bluuebunny/crossref_metadata_2025 huggingface dataset:
The German flood cooking book: ingredients and regional flavors of floods
Authors: Merz Ralf , Tarasova Larisa , Basso Stefano
Published: September 2022

Floods are generated by complex interactions between different processes that are still poorly understood especially at the large scale. Here we investigate 177,267 rainfall-runoff events across 373 German catchments to identify which spatial and temporal properties of precipitation events and wetness state of catchments lead to the emergence of floods by applying two machine learning approaches based on decision trees and random forests. We found that in wet mountainous catchments with rather shallow soils, rainfall characteristics play an ultimate role in modulating flood occurrence. Instead, in the drier catchments the occurrence of flood events is driven primarily by the pre-event wetness conditions and spatial interplay between soil moisture and rainfall within the catchment. Snow cover additionally enhances flood occurrence in all study catchments. The identified ingredients and regional flavors of flood events in Germany provide new insights on the spatial dynamics of hydro-meteorological processes leading to floods and might become an essential tool to foster regionally-coordinated flood management strategies and early warning systems.
Integrating equity into a water allocation model to promote water sharing in environments with vulnerable stakeholders
Authors: Xoxo Sinetemba , Tanner Jane , Hughes Denis , Mantel Sukhmani
Published: September 2022

While some progress has been made towards improving the sustainable management of water resources, challenges remain. In the water scarce Doring River, in South Africa, these are associated with achieving equitable sharing of the resource among a range of stakeholders which include commercial farmers and emerging farmers.  A participatory water sharing tool has been developed which aims to contribute to  water governance, and includes some key variables such as  the inclusion of uncertainty, environmental Reserve requirements (environmental flows), and the incorporation of socio-economic factors associated with water use. The Institute for Water Research at Rhodes University developed the water sharing tool in response to the Panta Rhei initiative. The tool promotes water sharing at a community level by different water users/user groups, and it encourages deliberation to identify an optimal water sharing (or reallocation) strategy by communicating frequency distributions of assurance shortfall risk. The tool explicitly considers epistemic and alleatory uncertainty; the water users’ value for environmental water requirements; and considers social heterogeneity using socio-economic factors that may influence the way people make water use decisions. However, the tool has never been applied in practice. To complete the tool’s development, a commercial farming setting (i.e. the Doring River in the Koue Bokkeveld region of South Africa) will be used as a case site. The model allocates the available water resource based on the differing impacts on users (impacts of the same deficit will be different for emerging and commercial farmers for example), and produces information which assists the stakeholders to manage the risks of the shortfalls. Ultimately, the stakeholders select the best water sharing option based on a number of possibilities, produced through various combinations of socio-economic factors. In light of growing water scarcity, and the highly uneven distribution of water often found in developing nations, the tool’s approach can be valuable in negotiating increasing water crisis among very different users/user groups.
The ecohydrological approach for Integrated Vulnerable Coastal Zone Resilience in arid regions
Authors: Amrouni Oula , Heggy Essam , Mahé Gil
Published: September 2022

Coastal wetland ecosystems are complex environments subject to physical factors and multiple yield supplies. The climate change impacts are strongly visible in those low-lying areas, in close relationships with the decrease of the continental water and sediment supply, marine storms and submersion. To understand the interactions between the coastal components we adopt the ecohydrology approach for a lagoon ecosystem in North Africa. The ecohydrology approach is based on as a compeling of well-experimented data as the sediment dynamics, the hydrology of the watershed basin and the coastal aquifer, and the biodiversity and the remote sensing observations in relation with the socioeconomic activities. The ecohydrology concept is focused in our research on the coastal ‘hot spot’ areas on the deltaic-lagoon and sandy barrier areas identified as very highly vulnerable to the sea level rise and marine disasters. The main goal is to establish a shared database and an innovative Nature Based Solution with the regional communities to enhance the coastal resilience and to better explore the aquatic resource for a sustainable blue economy, in the context of rapid environmental changes in the Mediterranean arid-regions, driven by both climate change and anthropogenic negative impacts on natural landscapes.
Advancing knowledge accumulation and synthesis in hydrology
Authors: Stein Lina , Wagener Thorsten
Published: September 2022

The number of publications in the field of Hydrology is rising at an almost exponential rate. In 2020, more than 25 000 articles were listed in Web of Science on the topic of Water Resources. This offers a wealth of knowledge for an improved understanding of the Earth System and Hydrology. However, it is increasingly difficult for hydrologists to keep aware of knowledge gains. How do we deal with this flood of information? Do we rely on pre-selection of papers based on publication date or journal impact factor? Do we specialise into increasingly narrow fields of knowledge?

These tendencies of a growing science can be detrimental to a broad hydrologic perspective as called for by the WMO Hydrologic Action Plan, the IAHS initiatives “Panta Rhei” and 23 UPH. Studying interacting processes is made increasingly difficult if we dissect our science into smaller and smaller parts to stay on top of the literature.

