bluuebunny/crossref_metadata_2025 huggingface dataset:
Laboratory study on wave attenuation by submerged mangrove canopies
Authors: Zhang Rong , Lei Jiaxin , Chen Yongping
Published: February 2023

With global climate change and sea level rise, the frequency and strength of coastal hazards are increasing. Nature-based solutions have been recognized as a kind of sustainable approach to coastal protection. Among them, mangroves play a crucial role in attenuating coastal waves, tides, and storm surges. From top to bottom, mangrove trees have a typical three-layered structure, consisting of leafy canopies, thick trunks, and intertwined roots. Most previous studies investigating mangrove-wave interaction oversimplified mangroves as rigid cylinders. In this way, the effects of the vertical morphology structure of mangroves on wave decay are ignored and have not been fully understood. To bridge this knowledge gap, we carried out a series of flume tests to compare the differences in the wave attenuation ability of artificial near-natural mangrove models and rigid cylinder models. The wave damping factor was calculated based on fitting the measured wave height evolution through the mangrove zone to the wave decay formula proposed by Dalrymple et al. (1984). It has been observed that the submerged mangrove canopies significantly enhanced the wave attenuation rate. To unify the correlations between the wave decay parameter and the varying submerged mangrove volumes under different waves and water depths, we proposed a new parameter, the hydraulic submerged volume index (HSVI), to quantify the wave damping contributions by mangrove canopies, stems, and roots respectively. A fitted linear correlation between the HSVI and wave damping factor was induced. Then the bulk drag coefficient versus nondimensional hydraulic parameters, i.e. Reynolds number Re, Keulegan-Carpenter number KC, and Ursel number Ur, were discussed in detail, and modified correlations considering the effects of varying characteristic length scales of nondimensional hydraulic parameters were proposed.
Improvement of Multi-Radar Quantitative Precipitation Nowcasting with Consistency Correction Method
Authors: Chu Zhigang
Published: February 2023

The quality of mosaic QPE directly determines the accuracy of QPF products from nowcasting models. However, there is a common spatial discontinuity phenomenon caused by the biases of multiple radars in mosaic QPE. Consistency correction, a type of multi-radar quality control method, can be used to mitigate the spatial discontinuity of mosaic QPE, but its improving effect on QPF products should be analyzed.For this consideration, a consistency correction method based on GPM KuPR proposed by Chu et al (2018a) was applied to the three S-band operational radars of China, and the improvement on QPE by Z-R relationship, deterministic QPF by S-SPROG (Spectral Prognosis), and ensemble QPF by STEPS (Short-Term Ensemble Prediction System) were analyzed. The results showed: 1) the raw reflectivity factors by the three operational radars over the same equidistance area were significantly different. After the consistency correction, the differences decreased to be less than 0.5 dB and the spatial discontinuity of mosaic products disappeared. 2) The precision of mosaic QPE was significantly improved after the correction, and the average RMSE of QPE decreased by 19.5%, and the TS of heavy rainfall and above rose by 44.8%. 3) The 0-1h deterministic QPF by S-SPROG, and ensemble QPF by STEPS were significantly improved after the correction. The deterministic (ensemble) TS of moderate rain and above rose by 11.9% (10.2%), and that of heavy rain and above increased by 34.2% (38.7%). 4) Furthermore, the consistency correction method contributed to precipitation velocity estimation, and decreased its RMSE by 25.0%. Clearly, the consistency correction method is significantly contributive to multi-radar mosaic QPE and precipitation nowcasting.
The San Bartolo lava flow field, Stromboli volcano, Italy: Reconstruction of the most recent historic flank eruption (2 kyr) affecting the inhabited area by photogrammetric and LIDAR from UASs aimed at hazard assessment
Authors: Vicari Annamaria , Famiglietti Nicola , Calvari Sonia , Marotta Enrica , Avino Rosario , Belviso Pasquale , Harris Andrew , De Luca Giovanni , Memmolo Antonino , Minichiello Felice , Peluso Rosario
Published: February 2023

The San Bartolo lava flow field is the most recent flank eruption occurred at Stromboli volcano about 2 ka ago on the NE flank of the island. Despite its importance in being the most recent example of flank activity outside the barren Sciara del Fuoco slope, where the recent activity concentrated, the eruption duration, its volume, and the sequence of events has not yet been reconstructed. In this paper, we present a new survey of the lava flow field, carried out both on the field and photogrammetric and LIDAR surveys from UASs, in order to estimate the erupted lava volume and to reconstruct the sequence of events and infer a possible duration and impact of the eruption. The analysis of the surveys allowed us to verify the contact with previous lava flow fields, allowing a more precise lateral extension of the lava delta along the coast, as well as an estimation of the thickness and volume, at least for the subaerial portion of the lava flow field. The morphology analysis of the lava flow field allowed us to recognize structures suggesting inflation and then stationing of the lava flow fronts, features indicating a long-lasting eruption and a complex interaction with the sea. Our results can provide a useful scenario should a flank eruption occur in the future, a possibility that was close to happening in 1998, when the ground deformation stations revealed a lateral intrusion in the shallow supply system of the volcano.  
NLP-based Cognitive Search Engine for the GEOSS Platform data
Authors: Kopsinis Yannis , Flokas Zisis , Mitropoulos Pantelis , Petrou Christos , Siozos Thodoris , Siokas Giorgos
Published: February 2023

