bluuebunny/crossref_metadata_2025 huggingface dataset:
Computer modeling of mineral dendrite growth
Authors: Woś Dawid , Szymczak Piotr
Published: February 2023

Mineral dendrites are an example of a pattern which forms in rocks when they are infiltrated by the hydrothermal, manganese-rich fluids. As these fluids mix with other oxygenated fluids within the fractured rock, manganese oxide is formed. The oxide then precipitates, forming intricate, branched patterns. Several models of this process have been proposed, which vary in complexity. One model assumes crystallization of manganese oxides directly on the surface of the growing dendrite, causing it to elongate. Another model involves an initial growth of small nanoparticles of manganese oxide, which then aggregate into larger structures. The evolution of the system in both models is described by the system of reaction-diffusion equations. We study this process using lattice-Boltzmann method to track the evolving concentrations of the species involved in reaction. Next, we analyze the dependence of the morphology of the resulting patterns on the physical parameters characterizing the reaction and growth, such as initial concentrations of manganese ions and oxygen molecules, reaction rates, nucleation thresholds or surface energy of the dendrites. Our study has been focused on planar structures, growing along fractures or bedding planes. We have investigated the impact of multiple infiltrations of manganese-bearing fluid on the morphology of the dendrites. We compare the numerical results to the morphologies of the real systems with the aim of reconstructing the hydrochemical conditions prevailing during their growth
Toward a hybrid tropical cyclone global model
Authors: Ingrosso Roberto , Boudreault Mathieu
Published: February 2023

The future evolution of tropical cyclones (TCs) in a warming world is an important issue, considering their potential socio-economic impacts on the areas hit by these phenomena. Previous studies provide robust responses about the future increase in intensity and in the global proportion of major TCs (Category 4–5). On the other hand, high uncertainty is associated to a projected future decrease in global TCs frequency and to potential changes in TC tracks and translation speed.Risk management and regulatory actions require more robust quantification in how the climate change affects TCs dynamics.  A probabilistic hybrid TC model based upon statistical and climate models, physically coherent with TCs dynamics, is being built to investigate the potential impacts of climate change. Here, we provide preliminary results, in terms of present climate reconstruction (1980-2021) and future projections (2022-2060) of cyclogenesis locations and TC tracks, based on different statistical models, such as logistic and multiple linear regressions and random forest.  Physical predictors associated with the TC formation and motion and produced by reanalysis (ERA5) and the Community Earth System Model (CESM) ensemble are considered in this study. 
Validation and use of a model for the calculation of trace element accumulation in soils
Authors: Thompson-Morrison Hadee , Moltchanova Elena , Gaw Sally , Robinson Brett
Published: February 2023

Most agricultural production requires applications of agrichemicals and amendments to promote crop growth and aid soil fertility. These include fertilisers, pesticides and organic amendments, such as composts. Many agrichemicals and soil conditioners contain Trace Elements (TEs) as either active ingredients (e.g., Cu-fungicides) or contaminants. When TE-containing amendments are applied repeatedly to soils and crops, these TEs may accumulate. Consequently, soil fertility may be affected if these TEs are allowed to reach threshold levels, and plant uptake of TEs may reach critical levels for plant growth and food safety. As such, repeated applications of TE-containing products to productive land may limit both the sustainability of productive systems and future land use in areas where these products are applied. It is both useful and necessary to understand likely timeframes for accumulation and to understand sustainable application rates which might be adopted. There are different approaches to determine this. The use of mass-balance models has been employed as one approach to calculate expected soil TE concentrations into the future under specified conditions. We have developed a suitable mass-balance model for the calculation of TE-accumulation in soils under productive systems. We have used the approach that the model should be simple, rationally convenient and work with biologically relevant concentrations. We have validated the model using data from long-term field trials. The validated model was used to calculate TE-accumulation in oil palm production soils from Indonesia. Based on our findings, it is likely that TE-accumulation will reach threshold levels in oil palm plantations in Indonesia within eight years. We predict that production will become limited by phytotoxic concentrations of trace elements. This will deleteriously impact the world’s largest vegetable oil production system. This model may therefore be a useful tool in determining the sustainability of inputs into productive soils in terms of TE-accumulation.
Phase state of PM2.5 in Seoul and Beijing and its effect on particle size distribution
Authors: Kim Daeun , Jeong Rani , Qui Yanting , Meng Xiangxinyue , Wu Zhijun , Zuend Andreas , Ha Yoonkyeong , Kim Changhyuk , Kim Haeri , Gaikwad Sanjit , Jang Kyoung-Soon , Lee Jiyi , Ahn Joonyoung , Song Mijung
Published: February 2023