One approach to address this problem of literature explosion might be to extend article metadata to include hydrology-specific information that can facilitate knowledge search, accumulation and synthesis. Imagine one could easily find all studies done in a specific location/ climate/ land use thus allowing a full picture of the hydrology of that region/ climate/ land use. It is important for a science like hydrology, which is strongly depending on experience, that local knowledge is not “forgotten” in a mountain of publications but can easily be integrated into larger understanding.

The leads to the question, what meta-information would be most useful in knowledge synthesis? Study location? Spatial and/or temporal scale? Models used? We are interested to hear further suggestions and needs by the community. Here, we would like to (re-)start the discussion on hydrologically-relevant metadata enrichment. With the recent advancement in text mining scholarly literature, it is critical to have this discussion now or miss out on opportunities in this field.

A science like hydrology strongly depends on experiences we gain and which we largely share through the articles we publish. Knowledge accumulation in our science is hindered if this exchange of knowledge becomes ineffective. We are afraid it already has!
The Initiation of a National Flood Studies Programme for South Africa: Overview and Progress to Date
Authors: Smithers Jeff
Published: September 2022

Floods have an impact on human survival, economic development and environmental sustainability through loss of life and significant economic loss as a consequence of the failure of structures (e.g. dams and culverts).  Estimates of design floods are required for the design of hydraulic structures and to quantify the risk of failure of the structures. Information on flooding is also essential for the development of safe human settlements, particularly in low lying areas.

Historical records of floods are used to both directly estimate design floods from the observed gauged data and to develop methods to estimate the design floods at ungauged sites. The longer the period of available gauged flow data, the more reliable the design floods and methods. Most of the methods currently used for design flood estimation in South Africa were developed in the late 1960s and early 1970s and are in need of updating with more than 40 years of additional data currently available and with new approaches used internationally.  In addition, climate change is expected to influence the magnitude and frequency of flooding, and hence this increased variability in flows need to be accounted for when determining flood risk.

Given the above, the South African National Committee on Large Dams identified the urgent need to update the data and methods used for design flood estimation in South Africa and, in conjunction with the Water Research Commission, initiated a National Flood Studies Programme (NFSP) to update these.  This paper will briefly summarise the performance of empirical, event-based deterministic and regional approaches currently used in South Africa and will provide an overview of new developments to date. This will include updates to design rainfall and probable maximum precipitation estimation, the identification and recommendation of the best probability distribution to use in flood frequency analyses, the development of regional quantile regression and index flood approaches, the determination of locally derived Curve Numbers for the SCS model using both observed and simulated flows, the investigation of an ensemble approach for the SCS-SA model, and the development of a continuous simulation approach to flood estimation on a national scale.
Investigation of the maximisation potential of large floods by spatio-temporal simulation of rainfall 
Authors: Haberlandt Uwe , Thiele Luisa-Bianca
Published: September 2022

Exceptional floods are caused by extreme meteorological conditions matching critical space-time scales of flood generation processes in a catchment. Although these events are very rare, they are possible and it would be helpful to know what might happen in these cases for risk assessment. Fortunate, for most of the flood events some factors are not “optimal” to cause an exceptional flood. This study investigates which reasonable changes on the flood producing storms may lead to exceptional floods. For that, observed storms are stochastically modified and analysed regarding its maximisation potential for floods. First the spatial patterns are modified, then the intensities are modified and finally both conditions are modified together. The pattern modification is based on space-time simulation conditioned on observations from a conventional rainfall station network. The rainfall intensities are modified with moisture maximisation but keeping the observed pattern constant according to radar rainfall observations. Many space-time rainfall realisations are produced and used as input for a rainfall-runoff model. Simulated annealing is used as conditional rainfall simulation approach and the HBV model to simulate the floods. This case study uses data from the Mulde river catchment in Germany and applies the methodology to a set of selected large flood events. It is expected, that the results reveal how extreme the floods could have become and whether increased intensities or pattern modification contributes more to the maximisation potential.
Increasing water use efficiency and understanding the value of information for the management of deficit irrigation systems
Authors: Schütze Niels
Published: September 2022

Due to climate change, extreme weather conditions such as droughts may have an increasing impact on the water demand and the productivity of irrigated agriculture. For the adaptation to changing climate conditions, the value of information about irrigation control strategies, future climate development, and soil conditions for the operation of deficit irrigation systems is evaluated. To treat climate and soil variability within one simulation-optimization framework for irrigation scheduling, we formulated a probabilistic framework that is based on Monte Carlo simulations. The framework can support decisions when full, deficit, and supplemental irrigation strategies are applied. For the analysis, the Deficit Irrigation Toolbox (DIT) is used for locations in arid and semi-arid climates. Deficit Irrigation Toolbox (DIT) is an open-source software to simulate and maximize crop-water productivity of deficit irrigation systems. The toolbox allows you to perform complex analysis of crop yield response to climate change, soil variability, and water management practices. A case study shows that information about soil data has a different value in arid and semi-arid regions. Therefore, the provided results can serve as an easy-to-use support tool for decisions about the importance of climate and soil data at a local or regional scale.
River runoff in European Russia under global warming
Authors: Kalugin Andrey
Published: September 2022

Regional spatially distributed runoff formation models for the Volga, Don, Northern Dvina, Pechora and Kuban river basins were developed using ECOMAG software, global databases (DEM, soils, landscapes) and weather station dataset. According to hydrological models, good or satisfactory results were obtained for calculating the daily runoff using the KGE criterion for each of 35 gauges, PBIAS for 34 gauges, NSE for 33 gauges. 

