Residential water demand is a key element of urban water systems, and hence its analysis, modelling and simulation is of paramount importance to feed modelling applications. During the last decades, the advent of smart metering technologies has released new streams of high-resolution water demand data, allowing the modelling of demand process at fine spatial (down to appliance level) and temporal (down to 1 sec) scales. However, high-resolution data (i.e., lower than 1 min) remains limited, while longer series at coarser resolution (e.g., 5 min or 15 min) do exist and are becoming increasingly more available, while the metering devices with such sampling capabilities have potential for a wider deployment in the near future. This work attempts to enrich the information at fine scales addressing the issue of data unavailability in a cost-effective way. Specifically, we present a novel framework that enables the generation of synthetic (yet statistically and stochastically consistent) water demand records at fine time scales, taking advantage of coarser-resolution measurements. The framework couples: a) lower-scale extrapolation methodologies to provide estimations of the essential statistics (i.e., probability of no demand and second-order properties) for model’s setup at fine scales, and b) stochastic disaggregation approaches for the generation of synthetic series that resamples the regime of the process at multiple temporal scales. The framework, and individual modules, are demonstrated in the generation of 1-min synthetic water demands at the household level, using 15 min data from the available smart meter.

How to cite: Kossieris, P., Tsoukalas, I., and Makropoulos, C.: A framework for cost-effective enrichment of water demand records at fine spatio-temporal scales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12141, https://doi.org/10.5194/egusphere-egu23-12141, 2023.

How to cite: Strigaro, D., Cannata, M., Capelli, C., and Lepori, F.: Cost-effective full monitoring system for long-term measurements in lake ecosystems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15274, https://doi.org/10.5194/egusphere-egu23-15274, 2023.

Inland surface water is the source of about 60% and a key component of the hydrological cycle. The monitoring of inland surface water is fundamental to understanding the effects of climate change on this key resource and preventing water stresses. Water levels traditionally measured by ground instruments like gauge stations are expensive and have high maintenance costs. Conversely, Earth Observation technologies can nowadays collect frequent and regular data with continuous monitoring of water reservoirs, reducing monitoring costs.

With the availability of new data, the need for a capable computation tool is crucial. Google Earth Engine (GEE), a cloud-based computation platform capable of integrating a high variety of datasets with powerful analysis tools [1], has recently added the Global Ecosystem Dynamics Investigation (GEDI) [4] to its wide archive. 

The GEDI [2] instrument, hosted onboard the International Space Station,  is a geodetic-class, light detection and ranging (LiDAR) system, having a 25 m spot (footprint) on the surface over which 3D structure is measured. The footprints are separated by 60 m along-track, with an across-track distance of about 600 m. The measurements are made over the Earth's surface nominally between the latitudes of 51.6° and -51.6°. GEDI was originally developed to enable radically improved quantification and understanding of the Earth’s carbon cycle and biodiversity. 

The available literature highlights that the quality of GEDI data is variable and impacted by several factors (e.g., latitude, orbit). Our preliminary analysis is focused on the accuracy assessment of the GEDI data, at first addressing the problem of outliers detection and removal, and secondly comparing the water levels measured by GEDI with reference ground truth; thus, we considered four lakes in Northern Italy for which level measurements from gauge stations are available.

The proposed outlier detection consists of two steps for each GEDI passage over water surfaces.

The first step is based on two flags implanted within GEDI bands. Specifically, the “quality_flag” indicates if the considered footprint has valid waveforms (1=valid, 0=invalid), due to anomalies in the energy, sensitivity, and amplitude of signals; the “degrade_flag” indicates the degraded state of pointing (saturation intensity of returned photons might reduce the accuracy of measurements) and/or positioning information (GPS data gap, GPS receiver clock drift).

The second step relies on the robust version of the standard 3σ test, implemented considering the NMAD (Normalized Median Absolute Deviation): every GEDI measurement not within -/+3*NMAD from the median is removed as outlier.

