P Borsa

S Arlyza

P H Barber

The phylogeography and taxonomy of a model-species complex, the blue-spotted maskray (formerly Neotrygon kuhlii): a short review

Keywords: Population genetics, phylogeny, stepwise colonization, Indo-West Pacific, conservation, obituary

The present paper reviews the phylogeography of an emblematic Indo-West Pacific stingray and aims at linking its taxonomic implications with conservation management. The blue spotted maskray was once understood to be a single species widely distributed in the Indo-West Pacific, from the Red Sea to Fiji and from southern Japan to New South Wales. Genetics have shown that it actually consists of a number of distinct lineages with parapatric distribution. Phylogenetic data suggest an evolutionary origin of this species complex in the southwestern Pacific in the Miocene. The blue-spotted maskray progressively colonized the Indo-West Pacific from the East to the West. The lineages in the western Coral Triangle and the Indian Ocean are the most recent. Against this updated taxonomic and phylogeographic background, there remains a need for research on the population dynamics and fisheries management of this increasingly threatened species complex. This paper is dedicated to the memory of Dr Irma S. Arlyza.

Obituary: Dr Irma S. Arlyza (1974-2019)

Dr. Irma S. Arlyza prematurely left us this year, and we would like to dedicate this paper to her memory. When one of us (P. Borsa) first met Irma at LIPI-P2O in Ancol in February 2008, she was a young researcher interested in the biology of the sharks and rays landed at ports throughout Indonesia. She desired to pursue a PhD program, to learn the theory and practice of molecular population genetics, and apply them to the phylogeographic study of Indonesia's sharks and rays. Irma subsequently began her PhD studies with P. Borsa focused on a limited number of stingray species, including the blue-spotted maskray Neotrygon kuhlii (then still a single nominal species assigned to the genus Dasyatis). This stingray is a geographically widespread, rather common shallow-water species, and is among the most commonly landed by shark and ray fishermen across Indonesia [1,2], making it an ideal study organism. Moreover, populations from the adjacent Java and Bali islands strongly differed in body size at first reproduction [1,2], and Australian geneticist R.D. Ward and co-authors had just reported an unusually high level of genetic divergence at the CO1 locus among populations of the blue-spotted maskray, indicating limited gene flow and potential cryptic species [3].

In the laboratory (Fig. 1) Irma was soon confronted to the problem of scoring a sufficient number of nuclear markers that would be reasonably polymorphic but also consistently scored across the geographic distribution of the species. It turned out that such ideal markers were excessively rare among the exonprimed intron markers she tested in the blue-spotted maskray. These difficulties led us to switch to molecular taxonomic investigations of the Himantura uarnak species complex as the core of her PhD project [START_REF] Borsa | Compte rendu de mission à Ancol et Cibinong[END_REF]. Irma had registered for S3 (the Indonesian PhD program) at Institut Pertanian Bogor (IPB). She obtained her S3 doctorate at IPB in 2013, based on her memoir entitled "Molecular identification of Himantura uarnak species complex (Batoidea: Dasyatidae) in Indonesia" [START_REF] Arlyza | Disertasi program pascasarjana[END_REF]. Meanwhile, the genetic data already produced in the blue-spotted maskray helped sorting out its intricate taxonomy. Deeply diverged lineages within the bluespotted maskray species complex were confirmed, explaining in part the difficulties encountered with PCRamplified intron markers.

Dr. Irma S. Arlyza was committed to understanding Indonesian marine biodiversity through field studies as well as the application of modern molecular tools. Her passion was the evolution and conservation of stingrays, the topic of her S3 thesis. While Irma largely studied marine fishes, she was also involved in international collaborations focused on understanding Indonesian marine biodiversity ranging from sea stars to snails and clownfish, and worked with a diversity of researchers, but particularly the late S.A. Karl and B.J. Wainwright, then S.A. Karl's PhD student at the Hawaii Institute of Marine Biology, and P.H. Barber of the University of California, Los Angeles. Nuclear-DNA markers were used on a series of shallow-water marine species collected throughout the geologically and ecologically complex Indo-Malay archipelago, to test hypotheses on the causes of genetic differentiation (e.g. [START_REF] Wainwright | [END_REF]). Irma used these international collaborations to help secure graduate training opportunities for other LIPI researchers, leaving a legacy of marine research in Indonesia that will hopefully continue well into the future.

Objectives

The Coral Triangle region has a high diversity of sharks and rays, including stingrays. Indonesia, the largest and most populous country in this region is also the world's top producer of sharks and rays [13]. Stingrays (Dasyatidae) represent nearly 40 000 tons annually, comprising over 40% of the total catch of sharks and rays in Indonesian waters, exceeding that of any other shark and ray family [14]. It is unlikely that such levels of exploitation, mostly unregulated and unmanaged, are sustainable [14][15][16]. Nearly two thirds of the shark and ray species occurring in the Indonesian seas are of conservation concern [17]. The biology and ecology of stingray species in this region of the world remain poorly studied, hampering effective management efforts. Yet, the blue-spotted maskray might be an exception. Drawing on previous work [1-4, 6, 8, 9, 18-24], the present paper aims at reviewing our current knowledge of the molecular phylogeography and taxonomy of the blue-spotted maskray. This should provide managers with some of the knowledge required to improve the conservation and fisheries management of this model-species complex.

Phylogeography

The blue-spotted maskray species complex has a wide geographic distribution. It occupies the entire tropical Indo-West Pacific, from the Red Sea to Fiji. The distribution includes all the eastern African coast from Djibouti to Mozambique, Madagascar, the Arabian Sea, the Sea of Oman and the Persian Gulf, the periphery of the Indian peninsula, the Gulf of Bengal and the Andaman Sea, southeastern Asia, the whole Indo-Malay-Philippine archipelago, Taiwan, the Japanese archipelago, the Micronesian islands and the whole Melanesia including West Papua, Papua New Guinea, the Solomon Islands, New Caledonia, Vanuatu, and Fiji. Around Australia, the blue-spotted maskray occurs all along the tropical coastline, from Western Australia to New South Wales.

Phylogenetic analyses provide important insights into the evolutionary relationships among the many lineages within this species complex. In a rooted phylogenetic tree, each node with descendants repre-sents the inferred most recent common ancestor of those descendants. Assuming a molecular clock, the depth of the node can be interpreted as an estimate of time since divergence. M. Puckridge and co-authors proposed a bayesian time-tree of species and lineages of the stingray family (Dasyatidae) based on CO1, 16S and RAG-1 sequences. The tree was calibrated using the oldest known dasyatid fossil, which was dated from the early Cretaceous [19]. The authors inferred the age of the last common ancestor to all blue-spotted maskrays to be in the Miocene, approximately 15.7 My (22-8 My) ago. This date coincides with the development of modern coral reef communities in the central Indo-West Pacific, including the Coral Sea [25]. Puckridge et al. [19] identified nine deeply divergent clades within the blue-spotted maskray, five of which had been detected previously [3,18]). Additional clades were found by Arlyza et al. [6,21]. The first split within the blue-spotted maskray species complex separated the New Caledonian maskray N. trigonoides from the remaining clades [21]. The next deeper node separated the haplogroup from West Papua, which is northwest to the Coral Sea, followed by a Moluccan lineage (immediately west of West Papua) from the remaining clades. The remainder of the lineages combined into a single sub-tree that includes all lineages west of the Moluccas. This phylogenetic pattern suggests that this lineage originated in the easternmost part of the species' distribution, followed by a repeated pattern of westward range expansion and divergence (Fig. 2) giving rise to its present Indo-West Pacific distribution. Differentiation among these groups was likely heightened through genetic drift, resulting from repeated population crashes and expansions [21,24] associated with Pleistocene sea level fluctuations.

Integrating the phylogenetic results with the geographic distribution of the different lineages shows a parapatric distribution (Fig. 2). "Parapatry" is the term used to describe a situation where pairs of taxa present separate but contiguous geographic distributions [27], and in the case of this species complex indicates reproductive isolation [27]. This result in turn confirms that the different lineages are distinct species. Indeed, reproductive isolation is one of the most obvious properties of a species, which distinguishes it from another species [28].

