TY - JOUR A1 - Carvalho, Thayslan A1 - Brosinsky, Arlena A1 - Foerster, Saskia A1 - Teixeira, Adunias A1 - Medeiros, Pedro Henrique Augusto T1 - Reservoir sediment characterisation by diffuse reflectance spectroscopy in a semiarid region to support sediment reuse for soil fertilization JF - Journal of soils and sediments : protection, risk assessment and remediation N2 - Purpose: Soil erosion by water yields sediment to surface reservoirs, reducing their storage capacities, changing their geometry, and degrading water quality. Sediment reuse, i.e., fertilization of agricultural soils with the nutrient-enriched sediment from reservoirs, has been proposed as a recovery strategy. However, the sediment needs to meet certain criteria. In this study, we characterize sediments from the densely dammed semiarid Northeast Brazil by VNIR-SWIR spectroscopy and assess the effect of spectral resolution and spatial scale on the accuracy of N, P, K, C, electrical conductivity, and clay prediction models. Methods Sediment was collected in 10 empty reservoirs, and physical and chemical laboratory analyses as well as spectral measurements were performed. The spectra, initially measured at 1 nm spectral resolution, were resampled to 5 and 10 nm, and samples were analysed for both high and low spectral resolution at three spatial scales, namely (1) reservoir, (2) catchment, and (3) regional scale. Results Partial least square regressions performed from good to very good in the prediction of clay and electrical conductivity from reservoir (<40 km(2)) to regional (82,500 km(2)) scales. Models for C and N performed satisfactorily at the reservoir scale, but degraded to unsatisfactory at the other scales. Models for P and K were more unstable and performed from unsatisfactorily to satisfactorily at all scales. Coarsening spectral resolution by up to 10 nm only slightly degrades the models' performance, indicating the potential of characterizing sediment from spectral data captured at lower resolutions, such as by hyperspectral satellite sensors. Conclusion: By reducing the costly and time-consuming laboratory analyses, the method helps to promote the sediment reuse as a practice of soil and water conservation. KW - Sediment characterization KW - Spectroscopy KW - Sediment reuse KW - Surface KW - reservoirs KW - Semiarid KW - Brazil Y1 - 2022 U6 - https://doi.org/10.1007/s11368-022-03281-1 SN - 1439-0108 SN - 1614-7480 VL - 22 SP - 2557 EP - 2577 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Cabieces, Roberto A1 - Olivar‐Castaño, Andrés A1 - Junqueira, Thiago C. A1 - Relinque, Jesús A1 - Fernandez-Prieto, Luis M. A1 - Vackár, Jiří A1 - Rösler, Boris A1 - Barco, Jaime A1 - Pazos, Antonio A1 - García‐Martínez, Luz T1 - Integrated Seismic Program (ISP): A new Python GUI-based software for earthquake seismology and seismic signal processing JF - Seismological research letters N2 - Integrated Seismic Program (ISP) is a graphical user interface designed to facilitate and provide a user-friendly framework for performing diverse common and advanced tasks in seismological research. ISP is composed of five main modules for earthquake location, time-frequency analysis and advanced signal processing, implementation of array techniques to estimate the slowness vector, seismic moment tensor inversion, and receiver function computation and analysis. In addition, several support tools are available, allowing the user to create an event database, download data from International Federation of Digital Seismograph Networks services, inspect the background noise, and compute synthetic seismograms. ISP is written in Python3, supported by several open-source and/or publicly available tools. Its modular design allows for new features to be added in a collaborative development environment. Y1 - 2022 U6 - https://doi.org/10.1785/0220210205 SN - 0895-0695 SN - 1938-2057 VL - 93 IS - 3 SP - 1895 EP - 1908 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Böhnke, Denise A1 - Krehl, Alice A1 - Moermann, Kai A1 - Volk, Rebekka A1 - Lützkendorf, Thomas A1 - Naber, Elias A1 - Becker, Ronja A1 - Norra, Stefan T1 - Mapping urban green and its ecosystem services at microscale-a methodological approach for climate adaptation and biodiversity JF - Sustainability / Multidisciplinary Digital Publishing Institute (MDPI) N2 - The current awareness of the high importance of urban green leads to a stronger need for tools to comprehensively represent urban green and its benefits. A common scientific approach is the development of urban ecosystem services (UES) based on remote sensing methods at the city or district level. Urban planning, however, requires fine-grained data that match local management practices. Hence, this study linked local biotope and tree mapping methods to the concept of ecosystem services. The methodology was tested in an inner-city district in SW Germany, comparing publicly accessible areas and non-accessible courtyards. The results provide area-specific [m(2)] information on the green inventory at the microscale, whereas derived stock and UES indicators form the basis for comparative analyses regarding climate adaptation and biodiversity. In the case study, there are ten times more micro-scale green spaces in private courtyards than in the public space, as well as twice as many trees. The approach transfers a scientific concept into municipal planning practice, enables the quantitative assessment of urban green at the microscale and illustrates the importance for green stock data in private areas to enhance decision support in urban development. Different aspects concerning data collection and data availability are critically discussed. KW - climate adaptation KW - urban green KW - mapping KW - ecosystem service cascade KW - model KW - surface type-function-concept KW - planning indicators KW - city district KW - level KW - urban planning practice KW - climate change Y1 - 2022 U6 - https://doi.org/10.3390/su14159029 SN - 2071-1050 VL - 14 IS - 15 PB - MDPI CY - Basel ER - TY - JOUR A1 - Buter, Anuschka A1 - Heckmann, Tobias A1 - Filisetti, Lorenzo A1 - Savi, Sara A1 - Mao, Luca A1 - Gems, Bernhard A1 - Comiti, Francesco T1 - Effects of catchment characteristics and hydro-meteorological scenarios on sediment connectivity in glacierised catchments JF - Geomorphology : an international journal on pure and applied geomorphology N2 - In the past decade, sediment connectivity has become a widely recognized characteristic of a geomorphic system. However, the quantification of functional connectivity (i.e. connectivity which arises due to the actual occurrence of sediment transport processes) and its variation over space and time is still a challenge. In this context, this study assesses the effects of expected future phenomena in the context of climate change (i.e. glacier retreat, permafrost degradation or meteorological extreme events) on sediment transport dynamics in a glacierised Alpine basin. The study area is the Sulden river basin (drainage area 130 km(2)) in the Italian Alps, which is composed of two geomorphologically diverse sub-basins. Based on graph theory, we evaluated the spatio-temporal variations in functional connectivity in these two sub-basins. The graph-object, obtained by manually mapping sediment transport processes between landforms, was adapted to 6 different hydro-meteorological scenarios, which derive from combining base, heatwave and rainstorm conditions with snowmelt and glacier-melt periods. For each scenario and each sub-basin, the sediment transport network and related catchment characteristics were analysed. To compare the effects of the scenarios on functional connectivity, we introduced a connectivity degree, calculated based on the area of the landforms involved in sediment cascades. Results indicate that the area of the basin connected to its outlet in terms of sediment transport might feature a six-fold increase in case of rainstorm conditions compared to "average " meteorological conditions assumed for the base scenario. Furthermore, markedly different effects of climate change on sediment connectivity are expected between the two sub-catchments due to their contrasting morphological and lithological characteristics, in terms of relative importance of rainfall triggered colluvial processes vs temperature-driven proglacial fluvial dynamics. KW - Functional connectivity KW - Graph theory KW - Climate change KW - Geomorphic systems Y1 - 2022 U6 - https://doi.org/10.1016/j.geomorph.2022.108128 SN - 