To assess the outlier detection procedure and to preliminarily evaluate the accuracy of the GEDI data, we compared the water levels inferred from the median of GEDI measurements after outlier removal with the contemporary water levels from hydrometric stations at four major lakes (Como, Garda, Iseo, Maggiore) in Northern Italy [3]. The comparison is ongoing over the period from GEDI activation until June 2022, for 3 years.

References

[1] Cardille, et al., 2022. Cloud-Based Remote Sensing with Google Earth Engine.

[2] Dubayah, et al., 2021. GEDI L3 gridded land surface metrics, version 1

[3] Enti Regolatori dei Grandi Laghi, 2022. Home Page - Laghi. www.laghi.net.

[4] University of Maryland, 2022. GEDI ecosystem lidar

How to cite: Hamoudzadeh, A., Ravanelli, R., and Crespi, M.: Gedi Data Within Google Earth Engine: Potentials And Analysis For Inland Surface Water Monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15083, https://doi.org/10.5194/egusphere-egu23-15083, 2023.

Evaluating the performance of water indices and quantifying the spatial distribution of water-related ecosystems are important for monitoring surface water resources of our study area since there is a limited study available to compute water indices using high-resolution and multi-temporal sentinel-2 data on a large scale. In addition, a comparative performance analysis of water indices methods using the aforementioned dataset on a country scale, showing their strengths and weaknesses, was missing too. To address these problems, this paper evaluated the performance of water indices for surface water extraction in Ethiopia. For this purpose, high spatial and multi-temporal resolution large-scale sentinel-2 data were employed and processed using the Google Earth Engine cloud computing system. In this study, seven indices, namely water index (WI) and automatic water extraction index (AWEI) with shadow and no shadow, normalized difference water index (NDWI), modified normalized difference water index (MNDWI), sentinel water index (SWI), and land surface water index (LSWI) were evaluated with overall accuracy, producer’s accuracy, user’s accuracy, and Kappa coefficient. The result revealed that the WI and AWEIshadow were the most accurate to extract the surface water compared to other indices in qualitative and quantitative evaluation of accuracy indicators obtained with a kappa coefficient of 0.96 and 0.95, respectively, and with overall accuracy for both in 0.98. In addition, the AWEIshadow index was also relatively better at suppressing shadow and urban areas. The accuracy difference between LSWI and other indices was significant which performed the worst with overall accuracy and kappa coefficients of 0.82 and 0.31, respectively. Using best-performing indices of WI and AWEIshadow, 82650 and 86530 square km of surface water fractions were extracted, respectively. Therefore, our result confirmed that WI and AWEIshadow indices generated better water extraction outputs using a high spatial and multi-temporal resolution of sentinel-2 data under a wide range of environmental conditions and water body types on the country scale.

How to cite: Abebe, M. T. and Breuer, L.: Performance of water indices using large-scale sentinel-2 data in Google Earth Engine Computing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2395, https://doi.org/10.5194/egusphere-egu23-2395, 2023.

Typically, hydrological models are calibrated using observed streamflow at the outlet of the watershed. This approach may fail to mimic landscape characteristics, which significantly impact runoff generation because the streamflow incorporates contributions from several hydrological components. However, remotely sensed evapotranspiration (AET) products are commonly used as additional data with streamflow to better constrain model parameters. Several researchers demonstrated the efficacy of AET products in reducing the degree of equifinality and predictive uncertainty, resulting in a significant enhancement in hydrological modelling. Due to the variety of publicly available AET datasets, which vary in their methods, parameterization, and spatiotemporal resolution, selecting an appropriate AET for hydrological modelling is of great importance. The purpose of this study is to investigate the difference in simulated hydrologic responses resulting from the inclusion of different remotely sensed AET products in a single and multi-objective calibration with observed streamflow data. The GLEAM_3.6a, GLEAM_3.6b, MOD16A2, GLDAS, PML_V2, TerraClimate, FLDAS, and SSEBop datasets were downloaded and incorporated into the calibration of the SWAT hydrological model. The findings indicate that the incorporation of remotely sensed AET data in multi-objective calibration tends to improve model performance and decrease predictive uncertainty, as well as significantly improves parameter identification. Furthermore, AET single-variable calibration results show that the model would have performed well in simulating streamflow even without streamflow data. Moreover, each dataset included in this investigation responded differently. GLEAM_3.6b and GLEAM_3.6a performed the best, followed by FLDAS and PML_V2, while MOD16A2 was the least performing dataset. Thus, this research supports the use of remotely sensed AET in the calibration of hydrological models as a best practice.