Molecular taxonomy

In their description of the blue-spotted maskray (as Trygon kuhlii), Müller and Henle included the drawing of an individual which they may have believed (erroneously so) was from Java, part of the East Indies then confused with India, which they designated as the type locality of the species [START_REF] Müller | Systematische Beschreibung der Plagiostomen, mit sechzig Steindrucktafeln[END_REF]. The type series comprised four specimens: one presumably from Java, whose whereabouts are to this date uncertain; one from West Papua collected during the 1826-1829 Astrolabe expedition; and two from Vanikoro, also collected by the Astrolabe expedition but already described by J.R.C. Quoy and J.P. Gaimard (as the "blue ray" Raia coerulea), something Müller and Henle were apparently unaware of [20]. The one syntype of N. kuhlii that was eventually chosen as lectotype by P.R. Last and co-authors [22] was one of the two specimens from Vanikoro. Both the lectotype and a specimen represented in watercolour by Quoy possess colour patterns that designate a species different from Müller and Henle's [START_REF] Müller | Systematische Beschreibung der Plagiostomen, mit sechzig Steindrucktafeln[END_REF] original description. Quoy and Gaimard's blue ray differs from Müller and Henle's description by the presence of a pair of darker blotches in the scapular region and a number of dark speckles all over the dorsal side. A detailed account of the taxonomic history of the species, which is marked with neglect, confusion and error, has been published [20,24]. Molecular genetics have provided evidence that the blue-spotted maskray consists of a complex of cryptic species [3,4,6,8,9,17,18,20,22]. Presently, the species complex nominally includes N. trigonoides, which inhabits the Coral Sea, and N. kuhlii, which might be a synonym because its colour patterns are similar to those of N. trigonoides [9,29]. The distribution of N. kuhlii is presently considered to be restricted to the single island of Vanikoro in the Santa Cruz archipelago. Three other species were described in 2016 [22]. These are N. australiae from northern Australia, N. caeruleopunctata from southern Bali and southern Java, and N. orientale whose distribution spans a wide archipelagic region that extends from the Java Sea to the Philippines (Fig. 2). While there is clear genetic support to recognizing these three species, their authors chose to describe them based on a series of morphological traits [22], none of which were diagnostic [8,23]. One species, N. varidens from the South China Sea earlier described by S. Garman [30] was resurrected [22]. Six additional species were described subsequently, including N. bobwardi from western Sumatra and Aceh, named after R. D. Ward as an acknowledgement of his early contribution to the taxonomy of the blue-spotted maskray [8], N. indica from the Indian Ocean [31], N. malaccensis from the Malacca strait [8], N. moluccensis from the Banda Sea [8], N. vali from the Solomon archipelago [23], and N. westpapuensis from Biak [8].

The latter six species were described mainly based on their DNA sequences. We also used spot patterns as a proxy of genetics, to distinguish N. vali from N. kuhlii. The other species were similarly re-described based on DNA sequences, except N. kuhlii for which no DNA sequence is yet available. Given that morphological data used to date have been unreliable and non-diagnostic (e.g. [22]), further advancing our understanding of the taxonomy of this group would be aided greatly by DNA sequence data [8,23,31].

Perspectives

Future genetic analyses may help uncover the genetic relationships of N. kuhlii to N. trigonoides and to other blue-spotted maskray lineages occurring in adjacent regions, including N. vali [23], whose holotype had been erroneously assigned to N. kuhlii by Last et al. [22] despite clear-cut morphological differences [20,23]. Sequencing the DNA of the alcohol-preserved lectotype of N. kuhlii might be helpful in this respect.

Suggestions for future research on the blue-spotted maskray species complex include the role played by geological and palaeoceanographic events in the differentiation of species and the demographic history of each of the species in the complex. The parapatric distribution of species, to be maintained, implies some reproductive isolation mechanism that deserves more scrutiny. Pre-zygotic isolation mechanisms may include interspecific differences in male clasper distal length and shape and possible matching differences in the morphology of the female urogenital apparatus; and interspecific differences in colour patterns, e.g. the number, relative size and colour tones of the blue spots.

Few data are available on either the biology or the fisheries of sharks and rays in the Indonesian seas [2,14,15], but the data available warn us that if unsustainable exploitation processes further, it will likely cause severe depletion of fisheries stocks, potentially leading to fisheries collapse and the ecological extinction of the most vulnerable species. For the species that may survive, over-exploitation will erode genetic variability thus hampering the ability of populations to cope with future environmental change. As stated by Fahmi et al. [2], "management and conservation actions are difficult to implement for such species when basic data on biology and diversity are not available in the region". In the blue-spotted maskray, individual movements have been tracked using physical tags, which indicated sedentarity of both males and females [32]. Reports of size at maturity of both males and females, a parameter essential to investigating population dynamics, indicated strong geographic variability [1,2,32,33]. While these findings focused on a few populations of blue-spotted maskrays that are now recognized as separate species, the demography of the other species in the species complex remains unaddressed.

In conclusion, future research on the demographic parameters of the blue-spotted maskray should consider its updated taxonomy. Given the poor reliability of morphological characters [8], such studies should include more reliably diagnostic DNA sequence data [3,8] or should be done in a geographically explicit framework given the parapatric distribution of species in the species complex. Such efforts are required to inform the effective management of the blue-spotted maskray. Similar efforts are required with other shark and ray species complexes similarly threatened by overfishing in the Indonesian seas and elsewhere.

Figure 1.

In the course of her PhD thesis' work, Irma S. Arlyza spent six months at Institut des sciences de l'évolution, Montpellier under the supervision of P. Berrebi and P. Borsa. Irma tested a wide array of exon-primed intron markers in two stingray species then identified as Himantura uarnak [Gmelin (ex Forsskål) 1789] and Neotrygon kuhlii (Müller and Henle 1841). She was able to confirm that both consisted of species complexes that it subsequently became possible to describe based on their mito-chondrial DNA sequences [4][5][6][7][8]. Irma co-authored the description of five new stingray species [7,8] and the resurrection of another [9]. (modified from [8]).Dotted lines delineate the presumed extent of occurrence of each species; arrows symbolize the stepwise colonization of the Indo-West Pacific by the blue-spotted maskray, as inferred from phylogenies [19,21,24]; R Ryukyu maskray [21]. B. Simplified phylogenetic tree of the blue-spotted maskray species complex (edited from [8]). C. Lithography of "Trygon kuhlii" as published by J. Müller and F.G.J. Henle [START_REF] Müller | Systematische Beschreibung der Plagiostomen, mit sechzig Steindrucktafeln[END_REF], which their description of the species was obviously based on. In an e-mail to P. Borsa, M.J.P. van Oijen from the Naturalis museum, Leiden revealed that this lithography was a faithful reproduction of a watercolour by Nagasaki-based Japanese artist K. Keiga ca. 1830 [20].

  Figure 1. In the course of her PhD thesis' work, Irma S. Arlyza spent six months at Institut des sciences de l'évolution, Montpellier under the supervision of P. Berrebi and P. Borsa. Irma tested a wide array of exon-primed intron markers in two stingray species then identified as Himantura uarnak [Gmelin (ex Forsskål) 1789] and Neotrygon kuhlii (Müller and Henle 1841). She was able to confirm that both consisted of species complexes that it subsequently became possible to describe based on their mito-chondrial DNA sequences[4][5][6][7][8]. Irma co-authored the description of five new stingray species[7,8] and the resurrection of another[9]. (Credit: P. Borsa/IRD, 24 May 2011).

Figure 2 .

 2 Figure2. A. Parapatric distribution of species in the blue-spotted maskray species complex, Neotrygon spp. (modified from[8]).Dotted lines delineate the presumed extent of occurrence of each species; arrows symbolize the stepwise colonization of the Indo-West Pacific by the blue-spotted maskray, as inferred from phylogenies[19,21,24]; R Ryukyu maskray[21]. B. Simplified phylogenetic tree of the blue-spotted maskray species complex (edited from[8]). C. Lithography of "Trygon kuhlii" as published by J. Müller and F.G.J. Henle[START_REF] Müller | Systematische Beschreibung der Plagiostomen, mit sechzig Steindrucktafeln[END_REF], which their description of the species was obviously based on. In an e-mail to P. Borsa, M.J.P. van Oijen from the Naturalis museum, Leiden revealed that this lithography was a faithful reproduction of a watercolour by Nagasaki-based Japanese artist K. Keiga ca. 1830[20].

Acknowledgement

This is a contribution of the PARI project, a cooperative research project between IRD, France and LIPI-P2O, Indonesia.


Brian Fg Katz
email: brian.katz@sorbonne-universite.fr

Sandie Le Conte

Peter Stitt

EVAA: A platform for Experimental Virtual Archaeological Acoustics to study the influence of performance space

Keywords: Archaeoacoustics, Archaeological Acoustics Auralization, Virtual Reality

Research in historical musical acoustics has for several decades focused significantly on instrument fabrication. Such research has been able to highlight the acoustical impact of material and construction choices. Musicological studies have concentrated in parallel on understanding historical notation, playing styles, and even changes in musician posture over the centuries. In studying player and listener conditions in these historical studies, little attention has been given to the acoustical conditions of the performance, aside from extreme cases such as cathedral acoustic conditions. Extending the methodologies of experimental archaeology, recent advances in computational accuracy of acoustic virtual reality simulations offer the possibility to create ecologically valid reconstructions of historic sites. We present the development of an interactive immersive real-time simulator allowing musicians to perform "live" within virtual reconstructions of historic venues, comprising real-time adaptation of source directives with performer movements, rendered in Higher Order Ambisonics. Observations of the impact of acoustic variations on player performance, and the comparisons of the resulting performance between historically suitable venues and modern performance spaces from an audience perspective will complete the feedback loop between performer and listener necessary for a full understanding of the historical musical context.

