This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come. ARTICLE HISTORY
Abstract:Hydrological models need to be adapted to specific hydrological characteristics of the catchment in which they are applied. In the lowland region of northern Germany, tile drains and depressions are prominent features of the landscape though are often neglected in hydrological modelling on the catchment scale. It is shown how these lowland features can be implemented into the Soil and Water Assessment Tool (SWAT). For obtaining the necessary input data, results from a GIS method to derive the location of artificial drainage areas have been used. Another GIS method has been developed to evaluate the spatial distribution and characteristics of landscape depressions. In the study catchment, 31% of the watershed area is artificially drained, which heavily influences groundwater processes. Landscape depressions are common over the 50-km 2 study area and have considerable retention potential with an estimated surface area of 582 ha. It was the scope of this work to evaluate the extent by which these two processes affect model performance. Accordingly, three hypotheses have been formulated and tested through a stepwise incorporation of drainage and depression processes into an auto calibrated default setup: (1) integration of artificial drainage alone; (2) integration of depressions alone and (3) integration of both processes combined. The results show a strong improvement of model performance for including artificial drainage while the depression setup only induces a slight improvement. The incorporation of the two landscape characteristics combined led to an overall enhancement of model performance and the strongest improvement in r 2 , root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) of all setups. In particular, summer rainfall events with high intensity, winter flows and the hydrograph's recession limbs are depicted more realistically.
Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species’ response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower‐mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present‐day gauging data. Species’ abundances were predicted for three periods: (1) baseline (1998–2017), (2) horizon 2050 (2046–2065) and (3) horizon 2090 (2080–2099) based on these empirical relationships and using high‐resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low‐flow conditions, leading to decreased abundances of species up to −42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower‐mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate‐change impacts on species abundances and can be applied to any stressor, species, or region.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.