Introduction

Climatic characterization is indispensable to define and analyze regional climates, mainly for urban, forest development. Conceptually, climate consists of mean atmospheric conditions within a minimum period of 30 years. Some researchers pointed out that climate is defined by climate classification systems, which are efficient methods to determine the climate classes of a given region (Alley 1984; Ajibola 2001; Cetin 2016; Jedd et al. 2018; Cetin 2015; Portmann et al. 2009; Rolland 2003; Cetin 2019; Sewell et al. 1968; Tacoral et al. 2017; Cetin 2020; Thompson 1992; Willmott and Feddema 1992; Yang 2002; Zeren Cetin and Sevik 2020; Willmott et al. 1985).

Forest is an economic activity greatly affected by weather conditions, as weather elements vary both geographically and seasonally, and can promote high damage to forests ecosystems. Plants need available soil water to complete their entire phonological cycle and have high productivity, and the evaluation of water availability for plants is essential for forest planning. An efficient way to quantify the available soil water is by using the climatological water balance; climatological water balance is a tool for accounting for the entry and exit of water in the soil in a given period (Almorox et al. 2015; Cetin 2015; Basile and Corbin 1969; Cetin 2019; Guilbert et al. 2014; Leao 2017; Mintz and Serafini 1992; Cetin 2016; Oke 1989; Parker 1982; Cetin 2020; Pejman et al. 2009; Portmann et al. 2009; Zeren Cetin and Sevik 2020).

Recently, studies pointed out that climatological water balance might vary according to the time of year due to air temperature and precipitation conditions, being important to make a seasonal and regional evaluation (Almorox et al. 2015; Chung and Kim 2019; Ajibola 2001; Guilbert et al. 2014; Jedd et al. 2018; Kumar et al. 1987; Cetin 2015; Leao 2017; Mintz and Serafini 1992; Oke 1989; Cetin 2019; Parker 1982; Pejman et al. 2009; Cetin 2020; Cetin 2016; Portmann et al. 2009; Rolland 2003; Tacoral et al. 2017; Thompson 1992; Insaf et al. 2013; Willmott and Feddema 1992; Yang 2002; Zeren Cetin and Sevik 2020; Willmott et al. 1985).

There are several methods of estimating climatological water balance in the international literature, but the methodology of Thornthwaite and Mather (1955) is the most used, as it presents a simplified and practical way to obtain soil water storage. Climatological water balance output variables allow the climate classification of several areas. Thornthwaite (1948) climate classification system is considered the most important in studies of forest, ecology, and water resources, precisely because it uses climatological water balance in its methodology. In this classification, the plant is considered the physical medium by which it is possible to carry water from soil to the atmosphere. In addition, Thornthwaite (1948) climate classification is based on humidity indices and thermal efficiency and has climatological water balance as a reference.

In this context, Thornthwaite (1948) climate classification indices are important in the interpretation of climate types of Bartin, simplifying the calculation process and interpretation of climatological water balance by forests. In this sense, we aimed to develop a climatological water balance by the Thornthwaite and Mather (1955) method, as well as the climatic characterization using the indices proposed by Thornthwaite (1948), for Bartin.

Materials and methods

The study was carried out in Bartin, located in the Black sea region Turkey. Bartin has an area of 1027.76 km2, with 15 meteorological stations that were taken the measurements. The coordinates of 41° 38′ 04″ N and 32° 20′15″E. Altitudes of Bartin range from 0 to 2000 m (Figs. 1, 2, 3, and 4). This urban city has stood out in the forest area, surpassing the national average in harvested area. Forest is the predominant activity in the urban city due to the richness of plants and soils and favorable climate conditions. The research used historical series of climate data from 15 metrological stations in Bartin between 1988 and 2019, which were divided into measurement regions.

Fig. 1
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Locations of Bartin

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Fig. 2
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Slope analysis of Bartin

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Fig. 3
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Altitudes of Bartin north to south

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Fig. 4
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Altitudes of Bartin east to west

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Air temperature (°C) and precipitation (mm) were collected on a daily scale from metrological stations. The collected data were used to estimate potential evapotranspiration with Eq. 1. The criterion for choosing this model was the data availability.

$$ E=0.01\ x\ \left(\frac{Q_o}{2.45}\right)x\ {T}_a\ x\ \mathrm{ND} $$
(1)

where E estimate potential evapotranspiration, Qo is the solar irradiance at the top of atmosphere, Ta is the mean air temperature, and ND is the number of days.