INTRODUCTION

The research and practice of "historically informed performance" (HIP) has advanced significantly in recent decades. This discipline can be summarized as a regard to performance which aims to be faithful to the approach, manner, and style of the musical era in which a work was originally conceived. Two aspects are typically considered in such efforts: performance practice of musicians and use of period instruments. However, little consideration has been given to the influence of performance space on the performance, instrument, or composition of the time. Using real-time virtual acoustic simulations, the EVAA project (Experimental Virtual Archaeological Acoustics) 1 aims to include the performance venue's acoustics as a third component of study for HIP. Placing musicians with original or historically accurate facsimiles of instruments in various virtual performance spaces, we examine the impact of the room's acoustics on performance. Such a study also informs investigations on the evolution of instruments themselves, with respect to the evolution of performance venues. Inclusion of the role of composition completes the circle, as it can be seen as both a driving force of change and a response to the changing physics of the instruments and rooms used for music performance. This paper presents the context and overview of the EVAA project, launched in early 2019, as well as a presentation of first results : a real-time simulation platform developed to facilitate the subsequent series of studies.

CONTEXT

Research in historical musical acoustics has for several decades focused significantly on instrument fabrication [START_REF] Boutin | Acoustic dissipation in wooden pipes of different species used in wind instrument making: An experimental study[END_REF][START_REF] Le Carrou | 18th and 19th French harp classification using vibration analysis[END_REF][START_REF] Conte | Beyond the boundaries: A multidisciplinary approach of the musical instrument[END_REF], highlighting the acoustical impact of material and construction choices. Musicological studies have, in parallel, concentrated on understanding notation, playing styles, and even changes in musician posture over the centuries. In studying player and listener conditions in these historical studies, acoustical conditions of the performance have been largely ignored [START_REF] Boren | Computational acoustic musicology[END_REF], aside from extreme cases such as cathedrals [START_REF] Postma | Creation and calibration method of virtual acoustic models for historic auralizations[END_REF][START_REF] Postma | Perceptive and objective evaluation of calibrated room acoustic simulation auralizations[END_REF]. Extending the methodologies of experimental archaeology [START_REF] Coles | Experimental Archaeology[END_REF][START_REF] Reynolds | Experiment and design: archaeological studies in honour of John Coles, chapter The nature of experiment in archaeology[END_REF], recent advances in computational accuracy of acoustic virtual reality simulations [START_REF] Postma | Creation and calibration method of virtual acoustic models for historic auralizations[END_REF] offer the possibility to create ecologically valid reconstructions [START_REF] Guastavino | Ecological validity of soundscape reproduction[END_REF] of historic sites. Generally limited to off-line rendering, simulating the audience perspective, we employ an interactive immersive real-time simulator allowing musicians to perform "live" within virtual reconstructions of historic venues. The simulator significantly advances upon previous realistic off-line renderings of historic sites. Analyzing the impact of acoustic variations on player performance, and comparisons of performances between historically suitable venues and modern performance spaces from an audience perspective, completes the feedback loop between performer and listener, for a full understanding of the historical musical context [START_REF] Boren | Computational acoustic musicology[END_REF].

PROJECT OVERVIEW

Since its inception, musical acoustics has focused predominantly on the production of sound for musical purposes, with that focus being on musical instruments. Musicology extends this domain into the humanities, highlighting the cultural and societal aspects of music history as well as composition. Room acoustics concentrates on the interaction of sound sources and rooms, with a strong focus on performance spaces due to their importance for listening. EVAA uses innovative virtual reality techniques to bring together researchers from these various disciplines to work on a question at the core of their mutual interaction: the influence of the performance room's acoustics on the development of instruments, the performance of musicians, and the details of musical composition. Based on ongoing research at the Musée de la musique concerning wind instruments in the context of facsimile fabrication (manufacturing techniques, materials used, acoustic behavior, playing techniques, etc.) EVAA will first focus on the reconstruction of venues of historical significance for small ensembles in the Baroque and Classical music periods, beginning with Parisian venues and the surrounding region, including the Salle de concert du Conservatoire and the Château de Versailles. Additional partners include the Pôle Supérieur d'enseignement artistique Paris Boulogne-Billancourt with activities on these periods and instruments and IRe-Mus with musicological expertise on the historical approach of music and acoustics and HIP issues.

Historic Instruments

The Musée de la musique has in its collection over 7000 musical instruments. Its main mission is to tell the story of "Art music" (Musique savante) through its collection. For conservation reasons, less than 5% of these are played regularly. No wind instruments are played due to hygrothermic gradients from musician's blowing. The current solution for listening to these instruments is via facsimiles. Facsimiles are constructed from detailed information on historic instruments: acoustical measurement, historical & organological research, and material characterization. While attention is given to the music played, the appropriateness of the musical period for the instrument, all are played in the same Amphitheatre: harpsichords, oboes, flute, guitars, etc. Current research concerns technical evolutions in the contexts of the evolution of music, playing techniques, and venues [START_REF] Le Carrou | 18th and 19th French harp classification using vibration analysis[END_REF][START_REF] Eveno | An acoustical measurement used for the understanding of historical wind instruments[END_REF]. In showing the history of the musical instrument construction process, a challenge is to study these changes according to venue, to propose to audiences and musicians a unique historical sound experience. EVAA will focus first on instruments such as Hotteterre flutes (17 th c.) and Delusse oboes (18 th c., one facsimile exists), from when such instruments entered into the music salon in Versailles. In 1684, French musical institutions reached their peak with the new association of violins and oboes at the Royal Academy. The Musée has at least four oboes dated end of the 17 th (oboe E.108, 1680). Similar oboes were played in the Chambre Royale and the Royal Academy Orchestra. Two famous constructors (early 18 th c.), have oboes in the collection. Acoustical characterization of the selected instruments with consider input impedance measurements for historical fingerings, providing acoustic information without playing. The objective is to investigate any evolution of the acoustics following evolutions in composition.

Room Acoustics

Composers of the Baroque and Classical eras, may have been aware of the effects of room acoustics on performances, adapting compositions to venues [START_REF] Herr | An acoustical history of theaters and concert halls: An investigation of parallel development in music, performance spaces, and the orchestra[END_REF]. However, such observations have not been supported by objective or subjective evaluations of the rooms' acoustics. We will soon conduct room acoustical measurements, documenting these architectures and improving understanding in specific evolutions in composition during this period, providing objective acoustical analyses. These measurements enable calibration of geometrical acoustic models, an essential step to perceptually realistic simulations. [START_REF] Postma | Creation and calibration method of virtual acoustic models for historic auralizations[END_REF] has shown that calibrated simulated auralizations can be subjectively comparable to measured ones. To date, this calibration is validated for vocal sources, and needs to be extended to musical content. The surrounding visual environment may be presented over non-disturbing VR devices, providing a multimodal environment. It has been shown that visual renderings affect auditory perception (distance, envelopment, and plausibility) [START_REF] Postma | Subjective Evaluation of Dynamic Voice Directivity for Auralizations[END_REF]. The EVAA platform will facilitate further evaluations assessing effects of visual "level of detail", e.g. lighting conditions or images resolution on both musician and audience.

Musician at the center

The professionalism of the instrumentalists is essential. If the musicians do not have sufficient knowledge of the instrument and its playing characteristics, results will be subject to errors affecting the produced sound: e.g. accuracy, power, and timbre. Characterizations of playing conditions include mechanical measurements of control parameters, like air force and movements [START_REF] Ernoult | Music in a bag? Controlling the bag of Majorcan and Galician bagpipes[END_REF]. Players may not feel exactly like in a real situation, behaving differently than in a real venue, but relative differences between two simulated venues would lead to similar differences in both real and the virtual conditions. This is evaluated through questionnaires and audio recordings in virtual and real venues. Experiments can investigate links between the evolution of instruments, venues, and repertoire. How does performance on an instrument change with venue? How do players' evaluations of instruments change with venue? Are some venues more appropriate for some instruments? How do evaluations relate to acoustic measurements? Musicians will play and evaluate facsimiles from different periods in simulated venues popular during these periods, with oboists and flutists from partners and external baroque ensembles, using protocols ensuring ecological validity [START_REF] Guastavino | Ecological validity of soundscape reproduction[END_REF][START_REF] Fritz | Perceptual Evaluation of Musical Instruments: State of the Art and Methodology[END_REF][START_REF] Paté | Influence of the Electric Guitar's Fingerboard Wood on Guitarists' Perception[END_REF]. Recordings will be analyzed to extract parameters that could differ: e.g. tempo, level, spectra, and ornamentation. Quantitative performance metrics will be compared to perceptual evaluations and the acoustic measurements. Recordings will be evaluated by musicians, music teachers, and researchers to investigate differences for audiences, helping to interpret signal analyses.

RENDERING ENGINE ARCHITECTURE 4.1 OVERVIEW OF RENDERING ENGINE

The aim of the rendering engine is to allow a musician or performer to be placed in different acoustical spaces in order to investigate how the room acoustics influence their performances, including the effects of instrument directivity and dynamic movement. To achieve this, performances will be captured using a wireless microphone placed in close proximity to their instrument. The directivity of the musician's instrument, incorporated via measurements or simulations, will be able to dynamically follow the motions of the performer within the virtual room in real-time. A conceptual overview is shown in Fig. 1(a). The rendering engine detailed here provides the dynamic simulation of a directional source using a series of pre-calculated room impulse responses (RIRs) 2 An overview of the processing architecture is shown in Fig. 1(b). The engine takes a mono sound source and processes it to a Higher Order Ambisonic (HOA) [START_REF] Daniel | Représentation de champs acoustiques, application à la transmission et à la reproduction de scènes sonores complexes dans un contexte multimédia[END_REF] audio stream used for playback. The virtual source orientation is driven by the orientation of the musician, captured using a motion tracking system. The Rendering Engine is currently implemented in C++ as a VST3 for use in the MAX real-time environment. An HOA receiver is situated in the simulated room for RIR computation. In the current case of interest, a performer in a virtual room, this receiver position is placed at the same position as the sound source. Additional receivers can be placed elsewhere in the room, allowing for listeners other than the performer to listen to the performance, or to allow the performer to replay their performance while listening from the audience.

