bluuebunny/crossref_metadata_2025 huggingface dataset:
Monitoring water turbidity with camera: a real scale experiment
Authors: Miglino Domenico , Saddi Khim Cathleen , Isgrò Francesco , Jomaa Seifeddine , Rode Michael , Manfreda Salvatore
Published: May 2023

Turbidity is one of the most critical metrics in water quality monitoring.  High turbidity in river basins can be an indicator of both organic and inorganic material presence. Improving existing river monitoring techniques is essential, given the growing presence of critical factors, such as climate change, population growth, and pollution in recent years.

In this study, a real scale experiment has been conducted in Selke River within the Bode catchment in Germany. The Bode basin is one of the best-instrumented catchments in Central Germany, managed by UFZ Helmholtz Centre for Environmental Research. In this experiment, the level of turbidity has been artificially increased by adding kaolin clay into the river, upstream enough from the monitored river cross-section to ensure the complete mixing between clay and water.  Kaolin is usually exploited to prepare turbidity standard solutions. In addition, it is a harmless, easy to handle, and low-cost clay mineral, which is also an abundant silicate in soils and sediments.

The monitoring field campaign has been conducted using different instruments, such as an optical camera, a multispectral camera mounted on fixed positions and a drone, which have been used to describe, from different points of view, the synthetic turbidity event generated. Different types of camera and installation settings have been investigated to understand the full potential of this technology for water quality monitoring. The gathered optical data was compared to the recorded turbidity of the UFZ sensors, which has been currently installed in the Selke river cross-section.

The final goal of this work is to build a reliable image processing procedure for the development of a camera system that could support existing monitoring techniques and increase the temporal and spatial resolution in  river monitoring.

Keywords: camera, UAS, river monitoring, sediment transport, image processing, spectral indices, remote sensing, drones, water quality assessment
How to quantify regional hydrological change impact: some examples from France
Authors: Habets Florence
Published: May 2023

Regional hydrology vibrates to the rhythm of the weather intercepted by the soil-vegetation continuum and controlled by human abstraction and managements.
How can we interpret the observations? Does an observed trend is a signal of climate change? or natural variability ? Is the absence of trend associated to compensating trends?

To do so, long-term observations are indeed a key issue. I’ll show a study on the Seine basin, for which we wanted to assess the impact of the Atlantic Multidecadal Variability on the river & groundwater flows. To do so, 60-years is barely enough, and it was necessary to cover all the XXth century. There are few research networks on such long period, and the required observations come mostly from the public survey. Several issues were to face: data rescue, re-interpretation of the data (from river level to river discharge) and  the combined study of modeling and observations. It remains hard to interpret all the observed variations, especially due to the strong artificialization of the basin. However, it helps interpret the impact of natural variability, and how it could impact the basin in the next decades.

Long term lysimetric observations can help interpret the impact of land cover change and agricultural practices change on the regional hydrology. By using a 60-year lysimeter data set with several crop rotations and a bare soil, we were able to assess the impact of climate change and the impact of catch crop on the groundwater recharge. Unfortunately, such data set are not that common, and it is one of the objectives of the OneWater French research program to help building a lysimeter long term network in France.

Another challenge is to estimate the effect of human management on the water resource.  For groundwater and river abstraction, most of the time, the observations are partial and most often at an annual time scale. Among the human impact, those associated to large reservoirs are difficult to hide. If in Spain, there is free access to the associated data, it is more difficult in France if they are devoted to hydroelectricity or irrigation.  Small dams are far more numerous, but their direct and cumulative effects are not easy to quantify, especially, since there are few information on how the reservoir fill and spill, and how the water is used. I’ll show some elements on how the combination of biotic and abiotic data can be used to assess the impact of small reservoirs and how their impact can change with climate change.

The results were achieved in collaboration with Remy Bonnet & Julien Boé, Antoine Sobaga, Bertrand Decharme & Nicolas Beaudoin, Jérôme Molénat, Nadia Carluer, Elodie Philippe, Patrick LeMoigne & Claire Magand
Quantifying global-warming-induced changes in spatial and temporal patterns of heavy precipitation events and the implications to flood properties in Mediterranean catchments
Authors: Morin Efrat , Rinat Yair , Armon Moshe
Published: May 2023

Flood properties are known to be sensitive to spatial and temporal patterns of precipitation, which in turn are affected by global warming. In this study, we investigated the effect of global warming on properties of heavy precipitation events (HPEs) in the eastern Mediterranean, focusing on hydrologically-important characteristics, including total precipitation amount, coverage area, precipitation duration and the distribution of rain rates for different durations. Then, we quantified how changes in precipitation due to global warming affect resulting flood properties for small-medium catchments in the study region.

We used the weather research and forecasting (WRF) model to simulate 41 HPEsin present and future (end of 21st century; RCP 8.5 scenario) climate conditions and output the precipitation fields at high resolution (1 km2, 10 min). The calibrated GB-HYDRA distributed hydrological model (<60 s, 100 m) was utilized to simulate floods from those HPEs in 4 small-medium-size basins (18–69 km2). To account for the rainfall spatial uncertainty in the simulations, spatial shifts were applied to the simulated HPEs in a range of 20 km north and south.