Effectively querying unstructured text information in large databases is a highly demanding task. Conventional approaches, such as an exact match or fuzzy search, return valid and thorough results only when the user query adequately matches the wording within the text or the query is included in keyword-tag lists. The GEOSS portal relies on conventional search tools for data and services exploration and retrieval, limiting its capacity. This challenge, recent advances in Artificial Intelligence (AI)-based Natural Language Processing (NLP) try to surpass with enhanced information retrieval and cognitive search. Rather than relying on exact or fuzzy text matching, it detects documents that semantically and conceptually are close enough to the search query. The EIFFEL EU-funded project aims to reveal the role of GEOSS as the default Digital Portal for building Climate Change (CC) adaption and mitigation applications and offer the Earth Observation community the ground-breaking capacity of exploiting existing GEOSS datasets. To this end, as a lead technological partner of the EIFFEL consortium, LIBRA AI Technologies, designs and develops an end-to-end advanced cognitive search system dedicated to the GEOSS Portal and exceeds current challenges.The proposed system comprises an AI language model optimized for CC-related text and queries, a framework for collecting a sizeable CC-specific corpus used for the language model specialization, a back-end that adopts modern database technologies with advanced capabilities for embedding-based cognitive search matching, and an open Application Programming Interface (API). The cognitive search component is the backbone of the EIFFEL visualisation engine, which will allow any GEOSS user, as well as the EIFFEL Climate Change application developing teams, to detect GEOSS data objects and services that are of interest for their research and application but could not effectively get accessed with the available GEOSS Portal search engine.The work described in this abstract is part of the EIFFEL European project. The EIFFEL project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101003518. We thank all partners for their valuable contributions.
Characteristics of the Potential Vorticity and its Budget in the Surface Layer over the Tibetan Plateau
Authors: Sheng Chen , Wu Guoxiong , He Bian , Liu Yimin
Published: February 2023

The variability of interior atmospheric potential vorticity (PV) is linked with PV generation at the Earth’s surface. The present paper reveals the features of the surface PV and provides a stepping stone to investigate the surface PV budget. In this study, the formats of the PV and PV budget adopting a generalized vertical coordinate were theoretically examined to facilitate the calculation of the surface PV and its budget. Results show that the formats of the PV and PV budget equations are independent of the vertical coordinate. While the vertical component of the surface PV dominates over the platform of the Tibetan Plateau, the horizontal component plays an important role over the slopes of the Tibetan Plateau, especially the southern slope owing to the strong in-situ meridional gradient of the potential temperature. These results indicate that the employment of complete surface PV not only provides a finer PV structure but also more appropriately reveals its effect on atmospheric circulation. Diagnosis based on reanalysis and model output demonstrates that the surface PV budget equation is well balanced both in terms of the climate mean and synoptic process, and the surface PV budget in June has a prominent diurnal cycle. The diabatic heating with a minimum in the early morning and a maximum from evening to midnight contributes dominantly to this diurnal cycle. It is further indicated that positive PV generation due to diabatic heating is essential for the formation, development, and movement of the Tibetan Plateau vortex.
Difference between rainy and dry year in Relations of activity and hydraulic parameters of landslide prone area: A case study in Xinzhuang, Southern Taiwan
Authors: Wang Ji-Shang , Lai Tung-Yang , Jan Chyan-Deng , Fu Guei-Lin , Tsai Cheng Hsiu , Liou Wei-Ze
Published: February 2023