The water balance proposed by Thornthwaite and Mather (1955) was calculated with an available water capacity in the soil equal to 100 mm. Soil water storage, water deficit, and water surplus of the soil–plant–atmosphere system were estimated. Box-plots with the mean, median, and outlier points were prepared for the distribution and variation in weather elements. These analyses are essential to understand the climate within each microregion in Bartin and enable the comparison between regions. The aridity indices proposed by Thornthwaite (1948) were used to characterize the studied locations as wet and dry. The calculations of aridity, water, and humidity indices were processed according to Eqs. 2 to 4.

$$ {I}_w=\frac{EW}{E}\ x\ 100 $$
(2)
$$ {I}_a=\frac{D}{E}\ x\ 100 $$
(3)
$$ {I}_h={I}_w-0,6\ x\ {I}_a $$
(4)

where Iw is the water index; Ia is the aridity index; Ih is the humidity index; and EW and D are the water surplus and deficit (mm), respectively, both from the climatological water balance; and E is the reference or potential evapotranspiration (mm). E is the potential evapotranspiration (mm), D is the water deficit in the soil–plant–atmosphere system (mm), EW is the water surplus of the soil–plant–atmosphere system (mm). The climate indices calculated for Bartin allowed generating maps using the kriging interpolation method, with the spherical model, one neighbor, and a 0.25° (25 km) resolution.

Results and discussion

Air temperature in Bartin presented a pattern in the monthly variation for microregions. Monthly air temperature values of microregions ranged from 16 to 28 °C, with a mean annual air temperature of 23 °C. The high air temperatures in the urban city occurred from January to April and November to December, with a mean of 25 °C. However, air temperature decreased from May to July, with a mean of 18 °C. The microregions of Bartin of west and south stood out among the localities with the highest and lowest air temperatures, respectively, with annual means of 26 and 22 °C (Figs. 5 and 6).

Fig. 5
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Annually air temperature values

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Fig. 6
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Monthly air temperature values

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The accumulated mean annual precipitation of Bartin was 1268 mm. Precipitation concentration and distribution in the city were uneven. The lowest precipitation values were observed from June to September. However, precipitations increased from January to May and October to December. Microregion, located in the south of the urban city, showed the highest annual precipitation, with a value of 1361 mm. These variations in air temperature and precipitation over the year may affect the development and productivity of forests in Bartin because, among economic activities, forest is the most vulnerable to climate variability.

Microregions showed different patterns in the water balance components and humidity index, as shown in Fig. 7. The annual potential evapotranspiration of Bartin was 1005.41 mm (± 51.10 mm). Bartin microregions, both located in the west of the urban city, had the highest annual potential evapotranspiration values.

Fig. 7
figure 7

General Humidity of Bartin

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Ulus, located in the east of Bartin, had values above 997 mm, which is below the mean of the annual potential evapotranspiration in the urban city, in the north, presented the highest annual potential evapotranspiration variation. Microregions located in the northwest presented the highest potential evapotranspiration, as their increase is related to an increase in the radiation balance, adjective effect, air temperature, and decrease in relative humidity.

The water surplus of Bartin showed a mean annual value of 123.7 mm (± 110.93 mm). Bartin had the highest variations in water surplus. Microregions of Bartin, both located in the north, and east showed a normal distribution of water surplus results. The pattern of inter-annual water surplus distribution in the microregions was similar.

Bartin presented water surplus below the mean annual value. Among microregions, Bartin had the highest mean annual water surplus, with a value of 318.06 mm (± 30.9 mm), and Bartin had the lowest water surplus, with a value of 12.04 mm (± 12.50 mm). The measurements of Bartin, including of district of Amasra, Arit, Hasankadi, Kozcagiz, Kurucasile, Ulus, Ulus Cubukeli, and Ulus Ceyupler Koyu (taken measurements point) presented the highest water surplus values, all above 331 mm per year.