We found a major decrease in precipitation accumulation (−30% averaged across events) in future HPEs. This decrease results from a substantial reduction of the rain area of storms (−40%) and occurs despite an increase in the mean conditional rain rate (+15%). In addition, the duration of the HPEs decreases (−9%) in future simulations. The above changes were consistent across events.

These changes have opposite directions, suggesting that flood properties changes are not trivial. Our simulations indicate a future decrease in both flood volume (-27%) and peak discharge (-20%, non-significant) at the outlet of the catchments. On the other hand, peak discharge is increasing in the future for small sub-catchments (< 5 km2). We currently expand this research to account for expected changes in future antecedent soil moisture conditions and land-use.

To conclude: with global warming, HPEs in the eastern Mediterranean are becoming drier and more spatiotemporally concentrated. Consequently, small and larger catchments respond differently to this change, with the former reacting to the increase in rain rates and producing higher flood peak discharge, while the latter reacts more to the reduction in total rainfall, area and duration, and results in lower flood volumes and peaks.
Mapping spatiotemporal soil moisture in highly heterogeneous agricultural landscapes using mobile dual-spectra cosmic-ray neutron probes
Authors: Looms Majken , Kragh Søren Julsgaard , Meyer Rena , Jensen Karsten Høgh , Andreasen Mie
Published: May 2023

The cosmic-ray neutron (CRN) probe has successfully been used to estimate soil moisture time series at various soil and land cover types across several climatic zones. Previous studies also demonstrate the value of mobile CRN campaigns (i.e. roving) for soil moisture mapping. However, the published study locations have mainly been homogeneous in terms of land cover and soil type. At such conditions, simple on-site calibration using small-scale soil samples can be sufficient. Nonetheless, soil sampling is typically time-consuming, is not always possible and/or is not necessarily representable of the true conditions. Furthermore, measured neutron intensities are dependent on all the hydrogen pools within the footprint, primarily soil moisture, but also litter layer and biomass. Thus, calibration using 100+ soil samples for each point along the survey route is necessary in highly heterogeneous agricultural landscapes. The requirement of such spatiotemporal calibration has hindered a full embracement of the CRN roving method. Neutron sensors with multiple energy sensitivities, here named dual-spectra CRN, can instead be combined to separate the influence of various hydrogen pools.

In this work, we used a dual-spectra CRN rover to collect data along a 34.5 Km NE-SW line in Denmark (approximately 176 line Km) at an average speed of 29 Km/h. The data was collected biweekly from December 2018 to May 2019 resulting in 12 campaigns in total. The dual-spectra averages of each campaign correlate to the SMAP soil moisture product, with a higher correlation for purer signals of thermal and epithermal neutron counts. Furthermore, the epithermal neutron intensity and thermal-to-epithermal ratio maps are dependent on the land cover type enabling the use of a simple and robust methodology to obtain spatiotemporal soil moisture maps using these multiple signals. The estimated spatiotemporal soil moisture values are within expected ranges and are not as the neutron signal dependent on land cover. Instead, the average soil moisture appears to be dependent on the estimated hydraulic conductivity map for the area.
Towards an Open Digital Twin of Soil-Plant System
Authors: Zeng Yijian , Alidoost Fakhereh , Schilperoort Bart , Liu Yang , Su Zhongbo
Published: May 2023

Climate projections strongly suggest that the 2022 sweltering summer may be a harbinger of the future European climate. Climate extremes (e.g., droughts and heatwaves) jeopardize terrestrial ecosystem carbon sequestration and hinder EU's goal of being climate-neutral by 2050. The construction of an open digital twin of the soil-plant system helps to monitor and predict the impact of extreme events on ecosystem functioning, the resulting information from which can be used to recommend measures and policies to increase the resilience of ecosystems to climate-related challenges. There are three main components of the soil-plant digital twin:  i) The soil-plant model for a digital representation of the soil-plant system; ii) Physics-aware machine learning algorithms to approximate the soil-plant model; and iii) Data assimilation framework to digest Earth Observation data to update the states of the soil-plant system. This paper will present a prototype of this open soil-plant digital twin.
Clustering Rangelands Based on NDVI Annual Patterns with different aridity grades
Authors: Sanz Ernesto , Martín Sotoca Juan José , Saa-Requejo Antonio , Díaz-Ambrona Carlos H. , Ruiz-Ramos Margarita , Rodríguez Alfredo , Almeida Andres , Moratiel Rubén , Tarquis Ana M.
Published: May 2023

Soil-vegetation-atmosphere transfer (SVAT) schemes explicitly consider the role of vegetation in affecting water and energy balance by considering its physiological properties. However, most current SVAT schemes and hydrological models do not consider vegetation a dynamic component. The seasonal and monthly evolution of the physiological parameters is kept constant year after year. This fact is likely crucial in transient climate simulations for hydrological models used to study climate change impact. Therefore, the analysis of vegetation dynamics became crucial to study these scenarios.

