ALBERT

Description: Remote-sensing-based machine learning approaches for water quality parameters estimation, Secchi Disk Depth (SDD) and Turbidity, were developed for the Valle de Bravo reservoir in central Mexico. This waterbody is a multipurpose reservoir, which provides drinking water to the metropolitan area of Mexico City. To reveal the water quality status of inland waters in the last decade, evaluation of MERIS imagery is a substantial approach. This study incorporated in-situ collected measurements across the reservoir and remote sensing reflectance data from the Medium Resolution Imaging Spectrometer (MERIS). Machine learning approaches with varying complexities were tested, and the optimal model for SDD and Turbidity was determined. Cross-validation demonstrated that the satellite-based estimates are consistent with the in-situ measurements for both SDD and Turbidity, with R2 values of 0.81 to 0.86 and RMSE of 0.15 m and 0.95 nephelometric turbidity units (NTU). The best model was applied to time series of MERIS images to analyze the spatial and temporal variations of the reservoir’s water quality from 2002 to 2012. Derived analysis revealed yearly patterns caused by dry and rainy seasons and several disruptions were identified. The reservoir varied from trophic to intermittent hypertrophic status, while SDD ranged from 0–1.93 m and Turbidity up to 23.70 NTU. Results suggest the effects of drought events in the years 2006 and 2009 on water quality were correlated with water quality detriment. The water quality displayed slow recovery through 2011–2012. This study demonstrates the usefulness of satellite observations for supporting inland water quality monitoring and water management in this region.

Description: Coastal zones are important areas for the development of diverse ecosystems. The analysis of chlorophyll a (Chl a), as an indicator of primary production in these regions, is crucial for the quantification of phytoplankton biomass, which is considered the main food chain base in the oceans and an indicator of the trophic state index. This variable is greatly important for the analysis of the oceanographic variability, and it is crucial for determining the tendencies of change in these areas with the objective of determining the effects on the ecosystem and the population dynamics of marine resources. In this study, we analysed the Chl a concentration distribution on the mainland coast of the Gulf of California based on the monthly data from July 2002 to July 2019, obtained from remote sensing (Moderate-Resolution Imaging Spectroradiometer Aqua (MODIS-Aqua) with a 9 km resolution). The results showed a clear distribution pattern of Chl a observed along this area with the maximum levels in March and minimum levels in August. A four-region characterisation on this area was used to make a comparison of the Chl a concentrations during warm and cold periods. The majority of the results were statistically significant. The spectral analysis in each of the four regions analysed in this study determined the following variation frequencies: annual, semi-annual, seasonal, and inter-annual; the last was related to the macroscale climatological phenomena El Niño-La Niña affecting the variability of the Chl a concentration in the study region.

Description: This study simulates annual net primary production (NPP) of forests over peninsular Spain during the years 2005–2012. The modeling strategy consists of a linked production efficiency model based on the Monteith approach and the bio-geochemical model Biome-BGC. Recently produced databases and data layers over the study area including meteorological daily series, ecophysiological parameters, and maps containing information about forest type, rooting depth, and growing stock volume (GSV), were employed. The models, which simulate forest processes assuming equilibrium conditions, were previously optimized for the study area. The production efficiency model was used to estimate daily gross primary production (GPP), while Biome-BGC was used to simulate growth (RG) and maintenance (RM) respirations. To account for actual forest conditions, GPP, RG, and RM were corrected using the ratio of the remotely-sensed derived actual to potential GSV as an indicator of the actual state of forests. The obtained results were evaluated against current annual increment observations from the Third Spanish Forest Inventory. Coefficients of determination ranged from 0.46 to 0.74 depending on the forest type. A simplified dataset was produced by applying regular increments in air temperature and reductions in precipitation to the original 2005–2012 daily series with the goal of covering the range of variation of the climate projections corresponding to the different climate change scenarios reported in the literature. The modified meteorological series were used to simulate new GPP, RG, and RM through Biome-BGC and corrected using GSV. Precipitation was confirmed as the main limiting factor in the study area. In the regions where precipitation was already a limiting factor during 2005–2012, both the increment in air temperature and the reduction in precipitation contributed to a reduction of NPP. In the regions where precipitation was not a limiting factor during 2005–2012, the increment in air temperature led to an increment of NPP. This study is therefore relevant to characterize the growth of Spanish forests both in current and expected climate conditions.

