Independent Project at the Department of Earth Sciences Självständigt arbete vid Institutionen för geovetenskaper

2017: 26

A Historical Analysis of Hydrological Drought in Sweden

En historisk analys av hydrologisk torka i Sverige

Jesper Larsson

DEPARTMENT OF EARTH SCIENCES

I N S T I T U T I O N E N F Ö R

G E O V E T E N S K A P E R

Independent Project at the Department of Earth Sciences Självständigt arbete vid Institutionen för geovetenskaper

2017: 26

A Historical Analysis of Hydrological Drought in Sweden

En historisk analys av hydrologisk torka i Sverige

Jesper Larsson

Copyright © Jesper Larsson Published at Department of Earth Sciences, Uppsala University (www.geo.uu.se), Uppsala, 2017

Sammanfattning En historisk analys av hydrologisk torka i Sverige Jesper Larsson I Sverige finns det en brist på studier angående hydrologisk torka trots att det existerar problem med torka idag. Hydrologisk torka kan ha allvarliga konsekvenser på både naturen och samhället när det kommer till vattentillgång, växt-och djurliv och jordbruk. Av den anledningen är det viktigt att studier görs som undersöker allvarligheten i den hydrologiska torkan i Sverige för att få en bättre förståelse. I den här studien användes ett månadsvis Q95 värde som ett tröskelvärde med ett minimum av fem dagar i följd under tröskelvärdet för att definiera hydrologisk torka. Metoden applicerades på fem avrinningsområden in Sverige med data som sträckte sig mellan 1961-2010.

Resultatet från studien visade på att hydrologisk torka var speciellt framträdande under vissa år. Dessa år verkade vara kopplade till varandra under två till tre år i följd. De visade även ofta liknande månader och antal dagar under tröskelvärdet. Andra studier gjorda över de Nordiska länderna visade på liknande resultat. Metoden överensstämde även till en stor del av historisk torka i Sverige. För att kunna ge en större och komplett bild av hydrologisk torka diskuterades några möjliga metoder. Nederbörd, snö, strömflöde, evapotranspiration och grundvatten skulle behöva räknas med för en mer precis studie. Standardiserade index kan täcka de mesta av de olika delarna, men för att få mera specifika förlustvärden så skulle även en tröskelnivå metod behöva implementeras i studien. Nyckelord: Hydrologisk torka, tröskelnivå metoden, index. Självständigt arbete i geovetenskap, 1GV029, 15 hp, 2017 Handledare: Thomas Grabs och Claudia Teutschbein Institutionen för geovetenskaper, Uppsala universitet, Villavägen 16, 752 36 Uppsala (www.geo.uu.se) Hela publikationen finns tillgänglig på www.diva-portal.org

Abstract A Historical Analysis of Hydrological Drought in Sweden Jesper Larsson In Sweden there is a lack of studies on the topic of hydrological drought even though it exist present problems of drought. Hydrological drought can have severe effects on both nature and society regarding water supply, animal life and agriculture. It is important to investigate the severity of hydrological drought in Sweden to get a better understanding of this phenomenon and its affects. To define hydrological drought this study used a Q95 monthly threshold with a minimum of 5 consecutive days below the threshold. This method was used on five catchments in Sweden with data ranging from 1961-2010.

The result from the study showed that hydrological drought was very prominent in some years. These years seemed to be often linked together in two to three consecutive years. They often had similar amount of days and months below the threshold. Other studies over the Nordic countries showed similar results. The method also gave a result that to a certain degree showed droughts that coincided with historical records of drought in Sweden. This gave a positive feedback of the index accuracy. To get a broader picture of how hydrological drought propagates in Sweden some possible choices were discussed. Precipitation, snow, streamflow, evapotranspiration and groundwater would need to be covered for a more precise study. Standardized indices have most of spectrum covered, but it would be suggested to implement the threshold level method as well to get accurate deficits. Key words: Hydrological drought, threshold level method, drought indices. Independent Project in Earth Science, 1GV029, 15 credits, 2017 Supervisors: Thomas Grabs and Claudia Teutschbein Department of Earth Sciences, Uppsala University, Villavägen 16, SE-752 36 Uppsala (www.geo.uu.se) The whole document is available at www.diva-portal.org