Vegetation dynamics, especially over large scales, can be monitored using remote sensing. The Normalised Difference Vegetation Index (NDVI) is still the most well-known and frequently used spectral indices derived from remote sensing, identifying vegetated areas and their condition. NDVI is based on plants' differential reflectance for different parts of the solar radiation spectrum.

In this work, we present a classification of rangelands in Spain based on the NDVI time series using them, like the result of SVAT and defining metrics and the Hurst Exponent from detrended fluctuation analysis. These areas are located in different precipitation and temperature regimen but with a Mediterranean climate with different aridity grades: Huescar, Castuera and Lozoya. K-means and unsupervised random forest were used to cluster the pixels using time series metrics and Hurst exponents. The clustering results will be discussed by comparing them to climate and topographical data.

References

Sanz E, Sotoca JJM, Saa-Requejo A, Díaz-Ambrona CH, Ruiz-Ramos M, Rodríguez A, Tarquis AM. Clustering Arid Rangelands Based on NDVI Annual Patterns and Their Persistence. Remote Sensing. 2022; 14(19):4949. https://doi.org/10.3390/rs14194949

Acknowledgements

Financial support from the project "CLASIFICACIÓN DE PASTIZALES MEDIANTE MÉTODOS SUPERVISADOS - SANTO" code RP220220C024, by Universidad Politécnica de Madrid, is highly appreciated.
A Swiss-wide network of hydro(geo)logical observatories
Authors: Moeck Christian
Published: May 2023

In recent years, important water-relevant research results have been achieved and numerous emerging issues have been identified. The posed challenges have to be elaborated, and solutions and measures must be developed. In this context, there is a great need to ensure a continuous competence building and to promote an exchange of results, protocols, infrastructure, and equipment as well as hydrological data. Among the different fresh water sources, groundwater is expected to play a key role in a resilient water future. For this reason, hydrogeological observatories are more necessary than ever.

Several existing, long-term hydrogeological observatories within Switzerland are currently being organized into a long-term national hydrogeological observatory network with the support of the Swiss groundwater network (CH-GNet; https://www.swissgroundwaternetwork.ch/en/). The current hydrogeologic observatories are complementary in terms of elevation, geology, use, and scientific as well as practical objectives. These observatories are managed by research groups or practice partners to ensure long-term operability. The observatories are heavily instrumented for long-term hydraulic and chemical water monitoring and are supplemented by field experiments and investigations. It is envisioned that synergies will be created to promote joint and future experiments by a large number of research groups with different expertise. In addition, these observatories are and will be an important tool to train students. National and international research groups have the opportunity to further develop approaches and improve their knowledge under "real" working conditions, as well as to develop and validate modelling and predictive numerical tools. The hydrogeological observatories are constantly further developed and we are open for any suggestions, remarks, and new partners. In our contribution, we present the already existing observatories, goals and the way forward.
Assimilation of soil moisture data from cosmic-ray neutron sensors into the integrated Terrestrial System Modeling Platform TSMP (case study: Rur catchment in Germany)
Authors: Li Fang , Reemt Bogena Heye , Bayat Bagher , Kurtz Wolfgang , Vereecken Harry , Hendricks Franssen Harrie-Jan
Published: May 2023

Cosmic-ray neutron sensors (CRNS) measure soil moisture in real-time at the field scale, bridging the gap between in situ measurements and remote sensing products. This is promising and has the potential to enhance hydrological model predictions through the assimilation of CRNS data and improve the estimation of model parameters. In this study, soil moisture measurements from a network of 13 CRNS in the Rur catchment (~2000km2, Germany) were assimilated into the integrated model Terrestrial System Modelling Platform (TSMP) by the ensemble Kalman filter (EnKF). In total 128 ensemble members were generated by perturbing atmospheric forcing variables and soil textures to account for the uncertainties. The data assimilation experiments (with and without soil hydraulic parameter estimation) were carried out in both a wet year (2016) and a dry year (2018), and later validated using an independent year (2017) without assimilation. The objectives of this study were to investigate the potential of CRNS assimilation for improving soil moisture and evapotranspiration (ET) characterization, estimation of soil hydraulic parameters at the catchment scale, and analysis of whether the data assimilation performance differs between wet and dry years. The data assimilation experiments showed that soil moisture estimation was significantly improved during the assimilation period at measurement locations, with a root mean square error (RMSE) reduction (compared to open loop simulations without assimilation) in the range of 36-60% either in the dry or wet year, and the improvements were limited by the measurement error of CRNS (0.03 cm3/cm3). The joint state-parameter estimation gives better performance than state estimation alone (more than 15% RMSE reduction), and 9% RMSE reduction in the verification period with the updated parameter. The jackknife experiments revealed that the measurement network (~1 site per 200 km2) was insufficiently dense because soil moisture characterization at independent verification locations only improved marginally with large differences between wet and dry years (with an RMSE reduction of 40% in 2016 and 16% in 2018). The improved predictions from the jackknife experiments, however, imply that the assimilation of soil moisture data from a CRNS network still has the potential to improve the soil moisture characterization on the catchment scale by updating the spatially distributed soil hydraulic parameters of the subsurface model. The comparison of simulated ET with the data from eddy covariance (EC) stations demonstrates that it is challenging to achieve great improvements in ET simulations through CRNS soil moisture assimilation (with the RMSE reduction of monthly ET ranging between 6% and 21%).
A Climate Based-Projection of Future Drought in Aegean Region of Turkey
Authors: Safari Mir Jafar Sadegh , Nuri Balov Mustafa , Vaheddoost Babak
Published: May 2023