0169-555X SN - 1872-695X VL - 402 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Bufe, Aaron A1 - Cook, Kristen L. A1 - Galy, Albert A1 - Wittmann, Hella A1 - Hovius, Niels T1 - The effect of lithology on the relationship between denudation rate and chemical weathering pathways BT - evidence from the eastern Tibetan Plateau JF - Earth surface dynamics N2 - The denudation of rocks in mountain belts exposes a range of fresh minerals to the surface of the Earth that are chemically weathered by acidic and oxygenated fluids. The impact of the resulting coupling between denudation and weathering rates fundamentally depends on the types of minerals that are weathering. Whereas silicate weathering sequesters CO2, the combination of sulfide oxidation and carbonate dissolution emits CO2 to the atmosphere. Here, we combine the concentrations of dissolved major elements in stream waters with Be-10 basin-wide denudation rates from 35 small catchments in eastern Tibet to elucidate the importance of lithology in modulating the relationships between denudation rate, chemical weathering pathways, and CO2 consumption or release. Our catchments span 3 orders of magnitude in denudation rate in low-grade flysch, high-grade metapelites, and granitoid rocks. For each stream, we estimate the concentrations of solutes sourced from silicate weathering, carbonate dissolution, and sulfide oxidation using a mixing model. We find that for all lithologies, cation concentrations from silicate weathering are largely independent of denudation rate, but solute concentrations from carbonates and, where present, sulfides increase with increasing denudation rate. With increasing denudation rates, weathering may therefore shift from consuming to releasing CO2 in both (meta)sedimentary and granitoid lithologies. For a given denudation rate, we report dissolved solid concentrations and inferred weathering fluxes in catchments underlain by (meta)sedimentary rock that are 2-10 times higher compared to catchments containing granitoid lithologies, even though climatic and topographic parameters do not vary systematically between these catchments. Thus, varying proportions of exposed (meta)sedimentary and igneous rocks during orogenesis could lead to changes in the sequestration and release of CO2 that are independent of denudation rate. Y1 - 2022 U6 - https://doi.org/10.5194/esurf-10-513-2022 SN - 2196-6311 SN - 2196-632X VL - 10 IS - 3 SP - 513 EP - 530 PB - Copernicus CY - Göttingen ER - TY - THES A1 - Brill, Fabio Alexander T1 - Applications of machine learning and open geospatial data in flood risk modelling N2 - Der technologische Fortschritt erlaubt es, zunehmend komplexe Vorhersagemodelle auf Basis immer größerer Datensätze zu produzieren. Für das Risikomanagement von Naturgefahren sind eine Vielzahl von Modellen als Entscheidungsgrundlage notwendig, z.B. in der Auswertung von Beobachtungsdaten, für die Vorhersage von Gefahrenszenarien, oder zur statistischen Abschätzung der zu erwartenden Schäden. Es stellt sich also die Frage, inwiefern moderne Modellierungsansätze wie das maschinelle Lernen oder Data-Mining in diesem Themenbereich sinnvoll eingesetzt werden können. Zusätzlich ist im Hinblick auf die Datenverfügbarkeit und -zugänglichkeit ein Trend zur Öffnung (open data) zu beobachten. Thema dieser Arbeit ist daher, die Möglichkeiten und Grenzen des maschinellen Lernens und frei verfügbarer Geodaten auf dem Gebiet der Hochwasserrisikomodellierung im weiteren Sinne zu untersuchen. Da dieses übergeordnete Thema sehr breit ist, werden einzelne relevante Aspekte herausgearbeitet und detailliert betrachtet. Eine prominente Datenquelle im Bereich Hochwasser ist die satellitenbasierte Kartierung von Überflutungsflächen, die z.B. über den Copernicus Service der Europäischen Union frei zur Verfügung gestellt werden. Große Hoffnungen werden in der wissenschaftlichen Literatur in diese Produkte gesetzt, sowohl für die akute Unterstützung der Einsatzkräfte im Katastrophenfall, als auch in der Modellierung mittels hydrodynamischer Modelle oder zur Schadensabschätzung. Daher wurde ein Fokus in dieser Arbeit auf die Untersuchung dieser Flutmasken gelegt. Aus der Beobachtung, dass die Qualität dieser Produkte in bewaldeten und urbanen Gebieten