Full Technical Report: Hydro Power production in a future climate

Transcription

1 Full Technical Report: Hydro Power production in a future climate Author name: Linnéa Gimbergson Author organization: SMHI Full Technical Report: Hydropower production in a future climate

2 Summary The focus of this case study has been to look at how a future climate change may affect inflow to hydropower reservoirs. Hydropower operators need information about inflow volumes and seasonal distribution both on short and long term in order to plan for production and maintenance work. The study has been carried out in cooperation with Vattenfall and the selected study site was Luleälven River in Northern Sweden. Hydrological model ensembles from the C3S SIS for Water have been used together with local observations. Results indicate that unregulated river flow in Luleälven River will be higher in the future compared to the reference period. Looking at the seasonal distribution of water, results show increasing flow in autumn, winter and beginning of spring and decreasing flow during summer. The temporal distribution is also affected by a shift in timing of snow maximum to earlier in spring, leading to an earlier flow peak from snow melt. The results from the case study shows the importance of considering climate change in decisions related to future hydropower production in Luleälven River. Further evaluation of long term consequences and possibilities will require additional studies, where methods developed in this study may be applied. Full Technical Report: Hydropower production in a future climate

3 Contents Introduction... 1 Step 1: SWICCA hydrological data... 2 Unregulated river flow... 2 Snow water equivalent... 2 Results... 4 Step 2: Local hydrological data, Luleälven River... 5 Results... 6 Step 3: Indicators of hydrology... 7 Unregulated river flow... 7 Snow water equivalent... 7 Results... 8 Comparison with observation Results Step 4: Basis for future hydro power operation Step 5: Evaluation, long term Conclusion of Full Technical Report References Full Technical Report: Hydropower production in a future climate

4 Introduction Forecasts and observations of water flowing into reservoirs is a key part of hydropower planning, as it determines the amount of water available for production. Daily short time production planning, optimization, price forecasting and long-term planning of investments are some examples where inflow data is used. A future climate change may impact volume and temporal distribution of inflow. Hydropower operators therefore need information about future conditions in order to make sustainable plans for continuous operation. Examples could be investments in dam safety or preparations to adjust production / regulation capacities. The contributing client in this study was Vattenfall, a major energy producer in Northern Europe with about 30 percent of their total electricity production from hydropower ( Today, Vattenfall use historical data to generate scenarios for long-term planning of hydropower. The historical records are linked to present conditions by defining a state with information about current water content in snow, soil and ground water. However, the historic records do not hold any information about future climate changes and hydrological climate scenarios are therefore an important complement to make long-term scenarios more representative of the future. The aim of this case study has been to test how pan-european hydrological climate data can be used to calculate indicators useful for hydropower operators. Focus has been on variables for unregulated river flow and snow storage. The study site is Luleälven River in Northern Sweden. The river runs through the county of Norrbotten, from the Norwegian boundary down to the Bay of Bothnia, with a drainage basin of about sq.km. It is one of the largest rivers regulated for hydropower in Sweden and Vattenfall is the only operator. In this study, unregulated river flow is taken as an estimation of inflow, which represents the flow of water into reservoirs. When estimating the amount of water available for hydropower, inflow is a more relevant measure than river flow as the distribution of river flow in time is often altered by regulation in power plants. Discharge from upstream hydropower plants is often known by production plans and this together with inflow from surrounding catchments gives the total amount of water available. Long-term mean values of inflow and (regulated) river flow are the same but seasonal variation can be very different, especially in a highly regulated river as Luleälven. The unregulated river flow data available from the C3S SIS Water have been generated by a special set-up of the pan-european hydrological model where lake regulations, hydropower plan regulations, and water withdrawal for irrigation has been removed. ( Full Technical Report: Hydropower production in a future climate 1

5 Step 1: SWICCA hydrological data Multimodel ensemble The hydrological climate data from SWICCA used in this study were unregulated river flow and snow water equivalent. Downloaded data sets include multimodel ensembles with results from hydrological model runs for reference period and future period (data for included in ensemble with unregulated river flow). The hydrological model runs in SWICCA have been done based on ensembles of bias-corrected climate model data as input. All SWICCA climate data used in this study are result from hydrological model runs with a pan-european model set up of the HYPE model (E-HYPE). Data sets were downloaded with catchment resolution corresponding to the model. Median catchments size in E-HYPE is 215 km 2. More details on the HYPE model and the input climate model data can be found on the SWICCA website ( Unregulated river flow Ensembles of unregulated river flow were downloaded as an Essential Climate Variable (ECV) data set, containing time series with daily mean values (m 3 /s) for the period Data were downloaded for eight catchments/model subbasins in Luleälven. For each catchment, values downloaded represent total flow from entire upstream area. Selected catchments given in figure 1 and table 1. Snow water equivalent Ensembles of snow water equivalent were downloaded from SWICCA as an indicator data set, containing 30-year mean values of monthly mean snow water equivalent (mm) for periods , , and Reference period data as absolute values in mm, future climate data as mm change relative to the reference period. Data were downloaded for all model subbasins within Luleälven drainage basin. Distribution of model sub-basins can be seen in Figure 1. 1 Two members of the SWICCA ensemble were missing for Members based on climate model combination GCM/RCM: HadGEM2-ES / RCA4, with RCP45 and RCP85. Full Technical Report: Hydropower production in a future climate 2