The frequency, intensity and duration of drought events are expected to increase during the coming years. Hence, the resilience against climate changes and water deficit would be of concerns to ensure agro-food and energy safety. To address this issue, the outputs of general circulation models (GCM) under various emission scenarios are used to generate two meteorological and hydrological drought indices for a number of meteorological stations scattered in three major basins namely Buyuk Menderes, Kucuk Menderes, and Gediz located in the western Turkey (the Aegean Region). The biases in the outputs of GCMs were corrected using linear scaling method with respect to the reference period (1990-2020). The results were assessed in two 30-years period as mid-time future (2041-2070) and late future (2071-2100). Afterward, the well-known standard precipitation index (SPI) together with the streamflow drought index (SDI) are determined based on the outputs of the climate scenarios for the allocated time periods. The results of the study showed a significant increase in the number and severity of the drought events by the end of the century under all emission scenarios.  
Upgrading standard weather station with cosmic ray neutron sensors in Italy: challenges, results, and opportunities.
Authors: Baroni Gabriele , Gianessi Stefano , Mazzoleni Riccardo , Alessandrini Cinzia , Gandolfi Claudio , Cazzuli Orietta , Ragazzi Francesca , Ferraris Stefano , Canone Davide , Ronchi Christian , Cremonini Roberto , Barbero Secondo
Published: May 2023

Over the last decades, several new observation systems have been developed, tested, and implemented in dedicated experimental sites by research groups in many countries all around the World. The data collected at these high-level test sites have boosted research and collaborations providing the basis for new hypothesis testing, better process understanding and model improvements. In contrast, national and more operational ground monitoring networks are still largely based on traditional instruments. Moreover, the different networks and the data are not always well integrated, even at the regional level. For these reasons, the capability to monitor the main components of the hydrological cycle over large areas is still limited and the observation systems to support the management of the water resources and for environmental protections can be improved. By using soil moisture and snow water equivalent monitoring as examples, in this contribution we present and discuss challenges, results and opportunities in upgrading national weather stations and improving the service provided by the public environmental agencies. Specifically, the difficulties of implementing ground monitoring networks are first discussed. The opportunities provided by the development of new non invasive sensors based on cosmic-ray neutrons detection are then presented. The activities and the results conducted during the last years to move this technology further from research to operation are shown. The current uptake from a number of Italian environmental agencies is reported. The key components and current challenges for a successful implementation are finally discussed.
Bridging structural and functional hydrological connectivity in dryland ecosystems
Authors: Crompton Octavia , Katul Gabriel , Thompson Sally , Lapides Dana
Published: May 2023

On dryland hillslopes, vegetation water availability is often subsidized by the redistribution of rainfall runoff from bare soil (sources) to vegetation patches (sinks). In regions where rainfall volumes are too low to support spatially continuous plant growth, such functional connectivity between bare soil and vegetated areas enables the establishment and persistence of dryland ecosystems.  Increasing the connectivity within bare soil areas can intensify runoff and increase water losses from hillslopes, disrupting this redistribution and reducing the water available to sustain ecosystem function.  Inferring functional connectivity (from bare to vegetated, or within bare areas) from structural landscape features is an attractive approach to enable rapid, scalable characterization of dryland ecosystem function from remote observations. Such inference, however, would rely on metrics of structural connectivity, which describe the contiguity of bare soil areas.  Several studies have observed non-stationarity in the relations between functional and structural connectivity metrics as rainfall conditions vary. Consequently, the suitability of using structural connectivity to provide a reliable proxy for functional connectivity remains uncertain and motivates the work here. 