Table of Contents Introduction…………………………………………………………………………….1 Method………………………………………………………………………………….3 Result…………………………………………………………………………………...4 Discussion……………………………………………………………………………...8 Conclusion……………………………………………………………………………..11 Acknowledgments…………………………………………………………………. …11 References……………………………………………………………………………..11 Appendix………………………………………………………………………………..14

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Introduction There are several different kinds of drought, metrological, agricultural, hydrological, and atmospheric (Smakthin, 2001). They all have different methods for studying and consequences. Drought studies in Europe have shown an increase in severity, duration and frequency of drought throughout the past decades (European commission, 2007). This has led to an increase of awareness of this problem. The European drought observatory was founded by the European commission and their joint research center. They have made complex indexes for evaluating drought in Europe, which have showed this increasing trend (European commission, 2007).

In a recent article, the Swedish agency for marine and water management (2017) warned about a decreasing flow in catchments around Sweden. They warned about a shortage of drinking water in the summer of 2017 and urged people to save as much water as possible. The reason behind the shortage is low precipitation over the last two years, especially during winter months. Already in 2016 Sweden experienced its driest year in the past 40 years, and with the same amount of precipitation as the summer of 2016, Sweden might experience the driest year for the past 100 years of record in 2017. This shows that the problem is very present, but the knowledge is very limited. That is the reason why studies on the subject are very important for the future of Sweden.

In this study historical records of hydrological drought in Sweden are examined. Hydrological drought is defined by lowered levels of groundwater, discharge and lake storage (Smakthin, 2001). There is not an objective consensus about how drought should be defined, but Tallaksen and van Lanens (2004) description defines drought as consistent and extensive deviation of natural water availability to less than normal. Hydrological drought can have many negative effects on both nature and society. It has a slower process than other types of drought, like a meteorological for example, which means that the effects will happen slowly but last longer. Hydrological drought can lead to consequences for water supply, water quality, agriculture and electricity production, which lead to both economic and ecologic loss (Van loon, 2015). It is important to note that drought is relative to its perspective, so one important question is what normal conditions are (Van Loon, 2015). One water level might be required for animal life to function, while another level is required to have a sustainable water supply.

To characterize hydrological drought low flow statistics are often used. There are several ways to define low flows. For example, it can be seasonal low flows during winter or summer or deficits on regular basis. Low flows are generally flows below the median flow of a river. Different low flows can be used to investigate different ecosystem functions of a river and can be used to indicate when a river is in a drought situation. Often parameters of minimum days of low flow are put in place to get rid of smaller drought events.

To be able to characterize hydrological drought and understand the hydrology in catchment areas many indices have been developed (Van Loon, 2015). Indices are used for finding out about the duration, magnitude and severity of a drought. Many so-called complex indices also exist that demand a lot of different data. All indices are focused on different aspects of drought so several must be put in place together to get a full picture.

