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Climate Impact on Floods – Changes of High-Flows in Sweden for the Past and Future (1911–2100)

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Climate Impact on Floods – Changes of High-Flows in Sweden for the Past and Future (1911–2100) Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Hydrol. Earth Syst. Sci. Discuss., 11, 7551–7584, 2014 www.hydrol-earth-syst-sci-discuss.net/11/7551/2014/ doi:10.5194/hessd-11-7551-2014 © Author(s) 2014. CC Attribution 3.0 License. This discussion paper is/has been under review for the journal Hydrology and Earth System Sciences (HESS). Please refer to the corresponding final paper in HESS if available. Climate impact on floods – changes of high-flows in Sweden for the past and future (1911–2100) B. Arheimer and G. Lindström Swedish Meteorological and Hydrological Institute, 601 76 Norrköping, Sweden Received: 3 June 2014 – Accepted: 20 June 2014 – Published: 4 July 2014 Correspondence to: B. Arheimer ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. 7551 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract There is an on-going discussion whether floods are more frequent nowadays than in the past and whether they will increase in a future climate. To explore this for Sweden we merged observed time-series from 69 sites across the country (450 000 km2) for 5 the past century with high-resolution dynamic scenario modeling of the up-coming century. The results show that the changes of daily annual high flows in Sweden oscillate between decades, but there is no significant trend for the past 100 years. A small tendency for high flows to decrease by 0.3–0.4 % per decade in magnitude and 10-year flood frequency was noted, but not statistically significant. Temperature 10 was found to be the strongest climate driver for river high-flows, as these are mainly related to snow melt in Sweden. Also in the future there will be oscillations between decades, but these were difficult to estimate as climate projections were not in phase with observations. However, in the long term, the daily annual high-flows may decrease by on average 1 % per decade, mainly due to lower peaks from snow melt in the spring 15 (–2 % per decade) caused by higher temperatures and shorter snow season. On the contrary, autumn flows may increase by 3 % per decade due to more intensive rainfall. This indicates a shift in flood generating processes in the future, with more influence of rain generated floods. This should be considered in reference data for design variables when adapting to climate change. Uncertainties related to the study are discussed in 20 the paper, both for observed data and for the complex model chain of climate impact assessments in hydrology. 1 Introduction Numerous severe floods have been reported globally in recent years and there is a growing concern that flooding will become more frequent and extreme as an effect 25 of climate change. Generally, a warmer atmosphere can hold more water vapor and, in effect, there is a growing potential for intense precipitation that may cause floods 7552 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (Huntington, 2006). Some scientists have argued that the observed changes in climate (e.g. observed increase in precipitation intensity) already have an impact on river floods (e.g. Kundzewicz et al., 2007, 2008; Bates et al., 2008). However, detection of changes in floods is associated with methodological problems and large uncertainties arise 5 when exploring trends in both past and future high flows. Changes of the river flood regime are traditionally analyzed either through statistical approaches using observed data (e.g. Lindström and Alexandersson, 2004; Stahl et al., 2010; Schmocker-Fackel and Naef, 2010), or through process-based numerical modeling using the scenario approach (e.g. Dankers and Feyen, 2008; Arheimer et 10 al., 2012; Bergström et al., 2012). Both these methods include potentials and many challenges, as discussed by Hall et al. (2013). To sum-up, the fundamental problems with climate impact assessments is that: (1) observed time-series may include natural long-term cycles, which may be induced by climatic oscillations or persistent memory of hydrological processes (Markonis and Koutsoyiannis, 2013; Montanari, 2012). This 15 will influence all statistical trend analysis and make them very sensitive to the period chosen for the study; (2) global climate models (GCMs) do not correspond to the observed climatology (Murphy et al., 2007) and uncertainties arise in each step of the model chain in hydrological impact assessments (Bosshard et al., 2013; Donnelly et al., 2014). As a response to the difficulties and uncertainties involved, much scientific 20 efforts during the last decade have been put on compensating for these two major problems to find methods for more robust trend analysis and scenario-model results (see full review in Hall et al., 2013). Most of the published works relate changes in climate to mean annual flow, while impact studies on high flows are rare and specific drivers are usually not 25 examined. One way to understand the change of flood generating processes is the analysis of seasonality. Some of the main driving processes such as synoptic precipitation, convective precipitation, and snowmelt events are highly seasonal. The flood occurrence within the year may therefore give clues on the flood producing drivers and their changes (e.g. Parajka et al., 2009; Petrow and Merz, 2009). 