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In this study, we simulated the snow water equivalent (SWE), rain‐on‐snow (ROS) events, evapotranspiration, and run‐off for the period 1961–2016 in a central European region covered by low mountain ranges (<820 m a.s.l.) using a distributed hydrological model TRAnspiration and INterception evaporation model (TRAIN). We utilized improved cloud‐free Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products to evaluate the modelled snow‐covered area, indicating a good performance of the snow modelling. We analysed the intra‐ and inter‐annual variations of the simulated hydrological variables and the synchronous climate variables (air temperature and precipitation). Trend detection indicates a significant SWE decline throughout the snow season, but principally at the high elevations; the most severe warming occurred in early spring (March), whereas precipitation showed a slight increase in January and February. The snowpack in February has displayed the most striking reduction during the past 56 years, which is likely related to both the highest susceptibility of snow to warming and the increased ROS occurrence in February since the early 1990s. The increased combination of high temperatures and extreme rainfalls, as well as the earlier snowmelt, has resulted in a run‐off increase during the earlier winter but a decrease in March. The expected changing climate towards warmer and wetter winters will probably exacerbate winter flooding in the future. [ABSTRACT FROM AUTHOR]

Geographic time series are usually non-stationary and contain different frequency components (e.g., seasonal variations, long-term and short-term fluctuations) which may significantly affect the overall variance structure in the original data. Based upon the monthly normalized difference vegetation index (NDVI), precipitation and temperature data for six different vegetation types in two precipitation regimes (low and high precipitation regimes) of Rhineland-Palatinate (Southwest Germany), this study aims to examine the temporal trends in the original time series of these variables and their relationships. In addition, the further objectives are to evaluate which time-scale is dominantly responsible for the trend production found in the original data and find out the certain time-scales that represent the strongest correlation between NDVI and climatic variables (i.e., precipitation and temperature). A combined approach using the discrete wavelet transform (DWT), Mann-Kendall (MK) trend test and correlation analysis was implemented to achieve these goals. The trend assessment for the original data shows that the monthly NDVI time series for all vegetation types in both precipitation regimes have upward trends, most of which are significant. The precipitation and temperature data for six vegetation types in two precipitation regimes present weak downward trends and significant increasing trends, respectively. The most important time-scales contributing the trend production in the original NDVI data are the 2-month and 8-month events. For precipitation, the most influential ones are 2-month and 4-month scales. The 4-month periodic mode predominantly affects the trends in the original temperature time series. Based on the original time series, the change in temperature is found to be the primary driver influencing the variability in vegetation greenness over this study area, while there is a negative correlation between NDVI and precipitation for all vegetation types and precipitation regimes. For the scale-dependent relationships between NDVI and precipitation, the 2-month and 8-month scales generally present the strongest negative correlation. The most significant positive correlations between NDVI and temperature are obtained at the 8- to 16-month scales for most vegetation types. The results of the present study might be beneficial for water resources management as well as agricultural and ecological development planning in Rhineland-Palatinate, and also provide a helpful reference for other regions with similar climate condition. [ABSTRACT FROM AUTHOR]

Mongolia is not only a water-scarce but also a data-scarce country with regard to environmental information. At the same time, regional effects of global climate change, major land use changes, a booming mining sector, and growing cities with insufficient and decaying water and wastewater infrastructures result in an increasingly unsustainable exploitation and contamination of ground and surface water resources putting at risk both aquatic ecosystems and human health. For the mesoscale (≈15,000 km²) model region of the Kharaa River Basin (KRB), we investigated (1) the current state of aquatic ecosystems, water availability and quality; (2) past and expected future trends in these fields and their drivers; (3) water governance structures and their recent reforms; and (4) technical and non-technical interventions as potential components of an integrated water resources management (IWRM). By now, the KRB is recognized as one of the most intensively studied river basins of the country, and considered a model region for science-based water resources management by the Mongolian government which recently adopted the IWRM concept in its National Water Program. Based on the scientific results and practical experiences from a six-year project in the KRB, the potentials and limitations of IWRM implementation under the conditions of data-scarcity are discussed. [ABSTRACT FROM AUTHOR]