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Complex drought indices can account for snow, precipitation, evapotranspiration, soil moisture and streamflow, such as, SWSI (Surface water supply index) and PDSI (Palmer’s drought severity index) (Hisdal et al, 2004). The information needed for these indices are often not available at large scale (Stahl et al, 2015). PDSI would not be suitable for a climate like Sweden, it was developed for USA and mostly targets semi-arid regions. PDSI does not account for snow which has an important role in Sweden. SWSI, on the other hand, takes snowpack into account combined with precipitation, reservoir storage and streamflow (Fleig et al, 2006). There are also standardized indices like meteorological indicators that could be used to investigate hydrological drought. SPI (Standard precipitation index) and SPEI (Standard precipitation and evapotranspiration index) are two indexes used by the European commission’s joint research center (Spinoni et al, 2015). SPI is one of the most used metrological indices and uses standardization to show anomalies which makes a regional comparison possible. It uses a distribution probability of the record of precipitation which is then normalized to a normal distribution (Van Loon, 2015). SPI can be calculated for different time-scales and with a larger timescale (6-24 months) it could be used to analyze hydrological drought (WMO, 2012). The problem with SPI is in its simplicity, it only accounts for precipitation. It could be hard to correlate the precipitation with the streamflow since the effect of low precipitation is not consistent with the response of the runoff (Fleig et al, 2006). SPI also lacks the ability to account for snow in a satisfying way for drought management. Like all standardized indices, it does not show a specific deficit, it shows drought in relative terms from the normal. (Van Loon, 2015). To account for snow melt and other factors different standardized indices have been developed that uses a similar method for calculating as SPI. Standardized snow melt and rain index (Staudinger, Stahl & Seibert, 2014), standardized soil-moisture anomalies (Orlowsky & Seneviratne, 2013) and standardized groundwater level index (Bloomfield & Marchant, 2013) are all indexes that use different factors to evaluate drought through a standardized way. The use of streamflow is common when investigating hydrological drought and many indices have been developed for that purpose. Standardized streamflow index is another standardized index that uses either observable or simulated streamflow (Vicente-Serrano et al, 2012).

Apart from the standardized indices it exists another group of indices commonly called threshold level methods. They use fixed or moving thresholds that to identify at what flow a river is considered to be in a drought and they can show duration, severity and frequency quite easily. There are many different threshold values one could choose depending on the purpose of the study. Commonly thresholds are taken from flow duration curves. Monthly or seasonal flow percentiles ranging from 70-95 % are usually used. (Van Loon, 2015) Calculating frequency and return period of mean annual minimum n-discharge are a common index. It uses the mean minimum flow of a certain amount of days (n) ranging from 1-30 for every year of record. In USA this index is used to calculate 10 year 7 days minimum flow, the lowest flow of 7 consecutive days for with a return year of 10 years. It is the most used low flow index throughout USA. (Fleig, 2006).

The purpose of this study is to investigate the severity of hydrological drought in a historical context by using an index of a Q95 threshold.

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The questions intended to be answered in this study are (a) how does hydrological drought propagate in Sweden, (b) is the Q95 index appropriate and what improvements could be made? This was done by investigating the flow in five catchments in Sweden with data up to 2010. Severity in this study is quantified by the duration of the drought and not its deficit in flow. The catchments are located throughout entire Sweden from the north to the south. In Table 1 some facts about the streams that were used in the study are shown. Table 1. Information about study catchments

Storbäck Ljusnan Norrström Emån Rönne Å

Station number 2234 1223 2244 1622 2128 Province Västerbotten Härjedalen Uppsala Jönköping Skåne

Station Name OSTVIK TÄNNDALEN VATTHOLMA2 BRUSAFORS HEÅKRA Start year 1980 1961 1980 1961 1974

Catchment Area (km2) 150,5 226,6 293,8 240,4 146,8

Method To find suitable indices for investigating hydrological drought certain choices have to be made. In this study the threshold level method was used, where a threshold dictates when the flow is low enough to be considered to be in a drought situation. There are several different ways to define a threshold. One common method is the use of frequencies obtained from a flow duration curve. The flow duration curve shows the percentage of time a river’s flow is exceeded. One could choose different percentiles as a threshold for investigating different characteristics of a river. The Q50 (50% exceedance) corresponds to the median, but to identify more severe low flows a lower threshold needs to be used (Hisdal et al, 2004). To investigate a general picture of hydrological drought and its trends a threshold value of Q95 was used in this study (Van Loon, 2015). With a Q95 threshold the flows that are exceeded 95% of the time can be identified. The reason behind this choice is that it is possible to depict the more extreme low flows which seem reasonable to avoid potential misunderstanding of the term drought.

The exceedance probability for the flow duration curves was calculated with Weibull’s formula; P = M / (n+1) (1) P stands for exceedance probability, M for the rank and n for the total number of days. Weibull’s formula was used after the data was ranked from the highest to lowest flow and an exceedance probability of exceedance was made for every day.

