Water and sediment fluxes in Mediterranean mountainous regions: comprehensive  dataset for hydro-sedimentological analyses and modelling in a mesoscale catchment (River Isábena, NE Spain)

Francke, Till; Foerster, Saskia; Brosinsky, Arlena; Sommerer, Erik; López‐Tarazón, José A.; Güntner, Andreas; Batalla, Ramón J.; Bronstert, Axel

doi:10.5194/essd-10-1063-2018

Cited by 5 publications

(5 citation statements)

References 26 publications

(28 reference statements)

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“…The Isábena catchment has been subject to intensive hydro‐sedimentological monitoring over the past decade (e.g., Bronstert et al, ), resulting in a favorable instrumentation situation (Figure ), which enabled testing the multidimensional analysis presented. The time‐series data used have been published and described by Francke et al ().…”

Section: Methodsmentioning

confidence: 99%

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What Did Really Improve Our Mesoscale Hydrological Model? A Multidimensional Analysis Based on Real Observations

Francke

Baroni

Brosinsky

et al. 2018

Water Resources Research

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Modelers can improve a model by addressing the causes for the model errors (data errors and structural errors). This leads to implementing model enhancements (MEs), for example, meteorological data based on more monitoring stations, improved calibration data, and/or modifications in process formulations. However, deciding on which MEs to implement remains a matter of expert knowledge. After implementing multiple MEs, any improvement in model performance is not easily attributed, especially when considering different objectives or aspects of this improvement (e.g., better dynamics vs. reduced bias). We present an approach for comparing the effect of multiple MEs based on real observations and considering multiple objectives (MMEMO). A stepwise selection approach and structured plots help to address the multidimensionality of the problem. Tailored analyses allow a differentiated view on the effect of MEs and their interactions. MMEMO is applied to a case study employing the mesoscale hydro‐sedimentological model WASA‐SED for the Mediterranean‐mountainous Isábena catchment, northeast Spain. The investigated seven MEs show diverse effects: some MEs (e.g., rainfall data) cause improvements for most objectives, while other MEs (e.g., land use data) only affect a few objectives or even decrease model performance. Interaction of MEs was observed for roughly half of the MEs, confirming the need to address them in the analysis. Calibration and increasing the temporal resolution showed by far stronger impact than any of the other MEs. The proposed framework can be adopted in other studies to analyze the effect of MEs and, thus, facilitate the identification and implementation of the most promising MEs for comparable cases.

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Section: Methodsmentioning

confidence: 99%

“…The model used data described in Francke et al (), also available in CUAHSI format via http://hiscentral.cuahsi.org/pub_network.aspx?n=5622 or Francke et al ().…”

Section: Data and Software Availability And Requirementsmentioning

confidence: 99%

What Did Really Improve Our Mesoscale Hydrological Model? A Multidimensional Analysis Based on Real Observations

Francke

Baroni

Brosinsky

et al. 2018

Water Resources Research

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“…But, what is expected to happen with vegetation dynamics in wet Mediterranean badlands? Current vegetation growth in wet badlands is limited no longer by water availability, as occurs in dry areas (Maestre et al, 2016), but by weathering processes associated to freeze–thaw cycles, particularly on north‐facing slopes, and by high erosion rates, preventing the natural regeneration of vegetation (Breton et al, 2016; Francke et al, 2018; Gallart et al, 2013b; Moreno‐de las Heras & Gallart, 2016). Climate scenarios and expected hydro‐geomorphological dynamics suggest a change in regolith dynamics, allowing the colonization and persistence of well‐developed biocrust communities that would contribute to reduce water erosion.…”