The landslide prone area, Xingzhuang has been identified as a deep-seated landslide prone area by Taiwan authorities. Where covers a 10.3 hectares’ area with an average slope of 22.8 degrees and 20 buildings around the slope toe. The majority lithology of upper slope is sand-shale interbedded with highly sand contented, which differs from lower slope in shale with mud contented. In order to grasp the activities of this area, we have installed a real-time compound monitoring station including GNSS, biaxial tiltmeter, ground water level meter, and rain gauge.The rainfall depth of 2021 and 2022 was 4,175 mm and 1,691 mm respectively. The difference was larger than 2400 mm in our study area which might induced the different activity behaviors. In this study, we discussed the relations of slope activity and hydrological parameters in last two years. The results show (1) The variation of X-direction of tiltmeter were about 7,500 and 3,500 (sec) in 2021 and 2022, respectively. The variation of Y-direction of tiltmeter were about 6,500 and 4,500 (sec) in 2021 and 2022, respectively. (2) In the same 6-hours rainfall intensity, the 6 hours tilt-angle of X and Y direction in 2021 were both two times of 2022. (3) In the same ground water level, the 6 hours tilt-angle of X and Y direction in 2021 were about 2 and 1.5 times of 2022, respectively. (4) In the same variation of 6-hours ground water level, no matter raising or decline ground water level the 6 hours tilt-angle of X and Y direction in 2021 were about 2.2 and 1.5 times of 2022, respectively. And the change rate of the 6 hours tilt-angle would be accelerated when the 6-hours variation of groundwater level was higher than 0.4 meters. On the whole, the rainy year would induce more active than dry year.
Emergence of Low-Frequency Temperature Variability in Instrumental Data and Model Simulations
Authors: Hébert Raphael , Laepple Thomas
Published: February 2023

The amplitude and spatial distribution of low-frequency natural variability is determinant for regional climate projections, but it is still poorly understood.  In a previous study, pollen-based temperature reconstructions were used to quantify spatial patterns of millennial temperature variability. This showed an inverse relationship across timescales with sub-decadal variability from instrumental data in extra-tropical regions over land (Hébert et al., 2022, under review). We concluded that due to varying marine influence, regions characterized by stable oceanic climate at sub-decadal timescales experience stronger long-term variability while continental regions with higher sub-decadal variability show weaker long-term variability. Indications of this relationship could also be inferred from instrumental data alone as regions of low sub-decadal variability were more likely to exhibit a steeper increase of variability over multi-decadal timescales and vice versa.  In the current work, the relationship found in the instrumental data was further investigated using different instrumental products. In addition, a large multi-model ensemble of CMIP6 models, as well as single-model ensembles, were considered for analysis and it was found that they do not systematically reproduce the relationship found in the instrumental data. This indicates a fundamental deficiency in the model simulations with regard to the mechanism driving the emergence of low-frequency climate variability. This characteristic being related to multi-decadal variability thus has important significance for multi-decadal regional climate projections and might be used as an emergent constraint in model evaluation and inter-comparison.
Saltmarsh rejuvenation in front of a levee - using a numerical model to inform designs
Authors: Dijkstra Jasper , Dzimballa Sarah , van Nieuwkoop Joana , Doeleman Madelief
Published: February 2023

The elevation and vegetation cover of salt marshes can contribute to wave attenuation in front of a levee, thus to coastal flood hazard reduction. The magnitude of such a contribution depends on the size, shape and cover of the marsh in relation to the normative hydrodynamic conditions. This function can change over time as the marsh grows or decays. Often, a high, mature marsh is appreciated because of the largest provision of flood hazard reduction compared to a lower and younger marsh. However, older marshes such as the Zuidgors along the Western Scheldt (Netherlands) might provide less ecological value (e.g., biodiversity) because they are lacking in dynamics and have a very homogeneous vegetation cover. For this reason, rejuvenation of older marshes is considered as a management option – but should not affect coastal safety unacceptably.  

Designs for marsh restoration or rejuvenation are often based on expert estimates. Because such an intervention has not often been carried out in similar environmental conditions, and because the development can be strongly determined by biophysical feedbacks, it is difficult to estimate in advance how the intervention will develop over time (decades). Especially quantitative substantiation of effects of different design variants on wave attenuation, siltation rate, plant and macrofauna establishment and possible use as a cattle grazing area is lacking.

In order to provide such insight in advance, and thus be able to make a more effective design for the various functions together, a combination of a flood hazard assessment tool (Hydra-NL) and a numerical model that imitates the development of a salt marsh may be a solution. To this end, a combination of Delft3D-FM and a salt marsh development model (Brückner et al., 2020) was created, showing how vegetation colonizes the excavated area in different design variants: higher or lower elevation, more or less exposed to waves, and wider connection to the open waters of the Western Scheldt. In particular, the elevation and dimensions of the intervention strongly determine the expected bed level change, and thus further development. The excavation in its present form has no significant effect on flood safety.
EURO1k: A high-resolution European weather model developed by Meteomatics
Authors: Pasquier Julie Thérèse , Rausch Johannes , Stauch Alexander , Fengler Martin
Published: February 2023

