1.
Shyrokaya, Anastasiya, et al.
(författare)
Significant relationships between drought indicators and impacts for the 2018-2019 drought in Germany
2024
Ingår i: Environmental Research Letters. - : Institute of Physics Publishing (IOPP). - 1748-9326. ; 19:1
Tidskriftsartikel (refereegranskat) abstract
Despite the scientific progress in drought detection and forecasting, it remains challenging to accurately predict the corresponding impact of a drought event. This is due to the complex relationships between (multiple) drought indicators and adverse impacts across different places/hydroclimatic conditions, sectors, and spatiotemporal scales. In this study, we explored these relationships by analyzing the impacts of the severe 2018–2019 central European drought event in Germany. We first computed the standardized precipitation index (SPI), the standardized precipitation evaporation index (SPEI), the standardized soil moisture index (SSMI) and the standardized streamflow index (SSFI) over various accumulation periods, and then related these indicators to sectorial losses from the European drought impact report inventory (EDII) and media sources. To cope with the uncertainty associated with both drought indicators and impact data, we developed a fuzzy method to categorize them. Lastly, we applied the method at the region level (EU NUTS1) by correlating monthly time series. Our findings revealed strong and significant relationships between drought indicators and impacts over different accumulation periods, albeit in some cases region-specific and time-variant. Furthermore, our analysis established the interconnectedness between various sectors, which displayed systematically co-occurring impacts. As such, our work provides a new framework to explore drought indicators-impacts dependencies across space, time, sectors, and scales. In addition, it emphasizes the need to leverage available impact data to better forecast drought impacts.
2.
Towner, Jamie, et al.
(författare)
Attribution of Amazon floods to modes of climate variability : A review
2020
Ingår i: Meteorological Applications. - : WILEY. - 1350-4827 .- 1469-8080. ; 27:5
Forskningsöversikt (refereegranskat) abstract
Anomalous conditions in the oceans and atmosphere have the potential to be used to enhance the predictability of flood events, enabling earlier warnings to reduce risk. In the Amazon basin, extreme flooding is consistently attributed to warmer or cooler conditions in the tropical Pacific and Atlantic oceans, with some evidence linking floods to other hydroclimatic drivers such as the Madden-Julian Oscillation (MJO). This review evaluates the impact of several hydroclimatic drivers on rainfall and river discharge regimes independently, aggregating all the information of previous studies to provide an up-to-date depiction of what we currently know and do not know about how variations in climate impact flooding in the Amazon. Additionally, 34 major flood events that have occurred since 1950 in the Amazon and their attribution to climate anomalies are documented and evaluated. This review finds that despite common agreement within the literature describing the relationship between phases of climate indices and hydrometeorological variables, results linking climate anomalies and flood hazard are often limited to correlation rather than to causation, while the understanding of their usefulness for flood forecasting is weak. There is a need to understand better the ocean-atmosphere response mechanisms that led to previous flood events. In particular, examining the oceanic and atmospheric conditions preceding individual hydrological extremes, as opposed to composite analysis, could provide insightful information into the magnitude and spatial distribution of anomalous sea surface temperatures required to produce extreme floods. Importantly, such an analysis could provide meaningful thresholds on which to base seasonal flood forecasts.
3.
Towner, Jamie, et al.
(författare)
Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin
2021
Ingår i: Hydrology and Earth System Sciences. - : Copernicus Publications. - 1027-5606 .- 1607-7938. ; 25:7, s. 3875-3895
Tidskriftsartikel (refereegranskat) abstract
Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (Glo-FAS 2.1) and observed data at 58 gauging stations are used to examine whether positive or negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (19792015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative El Nino-Southern Oscillation (ENSO) phases when the sea surface temperature (SST) anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing, however, does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO phases compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Nino and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.
4.
Zsoter, Ervin, et al.