A phase state of ambient aerosols is a key parameter to understand physicochemical properties of aerosols such as growth rate, size distribution, and mass concentration that affect climate and human health. However, only limited information of real aerosol phase states has been obtained. Herein, to explore phase states of fine particulate matter (PM2.5) in megacities, we collected daily PM2.5 filter samples during December 2020 – January 2021 in Seoul and Beijing. Optical microscopy and a poke-and-flow technique were used to observe the morphologies and phase states of the PM2.5. Results showed that the average phase states of the PM2.5 were significantly different in the two megacities. The PM2.5 existed as a liquid state to a semisolid in Seoul while it existed as a semisolid to a solid in Beijing. These differences were governed by the chemical composition of PM2.5 and aerosol liquid water content. Furthermore, the phase state of PM2.5 in two megacities was correlated with particle size distribution. Our findings can provide an understanding of the phase states of real-world aerosols and how the phase state is linked to chemical compositions, ALWC, and size distributions of PM2.5.
Urban non-point source pollution modelling: A physics-informed neural network approach
Authors: Tang Sijie , Wan Yin , Shang Fangze , Wang Shuo , Jiang Jiping
Published: February 2023

Over the past decades, urban non-point source (NPS) pollution has been the most severe threat to the urban water environment. The sharp increase of impervious surface and the high level of particulate matter from massive human activities exacerbated the water quality of surface runoff, leading to the significant urban NPS pollution globally whereby it is of importance to have a deep knowledge on the accumulation and transport of pollutants. A series of traditional physical models have been developed to simulate the runoff generating as well as the NPS pollution. However, a disadvantage of process-based modelling is its great demand for a large amount of field data which may normally be inaccessible, as well as the demand for the expertise in applying appropriate modelling method on specific study area. Empirical models do not characterize complex physical processes of NPS pollution and thus require fewer data and modelling skills. Nevertheless, the limitation is that these modelling approaches are region-sensitive and spatially untransferable. It is challenging to fill the gap between the requirement of urban water environment management and existing modelling performance on NPS pollution, in the absence of a more effective model with high accuracy, easy employment, and spatial transferability.Machine learning approach has been utilized in environmental studies for decades, and was originally believed to be a black box that can barely provide any physical insight into environmental processes. However, an approach named physics-informed neural networks (PINN) was proposed lately and then applicated in dynamical system. This approach embeds differential equations of priori knowledge into neural network to make modelling interpretable and generalizable. In this study, a physical process embedded LSTM network was proposed to formulate the cumulation and transport of urban NPS pollution in rainfall runoff, based on the coupling of LSTM and differential equations of classic exponential build-up/wash-off processes. Water quality data of urban runoff from sampling and continuous real-time monitoring campaigns distributed in China, USA and New Zealand were collected and fed into proposed network to model the primary NPS pollutant TSS. The results revealed that the hybrid PINN model excels the vanilla LSTM approach and auto-calibrated SWMM approach in accuracy and convenience. The interpretable model also enhanced the cross-catchment transferability of model for urban water management in data-poor area. In addition, the trained parameters of network units were found consistent with the prior knowledge of accumulation and transport of NPS pollutants, indicating the deep coupling of neural network and physical process. As a very early case of hybrid AI modelling in urban NPS pollution, this study provided a new perspective on water quality modelling and can help in improving the standards of urban environment governance.
Examination of Causes for Decrease in the Water Level of Beysehir Lake and Shrinkage in the Lake's Surface Area.
Authors: Erkoç Muharrem Hilmi
Published: February 2023

This study investigates the reasons for the decrease in the water level of Beysehir Lake and the shrinkage in the lake's surface area in recent years. For this purpose, the lake water level was determined from multi-mission satellite altimeter data, and the lake area was calculated using high-resolution optical satellite images. Data from Copernicus Global Land Service was used for multi-mission satellite altimeter data, and the lake level trend between 1993-2022 was calculated with the least squares method. European Space Agency's (ESA) Sentinel-2 high-resolution optical images were used to determine the change in the lake surface area between 2015 and 2020. These high-resolution optical images were processed with The Sentinel Application Platform (SNAP) software. The Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) were calculated based on processed optical images, and these indexes reflect the changes in water surface area. From the satellite altimeter data, a decreasing trend of 2.5 ± 0.5 cm/yr in the lake water level in the last ten years and shrinkage of approximately 8 km2 in the last 6 years from the satellite images were determined. The possibility of one of the most important reasons being drought was emphasized, and monthly average air temperature data and monthly average precipitation data were obtained from the Turkish General Directorate of Meteorology. With these data, 3- and 12-month Standardized Precipitation Evapotranspiration Index (SPEI) were calculated. Regarding these calculated drought indexes, moderate, extreme, and severe hydrological drought has been determined in the region. According to the analysis, drought is thought to be the most important reason for the decrease in the lake water level and shrinkage in the lake surface area.Keywords : Geodesy for Climate, Lake Water Level, Satellite Altimetry, In-situ observation, Sentinel-2
Water Cycle Changes in Reanalyses
Authors: Vargas Godoy Mijael Rodrigo , Markonis Yannis
Published: February 2023