unzureichend ist, wurde ein Verfahren zur nachträglichenVerbesserung mittels maschinellem Lernen entwickelt. Das Verfahren basiert auf einem Klassifikationsalgorithmus der nur Trainingsdaten von einer vorherzusagenden Klasse benötigt, im konkreten Fall also Daten von Überflutungsflächen, nicht jedoch von der negativen Klasse (trockene Gebiete). Die Anwendung für Hurricane Harvey in Houston zeigt großes Potenzial der Methode, abhängig von der Qualität der ursprünglichen Flutmaske. Anschließend wird anhand einer prozessbasierten Modellkette untersucht, welchen Einfluss implementierte physikalische Prozessdetails auf das vorhergesagte statistische Risiko haben. Es wird anschaulich gezeigt, was eine Risikostudie basierend auf etablierten Modellen leisten kann. Solche Modellketten sind allerdings bereits für Flusshochwasser sehr komplex, und für zusammengesetzte oder kaskadierende Ereignisse mit Starkregen, Sturzfluten, und weiteren Prozessen, kaum vorhanden. Im vierten Kapitel dieser Arbeit wird daher getestet, ob maschinelles Lernen auf Basis von vollständigen Schadensdaten einen direkteren Weg zur Schadensmodellierung ermöglicht, der die explizite Konzeption einer solchen Modellkette umgeht. Dazu wird ein staatlich erhobener Datensatz der geschädigten Gebäude während des schweren El Niño Ereignisses 2017 in Peru verwendet. In diesem Kontext werden auch die Möglichkeiten des Data-Mining zur Extraktion von Prozessverständnis ausgelotet. Es kann gezeigt werden, dass diverse frei verfügbare Geodaten nützliche Informationen für die Gefahren- und Schadensmodellierung von komplexen Flutereignissen liefern, z.B. satellitenbasierte Regenmessungen, topographische und hydrographische Information, kartierte Siedlungsflächen, sowie Indikatoren aus Spektraldaten. Zudem zeigen sich Erkenntnisse zu den Schädigungsprozessen, die im Wesentlichen mit den vorherigen Erwartungen in Einklang stehen. Die maximale Regenintensität wirkt beispielsweise in Städten und steilen Schluchten stärker schädigend, während die Niederschlagssumme in tiefliegenden Flussgebieten und bewaldeten Regionen als aussagekräftiger befunden wurde. Ländliche Gebiete in Peru weisen in der präsentierten Studie eine höhere Vulnerabilität als die Stadtgebiete auf. Jedoch werden auch die grundsätzlichen Grenzen der Methodik und die Abhängigkeit von spezifischen Datensätzen and Algorithmen offenkundig. In der übergreifenden Diskussion werden schließlich die verschiedenen Methoden – prozessbasierte Modellierung, prädiktives maschinelles Lernen, und Data-Mining – mit Blick auf die Gesamtfragestellungen evaluiert. Im Bereich der Gefahrenbeobachtung scheint eine Fokussierung auf neue Algorithmen sinnvoll. Im Bereich der Gefahrenmodellierung, insbesondere für Flusshochwasser, wird eher die Verbesserung von physikalischen Modellen, oder die Integration von prozessbasierten und statistischen Verfahren angeraten. In der Schadensmodellierung fehlen nach wie vor die großen repräsentativen Datensätze, die für eine breite Anwendung von maschinellem Lernen Voraussetzung ist. Daher ist die Verbesserung der Datengrundlage im Bereich der Schäden derzeit als wichtiger einzustufen als die Auswahl der Algorithmen. N2 - Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail. A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask. Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious. In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms. KW - flood risk KW - machine learning KW - open data KW - damage modelling KW - data-mining KW - Schadensmodellierung KW - Data-Mining KW - Hochwasserrisiko KW - maschinelles Lernen KW - offene Daten Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-555943 ER - TY - JOUR A1 - Braun, Jean T1 - Comparing the transport-limited and ξ-q models for sediment transport JF - Earth surface dynamics N2 - Here I present a comparison between two of the most widely used reduced-complexity models for the representation of sediment transport and deposition processes, namely the transport-limited (or TL) model and the under-capacity (or xi-q) model more recently developed by Davy and Lague (2009). Using both models, I investigate the behavior of a sedimentary continental system of length L fed by a fixed sedimentary flux from a catchment of size