(författare)
Hydrological Impact of the New ECMWF Multi-Layer Snow Scheme
2022
Ingår i: Atmosphere. - : MDPI. - 2073-4433 .- 2073-4433. ; 13:5
Tidskriftsartikel (refereegranskat) abstract
The representation of snow is a crucial aspect of land-surface modelling, as it has a strong influence on energy and water balances. Snow schemes with multiple layers have been shown to better describe the snowpack evolution and bring improvements to soil freezing and some hydrological processes. In this paper, the wider hydrological impact of the multi-layer snow scheme, implemented in the ECLand model, was analyzed globally on hundreds of catchments. ERA5-forced reanalysis simulations of ECLand were coupled to CaMa-Flood, as the hydrodynamic model to produce river discharge. Different sensitivity experiments were conducted to evaluate the impact of the ECLand snow and soil freezing scheme changes on the terrestrial hydrological processes, with particular focus on permafrost. It was found that the default multi-layer snow scheme can generally improve the river discharge simulation, with the exception of permafrost catchments, where snowmelt-driven floods are largely underestimated, due to the lack of surface runoff. It was also found that appropriate changes in the snow vertical discretization, destructive metamorphism, snow-soil thermal conductivity and soil freeze temperature could lead to large river discharge improvements in permafrost by adjusting the evolution of soil temperature, infiltration and the partitioning between surface and subsurface runoff.
5.
Harrigan, Shaun, et al.
(författare)
Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
2023
Ingår i: Hydrology and Earth System Sciences. - : European Geosciences Union (EGU). - 1027-5606 .- 1607-7938. ; 27:1, s. 1-19
Tidskriftsartikel (refereegranskat) abstract
Operational global-scale hydrological forecasting systems are usedto help manage hydrological extremes such as floods and droughts. The vastamounts of raw data that underpin forecast systems and the ability togenerate information on forecast skill have, until now, not been publiclyavailable. As part of the Global Flood Awareness System (GloFAS; https://www.globalfloods.eu/, last access: 3 December 2022) service evolution, in this paper daily ensemble river discharge reforecasts and real-time forecast datasets are made free and openly available through the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). They include real-time forecast data starting on 1 January 2020 updated operationally every day and a 20-year set of reforecasts and associated metadata. This paper describes the model components and configuration used to generate the real-time river discharge forecasts and the reforecasts. An evaluation of ensemble forecast skill using the continuous ranked probability skill score (CRPSS) was also undertaken for river points around the globe. Results show that GloFAS is skilful in over 93 % of catchments in the short (1 to 3 d) and medium range (5 to 15 d) against a persistence benchmark forecast and skilful in over 80 % of catchments out to the extended range (16 to 30 d) against a climatological benchmark forecast. However, the strength of skill varies considerably by location with GloFAS found to have no or negative skill at longer lead times in broad hydroclimatic regions in tropical Africa, western coast of South America, and catchments dominated by snow and ice in high northern latitudes. Forecast skill is summarised as a new headline skill score available as a new layer on the GloFAS forecast Web Map Viewer to aid user interpretation and understanding of forecast quality.
6.
Zsoter, Ervin, et al.
(författare)
How Well Do Operational Numerical Weather Prediction Configurations Represent Hydrology?
2019
Ingår i: Journal of Hydrometeorology. - : AMER METEOROLOGICAL SOC. - 1525-755X .- 1525-7541. ; 20:8, s. 1533-1552
Tidskriftsartikel (refereegranskat) abstract
Land surface models (LSMs) have traditionally been designed to focus on providing lower-boundary conditions to the atmosphere with less focus on hydrological processes. State-of-the-art application of LSMs includes a land data assimilation system (LDAS), which incorporates available land surface observations to provide an improved realism of surface conditions. While improved representations of the surface variables (such as soil moisture and snow depth) make LDAS an essential component of any numerical weather prediction (NWP) system, the related increments remove or add water, potentially having a negative impact on the simulated hydrological cycle by opening the water budget. This paper focuses on evaluating how well global NWP configurations are able to support hydrological applications, in addition to the traditional weather forecasting. River discharge simulations from two climatological reanalyses are compared: one "online" set, which includes land-atmosphere coupling and LDAS with an open water budget, and an "offline" set with a closed water budget and no LDAS. It was found that while the online version of the model largely improves temperature and snow depth conditions, it causes poorer representation of peak river flow, particularly in snowmelt-dominated areas in the high latitudes. Without addressing such issues there will never be confidence in using LSMs for hydrological forecasting applications across the globe. This type of analysis should be used to diagnose where improvements need to be made; considering the whole Earth system in the data assimilation and coupling developments is critical for moving toward the goal of holistic Earth system approaches.
