Abstract We develop new estimates of monthly water balance components from 1950 to 2019 for the Laurentian Great Lakes, the largest surface freshwater system on Earth. For each of the Great Lakes, lake storage changes and water balance components were estimated using the Large Lakes Statistical Water Balance Model (L2SWBM). Multiple independent data sources, contributed by a binational community of research scientists and practitioners, were assimilated into the L2SWBM to infer feasible values of water balance components through a Bayesian framework. A conventional water balance model was used to constrain the new estimates, ensuring that the water balance can be reconciled over multiple time periods. The new estimates are useful for investigating changes in water availability, or benchmarking new hydrological models and data products developed for the Laurentian Great Lakes Region. The source code and inputs of the L2SWBM model are also made available, and can be adapted to include new data sources for the Great Lakes, or to address water balance problems on other large lake systems.
In recent years, new advances in remote sensing techniques have made Digital Elevation Models (DEMs) become popular elevation data sources for delineating catchment boundaries.This application of DEMs is particularly useful in water accounting and river basin management for Vietnam, of which the river network has very high drainage density and has been facing many pressures arising from recent economic advances.However, catchment delineated from DEMs is highly dependable to the quality of original data sources, leading to potential discrepancy in the shape as well as catchment area of the boundaries delineated from different DEMs over specific locations in Vietnam.This study comprehensively investigates this issue by analyzing the differences across catchment boundaries delineated from the most popular DEMs (i.e., HydroSHEDS, MERIT, and TanDEM-X).The impacts of these discrepancies (due to using different DEMs) on identifying areal rainfall from a gridded data product are assessed to highlight the importance of selecting DEM data sources that are suitable for specific study area.
Abstract Despite increasing evidence of intensification of extreme precipitation events associated with a warming climate, the magnitude of peak river flows is decreasing in many parts of the world. To better understand the range of relationships between precipitation extremes and floods, we analyzed annual precipitation extremes and flood events over the contiguous United States from 1980 to 2014. A low correlation (less than 0.2) between changes in precipitation extremes and changes in floods was found, attributable to a small fraction of co‐occurrence. The covariation between precipitation extremes and floods is also substantially low, with a majority of catchments having a coefficient of determination of less than 0.5, even among the catchments with a relatively high fraction of annual maxima precipitation that can be linked to floods. The findings indicate a need for more investigations into causal mechanisms driving a nonlinear response of floods to intensified precipitation extremes in a warming climate.
<p>Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models and provide the foundation for improved understanding of the link between catchment characteristics, climate and hydrological responses. Numerous LSH datasets have recently been released, covering a wide range of regions and relying on increasingly diverse data sources to characterize catchment behaviour. These datasets offer novel opportunities for open hydrology, yet they are also limited by their lack of comparability, accessibility, uncertainty estimates and characterization of human impacts.</p><p>Here, we underscore the key role of LSH datasets in open hydrologic science and highlight their potential to enhance the transparency and reproducibility of hydrological studies.&#160; We provide a review of current LSH datasets and identify their limitations, including the current difficulties of inter-dataset comparison and limited accessibility of hydrological observations. To overcome these limitations, we propose simple guidelines alongside long-term coordinated actions for the community, which aim to standardize and automatize the creation of LSH datasets worldwide. This presentation will highlight how, by producing and using common LSH datasets, the community can increase the comparability and reproducibility of hydrological research.</p><p>This research was performed as part of the Panta Rhei Working Group on large-sample hydrology and is based on https://doi.org/10.1080/02626667.2019.1683182.</p>
Understanding changes in precipitation extremes is critical for designing mitigation measures for the potential implications of a warming climate. This study assessed changes in the magnitude and frequency of precipitation extremes over Vietnam using high-quality gridded daily precipitation observations from 1980 to 2010. The annual maxima precipitation was analyzed to detect historical changes in the magnitude of precipitation extremes, while the number of heavy precipitation events, defined using the peak-over-threshold approach, was used to assess changes in the frequency of precipitation extremes. We found a strong signal of changes in the frequency of heavy precipitation, with 28.3% of Vietnam’s landmass exhibiting significant increasing trends. The magnitude of annual maxima precipitation shows a mixed pattern of changes, with less than 10% of Vietnam’s landmass exhibiting significant (both increasing and decreasing) trends. To identify possible mechanisms driving changes in precipitation, we assessed the relationship between inter-annual variations in precipitation extremes and climate variability represented by the teleconnection patterns of the Northern Hemisphere. Using five climate indices, we found that teleconnections across the Indian and Pacific Oceans have implied large control over the characteristics of precipitation extremes across Vietnam, with up to 30% of Vietnam’s landmass exhibiting a significant relationship.