How to cite: Taia, S., Erraioui, L., Chao, J., El Mansouri, B., and Scozzari, A.: Applicability of remote sensing evapotranspiration products in reducing uncertainty and equifinality in hydrological model calibration of Oued El Abid watershed., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9701, https://doi.org/10.5194/egusphere-egu23-9701, 2023.

Currents transport the sediment discharge of the Amazon River as far as the Orinoco Delta (Venezuela).  The combined actions of waves (predominately from the NE) and the Guiana Current create mud banks of 30 km in width.  A continuous process of mud erosion and accretion propagates the mud banks westward  

The talk demonstrates tracking the mud banks with satellite-derived bathymetry (SDB).  The SDB method used here is not the familiar Lyzenga bottom radiance to depth inversion which works only in clear waters.  Here there is no bottom visibility.  Instead, the SDB uses the interaction of ocean waves with the bottom.  Ocean waves exhibit refraction, slower celerity, and reduced wavelength as they ‘feel’ the bottom.   These phenomena are observable regardless of water turbidity.

WKB has been successfully implemented with X-band radars on coastal towers and ships (by German and UK researcher groups); and with the WorldView and Pleiades satellites (by this author and others).  However, all these sensor modalities have small ground footprints (~10 km² to 100 km²).

The European Sentinel-2 satellites have dramatically increased WKB coverage to a regional scale.  This talk presents a Sentinel-2 view of the 1500 km muddy coastline, extending up to 50 km offshore (a total area of 75,000 km²).    

The leap in WKB possibilities was made possible by a 220 km image swath, repeat visits every five days, and the free distribution of the images from the Copernicus portal.

How to cite: Abileah, R.: Tracking mud banks on the 1500 km coastline from the Amazon to the Orinoco Delta, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16881, https://doi.org/10.5194/egusphere-egu23-16881, 2023.

The global warming is affecting the rising seas, which increase the saltwater contamination of the coastal zone in terms of intrusion and penetration in the delta system. The delta systems are characterized by complex dynamic between freshwater coming from continent and saltwater. The hydrodynamic system is greatly affected by the problem of climate change producing a scarce recharge of the aquifers and an increase of the upstream of the mixing zone in the surface waters. These conditions can hinder the water use for irrigation purpose leading to salinization of soils. This summer the Po River underwent a large saltwater intrusion crisis endangering the sustainability of the freshwater resources. The saline wedge in the Po Delta area defined salinisation of groundwater and the soil. These phenomena allow for the active ingression of seawater from the east because the hydraulic head is not sufficient to avoid water to flow inland from the sea. In order to define the water quality, the electrical conductivity (EC) is one of the typical used chemical-physical parameters. However, a common probe defines a punctual acquisition and, therefore, it is time consuming to make a monitor along a long river (> 50km), such as the Po di Goro, that is one of the Po River branches. The research group defined two fast geophysical approach for the monitoring of the saltwater penetration and intrusion. The FDEM method was used to detect the saline wedge in the river and the Electrical Resistivity Tomography was applied to monitor the hydrodynamic iteration between the river and the subsoil around the riverbanks. Two geophysical field activities were planned before and after the salt penetration crisis in the Po River, defined in the last summer. In detail, two ERTs and two long FDEM profiles were carried out along the Po di Goro river. Moreover, a “moving boat” approach with a multilevel EC probe was applied to join the acquired geophysical data set. The ERT sections highlighted how the salty water in the river contaminated the surrounding subsoil. The FDEM data sets defined the hydrodynamic of the saltwater wedge in the river detecting the salty plume front. These results highlight the great potential of the proposed geophysical approach to monitor the saline plume during crisis periods.

