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Patterns and drivers of water quality changes associated with dams in the Tropical Andes

Dams are an important and rapidly growing means of energy generation in the Tropical Andes of South America. To assess the impacts of dams in the region, we assessed differences in the upstream and downstream water quality of all hydropower dams in Colombia. We found evidence of substantial dam-induced changes in water temperature, dissolved oxygen concentration and suspended sediments. Dam-induced changes in Colombian waters violate regulations and are likely impacting aquatic life.

Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective

Although the “dry gets drier, and wet gets wetter (DDWW)” paradigm is prevalent in summarizing wetting and drying trends, we show that only 11.01 %–40.84 % of the global land confirms and 10.21 %–35.43 % contradicts the paradigm during 1985–2014 from a terrestrial water storage change perspective. Similar proportions that intensify with the increasing emission scenarios persist until the end of the 21st century. Findings benefit understanding of global hydrological responses to climate change.

High-resolution drought simulations and comparison to soil moisture observations in Germany

In this paper, we deliver an evaluation of the second generation operational German drought monitor (www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.

Improving hydrologic models for predictions and process understanding using neural ODEs

Neural ODEs fuse physics-based models with deep learning: neural networks substitute terms in differential equations that represent the mechanistic structure of the system. The approach combines the flexibility of machine learning with physical constraints for inter- and extrapolation. We demonstrate that neural ODE models achieve state-of-the-art predictive performance while keeping full interpretability of model states and processes in hydrologic modelling over multiple catchments.

Predicting soil moisture conditions across a heterogeneous boreal catchment using terrain indices

Terrain indices constitute a good candidate for modelling the spatial variation of soil moisture conditions in many landscapes. In this study, we evaluate nine terrain indices on varying DEM resolution and user-defined thresholds with validation using an extensive field soil moisture class inventory. We demonstrate the importance of field validation for selecting the appropriate DEM resolution and user-defined thresholds and that failing to do so can result in ambiguous and incorrect results.

Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams

The geologic structure of mountain watersheds may control how groundwater and streamwater exchange, influencing where streams dry. We measured bedrock depth at 191 locations along eight headwater streams paired with stream temperature records, baseflow separation and observations of channel dewatering. The data indicated a prevalence of shallow bedrock generally less than 3 m depth, and local variation in that depth can drive stream dewatering but also influence stream baseflow supply.

Technical note: Conservative storage of water vapour – practical in situ sampling of stable isotopes in tree stems

We developed a method of sampling and storing water vapour for isotope analysis, allowing us to infer plant water uptake depth. Measurements can be made at high temporal and spatial resolution even in remote areas. We ensured that all necessary components are easily available, making this method cost efficient and simple to implement. We found our method to perform well in the lab and in the field, enabling it to become a tool for everyone aiming to resolve questions regarding the water cycle.

The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL)

Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.

Morphological controls on surface runoff: an interpretation of steady-state energy patterns, maximum power states and dissipation regimes within a thermodynamic framework

In hydrology the formation of landform patterns is of special interest as changing forcings of the natural systems, such as climate or land use, will change these structures. In our study we developed a thermodynamic framework for surface runoff on hill slopes and highlight the differences of energy conversion patterns on two related spatial and temporal scales. The results indicate that surface runoff on hill slopes approaches a maximum power state.

Agricultural intensification vs. climate change: what drives long-term changes in sediment load?

This study explored the quantitative contribution of agricultural intensification and climate change to the sediment load of a small agricultural watershed. Rather than a change in climatic conditions, changes in the land structure notably altered sediment concentrations under high-flow conditions, thereby contributing most to the increase in annual sediment loads. More consideration of land structure improvement is required when combating the transfer of soil from land to water.

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