Rainfall-runoff simulations across a wide range of dryland hillslopes, under varying soil and rainfall conditions, are used to establish relations between structural and functional connectivity metrics.  The model results identify that the relations vary between two hydrologic limits -- a `local' limit, in which functional connectivity is related to structural connectivity, and a ‘global’ limit, in which functional connectivity is most related to the hillslope vegetation fraction regardless of the structural connectivity of bare soil areas. The transition between these limits within the simulations depends on rainfall intensity and duration, and soil permeability. While the local limit may strengthen positive feedbacks between vegetation and water availability, the implications of these limits for dryland functioning need further exploration, particularly considering the timescale separation between storm runoff production and vegetation growth.
From observations towards operational site-specific soil moisture ensemble forecasting
Authors: Hoffmann Richard , Görgen Klaus , Bogena Heye , Hendricks-Franssen Harrie-Jan
Published: May 2023

The use of numerical models for real-time management of water resources is becoming increasingly popular as the increasing frequency and intensity of extreme weather events negatively affect society, agriculture and crop yields. Prolonged droughts are becoming the new normal, which, among other things, increase the need for operational, site-specific soil moisture forecasting. A model that provides accurate site-specific soil moisture forecasts can support agriculture by contributing to precision irrigation and the provision of important information for crop planning, yield maximization and the coordination of field operations. Soil moisture assimilation has proven potential to provide appropriate initial conditions for such a forecast model. However, the operational estimation of an initial condition requires model-specific protocols for continuously incorporating new observational data into models for hydrological, crop, land surface, vadose zone, or subsurface processes that are not yet widely available. In this study, we present an automated data pipeline for operational, site-specific soil moisture ensemble forecasting based on the Community Land Model Version 5.0 (CLM5) taking the TERENO agricultural research station "Selhausen" in western Germany as an example. CLM5 simulates vegetation states, carbon and nitrogen pools prognostically. We compare land surface model prediction quality (e.g., soil moisture, crop yield) with and without weather forecasts and with and without near real-time soil moisture data assimilation. Climatological mean time series and 10-day ensemble weather forecasts from the German Weather Service, aggregated to the grid cell, are the atmospheric forcings in simulating future states. Forecasts start from the states of the last simulation time step with on-site measurements of precipitation, wind speed, air temperature, air pressure, relative humidity, and global radiation as the atmospheric forcings. In parallel with forward simulations from 2011-2021 (open loop experiment), soil moisture assimilation is being performed for 2018-2021 to generate site-specific initial conditions for the land surface model with reduced uncertainty. Forecasts starting from initial conditions based on soil moisture assimilation are more reliable as model bias is reduced. Preliminary results show that the inclusion of site-specific weather forecast uncertainties in the model improves the simulation of soil moisture dynamics at the plot scale and is thus important for optimizing irrigation schedules while keeping crop productivity stable.
Event water fractions in overland flow and shallow subsurface flow in a pre-Alpine headwater catchment in Switzerland
Authors: Leuteritz Anna , Gauthier Victor , van Meerveld Ilja
Published: May 2023

In steep humid catchments with a low permeability soil layer close to the surface, lateral flow at or near the soil surface is an important runoff mechanism. In these catchments overland flow and shallow (i.e., near-surface) subsurface flow also play a crucial role in nutrient and sediment mobilization and transport, and thus affect stream water chemistry. However, due to the lack of data on the spatial and temporal variability in the occurrence of overland flow and shallow subsurface flow and their isotopic signature, it is still poorly understood how rainfall event- and site characteristics affect the onset and mixing of these near-surface flow pathways.

We installed 14 small (1 m wide) runoff plots in a 20-ha headwater catchment in the Swiss pre-Alpine area that is underlain by Gleysols and Flysch bedrock. We coupled hydrometric measurements and stable water isotope data to infer the source (groundwater, soil water, and rainfall) of overland flow and shallow subsurface flow during rainfall events during the snow-free seasons of 2021 and 2022. Rainfall was sampled sequentially at two locations. The isotopic composition of pre-event water was determined based on the soil and groundwater samples taken at each plot prior to the event. Preliminary isotope hydrograph separation results for five rainfall events indicate a median event water fraction over all plots and events of 87% for overland flow and 58% for shallow subsurface flow and a very large variation in the event water contributions (30–100% for overland flow and 9–100% for shallow subsurface).

In this presentation, we will provide an overview of these new data on the temporal and spatial variability of isotopic composition in overland flow and shallow subsurface flow and describe how the event water fractions depend on rainfall event- and site characteristics (topographic position, vegetation cover, and antecedent moisture conditions). 
Observing spatio-temporal variations in rooting depth and density as a control factor for soil moisture dynamics
Authors: Herbst Mathias , Böske Lennart , Falge Eva
Published: May 2023

To understand and predict soil moisture dynamics it is essential to take the role of the vegetation into account. For example, hydrological processes in agricultural soils are strongly affected by seasonal vegetation dynamics in terms of rooting depth and root distribution. Here we present a new approach to monitor and model root dynamics and its influence on soil moisture in the critical zone using mini-rhizotrons combined with phenological observations.

The setup in the field observatory consists of a portable root scanner connected to a tablet computer and a number of acrylic glass tubes with a diameter of two inches that are inserted into the soil at the start of the growing season of selected crops. 360-degrees-scans of soil and roots are taken regularly at different depths in the tubes. Root parameters such as length, diameter, surface and density are identified automatically from the data for each soil layer. Complementary observations of aboveground plant phenology, obtained either by visual inspection in-situ or by remote sensing techniques, are related to the root parameters.