How to cite: Rizzo, E., Boldrin, P., Bondesan, A., Droghetti, F., Capozzoli, L., De MArtino, G., Ferrari, E., Fornasari, G., Giampaolo, V., and Neri, F.: DC and FDEM salt wedge monitoring of the Po di Goro river (Italy)., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5297, https://doi.org/10.5194/egusphere-egu23-5297, 2023.

Understanding subsurface properties within urban areas is critical for an adequate management of groundwater, for instance to delineate the migration of pollutants, artificial recharge systems or geothermal collectors. Information is available from extraction wells, yet the resolution of the information is limited to the locations where wells are available. Geophysical methods offer an alternative to gain subsurface information. However, asphalted roads and limited accessibility might reduce the applicability of electrical methods for investigations beyond a few meters, whereas vibrations due to traffic and railroads might hinder the application of seismic methods. In this work, we investigate the use of the transient electromagnetic (TEM) method to resolve the geometry of aquifers in urban areas. We propose the use of relative small loops to gain separation from buried structures and increase data quality in late times as required to reach a depth of investigations of ca. 40 m. Measurements were conducted in gardens located within cities deploying single-loop as well as in-loop geometries using two different instruments. Additionally, we evaluate our small loop configuration in a quasi noise-free site through comparison to larger loops and electrical methods. Analysis of the data demonstrate that relative small loops (12.5 m x 12.5 m) may be a possible solution to gain information in urban areas down to a depth of 30 m, yet a minimal separation to anthropogenic structures of ca. 5 m is required. Information at such depth can not be easily gain with refraction seismic or electrical resistivity tomographic measurements in such small areas. Moreover, our results reveal the possibility to gain similar information with smaller loops (6.25 m x 6.25 m), offering the possibility to increase the separation to sources of noise (i.e., buried infrastructure) and increase the data quality. The inversion of TEM measurements collected along a 100 m profile permitted to obtain vertical and lateral variations in aquifer geometry with a maximal depth of investigation of ca. 40 m, while DC-resistivity measurements in the same profile were limited to less than 10 m depth. Stochastic inversion of the data permitted to investigate the uncertainty in the obtained model parameters (resistivity and thickness of the resolved layers, i.e., aquifer).

How to cite: Flores Orozco, A., Aigner, L., and Ferk, J.: Evaluating the applicability of transient electromagnetic (TEM) data to characterize aquifer geometry in urban areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10657, https://doi.org/10.5194/egusphere-egu23-10657, 2023.

In the last years, the use of Deep Electrical Resistivity Tomography (DERT) has become more common for the investigation of areas with complex geological setting. The considerable resolution obtained through such a technique makes it possible to discriminate much more effectively the resistivity contrasts existing in the shallower crustal levels, thus providing more reliable information on the physical conditions of the rocks, the presence of structural discontinuity surfaces, on the presence and trend in the subsoil of aquifers and/or fluids of various origins.

For these reasons, some DERT investigations were carried out in a structurally complex area located close to Tramutola village, in the western side of the Agri Valley, where the largest onshore hydrocarbon reservoir in west Europe is present.

The Tramutola site represented a key sector for the early petroleum exploration and exploitation of the area. Natural oil spills were historically known since the 19th century in the investigated area, and these helped the national oil company to identify the first shallower hydrocarbon traces. Furthermore, a considerable amount of sulphureous hypothermal water (~28 °C with a flow rate of 10 l/s) with associated gases (mainly CH₄ and CO₂) was found during the drilling of the “Tramutola2” well (404.4 m) in 1936. From a geological point of view, the study area, is characterized by the presence of a complete section of the tectonic units of the southern Apennines and a complex structural framework, not yet fully clarified, which affect fluids circulation.