6 Figure 1 Distribution of sub-basins in pan-european hydrological model (gray lines) and selected catchments / model subbasins used for evaluation of unregulated river flow (green). Green areas represent the most downstream sub-basins in aggregated total catchments selected for study Full Technical Report: Hydropower production in a future climate 3

7 Table 1 Area of selected catchments in Luleälven Catchment/model sub-basin Total upstream area km 2 Suorva Vietas Satis Porjus Tjaktjajaure Parki Karats Letsi Boden Results Figure 2 shows example of unregulated river flow ensemble in downloaded data set from C3S SIS for Water. The values are for the Porjus catchment. Figure 2 Time series of unregulated total river flow in SWICCA ensemble. Example for catchment Porjus. Full Technical Report: Hydropower production in a future climate 4

8 Step 2: Local hydrological data, Luleälven River Observed inflow Observed inflow was calculated from time series with observed discharge (production water and spill) and reservoir level. Calculations were done per reservoir sub-basin and aggregated to get total inflow for catchments with corresponding upstream area as selected catchments in the pan-european model (figure 1). Distribution of reservoir sub-basins is given in figure 3. The data set covers the period but with some years missing in the start of the period for some catchments. See table 2 data period per catchment. Observed snow Data records from snow measurements done by Vattenfall were available from eight locations within Luleälven drainage basin. Records include values of snow mm water equivalent with one observation per year starting The measurements are made each spring just before snow melt and values are taken as representative of maximum snow storage. Stations and period of data are given in table 3. Table 2 Aggregated upstream area of selected catchments and time period of observed inflow data. Catchment name Area km 2 Period Suorva Vietas_Satis (Sitasjaure + Satihaure) Porjus Tjaktjajaure Parki Karats Letsi Boden Table 3 Location of snow measurements and period of observation used in this strudy. Station name Period Kuorpak Sitas fjäll Muddusjåkk Nautijaure Piertinjaure Vaisa fjäll Ålluokta Årrenjarka Full Technical Report: Hydropower production in a future climate 5

9 Figure 3 Distribution of reservoir sub-basins (gray lines) and snow observation points (black dot). Green areas represent the most downstream reservoir sub-basins in aggregated total catchments selected for study. Results In figure 4 is example of observed total inflow for catchment Boden Figure 4 Observed total inflow for catchment Boden. Full Technical Report: Hydropower production in a future climate 6

10 Step 3: Indicators of hydrology Unregulated river flow The indicator is unregulated river flow as percent of mean unregulated river flow in the reference period. It was defined as relative to avoid absolute values in results for future periods. For each of the selected catchment, indicators were calculated for long-term mean values and standard years (to plot seasonal variation) and compiled (/summarized?) as mean values over three future climate periods; , and All calculations were done for total flow, including water from upstream area of each catchment. Definition of indicator: uuuuuuuuuuuuuuuuuuuuuu rrrrrrrrrr ffffffff 100 mmmmmmmm uuuuuuuuuuuuuuuuuuuuuu rrrrrrrrrr ffffffff Calculation steps Iterated per ensemble member and climate period; , , and : Long-term mean calculated from daily m 3 /s values Standard year time series calculated from daily m 3 /s values. Resulting time series has a value for each day that equals the mean of all values given for that day in the specified period. Indicators for seasonal distribution (using standard year time series) and long-term mean calculated according to definition above Iterated per ensemble member and future climate period; , and : Indicator for long-term mean calculated according to definition above. A frequency analysis was done from the full time series of unregulated river flow, for given climate period. The analysis is done by sorting values in increasing order and extracting quantiles for the percentage of time that the flow exceeds a certain threshold values. Results were used to plot duration curves to see changes in extreme values. Statistics were calculated at the end to get indicator mean, min and max of all ensemble members. Snow water equivalent The indicator is defined in two parts; 1) mm change in maximum snow storage compared to reference period and 2) number of months shift in time for when maximum snow storage occur compared to reference period. All calculation steps are related to local snow water equivalent per model subbasin. Full Technical Report: Hydropower production in a future climate 7

