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The article presents the research results aimed at determining the impact of meteorological droughts on groundwater droughts in the Gwda River catchment (northern Poland). The analysis was based on the Standardised Precipitation Index (SPI) and Standardised Groundwater Index (SGI) in various cumulation periods (1, 6, 12, 18, 24, 30 and 36 months) from 1986-2015. Monthly groundwater levels measured in wells and monthly sums of precipitation from meteorological stations in the vicinity of those wells were used to assess the relationships between droughts. During the study period from 1986-2015, three to 43 meteorological droughts and one to five groundwater droughts were identified. Meteorological droughts were most numerous for the shortest cumulation period (1 month), while droughts for the longer accumulation of 24 to 36 months were less numerous. The SPI and SGI indices were most strongly correlated over the annual cycle in the upper part of the catchment (between the Sępólno Wielkie station and well I-33_1). The correlation coefficient r was highest (0.69) between SPI-18 and SGI-1. Correlations were much lower in the middle of the catchment, where the maximum annual r coefficient was 0.39. There was no correlation between droughts in the lower catchment (r=0.14). The correlations presented for the Gwda catchment indicate that the relationship between droughts is not clear. [ABSTRACT FROM AUTHOR]

Remote sensing precipitation data have the characteristics of wide coverage and revealing spatiotemporal information, but their spatial resolution is low. The accuracy of the data is obviously different in different study areas and hydrometeorological conditions. This study evaluated four precipitation products in the Yellow River basin from 2001 to 2019, constructed the optimal combined product, conducted downscaling with various machine algorithms, and performed corrections using meteorological station precipitation data to analyze the spatiotemporal trends of precipitation. The results showed that (1) GPM and MSWEP had the best four evaluation indicators, with R2 values of 0.93 and 0.90, respectively, and the smallest FSE and RMSE, with a BIAS close to 0. A high-precision mixed precipitation dataset, GPM-MSWEP, was constructed. (2) Among the three methods, the downscaling results of DFNN showed higher accuracy. (3) The results, after correction with GWR, could more effectively enhance the accuracy of the data. (4) Precipitation in the Yellow River Basin showed a decreasing trend in January, September, and December, while it exhibited an increasing trend in other months and seasons, with 2002 and 2016 being points of abrupt change. This study provides a reference for the production of high-precision satellite precipitation products in the Yellow River basin. [ABSTRACT FROM AUTHOR]

This study analyzes the variation trends of temperature and precipitation in the Dadu River Basin of China based on observed records from fourteen meteorological stations. The magnitude of trends was estimated using Sen’s linear method while its statistical significance was evaluated using Mann-Kendall’s test. The results of analysis depict increase change from northwest to southeast of annual temperature and precipitation in space. In temporal scale, the annual temperature showed significant increase trend and the annual precipitation showed increase trend. For extreme indices, the trends for temperature are more consistent in the region compared to precipitation. This paper has practical meanings for an effective management of climate risk and provides a foundation for further study of hydrological situation in this river basin. [ABSTRACT FROM AUTHOR]

This paper is focused on the probability modeling with a range of distribution models over two inland river basins in China, together with the estimations of return levels on various return periods. Both annual and seasonal maximum precipitations (MP) are investigated based on daily precipitation data at 13 stations from 1960 to 2010 in Heihe River and Shiyang River basins. Results show that GEV, Burr, and Weibull distributions provide the best fit to both annual and seasonal MP. Exponential and Pareto 2 distributions show the worst fit. The estimated return levels for spring MP show decreasing trends from the upper to the middle and then to the lower reaches totally speaking. Summer MP approximates to annual MP both in the quantity and in the spatial distributions. Autumn MP shows a little higher value in the estimated return levels than Spring MP, while keeping consistent with spring MP in the spatial distribution. It is also found that the estimated return levels for annual MP derived from various distributions differ by 22%, 36%, and 53% on average at 20-year, 50-year, and 100-year return periods, respectively. [ABSTRACT FROM AUTHOR]