To foster the efficient and sustainable use of the geothermal resource in Tramutola area, surface and subsurface geological, hydrogeological and new geophysical data were combined in order deepen our knowledges about the reservoir of the hypothermal fluids and their circulation.

The municipality of Tramutola is interested in the rehabilitation of the abandoned oil wells, both in terms of exploitation of the geothermal resource and for the realisation of a tourist “Park of energy”. The aim is to provide a wide audience with strategies, models, and technical skills capable of making visitors more active and critical towards the sustainable use of energy resources. Furthermore, the possible exploitation of geothermal resources of the Tramutola site represents a strategic action in the Basilicata region as a prototype of energy transition from fossil fuels to more environmentally friendly energy resources. This is also essential to satisfy the increased demand for clean energy in the area (no. 7 affordable and clean energy United Nations’ SDGs) and also contribute to climate change mitigation through the reduction of CO₂ emissions (13 climate action).

How to cite: Giampaolo, V., Capozzoli, L., De Martino, G., Lapenna, V., Prosser, G., Olita, F., Boldrin, P., and Rizzo, E.: Geofluids inferences using deep electrical resistivity tomography for a sustainable energy transition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14097, https://doi.org/10.5194/egusphere-egu23-14097, 2023.

Recent studies show emissions of dissolved methane (CH₄) in the meltwater from the Greenland Ice Sheet. To better understand the phenomenon and evaluate its potential significance for the Arctic CH₄ budget, continuous long-term measurements of dissolved CH₄ concentrations are needed. Commercially available dissolved CH₄ analyzers (DGEU-UGGA (LGR), CONTROS HydroC CH₄ (Kongsberg) and Mini CH₄ (pro-Oceanus)) generally have high power consumption and are very costly, limiting their operation in remote off-grid locations.

Here we present calibrations and field tests of a low-cost, low-power alternative – the "IceWorm" - for long-term monitoring of dissolved CH₄. The IceWorm uses a Figaro TGS2611-E00 metal oxide sensor (MOS). While MOS are cheap and power efficient, a known drawback is the sensitivity of the sensor's resistance to changes in humidity and temperature. In a previous prototype, we showed that by encasing the MOS in a hydrophobic and gas-permeable silicone membrane, a constant humidity in the headspace around the sensor can be achieved, yielding consistent results when deployed in glacial meltwater at constant temperature (0.0 – 0.1˚C)¹. In this updated version, the sensor was encased in a hydrophobic and gas-permeable Teflon membrane allowing for fast (~1 min) equilibrium between the water and headspace around the sensor and hence a rapid detection of changes in dissolved CH₄ concentrations.

The first calibration was performed by exposing the IceWorm to stepwise increasing Two field calibrations of the sensor performance in meltwater at 0.0˚C were done: Afterwards, the sensors remained in the field for several weeks in the subglacial meltwater stream and the sensors were recalibrated in lab air under the same conditions to check for long-term sensor drift. Initially, field calibrated to measure dissolved CH₄ in glacial meltwater at 0.0˚C, the IceWorm was also tested in a freshwater surface stream at temperatures between 1.6 – 15.7˚C. To account for the temperature difference, we compared the laboratory and field calibrations allowing us to correct the sensor output to temperature variations in the stream.

We will present time series of long-term measurements of dissolved CH₄ in two different types of water bodies and discuss the promising performance of the sensor at temperatures different to stable 0˚C as well as the usability of in-air calibrations compared to the field calibrations with discrete samples.

1. Sapper et al. (2022) DOI:10.5194/egusphere-egu22-9972

How to cite: Christiansen, J., Sapper, S. E., and Juncher Jørgensen, C.: The IceWorm: an improved low-cost, low-power sensor for measuring dissolved CH4 in water bodies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11724, https://doi.org/10.5194/egusphere-egu23-11724, 2023.