However, Bartin had the highest water deficit and variation in results. Amasra and Kurucasile, two districts of the region, presented the highest water deficit values in the urban city. Supplementary irrigation can be a strategy for the stability and productivity of forests in the driest microregions of the urban city, as its use during drought periods minimizes productivity losses.

The humidity index (Ih) presented a mean of 14.83 (± 10.46), as shown in Fig. 8. Bartin showed the lowest Ih, with a value of − 10.78 (± 7.32), and Amasra microregion had the highest Ih, with a value of 29.15 (± 3.54), showing a relationship with water deficit and water surplus in the microregions. The results of Ih from Kurucasile and Amasra showed a normal distribution; it showed no much variation. Arit, Hasankadi, Kozcagiz, Ulus, Ulus Cubukeli, and Ulus Ceyupler Koyu, on the other hand, showed the highest variation.

Fig. 8
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Humanity index of Bartin

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The mean annual water surplus in Bartin was 123.7 mm (± 123.1 mm). A water surplus was observed from January to July and September to December in the urban city. The highest water surplus was observed in January, with a value of 41.6 mm. The water deficit in Bartin was 73.95 mm (± 76.17 mm). The highest water deficit in Bartin was observed from May to November. August was the driest month in the urban city, with 14 mm of water deficit.

Amasra, Ulus, and microregion presented a mean annual water surplus of 79.53 mm (± 14.2 mm) and a mean annual water deficit of 130.3 mm (± 27.7 mm). Bartin presented the highest water surplus among the localities of the Arit, Hasankadi, and Kozcagiz microregions. The measurements of Ulus showed the highest water deficit in the microregion.

Mean annual water surplus and deficit values of 161.5 mm (± 85.5 mm) and 170.7 mm (± 35.6 mm), respectively, were observed in Bartin microregion. The localities of Amasra and Ulus presented the highest values of water surplus in the microregion. The locality of Arit had the highest mean annual water deficit in Ulus microregion.

The mean annual water surplus in Bartin microregion was 12.04 mm (± 12.5 mm), while its mean annual water deficit was 182.77 mm (± 133.1 mm), distributed from February to December. This microregion undergoes more than 9 months of water deficit. Among the localities of this microregion, Ulus presented the highest water surplus, while Kurucasile, Amasra, and Ulus had the same variation in water surplus and deficit.

Bartin microregion presented a mean annual water deficit of 61.45 mm (± 19.76), distributed from July to November, standing out September, which represents 26% of the water deficit (Fig. 9). The locality of Kurucasile had the highest water deficit in the microregion, with a value of 119 mm year−1. Ulus, Amasra, and Kurucasile presented the lowest water deficit values and stood out with the highest water surplus in the microregion.

Fig. 9
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Water deficit

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Bartin microregion had a mean annual water surplus of 293.1 mm (± 17.2 mm) and a mean annual water deficit of 98.4 mm (± 29.3 mm), with the highest concentration from July to October. The localities of Ulus and Amasra showed similar values of water surplus and deficit, as also observed for Kurucasile and Arit. Amasra had the highest water surplus in Ulus microregion, while Kurucasile had the highest mean annual water deficit.

Bartin microregion showed a mean annual water surplus of 308.06 mm (± 39.2 mm) and a mean annual water deficit of 134.2 mm (± 17.4 mm). The locality of Amasra had the highest water deficit. Ulus presented the highest water surplus in this microregion. In addition, this microregion has a high water deficit and surplus simultaneously.

Bartin microregion had a relatively low water deficit compared with other microregions, with a mean annual value of 16.9 mm (± 10.2 mm) concentrated from August to October. The mean annual water surplus of the Arit microregion was 176.37 mm (± 98 mm). The locality of Ulus presented the highest water surplus among localities of this microregion, besides a low water deficit of 2.76 mm. The water surplus index in the region was found in Amasra with a difference between both localities of 179 mm, showing a high variation in water surplus between localities of this microregion. Bartin showed the highest and best-distributed water deficit, with a value of 35.87 mm, differing considerably in relation to other localities.