Seasons can affect flow distribution, especially in countries like Sweden, where precipitation can be stored as snow and temperatures. There are different ways to account for seasons by dividing the Q95 by water year, using a moving mean or a monthly Q value. The difference between a moving mean and a monthly Q value are in their response to change in time. The moving mean is often calculated through 30 days, every day will be the mean of the previously and upcoming 15 days.

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That makes it hard to distinguish between dry and wet years because the threshold is solely dependent on each year, but it accounts for the possible change of flow from the first to last day of a month. This study adopted a monthly threshold instead where the threshold is dependent on the Q95 for a month throughout the entire data set. Every month of the year will have a corresponding Q95 for the entire record of data. This means that every catchment had 12 fixed Q95 thresholds, where for example all of the days in the January months were computed to the corresponding fixed January Q95 that represent the entire data record. This makes it possible to identify which years and months that have the most days below the threshold. Weibull’s formula was used on each month for all the years of data for all the catchments separately to construct the monthly threshold.

The next step for identifying hydrological drought was to select a minimum of consecutive days below the monthly thresholds for a period to be considerate a drought. This is useful to discard very short periods of days under the threshold that would not be considered as a drought (Hisdal et al, 2004). This study used a minimum of five consecutive days of flow beneath the monthly Q95 threshold as suggested by Tallaksen, Madsen & Clausen (1997), but there are many different suggestions regarding the minimum ranging from 3-10 days (Vogt and Salamon, 2015).

The periods classified as hydrological drought were manually extracted for five catchments (Table 1) located throughout entire Sweden. Results In studying hydrological drought many factors can be interesting and telling for the result. The five catchments as seen in table 2, had high maximum flows while the minimum does not show the same distance from the mean. Ljusnan was the catchment with the largest variability and Norrström was the one with the least. Another aspect worth noting is the difference between the mean and median (Table 2). There was a higher variation in the mean between the catchments than the median. This is probably caused by the high maximum values. All catchments were actually quite similar regarding their median flow, with a range of 0,37-0,82 mm. Table 2. Flow statistics for all the catchments

Rönne Å Emån Storbäck Ljusnan Norrström

Mean 1,138 0,633 0,909 1,918 0,595 Median 0,509 0,410 0,370 0,824 0,379

Max 14,420 6,325 15,098 34,697 3,999 Min 0,005 0,017 0,059 0,084 0,018 Q5 4,285 1,887 3,760 8,007 1,832

Q95 0,032 0,086 0,130 0,210 0,044 In the flow duration curves (Figure 2) it was possible to get a better picture of the high- and low flow characteristics. Until Q20 the catchments deviated from each other considerably, but moving down the section and already at Q30 the catchments started to show a more similar progression and flows. Here again Ljusnan stood out as the one catchment with highest flow regarding both sides of the median.

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Figure 1. Flow duration curves showing the exceedance probability (%) for the entire years of data for all the catchments. The investigation of the monthly Q95 thresholds showed a considerable variation regarding the month with the highest Q95 value. Norrström, Rönne Å and Emån had their lowest Q95 values during the summer months of June, July and August, they also had a similar pattern throughout the entire year. In contrary Ljusnan had its highest Q95 value during June and Storbäcken had its peak during May. In the first three months of the year all of the catchments showed a similar progression and flow around 0.2 millimeters. Towards the end of the year they again returned to similar Q95s. The months with the highest variability between the catchments are during the late spring to late autumn.

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Figure 2. Monthly Q95 for all the catchments. The result of the drought analysis showed a large variability between years and duration of drought. The results of the method are shown in Figure 4, which illustrates when in time drought events occurred and in the appendix more detailed tables for all the catchments are shown.