Description: Water vapor radiative effects (WVRE) at surface in the long-wave (LW) and short-wave (SW) spectral ranges under cloud and aerosol free conditions are analyzed for seven stations in Spain over the 2007–2015 period. WVRE is calculated as the difference between the net flux obtained by two radiative transfer simulations; one with water vapor from Global Positioning System (GPS) measurements and the other one without any water vapor (dry atmosphere). The WVRE in the LW ranges from 107.9 Wm 2 to 296.7 Wm − 2 , while in the SW it goes from − 64.9 Wm − 2 to − 6.0 Wm − 2 . The results show a clear seasonal cycle, which allows the classification of stations in three sub-regions. In general, for total (SW + LW) and LW WVRE, winter (DJF) and spring (MAM) values are lower than summer (JJA) and autumn (SON). However, in the case of SW WVRE, the weaker values are in winter and autumn, and the stronger ones in summer and spring. Positive trends for LW (and total) WVRE may partially explain the well-known increase of surface air temperatures in the study region. Additionally, negative trends for SW WVRE are especially remarkable, since they represent about a quarter of the contribution of aerosols to the strong brightening effect (increase of the SW radiation flux at surface associated with a reduction of the cloud cover and aerosol load) observed since the 2000s in the Iberian Peninsula, but with opposite sign, so it is suggested that water vapor could be partially masking the full magnitude of this brightening.

Description: Wastewater treatment plants are essential for preserving the water quality of freshwater and marine ecosystems. It is estimated that, in the UK, as much as 11 billion liters of wastewater are treated on a daily basis. Effective and efficient treatment of wastewater requires treatment plants to be maintained in good condition. Recent studies have highlighted the potential of unmanned aircraft systems (UASs) and image processing to be used in autonomous and automated monitoring systems. However, the combined use of UASs and image processing for wastewater treatment plant inspections has not yet been tested. This paper presents a novel image processing-UAS framework for the identification of failures in trickling filters and activated sludge facilities. The results show that the proposed framework has an accuracy of 95% in the detection of failures in activated sludge assets, with the accuracy ranging between 55% and 81% for trickling filters. These results are promising and they highlight the potential use of the technology for the inspection of wastewater treatment plants.

Description: In Zaruma city, located in the El Oro province, Ecuador, gold mines have been exploited since before the colonial period. According to the chroniclers of that time, 2700 tons of gold were sent to Spain. This exploitation continued in the colonial, republican, and current periods. The legalized mining operation, with foreign companies such as South Development Company (SADCO) and national companies such as the Associated Industrial Mining Company (CIMA), exploited the mines legally until they dissolved and gave rise to small associations, artisanal mining, and, with them, illegal mining. Illegal underground mining is generated without order and technical direction, and cuts mineralized veins in andesitic rocks, volcanic breccia, tuffs and dacitic porphyry that have been intensely weatherized from surface to more than 80 meters depth. These rocks have become totally altered soils and saprolites, which have caused the destabilization of the mining galleries and the superficial collapse of the topographic relief. The illegal miners, called "Sableros", after a period of exploitation at one site, when the gold grade decreased, abandon these illegal mines to begin other mining work at other sites near mineralized veins or near legalized mining galleries in operation. Due to this anthropic activity of illegal exploitation through the mining galleries and “piques” that remain under the colonial center of the city, sinkings have occurred in various sectors detected and reported in various technical reports since 1995. The Ecuadorian Government has been unable to control these illegal mining activities. The indicators of initial subsidence of the terrain are small movements that accumulate over a time and that can be detected with InSAR technology in large areas, improving the traditional detection performed with geodetic instrumentation such as total stations and geodetic marks. Recent subsidence at Fe y Alegría-La Immaculada School, the city’s hospital and Gonzalo Pizarro Street, indicates that there is active subsidence in these and other sectors of the city. The dynamic triggers that have possibly accelerated the rate of subsidence and landslides on the slopes are earthquakes (5 to 6 Mw) and heavy rains in deforested areas. Although several sinks and active subsidence caused by underground mining were detected in these sectors and in other sectors in previous decades, which were detailed in various reports of geological hazards prepared by specialized institutions, underground mining has continued under the colonial city center. In view of the existing risk, this article presents a forecasting methodology for the constant monitoring of long-term soil subsidence, especially in the center of the colonial city, which is a national cultural heritage and candidate for the cultural heritage of humanity. This is a proposal for the use of synthetic aperture radar interferometry (InSAR) for the subsidence analysis of topographic relief in the colonial area of the city of Zaruma by illegal mining galleries.