11 (ssssssss mmmmmmmmmmmmmm mmmm ) (ssssssss mmmmmmmmmmmmmm mmmm ) (mmmmmmmmh wwwwwwh ssssssss mmmmmmmmmmmmmm ) (mmmmmmmmh wwwwwwh ssssssss mmmmmmmmmmmmmm ) Calculation steps Iterated per ensemble member: Data extracted for model sub-basins within Luleälven drainage area (original file downloaded from demonstrator included data for a larger area) Iterated per model sub-basin: Snow mm water equivalent in future climate periods calculated from snow mm water equivalent in reference period and mm change in snow water equivalent in future periods Values of maximum snow mm water equivalent extracted for reference and future periods Month with maximum snow mm extracted for reference and future periods Indicators calculated according to definitions above Statistics were calculated at the end to get indicator mean value of all ensemble members. Result tables were exported and changes plotted in result maps covering the total Luleälven catchment area. Results Unregulated river flow Following is example of the indicator for unregulated river flow calculated for catchment Porjus. Change in seasonal variation in graph (figure 5) and change in long term mean in table (table 4). Corresponding results have been produced for all selected study catchments, for period , , All indicator results are related to flow from total upstream catchment. Full Technical Report: Hydropower production in a future climate 8

12 Figure 5 Unregulated river flow as percent of mean unregulated river flow in reference period. Seasonal distribution, upper graph: daily values October September, solid lines give mean of climate models and shaded intervals gives min and max of climate models. Duration curve, lower graph: values on x-axis give percent of time when unregulated river flow exceeds threshold values (read from y-axis). X-axis has Gaussian scaling to easier see changes in highest and lowest flow interval. Solid lines give mean of climate models and dashed lines give min and max of climate models. In both graphs, reference period is shown in black. Table 4 Long-term mean of unregulated river flow in future climate periods as percent of mean unregulated river flow in reference period. Sub-basin Period RCP26 RCP45 RCP85 Porjus Full Technical Report: Hydropower production in a future climate 9

13 Maximum snow water equivalent Following in figure 6 is example of the indicator for snow water equivalent calculated for period and RCP45. Maps have been produced for all three future climate periods, , and , including results for RCP26 and RCP85. Figure 6 Change in maximum snow water equivalent (RCP45) relative to reference period, mean values in mm. Numbers per model sub-basin give the shift in time (months) for when snow maximum occur, mean of (RCP45) compared to reference period Full Technical Report: Hydropower production in a future climate 10

14 Comparison with observation Unregulated river flow and inflow Long-term mean values and standard years were calculated from available records of observed total inflow from step 2. For each of the selected catchment, seasonal distribution and mean values of total inflow were plotted and compared with seasonal distribution and mean value calculated from unregulated total river flow in C3S SIS water reference data. Snow Mean values of observed snow maximum were calculated from available historical records from step 2. Results per observation point were plotted in maps of mean snow water equivalent in reference period, given in the C3S SIS water ensemble. Results Unregulated river flow Figure 7 gives long-term mean of unregulated river flow from C3S SIS water reference data relative to long-term mean of observations. Figure 8 gives an example from comparisons of seasonal distribution between unregulated river flow from C3S SIS water and observations. The example is from the Porjus catchment. Comparisons have been done for all selected study catchments. Figure 7 Mean of unregulated total river flow from reference period data in SWICCA ensemble relative to mean of observed total inflow. Full Technical Report: Hydropower production in a future climate 11

15 Figure 8 Seasonal distribution of observed total inflow and unregulated total river flow from pan-european model. Values for catchment Porjus. Unregulated river flow given as mean of climate models in Swicca reference data. Compared with observations the pan-european model underestimates river flow in Luleälven by nearly 50% (figure 7). As seen in figure 8, the difference is mainly to do with a smaller volume in the spring flow peak from snow melt. An underestimation of snow volume can also be seen from comparison between snow observations and modelled reference values of snow from the pan- European model, although observations are too few to evaluate further and draw conclusions. Step 4: Basis for future hydro power operation Changes in unregulated river flow and snow storage Results indicate that unregulated river flow in Luleälven River will increase in coming decades. Changes in long-term mean values for studied catchments are in the interval 3-31% at the end of the century. The flow pattern is also changed as a consequence of higher temperature and more precipitation in winter. Graphs of future seasonal distribution for studied catchments point towards higher flow in autumn, winter and beginning of spring, and lower flow during summer. The changes in flow pattern are most clearly seen for the western, mountainous parts of the river where results also indicate a reduction of spring flow peak in the future. Together with higher flow during winter this indicates a more evenly distribution of flow in the future compared to the reference period. The temporal distribution of water is also affected by a shift of snow maximum to earlier in spring, leading to earlier flow peak from snow melt. The shift of spring flow peak in time is seen for all study catchments. All changes are relative reference period Changes seen in results of future snow maximum are in line with those seen for unregulated river flow. Results maps indicate that snow maximum volumes are reduced in almost all parts of the river and that snow maximum will occur earlier in winter, corresponding with earlier spring peak flow seen in graphs of future seasonal distribution. The largest decrease in snow maximum is seen in the Full Technical Report: Hydropower production in a future climate 12

