*3.2. Trends in Meteorological and Hydrological Drought Occurrences*

The results of the trend analysis for a series of SPI values (time scales of 1, 3, 6, 9 and 12 months) for individual meteorological stations are presented in Table 6. A statistically insignificant trend was noted at most meteorological stations. Out of eight meteorological stations, a statistically significant upward trend was recorded at only two stations, and a downward trend at one station (the drought intensified). The downward trend in the SPI value for the meteorological station in Kłodawa means that the meteorological drought increases in the period of accumulation of 3–12 months. The Z value obtained for the Kłodawa station was relatively high and ranged from −1.817 to −4.317, and the Theil– Sen slope was between −0.0007 and −0.0018. The test results for the Kłodawa station (Tables 6 and 7) show that the expected Z value is negative for the indices, and the Theil–Sen slope is also always negative.

**Table 6.** Results of trend analysis SPI in different time scales in the period of 1981–2016 at meteorological stations.



**Table 6.** *Cont.*

Description: N—no significant trend, D—significant decreasing trend, I—significant increasing trend.

**Table 7.** Results of trend analysis SRI in different time scales in the period of 1981–2016 at hydrological stations.


Description: N—no significant trend, D—significant decreasing trend, I—significant increasing trend.

The upward trend in the SPI value at the stations in Sompolno and Kołuda Wielka indicates that the phenomenon of meteorological drought is decreasing. The highest Z values, between 3.25 and 5.08, were obtained during the 3-, 6-, 9- and 12-month accumulation periods, while the Theil–Sen slope values were between 0.009 and 0.0019.

In the case of hydrological droughts, a statistically significant downward trend was recorded at the Łysek station in all analysed periods of accumulation. This means a noticeable increase in drought occurrences in the analysed multi-year period of 1981–2016. Z values were negative and ranged from −5.34 to −6.27, while Theil–Sen values were between −0.0013 to −0.0019. An upward trend was recorded at the No´c Kalina station. Z values ranged from 2.21 to 4.07, while the Theil–Sen slope ranged from 0.0008 to 0.0017. In the case of Pako´s´c station, the trend was statistically insignificant. The Z value calculated in the 12-month accumulation period in Pako´s´c approaches the region of a trend acceptance, which might indicate that the trend in Pako´s´c in the longer accumulation period is determined by the occurrence of hydrological droughts at the Łysek station.

Spatial distributions of trends (significant and insignificant) for a series of SPI and SRI values for the 1, 3-, 6-, 9- and 12-month time scales are shown in Figure 3.

#### *3.3. Correlations between SPI and SRI Values*

In order to establish the relationship between meteorological droughts occurring in the catchment area of the Upper Note´c and hydrological droughts, an analysis of the correlation between the SPI and SRI indices was carried out using the Pearson correlation analysis. The results showed that the strongest correlation between SPI and SRI in the analysed period of 1981–2016 was obtained at the 12-month time scale (r = 0.51) (Figure 5). In the case of individual years, the highest correlation indicators between hydrological and meteorological droughts varied depending on the length of the accumulation period. The strength of the relationship between SPI and SRI in the catchment area of the Upper Note´c River was higher for long accumulation periods (6 and 9 months), and lower for the short ones (1 and 3 months). The highest correlation values for the 1-month accumulation period were recorded in 1998 (r = 0.76), while for the 3-month accumulation period the highest values were recorded in 1982 (r = 0.83) and 1996 (r = 0.81). For the 6-month accumulation period, the maximum correlation index was recorded in 1987 (r = 0.94) and in 1982 (r = 0.91). High values were obtained in 1987 for the 9-month accumulation period (r = 0.94) and the 12-month accumulation period (r = 0.90).

#### *3.4. Discussion*

Understanding the changes in the intensity of droughts in the past and being able to predict expected changes over different time scales is incredibly important, as precipitationdriven hydrological processes (e.g., evapotranspiration and surface and groundwater discharge) affect all water reserves [86]. In this study, we found that in the analysed period of 1981–2016, there was a relationship between the occurrence of meteorological and hydrological droughts. The strength of this relationship varied. The analysed multi-year period of 1981–2016 showed a high variability, from dry years (SPI ≤ −1.0) to wet years (SPI ≥ 1.0), which can be concluded from the SPI values in various time scales. The driest years included 1982, 1989, 1992, 2003 and 2015. In these years, meteorological droughts covering not only the region of Poland, but parts of Europe, were recorded. Meteorological droughts which have occurred in Europe since the beginning of the 21st century, and were accompanied by heat waves in 2003, 2006, 2010, 2015, are great examples of such phenomena [87–91].