7.
8.
Boelee, Leonore, et al.
(författare)
Estimation of uncertainty in flood forecasts—A comparison of methods
2019
Ingår i: Journal of Flood Risk Management. - : Wiley. - 1753-318X. ; 12:Supplement: 1
Tidskriftsartikel (refereegranskat) abstract
The scientific literature has many methods for estimating uncertainty, however, there is a lack of information about the characteristics, merits, and limitations of the individual methods, particularly for making decisions in practice. This paper provides an overview of the different uncertainty methods for flood forecasting that are reported in literature, concentrating on two established approaches defined as the ensemble and the statistical approach. Owing to the variety of flood forecasting and warning systems in operation, the question "which uncertainty method is most suitable for which application" is difficult to answer readily. The paper aims to assist practitioners in understanding how to match an uncertainty quantification method to their particular application using two flood forecasting system case studies in Belgium and Canada. These two specific applications of uncertainty estimation from the literature are compared, illustrating statistical and ensemble methods, and indicating the information and output that these two types of methods offer. The advantages, disadvantages and application of the two different types of method are identified. Although there is no one "best" uncertainty method to fit all forecasting systems, this review helps to explain the current commonly used methods from the available literature for the non-specialist.
9.
Harrigan, Shaun, et al.
(författare)
GloFAS-ERA5 operational global river discharge reanalysis 1979-present
2020
Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 12:3, s. 2043-2060
Tidskriftsartikel (refereegranskat) abstract
Estimating how much water is flowing through rivers at the global scale is challenging due to a lack of observations in space and time. A way forward is to optimally combine the global network of earth system observations with advanced numerical weather prediction (NWP) models to generate consistent spatio-temporal maps of land, ocean, and atmospheric variables of interest, which is known as a reanalysis. While the current generation of NWP models output runoff at each grid cell, they currently do not produce river discharge at catchment scales directly and thus have limited utility in hydrological applications such as flood and drought monitoring and forecasting. This is overcome in the Global Flood Awareness System (GloFAS; http://www.globalfloods.eu/, last access: 28 June 2020) by coupling surface and sub-surface runoff from the Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (HTESSEL) land surface model used within ECMWF's latest global atmospheric reanalysis (ERA5) with the LISFLOOD hydrological and channel routing model. The aim of this paper is to describe and evaluate the GloFAS-ERA5 global river discharge reanalysis dataset launched on 5 November 2019 (version 2.1 release). The river discharge reanalysis is a global gridded dataset with a horizontal resolution of 0.1 degrees at a daily time step. An innovative feature is that it is produced in an operational environment so is available to users from 1 January 1979 until near real time (2 to 5 d behind real time). The reanalysis was evaluated against a global network of 1801 daily river discharge observation stations. Results found that the GloFAS-ERA5 reanalysis was skilful against a mean flow benchmark in 86% of catchments according to the modified Kling-Gupta efficiency skill score, although the strength of skill varied considerably with location. The global median Pearson correlation coefficient was 0.61 with an interquartile range of 0.44 to 0.74. The long-term and operational nature of the GloFAS-ERA5 reanalysis dataset provides a valuable dataset to the user community for applications ranging from monitoring global flood and drought conditions to the identification of hydroclimatic variability and change and as raw input for post-processing and machine learning methods that can add further value. The dataset is openly available from the Copernicus Climate Change Service Climate Data Store: https://cds.climate.copernicus.eu/cdsapp#!/dataset/cems-glofas-historical?tab=overview (last access: 28 June 2020) with the following DOI: https://doi.org/10.24381/cds.a4fdd6b9 (C3S, 2019).
10.
Lavers, David A., et al.
(författare)
A Vision for Hydrological Prediction
2020
Ingår i: Atmosphere. - : MDPI AG. - 2073-4433 .- 2073-4433. ; 11:3
Tidskriftsartikel (refereegranskat) abstract
IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society's ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skillful, thus leading to socioeconomic benefits for the citizens of Europe and beyond.