Accurate and precise weather forecasting is essential for a wide range of applications and industries, from agriculture to transportation to renewable energy. However, current weather models often struggle to represent the weather accurately due to limitations in spatial resolution. Global models with broad resolution are unable to represent small-scale weather features, such as convective thunderstorms or local wind patterns, while regional high resolution models are highly dependent on boundary conditions and typically provide forecasts for a small domain. To fill this gap, Meteomatics has developed the EURO1k model, the first pan-European weather model with a 1km2 resolution. The EURO1k model consists of approximately 20 million grid points and is run 24 times per day, with a forecast horizon of 24 hours. It is based on the WRF (Weather Research and Forecasting) model and uses global ECMWF-IFS model data for boundary conditions. In addition to standard data sources such as weather stations, radar and satellite data, and radiosondes, the EURO1k model also ingests data from a network of Meteodrones, small unmanned aircraft systems (UAS) developed by Meteomatics which collect vertical atmospheric profiles up to 6000m in altitude. The high resolution of the EURO1k model allows it to accurately represent small-scale weather patterns, resulting in highly accurate and precise forecasts. This is evident in verifications against weather station observations, which show a very good agreement between model output and a range of weather variables including wind, temperature, and radiation. Statistical analyses of EURO1k model output against observations from 5000 weather stations in Europe demonstrate better accuracy compared to other global and regional models. This has important implications for industry and the public. The EURO1k model can improve the forecasting of extreme weather events, allowing for better preparation and response. It can also enhance the prediction of renewable energy production, which depends on weather conditions. This increases the cost efficiency of renewable energies and help to reduce CO2 emissions. And, most importantly, it provides a more accurate and reliable weather forecast for communities across Europe. Overall, the EURO1k model represents a major advance in numerical weather prediction, bringing improved understanding and forecasting of the weather to a wide range of users.
Effectiveness for Drought of Nature-based Flood Measures in Headwater Streams: Evidence-Based Practise in NW-Europe
Authors: Lansu Angelique , Wieles-Rietveld Charlotte , Ruysseveldt Nico , Bogatinoska Borjana , van Wijnen Jikke , van Lamoen Frank , Stoorvogel Jetse
Published: February 2023

Drought is a topical issue, given extreme drought records in NW Europe, the establishment of water coordination bodies and the perceived impact of drought on society. Climate change is driving disruptions in the hydrological cycle. In North-West Europe, in recent years, solutions to counter the effects of floods and flooding have been co-designed in a participatory manner in society. The question in this study is whether these Nature-based Solutions (NbS) to adapt to flooding are also effective to mitigate the effects of drought. We studied this research question based on field expertise from some 40 water professionals involved in the co-creation and implementation of NbS in 8 headwater catchments in NW Europe (southern England, northern France, Flanders, southern Netherlands; project Interreg 2 Seas Co-Adapt (2019-2023).Based on the concept of evidence-based practice (EBP), we combined the field expertise of these water professionals with scientific knowledge to arrive at best practices. The NbS studied were predefined by process function (geomorphological, hydrological. soil-land).  To collect and evaluate the field expertise (practical knowledge), we conducted a Consensus Decision Process. This process consisted of a brainstorming phase (collecting) and a consensus phase (evaluating). This process at two time-intervals was conducted online, in the form of synchronous, online sessions in an online collaboration tool (Mural). The scientific knowledge from a Systematic literature review on NbS as flood measures were compared in the EBP with the collected practical knowledge from the Consensus Decision Process, and evaluated based on the criteria 'effect on drought' and 'synergy/trade-off with NbS'. Obtained results have been tested on outcomes from modelling NbS and drought in catchment Aa/Weerijs (NL; H2020 EIFFEL4Climate; 2021-2024) and expertise of the water professionals of this catchment. The result is that the most effective drought mitigation measures are: storage solutions, slow the flow measures and soil processes. If the underlying steering processes (geomorphology, hydrology, soil-land) are included in the design of flood measures, it is expected that after implementation of NbS in head waters, the water storage capacity will increase and ecological drought will decrease.
A Novel Transform For Extracting Dispersion Curve From Multiple Components of Ambient Noise Cross-correlation Function
Authors: Zhang Gongheng , Feng Xuping , Chen Xiaofei , Liu Qi , Gao Lina
Published: February 2023

Ambient noise tomography has been a widely used method for imaging the structure of the lithosphere. A key step in this method is extracting the dispersion curve from ambient noise cross-correlation. Based on the single force displacement formula of Generalized Reflection and Transmission method, we obtained the type of Bessel function in different components of the cross-correlation function. Borrowing the idea of the S transformation and replacing the exponential function in which with the corresponding Bessel function to different components of cross-correlation function, we define a new transformation, named SJ transformation, to extract Rayleigh wave dispersion curve from ZZ, ZR, RZ, RR component and Love wave dispersion curve from TT component. Using synthetic test, the extracted dispersion curve fits the theoretical dispersion curve well, which’s error rate < 1%, and in field data test, the extracted dispersion curve of the Rayleigh wave from different component matches each other well. Although the SJ spectrum of ZZ component may be distorted by noise, there may be no influence in other components, which provide the possibility to extract Rayleigh wave dispersion curve with a wider frequency band.
Addition of Alkalinity to Rivers: a novel strategy for Ocean Alkalinity Enhancement
Authors: Sterling Shannon , Halfyard Edmund , Hart Kristin
Published: February 2023