ROOM SIMULATION

It is assumed at this point that a suitable geometrical acoustics model has been created, allowing for an accurate acoustic simulation of the room. In order to generate different source directivity patterns at run-time, an overlapping beam approach [START_REF] Postma | Subjective Evaluation of Dynamic Voice Directivity for Auralizations[END_REF] is used where RIRs are calculated for a set of directional beam-sources of differing orientations. Each beam-source simulation produces an HOA-RIR of order M rec , resulting in N × (M rec + 1) 2 impulse responses for each source/receiver position combination, where N is the number of beams. The number, directivity, and orientation of the beams depends on the reproduced spatial accuracy of the final source directivity -more detailed directivity patterns will require more, and narrower, beams be used. The spatial accuracy is a function of the spherical harmonic order M used for the representation. In [START_REF] Postma | Subjective Evaluation of Dynamic Voice Directivity for Auralizations[END_REF] the beam patterns were defined using strategic control points and spline interpolation. In the current improved version, beam patterns are reformulated as M-th order cardioid patterns;

g(θ , φ ) = (0.5 + 0.5 cos(θ ) cos(φ )) M , (1)
where θ and φ are the azimuth and elevation directions of radiation (see Fig. 2(a) for M ≤ 3). A first-order spherical harmonic approximation of source directivity requires four sources in a tetrahedral arrangement with beams of cardioid directivity. For higher order directivity patterns, the beam directivity is that of a higher order cardioid. Second-order approximation requires 12 sources arranged in an icosahedron and second-order cardioid directivity. Third-order requires 20 sources arranged in a dodecahedron and third-order cardioid directivity. Figure 2(b) shows the orientations of the set of beams for M ≤ 3.3 Each order's set of beams sum to produce an omnidirectional directivity pattern, ensuring that the desired directivity can be varied from that of a single beam (or any arbitrary M-th order pattern) to an omnidirectional source. The beam directivities can be converted to spherical harmonics via:

b M = 1 N Y M g n , (2)
where

Y M = [y M (θ 1 , φ 1 ), . . . , y M (θ N , φ N )]
is the (M + 1) 2 × N matrix that encodes a function over the N beam directions to spherical harmonics of order M, y M (θ n , φ n ) is the vector of spherical harmonic coefficients in the n-th beam direction, and g n = [g n (θ 1 , φ 1 ), . . . , g n (θ N , φ N )] T is the vector containing the n-th beam's gain in the directions of all N beams.

SPHERICAL HARMONIC SOURCE DIRECTIVITY

If the frequency-dependent source directivity to be simulated has been measured on a regular spherical grid then it can be converted to an M-th order spherical harmonic representation x M (ω). Assuming the source directivity is measured in the same directions as the required number of beams, conversion to spherical harmonics is realized via;

x M (ω) = 1 N Y M g N (ω), (3)
where g N (ω) is the vector of measured source gains in each of the measurement directions. If the measurement grid of the source is not completely regular, regularization can be used to ensure accurate conversion to the spherical harmonic domain.

IMPULSE RESPONSE PRE-PROCESSING

To improve CPU usage, the different beam RIRs are processed prior to convolution to provide a single HOA-RIR for the given instrument directivity and real-time orientation data, minimizing the number of real-time convolutions. The N-beam HOA-RIRs are first loaded into the engine and all N × (M rec + 1) 2 IRs are processed for use in the convolution engine. Due to IR lengths, an overlap-add uniform-partitioned frequency domain convolution is used [START_REF] Torger | Real-time Partitioned Convolution for Ambiophonics Surround Sound[END_REF], requiring IRs to be segmented prior to transforming to the frequency domain via FFT. The composite source is represented by N beams, each with an HOA receiver. As N ≥ (M + 1) 2 , the source representation is converted from a beam-basis to a spherical harmonic basis. The result a source represented in spherical harmonics, with each harmonic having an HOA receiver. A composite HOA-RIR is generated as a weighted sum across source-spherical harmonics (detailed in Sec. 4.5). With the potential RIR lengths and the dynamic update requirements, this approach ensures a minimum number of channels during real-time processing.

Conversion from an N-beam source representation to spherical harmonics is done on a per-segment basis. The N × L matrix transfer functions H i (ω) of i-th segment are converted to a spherical harmonic representation via;

Ĥi (ω) = B † M H i (ω) (4)
where Ĥi (ω) is the (M + 1) 2 × L matrix of the spherical harmonic representation of the source for each of the L playback channels for the i-th segment,

B M = [b M (θ 1 , φ 1 ), . . . , b M (θ N , φ N )]
T is the matrix of beam spherical harmonics from equation ( 2), and † indicates the Moore-Penrose pseudo-inverse. Ĥi (ω) is stored for use during real-time processing. All subsequent processing is performed in the frequency domain, avoiding costly FFTs of lengthy new impulse responses for each change of source orientation.

It should be noted that geometrical acoustic simulations can include stochastic elements due to methods of scattering/diffusion implementation. This means that the summation of the results of multiple simulations would exhibit amplitude summing in the direct and early portions of the RIR and energetic summation in the later portions. The impact of this remains to be examined.

INSTRUMENT SOURCE ROOM IMPULSE RESPONSE GENERATION

The engine allows for the rendering of a sound source with a pre-defined directivity pattern x M (ω) and variable orientation. The advantage of representing the source directivity in the spherical harmonic domain is that it allows for simple, efficient rotation via the application of a rotation matrix, ensuring that the source can have its orientation changed freely, following the motion of the musician playing in the virtual room. Assuming the directivity pattern of the source is time-invariant and only the orientation changes, the rotated spherical harmonic source directivity is obtained by;

xM (ω,t) = R(α, γ, β ,t)x M (ω), (5)
where R(α, γ, β ,t) is the (M + 1) 2 × (M + 1) 2 time-varying rotation matrix as a function of the rotation angles yaw α, pitch β and roll γ. The rotations are applied in the order yaw, pitch, then roll. The spherical harmonic representation of the current source directivity is then used to calculate the final transfer function for each of the I segments. This is achieved by multiplying Ĥi (ω) (from equation ( 4)) by the desired source directivity pattern xM (ω,t).

hi (ω,t) = ĤT i (ω)x M (ω,t). (6)
The transfer functions hi (ω,t) for each of the segments are then loaded in to the partitioned convolution engine.

SOURCE RENDERING

The captured mono input is convolved with resulting set of transfer functions hi (ω,t) to generate L HOA output channels. In order to continuously update the impulse responses, a separate thread is run that monitors the orientation of the source. If a change occurs then it generates a new composite transfer function hi (ω,t) corresponding to the latest orientation. Once the new HOA-RIR has been generated (see Sec. 4.5), it is loaded in to the convolution engine. This process ensures that audio dropouts do not occur while the audio thread waits for a new HOA-RIR as the generation time can be longer than one I/O buffer, especially for long RIRs and higher playback orders.

A change in source directivity or orientation necessitates the generation of a new HOA-RIR. This, in turn, requires interpolation between the old and new impulse responses used in the convolution engine to avoid audible artefacts. This is achieved by cross-fading between two convolution engines: one using the old HOA-RIR and another using the new. This smooths any discontinuities and removes artefacts from the output stream at the CPU cost of requiring a second convolution engine.

PLAYBACK

The output of the convolution engine is an HOA audio stream. Higher order signals provide greater spatial and timbral fidelity, at the cost of increased CPU load. The HOA stream can be decoded to an array of loudspeakers, allowing the musician to be placed acoustically in the virtual room. Playback on loudspeakers requires an appropriate decoder to ensure low reproduction error. As an alternative to decoding to loudspeakers, the HOA stream can be decoded to binaural audio for playback over headphones using a virtual loudspeaker approach [START_REF] Noisternig | A 3D Ambisonic Based Binaural Sound Reproduction System[END_REF] or more advanced methods [START_REF] Zaunschirm | Binaural rendering of Ambisonic signals by head-related impulse response time alignment and a diffuseness constraint[END_REF][START_REF] Schörkhuber | Linearly and Quadratically Constrained Least-Squares Decoder for Signal-Dependent Binaural Rendering of Ambisonic Signals[END_REF]. If binaural decoding is used, the orientation of the musician's head must be tracked in addition to that of the instrument, with the sound field appropriately rotated to compensate, to ensure a realistic rendering. HOA allows for efficient rotation of the entire sound field via the application of a rotation matrix to the audio signals to generate a new audio stream, similar to the rotation of the source directivity in Eq. ( 5).

POTENTIAL IMPROVEMENTS AND EXTENSIONS

The current engine uses time-domain cross-fades when a new HOA-RIR is loaded to the convolution process, requiring two convolution engines to run concurrently. A more efficient method is available that applies the cross-fade in the frequency domain [START_REF] Vickers | Frequency-domain implementation of time-varying FIR filters[END_REF][START_REF] Wefers | Efficient time-varying FIR filtering using crossfading implemented in the DFT domain[END_REF] and could improve the efficiency of the current engine.