Results from mini-rhizotron data collected at two observatories in Germany show that vertical root distribution and maximum rooting depth in agricultural soils, which varies with plant species and phenology, weather patterns, soil type and management, irrigation etc., are crucial parameters to explain the observed temporal variability and vertical gradients in soil moisture satisfactorily. Deriving these parameters from above-ground phenology and incorporating them into a soil water model led to a significant improvement when compared to a model version based on reference rooting depths from the literature. Thus, we argue that mini-rhizotrons constitute a useful supplement to hydrological observatories and can help understand and predict soil moisture dynamics in the critical zone.
When does near-surface flow occur in a pre-Alpine headwater catchment?
Authors: Gauthier Victor , Leuteritz Anna , van Meerveld Ilja
Published: May 2023

Overland and subsurface flow are major runoff processes but remain poorly understood for pre-Alpine catchments with low permeability soils. The connectivity of these near-surface flow pathways leads to quick changes in streamflow during events. However, their occurrence is highly variable in both space and time, and depends on the geomorphological setting and event characteristics. Therefore, the aim of the TopFlow project is to investigate the generation and connectivity of overland flow and shallow subsurface flow in a Swiss pre-Alpine catchment.

We installed runoff plots at 14 locations inside a 20-ha catchment to measure overland flow and shallow (up to ~40 cm) subsurface flow during two summers: 2021 and 2022. In addition, we used homemade electrical resistance sensors to detect near-surface flow and saturation and we measured groundwater levels and soil moisture. The plots are located at different topographic locations and under different vegetation. In this presentation, we will present our first results on the occurrence of the overland flow and shallow subsurface flow and relate them to the topographic position and rainfall- and antecedent wetness conditions.
Monitoring Environmental Variables to Promote Precision Agriculture
Authors: Maggioni Viviana , Massari Christian , Kandasamy Janani , Xue Yuan , Modanesi Sara , De Santis Domenico , Manca di Villahermosa Francesca Sofia , Penna Daniele , Benettin Paolo , Dionigi Marco
Published: May 2023

Precision agriculture is a modern approach based on farm and irrigation management to improve the efficiency in the use of water resources. Precision agriculture, therefore, maximizes crop productivity and yield through technologies that identify, analyze, and monitor variability within a field and optimize profitability, sustainability, and land protection. This study proposes a combination of approaches to monitor a suite of environmental variables with the goal of improving agricultural management. We selected the experimental vineyard of Grignanello (Tuscany, Italy), located on a mild slope at 350 m.a.s.l in the famous Chianti wine region, where extensive ecohydrological data are available. In combination with this set of ground-based observations, the Environmental Policy Integrated Climate Model (EPIC) is adopted to model key variables for crop production, including soil temperature and soil water content. Using the EPIC model, we generate three sets of simulations based on three different parameterizations (i.e., original cosine, enhanced cosine, and pseudo heat transfer). By comparing model output against ground-based measurements and UAV-based soil temperature, we assess what model set-up is more accurate and for which environmental variable of interest. Furthermore, a new set of soil temperature and soil moisture estimates is obtained by taking the mean of the three EPIC simulations. Thus, we assess the possibility to improve the performance of the single models, as shown in previous studies across the Central Valley in California. Outcomes from this work will provide a solid basis towards developing a decision guidance system for precision agriculture management. 
Mapping of potential groundwater dependent vegetation zones in the Mediterranean using a simple index based on global-available geodata and high-resolution remote sensing
Authors: El-Hokayem Léonard , De Vita Pantaleone , Conrad Christopher
Published: May 2023

Groundwater resources are biodiversity hotspots, and provide crucial ecosystems services. Yet, groundwater dependent ecosystems (GDEs) are exposed to several anthropogenic threats, including climate and land use change. Tackling these threats requires improving the on-the-ground identification of GDEs at the global scale and especially in vulnerable areas such as the Mediterranean biome where water is scarce.

In order to identify the location of groundwater dependent vegetation (GDV) in the landscape and create a harmonized global map of GDV a novel multi-instrument and multi-scale approach was developed. The approach combines a geodata-based potential GDV zones-index (pGDVZ) together with high-resolution vegetative, hydrogeological and topographic remote sensing parameters.

The pGDVZ integrates global and openly available datasets to combine groundwater vegetation interaction, land use, soil characteristics and landscape wetness potential. The index is currently tested for the whole Mediterranean. Results can help to pinpoint areas of high GDVZ potential where regional high-resolution identification of GDV is necessary.