Effective carbon dioxide removal (CDR) strategies are urgently needed to reduce risks of climate change. Here we propose a new strategy for Ocean Alkalinity Enhancement that targets the land-to-ocean component of the inorganic carbon cycle: river-based alkalinity and weathering enhancement (RAWE). RAWE adapts freshwater acidification mitigation technology to capture CO2 through mineral weathering and by increasing rivers’ capacity to retain and transport bicarbonate to long-term storage in the ocean. Field experiments in Nova Scotia rivers demonstrate the proof of concept, and global-scale modelling of RAWE indicates a potential millions of tonnes of CDR per year. Results suggest that RAWE meets CDR criteria, such as scalability, permanence, safety, and ability to simply quantify the CO2 removed, whilst delivering ecological co-benefits. 
Application of Deep Recurrent Neural Networks for Flood Prediction and Assessment
Authors: Heidari Elnaz , Samadi Vidya
Published: February 2023

Recent years have seen an uptick in the frequency of flood records occurring in the United States, with South Carolina (SC) being particularly hard hit. This study developed various deep recurrent neural networks (DRNNs) such as Vanilla RNN, long short-term memory (LSTM), and Gated Recurrent Unit (GRU) for flood event simulation. Precipitation and the USGS gaging data were preprocessed and fed into the DRNNs to predict flood events across several catchments in SC. The DRNNs are trained and evaluated using hourly datasets, and the outcomes were then compared with the observed data and the National Water Model (NWM) simulations. Analysis suggested that LSTM and GRU networks skillfully predicted the shape of flood hydrographs, including rising/falling limb, peak rates, flood volume, and time to peak, while the NWM vastly overestimated flood hydrographs. Among different climatic variables that were forced into the DRNNs, rainfall amount and spatial distribution were the most dominant input variables for flood prediction in SC.
Applications of multi-scale remote sensing data to determine potential landslides in the Laonong watershed areas
Authors: Chen Rou-Fei , Li Chris , Chen Tzung-Ting , Chen Yi-Chung
Published: February 2023

Since its opening to traffic, the Southern Cross-Island Highway has been playing an important role in linking Southern and Eastern cities in Taiwan. Nevertheless, Southern Cross-Island Highway was firstly struck by the 1999 Ji-ji Earthquake, which resulted in collapses along the route, and then Typhoon Morakot, which caused damages of 22 bridges and a number of deep-seated landslides between Meishan of Kaohsiung and Siangyang on the East. A long-term road reconstruction and improvement project of Southern Cross-Island Highway was therefore initiated in 2009. In August 2021, the torrential rain triggered a deep-seated landslide located in the upstream of Yusui Stream and an enormous amount of debris was brought to the downstream and crashed Minbaklu Bridge between Meishan and Siangyang. Although the Directorate General of Highways cleared the route and built a temporary steel bridge for people to pass through, this incident has highlighted the fact that the road breaks when plum rain or torrential rain occurs. This project has adopted optical satellite imagery, aerial LiDAR and UAV, technologies that complement each other with their respective benefits and drawbacks. Aerial LiDAR can remove vegetation and present the real ground surface, enabling researchers to calculate the volume of landslide materials of Yusui Stream and Putanpunas Stream using LiDAR derived DTM (digital terrain model) constructed based on the images collected between 2016 and 2022. The three-dimensional terrain interpretation and landslide volume calculation results reveal that the landslide surface area had been continuously increased over the last six years due to abundant rainfall brought by typhoons and torrential rain, causing an enormous volume of debris falling into the main river channel and piled up at its confluence with Laonong River. Nevertheless, the interpretation can be hard in areas with small-scale shallow landslide due to smaller changes to the surface elevation. Optical satellite imagery before and after the sliding is therefore required to quantify the change of landslide volume, helping to determine potential landslide and accumulation areas even more effectively.
Lunar plasma and electrostatic environment: numerical approach and its future prospects
Authors: Miyake Yohei , Nakazono Jin
Published: February 2023

Mission preparation for lunar exploration using landers has been rapidly increasing, and strong demand should arise toward precise understanding of the electrostatic environment. The lunar surface, which has neither a dense atmosphere nor a global magnetic field, gets charged electrically by the collection of surrounding charged particles of the solar wind or the Earth's magnetosphere. As a result of the charging processes, the surface regolith particles behave as "charged dust grains". Dust particles have been suggested to have adverse effects on exploration instruments and living organisms during the lunar landing missions, and their safety evaluation is an issue to be solved for the realization of sustainable manned lunar explorations. It is necessary to develop comprehensive and organized understanding of lunar charging phenomena and the electrodynamic characteristics of charged dust particles.It is widely accepted that the surface potential of the lunar dayside is, "on average" several to 10 V positive due to photoelectron emission in addition to the solar wind plasma precipitation. Recent studies, however, have shown that insulating and rugged surfaces of the Moon tend to make positive and negative charges separated and irregularly distributed, and intense and structured electric fields can be formed around them. This strong electric field lies in the innermost part of the photoelectron sheath and may contribute to mobilizations of the charged dust particles. Since this strong electric field develops on a spatial scale of less than the Debye length and can take various states depending on the lunar surface geometry, it is necessary to update the research approach. In this paper, we will discuss the direction of the near-surface plasma, electrostatic, and dust environment for upcoming lunar landing missions.
Geodetic sensing of mass variations due to climatic conditions
Authors: Ray Jagat Dwipendra , Patar Swapnali , Mahata Rebarani
Published: February 2023