7553 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Hall et al. (2013) argue that future work should aim to draw upon, extend, and combine the strength of both the flow record analysis and the scenario approach. The present study is in line with this idea to merge analysis of long time-series of the past with dynamic scenario modeling of the future. Moreover, climate change detection 5 should be based on good quality data from observation networks of rivers with near- natural conditions (e.g. Lindström and Bergström, 2004; Hannah et al., 2010) and time- series of more than 50–60 years are recommended to account for natural variability (Yue et al., 2012, Chen and Grasby, 2009). In this study, we therefore used 69 unregulated rivers with gauged time-series 10 for 100 years (1911–2010) to examine recorded changes in flood frequency and magnitude. The modeling of the future was performed according to the typical impact modelling chain: “emission scenario–global climate model–regional downscaling– bias correction–hydrological model–flood frequency analysis”, using the national hydrological-model system S-HYPE for Sweden with observed climatology, and for two 15 climate model projections of 100 years (2000–2100). An overlapping period of 50 years was used to check the agreement between observed and modelled trends in high flows. The following scientific questions are being addressed in this paper: 1. What changes in daily annual high-flows have we experienced in Sweden during the last century, and which future changes can we expect for the next hundred 20 years? 2. Which climate drivers can be attributed to such changes? 3. How will flood regime and dominating flood-generation processes change in the future? 7554 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 Data and Methods 2.1 Landscape characterization and observed high-flows of the past Sweden is situated in Northern Europe and has a surface area of about 450 000 km2. About 65 % is covered by forest, but there are significant agricultural areas in the south 5 of the country. Sweden is bordered by mountains to the west and a long coastline to the south and east, meaning that the country is drained by a large number of rivers which start in the west and run eastwards to the Baltic Sea and southwest to the North Atlantic Sea. Most of the rivers are regulated as some 50 % of the Swedish electricity consumption originates from hydropower. To search for general tendencies 10 in flood change, results from analyses of long-term records and scenario modelling was aggregated to four regions in Sweden (Fig. 1) defined by Lindström and Alexandersson (2004). The river basins in these regions have similarities in climate and morphology but also represent the Swedish catchments of the marine basins. 69 gauges with long records and no, or very little, up-stream regulation in the catchment, were chosen from 15 the national water archive to represent the four regions (Fig. 1). 2.2 Model approach of the past and the future Water discharge and hydrometeorological time-series of the past and the future was extracted from a national multi-basin model system for Sweden, called “S-HYPE”. The model system covers more than 450 000 km2 and produces daily values of hydrological 20 variables in 37 000 catchments from 1961 and onwards. It is based on the processed- based and semi-distributed HYdrological Predictions for the Environment (HYPE) code (Lindström et al., 2010). The S-HYPE application (Strömqvist et al., 2012; Arheimer and Lindström, 2013) covers the Swedish landmass including transboundary river basins. The first national model-system was launched in 2008, but S-HYPE is continuously 25 improved and released in new versions every second year. Observations are available in 400 sites for model evaluation of daily water discharge. The present study on 7555 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | changes in flood magnitude and frequency was made using the S-HYPE version from 2010. The S-HYPE model was forced with daily precipitation and temperature, using national grids of 4 km based on observations and climate model results, respectively. 5 The grid based on observations is produced daily by optimal interpolation of data from some 800 meteorological stations considering variables such as altitude, wind speed and direction, and slopes (Johansson, 2002). For this study on floods, gridded values were transformed to each subbasin for the period 1961–2010 to force the S-HYPE model.
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