It is also possible to interpolate between different directivity patterns in the spherical harmonic domain. This would, for example, allow for the variation of directivity patterns based on the source characteristics. For example, the directivity pattern of a singer could be changed to adapt to different vowel sounds, which have been shown to produce different directivities [START_REF] Katz | Human voice phoneme directivity pattern measurements[END_REF].

  (a) Conceptual visualization of a performer placed virtually in the Château de Versailles with the virtual room acoustics reproduced over a loudspeaker array in an acoustically controlled environment. (b) Schematic diagram of the rendering engine for real-time dynamic source directivity.

Figure 1 .

 1 Figure 1. Conceptual and schematic overview of the rendering engine.

  Horizontal cross-section of the beam directivity patterns for order M = 1, 2, 3. The directions of the beams for orders M = 1, 2, 3.

Figure 2 .

 2 Figure 2. The beam widths and directions used to enable maximum source directivities of M = 1, 2, and 3.

RIRs for this study were computed using CATT-Acoustic[START_REF] Dalenbäck | CATT-Acoustic v9 powered by TUCT user manuals[END_REF] but the methodology is not limited to any given software.

Orders M > 3 can be accommodated using t-design layouts[START_REF] Hardin | Mclaren's improved snub cube and other new spherical designs in three dimensions[END_REF], although the current implementation of the engine is limited to third-order.

ACKNOWLEDGEMENTS

This work was funded in part by a starter grant from the Collegium Musicae Institute, Sorbonne Université. Additional funding has been provided by a grant from the Fondation des Sciences du Patrimoine and a grant from the Ile-de-France Region -DIM "Matériaux anciens et patrimoniaux".


Emmanuel Mignot
email: emmanuel.mignot@insa-lyon.fr

Xuefang Li

Benjamin Dewals

Experimental modelling of urban flooding: a review

Keywords: urban flood, experimental models, databases, flow processes, model set-ups

We review the 45 available studies of urban flooding based on laboratory experiments. We distinguish between the studies focusing on the flow in (i) a single street intersection, (ii) surface-sewer exchanges, (iii) an array of obstacles and (iv) quasi-realistic urban districts. We discuss the main flow processes which are covered in the various studies and detail which flow variables were recorded. This enables identifying flow processes for which comprehensive experimental datasets are available from those which require additional experimental research. We also highlight the typical ranges of scale factors used, which depend mainly on the extent of the studied area (from very local up to the district level). This review aims at helping computational modellers to pinpoint the most suitable dataset for validating their numerical approaches and laboratory modellers to identify gaps in current experimental knowledge of urban flooding.

Introduction

Among all natural disasters, floods are the most frequent and they affect the highest number of people globally (UNISDR, 2015). Flood risk is particularly severe in urban areas [START_REF] Chen | Urban flood risk warning under rapid urbanization[END_REF].

Improving urban flood risk management has become a high priority at virtually all levels of governance [START_REF] Fang | Adapting Chinese cities to climate change[END_REF]. The proper design and evaluation of measures to enhance urban floodresilience should be based on the analysis of a range of scenarios, in which various hydrometeorological conditions and management options are tested. This requires the accurate modelling of inundation extents, water depths, discharge partition and flow velocity in urbanized flood prone areas, since these parameters are critical inputs for flood impact modelling [START_REF] Kreibich | Costing natural hazards[END_REF].

For relatively rural areas, flood modelling and inundation mapping have become common practice [START_REF] Falconer | Flood Modelling and harzard assessment for extreme events in riverine basins[END_REF][START_REF] Teng | Flood inundation modelling: A review of methods, recent advances and uncertainty analysis[END_REF]. Based on the 1D or 2D shallow-water equations (SWE), the accuracy of these computations depends mainly on the quality of hydrological and topographic input data [START_REF] Dottori | Detailed data is welcome, but with a pinch of salt: Accuracy, precision, and uncertainty in flood inundation modeling[END_REF]. In contrast, floods in urban areas exhibit more diverse and complex flow processes, as the water follows multiple flow paths such as crossroads, sewers, courtyards, parks, flow around or within buildings and pieces of urban furniture [START_REF] Paquier | From Hydraulic Modelling to Urban Flood Risk[END_REF][START_REF] Falconer | Flood Modelling and harzard assessment for extreme events in riverine basins[END_REF].

Numerical models used for urban flood simulations need to account for these specific features of the urban environment. For about two decades, the quality and complexity of urban flood simulations have steadily increased. Starting from standard 1D or 2D models [START_REF] Mark | Potential and limitations of 1D modelling of urban flooding[END_REF]Mignot et al., 2006a), more sophisticated numerical approaches have become gradually available:

• additional processes were included in the models, such as the rain falling directly on the street network [START_REF] Pons | Simulation of flash floods in Marseille and Bordeaux with a two-dimensional runoff model[END_REF][START_REF] Paquier | Estimating uncertainties for urban floods modelling[END_REF], short waves or tsunami long waves invading a city [START_REF] Park | Tsunami inundation modeling in constructed environments: A physical and numerical comparison of free-surface elevation, velocity, and momentum flux[END_REF], human evacuation during a flood [START_REF] Bernardini | A preliminary combined simulation tool for the risk assessment of pedestrians' flood-induced evacuation[END_REF], among others;

• high resolution digital elevation models (DEM), such as laser altimetry with a resolution as fine as 0.5 m in some urban areas [START_REF] Van Ootegem | Exploring the potential of multivariate depth-damage and rainfall-damage models[END_REF], have enabled super precise descriptions of the urban domains [START_REF] Ozdemir | Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data[END_REF];

• isotropic and anisotropic porosity-based models (e.g., [START_REF] Bruwier | Shallow-water models with anisotropic porosity and merging for flood modelling on Cartesian grids[END_REF]), coupled 1D (in streets) and 2D (in crossroads) models [START_REF] Ghostine | Comparison between a coupled 1D-2D model and a fully 2D model for supercritical flow simulation in crossroads[END_REF], as well as improved computational techniques such as cloud computing [START_REF] Glenis | Flood modelling for cities using Cloud computing[END_REF] or model implementation on graphical processing unit (Apel et al., 2016;[START_REF] Smith | Towards a hydrodynamic modelling framework appropriate for applications in urban flood assessment and mitigation using heterogeneous computing[END_REF], have been developed to enable efficient coverage of large spatial areas;

• although still in its infancy, modelling the interactions between surface flow and the sewer system has been tested, based on a 1D description of the underground system and 0D, 1D or 2D approaches for surface flow, each with scientific challenges [START_REF] Leandro | Comparison of 1D/1D and 1D/2D coupled (sewer/surface) hydraulic models for urban flood simulation[END_REF][START_REF] Seyoum | Coupled 1D and Noninertia 2D Flood Inundation Model for Simulation of Urban Flooding[END_REF][START_REF] Bazin | Modeling flow exchanges between a street and an underground drainage pipe during urban floods[END_REF].

Nonetheless, further numerical developments are needed to incorporate more details (urban furniture, street profiles, façade misalignments, parked cars) as well as additional processes generally overlooked so far (water entering the buildings, more realistic interactions river/surface/sewers, transport of cars, pollutants, computing rescue operations …). Since 3D computations [START_REF] Ghostine | Simulation of supercritical flow in crossroads: Confrontation of a 2D and 3D numerical approaches to experimental results[END_REF][START_REF] Gems | 3-D hydrodynamic modelling of flood impacts on a building and indoor flooding processes[END_REF][START_REF] Rodi | Turbulence modeling and simulation in hydraulics: a historical review[END_REF] will not be a viable option for operational flood analysis and mapping in the coming years, many processes will not be captured explicitly by operational flood models. They will have to be reproduced through appropriate analytical-empirical parametrizations.

The development and validation of these parametrization requires high quality and reliable reference data.

Field data, such as watermarks and aerial imagery, remain generally scarce, uncertain and insufficient to reflect the whole complexity of inundation flows in urbanized flood-prone areas, particularly under more extreme future conditions [START_REF] Neal | Distributed whole city water level measurements from the Carlisle 2005 urban flood event and comparison with hydraulic model simulations[END_REF]. Additional information on the velocity fields and discharge partitions are necessary to understand the multi-directional flow pathways induced by the built-up network of streets, buildings and underground systems (e.g., drainage network). There is also a lack of observations of pluvial urban floods, mainly due to the short duration and local nature of intense rainfall events. To address this lack of validation data from the field, laboratory models are an appealing alternative, since they provide accurate measurements of flow characteristics under controlled conditions. Therefore, this paper aims at reviewing the existing datasets of urban flood laboratory experiments. This review may benefit to both numerical modellers willing to test and validate innovative computational approaches, and experimentalists looking for comparison datasets or willing to close knowledge gaps. The paper presents also an inventory of the flow processes for which experimental research was undertaken or still to be handled. Field data are excluded on purpose, as they are generally sparser and more uncertain.