For example, the Volga basin model based on the Earth system models output data reproduces the annual runoff over the historical period with an error of 1.5–6% relative to the calculation based on the weather station data. The largest relative calculation errors are typical for the winter runoff (up to 17%), and the smallest for the runoff during the spring flood (up to 6%).

Under global warming and critical threshold of 1.5°С and 2°С (in the context of UPH #1), the assessment of the runoff anomalies of the Volga and its main tributaries showed the following general features: an increase in winter runoff, a decrease in runoff during the spring flood and summer-autumn, and, as a result, a decrease in annual runoff. The decrease in annual runoff was 10–11% under the realization of both warming scenarios relative to the period 1970–1999. The largest relative decrease in runoff by 17–20% was noted for the Oka and Upper Volga, while for the Kama only by 1–5%. The increase in the winter runoff of the Volga amounted to 17% and 28% under global warming of 1.5°C and 2°C, respectively. The negative runoff anomalies for the period of spring flood and summer-autumn were in the range of 21–23%. The most intense increase in winter runoff by 30–40% was characteristic of the Upper Volga, and the least intense was for the Oka by 12–20%, depending on the rate of global warming. The largest relative decrease in runoff during the spring flood and summer-autumn was noted in the Upper Volga (about 40%), and the smallest was noted in the Kama by 8–10%.

This study was supported by the Russian Science Foundation (project No. 20-77-00077).
Assessing the Accuracy of Multiple Algorithms Combining Sentinel-1 and Sentinel-2 for the Citrus Classification and spatialization of the Actual Evapotranspiration Obtained from Flux Tower Eddy Covariance: Case Study of Cap Bon, Tunisia.
Authors: Chakhar Amal , Zitouna-Chebbi Rim , Hernández-López David , Ballesteros Rocío , Mahjoub Imen , Moreno Miguel A.
Published: September 2022

Land use and water resources are closely linked. Every single type of land use has a different influence on the hydrologic cycle, consequently impacting the people and the natural resources. The use of advanced technologies, for example monitoring the agricultural resources using remote sensing, offers the possibility to assess the water demand, to know the total cultivated area with the precise distribution of crops and enables the regularly acquisition of data distributed in space and time. The citrus sub-sector is of paramount importance in the Tunisian agricultural sector. The Cap Bon region has the main production area with 75% of the total citrus area. Tracking changes in citrus crops over time is important for water resource management at regional scale and for economic stability. Given the socio-economic importance of the citrus sector in the Cap Bon region, it is very important to estimate the total area of citrus in the Cap Bon region. Therefore, the main objectives of this current work are:

To integrate multitemporal synthetic aperture radar SAR data, Sentinel-1, and optical data Sentinel-2, together to determine the best machine learning algorithm that allowed obtaining the most accurate citrus crop classification in the region.

To study and analyze the temporal signatures of the Normalized Difference Vegetation Index (NDVI) of the classified crops, mainly the citrus, with the purpose to provide the maximum amount of information that allow the differentiation between the crops.

To study the potential relation between NDVI and Evapotranspiration (ET) fluxes measured with the eddy covariance method for a citrus orchard to extrapolate the eddy tower measurements to greater scales.

To achieve these objectives, we evaluated the performance of 22 nonparametric classifiers during the period September 2020 – June 2021. Additionally, ET measured by the eddy covariance method was available for the same period. The results revealed that the best performing classifier is the Ensemble classifiers with an accuracy equal to 84.3%. Consequently, our results provide a significant contribution to the citrus classification in the Cap Bon region and highlight the potential to extrapolate accurate ET estimation to larger scales using the vegetation index obtained from Sentinel-2 data.
How can geochemistry and isotope hydrology tools tell us about alluvial groundwater-wetlands interactions and subsequent carbon balance? Case of the Moltifau Mediterranean peatland (Corsica Island, France)
Authors: Santoni Sébastien , Garel Emilie , Huneau Frédéric , Gillon Marina , Babic Milanka , Mattei Alexandra
Published: September 2022

