theirjoint combination (marginal, conditional, joint distributions) 9

10 Uncertainty analysis : Soil use distribution, water demands, system operation The call effect Resampling: 1 event, v events, season, year, V years by the Weather Generator GIS definition of the environment, and parameter values in the governing equations Watershed distributed physical/ global models (WiMMed software, 2010) Results: N groups made up by1 event, or v events, or 1 season, or 1 year, or V years Cost analysis: Damage increase Unit value increase N groups of results for the A state variables previously selected Probability distribution functions for each A variable and theirjoint combination (marginal, conditional, joint distributions) 10

11 2 Some examples: Water management in the Guadalquivir River Basin, Spain The Guadalquivir River Basin: km 2 µ DEM (m) Upstream watershed estuary Estuary limit Hydrological network High : 3401 Low : km km Hydrological network Guadalquivir catchment area 11

12 12

13 And what about extreme droughts? Increased damage 2 x 104 Annual average discharge in Alcala dam and irrigation area evolution Thousand of hectares hm 3 /year hm 3 año -1 ha /32 35/36 39/40 43/44 47/48 51/52 55/56 59/50 63/64 67/68 71/72 75/76 79/80 83/84 87/88 91/92 95/96 99/00 03/04 07/ % 28% /32 35/36 39/40 43/44 47/48 51/52 55/56 59/50 63/64 67/68 71/72 75/76 79/80 83/84 87/88 91/92 95/96 99/00 03/04 07/08 59% 57 % 122 % 76 % 181 % 13

14 Soil use evolution: Olive crop expansion in irrigated areas Upstream watershed Estuary Soil use Surface (ha) Surface (ha) % change % change Urban and residential areas % % Irrigated crops % % Non irrigated crops % % Marshes and tidal areas % Olive crop % % Reservoirs and dykes % % Rice crop % Channels % % 14

15 Additional consequences: coastalareas occupation 15

16 16

17 Conclusions The call effect associated to enhanced protection against both flood and water scarcity is likely to appear when adaptation actions are achieved, so specific complementary rules and/restrictions must be foreseen to avoid the associated risk. The combination of Monte Carlo simulation for the analysis with an adequate evolution in time of the variable on which the call effect acts is necessary to obtain an adequate response of the system. The inclusion of this call effect in time affects directly the final risk resulting from the analysis. Provided that adaptation actions can cope with small to medium sized events, the prior assessment should confirm that extreme events out of control do not result in risk values non acceptable from a multicriteria point of view, unless complementary actions can be performed. Adaptation limits must be foreseen and complete simulations including the call effect in a risk analysis framework is a consistent method to prevent indirect risk excess. Prospective Different approaches to model and include the call effect impact on uncertainty and risk analyis are being tested at the study case. The final simulation platform will include the different options together with an exploratory module, making the final model an useful and efficient tool to assess the decision making process in integrated river basin and coastal areas management. 17

18 Including the human factor in adaptive actions to face climate change María J. Polo, M.A. Losada Andalusian Institute for Earth System Research University of Cordoba and University of Granada, Spain ACKNOWLEDGEMENT This study was supported by the Environmental Department of the Andalusian Regional Government, and a Collaborative Agreement between the University of Córdoba, University of Granada and CSIC. The authors also thank the CLIMA network of the Andalusian Government for the weather data used in this work, and the Guadalquivir River Basin Office for the water flow data.

19 Tak! Muchas gracias Thank you for your attention 19