Looking at hydrological drought and its severity, Rönne Å (Table A1) had 24 days under the threshold in November 1975, March 1987 and July 2006, also 25 days under the threshold in February 2010. These are Rönne Å’s months with the most days under the threshold. The most pronounced years of drought were all located during the 2000s. The two years with the most days under the threshold were 2010, with 72 days of drought and 2009, with 65 days of drought. 2003, 2006 and 2008 was the years with most days after that with 32 or more days under the threshold. Under the 2000s there were 274 days under the threshold compared to 193 days for the entire rest of the years.

Norrström’s (Table A2) most pronounced months of drought were during January, Feburary and March in 1996, and October 2007 where the entire months were below the threshold. Four years in particular showed higher number of days below the threshold. 2007 had a period from May to November with 125 days of drought, where August (29) and October (31) had the longest duration. The three other years were 1996, 1989 and 1993, with 114, 96 and respectively 60 days below the threshold. In 1996 three consecutive months were under the threshold from January to March, and 23 days in April. 1989 had a period from July to October and December below the threshold, September had 28 days below the threshold which was the highest amount of days. 1993 had five months from March to July, with 18 days in May being the most days below the threshold for that period.

Emån (Table A3) had more varied periods under the threshold than the previously mentioned catchments. 1992 and 1970 had the most days below the threshold, 1992 had 106 days over a period from June to October and 1970 had 84 days from Janaury to April. Other pronounced years were 1963, 1987, 1989 and 1990, they had between 35-59 days below the threshold. Droughts in1963 and 1987 were concentrated on three first months of the year and in 1989 and 1990 they were concentrated from April to June.

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Storbäck’s (Table A4) most severe years were during 1983, 1996 and 2002. There was not a consecutive period of months in 1983, five months was spread out between February to September, but it had the most days below the threshold at 78 days. In 1996 the months of February to March had 62 days below the threshold. In 2002 three months with 72 days were under the threshold. Also 1984 and 2006 had several months with drought. 1984 had five consecutive months in which the periods below the threshold ranged from 5 to14 days. The period in 2006 was more concentrated with three months of 57 days.

The three most severe years in Ljusnan (Table A5) were 1968, 1979 and 1980. Six months from July to December in 1968 showed a period below the threshold of in total 110 days. The most severe year was 1979 with a period of 139 days below the threshold in January to May, where the entire months of February and March were below their respective monthly thresholds. In 1980 the same period had days below the threshold except for May and had 106 days below the threshold. Almost the entire months of January, February and March were below the threshold. Other pronounced years were 1994 and 2010 with 71 and 46 days below the threshold.

Figure 3. The charts show the total sum of days below the threshold for every year with a

minimum of five consecutive days below the threshold.

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Discussion Since this is only a historical analysis more work needs to be done to evaluate what kind of future Sweden has. Studies on the effect of precipitation and evaporation could be useful to a more accurate sight in the future. To get a more accurate picture of hydrological drought more indices could be used. Which indices one chooses to use is going to directly affect your result.

One of the problems in the study is the use of a monthly Q95 threshold. It suggests that all flows beneath the threshold are considered as a drought situation and that might not be entirely true. It is important to note that the Q95 threshold merely identifies low flows accounted for catchments regular flow. So the Q95 threshold does not necessarily imply a situation where functions in society and nature are affected. Ljusnan showed a particular high Q95 value for the summer months compared to the other catchments. The reason behind that might be a late snow melt and spring flood.

The result showed more severe droughts in some catchments. Ljungan and Norrström had several years with more than 100 days below the threshold. That is about a third of a year below the threshold. With that many days below the threshold functions like water supply were likely affected. The study also revealed several potential trends regarding hydrological drought, both duration and placement in time. Rönne Å is the only catchment for which there seems to be a trend of increasing amount of days under the Q95 threshold during the period between 1974-2010. It had 274 days under the threshold during 2003-2010 compared to 193 days for the rest of the years. It was a significant amount of days during the 2000s that could have been classified as hydrological drought. In contrary Emån and Ljusnan actually showed a decrease of amount of days under the threshold in the period between 2000-2010. Norrström had a major period of several months in 2007 under the threshold, but a part from that showed no indication of an increase of amount of days. Storbäck had periods under the threshold during the early 2000s, but showed a decline running up to 2010. The reason for Rönne Ås increasing amount of days could be due to many different factors. Rönne Å is located in Skåne, close to the border of Denmark, and is the catchment located most to the south. Different metrological conditions could be one of the reasons why the other catchments did not show the same trend. The river also has three power plants, so the reasons could also be linked to them. This trend of a decreasing amount of days of low flow needs to be reviewed with caution. If a lower Q-value had been used it might have shown a different result. To get a more accurate picture more indices would be needed to actually show if there is an increasing trend in these catchments.