Wetlands are essential for humankind as they provide climate change mitigation through ecosystem services. Peatlands are wetlands also known as carbon sinks through peat accumulation. In the Mediterranean, peatlands represent up to 42% of the total wetland surface but remain under-investigated. The existing knowledge suggests they are shaped by their local environment, making them small, scattered, and groundwater-dependent. One of the most important knowledge gaps lies in the characterization and quantification of the water balance components necessary for biodiversity conservation and peat accumulation. Thus, additional information on peatlands could help delineate their hydrological vulnerability and resilience capacity to climate change. Approaches combining water level monitoring, geochemistry, and isotope hydrology tools have been widely employed to characterize the origin, periodicity, and recharge mechanisms of very large and well-developed wetlands mainly in cold humid climates. The same approach towards the investigation of more seasonal and inhomogeneous recharge mechanisms of Mediterranean peatlands is largely missing and has never been attempted to investigate the subsequent impacts on their carbon balance. To fill this gap, the alluvial peatland of Moltifau has been selected for its location in the western Mediterranean region at low altitude worsening seasonal drought conditions and vulnerability to climate change. An innovative multi-tracing experiment including geochemical and isotope hydrology tools such as physic-chemical parameters, major ions, δ18O, δ2H, 3H, 87Sr/86Sr and δ13CDIC has been conducted benefiting from strong isotope contrasts due to varied lithology in a high elevation catchment. Five quarterly field campaigns in contrasting hydrological conditions were carried out between May-2018 and Jun-2019. The tracers highlighted the peatland’s rain and river dependency during fall-winter, as well as its river and multiple groundwater origin during spring-summer. Furthermore, our results show the impacts of such a recharge seasonality on hydrochemical processes and explain most of the variation in carbon fluxes, except in summer. In the future, the analysis and interpretation of peat chemical properties and isotopic signatures of CO2 emissions will provide further information on the carbon storage dynamics of Mediterranean peatlands. This work illustrates the strong potential of isotopes in the study of water and carbon cycle interactions at the hydro-ecosystem scale.
Time Asymmetry and Stochastic Modelling of Streamflow
Authors: Vavoulogiannis Stelios , Iliopoulou Theano , Dimitriadis Panayiotis , Koutsoyiannis Demetris
Published: September 2022

Time asymmetry, i.e., temporal irreversibility, has a very important role in many scientific fields and has been studied thoroughly. Its detection in time series indicates the need to preserve it in stochastic simulations. This also seems to be the case for the streamflow process in hydrological simulation. Relevant large-scale studies have shown that time asymmetry of the streamflow is absolutely evident at small scales (hours) and vanishes only at larger scales (several days). The latter highlights the need to reproduce it in flood simulations of fine-scale resolution. To this aim, an enhancement of a recently proposed simulation algorithm for irreversible processes was developed, based on an asymmetric moving average (AMA) scheme that allows for the explicit preservation of time asymmetry at two or more timescales simultaneously. The method is tested through some case studies from around the world to further explore the method’s strengths and limitations and to examine the stochastic characteristics of the simulated results.
Sustainability Assessment: The role of Indicator-based Frameworks in Sustainable Water Management
Authors: Shafiei Mojtaba , Gharari Shervan , Gharesifard Mohammad , Ghoreishi Mohammad , V. Castro Cyndi
Published: September 2022

The concept of sustainability in water management remains an amorphous notion. Despite its widespread use, there is not a shared and accepted definition of the concept of sustainability in water management, including its monitoring and assessment, particularly at river basin scale. Sustainability Assessment (SA) can be defined as any process that aims at planning and direct decision-making toward sustainable development. An interdisciplinary approach for understanding, measuring and monitoring sustainability of water management practices includes the holistic development of Indicator-Based Assessment (IBA) frameworks as policy/decision support tools. The IBA refers to the positive, negative, and neutral qualifications of an indicator based on the comparison between its observed evolution (and/or status), and the desired evolution set for the indicator by means of a frame of reference. Therefore, developing IBA frameworks help to synthesize information and monitor changes in water management systems.

Recently, developing indicator-based assessment frameworks and constructing indexes have evolved significantly toward monitoring the United Nations Sustainable Development Goals (UN SDGs). However, there are limited studies on developing sustainability indexes or indicator-based sustainability assessment frameworks at the river basin scale for complex issues of water management. The aim of this work is to provide a review of i) the concept of SA in water management and also ii) the methodology of indicator-based framework development. Finally, a case study of developing an indicator-based sustainability assessment framework is presented for the Mashhad River basin in Iran.
Expanding information for flood frequency analysis using a weather generator and distributed hydrological modelling in a Spanish Mediterranean catchment
Authors: Beneyto Carles , Aranda José Ángel , Salazar-Galán Sergio , García-Bartual Rafael , Albentosa-Hernández Eduardo , Francés Félix
Published: September 2022

Flood risk management requires the knowledge of flood quantiles associated with high return periods. To date and due to the short temporal length of the maximum available flow records, these present very high uncertainties. This scarcity makes unfeasible the use of classical statistical methods, becoming necessary to advance in a methodological approach of flood frequency analysis based on the understanding of the main hydrological processes and taking advantage of the better information on extreme rainfall at regional scale. In this article, a storm modeling approach with a weather generator (WG) and distributed hydrological modeling including sediments (TETIS model) are proposed to support the frequency analysis, being implemented in a case study: the Segura river basin (Murcia, Spain) with 14,000 km2. Specifically, the methodology consists of the following steps:

Perform a regional study of annual maximum daily precipitation.

