Interventions and Climate Change Impacts on the Water Cycle H.P. - PowerPoint PPT Presentation

Discriminating Among Direct Human Interventions and Climate Change Impacts on the Water Cycle H.P. Nachtnebel (IWHW-BOKU) hans_peter.nachtnebel@boku.ac.at Hydropredict2010 H.P. Nachtnebel

Organisers and sponsors Hydropredict2010 H.P. Nachtnebel

Organisation of the presentation • Objectives and introduction • Methodology for assessing human impacts • Methodology for climate change impact studies • Identified changes and discrimination among CC and HI • Summary and conclusions Hydropredict2010 H.P. Nachtnebel

Objectives • Analysis of changes in the hydrological cycle • Evaluation of methodological approaches to discriminate among impacts originating from climate change, direct human intervention and natural variability of processes • Elaboration of techniques for regional impacts studies Hydropredict2010 H.P. Nachtnebel

Hydropredict2010 H.P. Nachtnebel

Methodology for the assessment of human interventions • Time series analysis • Experiments • Comparative studies • Detailed (physical) hydrological models Hydropredict2010 H.P. Nachtnebel

Role of scale From Blöschl et al; 2007 Hydropredict2010 H.P. Nachtnebel

Human Impacts at different scales • Linear, local measures (river channelisation) • Regional spatial measures (land use changes) • Large scale impacts (land use changes) Hydropredict2010 H.P. Nachtnebel

Channelisation of rivers Hydropredict2010 H.P. Nachtnebel

Impacts on floods Partial duration series of floods (1961-1992) River training works Hydropredict2010 H.P. Nachtnebel

Climate change ? • No significant changes in the annual precipitation (rather a decrease) • No significant change in intensive rainfall events Partial duration series of intensive rainfall events (Sajach) Hydropredict2010 H.P. Nachtnebel

Comparison of input and output • No significant change in precipitation (neither in Input Input total amount, nor in extremes) • Increase in flood ferquency and intensity Output Output Hydropredict2010 H.P. Nachtnebel

Land use changes in a smaller catchment • Catchment area about 700 km 2 • Increase in forested area in the last 100 years • Channelisation of rivers (up to 30 years flood) • Small increase in residential area Hydropredict2010 H.P. Nachtnebel

Assessment of Land Use Changes Identification of homogeneous regions Snow layer Snow layer Soil layer Surface runoff Interflow Groundwater flow Surface runoff HBV-type A distributed model is applied (Debene and Nachtnebel, 2004) Hydropredict2010 H.P. Nachtnebel

Assessment of River Training Works in the Traisen catchment Peak flow versus changes Debene (2004) Discharge (m 3 /s) Changes in the peak flow Hydropredict2010 H.P. Nachtnebel

Assessment of Land Use Changes The 1997 event under Peak flow (m3/s) conditions of 1880 The 1997 flood Change in Peak flow Hydropredict2010 H.P. Nachtnebel

Impacts on Aral Sea Hydropredict2010 H.P. Nachtnebel

Modelling the consequences • Modelling and simulation tools hydrological model water balance model water management models agricultural models economic model ecological model (salinity, variability, depth) • Impacts on the water bodies of Aral Sea • Impacts on the Delta areas • Impacts on the Priaralie region Hydropredict2010 H.P. Nachtnebel

The Aral Sea catchment • Growth of population • Enlargement of irrigation from 1950-1980 • Increase of industrial water demand • Inefficient water use • Lack of international cooperation • The inflow to Aral Sea has been drastically reduced • The seasonal cycle has been changed • ….. Hydropredict2010 H.P. Nachtnebel

Conclusions • The direct human impacts are measurable • The human impacts may change the water regime drastically • Human impacts may chane also the seasonal cycle • What‘s about climate impacts ? Hydropredict2010 H.P. Nachtnebel

Methodology for the assessment of climate change impacts • Trend analysis of time series • Comparative catchment 1912 1969 studies Vernagt glacier Wanner et al. 2000 • GCMs and RCMs • Downscaling approaches Hydropredict2010 H.P. Nachtnebel

Do Heavy Rainfall Events Become more Frequent ? Number of days per year with more than 30 mm/day (Vienna) Zahl der Tage mit mehr als 30 mm Niederschlag in Wien Reihe 1961 - 2001 6 5 5 YES !!!! 4 4 4 4 Tage 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Jahr (after Rudel, ZAMG 2002) Hydropredict2010 H.P. Nachtnebel