The regional GDV-mapping concept implements different criteria aiming at: 1) high vitality and wetness during dry periods (e.g., Enhanced Vegetation Index, Normalized Difference Vegetation Index, Normalized Difference Water Index), 2) low seasonal changes in vitality, 3) low interannual changes in vitality, 4) high topographic potential of water accumulation and low water table depth and 5) general topography (elevation, slope). Processing of different remote sensing data (e.g., Sentinel 1;2, Digital Elevation Models, MODIS) is performed using the Google Earth Engine. Botanical mapping as well as integration of several geodata is used for validation and calibration of derived GDV-likelihoods. Furthermore, the integration of vegetation plots extracted from sPlot, the global vegetation database introduces a novel methodology to train machine learning algorithm for classification and modelling of GDV.

After successfully testing the mapping approach at local scale in the ‘Cilento, Vallo di Diano and Alburni National Park’ in Campania (Italy), a two-step upscaling methodology is currently designed to implement the concept on regional (county) and global (biome) scale.
Evapotranspiration partitioning over irrigated wheat in a semi-arid region using in-situ measurements and AquaCrop model.
Authors: Bouras El houssaine , Amazirh Abdelhakim , Rafi Zoubair , Jarlan Lionel , Khabba Said , Merlin Olivier , Er-Raki Salah
Published: May 2023

Accurate estimation of the partitioning of actual evapotranspiration (ETa) into plant transpiration (Tr) and soil evaporation (E) is difficult but important for assessing biomass production and the allocation of increasingly scarce water resources. This work aims to evaluate the performance of the AquaCrop model to estimate actual crop ETa and its components (Tr and E) over drip irrigated wheat fields in the semi-arid region of Morocco. Field experiments were carried out during 2016-2017 season on an irrigated winter wheat field in semi-arid region of Morocco. Wheat ETa and its partitioning components (Tr and E) were measured by using the eddy covariance (EC) system and the sap flow system (SF). The obtained results showed that the AquaCrop model adequately simulated canopy cover (CC), ETa and wheat biomass. The coefficient of determination (R2) between observed and measured CC, ETa and biomass were 0.98, 0.72 and 0.98 respectively. With regard to the ETa partitioning, the results indicate that the estimate of Tr using the AquaCrop model is well consistent with those of the in-situ measurements with SF. The Root mean square error (RMSE) between the observed and simulated Tr was about 0.60 mm.day-1. This work demonstrates that the AquaCrop model has reliable accuracy in simulating wheat growth, production and ETa partitioning. As a result, this model provides a technical means of application to formulate optimal irrigation schedules.
Landslide Early Warning System based on Machine learning and radar data
Authors: Santonastaso Giovanni Francesco , Marino Pasquale , Roman Quintero Daniel Camilo , Greco Roberto
Published: May 2023

In the area of Casamicciola, on the island of Ischia, in the Gulf of Naples, on November 26, 2022, heavy rain triggered landslides that killed people and caused great damage to buildings and roads. Rain gauges on the island recorded heavy rainfall starting at midnight on November 25. The 6-hour cumulative rainfall (between 00:00 on 25/11 and 06:00 on 26/11) resulted 126 mm. The peak hourly rainfall at the two nearest rain gauges was 51.6 mm in Forio and 50.4 mm in Monte Epomeo, attained just before the triggering of the major landslide. The attainment of critical rainfall depth was so sudden, that rain gauges recordings did not allow deploying timely risk mitigation measures. In this context, an effective Landslide Early Warning System (LEWS), based not only on rain gauges, would be an important tool to mitigate the impact of landslides. The goal of a LEWS is to provide timely information to individuals and organizations, so that they can take appropriate actions to reduce the risk. These systems typically use a combination of monitoring networks and modeling techniques, to issue real-time warnings when the probability of a landslide becomes high. A well-designed LEWS can save lives, reduce property damage, and minimize the economic impact of the events.

In this paper, a novel approach to LEWS, based on machine learning and radar data, is proposed. Specifically, a random forest model is trained to define pre-alarm thresholds based on radar measurements available on the portal MISTRAL (Mistral portal Meteo Italian SupercompuTing poRtAL), and on rainfall measurements from four rain gauges on the island of Ischia. Two concentric monitoring areas around the island of Ischia are divided into 16 sectors, and the model evaluates every five minutes the percentage of nodes in each sector where the rainfall height detected by the radar exceeds assigned thresholds, corresponding to pre-alarm stages. Preliminary results show the prospects of using machine learning in LEWS.
A novel combined approach for bridging scales in spatiotemporal soil moisture monitoring applying metrological principles
Authors: Oswald Sascha E. , Rothermel Sebastian , Baroni Gabriele , Balenzano Anna , Kjeldsen Henrik , Schrön Martin , Zboril Miroslav
Published: May 2023