The paper is organized in three parts. The existing experimental datasets dedicated to the analysis of urban flood processes are reviewed in Sect. 2. In Sect. 3, the coverage of the main urban flood process by dedicated laboratory experiments is evaluated; enabling us to point out the flow processes for which no or limited experimental data are currently available. Finally, Sect. 4 links the main findings to the corresponding numerical approaches, highlighting those which lack validation data. Hints for future experimental research are proposed.

State of the art of available urban flood datasets

Table 1 lists the available experimental datasets related to urban flooding. Most experiments were performed in the last 15 years, suggesting a growing worldwide interest for urban flood laboratory data, as the corresponding numerical models also improved considerably. The experimental studies focused on four main flow types: (i) flow in street intersections, (ii) vertical exchanges between the sewer system and the streets, (iii) flow within regular grids of emerging rectangular obstacles representing idealized buildings or building blocks and (iv) flow within more realistic urban districts.

Table 1 is organized in four blocks (I to IV), each of them corresponding to one flow type.

As shown in the first column of Table 1, the experiments considered five different origins of the water, i.e. the cause of flooding. First, upstream runoff (UR) corresponds to experiments in which the water is supplied from an upstream boundary, mainly via a reservoir with a controlled discharge. It usually refers to flood events for which the overflow or rain takes place upstream of the urban area and water enters the urban domain as surface flow. Second, river overflow (RO) corresponds to configurations where the overflow takes place within the urban area and thus the river and the overtopping of the banks are explicitly included in the experiments. In such a case, the upstream boundary condition is a controlled discharge within the river. Sewer overflow (SO) is similar to river overflow except that in this case the water invading the surface comes from an exceeded capacity of the sewer within the urban domain; the upstream boundary condition is then a controlled discharge in the sewer inlet. The fourth origin of water is the rainfall over the studied domain (RA), which is the case of fully urban watersheds [START_REF] Pons | Simulation of flash floods in Marseille and Bordeaux with a two-dimensional runoff model[END_REF][START_REF] Paquier | Estimating uncertainties for urban floods modelling[END_REF]. Then the upstream boundary condition is a complex spatial (and temporal) distribution of water jets from a wellcontrolled rainfall simulator. Finally, the tsunami (TS) type is a long wave imposed off-shore that propagates over the sea domain and invades an urban area when reaching the coast and overtopping the shore protection furniture. Note that these five types of origin of the water can be unique or coupled with each other, as for some UR & SO cases in Table 1 (ID 19,20,22,23).

The diversity of the analysed flow patterns (columns 2, 5 and 7 in Table 1) emphasizes the complexity of urban flood processes, involving subcritical and supercritical flow regimes, openchannel and pressurized flow, both at the surface or in the underground system, interacting with obstacles, building blocks etc. Among the 45 reported studies, very few address identical flow patterns. The experimental set-ups reproduce either a synthetic urban area (highly simplified streets, 90° intersections and impervious rectangular buildings) or a simplified version of a real city (reproducing the topology of the city but with a highly simplified representation of the facades and street profiles) or finally a more realistic representation of an urban district based on the field DEM (with each individual building being included).

The location of the set-up is indicated to help the reader contact the research team responsible for the flume (columns 3 and 4 in Table 1). It also reveals that the experiments were performed in 17 different countries, confirming the global interest for urban flood experimental data.

Columns 6 and 10 in Table 1 provide the typical dimensions of the laboratory model. A plausible scale factor was derived, by assuming a typical street width equal to 15m and a gully width of 60cm at the prototype scale. Some set-ups aim at analysing in detail local flow features (e.g. flow in a street intersection, single vertical exchange structure, flow around one isolated building …), while others focus on larger scale flow characteristics, such as the flow in a street-network, but with a lower spatial resolution and measurement accuracy. As a consequence, the scale factor of models of street intersections or vertical exchange works typically ranges between 1/10 and 1/50, while those of experiments covering an entire urban district or a grid of obstacles range between 1/30 and 1/200. The experiments of [START_REF] Herbich | Large-scale roughness in open-channel flow[END_REF] correspond to the largest model extent for tests involving a grid of obstacles. The largest models of urban districts are those of [START_REF] Ishigaki | Hydraulic model tests of inundation in urban area with underground space[END_REF][START_REF] Güney | Distorted Physical Model to Study Sudden Partial Dam Break Flows in an Urban Area[END_REF], with a setup length of 20m and 16m, respectively, representing real-world urban areas of 3km and 2.4km in length.

Finally, columns 8 and 9 in Table 1 report the number of tested configurations and type of recorded data. The measured data strongly depend on the scale of the experiment. For very local flow patterns, such as flows in street intersections and vertical exchange structures (blocks I and II in Table 1), spatially distributed flow characteristics are generally available, including 3D velocity fields and 2D water depth fields, together with more global flow variables such as discharges in the different branches. Moreover, for these local flow pattern experiments, the number of tested configurations remains low (below 10) when spatially distributed data were recorded; whereas it reaches up to 200 configurations when only the discharges were recorded. For the experiments investigating larger scale flow patterns such as obstacle grids and urban districts, spatially distributed data are rare and mostly local velocities and water depths were recorded with pointwise measurement tools, except for surface velocity fields derived in some cases from large scale particle image velocimetry (using a camera located above the experimental setup).

Overall, Table 1 demonstrates the availability of rich laboratory datasets covering a broad spectrum of typical urban flood conditions. In the following, we distinguish between the flow processes comprehensively studied and those calling for more laboratory investigations.

Advances of urban flood processes analysis

By listing the existing experimental datasets, Sect. 2 reveals that a wide range of flow processes were reproduced experimentally. Here, we attempt to present an inventory of the main flow processes of engineering relevance in urban flood studies (Table 2), and to relate them to the works listed in Table 1. This enables assessing whether the existing experimental datasets are comprehensive enough for the validation of the representation of each flow process in numerical models. Table 2 suggests that experimental datasets do exist for most urban flow processes of interest; but not for all of them.

Regarding the origin of water, most common flood origins were reproduced experimentally. The main deficiency is the intrusion of water waves from a storm surge, with the water from the sea, overtopping the protection dikes and invading coastal cities with very unsteady flows, as described by [START_REF] Maspataud | Potential impacts of extreme storm surges on a low-lying densely populated coastline: the case of Dunkirk area, Northern France[END_REF]. One main question is the evolution of the unsteadiness as the flow propagates within the urban areas, merges or splits at crossroads and in open spaces: will the typical hydrograph time-scale increase or decrease compared to the surge hydrograph? The validation of numerical simulations certainly requires dedicated experimental data. Moreover, the knowledge on intrusion of water through direct rain on the city domain should be further improved. In particular, as the rain falls on the buildings roofs, part of the water reaches the sewer network (through the gutters) and the rest reaches the surrounding streets or gardens (with possible infiltration) with some surface runoff on the private slots. These processes, computed by [START_REF] Pons | Simulation of flash floods in Marseille and Bordeaux with a two-dimensional runoff model[END_REF] and [START_REF] Paquier | Estimating uncertainties for urban floods modelling[END_REF], still require high quality data to enable deriving empirical parametrizations specific to urban catchments.

Future research should also consider the complex coupling between several flood origins.

Numerous datasets of flows in street networks (or within arrays of buildings) were published in the recent years. These consider steady or unsteady flows, including steep hydrographs, at single or multiple street intersections. One main deficiency regarding surface flow corresponds to the consideration of obstacles present in the streets [START_REF] Mignot | Impact of topographic obstacles on the discharge distribution in open-channel bifurcations[END_REF] and steep urban areas where mostly supercritical flow conditions take place. In such cases, hydraulic jumps occur at the street intersections [START_REF] Mignot | Flow patterns in a four-branch junction with supercritical flow[END_REF] and in the vicinity of obstacles [START_REF] Bazin | Computing flooding of crossroads with obstacles using a 2D numerical model[END_REF].

Although the flow in street networks has been deeply studied experimentally, it is not the case of the flow invading other compartments of the urban fabric:

• vertical flow interaction between the underground sewer and the street surface was investigated locally, at the level of one exchange structure or a single street, but it remains undocumented at the level of an entire urban district;

• similarly, data on flow exchanges between the streets and the blocks / slots (building blocks, gardens, hospitals, etc…) through openings (gates, doors, windows…) remain scarce, both at the local level (one facade, one building) and at the district level, while such calculations have been performed for already some time [START_REF] Hingray | Hydraulic vulnerability of elementary urban cell[END_REF][START_REF] Inoue | Numerical simulation models of inundation flow in urban area[END_REF].

Existing experimental works focused not only on the flow dynamics; but so-called "associated events" have also been considered due to their importance for operational flood risk management. For instance, much attention has been paid to the stability and safety of human beings and cars within flooded streets. These valuable experiments enable estimating, from the hydrodynamics, the level of risk for citizens and goods in flooded urban areas. Nevertheless, the behaviour of transported cars or other mobile furniture (either floating or within the water column) in a street network, and the possibility of creating dams at crossroads or street contractions (Mignot et al., 2006b) was not yet investigated in laboratory experiments. Also, experiments on people evacuation were conducted at a single institution (DRPI, Kyoto, Japan) and reproducing similar measurements is desirable.