Remote sensing data and reanalyses complement traditional surface-based measurements and offer unprecedented coverage over previously inaccessible or unmonitored regions. Even though these have improved the quantification of the global water cycle, their varying performances and uncertainties limit their applicability. Herein, we discuss how a framework encompassing precipitation, evaporation, their difference, and their sum could further constrain uncertainty by unveiling discrepancies otherwise overlooked. Ahead, we physically define precipitation plus evaporation to sustain its appropriateness to describe reanalyses. We investigated how well the global water cycle fluxes are represented in four reanalysis data sets (20CR v3, ERA-20C, ERA5, and NCEP1). Among them, we observe four different responses to the temperature increase between 1950-2010, with ERA5 showing the best agreement with the water cycle acceleration hypothesis. Our results show that implementing the framework proposed can improve the evaluation of reanalyses' performance and enhance our understanding of the water cycle changes on a global scale.
Degradation of phosphorus-containing natural organic matter facilitates enrichment ofgeogenic phosphorus in Quaternary aquifer systems: A molecular perspective
Authors: Tao Yanqiu , Du Yao , Deng Yamin , Ma Teng , Wang Yanxin
Published: February 2023

High levels of geogenic phosphorus (P) in groundwater have been widely found worldwide, posing a potential threat to aquatic environment. Although degradation of P-containing natural organic matter (NOM) is an important process driving the enrichment of geogenic P, the detailed mechanism underlying P enrichment based on dissolved organic matter (DOM) characterization remains unclear. Herein, we chose high-P Quaternary aquifer systems in the central Yangtze River Basin, and used molecular characteristics of P-containing DOM coupled with hydrogeochemistry and carbon isotopes to unravel the detailed mechanisms responsible for the enrichment of geogenic P. The results indicate that P-containing NOM is the most critical factor controlling P enrichment in groundwater. The molecular characterization via Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) reveals that a total of 208–1534 P-containing compounds were detected in 10 groundwater samples, and predominantly consisted of one-P-atom (1P) and two-P-atom (2P) compounds. Compared to 1P compounds, 2P compounds have greater numbers of N/S-containing compounds; smaller proportions of highly unsaturated and aliphatic compounds (considered as intermediates or end-products of biodegradation); larger proportions of polyphenols and polycyclic aromatics (considered as sedimentary inputs from terrestrial vascular plants); lower H/C and nominal oxidation state of carbon (NOSC) values; and higher m/z, O/C, P/C, N/C, double bond equivalents (DBE), and aromaticity index (AI) values. We find that, at the molecular level, the degradation of P-containing DOM overall results in an increase in H/C and a decrease in O/C, and a processing gradient is observed from 2P to 1P compounds. To our knowledge, this is the first study to reveal the underlying mechanism for the enrichment of geogenic P from a molecular perspective in alluvial-lacustrine aquifer systems worldwide, which improve our understanding of biogeochemical behavior of P in subsurface environment.
Rainwater harvesting as climate change adaptation strategy for durum wheat production in Sardinia
Authors: Viola Francesco , Deidda Roberto , Urru Salvatore , Cristiano Elena
Published: February 2023

The Mediterranean region is widely recognized as a climate change hotspot, where, mainly due to the increase of CO2 concentration, both historical records and future climate models’ projections reveal an increase of the daily average temperature and a reduction of the mean annual precipitation, with less frequent but more intense rainfall events. These changes could have strong impacts on the durum wheat production, and consequently to the food chain that derives from it. Water availability is expected to be the main limiting factor in the durum wheat growth, which is usually rainfed in Mediterranean region. On the other hand, CO2 increase may act as a counterbalance factor, by increasing the water use efficiency. In this work, within the framework of the H2020 European Union project ARSINOE (“Climate-resilient regions through systemic solutions and innovations”), we investigated the possibility to adapt durum wheat production to climate changes, compensating the rainfall reduction with emergency irrigation derived from a rainwater harvesting system, with the aim to keep constant the durum wheat production or alleviate the yield reduction. The Aquacrop model, a crop growth model developed by FAO’s Land and Water Division, has been calibrated to reproduce the actual durum wheat production in the Campidano region in Sardinia (Italy), implementing the local climate and soil characteristics. The model has been then used to simulate the crop production in correspondence of different bias corrected future climate scenarios, which foreseen an average rainfall reduction and increase of average temperature and CO2 concentration in the atmosphere. A rainwater harvesting system to collect rainfall from the rooftops or impervious surface within the cultivated area (100m2/ha) has been designed and the volume for potential emergency irrigation has been estimated year by year. Preliminary results show the importance of implementing rainwater harvesting systems to provide emergency irrigation and sustain durum wheat production in a context of climate changes.AcknowledgmentsThis project has received funding from the European Union’s Horizon H2020 innovation action programme under grant agreement 101037424.
Climate impact on surface-subsurface hydrology considering meteorological and land use projections.
Authors: Ali Muhammad Haris , Popescu Ioana , Jonoski Andreja , Solomatine Dimitri
Published: February 2023