One of the key environmental variables and essential climate variable is soil moisture, with its high relevance for applications such as agriculture, forestry, water management including hydrometeorological extreme events or hydrological modelling. Yet accurate measurement of soil moisture is limited by its high natural spatiotemporal variability, given spatially (vertically and horizontally) variable hydraulic properties of soil, and events that are highly variable themselves (in time, extension and intensity).One geophysical method to close the gap between point-scale measurements and satellite-based remote sensing is Cosmic Ray Neutron Sensing (CRNS). Its integration area of about 0.1 km² is above the coverage of wireless sensor networks and at least when combined to CRNS clusters can cover several pixels of high resolution satellite remote sensing, e.g. by the ESA Sentinel-1 Earth Observation mission. We combine these three methods to bridge the scales in monitoring of soil moisture, and this within a novel metrological framework on validation and standardization.The basis for that is an EU-wide collaboration project of 18 institutions called SoMMet[1]. Its approach is to thoroughly establish CRNS as a bridging method at intermediate scale by linking it to point-scale soil moisture sensors with certification according to newly established metrological standards while testing a range of CRNS detector designs in facilities for neutron metrology. The aim is to achieve an improved comparability and reliable estimates of uncertainty and provide recommendations on network design and validation practices, which shall result in a more widespread transfer into remote sensing applications and hydrological modelling.A central component is to conduct field comparison and testing campaigns covering the different scales at three high-level field sites across Europe. One of the candidate sites is located close to Potsdam, Northern Germany. Having evolved from temporary soil moisture field campaigns it hosts the sole long-term CRNS cluster (currently 15 CRNS probes) that covers a conjoined area. This is somewhat similar to wireless in-situ sensor networks, but working non-invasively, with partially overlapping footprints and last not least on larger scale, here about 0.6 km² altogether. We will present examples of SoMMet field test sites, and especially first results of this CRNS cluster from 2023 in its recently extended coverage set-up that now brings it further up to satellite remote sensing resolution.
[1] Acknowledgment: The project 21GRD08 SoMMet has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States.
Satellite images potentiality for calibration of hydrodynamic model in estuaries and coastal areas
Authors: Menzione Antonia , Mancini Marco
Published: May 2023

Over the last decades, numerous models for sediment transport prediction have been proposed with application to littoral transport. However, the morpho-dynamic interactions that occur at the river mouth are still largely unexplored given different concurring phenomena, deriving from both river hydraulics and marine hydrodynamics. Against the high technical-scientific interest, the calibration of the hydrodynamic models of coast-mouth interaction presents,a lack of possible observations, due to both the spatial extension of domains and to their strong two-dimensional pattern.

To overcome this, the present work investigates the possibility of using satellite images, as tools for calibrating and validating hydrodynamic numerical models, an approach already successfully used over the years in the field of hydrological modelling.

For this purpose, hydrodynamic model (TELEMAC2D) were used to simulate the hydrodynamic components and the relative sediment transport  components (SISYPHE), and the pattern of the superficial velocities fields is compered with the remote sensing images.

In this study two different cases study in Adriatic Basin ware analysed. The River Piave (220 km), which flows from the eastern Italian Alps to the North Adriatic Sea, and a river in the southern part of Italy, Ofanto River (134km). The configuration of the Adriatic basin has such a shape as to generate particular tidal and wave conditions, which is why it is important to carry out a hydrodynamic study upstream, using the various drivers both on the river side and on the seaside, such as water discharge, tide, wind, etc. Then, depending on the results obtained from the hydrodynamic model, the dispersion of sediment during a flood event is analysed.

Early results show potential for using satellite images of suspended sediment plumes as calibration targets for numerical models.
TVET SUDS MAR opportunities for water sustainability
Authors: Amanzholova Raushan , Stefan Dr.Catalin , Sallwey Dr. Jana , Ongdas M.Sc. Nurlan , Sarbassov Dastan , Sailaubek Akgulim , Sagin Dr.Jay
Published: May 2023

Floods and droughts are widespread emergency event (EE) issues in Central Asian (CA) countries. Water sustainability and efficient use of water resources are connected to complicated problems in CA. SustDrain (https://www.susdrain.org/ )  will be reasonable to expand in an application for the proper water management, collection, and efficient use of flood water. We are working on the potential expansion in applications of the TERESA project for CA, https://teresa.inowas.com/about/. TERESA is a nature-based solution for urban catchments by combining the advantages of sustainable urban drainage (SUDS) and MAR systems. The vulnerability to flooding and the growing demand for drinkable water are complicated issues for CA regions. Integrated water management, which integrates surface water management (stormwater catchment, flood protection) and groundwater management, is required to address both issues simultaneously (recharge measures, recovery for different uses). The development of multifunctional solutions should reduce stormwater runoff and increase groundwater recharge for the mitigation of flooding and protection of groundwater-dependent ecosystems. Some of the complexities to expanding the TERESA project applications are related to the acceptance of this approach with the expansion of the connected TVET (technical and vocational education and training) programs among the CA communities. The current customs, community attitude, and legislation system will be reasonable to update in combination with water efficiency technologies, modeling, and prediction analysis. For example, snow in urban Kazakhstan areas is categorized as “ waste”, and municipalities usually collect snow and damp snow by moving out by the big tracks in the garbage collection sites, without proper localized SusDrain MAR approach, as the TERESA project implementation program suggests. The current status of the TVET SUDS MAR activities for CA communities will be presented during the conference