Flavia Tauro

Time of concentration: a paradox in modern hydrology

Abstract The time of concentration is a primary parameter for a variety of modern hydrological models adopted in professional and scientific communities. Nevertheless, a universally accepted working definition of this parameter is currently lacking and several definitions can be found in the technical literature along with related estimation procedures. This study brings to light the inherent variability of these definitions through the empirical analysis of four small basins. These case studies demonstrate that available approaches for the estimation of the time of concentration may yield numerical predictions that differ from each other by up to 500%. Editor D. Koutsoyiannis Citation Grimaldi, S., Petroselli, A., Tauro, F. and Porfiri, M., 2012. Time of concentration: a paradox in modern hydrology. Hydrological Sciences Journal, 57 (2), 217–228.

Large-Scale Particle Image Velocimetry From an Unmanned Aerial Vehicle

Large-scale particle image velocimetry (LSPIV) enables nonintrusive and continuous characterization of surface flow velocities in natural watersheds. However, current LSPIV implementations are based on hxed cameras that only allow for surface flow monitoring at a limited number of locations on the water stream. This paper seeks to leverage the growing held of unmanned aerial vehicles to transform LSPIV practice, by enabling rapid characterization of large water flow systems in areas that may be difhcult to access by human operators. Toward this aim, a lightweight and low cost quadrotor is developed to host a digital acquisition system for LSPIV. A gimbal is realized in house to maintain the camera lens orthogonal with respect to the water surface, thus preventing image orthorectihcation. Field experiments demonstrate that the vehicle is able to stably hover above an area of 1 × 1 m2 for 4 min with a payload of 532 g. The feasibility of quadrotor-based LSPIV is demonstrated through tests in an outdoor laboratory setting and over a natural stream.

Orienting the camera and firing lasers to enhance large scale particle image velocimetry for streamflow monitoring

Large scale particle image velocimetry (LSPIV) is a nonintrusive methodology for continuous surface flow monitoring in natural environments. Recent experimental studies demonstrate that LSPIV is a promising technique to estimate flow discharge in riverine systems. Traditionally, LSPIV implementations are based on the use of angled cameras to capture extended fields of view; images are then orthorectified and calibrated through the acquisition of ground reference points. As widely documented in the literature, the identification of ground reference points and image orthorectification are major hurdles in LSPIV. Here we develop an experimental apparatus to address both of these issues. The proposed platform includes a laser system for remote frame calibration and a low-cost camera that is maintained orthogonal with respect to the water surface to minimize image distortions. We study the feasibility of the apparatus on two complex natural riverine environments where the acquisition of ground reference points is prevented and illumination and seeding density conditions are challenging. While our results confirm that velocity estimations can be severely affected by inhomogeneously seeded surface tracers and adverse illumination settings, they demonstrate that LSPIV implementations can benefit from the proposed apparatus. Specifically, the presented system opens novel avenues in the development of stand-alone platforms for remote surface flow monitoring.

Characterization of buoyant fluorescent particles for field observations of water flows.

In this paper, the feasibility of off-the-shelf buoyant fluorescent microspheres as particle tracers in turbid water flows is investigated. Microspheres’ fluorescence intensity is experimentally measured and detected in placid aqueous suspensions of increasing concentrations of clay to simulate typical conditions occurring in natural drainage networks. Experiments are conducted in a broad range of clay concentrations and particle immersion depths by using photoconductive cells and image-based sensing technologies. Results obtained with both methodologies exhibit comparable trends and show that the considered particles are fairly detectable in critically turbid water flows. Further information on performance and integration of the studied microspheres in low-cost measurement instrumentation for field observations is obtained through experiments conducted in a custom built miniature water channel. This experimental characterization provides a first assessment of the feasibility of commercially available buoyant fluorescent beads in the analysis of high turbidity surface water flows. The proposed technology may serve as a minimally invasive sensing system for hazardous events, such as pollutant diffusion in natural streams and flash flooding due to extreme rainfall.

Measurements and Observations in the XXI century (MOXXI): innovation and multi-disciplinarity to sense the hydrological cycle

ABSTRACT To promote the advancement of novel observation techniques that may lead to new sources of information to help better understand the hydrological cycle, the International Association of Hydrological Sciences (IAHS) established the Measurements and Observations in the XXI century (MOXXI) Working Group in July 2013. The group comprises a growing community of tech-enthusiastic hydrologists that design and develop their own sensing systems, adopt a multi-disciplinary perspective in tackling complex observations, often use low-cost equipment intended for other applications to build innovative sensors, or perform opportunistic measurements. This paper states the objectives of the group and reviews major advances carried out by MOXXI members toward the advancement of hydrological sciences. Challenges and opportunities are outlined to provide strategic guidance for advancement of measurement, and thus discovery.

Flow monitoring with a camera: a case study on a flood event in the Tiber River

Monitoring surface water velocity during flood events is a challenging task. Techniques based on deploying instruments in the flow are often unfeasible due to high velocity and abundant sediment transport. A low-cost and versatile technology that provides continuous and automatic observations is still not available. Among remote methods, large-scale particle image velocimetry (LSPIV) is an optical method that computes surface water velocity maps from videos recorded with a camera. Here, we implement and critically analyze findings obtained from a recently introduced LSPIV experimental configuration during a flood event in the Tiber River at a cross section located in the center of Rome, Italy. We discuss the potential of LSPIV observations in challenging environmental conditions by presenting results from three tests performed during the hydrograph flood peak and recession limb of the event for different illumination and weather conditions. The obtained surface velocity maps are compared to the rating curve velocity and to benchmark velocity values. Experimental findings show that optical methods should be preferred in extreme conditions. However, their practical implementation may be associated with further hurdles and uncertainties.

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

Fluorescent eco-particles for surface flow physics analysis

In this letter, we describe a novel methodology for fabricating inexpensive environmentally-friendly fluorescent microparticles for quantitative surface flow visualization. Particles are synthesized from natural white beeswax and a highly diluted solution of a nontoxic fluorescent red dye. Bead fluorescence exhibits a long lifetime in adverse conditions, such as exposure to weathering agents, and is enhanced by Ultra Violet radiation. The fluorescent eco-particles are integrated in a particle image velocimetry study of circular hydraulic jump to demonstrate their feasibility in tracing complex surface flows.

Unraveling Flow Patterns through Nonlinear Manifold Learning

From climatology to biofluidics, the characterization of complex flows relies on computationally expensive kinematic and kinetic measurements. In addition, such big data are difficult to handle in real time, thereby hampering advancements in the area of flow control and distributed sensing. Here, we propose a novel framework for unsupervised characterization of flow patterns through nonlinear manifold learning. Specifically, we apply the isometric feature mapping (Isomap) to experimental video data of the wake past a circular cylinder from steady to turbulent flows. Without direct velocity measurements, we show that manifold topology is intrinsically related to flow regime and that Isomap global coordinates can unravel salient flow features.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F2 partially inbred population (termed here ‘POP6’), whose F1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (Tc) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. Tc derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance (gs) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.