Understanding the effects of climate change on surface-subsurface hydrology is critical for improving water resources management in a basin. In such cases, the use of hydrological models to quantify and assess water resources is a common practice. With the increasing population and human interventions, the land use changes drastically. The land cover plays a vital role in hydrology as it defines the properties of land surface in the models. So far, majority-of the studies accessing the future climate change consequences on hydrology take into account only the meteorological variables under different climatic projections, neglecting the future land use changes assuming it as static. However, that is not the case, because majority of the earth's surface has altered as a result of human activities, and these changes are represented in models via land use maps.The study presented herein, aims to assess the surface-subsurface response of the catchment under combined effect of meteorological variables and land use future projection. The analysis is performed on the Aa of Weerijs catchment which is a meso-scale transboundary watershed between Belgium and the Netherlands. The future projections of the meteorological variable were obtained from the Royal Netherlands Meteorological Institute (KNMI-14) website for the Netherlands and the same trends were implemented for the Belgium part of the catchment. For the land use, the European Space Agency (ESA) Climate Change Initiative (CCI) Land Cover (LC) maps of the study area for the year 1992 to 2021 were downloaded and linearly projected for the year 2050. The developed projected map was also compared with projected land use map of year 2050 by LUISA (Land Use-based Integrated Sustainability Assessment) modelling platform.To investigate the hydrological regime of the area, the fully distributed physically based hydrological model coupled with a hydrodynamic model using MIKE-SHE and MIKE-11 modeling tools was developed. The base model was set up for the year 2009 to 2016. In addition to discharge, the groundwater heads are used to evaluate the model performance.After setting up the base model, firstly, we analyzed the surface and subsurface response of the catchment considering that the land use in the area is the same as it was in 1992. Secondly, we analyzed the catchment response for the year 2050 by considering the meteorological variables as well as land use future projection.The study provides unique estimates of future climate change and associated hydrological implications. The findings of the study will be valuable to plan and suggest significant modifications in the current strategies for water management in the area. Moreover, it can contribute to the efficient integration of spatial planning with water management.
Hybrid Multi Models Ensemble Framework Based on Clustering Algorithms for Runoff Reconstruction
Authors: Singh Ujjwal , Maca Petr , Hanel Martin
Published: February 2023

Runoff is the key hydrological process, which is vital to the sustaining of human life on earth in examiningthe climate change scenario. There are a lot of hydrological models available to simulate the runoff, butthese models’ outputs have biases due to uncertainty. Most machine learning algorithms cannot capturethe runoff generated by the real-world complex hydrological system accurately. The hybrid model combinesthe efficiency of hydrological, machine learning, and ensemble modeling to minimize the bias of output [1],[2]. The recent development of evolutionary computation in hybrid modelling frameworks combines theefficiency of different components such as hydrological models, spatial autocorrelation, machine learning,and machine learning ensemble to estimate robust and less biased runoff [1]. However, these componentsneed to significantly capture the heterogeneity and similarity of the catchment properties, which are highlylinked with the spatial variation of various hydrological patterns. Clustering is a technique that can groupsimilar types of hydrological patterns, which can be integrated within a hybrid modeling framework.However, there is rarely found literature on the hybrid framework, which consists of different clusteringtechniques and their ensemble. These clustering algorithms are based on different categories. We proposedthe hybrid ensemble framework based on extended input data, hydrological models, different clusteringalgorithms, deep learning, and an ensemble of deep learning to reconstruct the minimum biased surfacerunoff. We tested our proposed hybrid framework, which is robust compared to previously developedframeworks. This proposed hybrid framework methodology will help to develop a new hybrid algorithmto estimate the less biased surface runoff using various available climate data to understand the dynamicsof surface runoff for different spatial-temporal scales and climates. [1] U. Singh, P. Maca, M. Hanel, et al., “Hybrid multi-model ensemble learning for reconstructing griddedrunoff of europe for 500 years,” vol. Available at SSRN: doi: 10 . 2139 / ssrn . 4188518. [Online].Available: http://dx.doi.org/10.2139/ssrn.4188518.[2] S. M. Hauswirth, M. F. Bierkens, V. Beijk, and N. Wanders, “The suitability of a hybrid frameworkincluding data driven approaches for hydrological forecasting,” Hydrology and Earth System SciencesDiscussions, pp. 1–20, 2022. 
 