16 upstream, mountainous parts of the river, the same parts where the reduction of spring flow peak is most clearly seen. An exception to decreasing snow maximum can be seen for sub-basins in the Tjaktjajaure catchment where snow maximum is instead increasing. This might be due to lower temperatures in these parts of the river that causes a greater part of the increasing winter precipitation to be stored as snow, compared with surrounding areas. The shift towards earlier snow maximum is seen for all parts of the river. Changes given by RCP85 are around 0,5-1,3 months at the end of the century. Consequence for hydropower For Vattenfall as hydropower producer operating in Luleälven River, these changes in volumes and temporal distribution of water would likely require a different seasonal regulation than today. It might, for example, reduce the need to store large volumes of meltwater for cold winter months. Maintenance work and routines related to dam safety are other parts that might be affected by changing volumes and flow pattern in the river. Further studies are needed to get a more complete picture of the consequences for future hydropower in Luleälven. This would probably include new model simulations. The differences seen between observations and model results in reference data may be reduced by additional model calibration of the E-HYPE model. Using a HYPE model set up for Sweden to run the hydrological climate simulations could also be an alternative, in order to have a model representation better correlated with conditions in northern Sweden. To fully evaluate the potential for future hydropower production, changes related to other components of the energy sector, e.g. wind and solar energy, must also be considered. Step 5: Evaluation, long term Results from this case study shows the importance of considering climate change in decisions related to future operation of Luleälven River. A more detailed evaluation of long term consequences, as well as the possibility to use results to adjust historical records, will require additional studies, where methods developed in this study may be applied. Apart from water availability, there are many other factors important for hydropower production that may change in the future. Energy price, transfer capacities, amount of wind and solar energy are some examples. The role of hydropower and the regulation of the river system are dependent on all of these factors and it is therefore difficult to say, just from looking at changes in volume and temporal distribution of water, what the possibilities for hydropower will be in the future. Vattenfall is also interested in the possibility to use seasonal forecasts to get scenarios needed for long-term production planning. Ensemble scenarios from a seasonal forecast of 1-6 months could be an alternative to the scenarios based on historical records that are used today. For hydropower planning in Luleälven and other rivers in the northern parts of Sweden and Norway, main interest is to have good seasonal forecasts covering the snow melt season in spring and summer. One advantage of using seasonal forecast instead of scenarios from historical records is the connection to present weather situation close to the start Full Technical Report: Hydropower production in a future climate 13

17 of the snow melt season. So far though, the trust in the skill of seasonal forecasts has not been big enough for Vattenfall to fully rely on seasonal forecast in their long-term production planning. Historical records are therefore still an important part of long-term planning, thereby also the need to adjust historical data for better correlation with climate changes. Full Technical Report: Hydropower production in a future climate 14

18 Conclusion of Full Technical Report The objective of this case study was to identify and test methods for calculating indicators useful for hydropower, based on pan-european hydrological climate data. Two indicators have been identified and results have been calculated and evaluated for catchments in Luleälven River. Results indicate that a future climate change would have an impact on both volume and seasonal distribution of water in Luleälven River. For catchments studied, indicators point towards higher river flow in the future compared to the reference period. The increase in river flow is seen in autumn, winter and beginning of spring, followed by a decrease to lower flow during summer. Results also shows the effect from a shift in timing of snow maximum to earlier in spring, leading to an earlier flow peak from snow melt. Definition of indicators and methods to calculate results that have been used in this study can be applied in similar studies for other rivers. For Luleälven River, comparisons between reference data from the pan-european hydrological model and observations show large differences in volume. Further studies, including new model calibration and simulation, are therefore necessary in order to have indicators useful for a more detailed evaluation of the potential for future hydropower in Luleälven. A more complete evaluation would also need to include changes related to other components of the energy sector, e.g. wind and solar energy. Full Technical Report: Hydropower production in a future climate 15

19 References SWICCA Meta data PDF Metadata_RiverFlowUnreg_catchment.pdf Metadata_SnowWaterEquivalent_catchment.pdf IHMS, Integrated Hydrological Modelling System Manual Version 6.4 B. Johansson, 2014 Full Technical Report: Hydropower production in a future climate 16