• Hydrologic processes are analyzed based on coupled land-hydro-atmosphere perspective. • Oscillations in atmospheric conditions cause seesaw variations in river runoff. • Warming leads to opposite hydrological responses depending on permafrost conditions. • Cross-correlation is introduced to detect the effect of permafrost degradation. Changes in the cryosphere caused by global warming are expected to alter the hydrological cycle, with consequences to freshwater availability for humans and ecosystems. Here, we combine data assimilation, cross-correlation analysis, simulation techniques, and the conceptual steady-state Budyko framework to examine the driving mechanisms of historical hydrological changes at annual, seasonal, and monthly scales. We focus on two southern Siberian basins with different landscape properties: the semi-arid Selenga, characterized by discontinuous, sporadic, and isolated permafrost; and the boreal Aldan, which is underlain by continuous permafrost. Our results indicate that the two basins show divergent trends in river runoff over the period 1954–2013. In Selenga, runoff exhibits a significant decreasing trend (−1.3 km3/10yrs, p≤0.05), whereas a remarkable increasing trend (4.4 km3/10yrs, p≤0.05) occurs in Aldan. Given the negligible trends in precipitation over both basins, we attribute these contrasting changes to different impacts from warming-induced permafrost degradation. The Selenga basin, which is dominated by lateral degradation (i.e., decreasing permafrost extent), suffers from severe water loss via the enhanced infiltration of water that was previously stored close to the surface. This leads to a water-deficit surface condition. In the Aldan basin, in contrast, vertical degradation prevails: the thickened active layer is still underlain by a frozen layer with low permeability that sustains water-rich surface conditions. Furthermore, summer runoff shows contrasting oscillations, with wet-dry-wet-dry and dry-wet-dry-wet state evolutions in the Selenga and Aldan basins, respectively. We attribute such variabilities to the "seesaw-like" oscillations in summer precipitation associated with the propagation of Rossby wave trains across the Eurasian continent. We also find that warming-induced permafrost degradation over the 30-year period from 1984 to 2013 has led to strong regime shifts in river runoff in both basins. Our study highlights the importance of examining the mechanisms that drive changes in water availability from an integrated land-hydrology-atmosphere system perspective. [ABSTRACT FROM AUTHOR]

High topographic heterogeneity and complex mechanisms between the atmosphere and the ground create unique hydro-climatic processes over mountainous regions. Based on in situ observations, we present the spatial variability of ground surface temperature (GST) in the Khentii Mountains of northern Mongolia, which is situated at the southern fringe of the Eurasian permafrost zone. Changes in the hydrothermal regime of the active layer were investigated in association with changing climate and wildfire effects. The results reveal that the GST tends to increase continuously since 2011 in both thawing and freezing seasons, and varies significantly within a short horizontal distance, particularly during the thawing season. Extreme weather events, such as drought and heavy snowfall, amplify the increase in the ground temperature and deepen the seasonal thawing depth. The fire-induced loss in organic layer resulted in a greater heat penetration deeper into the ground and unbalanced the moisture distribution. Overall, the thawing depth is greater by >1.7 m under severely burned forest, compared to unburned forest. Given that about 30% of the boreal forest was affected by wildfire in the study area, the ground thermal regime changed considerably. The findings suggest that the combination of regional temperature rise and more frequent extreme weather and wildfire events in the region triggers permafrost degradation and alters the hydrothermal regime in the future. [ABSTRACT FROM AUTHOR]

Livestock production is a socioeconomic linchpin in Mongolia and is affected by large-scale livestock die-offs. Colloquially known as dzuds, these die-offs are driven by anomalous climatic events, including extreme cold temperatures, extended snow cover duration (SCD) and drought. As average temperatures across Mongolia have increased at roughly twice the global rate, we hypothesized that increasing cold season surface melt including soil freeze/thaw (FT), snowmelt, and icing events associated with regional warming have become increasingly important drivers of dzud events as they can reduce pasture productivity and inhibit access to grazing. Here, we use daily brightness temperature (Tb) observations to identify anomalous surface melt and icing events across Mongolia from 2003–2016 and their contribution to dzuds relative to other climatic drivers, including winter temperatures, SCD, and drought. We find a positive relationship between surface melt and icing events and livestock mortality during the fall in southern Mongolia and during the spring in the central and western regions. Further, anomalous seasonal surface melt and icing events explain 17–34% of the total variance in annual livestock mortality, with cold temperatures as the leading contributor of dzuds (20–37%). Summer drought showed the greatest explanatory power (43%) but overall had less statistically significant relationships relative to winter temperatures. Our results indicate that surface melt and icing events will become an increasingly important driver of dzuds as annual temperatures and livestock populations are projected to increase in Mongolia. [ABSTRACT FROM AUTHOR]