Weather patterns are usually cyclical and precipitation is one of the most important factors contributing to different flows. The late 80s to the mid-90s had very pronounced low flows and it is mostly consistent with all the catchments. In particular 1996s first five months which had periods of Q95 low flows in all the catchments. In the two catchments with data running back to 1961 also showed an increase of low flows around the mid-60s. The result did not show a lot of coherency between the catchments.

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Every catchment seemed to have its own local effects. Sweden is a long country with different climates, but it is still surprising that the result did not show more similarities between the catchments. What all catchments show are that certain years experience significant droughts, with a large part of the year below the threshold. Periods of years with low flows seem to be reoccurring and as the Agency for marine and water management (2017) reported the last two years have been very dry in Sweden. Looking at the severity, most days below the threshold are often grouped together in consecutive months. There are some years with only one month or two that experience days below the threshold, but on many occasions it is just a few days. The most severe periods are usually four or five consecutive months during the same year. These consecutive months also seems to effect the year after. The result showed that two or three consecutive years seem to be connected to each other and often the same months both years showed days below the threshold. That goes in line with the report from the agency for marine and water management (2017) for Sweden’s current situation with two very severe years of drought seen in a historical context.

In a study by Stahl (2001) an extensive investigation about hydrological drought across Europe were made with data ranging from the 1962-1990. The study used a similar threshold index as in this study, but used a moving mean of 28 days and different Q-values, the closest to this study were a Q90. 9 stations, mostly located near the border to Norway, in Sweden were used. The study showed similar results regarding the persistency of drought. All 9 stations got the highest persistent ranking and showed a concentration of drought events rather than spread out across time in short events. The trend analysis showed a positive trend with more days below the threshold running up to 2010 in the south of Sweden and a negative or no trend in the rest of Sweden. Rönne Å, as earlier mentioned located in Skåne, were the only river that showed a prominent positive trend. The study only showed moderate similarities regarding the severity by year. This could be expected since the method between the two studies is different. Although this study showed similarities with the result the data range is problematic. There is a 20 year difference in data, their study only run up to the 1990, which might not give the most accurate comparison. Hisdal et al (2006) did a study on hydrological drought in the Scandinavia during summer months using the threshold level method with a Q70-value to locate droughts. It showed a decrease in hydrological drought by using the Man-Kendall test for 30 year periods running from 1902-2000. The studies seemed to show a similar result. Another way to determine the accuracy of this method is by looking at historical records of dry years in Sweden. SMHI (2003) mention several years that experienced drought, 1976, 1992 and 1994 had very low streamflow and 1976 and 1996 had very little runoff. There are differences between different regions of Sweden where drought could propagate differently and although this paper did not address drought after 2003. Looking at the result from this study it was possible to see that during the early to mid-90s there were concentrations of days below the threshold in most catchments. 1976 was not as visible in the three catchments with data ranging back to 1976, but all three catchments did show some months with days below the threshold.

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Most scientists seem to agree that with the global warming we will have more extreme weather, which would lead to more dry and wet periods. Many studies on the global warming done in Europe seem to agree. Forzieri et al (2014) made a study on the future of drought in Europe and it showed that particularly the winter season would experience a significant rise in temperature, which would affect the evaporation leading to more droughts. Wong et al (2010) predicted a longer duration of hydrological drought in the future in Norway. Hisdal et al (2006) came to similar conclusion where the result predicted an increase of severity, particular in the Southeastern parts of Norway. Since Sweden has a similar climate it could be expected to have a similar future as Norway. This shows that Sweden is in a need for studies on this subject.