Measurements of hydrodynamic forces on buildings or facades, and the transport of sediments in flooded urban areas have received relatively little attention up to now. Finally, neither the access of rescue vehicles through flooded streets, nor the dispersion of pollutants (e.g. from flooded industry or damaged trucks) within a street network have been tested. Improved numerical modelling of these "associated events" would be of substantial added-value for the management of urban flood risk, but this still requires additional experimental data for model development and validation.

Conclusion

Based on the analysis of 45 laboratory studies and the identification of the main flow processes of significance in urban flooding, the previous sections have highlighted the need for additional (ambitious) experimental efforts to support the development and validation of more realistic computational models of urban floods. This is particularly the case as next-generation urban flood simulations should not only accurately replicate the water flows but also include the so-called associated events (Sect. 3). Indeed, as shown in Table 1 andTable 2, validation data are available for assessing most types of numerical models commonly used in engineering and research to simulate urban floods, namely (upper part of Table 3):

• 2D-SWE, or the 2D-SWE coupled with a porosity model, or the coupled 1D (in the streets) and 2D (in the crossroads) SWE, to compute surface flow in the urban area;

• coupled 2D-SWE (in the streets) and 1D-SWE (in the sewer network), along with exchange models, to compute the coupled flows in both the underground and surface layers of the urban area;

• 2D-SWE or Boussinesq-type equations to compute long and/or short waves approaching the shore and invading coastal urban areas;

• 3D Reynolds-averaged Navier-Stokes equations at the level of an isolated building [START_REF] Gems | 3-D hydrodynamic modelling of flood impacts on a building and indoor flooding processes[END_REF] or a single street intersection [START_REF] Ghostine | Simulation of supercritical flow in crossroads: Confrontation of a 2D and 3D numerical approaches to experimental results[END_REF].

In contrast, more advanced numerical models (lower part of Table 3) are required to represent the "associated events" occurring during urban floods, for which dedicated experimental data are virtually unavailable. For instance, empirical or semi-analytical parametrizations are required to estimate the amount of water entering the buildings or blocks, for computing sediment and pollutant transport in urban environments, or entrainment of pieces of urban furniture within a flooded network of streets.

Similarly, specific numerical developments are needed for computing the behaviour of rescue vehicles, citizen evacuation, etc. using agent based approaches.

The authors recommend that future experimental research aims at getting more quantitative insights into these associated processes closely intertwined with flow behaviour during urban flooding. High quality experimental observations of these processes will contribute to unlock key bottlenecks in the current modelling practice and, consequently, pave the way for more integrative analyses of the urban water and anthropic systems under (extreme) flooding conditions.

Abt, S.R., Wittier, R.J., Taylor, A., Love, D.J., 1989. Human stability in a high flood hazard zone. Journal of the American Water Resources Association 25(4), 881-890. Apel, H., Martinez Trepat, O., Nghia Hung, N., Thi Chinh, D., Merz, B., Viet Dung, N., 2016. (2) see Abt et al. (1989), [START_REF] Russo | Pedestrian hazard criteria for flooded urban areas[END_REF], [START_REF] Xia | New criterion for the stability of a human body in floodwaters[END_REF][START_REF] Martínez-Gomariz | Experimental study of the stability of pedestrians exposed to urban pluvial flooding[END_REF] and the review by [START_REF] Kvocka | Flood hazard assessment for extreme flood events[END_REF]; older papers also exist. Citizen evacuation, rescue access R ( 5) N

(1) Reynolds-averaged Navier-Stokes equations;

(2) Large-Eddy simulations;

(3) Shallow-water equations (see [START_REF] Rodi | Turbulence modeling and simulation in hydraulics: a historical review[END_REF] for details of the models and applications);

(4) C = common practice, R = research models, U = unavailable in the context of urban flood modelling;

(5) Mostly for tsunami cases, see for instance [START_REF] Wang | An agent-based model of a multimodal nearfield tsunami evacuation: Decision-making and life safety[END_REF].

  Combined fluvial and pluvial urban flood hazard analysis: Concept development and application to Can Tho city, Mekong Delta, Vietnam. Natural Hazards and Earth System Sciences 16(4), 941-961. Arrault, A., Finaud-Guyot, P., Archambeau, P., Bruwier, M., Erpicum, S., Pirotton, M., Dewals, B., 2016. Hydrodynamics of long-duration urban floods: hacknewline experiments and numerical modelling. Natural Hazards and Earth System Sciences 16(6), 1413-1429.Baba, Y.,Ishigaki, T., Toda, K., 2017. Experimental studies on safety evacuation from underground spaces under inundation situations. Journal of JSCE 5(1), 269-278.

Table 1 :

 1 Databases available in literature for validation of urban flood numerical models 1

	Water origin (1)	Flow pattern	Location of set-up	Reference	Additional remarks	Length of set-up (m)	Steady (S)/ Unsteady (U)	[Availability] (2) Number of configurations	Types of data	Scale factors (3)	ID
					I Flow at street intersections
			INSA/LMFA (Lyon, France)	Mignot et al. (2012)		5	S	1 [B]	3D velocity field	SW=0.3m SF~1/50	(1)
	UR	3-branch subcritical junction	IIHR (Iowa, USA) Gent University (Gent, Belgium)	Weber et al. (2001) Schindfessel et al. (2015)	Rectangular sections with chamfers	22 33	S S	6 [A] 2 [D]	3D velocity field 3D velocity field	SW=0.91m SF~1/16 SW=0.98m SF~1/15	(2) (3)
			Gent University (Gent, Belgium)	Creëlle et al. (2017)		12	S	6 [D]	Water depth field	SW=0.4m SF~1/38	(4)
	UR	3 branch transcritical and supercritical junction	EPFL (Lausanne, Switzerland)	Hager (1989a & 1989b)		2	S	8 [A] & [C]	2D velocity field	SW=0.099m SF~1/152	(5)
	UR	3-branch subcritical bifurcation	INSA/LMFA (Lyon, France)	Mignot et al. (2013)	Without/with 10 obstacles (urban furniture)	5	S	14 flows x 10 obstacles [D]	* Flow discharge configs.) + 2D velocity field (for 1 flow with 10 obstacle	SW=0.3m SF~1/50	(6)
			IIHR (Iowa, USA)	Barkdoll et al. (1998)		2.7	S	1 [C]	2D velocity field & water depth field	SW=0.152m SF~1/100	(7)
	UR	3-branch critical & supercritical bifurcation	INSA/LMFA (Lyon, France) INSA/LMFA (Lyon, France)	ElKadi et al. (2011) Rivière et al. (2018)		5 5	S S	~100 [B] 62 [B]	Discharge distribution to the downstream branches + water depth field for 1 flow Discharge distribution and water depth fields	SW=0.3m SF~1/50 SW=0.3m SF~1/50	(8) (9)
	UR	4-branch subcritical intersection	INSA/LMFA (Lyon, France) UPC (Barcelona, Spain)	Rivière et al. (2011) Nanía et al. (2011)		5 8.5	S S	220 [B] 159 [A]	Discharge distribution to the downstream branches Discharge distribution to the downstream branches	SW=0.3m SF~1/50 SW=1.5m SF~1/10	(10) (11)
			INSA/LMFA (Lyon, France)	Rivière et al. (2014)		5	S	113 [B]	Discharge distribution to the downstream branches	SW=0.3m SF~1/50	(12)
	UR	4-branch transcritical & supercritical flows	INSA/LMFA (Lyon, France)	Mignot et al. (2009) & Mignot et al. (2008)		4.5	S	~200 [B] & [B]	Discharge distributions to the downstream branches + 8 water depth fields	SW=0.3m SF~1/50	(13)
			UPC (Barcelona, Spain)	Nanía et al. (2004) & Nanía et al. (2014)		8.5	S	~200 [B] & [B]	Discharge distribution to the downstream branches	SW=1.5m SF~1/10	(14)
					II Vertical exchanges (street/sewage)
	SO	1 overflow exchange structure (1 way: from	University of Coimbra (Coimbra,	Lopes et al. (2017) & Romagnoli et al.		0.6	S	4 [B] & [B]	3D velocity field	GW=0.6m SF~1	(15)