In the studied area, an increase in the intensity of meteorological droughts (downward trend) was observed at only one out of eight meteorological stations. A statistically significant, clear upward trend in SPI drought was identified at two stations. More distinct trends, but opposite in direction, were observed in the case of hydrological droughts recorded at the stations in Łysek and No´c Kalina. The obtained statistics for the Pako´s´c station, calculated in the 12-month accumulation period, point to the rejection of the null hypothesis on the lack of a statistically significant trend. The same direction of changes in the trend was recorded at the Łysek and Pako´s´c stations. This means an increase in the intensity of hydrological droughts. In the longer accumulation period, the occurrence of hydrological droughts at the Łysek station determines the hydrological droughts at the Pako´s´c station.

The strength of the relationship between meteorological droughts and hydrological droughts shows significant variation. This variation is not only the result of the size of the annual sums of precipitation, but also if an increase in air temperature in the analysed area (Figure 2), which leads to an increase in evapotranspiration [92]. Anthropogenic activities related to the operation of a lignite open pit have a significant impact on the analysed area. Some of the water from the mine drainage was directed to the Note´c River above the No´c Kalina station. The amount of water varied in individual years and depended on the location of the exploitation operations. According to Wachowiak [93], in the period of 1995–2009 the Upper Note´c was flooded with some of the mine water from the drainage of the Lubstów open pit. Since 2009, there have been cases of mine water discharge from the Tomisławice open pit via the Pichna River. The correlations between meteorological and hydrological droughts were variable, in some years the strength of the relationship was high (positive correlation), while in other years the relationship was low (negative correlation).

**Figure 5.** Correlation coefficient r between average SPI and SRI in Pako´s´c for different periods of accumulation in the period of 1981–2016 (*n*—number of accumulated months).

The Pearson correlation analysis shows that there is a relationship between meteorological and hydrological droughts in the study area. However, it should be emphasized that these results should not be directly interpreted. In the correlation analysis, a nonlinear relationship can be inadequately described or undetected [94]. Non-linear models (polynomial, exponential and logarithmic) for the relationship between meteorological and hydrological droughts were analysed in the research conducted by Salimi et al. [95].

The research on the correlation between droughts conducted by Tokarczyk and Szali ´nska [44] for catchments with large areas showed that the largest correlations between SPI and SRI occurred for longer periods of accumulation. Similar relationships between meteorological and hydrological droughts were obtained for other catchments in Poland [43]. In the case of the catchment area of the Upper Note´c River, the relationships between meteorological and hydrological conditions are not natural. The flow regime depends on the amount of water discharged in particular periods, and on the retention capacity of lakes, which is particularly noticeable at the Pako´s´c station. The amount of water accumulated in the Pako´s´c reservoir, through which the Note´c flows, is regulated by a water accumulating weir.

#### **4. Conclusions**

The study analysed the trends in meteorological and hydrological drought occurrences in the long-term period of 1981–2016, for the catchment area of the Upper Note´c River. The identification of a meteorological drought was carried out with the use of an SPI, based on monthly precipitation totals from eight meteorological stations. Hydrological drought was determined by means of an SRI for the monthly discharges of the Note´c, which were obtained from three hydrological stations. Non-parametric Mann–Kendall tests and the Sen slope were used to determine trends. The following conclusions might be drawn:


The example of the catchment area of the Upper Note´c River indicates that the management of water resources requires the use of at least several indicators that will allow an assessment of the actual state of water reserves. Using the SPI to detect meteorological droughts can be used as a drought warning system [96]. In some cases, the value of the SRI depends on the way water is managed within the catchment area. The size of the runoff may be disturbed by anthropogenic factors. Effective water resource management strategies require constant monitoring of water reserves, which should be consulted among various stakeholder groups related in particular to industry, and agriculture.

**Author Contributions:** Conceptualization, K.K.-W., A.P. and D.K.; methodology, K.K.-W. and A.P.; software, K.K.-W. and A.P.; validation, K.K.-W. and A.P.; formal analysis, K.K.-W., A.P. and D.K.; resources, K.K.-W. and A.P.; data curation, K.K.-W. and A.P.; writing—original draft preparation, K.K.-W.; writing—review and editing, K.K.-W., A.P. and D.K.; visualization, A.P.; supervision, K.K.-W., A.P. and D.K.; project administration, K.K.-W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