The amount of indices available is quite overwhelming, it all depends on the purpose of the study. SPI is a common choice to get an easy overview of drought in an area, but as Vicente-Serrano et al (2012) pointed out SPEI might be a better choice. Although precipitation is the driving factor behind drought, the temperature is on the rise and therefore evapotranspiration is going to play a bigger role. It could be useful to use this meteorological index to get an understanding of the effect precipitation and evapotranspiration has on a catchment and its stream. Hisdal et al (2006) investigated drought and floods for the Nordic countries. The study also showed that precipitation and evaporation during the winter months had a significant effect on summer drought. One of the larger issues of standardized indices is that they result in relative measures of drought severity. A detailed deficit volume is needed in some sectors as water management (Van Loon, 2015). When it comes to complex indices, like SWSI, they are not great at regional studies because catchments cannot be easily compared with each other Fleig et al (2006). The weight of the different factors has to be decided and readjusted in time which makes it difficult to get a homogenous time series and the objectivity is there for affected (Garren, 1993). SWSI could still be a useful tool to test the accuracy of chosen indices in regional study (Fleig et al, 2006). The use of percentiles from flow duration curve as a threshold is a common method and it is useful for its ability to easily determine the severity and duration of drought. It is especially useful for countries like Sweden with a strong winter since it is capable to distinguish between seasonal droughts. However, it has been shown in Fleig (2004) that because this method is sensitive to chosen dates, the result will change significant depending on how the seasons are defined. Another drawback was that without standardization it was more difficult to compare regions with different climates (Van Loon, 2015).

To make a consistent hydrological drought study in Sweden it would be recommended to use several indices to cover the whole spectrum of hydrological drought, precipitation, streamflow, groundwater, snow and reservoir levels (Hayes et al, 2010). The joint research center and the European drought observatory use a combined drought indicator, but it is mostly concentrated on agriculture drought (Sepulcre-Canto et al, 2012). Many standardized indexes have been developed to cover the whole spectrum of drought. A good starting point for future studies could be to combine some of these indices to get a good picture on how drought propagates and its frequency in Sweden. To get a more detailed result that could be more practical in water management the threshold level method could be useful.

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Conclusion Hydrological drought in Sweden seems to occur in the same manner as in countries with similar climate. Two to three years was often linked together and in some cases the same months was also present. The effects of hydrological drought seem to be long lasting. There was a lot of variability between the catchments, but some years tended to be more present in all of the catchments and many of those years were recorded historically as dry years. This study did not find any consistent signs of an increase of the frequency of hydrological droughts which is consistent with the results from other studies of the Scandinavian countries. It did give an understanding of the tendencies of hydrological drought in Sweden and showed the possibilities of this index. This index work well when it came to identifying drought historically and measuring the severity of those events. For a bigger picture and understanding of the wide spectrum of hydrological drought more indices need to be put together to an index. The different methods will allow to account for different characteristics of hydrological droughts. For government applications an index should cover most of the spectrum of precipitation, snow, streamflow and groundwater. SPEI, standardized snow and rain index, streamflow index and groundwater index are some examples of possible indices to cover this spectrum. The threshold level method should be used for more detailed deficits and in depth study. Complex indices would be most useful to verify results in regional studies. For a complete picture, which would be recommended, all three different methods should be considered to get as many dimensions as possible for the understanding of hydrological drought in Sweden. Acknowledgements I would like to thank my supervisors Thomas Grabs and Claudia Teutschbein for the help and guidance in this study. References Bloomfield, J.P & Marchant, B.P. (2013). Analysis of groundwater building on the

standardized precipitation index approach. Hydrological Earth System Science. Vol. 17, pp. 4769-4787.

European Commission (2007). Addressing the challenge of water scarcity and droughts in the European Union, Impact Assessment. Brussels: SEC (2007:993).