Regularly directed complex linear landforms in central Europe: a large-scale disperse or zone distribution, and indication of associated landscape phenomena
Authors: Roštínský Pavel , Nováková Eva
Published: February 2023

The parallel linear landforms, frequent phenomena in many places on the Earth's crust surface, were systematically assessed in the area of central Europe (~3,000 km longitudinally, ~2,000 km latitudinally). In total, we estimated yet ~24,000 items. Several (>5) variously oriented large systems (networks) of such topographic features pervade fairly regularly the region.Our study using the LiDAR or SRTM data (1) allowed to outline spatial distribution of the occurring lines, mostly by considering basic complex surface geometries or directional trends (including chaining of landforms of different types) instead of simple linear elements (valley sections, slopes, ridges) commonly applied during automatic extraction procedures. Primarily created in the Czech national conformal conic S-JTSK projection as straight features, the landforms are displayed as slightly bended curves in the WGS geographical coordinates. Usually, a general trend of some important regional fault system of Palaeozoic or Mesozoic origin served as primary direction at searching for analogous surface elements within the particular linear network in the surroundings. However, most of the linear landforms do not correspond to geological boundaries since the topographic features of all the distinguished directions are dispersed across many of regional geological units. But the elongated element clusters (zones) can accord with significant geological structures (basins, mountain ranges, or their margins) and some linear topographic features fairly correspond with current spatial limits of young sedimentary formations (covers).(2) A plenty of other regional or local natural phenomena in the present-day landscape are closely associated with the linear landform systems. The regional features include general orientation and detailed shape of river and valley network sections (abundant deflections into the main directions), dense block segmentation of the topographic structure (separation of lower and higher surface levels) or location of concentrated surface erosion; all the main linear systems are followed by the same such expressions. Locally, smaller landforms like related saddles, cuestas, anomalously shaped meanders, river terrace risers, land slide or even cirque elements have evolved. Thus, the linear networks strongly influenced upper parts of the Earth's crust.Besides aspects of the subject presented, a discussion on various development stages of linear landforms and related features in the deeper Earth's crust possibly including also some plate tectonics elements, as precursors of the focused surface expressions, is called for to provide proper explanation of the extensive phenomenon.
A truly Very Broad Band (VBB) borehole seismometer with flat response over 5 decades of frequency
Authors: Guralp Cansun , Rademacher Horst , Minchinton Paul , Kirrage Robert , Alimov Maksim , Jones Rebekah , Boustead Nichola
Published: February 2023

Decades ago new opportunities in seismology were opened by the development of broadband seismic sensors with feedback. The three defining characteristics of these instruments were the bandwidth extension to longer periods, a much lower intrinsic noise and a higher dynamic range. However, the goal of further extending their bandwidth to frequencies above 100 Hz has proven elusive, because these sensors are plagued by parasitic resonances leading to modes not controllable by the feedback system.Here we present a new low noise seismic borehole sensor with a truly VBB flat response over five frequency decades from 2.7 mHz (360 sec) to 270 Hz. The instrument has no mechanical resonances below 400 Hz. We achieved the bandwidth extension to high frequencies with improvements of the mechanical design, i.e. the arrangement of the pivots and the geometry of the spring.The design is realized in a borehole arrangement, where three sensors are stacked in 90 degree angles to each other. Including a singe jaw holelock as a clamping mechanism the complete stack has a diameter of 89 mm, is 625 mm long and weighs about 24.5 kg. We show test results from three co-located complete borehole sensors with identical frequency responses.
Long-term reconstruction of a large-scale landslide of a LIA lateral moraine in the Upper Kaunertal in Tyrol, Austria
Authors: Altmann Moritz , Haas Florian , Rom Jakob , Fleischer Fabian , Heckmann Tobias , Ressl Camillo , Becht Michael
Published: February 2023

