| 1. |
- Arheimer, Berit, et al.
(författare)
-
The IAHS Science for Solutions decade, with Hydrology Engaging Local People IN a Global world (HELPING)
- 2024
-
Ingår i: Hydrological Sciences Journal. - 0262-6667 .- 2150-3435.
-
Tidskriftsartikel (refereegranskat)abstract
- The new scientific decade (2023-2032) of the International Association of Hydrological Sciences (IAHS) aims at searching for sustainable solutions to undesired water conditions - may it be too little, too much or too polluted. Many of the current issues originate from global change, while solutions to problems must embrace local understanding and context. The decade will explore the current water crises by searching for actionable knowledge within three themes: global and local interactions, sustainable solutions and innovative cross-cutting methods. We capitalise on previous IAHS Scientific Decades shaping a trilogy; from Hydrological Predictions (PUB) to Change and Interdisciplinarity (Panta Rhei) to Solutions (HELPING). The vision is to solve fundamental water-related environmental and societal problems by engaging with other disciplines and local stakeholders. The decade endorses mutual learning and co-creation to progress towards UN sustainable development goals. Hence, HELPING is a vehicle for putting science in action, driven by scientists working on local hydrology in coordination with local, regional, and global processes.
|
|
| 2. |
- Blösch, Günter, et al.
(författare)
-
Twenty-three unsolved problems in hydrology (UPH) - a community perspective
- 2019
-
Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 64:10, s. 1141-1158
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 3. |
- Papacharalampous, Georgia, et al.
(författare)
-
Global-scale massive feature extraction from monthly hydroclimatic time series : Statistical characterizations, spatial patterns and hydrological similarity
- 2021
-
Ingår i: Science of the Total Environment. - : Elsevier. - 0048-9697 .- 1879-1026. ; 767
-
Tidskriftsartikel (refereegranskat)abstract
- Hydroclimatic time series analysis focuses on a few feature types (e.g., autocorrelations, trends, extremes), which describe a small portion of the entire information content of the observations. Aiming to exploit a larger part of the available information and, thus, to deliver more reliable results (e.g., in hydroclimatic time series dustering contexts), here we approach hydroclimatic time series analysis differently, i.e., by performing massive feature extraction. In this respect, we develop a big data framework for hydroclimatic variable behaviour characterization. This framework relies on approximately 60 diverse features and is completely automatic (in the sense that it does not depend on the hydroclimatic process at hand). We apply the new framework to characterize mean monthly temperature, total monthly precipitation and mean monthly river flow. The applications are conducted at the global scale by exploiting 40-year-long time series originating from over 13 000 stations. We extract interpretable knowledge on seasonality, trends, autocorrelation, long-range dependence and entropy, and on feature types that are met less frequently. We further compare the examined hydroclimatic variable types in terms of this knowledge and, identify patterns related to the spatial variability of the features. For this latter purpose, we also propose and exploit a hydroclimatic time series dustering methodology. This new methodology is based on Breiman's random forests. The descriptive and exploratory insights gained by the global-scale applications prove the usefulness of the adopted feature compilation in hydroclimatic contexts. Moreover, the spatially coherent patterns characterizing the clusters delivered by the new methodology build confidence in its future exploitation. Given this spatial coherence and the scale-independent nature of the delivered feature values (which makes them particularly useful in forecasting and simulation contexts), we believe that this methodology could also be beneficial within regionalization frameworks. in which knowledge on hydrological similarity is exploited in technical and operative terms.
|
|
| 4. |
- Tyralis, Hristos, et al.
(författare)
-
Expectile-based hydrological modelling for uncertainty estimation : Life after mean
- 2023
-
Ingår i: Journal of Hydrology. - : Elsevier. - 0022-1694 .- 1879-2707. ; 617
-
Tidskriftsartikel (refereegranskat)abstract
- Predictions of hydrological models should be probabilistic in nature. Our aim is to introduce a method that estimates directly the uncertainty of hydrological simulations using expectiles, thus complementing previous quantile-based direct approaches as well as generalizing mean-based approaches. Expectiles are new risk measures in hydrology. Compared to quantiles that use information of the frequency of process realizations over a specified value, expectiles use additional information of the magnitude of the exceedances over the specified value. Expectiles are least square analogues of quantiles and can characterize the probability distribution in much the same way as quantiles do. Moreover, the mean of the probability distribution is the special case of the expectile at level 0.5. To this end, we propose calibrating hydrological models using the expectile loss function, which is strictly consistent for expectiles. We apply our method to 511 basins in contiguous US and deliver predictive expectiles of hydrological simulations with the GR4J, GR5J and GR6J hydrological models at expectile levels 0.5, 0.9, 0.95 and 0.975. An honest assessment empirically proves that the GR6J model outperforms the other two models at all expectile levels. Great opportunities are offered for moving beyond the mean in hydrological modelling by simply adjusting the objective function.
|
|