Fleig, A., Tallaksen, L & Hisdal, H. (2006). Drought indices suitable to study the linkage to large-scale climate drivers in regions with seasonal frost influence. Proceedings of the fifth FRIEND world conference, Havana, Cuba, November 2006 IAHS publ. 308, 2006.

Forzieri, G., Feyen, L., Rojas, R., Flörke, M., Wimmer, F. & Bianchi, A. (2014). Ensemble projections of future stream droughts in Europe. Hydrology and Earth System Science, vol. 18, pp. 85-108.

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Hayes, M., Svoboda, M., Wall, N. & Widhalm, M. (2010). The Lincoln declaration on drought indices: universal meteorological drought index recommended. Bulletin of the American meteorological society, vol. 92, pp. 485-488.

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Orlowsky, B. & Seneviratne S.I. (2013). Elusive drought: uncertainty in observed trends and short- and long-term CMIP5 projections. Hydrological Earth System Science, vol. 17, pp. 1765-1781.

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Internet resources Havs och Vatten myndigheten. (2017). Vattenbrist hotar stora delar av landet. https://www.havochvatten.se/hav/fiske--fritid/miljopaverkan/vattenbrist/uppmaning-till-beredskap-att-spara-vatten.html [2017-05-15]

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Appendix The full results of the days below the threshold for all five catchments. Table A1: Number of drought days per month in the Rönne Å catchment

Year Jan Feb Mar April May June July Aug Sep Oct Nov Dec 1974

11

1975

24 1976

6 6

1979

7 1983

13

1986

6 1987

24

1989

8

11 1990

8

1992

6 1993

11

1995

13 1996 9 7 6

1997 17 2003

8

11

6 10

2004 2005

7

11 2006

24 8

2007

5

8 2008

12 21 6

2009

15 7

10 19 14 2010 22 25

5

13 7

15

Table A2: Number of drought days per month in the Norrström catchment

Year Jan Feb Mar April May June July Aug Sep Oct Nov Dec 1984 5 1989 19 20 28 7 22 1990 8 9 1991 1992 7 22 6 1993 15 6 18 16 5 1994 5 1995 5 1996 31 29 31 23 1999 27 24 2000 7 2002 13 2003 9 2006 7 2007 10 12 16 29 16 31 11

Table A3: Number of drought days per month in the Emån catchment.

Year Jan Feb Mar April May June July Aug Sep Oct Nov Dec 1962

9

1963 20 9 11 6 1964

12 7

6

1968

13 1969

31

1970 30 28 18 8 1974

12

1975

15 1976

9 6

1980

5 1982

12

9 7

1983

17

7 1987 17 17 25

1989

7 10 10

7

13 1990

14 14 7

1991

19

5 1992

22 31 23 13 17

1993

15 18 1994

13 19

1996

10 7

6 1999

28

2000

11 8 2002

5

2003

7 2006

11

16

Table A4: Number of drought days per month in the Storbäck catchment.

Year Jan Feb Mar April May June July Aug Sep Oct Nov Dec

1980 22 1982

7 8

1983

22 31

9 5

11 1984

5 5 14 6 6

1985

19 1990

14

1992

7 1993

8

1994

7 1995

18 8

1996

12 20 15 15 2002

5

27 30 10

2003

14

21

6 12

2004 26 5 2006

23 28 6

2007

11 2010

22

17

Table A5: Number of drought days per month in the Ljusnan catchment. Year Jan Feb Mar April May June July Aug Sep Oct Nov Dec 1962

5

1966

11 9 9 1967

5

1968

16 16 30 26 12 10 1969

6

1970

8 11 1971

13

1973

6 1976

6

11 12

1977

5 1978

8 7

1979 16 28 31 25 12

12 15 1980 30 29 31 16

1981

5

21 28 1982 31 9

13

1983

8 10 10 1985

6

1986

10 6 6 1994

8 31 22

5 5

1996

10 2000

10

2002

8 12 2004

9

2006

5

17 2007

17

2010

9

13 24