Section: Resultsmentioning

confidence: 99%

Mediterranean badlands: Their driving processes and climate change futures

Nadal‐Romero

Rodríguez‐Caballero

Chamizo

et al. 2021

Earth Surf Processes Landf

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Badlands are landforms that occur all over the World. In the Mediterranean region, badlands are found in both dry (arid and semi‐arid) and wet (subhumid and humid) environments, and are characterized by complex hydro‐geomorphological dynamics, high intense erosion processes and extreme sediment yield. Understanding the impact of Global Change is key to predict the on‐site and off‐site effects on badland dynamics, particularly its consequences on bedrock weathering, on sediment yield and delivery and on plant colonization. Here, conducting a systematic literature review, we analyzed an extensive database and identified the main climate‐drivers affecting the hydro‐geomorphological dynamics in Mediterranean badlands (based on non‐metric multidimensional scaling and structural equation modeling analysis). Later, we examined the main impacts expected from climate change forecasting in the near future, and we explored the interactions between badlands response to climate variation. In Mediterranean badlands, weathering processes are mainly related to wetting–drying cycles and freeze–thaw cycles in dry and wet badlands, respectively. In both environments, rainfall amount appears as the main driver for runoff response, and rainfall amount and rainfall intensity for erosion dynamics. Future climate scenarios forecast a decrease in annual rainfall, number of rainfall events and frost days, and in soil moisture, and an increase in rainfall intensity. These changes will have direct hydro‐geomorphological implications with direct and indirect effects on badland dynamics. This may result in a decrease in annual runoff in dry badlands, but the occurrence of more frequent extreme events would increase soil erosion and could negatively affect biological soil crust. In wet badlands, weathering and erosion processes may decrease, and a stabilization of the slopes, with consequently improved vegetation growth, may be expected. In addition, the forecasted changes must be taken into account, especially considering the possible off‐site effects of these extreme environments.

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“…In addition, the mountainous catchment consists of several subcatchments with varying hydrological and meteorological conditions, which provide different settings to apply the proposed framework of this study and investigate the influence of hydro‐meteorological conditions on the identification of model structures. Recorded time series data have recently been published and described by Francke, Foerster, et al (2018).…”

Section: Case Studymentioning

confidence: 99%

“…Meteorological and discharge data were obtained from the data set of Francke, Foerster, et al (2018). This includes rainfall data from 18 stations, temperature from nine stations, and solar radiation and air humidity data from two stations within or in close vicinity to the study area.…”

Section: Case Studymentioning

confidence: 99%

How to Tailor My Process‐Based Hydrological Model? Dynamic Identifiability Analysis of Flexible Model Structures

Pilz

Francke

Baroni

et al. 2020

Water Resources Research

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In the field of hydrological modeling, many alternative representations of natural processes exist. Choosing specific process formulations when building a hydrological model is therefore associated with a high degree of ambiguity and subjectivity. In addition, the numerical integration of the underlying differential equations and parametrization of model structures influence model performance. Identifiability analysis may provide guidance by constraining the a priori range of alternatives based on observations. In this work, a flexible simulation environment is used to build an ensemble of semidistributed, process‐based hydrological model configurations with alternative process representations, numerical integration schemes, and model parametrizations in an integrated manner. The flexible simulation environment is coupled with an approach for dynamic identifiability analysis. The objective is to investigate the applicability of the framework to identify the most adequate model. While an optimal model configuration could not be clearly distinguished, interesting results were obtained when relating model identifiability with hydro‐meteorological boundary conditions. For instance, we tested the Penman‐Monteith and Shuttleworth & Wallace evapotranspiration models and found that the former performs better under wet and the latter under dry conditions. Parametrization of model structures plays a dominant role as it can compensate for inadequate process representations and poor numerical solvers. Therefore, it was found that numerical solvers of high order of accuracy do often, though not necessarily, lead to better model performance. The proposed coupled framework proved to be a straightforward diagnostic tool for model building and hypotheses testing and shows potential for more in‐depth analysis of process implementations and catchment functioning.

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Water and sediment fluxes in Mediterranean mountainous regions: comprehensive dataset for hydro-sedimentological analyses and modelling in a mesoscale catchment (River Isábena, NE Spain)

Cited by 5 publications

References 26 publications

What Did Really Improve Our Mesoscale Hydrological Model? A Multidimensional Analysis Based on Real Observations

What Did Really Improve Our Mesoscale Hydrological Model? A Multidimensional Analysis Based on Real Observations

Mediterranean badlands: Their driving processes and climate change futures

How to Tailor My Process‐Based Hydrological Model? Dynamic Identifiability Analysis of Flexible Model Structures

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