Calibration of a WG on a daily scale and generation of a long daily precipitation series (5,000 years)

Extreme storm selection (698) and temporal disaggregation into sub-daily scale (hourly)

Implementation of TETIS at hourly resolution and hydrological simulation of selected storms

Final peak flow frequency analysis and validation of the methodology

A validation of the methodology has been carried out with historical flood data considering six catastrophic flood events since 1825. According to the results obtained, a significant reduction in the uncertainty associated with both rainfall and flow quantiles has been achieved. For the last major flood in September 2019, the results have shown that, in the Abanilla tributary (one of the main flow contributors to the flood zone), the recorded peak flow is highly likely to correspond with an event with a medium probability of flooding (around a 100-year return period), although it corresponds with a rainfall event with a return period between 10 and 1000-year, depending on the location of the rain gauge within the Abanilla subcatchment.

Finally, it is possible to advance in an analysis of risk management measures to evaluate their effectiveness and viability, comparing present conditions and future scenarios and considering different strategies (structural and non-structural measures or nature-based solutions).
How much can we simplify irrigation in an integrated modelling purpose? A case study in southern France
Authors: Soutif-Bellenger Myriam , Thirel Guillaume , Therond Olivier , Villerd Jean
Published: September 2022

The estimation of irrigation amounts and timings is crucial for the design of water management strategies at the regional scale. However, simplified modelling approaches are often preferred even though very complex and high-accuracy crop models or agent-based models exist. In this study, we develop a sensitivity analysis to evaluate the impacts of simplifications and hypotheses in irrigation modelling. For this, different simple modelling approaches based on the CropWat model were compared to a multi-agent based approach (Maelia), which served as a benchmark. To make an in-depth comparison between simulations, several indicators characterizing daily simulated irrigation were calculated and a decomposition of variance was carried out to measure impacts of diverse factors on irrigation. Applied over a downstream portion of the Aveyron River (southern France), the sensitivity analysis shows a high variability between simulations in function of modelling assumptions. It also shows that several simplifying approaches were able to reproduce the high-accuracy model estimation of irrigation. Decisive variation factors we identified are rules of triggering and quantification of daily irrigation, irrigation period definition and evapotranspiration estimation. Recommendations to take into account highlighted variability linked to farmers’ irrigation practices are introduced in this work, consisting in a combining a set of irrigation models. In function of advancement, a complete integrated agro-hydrologic modelling chain might be presented.
Risk of extreme rainfall in tne Bandama basin (West Africa): Contribution of multifractal analysis
Authors: Meledje N'diaye Edwige Hermann , Koffi Bi Kassia Francis , Kouassi Kan Martin , N'go Yao Alexis , Kouassi Kouakou Lazare
Published: September 2022

The floods that have affected many African countries south of the Sahara have not exempted Ivory Coast, especially since the 1970s. The impact of these events has led to major climatic disruptions, particularly the occurrence of extreme rainfall. In the Bandama catchment area, in September 2018 alone, the heavy rains that fell led to a flooding of the Bandama River. The towns of Zenoula and Bouaflé were flooded, plantations destroyed. According to the Agence de Presse Ivoirienne (AIP) on 22 September 2018, a total of 2017 people including 1130 children are affected in Bouaflé. In this context, it is important to better understand how the irregularity and distribution of extreme rainfall occurs in order to adopt preventive measures. However, the lack of studies on climate trends does not allow us to anticipate environmental problems. Indeed, the simplest way to understand this variability, although the necessary concepts and notions must be available, is to consider that there is an elementary and scale-invariant process that reproduces this variability from scale to scale. The possibility of characterising and modelling the variability of precipitation from scale to scale rather than at a given scale has led to a number of studies on multifractal precipitation (Lovejoy et al., 1987; Hubert et al., 2002). The objective of this study is to highlight the occurrence of extreme rainfall in the Bandama catchment using multifractal analysis. For this work, daily data from 2005 to 2010 from 10 stations (Yamoussoukro, Bouaflé, Dimbokro, Ferkessedougou, Niakara, Séguela, Bouaké, Tiassalé, Grand-Lahou, Zuenoula) were considered. Three intensity thresholds (with respective values of 20; 35; 50 mm/d) were studied. For these thresholds, the respective fractal dimension is 0.321; 0.249; 0.232.  The probability of obtaining a rainy day with thresholds set at 50 mm, 35 mm, 20 mm is respectively 0.069; 0.074; 0.093 over one month. The probability of obtaining rainy days for the three thresholds is spatialized over the catchment.