Since the end of the Little Ice Age around 1850, global warming has led to rapid landscape changes, especially in high mountain areas. The ongoing glacier melt leads to an expansion of the LIA glacier forefields, so-called proglacial areas. The exposed lateral moraines often show increased sediment activity over decades and centuries, which is generally described as the paraglacial adjustment process. Slope instabilities are caused, for example, by the loss of the support from the melting glaciers, which can lead to large landslides and thus heavy deformations. In order to understand corresponding geomorphological processes, it is important that surface changes can be reconstructed and analysed in high spatial and temporal resolution. However, aerial photographs of the European Alps, which are well suited for observing proglacial areas, only extend to the middle of the 20th century, thus resulting in a temporal limitation.Therefore, in this work we show a nearly 100-year quantitative monitoring of a large-scale deformation of a LIA lateral moraine in the glacier forefield of the Gepatschferner in the upper Kaunertal (Tyrol, Austria). We achieve this long-term (1922 to 2021) observation by combining different topographic data sets based on different remote sensing methods and techniques. The reconstructed earth surfaces are based on airborne LiDAR data (2006 to 2021) and photogrammetric DEMs (1953 to 2003) as well as a historical stereophotogrammetric map from 1922, which was also generated into a DEM. In total, eight DEMs were generated and corresponding DoDs calculated.Different landslides within the first three epochs (1922 to 1953, 1953 to 1971 and 1971 to 1983) could be determined on the slope, which can be directly linked to the corresponding glacier melt. Even after the landslide processes (from 1983 onwards), continuous geomorphological activity could be observed until today (2021), whereby the total volume of net erosion of all epochs (from 1922 to 2021) added up to approx. 486,000 m³.
Influence of sanitary infrastructure on nutrient transport mechanisms in a headwater catchment
Authors: Spill Caroline , Ditzel Lukas , Gassmann Matthias
Published: February 2023

Sanitary infrastructures draining smaller villages are often not taken specifically into account when discussing catchment transport process. One reason is the limited data availability, as they are usually not part of (high frequency) monitoring strategies, although it has been shown, that they can have a significant impact on water quantity and quality. Especially in first- or second-order streams, they can contribute a big share to the discharge volumes. At the same time, the dilution effect of small streams is limited. This is critical, as e.g. wastewater treatment plants (WWTPs) often have to meet lower requirements compared to their bigger counterparts treating water from cities, meaning, that especially nutrient concentrations can be still high in the effluent.We measured discharge and different water quality data in a headwater stream (2.77 km²), which is influenced by agriculture, a small village and point sources: two combined sewer overflows (CSOs) and one WWTP. In comparison to other studies, we decided to implement our measurements shortly after the point sources, to measure the nutrient signal with little influence of in-stream processes.The WWTP always contributed a high share of water, especially during dry periods. However, the discharge from the WWTP was much higher, than one would expect based on the number of inhabitants. Water quality data from the WWTP suggest, that groundwater is infiltrating into the sewer system and is additionally treated within the WWTP. This could also explain the high number of CSO events: infiltrating groundwater leads to the exceedance of the sewer system design capacities even at medium-sized rainfall events. As a consequence, not only CSO events occur more often, but also cleaning processes within the WWTP seem to be interrupted, explaining the increasing ammonium and ortho-phosphorus concentrations during events. Especially during long-lasting events with several peaks, the hysteresis analysis shows the activation of different nutrient sources, indicating a complex interaction between the sanitary infrastructure and the catchment itself.Our data shows, that even small point sources from villages can have a significant influence on water quantity and quality. Similar to agricultural or natural catchments, their individual influence varies depending on season and pre-event conditions and are not constant throughout the year.
What is going on within Google Earth Engine? A Systematic Review and Meta-Analysis
Authors: Pérez-Cutillas Pedro , Pérez-Navarro Alberto , Conesa-García Carmelo , Zema Demetrio Antonio , Amado Álvarez Jesús Pilar
Published: February 2023

Google Earth Engine (GEE) is a geospatial processing platform based on geo-information applications in the 'cloud'. This platform provides free access to huge volumes of satellite data for computing, and offers support tools to monitor and analyse environmental features on a large scale. Such facilities have been widely used in numerous studies about land management and planning. Considering the current lack of relevant overviews, it may be useful to evaluate the utilization paths of GEE and its impact on the scientific community. For this purpose, a systematic review has been conducted using the PRISMA methodology based on 343 articles published from 2020 to 2022 in high-impact scientific journals, selected from the Scopus and Google Scholar databases. After an overview of the publishing context, an analysis of the frequency of satellite features, processing methods, applications are carried out, and a special attention is given to the COVID-19 studies. Finally, the geographical distribution of the reviewed articles is evaluated, and the citation impact metrics is analysed. On a bibliometric approach, 90 journals published articles on GEE in the reference period (January 2020 to April 2022), and this large number of journals reveals the multidisciplinary application of GEE platform as well as the interest of publishers towards this topic of relevance for the international scientific community. The results of the meta-analysis following the systematic review showed that: (i) the Landsat 8 was the most widely-used satellite (25%); (i) the non-parametric classification methods, mainly Random Forest, were the most recurrent algorithms (31%); and (iii) the water resources assessment and prediction were the most common methodological applications (22%). A low number of articles about COVID-19, in spite of the planetary importance of the pandemic effects. The reviewed articles were geographically distributed among 86 countries, China, United States, and India accounting for the large number. 'Remote Sensing' and 'Remote Sensing of Environment' were the leading journals in the citation impact metrics, while the Random Forest method and the agriculture-related applications being the mostly cited. It is expected that these results might change over the mid to long term, due to fast progress in environmental and spatial information technologies, although currently our findings may be worthwhile and useful for assessing the current global deployment of GEE platform.
Late quaternary carbonate (pteropod) preservation in the Indian Ocean sediments: inferences on the paleoclimate and paleoceanography
Authors: Edayiliam Sreevidya , Adukkam Veedu Sijin Kumar , Bejugam Nagender Nath
Published: February 2023

