Bistricean Petrica

In the last 53 years, at all 13 meteorological stations in the Republic of Moldova, the values of the THI bioclimatic index indicate a significant warming of the March, June, July and August months. The summer and, secondary, the spring have the strongest warming. If the spring warming has positive bioclimatic effects, these effects are not available for the summer warming. The average THI values are slightly higher than the 20°C threshold only in the southern part of Moldova. Even so, on short time intervals (groups of days or at noon and afternoon hours), the values of the THI index can be even higher than the 30°C threshold. From a bioclimatic point of view, this means there are time intervals with extreme discomfort caused by heat waves. The results of different homogeneity tests applied for the THI time series show that, beginning with 1988-1989 and especially after 2000, the atmospheric warming has been accelerated. During these years thermal jumps of approximately 1°C (0.8°C by using the BHR test on annual values, 1.27°C by using the SNH test on summer values) were identified.

The temperature of a streamwater that collects water from 4 thermal groundwater sources in Valea Băilor (Moneasa, Romania) was monitored from November 2015 until February 2016. The thermal groundwater flow crosses limestones and dolomites before reaching the topographic surface. The thermal groundwater is used for local economic purposes. The average stream temperature during November-February was 23.88°C. The standard deviation of the recorded water temperature was only 0.15°C, while the difference between the maximum and minimum values was 0.75°C. The water temperature of the thermal stream, measured at 1 m distance from the thermal springs (which are grouped together in a common constructed exurgence area) does not exhibit the diurnal oscillation of the day-night cycle recorded in the air temperature. The average air temperature recorded in Valea Băilor, near the water monitoring point, from November 2015 to January 2016 was 1.47°C. The standard deviation of the air temperature was 4.16°C, while the difference between the maximum (positive number) and minimum (negative number) values was 28°C. Longer air and water temperature time series could be used to decide if there is any correlation between the local climate and the studied thermal springs.

A campaign for a continuous monitoring of the water temperature of a thermal streamwater was undertaken from December 2015 until February 2016. The streamwater originates in a former mining tunnel drilled into limestone, near Cerna River, at the upstream limit of the Băile Herculane (Romania) built area. The water measurements were obtained inside the tunnel, near its outer end. In parallel, air temperature measurements were done in the exterior air, near the tunnel. The average water temperature (measured every 30 minutes during the entire campaign) was 41.73°C, while the average air temperature (recorded each hour) was 3.17°C. The standard deviation was 1.8°C for the water temperature and 4.67°C for the air temperature. The maximum temperature was 43.795°C for water and 18.5°C for air, while the minimum temperature was 35.511°C for water and -9°C for air. The water temperature sometimes follows the air temperature and records diurnal cycles. There is a mountain valley topoclimate in the area, but the mine microclimate influences the water temperature. The thermal springs along the Cerna River have an important impact (through their number and discharge) on the water temperature of this river.

The main objectives of this study are to investigate the spatial distribution and changes in reference evapotranspiration (ET0) in the Republic of Moldova. Monthly data of maximum and minimum air temperature, sunshine duration, relative humidity, and wind speed recorded at 14 weather stations over a period of 52 years (1961–2012) were used. ET0 was computed based on the FAO Penman-Monteith formula. Annual and growing seasons of winter wheat and maize time series were analyzed for the 1981–2012 period as well as for the 1961–1980. The trends and their statistical significance in ET0 series were detected using Mann-Kendall test and T test, while the magnitude of the trends was estimated using Sen’s slope and linear regression. For the 1981–2012 period, the results indicated that annual ET0 had a positive trend in more than 90 % of the time series according to both parametric and nonparametric methods. The magnitude of positive trends in annual ET0 series ranged between 13.80 and 72.07 mm/decade. In the growing seasons of winter wheat and maize, the results are similar to those found in the annual series. Significant decreasing trends dominated over the 1961–1980 period.