Table Click here to download Table: Table 1_final.DOC

 Click

	Water origin (1) Water origin (1)	Flow pattern Flow pattern	Location of set-up Location of set-up	Reference Reference	Additional remarks Additional remarks	Length of set-up (m) Length of set-up (m)	Steady (S)/ Unsteady (U) Steady (S)/ Unsteady (U)	Number of configurations [Availability] (2) [Availability] (2) Number of configurations	Types of data Types of data	Scale factors (3) Scale factors (3)	ID ID
		sewer to surface)	Portugal) UPC (Barcelona, Spain) Tsinghua Université (Beijing, China)	(2013) Russo, Gómez, and Tellez (2013) Zhou and W. Yu (2016)	Aligned obstacles: pervious & impervious	10	5.5	S	S	280 [B] 30 [D]	Exchanged discharge to sewer Water depths + 2D velocity fields	SF=1 Sw=0.05m SF~1/300	(16) (30)
	UR UR	inlet exchange structure (1 way: from surface to sewer) Uniform flow in a large grid of obstacles	Faculty of Civil Engineering (Belgrade, Serbia) DPRI (Kyoto, Japan) INSA/LMFA (Lyon, France)	Despotovic et al. (2005) Lee et al. (2012) Guillen-Ludena et al. (2017)	(without and with clogging effects) Aligned obstacles forces on buildings on rough bed with	8		5 6	S	S S	~100 [C] 12 [B] 50 [B]	Exchanged discharge to sewer + flow spreading on the street Exchanged discharge + water depths Normal water depth + Forces velocity field (1 exp) on buildings (50 exp) & 2D	SF~1 SF=1/10 Various Sw	(17) (18) (31)
	UR & SO RO	1 exchange structure (2 ways between surface and sewer) River overflow around obstacles	University of Sheffield (UK) Pennsylvania State U. (USA) U. of Coimbra (Portugal) Polytechnico di Milano (Italy)	Rubinato et al. (2017) & Martins et al. (2017) Herbich and Shulits (1964) Beg et al. (2017) Beretta et al. (2018)	Staggered obstacles Rain with/without wind effect and	8 9.5 2.23 16	S + U S S S	46 80 [C] [A] & [A] 19 [B] 1 [B]	Exchanged discharges (steady + time evolution) + Normal water depth (uniform flow) water depths Exchanged discharges + velocity fields + pressure heads Local velocities and water depths	SF=1/6 Various Sw SF=1/25 GW=0.6 SF~1	(19) (32) (33) (20)
	UR UR & SO RA UR & SO TS	street with several inlets 1 street with several exchange structures (2 ways) Rain over a group of buildings half-street + 3 exchange structures (2 ways: collect and overflow) Long wave over an obstacle grid at the shore	U. of Coimbra (Portugal) DPRI (Kyoto, Japan) University of Coimbra (Portugal) University of A Coruna (A Coruna, Spain) DPRI (Kyoto, Japan) Leibniz University (Hanover, Germany)	Leandro et al. (2010) Bazin et al. (2014) Isidoro et al. (2013) JinNoh et al. (2016) Cea et al. (2010) Fraga et al. (2017) Tomiczek et al. (2016) Goseberg (2013)	static/dynamic storm effects. 4 tested building distributions Rain over buildings with roofs Aligned obstacles Aligned and staggered obstacles	2 2.5 45 18	36 10 6	S S + U U U S + U U	36 [B] 2 steady 2 unsteady [C] 30 [B] 72 [B] 6 steady 2 unsteady [B] 5 [B] 63 (2 repetitions) [B] 24 (290 with repetitions) [A]	Exchanged discharge Water depth and pressure head along the street (+ total exchanged discharge for Bazin2014) Outflow hydrographs Outflow hydrographs Water depth in street and in pipes + discharge in pipes Water depth + pressure on obstacles Maximum run-up extension, water depths, velocities	SW=0.5m SF~1/30 Sw=0.8m Various Sw SF~1/20 Various Sw SF=1/20 SF=1 SF=1/20 Various Sw	(21) (34) (22) (35) (23) (36) (37)
					III Flow through a regular grid of emerging obstacles IV Urban district
	UR UR RO UR UR	Non-uniform flow in a patch of obstacles Flow in a street network Flow around buildings	UCL (Louvain la Neuve, Belgium) DPRI (Kyoto, Japan) IMFS (Strasbourg, France) CESI (Milan, Italy) National Taiwan University (Taiwan) Univ. of South Carolina (Columbia, USA) UNSW (Sydney, Australia) KICT (South Korea) Dokuz Eylül University (Izmir,	Soares-Frazão and Zech (2008) Ishigaki et al. (2003) Velickovic et al. Arrault et al. (2017) Lhomme et al. (2007) (2016) and Finaud-Guyot et al. (2018) Testa et al. (2007) Huang et al. (2014) LaRocque et al. (2013) Smith et al. (2016) Kim et al. (2015) Güney et al. (2014)	aligned obstacle grid (aligned with flow axis and rotated) With & without connections (48) to underground Staggered obstacle grid (aligned with Synthetic district flow axis) aligned & staggered obstacles River overtopping towards urbanized area aligned obstacles (aligned with flow Mostly supercritical flows axis) Aligned obstacles Dam break on a group of buildings	15 20 5 5 12 8 12.5 30 16	U (dam break) U S S U (dam break) S S S U (dam break) U	2 [B] 2 [C] 20 [B] 1 [D] 16 [B] 12 [A] 2 [A] 7 [D] 1 [A] 2 [D] 1 (5 repetitions) [D]	Water depth Surface velocity fields Water depths, surface velocities & outflow discharges Water depth profiles Water depths Surface velocity fields Water depth profiles & Outflow discharges Water depths Surface velocity field + water depth field Water depth profiles Surface velocity field + water depth field Water depths Water depths (10 locations) and velocities (4 locations)	Sw=0.1m SF~1/150 SF=1/100 SF=1/200 SF=1/100 SF=1/50 Various Sw SF=1/30 SW=0.1m SF~1/150 SF=1/150	(24) (38) (25) (39) (26) (27) (40) (28) (41) (29) (42)
					3

Table 2 :

 2 Urban flood processes and corresponding data availability for validation S=scare, C=comprehensive(1) see recent extensive review by[START_REF] Martínez-Gomariz | Stability criteria for flooded vehicles: a state-of-the-art review[END_REF] and recent work by[START_REF] Martínez-Gomariz | A new experiments-based methodology to define the stability threshold for any vehicle exposed to flooding[END_REF].

	Main processes	Sub-processes	Id. from Table 1	S,C
		Rain on urban domain	34, 35	S
		River overtopping towards urban area	33, 40, 43	C
	Origin of	Dam break upstream from city	24, 27, 29, 42	C
	the water	Tsunami (long) wave invading the city	36, 37, 44, 45	C
		Wave submersion / storm surges	Not available	-
		Sewage overflow	15, 19-23	C
		Open-channel flows around a group of buildings:
		• Steady sate	25, 26, 28, 30-33, 40, 41	C
		• Transient flow (bank overtopping, flood wave, dike submersion wave…)	24, 27, 29, 34-37, 42-45	C
		• Subcritical flow regime	25, 26, 28, 30-33	C
		• Supercritical flow regime	41, 43	S
	Flow in	• Wave front	24, 27, 29, 36, 37, 42, 44, 45	C
	streets	Open-channel flows in one street intersection	1-14	C
		Open-channel flows in a street network:
		• Steady	39	S
		• Transient flow	38	S
		• Subcritical flow regime	38, 39	S
		• Supercritical flow regime	Not available	-
		Flow interaction with fixed furniture	6	S
		Sewer-street exchanges:
		• 1 exchange structure	15-20	C
	Flow in	• 1 street & 1 pipe with exchange structures	21-23	S
	other compart-	• Street & pipe network with exchange structures	Not available	-
	ments of the urban	Flow within and through buildings / building blocks	30, 43 + Liu et al. (2018)	S
	fabric	Flow through open-areas: gardens / semi-
		urbanized private parcel / above walls / through	Not available	-
		vegetated or semi-pervious fences…
		Flow in underground spaces	38 + Takayama et al. (2007)	S
		Cars transport :
		• Stability of a single car	Ref (1)	C
		• A group of cars in one street intersection creating dams	Not available	-
		• Single car or a group of cars transported in a street network	Not available	-
	Associated events	Risk and evacuation of people : • Human stability • Human evacuation (through doors, corridor, staircase, from cars)	Ref (2) Ref (3)	C S
		Forces on buildings	31, 43	S
		Sediment transport	43	S
		Rescue access and processes (via army, ambulance, fire-men, etc…)	Not available	-
		Pollution dispersion	Not available	-

* *

Table Click here to download Table: Table 2.DOC

 Click

Table 3 :

 3 Typology of numerical models applied to compute urban flood events

	Type of model	Typical processes	Level of development (4)	Available exp. data
				(Yes, No)
	3D RANS (1) or LES (2)	1 street intersection Flow around 1 building	C	Y
	2D SWE (3)	Street surface (local to large scale)	C	Y
	2D SWE + porosity models	Urban district	C / R	Y
	1D-2D SWE (1D=streets / 2D=crossroads)	Urban district	R	Y
	1D-2D SWE (1D=sewer / 2D=streets)	Coupled flow in streets and sewers	R	Y
	2D SWE or Boussinesq-type equations	Overland Tsunami	C	Y
	Hydrodynamics + morphodynamic model	Building foundation scour, sediment deposits around buildings…	U	N
	Hydrodynamics	Flow exchange between streets and
	+ empirical /analytical	built-up or open areas through	U	N
	exchange formulae	openings (gates, doors, windows…)
	Hydrodynamics + advection-diffusion model	Pollutant transport	U	N
	Hydrodynamics + Lagrangian model	Transport of urban furniture and debris (cars, trees, etc…)	U	N
	Hydrodynamics
	+ agent based model

Table Click here to download Table: Table 3.DOC

 Click

(3) see[START_REF] Ishigaki | Evacuation criteria during urban flooding in underground space[END_REF] Baba et al. (2017)

List of Table captions:

Table 1: Databases available in literature for validation of urban flood numerical models Table 2: Urban flood processes and corresponding data availability for validation Table 3: Typology of numerical models applied to compute urban flood events Water depths and velocities SF=1/50 (45)

(1) UR=Upstream runoff, RO = River overflow, SO = Sewer overflow, TS=Tsunami, RA = Rain over the domain