To evaluate the preservation pattern of pteropods and their relationship with climatic and oceanographic history in the Laccadive Sea, a temporal variation analysis of pteropod abundance was done. For that, we employed preservation indices from calcite (Globigerina bulloides%, Globorotalia menardii abundance), as well as aragonite (e.g., total pteropod abundance, Limacina Dissolution Index (LDX), fragmentation ratio). To determine if pteropod shells have been preserved over time, we used estimated pteropod abundance. The pteropod preservation record displays excellent preservation during cold stadials, evidenced by the lower values of aragonite dissolution proxies than during the interglacials/interstadials, similar to the preservation records from other northern Indian Ocean cores evidenced by the lower values of aragonite dissolution proxies than during the interglacials/interstadials. The shallow aragonite compensation depth (ACD), weaker oxygen minimum zone (OMZ), and the lower southwest monsoon (SWM)-induced productivity are thought to be the cause of the basin-wide pteropod preservation events during the cold stadials (ACD). Additionally, during an intense northeast monsoon (NEM), the advection of cold, low-saline waters from the Bay of Bengal to the Laccadive Sea, as well as the intrusion of southern-sourced intermediate water ventilation, may have caused a deep vertical mixing of oxygen-rich surface waters, raised the pH of thermocline waters and deepened the ACD. However, the local fluctuations in the water mass properties, such as the increased productivity maxima, the intense OMZ, and shallow ACD, as well as changes in the aragonite, are responsible for the poor pteropod abundance, poor preservation and strong dissolution during the Holocene, Bølling-Allerød (B/A) and interstadial periods.The calcification proxy indicates that the aragonite undersaturation and reduced calcification occurred during 19-16.5 kyr, preferably due to the depletion in the oceanic alkalinity caused by enhanced upwelling-induced carbonate ion exchange between the intermediate and deep water. In contrast, the preferential dissolution of smaller shells in the sediments (marked by increased average shell size and higher values of Limacina dissolution index (LDX) corresponds to strengthened OMZ and shallower ACD, pointing towards the post-depositional dissolution of aragonite shells. Therefore, the overall decrease of pteropod content of the deposits in the stadial/interstadials suggests a combination of monsoon-associated changes in water column properties, variability in aragonite saturation, intermediate water ventilation and sediment rate.
Testing the transferability of a Bayesian Belief Network to diverse agricultural catchments using high-resolution hydrology and land management data sets
Authors: Negri Camilla , Schurch Nicholas , Wade Andrew J. , Mellander Per-Erik , Glendell Miriam
Published: February 2023

Phosphorus (P) pollution from agriculture is a major pressure on maintaining and improving water quality worldwide. In Ireland, the Agricultural Catchments Programme (ACP) was created to evaluate the Good Agricultural Practice measures implemented under the EU Nitrates Directive. Considerable monitoring and research have been done into the drivers of, and controls on, nutrient loss in these catchments.Managing P pollution in agricultural catchments requires informed decisions about the pollution risks using catchment-scale understanding which, in turn, requires a systemic modelling and assessment approach. Bayesian Belief Networks (BBNs) support system-level thinking as they can represent complex systems (such as rivers and catchments) and integrate disparate information sources while representing uncertainty. In a previous study, a BBN was developed using the ‘source-mobilisation-transport-continuum’ and parameterized for a 12 km2 agricultural catchment with flashy hydrology on poorly drained soils and grassland as the dominant land use. Seven years of hourly turbidity and discharge measurements at catchment outlet, and mapped soil P content were used to inform parameterization. Literature data and expert opinion were included to complement the dataset when information on point-source pollution (farmyard and septic tank nutrient losses) was lacking.In the current study, the BBN is developed further and is parameterized using a monthly time-step for three additional diverse ACP catchments: two arable land-dominated catchments with contrasting hydrology (well-drained vs poorly drained) and a well-drained grassland catchment to test model transferability. In a step forward from the previous model, we quantify P losses from a sewage treatment plant in one of the arable catchments, and we consider biota in-stream P removal as an additional process. Lastly, the observed TRP concentrations were bootstrapped to obtain monthly TRP distributions which are compared to predictions from the BBN to validate the model.Results showed that the model performs well for the target catchment but applying it to other catchments is key to assessing its generalizability and utility. Here, preliminary results explore whether the BBN can capture the differences in P loss risk between catchments and the reasons for this.In addition, testing the model transferability to other catchments is important to (a) inform on the differences in P loss between catchments, and (b) inform model testing in data-sparse catchments. Future research will be focussed on integrating climate change scenarios in the model to inform the targeting of mitigation measures under future change, foster discussion with stakeholders, and provide support to decision-makers.
Community Building for Data Sharing and Open Science within the Earth, Space, and Environmental Sciences
Authors: Vrouwenvelder Kristina , Stall Shelley
Published: February 2023