Do Heavy Rainfall Events Become more Frequent ? Number of days per year with more than 30 mm/day (Vienna) Zahl der Tage mit mehr als 30 mm Niederschlag in Wien Reihe 1903 - 2001 6 5 5 5 5 5 44 4 4 4 44 4 4 4 NO !!!! 4 Tage 3 3 3 3 33 3 3 3 3 3 3 3 3 2 2 2 22 2 2 2 2 2 22 22 222 2 2 2 2 2 2 2 2 22 2 2 2 2 1 1 1 1 1 11 1 11 11 1 1 11 1 1 1 1 1 1 1 00 0 0 0 00 0 0 0 0 0 0 0 00 0 0 0 0 0 1903 1905 1907 1909 1911 1913 1915 1917 1919 1921 1923 1925 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 Jahr (after Rudel, ZAMG 2002) Hydropredict2010 H.P. Nachtnebel

Possible impacts of climate change on the water balance of Austria • Analysis at the catchment scale require high Anomalies in temperature Anomalies in rainfall resolution models (RCMs) or any downscaling approach • REMO-UBA RCM was used (10*10 km grid) Quelle: Formayer Hydropredict2010 H.P. Nachtnebel

Analysis of RCMs • The simulated T and P time series show large deviations from observations • The spatial pattern is shifted • Data need adjustment (bias correction, transfomation, quantile mapping, etc.) • The scenario outputs show large differences in P • Large uncertainty in the simulated data Hydropredict2010 H.P. Nachtnebel

Comparison between simulation and observation for the control period Hydropredict2010 H.P. Nachtnebel

Climate signal in T and P Temperature Precipitation Difference of long term mean values (1961-1990 und 2036-2065) A1B scenario Hydropredict2010 H.P. Nachtnebel

Changes of long term mean values of precipitation Long term mean annual precipitation Hydropredict2010 H.P. Nachtnebel

Hydrological simulation • RCM- data were corrected • A 1*1 km grid was used for Austria • Simualtion at monthly time steps • The hydrological model was calibrated for the past by fitting to 188 gauging stations • Glaciers were also simulated Hydropredict2010 H.P. Nachtnebel

Some simulation results (1961-1990) flow duration curves Hydropredict2010 H.P. Nachtnebel

Veränderungen im Abfluss Changes in mean annual runoff A1B scenario Difference between 1961-1990 in mm - 2011-2040 - 2036-2065 - 2061-2090 Hydropredict2010 H.P. Nachtnebel

Water balance of Austria • The observed trend in the last fifty years is also found in the hydrological simulations • A different development N and S of the mountains (in the South decrease in the North a small increase in P) • Runoff decreases between 5-25 % due to increased evaporation Hydropredict2010 H.P. Nachtnebel

Large scale simulations: precipitation Hydropredict2010 H.P. Nachtnebel

Large scale simulations: runoff Hydropredict2010 H.P. Nachtnebel Change in annual river runoff between the 1961-1990 baseline period and two future time slices (2020s and 2070s) for the A2 scenarios (Alcamo et al., 2007).

Considering both: • Human impacts: dams, irrigation,… • Climate change • At the global scale Hydropredict2010 H.P. Nachtnebel

Hydropredict2010 H.P. Nachtnebel

Hydropredict2010 H.P. Nachtnebel

Hydropredict2010 H.P. Nachtnebel

Water Stress Changes until 2025 80% of future stress from population & development not climate change! e.g. 85% US global change research funding goes to climate and carbon (Vörösmarty et al. 2001) Hydropredict2010 H.P. Nachtnebel

Role of scale • Land use impact may increase with catchment area (Aral Sea catchment, Nile,…) • Climate change impact may decraese with catchment area (when areas with different climate signals are within the catchment) Hydropredict2010 H.P. Nachtnebel

Summary and conclusions • In all our data we find both: human impacts and climate change • In many regions the direct human impacts on water resources are much larger than expected changes • For climate change impacts studies a careful adjustment of RCM data is needed, otherwise… • Large uncertainty in RCMs • Select different model outputs and different emission scenarios Hydropredict2010 H.P. Nachtnebel

Thank you for your attention Hydropredict2010 H.P. Nachtnebel