The Earth Surface undergoes continuous deformation due to surface mass variations. These mass variations are primarily caused by the hydrological cycle, snowfall, ice melt and glacial isostatic adjustment (GIA). Modern geodetic sensing techniques like the Global Navigational Satellite System (GNSS) can sense these mass variations with unprecedented accuracy.  Therefore, the GNSS positioning time series provides a unique opportunity to study these mass variations and their causes.In this study, we have used the GNSS time series from the region of Africa and Antarctica to analyse the mass variations. Conditions like draught and ice melting characterise these two regions. Therefore this current study will look at the signals of these two physical conditions. The results obtained are discussed and analysed.
A differentiable ecosystem modeling framework for large-scale inverse problems: demonstration with photosynthesis simulations
Authors: Aboelyazeed Doaa , Xu Chonggang , Hoffman Forrest M. , Jones Alex W. , Rackauckas Chris , Lawson Kathryn , Shen Chaopeng
Published: February 2023

Photosynthesis plays an important role in carbon, nitrogen, and water cycles. Ecosystem models for photosynthesis are characterized by many parameters that are obtained from limited in-situ measurements and applied to the same plant types. Previous site-by-site calibration approaches could not leverage big data and faced issues like overfitting or parameter non-uniqueness. Here we developed a programmatically differentiable (meaning gradients of outputs to variables used in the model can be obtained efficiently and accurately) version of the photosynthesis process representation within the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) model. This model is coupled to neural networks that learn parameterization from observations of photosynthesis rates. We first demonstrated that the framework was able to recover multiple assumed parameter values concurrently using synthetic training data. Then, using a real-world dataset consisting of many different plant functional types, we learned parameters that performed substantially better and dramatically reduced biases compared to literature values. Further, the framework allowed us to gain insights at a large scale. Our results showed that the carboxylation rate at 25°C (Vc,max25), was more impactful than a factor representing water limitation, although tuning both was helpful in addressing biases with the default values. This framework could potentially enable a substantial improvement in our capability to learn parameters and reduce biases for ecosystem modeling at large scales.
Soil Data Harmonization to Create a Global Soil Data Platform
Authors: Miglio Ester , Sala Simone , Nafissi Anahita , Pandit Sandeep
Published: February 2023

The management of our soils plays a crucial role in addressing some of our greatest challenges, such as food security and climate change. Working together across national borders is essential for securing the health and quality of our soil in the future. With multi-stakeholder processes, language and the use of language is very important since the capability of understanding each other is critical. Developing a common language facilitates learning together, trust-building, defining common viewpoints, resolving disagreements, and arriving at technically sound and practical solutions.  

This document represents the initial attempt to create a common soil domain ontology and data model to support the creation of a user-friendly infrastructure in accordance with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles for uploading, managing, and providing comparable soil data at global scale. To meet these requirements, the review and application of accepted and widely used standards, conventions, and guidelines for the ingestion, organization, and sharing of soil data is necessary. The document should be regarded as a living document that evolves along with the progress of the project and in response to stakeholder feedback.  

This project began with the development of an ontology for the soil domain and the identification of representational terms. This was done by following a data-driven approach, which allowed the determination of relevant entities by making strategic decisions based on data analysis and organization, while facilitating a modular expansion of the knowledge base. Next, a standardized soil vocabulary was defined to facilitate data sharing and discovery. 

Furthermore, soil analytical information is collected and modelled across a variety of data sources, as well as SI units and non-SI units accepted for use with the International System of Units. Finally, a list of relevant conversion factors, regressions, and pedotransfer functions was collected to facilitate data comparison across different data bases.  
Measuring erosion on uplifting coasts: Shore platform downwearing rates and pattern on inter-tidal rocks at Māhia Peninsula, New Zealand
Authors: Omidiji Jokotola , Stephenson Wayne , Norton Kevin , Dickson Mark
Published: February 2023