According to the daily maximum and minimum temperature and the precipitation at 40 meteorological stations in the Daqing River Basin of China during 1980–2015, the spatial and temporal trends of extreme temperature and precipitation are analyzed. The trend strengths, stability, and magnitude are calculated for ten indices of temperature and eight indices of precipitation. The results show that trends of extreme temperature indices are significant, but extreme precipitation indices are insignificant. Through the extreme temperature indices, the cold indices of extreme temperature decrease steadily and the warm indices of extreme temperature rise steadily, indicating that the trends of temperature rising in the basin are obvious and stable. In addition, indices of the extreme precipitation indicate that the consecutive dry days (CDD) decrease, the heavy precipitation days (R20) and the consecutive wet days (CWD) increase, and the annual total precipitation (PRCPTOT) increases steadily. The results have certain scientific value for climate change and a series of impacts brought by climate change in the Daqing River Basin. [ABSTRACT FROM AUTHOR]

The aim of the study was to determine the impact of precipitation on the volume of river discharge on a multiannual and seasonal basis. The research area covered the Osa River agricultural catchment located in northern Poland. For the purposes of the analysis, there were used the data from the Institute of Meteorology and Water Management - National Research Institute, covering average monthly sums of precipitation at the meteorological station in Radzyń Chełmiński and average monthly flows of the Osa River in the gauging station Rogóźno in 1966-2015. For the identification of dry and wet periods, the Standardized Precipitation Index (SPI) was used in various accumulation periods, i.e. 1, 3, 6, 9 and 12 months. In the years 1966-2015, the number of dry months (SPI ≤ -1.0) prevailed over wet months (SPI 1.0). Depending on the length of the precipitation accumulation period (1, 3, 6, 9 or 12 months), there were identified between 89 and 138 dry months, which constituted from 14.8% to 23% of all months in the analyzed multi-year period, respectively. Wet months accounted for 81 (13.5%) to 100 (16.7%) months. Relationship between SPI values in different periods of accumulation and average discharge (SQ) of Osa River was presented in the form of a correlation coefficient r. The highest correlation coefficient between SPI and SQ was obtained between precipitation in accumulation period of 6 months and average monthly discharge (r = 0.72). The indicators can be used for a drought early warning system, which is of particular importance for agricultural areas. [ABSTRACT FROM AUTHOR]

Based on the observation data of 41 surface meteorological stations in Wujiang River Basin from 1960 to 2016, the temporal and spatial variation laws of precipitation days and intensity in flood season (May to September) in Wujiang River Basin are analyzed. It is found that the distribution of precipitation in Wujiang River Basin is characterized by inhomogeneity of spatial change and tendency of temporal change. In terms of spatial distribution, affected by geographical position and topography, Wujiangdu is regarded as the boundary in terms of latitude. From the topographic point of view, because of the terrain in the vicinity of high mountains, precipitation frequency and value are larger, and precipitation also has a good correlation with the spatial distribution of temperature, humidity and wind speed; in the time variation, the frequency of rain days has an upward trend while the corresponding average precipitation is declining. The proportion of heavy rain days is decreasing while the corresponding average precipitation is increasing, and the relative humidity is decreasing. The surface air temperature is on the rise while the wind speed is on a fast downward trend. [ABSTRACT FROM AUTHOR]

Precipitation time series with high temporal resolution are desired for hydrological modelling and flood studies. Yet the choice of an appropriate resolution is not straightforward because the use of too high a temporal resolution increases the data requirements, computational costs and, presumably, associated uncertainty, while performance improvement may be indiscernible. In this study, the effect of averaging hourly precipitation on model performance and associated uncertainty is investigated using two data sources: station network precipitation (SNP) and radar-based precipitation (RBP). From these datasets, time series of different temporal resolutions were generated, and runoff was simulated for 13 pre-alpine catchments with a bucket-type model. Our results revealed that different temporal resolutions were required for an acceptable model performance depending on the catchment size and data source. These were 1–12 h for small (16–59 km2), 3-21 h for medium (60–200 km2), and 24 h for large (200–939 km2) catchments. [ABSTRACT FROM PUBLISHER]

