In cold regions, every year, river-ice jams generate sudden, surprising, intense flooding that challenges the capacity of public security services. This type of flood is commonly unpredictable and often appears chaotic because its occurrence depends on multiple, interacting weather, hydrological, ice and morphological parameters. This paper presents the findings of a research project assessing how climate change impacts dynamic river-ice breakup and associated floods along seven rivers of the province of Quebec, Canada. A combination of empirical river-ice breakup models, state-of-the-art hydrological simulations and standardized climate projections was used to estimate the historical (1972–2000) and future (2042–2070) frequencies of dynamic breakup events. Ice jam flood damage reimbursement data were used to predict changes to financial risk associated with dynamic breakup events. Results show that, overall, ice-jam floods will generate more damage in the future, which justifies watershed-based flood adaptation plans that take into account cold regions hydrological processes. The success of the methodology also sets the table for a comparable project that would include more rivers from different regions of Northeastern America. Full article

Climate change is increasingly affecting the water cycle and as freshwater plays a vital role in countries’ societal and environmental well-being it is important to develop national assessments of potential climate change impacts. Focussing on New Zealand, a climate-hydrology model cascade is used to project hydrological impacts of late 21st century climate change at 43,862 river locations across the country for seven hydrological metrics. Mean annual and seasonal river flows validate well across the whole model cascade, and the mean annual floods to a lesser extent, while low flows exhibit a large positive bias. Model projections show large swathes of non-significant effects across the country due to interannual variability and climate model uncertainty. Where changes are significant, mean annual, autumn, and spring flows increase along the west and south and decrease in the north and east. The largest and most extensive increases occur during winter, while during summer decreasing flows outnumber increasing. The mean annual flood increases more in the south, while mean annual low flows show both increases and decreases. These hydrological changes are likely to have important long-term implications for New Zealand’s societal, cultural, economic, and environmental well-being. Full article

Improved water resource management relies on accurate analyses of the past dynamics of hydrological variables. The presence of low-frequency structures in hydrologic time series is an important feature. It can modify the probability of extreme events occurring in different time scales, which makes the risk associated with extreme events dynamic, changing from one decade to another. This article proposes a methodology capable of dynamically detecting and predicting low-frequency streamflow (16–32 years), which presented significance in the wavelet power spectrum. The Standardized Runoff Index (SRI), the Pruned Exact Linear Time (PELT) algorithm, the breaks for additive seasonal and trend (BFAST) method, and the hidden Markov model (HMM) were used to identify the shifts in low frequency. The HMM was also used to forecast the low frequency. As part of the results, the regime shifts detected by the BFAST approach are not entirely consistent with results from the other methods. A common shift occurs in the mid-1980s and can be attributed to the construction of the reservoir. Climate variability modulates the streamflow low-frequency variability, and anthropogenic activities and climate change can modify this modulation. The identification of shifts reveals the impact of low frequency in the streamflow time series, showing that the low-frequency variability conditions the flows of a given year. Full article

Storage and runoff are the two fundamental surface hydrological variables of a catchment. Research studies have been focused on the storage-runoff (S-R) hysteretic relationship of a catchment and its explanation very recently, thanks to satellite gravimetry. However, a complete analysis of a hydrological process starting from recharge to runoff has not been investigated. The S-R hysteretic relationship of Yangtze River Source Region (YRSR) situated in the northeast Tibetan Plateau is also unexplored. This study aims to investigate the Recharge-Storage-Runoff relationship of this catchment using gravimetrically-derived terrestrial water storage (TWS), satellite-derived and gauged precipitation, land surface modeled and gauged evapotranspiration, and runoff data measured during 2003–2012. We found that the Pearson correlation coefficient (PCC) of S-R relationship is 0.7070, in addition to the fact that the peak of runoff every year comes earlier than that of the storage. This finding enables us to further calculate equivalent runoff based on water balance equation using the above data, while comparing to measured runoff time series. The comparison of Global Land Data Assimilation System (GLDAS)-derived (gauge-derived) equivalent runoff against measured runoff reveals a PCC of 0.8992 (0.9402), respectively, indicating both storage and runoff are largely controlled by the recharge derived from precipitation and evapotranspiration. This implies the storage is not coupled with runoff prominently due to steep topography in YRSR unable to hold the water in the form of storage. Exceptional anomalous water storage time series in 2006 has also been investigated. We speculate that the low rainfall might partly be related to an El Niño Southern Oscillation event. The low rainfall and abrupt groundwater transfer are likely to be the causes of the anomaly in 2006. Full article