Rapid warming has reduced seasonal snow cover and changed the hydrological regimes over many areas of the globe. Temperature increase cannot only stimulate snowmelt but also favors a shift of wintertime precipitation towards rainfall, especially in Western and Central Europe that has temperate and humid winters. We assume that the mid-season (January-February) instead of the end-season (March) snow is particularly sensitive to warming in the low mountain ranges of Europe, and increased rain-on-snow events are associated with the currently frequent winter floods. To validate this assumption, we simulated the snow water equivalent (SWE), rain-on-snow (ROS) events, evapotranspiration, runoff and percolation for the period 1961-2016 in Rhineland-Palatinate, southwestern Germany (< 820 m a.s.l.) using a distributed hydrological model (TRAIN). We analyzed the intra- and inter-annual variations of the simulated hydrological variables and the synchronous climate variables (air temperature and precipitation). Early spring (March) displayed the strongest warming and the January-February warming was less severe or insignificant. Precipitation amounts did not show significant trends. However, the snowpack in February experienced the most striking reductions, which is likely explained by both the highest susceptibility of snow to warming and the increased ROS occurrence in February since the early 1990s. An increment in runoff and percolation in the earlier winter is probably related to a combination of high temperatures and more rainfalls at that time. The expected changing climate towards warmer and wetter winters but drier springs will probably exacerbate the winter flooding and spring/summer drought risks in the future. [ABSTRACT FROM AUTHOR]

While it is well recognized that the frequency and intensity of flood events are increasing worldwide, the environmental, economic, and societal consequences of remobilization and distribution of pollutants during flood events are not widely recognized. Loss of life, damage to infrastructure, and monetary cleanup costs associated with floods are important direct effects. However, there is a lack of attention towards the indirect effects of pollutants that are remobilized and redistributed during such catastrophic flood events, particularly considering the known toxic effects of substances present in flood-prone areas. The global examination of floods caused by a range of extreme events (e.g., heavy rainfall, tsunamis, extra- and tropical storms) and subsequent distribution of sediment-bound pollutants are needed to improve interdisciplinary investigations. Such examinations will aid in the remediation and management action plans necessary to tackle issues of environmental pollution from flooding. River basin-wide and coastal lowland action plans need to balance the opposing goals of flood retention, catchment conservation, and economical use of water. [Display omitted] • Flood-induced mobilization of contaminated sediment poses significant risk. • Scientific, economic, and political consequences of flood events in a global context. • Risks and tools to investigate effects of contaminant remobilization during floods. [ABSTRACT FROM AUTHOR]

• An observation-based natural and human-impacted catchment comparison method is proposed. • Human influence are quantified based on gridded socio-economic and land use data. • Climatic and anthropogenic influences on drought propagation are investigated. • Climate change accelerates the response of hydrological drought to meteorological drought. • Human activities delay the propagation from meteorological to hydrological drought. It is crucial to investigate how a precipitation deficit is transformed into hydrological drought and how climate change and human activities affect this transformation process, which is helpful to gain a deep understanding of drought propagation process in this changing environment. This study proposed an observation-based natural and human-impacted catchment comparison method to assess the impacts of climate change and human activities on propagation from meteorological drought to hydrological drought. The method mainly consists of the following three steps: (1) selection of natural catchments through analysis of trends and change points of hydro-meteorological data, as well as statistics analysis of human influence based on land use and socio-economic indicators data sets; (2) calculation of drought propagation characteristics (e.g., drought severity, duration, and propagation time) based on run theory and the Pearson correlation coefficient; and (3) comparison of drought propagation characteristics of natural catchments between undisturbed and disturbed periods to identify the impacts of climate change on drought propagation, and comparison of the propagation characteristics between natural and human-impacted catchments during the disturbed period to investigate human influence on drought propagation. The Laohahe basin (with eleven sub-catchments), located in northern China, was evaluated via the proposed procedure, and standardized precipitation index (SPI) and standardized runoff index (SRI) were used to characterize meteorological and hydrological droughts, respectively. The results demonstrate that the proposed method is suitable tool for distinguishing natural and human-impacted catchments, and separating the impacts of climate change and human activities on drought propagation. Furthermore, the comparison results of different schemes show that climate change accelerates the propagation from meteorological drought to hydrological drought in the Laohahe basin, shortening it by approximately 3 months. Human activities, however, disturb and then delay the natural propagation from meteorological drought to hydrological drought, retarding it by 11–12 months. Although the Laohahe basin was selected as a case study in this paper, the proposed method can be applied in other regions as well to improve drought prediction and water resources management. [ABSTRACT FROM AUTHOR]