The climate of Atndalen Valley is described by data collected by the standard network of stations currently run by the Norwegian Meteorological institute. It consists of one weather station (Sørneset) with full instrumental equipment, and three precipitation stations with a reduced set of equipment. At the latter stations, precipitation, snow depth, and snow cover are observed. Most of the stations, including the weather station, are situated in the central part of the watershed, near Atnsjøen. The climate of the Atndalen is of a continental type with precipitation minimum in late winter or spring and maximum during summer. The mean annual precipitation is about 500 mm near Atnsjøen (701 m a.s.l.) for the 30 year normal period 1961–1990. At the meteorological station Sørneset the warmest month is July, 11.2 °C, while the coldest month is January, -9.9 °C, i.e. an annual amplitude of 21.1 °C. The mean cloud cover varies from 4.5 oktas in February to 5.4 oktas in July, September and October. The highest ratio of relative sunshine is about 50% in spring. The mean snow depth increases during winter and early spring and reaches its maximum of 68 cm in March. The snow cover disappears on 9 May ±12 days and establishes on 5 November ±18 days. Variations in precipitation (since 1904) and temperature (since 1864) were studied on a decadal time scale by Gaussian filtering technique, and the significance of trends on the 0.05 level were studied by the Mann–Kendall test. For the whole period no significant trend in annual precipitation was detected. The maximum value was located to the 1920s and the minimum value to the 1910s. Annual mean temperature has increased significantly since 1864, and the classical temperature optimum in the 1930s was surpassed in the 1990s. By adopting a sinus model including the first Fourier component, trends and variations in climatological periods as well as heat and frost sums were studied. The frost free period has since 1864 increased by 13 days within 100 years based on a linear trend line. Earlier passing dates in spring largely account for the increase. The length of the growth season also increased up to about 1950. The annual heat sum shows a linear increase of about 103 daydegrees per 100 years while the annual frost sum varies considerably from period to period and fitted badly with a linear model. [ABSTRACT FROM AUTHOR]

The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen's slope, Spearman's rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for "high" monthly precipitation. According to the "low" monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as "high" and "low" values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods. [ABSTRACT FROM AUTHOR]

Twenty-five climate indices based on daily maximum and minimum temperature and precipitation at 15 meteorological stations were examined to investigate changes in temperature and precipitation extremes over the Yarlung Tsangpo River Basin (1970–2017). The trend-free prewhitening (TFPW) Mann–Kendall test and Pettitt's test were used to identify trends and abrupt changes in the time series, respectively. The results showed widespread significant changes in extreme temperature indices associated with warming, most of which experienced abrupt changes in the 1990s. Increases in daily minimum and maximum temperature were detected, and the magnitude of daily minimum temperature change was greater than that of the daily maximum temperature, revealing an obvious decrease in the diurnal temperature range. Warm days and nights became more frequent, whereas fewer cold days and nights occurred. The frequency of frost and icing days decreased, while summer days and growing season length increased. Moreover, cold spell length shortened, whereas warm spell length increased. Additionally, changes in the precipitation extreme indices exhibited much less spatial coherence than the temperature indices. Spatially, mixed patterns of stations with positive and negative trends were found, and few trends in the precipitation extreme indices at individual stations were statistically significant. Generally, precipitation extreme indices showed a tendency toward wetter conditions, and the contribution of extreme precipitation to total precipitation has increased. However, no significant regional trends and abrupt changes were detected in total precipitation or in the frequency and duration of precipitation extremes. [ABSTRACT FROM AUTHOR]