Lake Śniardwy is the largest among more than 7000 Polish lakes. So far, it has not been a subject of detailed investigations concerning long-term changes in water temperature or ice regime. A considerable change in thermal and ice conditions has been observed in the period 1972–2019. Mean annual water temperature increased by 0.44°C dec–1 on average, and was higher than an increase in air temperature (0.33°C dec–1). In the monthly cycle, the most dynamic changes occurred in April (0.77°C dec–1). In the case of ice cover, it appeared increasingly later (5.3 days dec–1), and disappeared earlier (3.0 days dec–1). The thickness of ice cover also decreased (2.4 cm dec–1). Statistical analysis by means of a Pettitt test showed that the critical moment for the transformations of the thermal and ice regime was the end of the 1980’s. In addition to the obvious relations with air temperature for both characteristics, it was evidenced that the occurrence of ice cover depended on wind speed and snow cover. The recorded changes in the case of Lake Śniardwy are considered unfavourable, and their consequences will affect the course of physical, chemical, and biological processes in the largest lake in Poland.
Subtropical regions have clay-rich, weathered soils, and long dry periods followed by intense rainfall that produces large fluctuations in soil water content (SWC) and hydrological behavior. This complicates predictions of spatiotemporal dynamics, as datasets are typically collected at too coarse resolution and observations often represent a duration that is too short to capture temporal stability. The aim of the present study was to gain further insights into the role of temporal sampling scale on the observed temporal stability features of SWC order to aid the design of optimal SWC sampling strategies. This focused on both sampling frequency and total monitoring duration, as previous analyses have not considered both of these sampling aspects simultaneously. We collected relatively high resolution data of SWC (fortnightly over 3.5 years) for various soil depths and under contrasting crops (peanuts and citrus) at the red soil region of southeast China. The dataset was split into a three-year training period and a six-month evaluation period. Altogether 13 sampling frequencies (intervals ranging from 15 to 240 days) and eight monitoring duration periods (between three and 36 months) were derived from the training period to identify temporal stability features and the most time stable location (MTSL). The prediction accuracies of these MTSLs were tested using the independent evaluation data. Results showed that vegetation type did affect the spatio-temporal patterns of SWC, whereby the citrus site exhibited a stronger temporal variation and weaker temporal stability than the peanut site. However, the effects of both sampling frequency and observation duration were more pronounced, irrespective of the role of vegetation type or soil depth. With increasing sampling interval or decreasing monitoring duration, temporal stability of SWC was generally overestimated; by less than 10% when sampling interval increased from every 15 to 240 days and by up to 40% with duration decreasing from 36 to 3 months. Our results suggest that sampling strategies and trade-offs between sampling interval and duration should focus on capturing the main variability in hydro-climatological conditions. For subtropical conditions, we found that sampling once every 45 days over 24 months to be the minimum sampling strategy to ensure errors in SWC temporal stability of less than 10%.