A(0) in a nearby active orogen through which sediments transit to a fixed base level representing a large river, a lake or an ocean. This comparison shows that the two models share the same steady-state solution, for which I derive a simple 1D analytical expression that reproduces the major features of such sedimentary systems: a steep fan that connects to a shallower alluvial plain. The resulting fan geometry obeys basic observational constraints on fan size and slope with respect to the upstream drainage area, A(0). The solution is strongly dependent on the size of the system, L, in comparison to a distance L-0, which is determined by the size of A(0), and gives rise to two fundamentally different types of sedimentary systems: a constrained system where L < L-0 and open systems where L > L-0. I derive simple expressions that show the dependence of the system response time on the system characteristics, such as its length, the size of the upstream catchment area, the amplitude of the incoming sedimentary flux and the respective rate parameters (diffusivity or erodibility) for each of the two models. I show that the xi-q model predicts longer response times. I demonstrate that although the manner in which signals propagates through the sedimentary system differs greatly between the two models, they both predict that perturbations that last longer than the response time of the system can be recorded in the stratigraphy of the sedimentary system and in particular of the fan. Interestingly, the xi-q model predicts that all perturbations in the incoming sedimentary flux will be transmitted through the system, whereas the TL model predicts that rapid perturbations cannot. I finally discuss why and under which conditions these differences are important and propose observational ways to determine which of the two models is most appropriate to represent natural systems. Y1 - 2022 U6 - https://doi.org/10.5194/esurf-10-301-2022 SN - 2196-6311 SN - 2196-632X VL - 10 IS - 2 SP - 301 EP - 327 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Blanchard, Ingrid A1 - Petitgirard, Sylvain A1 - Laurenz, Vera A1 - Miyajima, Nobuyoshi A1 - Wilke, Max A1 - Rubie, David C. A1 - Lobanov, Sergey S. A1 - Hennet, Louis A1 - Morgenroth, Wolfgang A1 - Tucoulou, Rémi A1 - Bonino, Valentina A1 - Zhao, Xuchao A1 - Franchi, Ian T1 - Chemical analysis of trace elements at the nanoscale in samples recovered from laser-heated diamond anvil cell experiments JF - Physics and chemistry of minerals N2 - High pressure and high temperature experiments performed with laser-heated diamond anvil cells (LH-DAC) are being extensively used in geosciences to study matter at conditions prevailing in planetary interiors. Due to the size of the apparatus itself, the samples that are produced are extremely small, on the order of few tens of micrometers. There are several ways to analyze the samples and extract physical, chemical or structural information, using either in situ or ex situ methods. In this paper, we compare two nanoprobe techniques, namely nano-XRF and NanoSIMS, that can be used to analyze recovered samples synthetized in a LH-DAC. With these techniques, it is possible to extract the spatial distribution of chemical elements in the samples. We show the results for several standards and discuss the importance of proper calibration for the acquisition of quantifiable results. We used these two nanoprobe techniques to retrieve elemental ratios of dilute species (few tens of ppm) in quenched experimental molten samples relevant for the formation of the iron-rich core of the Earth. We finally discuss the applications of such probes to constrain the partitioning of trace elements between metal and silicate phases, with a focus on moderately siderophile elements, tungsten and molybdenum. KW - NanoSIMS KW - Nano-XRF KW - Diamond anvil cell KW - Focused ion beam Y1 - 2022 U6 - https://doi.org/10.1007/s00269-022-01193-7 SN - 0342-1791 SN - 1432-2021 VL - 49 IS - 6 PB - Springer CY - New York ER - TY - JOUR A1 - Berner, Nadine A1 - Trauth, Martin H. A1 - Holschneider, Matthias T1 - Bayesian inference about Plio-Pleistocene climate transitions in Africa JF - Quaternary science reviews : the international multidisciplinary research and review