Open Science is transformative, removing barriers to sharing science and increasing reproducibility and transparency. The benefits of Open Science are maximized when its principles are incorporated throughout the research process, through working collaboratively with community members and sharing data, software, workflows, samples, and other aspects of scientific research as FAIRly and openly as possible. However, the paths toward Open Science are not always apparent. Developing Open Science skills is an ongoing practice, and while these skills enhance outcomes for individual researchers as well as the broader community, there are many concepts, approaches, and tools to learn along the way.How can we break down the barriers confronting researchers in their Open Science journey? How can we develop and support necessary infrastructure to reuse, distribute, and reproduce the outputs of scientific research? How do we create a culture where having better tools, practices, and methods helps us achieve this goal? We will share work by AGU, our collaborators, and the broader community to support researchers in the Open Science journey, build groups to share resources, leading practices, and experiences, and help develop networks of support across the Earth, space, and environmental science community at all levels, to better support the culture of the future.
Thermal impact of underground car parks on groundwater
Authors: Noethen Maximilian , Hemmerle Hannes , Benz Susanne , Menberg Kathrin , Epting Jannis , Blum Philipp , Bayer Peter
Published: February 2023

In addition to the continuous increase of groundwater temperatures due to global warming, heat losses from infrastructure, (underground) buildings and geothermal use lead to thermal anomalies on regional to local scales. Often, these local heat accumulations (hot spots) of groundwater temperatures are associated with underground car parks (UCP). They represent sizeable infrastructures that are typical for densely built-up areas and are numerous in many cities. Unlike regular basements, they often reach beneath the groundwater table and heat up due to frequent traffic. They therefore act as heat sources for groundwater. By analysing long-time data from 31 sites in Germany, Austria, and Switzerland, we discovered seasonally varying heat flux intensities and even directions. While all UCPs heat the groundwater during the warm period, most UCPs cool the groundwater in the cold period. Only few act as continuous heat source all year round. We also discuss characteristics and their influence on the temperature such as the type of use (public/private) and the depth of the UCP. Furthermore, we present the results of a spatial analysis of heat fluxes and flows from over 5000 UCPs in Berlin, Germany. By discussing the range of heat fluxes and the hydrogeological conditions that lead to regional differences, we demonstrate the role of UCPs for subsurface urban warming. The results show that about 40 % of Berlin’s total heat flow from UCPs occurs in the “Mitte” district, where the density of UCPs is highest and the distance to the groundwater table is typically below 4 m. Finally, the knowledge gained about subsurface heat sources can help improve urban thermal groundwater management and highlights the potential for recovering waste heat from UCPs through geothermal applications.
The 2D resistivity measurement eror and its effect on the model accuracy
Authors: Doyoro Yonatan Garkebo , Chang Ping-Yu
Published: February 2023

We examine the measurement noise of electrical resistivity tomography and assess its effect on the inverted results. The observed and numerically simulated resistivity datasets are analyzed regarding noise distributions. We evaluate and present the contact resistance, reciprocal and repeating errors, potential noise, artificial effect on 2D resistivity measurement, inversion misfit, and model accuracy. The result shows considerable measurement noise variation for dry and wet conditions. This study uses a 3% repeatability error cut-off, and about 3.2% of the dry season and 0.83% of the wet season datasets are above cut-off values.  The result also exhibits an inverse relationship between the precipitation and reciprocal error. The resistivity measurement in dry conditions generally indicates high contact resistance, repeatability error, and reciprocal errors, resulting in significant data discarding. We also reveal the misfit between observed and model-predicted resistivity data; a high discrepancy is exhibited for noisy data, leading to substantial model error. The depth of investigation (DOI) threshold depth decrease with increasing measurement noise. This study will give insight into measurement noise evaluation, allow cut-off value, assess data noise propagation and its effects on the data misfits and inverted models, and reduce model misinterpretation.