Recent erosion rates from tectonically active coasts provide evidence of rapid rock breakdown following coseismic uplift. These rates are needed to solve puzzles about 'missing' marine terraces that prevent accurate reconstruction of past sea levels, earthquakes and rock coast evolution. Yet little scientific effort has been put into investigating the impact of tectonism on shore platform development. It is also presently unclear if erosion records from one coast can be extrapolated to other regions with similar tectonic, geologic, or geomorphic characteristics. We present shore platform downwearing rates and processes measured using the traversing micro-erosion meter (TMEM) and Structure-from-Motion photogrammetry from an inter-tidal shore platform uplifted by 3.1 m between 100 to 300 years ago. The site is a mudstone platform at Kahutara Point, Māhia Peninsula, North Island, New Zealand. Over 1.43 years, the mean annual downwearing rate was 1.94 mm/yr, while the total erosion at individual TMEM stations ranged from 0.29 to 8.31 mm (equivalent to mean erosion rates of 0.07 to 5.82 mm/yr). We found a lack of any spatial pattern in erosion rates cross-shore, suggesting the equal efficiency of waves and weathering processes. Orthophotographs of the eroded rock surfaces support the combined role of marine processes (waves and tides), sub-aerial weathering processes, salt weathering and biological activity in the erosion of the mudstone platforms at Kahutara Point. The mean erosion rate of 1.94 mm/yr from the Māhia Peninsula is similar to the mean post-uplift rate of 2.25 mm/yr reported for the Kaikōura Peninsula, New Zealand, where platforms were uplifted by ~1 m in 2016. This result suggests a comparable pattern of erosion response at both sites following co-seismic uplift and provides the first field evidence to support the comparison of the Kaikōura and Māhia shore platforms, thus helping to inform marine terrace development and destruction.
Advancing community water resources modeling in the Cooperative Institute for Research to Operations in Hydrology (CIROH)
Authors: Burian Steve , Clark Martyn , Shen Chaopeng , Spiteri Ray , Halgren James , Patel Arpita , van Beusekom Ashley , Cohen Sagy , Ogden Fred
Published: February 2023

The Cooperative Institute for Research to Operations in Hydrology (CIROH) is a consortium of 28 institutions to advance the National Oceanic and Atmospheric Administration’s (NOAA) science and services capabilities to provide actionable water resources intelligence. CIROH’s research aims to improve water prediction and supports four broad themes: (1) water resources prediction capabilities; (2) community water resources modeling; (3) hydroinformatics; and (4) application of social, economic and behavioral science to water resources prediction. CIROH outcomes will inform hydrological process understanding, operational forecasting techniques and workflows, community engagement in water modeling, open-source software development, translation of forecasts to actionable products, and use of predictions in decision making. This presentation will focus on CIROH’s research in community water modelling. In this theme, CIROH research focuses on advancing the predictive capabilities of the next-generation National Water Resources Modeling framework (NextGen framework) that is being developed for operational large-domain water prediction at NOAA’s National Water Center (NWC). The presentation will give examples of ongoing CIROH model development efforts to (1) integrate physical process representations into the NextGen framework across multiple levels of process granularity; (2) assess accuracy-efficiency trade-offs in the numerical solution of model equations across large spatial domains; (3) coupling process components that have hitherto been neglected in large-domain terrestrial system models (e.g., glacier hydrology, snow redistribution, connectivity of wetlands, land-atmosphere interactions over sparse forests, tile drainage, etc.); and (4) use hybrid machine learning methods to advance large-domain parameter estimation capabilities. The presentation will also highlight the establishment of research enabling infrastructure to support CIROH’s ongoing modeling advancement efforts. In summary, we will identify major challenges encountered and the high-priority research that is needed to advance capabilities in large-domain hydrologic prediction.
Norwegian Ships of Opportunity Program for marine and atmospheric research
Authors: King Andrew , Jaccard Pierre , Frigstad Helene , Harvey Therese , Sørensen Kai , Wehde Henning , Eastwood Steinar , Sagerup Kjetil
Published: February 2023

NorSOOP (Norwegian Ships of Opportunity Program) is a national research infrastructure which began in 2018 and is financed by the Research Council of Norway. Its main goal is to build a network of ships of opportunity capable of providing marine and atmospheric observations that are relevant for improving our understanding of coastal and oceanic ecosystems and also covers a subset of the Global Ocean Observing System (GOOS) essential ocean variables. NorSOOP ships of opportunity are part of the European GOOS (EuroGOOS) FerryBox Task Team and have contributed to various projects focused on marine ecosystem change, carbon dioxide/ocean acidification, pollution/microplastics, and remote sensing – at the local/municipality, national, and European level (including Horizon 2020 JERICO-S3, NAUTILOS, MINKE, and EuroSea projects). The objectives of NorSOOP include: (1) upgrade existing FerryBox installations and establish new ships of opportunity in Norwegian waters and the Arctic and North Atlantic; (2) provide and support high-quality and cost-efficient basic and applied ocean and atmosphere research; (3) foster innovation and growth for maritime, environmental sensor, and aquaculture industries. This talk will provide the latest developments, installations, and results as well as updates of the past and future activities within the project.
Optimizing agronomic management for soil health, water quality, crop production and profitability in the Texas Blackland Prairie
Authors: Smith Douglas , Adhikari Kabindra , Hajda Chad
Published: February 2023