Keywords: Occurrence of extreme rainfall, multifractal, Bandama basin, Ivory Coast
SMASH - Spatially distributed Modelling and ASsimilation for Hydrology: Python wrapping towards enhanced research-to-operations transfer
Authors: Jay-Allemand Maxime , Colleoni François , Garambois Pierre-André , Demargne Julie
Published: September 2022

The prediction of extreme hydrological events at high resolution is a tough scientific challenge linked to major socio-economic issues. Accurate numerical models are crucially needed to perform reliable and meaningful operational predictions. In this context, modern and efficient modeling tools are required to integrate scientific progress and numerical advances, take advantage of the wealth of information provided by new generations of satellite and sensors in complement of in situ data, and meet the needs of diverse end users.
This contribution presents the tailoring of a computational hydrological modeling and data assimilation code, SMASH (Spatially distributed Modelling and ASsimilation for Hydrology), originally written in Fortran. This aims to facilitate scientific enhancements and their transfer to the operational French flash flood warning system, Vigicrues Flash. Thanks to the recent f90wrap library (Kermode J., 2020), the whole SMASH toolchain has been wrapped for use in a Python environment. The new wrapped SMASH is compiled as shared library, loaded in a Python environment and benefits from advanced Python libraries for pre- and post-processing, optimization and machine learning (Virtanen P., 2020 and Stančin I., 2019 and Sarkar D., 2018 and Lawhead J., 2019). The SMASH Python toolchain currently includes (i) a modular hydrological model, (ii) fortran solvers, (iii) the corresponding adjoint model obtained by automatic differentiation with the Tapenade engine (Hascoet L., 2013) and (iv) a Python class to simplify the Python-Fortran interface. The wrapped code features a revamped structure and gains in modularity. The validation of the wrapped SMASH toolchain is performed via comparisons, over several academic and real cases, against the reference results from the original SMASH Fortran code (Colleoni F., 2021 and Jay-Allemand M., 2020).
These Python wrappers offer several perspectives: SMASH will ease the transfer of scientific enhancements into operations, in particular for the national Vigicrues Flash service; coupling SMASH with probabilistic precipitation nowcasting could be facilitated with the Python libraries Pysteps (Pulkkinen S, 2019); future toolchain improvements will benefit from up-to-date numerical technologies, such as parallel computing, model couplings, hybrid solvers, web services and mapping, as well as uncertainty modeling and data assimilation algorithms.
River discharge estimation from SWOT satellite using Hybrid Bayesian-Variational method
Authors: Oubanas Hind , Gejadze Igor , Malaterre Pierre-Olivier
Published: September 2022

The Surface Water and Ocean Topography CNES and NASA mission, planned for launch in late 2022, will provide a global mapping of the water surface elevation, width and slope of rivers wider than 100m worldwide. The estimation of discharge using solely the SWOT-type observations together with the existing satellite data has received a noticeable attention recently. The attempts to solve this problem have expectedly confirmed that it is ill posed and additional data could be needed, such as the estimates of the mean, minimum and maximum discharge from the available global scale hydrological databases. However, taking into account the accuracy of such estimates and the issue of their relevance to the study period, the problem remains challenging. We suggest a new estimation method, designed specially to reduce the solution bias. It combines Bayesian and Variational approaches to improve the algorithm robustness and stability. In this method the likelihood function is computed, allowing a useful analysis of equifinality often encountered in discharge estimation problems for ungauged basins. The algorithm is designed for global and/or basin-scale applications given the multi-level structure of the methodology. The latter involves different levels of complexity in terms of the representation of the flow dynamics and therefore different computational requirements. Here, we investigate discharge and bathymetry estimation under strong uncertainties from SWOT simulations and their combination with optical (Landsat and Sentinel 2) and altimetry (Jason, ENVISAT, Sentinel 3) data. The global application involves a Python low-cost algorithm that will be run globally through the Confluence platform implemented by UMass with the SWOT Science Team.

Keywords: Data assimilation, Bayesian estimation, remote sensing, SWOT, hydraulic modelling, discharge estimation, altimetry, optical imagery, rivers
Consideration of sample size uncertainty for the regionalization of type-specific flood frequency analyses
Authors: Fischer Svenja , Schumann Andreas
Published: September 2022

