Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. <P style='line-height: 20px;'> Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. <P style='line-height: 20px;'> Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (<I>SWVI</I>), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. <P style='line-height: 20px;'> In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the <I>SWVI</I> was able to identify the presence of a sort of 'early' signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability

EVIDENCE OF WEAK CHAOS WITHIN PLUG-SLUG TRANSITION IN HORIZONTAL TWO PHASE FLOW

Intermittent behaviour has been observed in gas-liquid flows in a horizontal pipe and a weak sign of deterministic chaos has been diagnosed within a transition from plug to slug flow. The analysis has been performed on the basis of an algorithm which exploits the concept of short-term predictability of chaotic motions. The method is completely non-parametric and works whatever the distribution function of the data points may be. The weak sign of chaos is in contrast with the Lorenz-type systems (strong chaos) and supports the idea of Kolmogorov about irregular motion in hydrodynamical systems

The VIIRS-Based RST-FLARE configuration: The Val d'Agri Oil Center Gas Flaring Investigation in between 2015-2019

The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d'Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring

Advanced Satellite Technique for Volcanic Activity Monitoring and Early Warning.

Nowadays, satellite remote sensing is an important tool for volcanic activity monitoring, thanks to several operational satellite platforms providing data everywhere with high observational frequencies and generally at low cost. Among different techniques available, an advanced satellite method, named RST (Robust Satellite Technique). based on the multitemporal analysis of satellite data, has shown a high capability in volcanic activity monitoring. This approach has proved capable of identifyimg and tracking volcanic ash Cloud and of correctly detecting and monitoring volcanic thermal anomalies. This paper analyzes some recent results, obtained applying this approach to the last eruptive events of Mt. Etna using both polar and geostationary satellites. In particular, for the first time, this approach is implemented on the present geostationary platform MSG-SEVIRI, with 15 min of temporal resolution. Preliminary results, together with a future potential of this implementation, are shown and discussed. Moreover, a differential RST index in time domain is also proposed for near real-time application, as a possible contribution to the development of an efficient early warning satellite system for volcanic hazard mitigation

A Multi-Sensor Exportable Approach for Automatic Flooded Areas Detection and Monitoring by a Composite Satellite Constellation

Timely and frequently updated information about flood-affected areas and their space-time evolution are often crucial in order to correctly manage the emergency phases. In such a context, optical data provided by meteorological satellites, offering the highest available temporal resolution (from hours to minutes), could have a great potential. As cloud cover often occurs reducing the number of usable optical satellite images, an appropriate integration of observations coming from different satellite systems will surely improve the probability to find cloud-free images over the investigated region. To make this integration effective, appropriate satellite data analysis methodologies, suitable for providing congruent results, regardless of the used sensor, are envisaged. In this paper, a sensor-independent approach (RST, Robust Satellites Techniques-FLOOD) is presented and applied to data acquired by two different satellite systems (Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration platforms and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System satellites) at different spatial resolutions (from 1 km to 250 m) in the case of Elbe flood event occurred in Germany on August 2002. Results achieved demonstrated as the full integration of AVHRR and MODIS RST-FLOOD products allowed us to double the number of satellite passes daily available, improving continuity of monitoring over flood-affected regions. In addition, the application of RST-FLOOD to higher spatial resolution MODIS (250 m) data revealed to be crucial not only for mapping purposes but also for improving RST-FLOOD capability in identifying flooded areas not previously detected at lower spatial resolution

AVHRR Automated detection of volcanic clouds.

A new satellite‐based technique has recently been proposed which seems suitable for an automatic detection of volcanic clouds in daytime conditions. In this paper the robustness of such a new approach, in particular in detecting early eruptive clouds, is evaluated, on several eruptive events at Mt Etna, by using five years of Advanced Very High Resolution Radiometer (AVHRR) data. The detection scheme is discussed together with its possible extension to night‐time monitoring and the improvements expected by its application to the next generation of satellite sensors (in particular Spinning Enhanced Visible and Infrared Imager (SEVIRI)) with enhanced spectral and temporal resolution. The proposed approach seems to overcome the limitations related to other proposed methods which, in some conditions (very fresh eruptive clouds, cold‐backgrounds, etc.), give false or missed detection and will no longer be applicable to the next generation of Geostationary Operational Environmental Satellites (GOES) due to the planned reduction of their thermal infrared channels until 2010