Description: The lack of urban sustainability is a widespread deficiency in urban agglomerations. To achieve adequate land use, we present a methodology that allows for: 1) the identification of the impacts caused by urban expansion since 1956 to the present in Salamanca (Spain); and 2) the promotion of a more sustainable future in urban development. A multi-temporal assessment of land use was made by remote sensing, while sustainability criteria were analyzed using the multicriteria analysis (MCA) with Geographical Information Systems (GIS). In addition, we established recommendations for soil carbon management in semi-arid ecosystem soils that contribute to climate change mitigation. The results show an increase of the urbanized area from 3.8% to 22.3% in the studied period, identifying up to 15% of buildings in zones with some type of restriction. In 71% of the cases, urbanization caused the sealing of productive agricultural soils (2519 Ha), almost 20% of which were of the highest quality. In last few decades, an excessive increase of built-up areas in comparison to population dynamics was identified, which causes unnecessary soil sealing that affects the food production and the capacity to mitigate climate change by managing the carbon cycle in the soil.

Description: The optimization of forest management in the surroundings of roads is a necessary task in term of wildfire prevention and the mitigation of their effects. One of the reasons why a forest fire spreads is the presence of contiguous flammable material, both horizontally and vertically and, thus, vegetation management becomes essential in preventive actions. This work presents a methodology to detect the continuity of vegetation based on aerial Light Detection and Ranging (LiDAR) point clouds, in combination with point cloud processing techniques. Horizontal continuity is determined by calculating Cover Canopy Fraction (CCF). The results obtained show 50% of shrubs presence and 33% of trees presence in the selected case of study, with an error of 5.71%. Regarding vertical continuity, a forest structure composed of a single stratum represents 81% of the zone. In addition, the vegetation located in areas around the roads were mapped, taking into consideration the distances established in the applicable law. Analyses show that risky areas range from a total of 0.12 ha in a 2 m buffer and 0.48 ha in a 10 m buffer, representing a 2.4% and 9.5% of the total study area, respectively.

Description: In this study, an analysis of the capabilities of unmanned aerial vehicle (UAV) photogrammetry to obtain point clouds from areas with a near-vertical inclination was carried out. For this purpose, 18 different combinations were proposed, varying the number of ground control points (GCPs), the adequacy (or not) of the distribution of GCPs, and the orientation of the photographs (nadir and oblique). The results have shown that under certain conditions, the accuracy achieved was similar to those obtained by a terrestrial laser scanner (TLS). For this reason, it is necessary to increase the number of GCPs as much as possible in order to cover a whole study area. In the event that this is not possible, the inclusion of oblique photography ostensibly improves results; therefore, it is always advisable since they also improve the geometric descriptions of break lines or sudden changes in slope. In this sense, UAVs seem to be a more economic substitute compared to TLS for vertical wall surveying.

Description: This work evaluates the sensitivity of CO2 air–sea gas exchange in a coastal site to four different model system configurations of the 1D coupled hydrodynamic–ecosystem model GOTM–ERSEM, towards identifying critical dynamics of relevance when specifically addressing quantification of air–sea CO2 exchange. The European Sea Regional Ecosystem Model (ERSEM) is a biomass and functional group-based biogeochemical model that includes a comprehensive carbonate system and explicitly simulates the production of dissolved organic carbon, dissolved inorganic carbon and organic matter. The model was implemented at the coastal station L4 (4 nm south of Plymouth, 50°15.00’N, 4°13.02’W, depth of 51 m). The model performance was evaluated using more than 1500 hydrological and biochemical observations routinely collected at L4 through the Western Coastal Observatory activities of 2008–2009. In addition to a reference simulation (A), we ran three distinct experiments to investigate the sensitivity of the carbonate system and modeled air–sea fluxes to (B) the sea-surface temperature (SST) diurnal cycle and thus also the near-surface vertical gradients, (C) biological suppression of gas exchange and (D) data assimilation using satellite Earth observation data. The reference simulation captures well the physical environment (simulated SST has a correlation with observations equal to 0.94 with a p 〉 0.95). Overall, the model captures the seasonal signal in most biogeochemical variables including the air–sea flux of CO2 and primary production and can capture some of the intra-seasonal variability and short-lived blooms. The model correctly reproduces the seasonality of nutrients (correlation 〉 0.80 for silicate, nitrate and phosphate), surface chlorophyll-a (correlation 〉 0.43) and total biomass (correlation 〉 0.7) in a two year run for 2008–2009. The model simulates well the concentration of DIC, pH and in-water partial pressure of CO2 (pCO2) with correlations between 0.4–0.5. The model result suggest that L4 is a weak net source of CO2 (0.3–1.8 molCm−2 year−1). The results of the three sensitivity experiments indicate that both resolving the temperature profile near the surface and assimilation of surface chlorophyll-a significantly impact the skill of simulating the biogeochemistry at L4 and all of the carbonate chemistry related variables. These results indicate that our forecasting ability of CO2 air–sea flux in shelf seas environments and their impact in climate modeling should consider both model refinements as means of reducing uncertainties and errors in any future climate projections.