The regionalisation of flood frequencies is a precondition for the estimation of flood statistics for ungauged basins. We propose a flood type-specific regionalization, to take into account the different flood-generating processes. The different flood types are classified according to their meteorological causes. Their probability distributions are modelled by type-specific distribution functions which are combined into one statistical annual mixture model. For regionalisation, we specified the parameters of each type-specific probability distribution separately with hierarchical clustering and regressions from catchment attributes. By selection of the most relevant features, depending on the flood type, the specifics of flood-generating processes were considered. This approach offers a higher degree of freedom for regionalisation as it describes the relationships between catchment characteristics, meteorological causes of floods and response of watersheds. However, as for many regionalisation procedures, uncertainty is created by different observation periods of the gauged catchments used for regionalisation. Due to different observation periods, extreme events can be included in one sample, while for the neighboring catchment with shorter observation period this may not be the case. This stochastic uncertainty results in a heterogeneity of second and third moments which may bias the regionalization. We analyzed different scenarios to take into account this uncertainty and to include the information of long observation periods as well as the occurrence of extreme events for correcting the distribution parameters accordingly. This leads to more homogeneous regionalisation results.
Assessing the effects of urbanization on flood events using hydrological modelling: A case study of the Oued Fez urban catchment (Morocco)
Authors: Bouizrou Ismail , Chahinian Nanée , Perrin Jean-Louis , Müller Remy , Rais Naoual
Published: September 2022

Urban catchments are very complex systems due to urban development. In these contexts, the intense urban expansion induces local changes in the hydrological cycle and increases flood risk by extending impervious surfaces and altering the natural watercourses. Therefore, modelling them is a challenging task specially in data-sparse regions. Indeed, a compromise has to be reached to take into account the heterogeneity while avoiding over parameterisation. The Oued Fez catchment located in the northern part of Morocco is a typical example of urban catchments: its land cover is highly heterogeneous and has channelised water courses. In this work, the ATHYS modelling platform is used to simulate 59 selected flood events monitored on the urban and peri-urban parts of the Oued Fez catchment over the 2008-2018 periods. Two production functions, SCS (Soil Conservation Service) and a linear reservoir are combined with the lag and route transfer function. The drainage network is derived based on a high-resolution Digital Elevation Model (Source Dem from ALOS PALSAR RTC, https://asf,alaska,edu/datasets/sar-data-sets/alos-palsar/, 12,5m resolution). The road network is used as a proxy of the stormwater network to force the drainage directions along the motorways and three types of land use classes are used to parameterize the two production functions. Tests are carried out at hourly and sub-hourly time steps using both the natural and modified drainage networks. The main results show that using the road network and minimal land use classes improves model performance. The field data also shows that despite lower rainfall values, the highest peak flow values are recorded in 2017/2018.  This is due to stream channelisation and increased stormwater network coverage.

Keywords: Hydrological modelling; Flood events; Urbanization; Distributed hydrological models; ATHYS, Data-scarce regions ; Oued Fez catchment.
Impact of changing climate on thawing and snowmelt-driven gully erosion in Eastern Romania
Authors: Niacsu Lilian , Ionita Ion , Poesen Jean
Published: September 2022

Gully erosion has been recognized as an important environmental threat in the Moldavian Plateau of Eastern Romania. The main objective of this study was to better understand gully development by providing quantitative information from long-term field measurements in small catchments over a 60 year period (1961-2020). Several methods were used to accurately measure and estimate gully growth.

Intense gully erosion has sculptured remarkable landforms around the town of Barlad. The permanent gully systems consist of two main gully types, discontinuous and large continuous gullies in valley bottoms. The discontinuous gullies are associated with small catchments (usually <100 ha in area) and ephemeral peak runoff discharges are usually ≤2 m3 s-1.

Fourteen representative continuous gullies were selected, most of them having catchment areas <500 ha. Linear gully head retreat and areal gully growth rates were quantified for six decades. The results obtained indicate that gully erosion rates have decreased since 1960s (i.e. 19.5 m yr-1 linear gully head retreat) to 3.2 m yr-1 during last decade.

Gully growth is believed to be mainly triggered by severe rainstorms and resultant runoff events. However, the impact of late winter (especially thawing and snowmelt runoff) on gully development is often overlooked.  Mean annual air temperature at Barlad (Romania) is 10.2oC and means annual precipitation is 508 mm (1961-2020), of which 35% falls during the cold season (October-March). Multiple annual field measurements on the growth of six continuous gullies between 1981-2000 indicate that half of the mean gully growth occurred in the cold season (in late winter, mainly in March).Based on data collected from different locations in the temperate zone of the Northern Hemisphere, it is possible to postulate that the relative contribution of the cold season to the gully development is highly variable and is closely related to climatic conditions. Thus, the contribution is very small in north-east China, ~25% in western Iowa (USA), ~50% in the Barlad Plateau (eastern Romania) and ~67% in the Middle Volga region (Russian Federation).
Low-flow forecasting in France using the PREMHYCE operational platform: recent advances and perspectives
Authors: Tilmant François , Bourgin François , Véron Anne-Lise , Rousset Fabienne , Willemet Jean-Marie , François Didier , Le Lay Matthieu , Vergnes Jean-Pierre , Perrin Charles , Magand Claire , Morel Mathilde
Published: September 2022