This study assesses the change of the seasonal runoff characteristics in 98 catchments in central Europe between the reference period of 1981–2010, and in the near future (2011–2040), mid future (2041–2070) and far future (2071–2099). Therefore, a large ensemble of 50 hydrological simulations featuring the model WaSiM-ETH driven by a 50-member ensemble of the Canadian Regional Climate Model, version 5 (CRCM5) under the emission scenario Representative Concentration Pathway (RCP 8.5) is analyzed. A hierarchical cluster analysis is applied to group the runoff characteristics into six flow regime classes. In the study area, (glacio-)nival, nival (transition), nivo-pluvial and three different pluvial classes are identified. We find that the characteristics of all six regime groups are severely affected by climate change in terms of the amplitude and timing of the monthly peaks and sinks. According to our simulations, the monthly peak of nival regimes will occur earlier in the season and the relative importance of rainfall increases towards the future. Pluvial regimes will become less balanced with higher normalized monthly discharge during January to March and a strong decrease during May to October. In comparison to the reference period, 8% of catchments will shift to another regime class until 2011–2040, whereas until 2041–2070 and 2071–2099, 23% and 43% will shift to another class, respectively. Full article

The widely distributed lakes, as one of the major components of the inland water system, are the primary available freshwater resources on the earth and are sensitive to accelerated climate change and extensive human activities. Lakes play an important role in the terrestrial water cycle and biogeochemical cycle and substantially influence the health of humans living in the surrounding areas. Given the importance of lakes in the ecosystem, long-term monitoring of dynamic changes has important theoretical and practical significance. Here, we extracted water body information and monitored the long-term dynamics of Bosten Lake, which is the largest inland lake in China. We quantified the meteorological factors of the study area from the observation data of meteorological stations between 1988 and 2018. The characteristics of climate change and its correlation with the change of area in the Bosten Lake Basin in the past 30 years were analyzed. The major contributions of this study are as follows: (1) The initial water body was segmented based on the water index model Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) with a pre-assigned threshold value. The results were evaluated with the area extracted through artificial visual interpretation. Then we conducted mathematical morphology operators, opening and closing operations, and median filter to eliminate noise to ensure the accuracy of water body information extraction from the Bosten Lake. A long-term water surface area database of the Bosten Lake was established from high-resolution remote sensing images during 1988–2018. (2) Due to the seasonal difference of snow, ice content, and other objects on images, the areadynamics of Bosten Lake in the recent 30 years were analyzed separately in dry season and rainy season. The water surface area of Bosten Lake showed large inter-annual variations between 1988–2018. (3) Based on the assumption that climatic change has more direct effects on lake than human activities, six meteorological factors were selected to analyze the impacts of climate change on the annual mean lake surface area. The result indicated that in the past 30 years, climate conditions in the Bosten Lake Basin fluctuated greatly. We conducted correlations analysis between the areal dynamics of the Bosten Lake and the meteorological factors. Here, the annual average evaporation had the highest correlation with the areal dynamics of Bosten Lake followed by air temperature, precipitation, sunshine hours, and relative humidity, while the annual average wind speed had the weakest correlation. Full article

It is not clear how projected climate change will impact the hydrological functioning of complex catchments that have significant karst characteristics. Therefore, in this paper we focused on the investigation of the low- and high-flow characteristics of the karst Ljubljanica River catchment. One smaller (51 km²) and one larger (1135 km²) catchment were selected in order to investigate the projected climate change impact on the hydrological conditions. For the investigation of the hydrological situation in the future, we used a lumped conceptual hydrological model. The model was calibrated using past measured daily data. Using the calibrated model, we investigated the impact of five different climate models outputs for the moderately optimistic scenario (RCP4.5). We investigated the situation in next 30-years periods: 2011–2040, 2041–2070, and 2071–2100. Several low and high-flow indices were calculated and compared. The results indicate that a summer precipitation decrease (i.e., 2011–2070) could lead to lower low-flow values for the investigated areas, which could increase the vulnerability of karst areas. Thus, additional focus should be given to water resource management in karst areas. On the other hand, mean flow could increase in the future. The same also applies for the high-flows where flood frequency analysis results indicate that a climate adaptation factor could be used for the hydrotechnical engineering design. However, differences among investigated models are large and show large variability among investigated cases. Full article