Bartin microregion has 15 measurements of districts and is the largest in territorial extension, among other microregions. The locality of Amasra had the highest water surplus among localities. This microregion stood out for having high values of water surplus, showing an annual mean of 179.22 mm (± 111.3 mm. Kurucasile had the highest water deficit, while Ulus showed the lowest values; this region had a mean water deficit of 8.21 mm (± 6.34 mm).

Bartin microregion showed a water deficit value of 14.36 mm year−1 (± 16 mm). The measurements of Ulus had the highest water deficit among the regional localities, representing 37% of the sum of the values. This microregion has a mean annual water surplus of 98.7 mm (± 95.73 mm). Among the regional localities, Amasra stood out because its mean annual value exceeded 285 mm, being well distributed from January to June and October to December.

Ulus microregion had a mean annual water surplus of 397.78 mm (± 57.5 mm). The measurements of Amasra stood out for having 54 mm above the regional mean. Ulus and Kurucasile presented the same water surplus. However, Amasra presented the highest water deficit in this microregion.

The mean annual water deficit in Bartin microregion was 91.5 mm (± 28.9 mm), with a water surplus of 197 mm. The highest and lowest mean annual water surplus values were observed in Amasra and Ulus, respectively. Moreover, the highest and lowest water deficit values were found in Kurucasile and Arit, respectively.

Bartin had a high spatial variation in water deficit and surplus. The increase in water surplus occurred from west to east of Bartin, with the highest values of water surplus concentrated in the south and north of the urban city. Amasra microregion, located in the west, had the lowest water surplus values, while the regions of Amasra north and Ulus south showed the highest values.

Precipitation directly influences water balance. Rolland (2003), Yang (2002), Pejman et al. (2009), and Portmann et al. (2009) analyzed spatial and seasonal precipitation variations. They found that precipitation occurs more frequently in northern and southwestern urban city due to influences of continental equatorial air mass from the north and tropical air mass from the east, mainly throughout the south region. In addition, there is the orographic precipitation that occurs in region.

The increase in water deficit in the microregions of Bartin occurred in the south-northwest direction, as shown in the strong negative correlation between latitude and water deficit. The highest water deficit values were observed as latitude decreased. Ulus microregion south showed the lowest water deficit, while Bartin west had the highest water deficit values.

According to the humidity index (Ih), the Bartin city presented three climate types: humid, moist subhumid, and dry subhumid, which is shown Fig. 10, which was already expected due to the sensitivity of the Thornthwaite classification criteria (Thornthwaite 1948; Thornthwaite and Mather 1955; Kumar et al. 1987; Almorox et al. 2015; Leao 2017). The moist subhumid index was more prevalent in the urban city, covering 48.4% of all localities, while dry subhumid had the lowest presence, covering only 7.8% of the urban city. Ulus microregion, located in the west of Bartin, presented the highest water deficit value, being classified as dry subhumid. Microregions with the highest water surplus values, such as Kurucasile and Amasra, were classified as humid.

Fig. 10
figure 10

Climatic comfort region of Bartin

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The measurements of Amasra, located in Bartin, was classified as having the climate type humid. These measurements had mean annual water surplus and deficit values of 595.41 and 123.43 mm, respectively. These indices can be useful in mesoscale or toposcale studies, in which the effects of topography directly interfere with climatic elements and, consequently, planning of regional urban, environmental, and forestry activities.

The knowledge of the regional climate results in sustainable and more profitable systems, in addition to greater forest planning and management. The introduction of smart forest practices, such as the use of weather stations, is interesting to deal with changes in forest climatic zones, which lead to changes in cultivation patterns.

Conclusions

The prevailing climate in the urban city of Bartin is classified as moist subhumid. Bartin has two well-defined periods over the year: a dry and a rainy period. The three climate types that predominate in Bartin, according to the Thornthwaite (1948) classification, are humid, moist subhumid, and dry subhumid.

The water characterization in Bartin showed 123.67 mm year−1 of water surplus, 79.7 mm year−1 of water deficit, and 1003.9 mm year−1 of potential evapotranspiration. Water deficit and potential evapotranspiration decrease as latitude increases.