Agronomic management is known to affect critical ecosystem services such as soil health, the quality of runoff water and crop production. However, few studies have been able to evaluate all the ecosystem services at the small catchment scale (1-10 ha) through long-term studies. As a part of the Long-Term Agroecosystem Research (LTAR) Network in the US, work at the Riesel Watersheds in Texas has been able to evaluate the role of managing fields with a focus on soil health practices (e.g., no-tillage, cover crops, reduced fertilizer inputs) compared to traditional practices. This presentation will provide the results of five years of study on the management practices related to soil health, water quality, and crop production. In the US, many producers make decision based on economics, so profitability of the practices will also be presented. In brief, reduced fertility inputs coupled with no-tillage and cover crops resulted in gross losses for most years; however, in the fifth year of study these practices resulted in a gross profit of $836 USD/ha, despite a severe drought and high variable costs associate with production. Further, event mean concentrations for dissolved reactive phosphorus were roughly half (0.06 vs 0.13 mg/L) for the field managed for soil health compared to the traditionally managed field. In light of expected high input costs and climate variability, agronomic management to promote soil health and water quality may provide additional benefits to producers.
MICA: A fast and flexible solution for real-time flood mapping – An application on 2015 Cannes Antibes flood
Authors: Bredimas Alexandre , Cambonie Tristan
Published: February 2023

Fast-flood prediction challenges both scientists and stakeholders. Flood evolution is extremely sensitive to input data regarding rain forecasts and the actual status of infrastructures and soil. Accurate and quick modelling is critical to the responsiveness and decision-making of all stakeholders for an optimal allocation of the resources required to limit the damages to the infrastructure and the risk to the population.BlueMapping develop a decision-support tool called MICA. MICA is a cellular automata model building on previous academic models, especially CADDIES, with tailored adaptations.The code of MICA has been industrialised into a high-performance calculation algorithm based on parallel computing using GPUs. It has been deployed on the Amazon Web Services cloud. It provides an efficient, scalable and flexible solution for pluvial flood prediction.MICA's potential will be illustrated with the test case of fast-flood inundations that hit the watershed of Cannes and Antibes (South of France) in October 2015. The code runs in a few minutes on this 149 km2 watershed. The result will be benchmarked with a standard model and the actual maximum depth measurements.
Exploring the added value of low-cost sensors via citizen observatories for peak rainfall monitoring in cities (Case study: Brussels)
Authors: Verbeiren Boud , Lemmens Julien
Published: February 2023

Rainfall is the driving force of hydrological events. In order to predict Pluvial Flooding in cities modelling approaches make use of rainfall data of various sources: radar-based observations and predictions, high-precision rain gauges (like the OTT Pluvio² types used in the Brussels monitoring network Flowbru.be). The first have the advantage of being area-covering and having predictive power, the latter providing more precise absolute and ground-based rainfall measurements but potentially lacking spatial representativity. In an urban setting , high-density rainfall measurements are important as a little shift in rainfall may lead to a significantly different hydrological response (peak flow at different location in sewer network). The main objective is to explore the potential of low-cost rain sensors as complement for extreme peak rainfall monitoring in Brussels, Belgium. Within the frame of the FloodCitiSense project (www.floodcitisense.eu) rainfall data has been collected during 2 years (2019-2021) using low-cost acoustic rain sensors, installed via citizen observatories. For the data analysis we focus mainly on convective rain storms typically occurring during summer time, which are most often very localized and challenging to measure and/or predict.The research questions were as following: (1) What is the performance of the low-cost sensors compared to the existing high-precision rain gauges of the FLOWBRU monitoring network in network? (2) Can we improve the quantitative estimation of extreme rainfall distribution using the measurements of the low-cost sensors?A comparative analysis, focusing on rainfall events with a return period of 10 years (T10), between a local low-cost acoustic rain sensor and a high-precision FLOWBRU rain gauge, installed at the same location (Royal Meteorological Institute) revealed a relative strong correlation between both rainfall timeseries, but a significant under estimation of cumulative rainfall during the events. A regression analysis enabled to develop a dynamic multiplier, varying in function of the rainfall intensity per 5-min timestep, improving the rainfall estimated by the low-cost sensor. Therefore the multiplier has been used to re-calibrate all low-cost measurements. In order to answer the second research question a spatial interpolation (Inverse Distance Weighted) using the cumulative rainfall per T10 event from FLOWBRU stations WITH and WITHOUT the low-cost stations has been applied. As a reference radar QPE images were used (cumulative rainfall per T10 event). Although yielding variable results, the use of the low-cost sensor data shows clearly an added value for (extreme) peak rainfall monitoring in Brussels.