With increasing environmental pressure due to global climate change, increases in global
population and the need for sustainable obtained resources, water resources management
is critical. In-situ sensors are fundamental to the management of water systems by providing
early warning, forecasting and baseline data to stakeholders. To be fit-for-purpose,
monitoring using in-situ sensors has to be carried out in a cost effective way and allow
implementation at larger spatial scales. If networks of sensors are to become not only a
reality but common place, it is necessary to produce reliable, inexpensive, rugged sensors
integrated with data analytics.

In this context, the aim of this project was to design and develop a low cost, robust and
reliable optical sensor which capable of continuous measurement of chemical and physical
parameters in aquatic environments. An iterative engineering design method cycling
between sensor design, prototyping and testing was used for the realisation and optimisation
of the sensor. The sensor can provide absorption, scatter, and fluorescence readings over a
broad spectral range (280nm to 850nm) and temperature readings in real-time using a suite
of optical sensors (CMOS Spectrometers and photodiode detector), custom designed LED
array light source and a digital temperature probe. Custom electronics and firmware were
developed to control the sensor and facilitate data transmission to an external network.
Sensor electronics are housed in a marine grade watertight housing; the optical components
are mounted inside a custom designed 3D-printed optical head which joins with the sensor
housing. The sensor is capable of measuring a range of optical parameters and temperature
in a single measurement cycle. Sensor analytical performance was demonstrated in the
laboratory, for detection and quantification of turbidity using analytical standards and in the
field by comparison with a commercially available multi- parameter probe (YSI, EXO 2).
The laboratory and field trials demonstrate that the sensor is fit-for-purpose and an excellent
tool for early warning monitoring by providing high frequency time-series data, operate
unattended in-situ for extended periods of times and capture pollution events.

Acknowledgement - This research is carried out with the support of Project Ireland’s 2040’s
Disruptive Technologies Innovation Fund.

How to cite: Power, S., Free, L., Richards, C., Briciu-Burghina, C., Delgado Ollero, A., Clinton, R., and Regan, F.: A low-cost novel optical sensor for water quality monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14977, https://doi.org/10.5194/egusphere-egu23-14977, 2023.

Soil moisture is an essential parameter for irrigation management, transport of pollutants and estimation of energy, heat, and water balances. Soil moisture is one of the most important soil spatial-temporal variables due to the highly heterogeneous nature of soils which in turn drives water fluxes, evapotranspiration, air temperature, precipitation, and soil erosion. Recent developments have seen an increasing number of electromagnetic sensors available commercially for soil volumetric water content (θ) and their use is expanding providing decision support and high-resolution data for models and machine learning algorithms.

In this context, two demonstrations of in-situ LoRaWAN sensor networks are presented. The 1^st one is from a grassland site, Johnstown Castle, Wexford Ireland where a network of 10 low-cost soil moisture (SM) sensors has been operating for 12 months. The 2^nd network has been operating for 6 months at a peatland site (Cavemount Bog, Offaly, Ireland) which is currently undergoing a rehabilitation process through re-wetting. At this site, in addition to SM sensors, ultrasonic sensors are used for continuous measurement of the water table at 7 locations. For both sites, the analytical performance of the SM sensors has been determined in the laboratory, through calibrations in liquids of known dielectric permittivity and through field validation via sample collection or time domain-reflectometry instrumentation (TDR). Experiences and recommendations in deploying, maintaining, and servicing the sensor networks, and data management (cleaning, validation, analysis) will be presented and discussed. Emphasis will be placed on the key learnings to date and the performance of the low-cost sensor networks in terms of collected data.

Small-scale sensor networks like these are expected to bridge the gap between the low spatial resolution provided by the satellite-derived products and the single point/field measurements. Within the project, the sensor network will provide spatial observations to complement existing fixed point measurements. It will allow researchers to investigate SM dynamics at field scale in response to different soil types, soil density, elevation, and land cover.

How to cite: Briciu-Burgina, C., Zhou, J., Ali, M. I., and Regan, F.: Low-cost in-situ sensor networks for soil moisture and water table measurements: experiences and recommendations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15814, https://doi.org/10.5194/egusphere-egu23-15814, 2023.