journal N2 - During the last 5 Ma the Earth's ocean-atmosphere system passed through several major transitions, many of which are discussed as possible triggers for human evolution. A classic in this context is the possible influence of the closure of the Panama Strait, the intensification of Northern Hemisphere Glaciation, a stepwise increase in aridity in Africa, and the first appearance of the genus Homo about 2.5 - 2.7 Ma ago. Apart from the fact that the correlation between these events does not necessarily imply causality, many attempts to establish a relationship between climate and evolution fail due to the challenge of precisely localizing an a priori unknown number of changes potentially underlying complex climate records. The kernel-based Bayesian inference approach applied here allows inferring the location, generic shape, and temporal scale of multiple transitions in established records of Plio-Pleistocene African climate. By defining a transparent probabilistic analysis strategy, we are able to identify conjoint changes occurring across the investigated terrigenous dust records from Ocean Drilling Programme (ODP) sites in the Atlantic Ocean (ODP 659), Arabian (ODP 721/722) and Mediterranean Sea (ODP 967). The study indicates a two-step transition in the African climate proxy records at (2.35-2.10) Ma and (1.70 - 1.50) Ma, that may be associated with the reorganization of the Hadley-Walker Circulation. . KW - Plio-Pleistocene KW - Hadley-Walker Circulation KW - climate transition KW - Bayesian inference KW - time series analysis KW - ODP 659 KW - ODP 721/722 KW - ODP 967 Y1 - 2022 U6 - https://doi.org/10.1016/j.quascirev.2021.107287 SN - 0277-3791 SN - 1873-457X VL - 277 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Ben Nsir, Siwar A1 - Jomaa, Seifeddine A1 - Yildirim, Umit A1 - Zhou, Xiangqian A1 - D'Oria, Marco A1 - Rode, Michael A1 - Khlifi, Slaheddine T1 - Assessment of climate change impact on discharge of the lakhmass catchment (Northwest Tunisia) JF - Water N2 - The Mediterranean region is increasingly recognized as a climate change hotspot but is highly underrepresented in hydrological climate change studies. This study aims to investigate the climate change effects on the hydrology of Lakhmass catchment in Tunisia. Lakhmass catchment is a part of the Medium Valley of Medjerda in northwestern Tunisia that drains an area of 126 km(2). First, the Hydrologiska Byrans Vattenbalansavdelning light (HBV-light) model was calibrated and validated successfully at a daily time step to simulate discharge during the 1981-1986 period. The Nash Sutcliffe Efficiency and Percent bias (NSE, PBIAS) were (0.80, +2.0%) and (0.53, -9.5%) for calibration (September 1982-August 1984) and validation (September 1984-August 1986) periods, respectively. Second, HBV-light model was considered as a predictive tool to simulate discharge in a baseline period (1981-2009) and future projections using data (precipitation and temperature) from thirteen combinations of General Circulation Models (GCMs) and Regional Climatic Models (RCMs). We used two trajectories of Representative Concentration Pathways, RCP4.5 and RCP8.5, suggested by the Intergovernmental Panel on Climate Change (IPCC). Each RCP is divided into three projection periods: near-term (2010-2039), mid-term (2040-2069) and long-term (2070-2099). For both scenarios, a decrease in precipitation and discharge will be expected with an increase in air temperature and a reduction in precipitation with almost 5% for every +1 degrees C of global warming. By long-term (2070-2099) projection period, results suggested an increase in temperature with about 2.7 degrees C and 4 degrees C, and a decrease in precipitation of approximately 7.5% and 15% under RCP4.5 and RCP8.5, respectively. This will likely result in a reduction of discharge of 12.5% and 36.6% under RCP4.5 and RCP8.5, respectively. This situation calls for early climate change adaptation measures under a participatory approach, including multiple stakeholders and water users. KW - hydrological modeling KW - HBV-light model KW - Mediterranean KW - discharge KW - climate change KW - RCP4,5 and 8,5 Y1 - 2022 U6 - https://doi.org/10.3390/w14142242 SN - 2073-4441 VL - 14 IS - 14 PB - MDPI CY - Basel ER -