Advanced satellite technique for volcanic activity monitoring and early warning

Nowadays, satellite remote sensing is an important tool for volcanic activity monitoring, thanks to several operational satellite platforms providing data everywhere with high observational frequencies and generally at low cost. Among different techniques available, an advanced satellite method, named RST (Robust Satellite Technique), based on the multitemporal analysis of satellite data, has shown a high capability in volcanic activity monitoring. This approach has proved capable of identifying and tracking volcanic ash cloud and of correctly detecting and monitoring volcanic thermal anomalies. This paper analyzes some recent results, obtained applying this approach to the last eruptive events of Mt. Etna using both polar and geostationary satellites. In particular, for the first time, this approach is implemented on the present geostationary platform MSG-SEVIRI, with 15 min of temporal resolution. Preliminary results, together with a future potential of this implementation, are shown and discussed. Moreover, a differential RST index in time domain is also proposed for near real-time application, as a possible contribution to the development of an efficient early warning satellite system for volcanic hazard mitigation

Integration of optical and passive microwave satellite data for flooded area detection and monitoring

Flooding represents a serious threat to millions of people around the world and its hazard is rising as a result of climate changes. From this perspective, flood risk management is a key focus of many governments, whose priority is to have frequently updated and accurate information about the flood state and evolution to promptly react to the disaster and to put in place effective countermeasures devoted to limit damages and human lives losses. Remote sensing technology allows for flood monitoring at different spatial and temporal resolutions with an adequate level of accuracy. In particular, for emergency response purposes, an integrated use of satellite data, acquired by both optical and passive or active microwave instruments, has to be preferred to have more complete and frequently updated information on soil conditions and to better support decision makers. In this framework, multi-year time series of MODIS (Moderate Resolution Imaging Spectroradiometer) and AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observing System) data were processed and analyzed. In detail, the Robust Satellite Techniques (RST), a multi-sensor approach for satellite data analysis, has been implemented for studying the August 2002 Elbe river flood occurred in Germany, trying to assess the potential of such an integrated system for the determination of soil status and conditions (i.e. moisture variation, water presence) as well as for a timely detection and a near real time monitoring of critical soil conditions

On the use of AMSU-based products for the description of soil water content at basin scale

Abstract. Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Besides in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors on board of airborne and/or satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit-A (NOAA-AMSU-A) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months (3 March 2010–18 May 2010), was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements were carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5 yr data time series) was made using soil moisture simulated by a hydrological model. Measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both time series of indices have been filtered by means of an exponential filter to account for the fact that microwave sensors only provide information at the skin surface. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the general trend of soil moisture, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI

Earthquake-Related Signals in Central Italy Detected by Hydrogeochemical and Satellite Techniques

Central Apennines are one of the highest seismic risk regions in Italy. A number of energetic events ((Formula presented.) &gt; 5) struck the region during the period 2004–2017, killing several hundreds of people (e.g., 294 casualties associated with the August 24th, 2016, (Formula presented.) 6.0 event of Amatrice). These earthquakes impacted piezometric levels, springs discharges, and groundwater chemistry across a large area, even at distances of dozens of kilometers from the epicenters. Here we present a multidisciplinary dataset based on hydrogeochemical and satellite observations associated with the seismic events that occurred in Central Italy during the period 2004–2017, which combines information derived from the application of groundwater monitoring and satellite techniques. Groundwater monitoring techniques allowed for the detection of hydrogeochemical anomalies in spring and well waters (14 water sampling points in total, with 22 variations larger than (Formula presented.)), while satellite techniques were applied to detect time-space variations in ground thermal emissions. We detected two significant, almost synchronous, anomalies in 2009 and 2016–2017 with both techniques, and we tentatively correlated them to crustal deformation processes. Part of the observed signals were detected before mainshocks, and they appear to be related to aseismic slip or to seismic slip eventually induced by minor fluctuations in seismicity. We argue that the combination of two factors, i.e., the shallow depth of local earthquakes and the concurrent deepening of groundwater circulation paths to several km depth, allow for the recording of variations in the stress field by geofluids released at the surface