In many countries, rivers are the primary supply of water. A number of uses are concerned (drinking water, irrigation, hydropower…) and can be strongly affected by water shortages. Therefore, there is a need of early anticipation of low-flow periods to improve water management. This is strengthened by the perspective of having more severe summer low-flows in the context of climate change. Several French institutes (BRGM, EDF, INRAE, Lorraine University and Météo-France) have been collaborating to develop an operational tool for low-flow forecasting, called PREMHYCE (Tilmant et al., 2020). This platform produces forecasts in real time on more than 900 catchments in metropolitan France since 2017, in cooperation with French operational services of water management. PREMHYCE includes five hydrological models which can be calibrated on gauged catchments and which assimilate flow observations. Low-flow forecasts based on ensemble streamflow prediction (ESP) can be issued up to either 15 days ahead, based on scenarios from the European Centre for Medium-Range Weather Forecasts (ECMWF) or 90 days ahead, using historical climatic data as ensembles of future input scenarios. These climatic data (precipitation and temperature) are provided by Météo-France with the daily gridded SAFRAN reanalysis on the 1958-2020 period, which includes a wide range of conditions. Outputs from the different hydrological models are combined into a simple multi-model approach to improve robustness of the forecasts. The tool provides text files and graphical representation of forecasted low-flows, and probability to be under low-flow thresholds provided by users. In 2020, a website has been developed allowing easier access to the forecasts for users. The presentation will show the main characteristics of this operational tool and results on the recent low-flow periods.

 

Keywords: low-flow forecasting, hydrological model, ensemble streamflow prediction, water resource management

Reference
Tilmant, F., Nicolle, P., Bourgin, F., Besson, F., Delaigue, O., Etchevers, P., François, D., Le Lay, M., Perrin, C., Rousset, F., Thiéry, D., Magand, C., Leurent, T., Jacob, E., 2020: PREMHYCE: an operational tool for low-flow forecasting, La Houille Blanche (5) 37-44, DOI: 10.1051/lhb/2020043
The Effect of Water Vapor Originating from Land on the 2018 Drought Development in Europe
Authors: Al Hasan Fares , van der Ent Ruud , Link Andreas
Published: September 2022

The 2018 summer drought in Europe was particularly extreme in terms of intensity and impact due to the combination of low rainfall and high temperatures. However, it remains unclear how this drought developed in time and space in such an extreme way. In this study we aimed to get a better understanding of the role of land-atmosphere interactions. More specifically, we investigated whether there was a change in water vapor originating from land, if that caused a reduction in rainfall, and by this mechanism possibly the propagation and intensification of the drought in Europe. We used a global gridded dataset of the fate of land evaporation (i.e., where it ends up as precipitation) to investigate whether the drought intensification and propagation was impacted by the reduction in water vapor transported from the regions that first experienced the drought. It was found that during the onset phase of the 2018 drought in Europe that the water vapor originating from land played an important role in mitigating the precipitation anomalies as, for example, the share of land evaporation contributing to precipitation increased from 27% (normal years) to 38% (2018) during July in West of Europe. Land evaporation played a minor role in amplifying it during the intensification phase of the drought as the share of land evaporation contribution to precipitation decreased from 23% (normal years) to 21% (2018) during August in West of Europe. These findings are somewhat in contrast to similar studies in other continents that found the land surface to play a strong amplifying role for drought development. These results were recently published here: https://doi.org/10.3390/w13202856. Speculating what this case study means for future extreme droughts in Europe, we can at least conclude that for West of Europe the positive feedback loop between drought, soil moisture, vegetation, evaporation and precipitation is still weak even under extreme circumstances, and that probably quite a severe climate changes scenario would be needed to change this.
Characteristics and process controls of statistical flood moments in Europe - a data-based analysis
Authors: Lun David , Viglione Alberto , Bertola Miriam , Komma Jürgen , Parajka Juraj , Valent Peter , Blöschl Günter
Published: September 2022

Recent studies have sought to characterize variations of the annual maximum flood discharge series over time and across space in Europe. To further support these studies, we conduct a pan-European assessment of process controls on key statistical properties of these series, including the mean annual flood (MAF), coefficient of variation (CV) and skewness (CS) of flood discharges. We analyse annual maximum flood discharge series from 2370 catchments in Europe without strong human modifications covering the period 1960-2010. We explore how the estimated moments MAF, CV and CS vary due to catchment size, climate and other controls across Europe.

The process controls on the flood moments are identified through correlation and multiple linear regression analyses and the interpretation is aided by a seasonality analysis. Precipitation-related covariates are found to be the main controls of the spatial patterns of MAF in most of Europe except for regions in which snowmelt contributes to MAF, where air temperature is more important. The Aridity Index is, by far, the most important control on the spatial pattern of CV in all of Europe. Overall, the findings suggest that, at the continental scale, climate variables dominate over land surface characteristics, such as land use and soil type, in controlling the spatial patterns of flood moments.

Finally, to provide a performance baseline for more local studies, we assess the estimation accuracy of regional multiple linear regression models for estimating flood moments in ungauged basins.