Simulated suspended sediment flows in South America using hydrological-hydrodynamic modeling

2021 ◽  
Author(s):  
Hugo Fagundes ◽  
Fernando Fan ◽  
Rodrigo Paiva ◽  
Vinicius Siqueira ◽  
Diogo Buarque ◽  
...  
Keyword(s):  
South America ◽  
Model Performance ◽  
Suspended Sediments ◽  
Sediment Supply ◽  
Regional Studies ◽  
In Situ Data ◽  
Sediment Flow ◽  
Spatio Temporal ◽  
Negative Impacts

<p>Suspended sediments (SS) have an important role in the maintenance of several ecosystems by supplying them with nutrients. On the other hand, erosion and sediment transport can carry pollutants and pesticides, contributing to the negative impacts on the aquatic biota. Besides that, sediment supply for the rivers is often a driver to geomorphologic changes occurring in the rivers. Erosion and sediment rates in South America are considerably high in comparison to northern continents in the world. In this study we modeled the natural (non affected by reservoirs) spatio-temporal dynamic of suspended sediments in South America, including deposition rates in floodplain areas, using the sediment continental model MGB-SED SA. The model performance was evaluated aga inst 595 in-situ stations; 80 sites using results from regional studies; and 51 sites using results from a global sediment model. For most places, model performance analysis shows a better agreement between simulated and observed (in-situ) data than when results were compared to regional studies and a global model data. A better representation of sediment flow in rivers and floodplains was possible due to the use of hydrodynamic river routing. Based on MGB-SED SA estimates, South America delivers to the oceans 1.00×10<sup>9</sup> t/year of SS. The bigger suppliers are the Amazon (4.36×10<sup>8</sup> t/year), Orinoco (1.37×10<sup>8</sup> t/year), La Plata (1.11×10<sup>8</sup> t/year), and Magdalena (3.26×10<sup>7</sup>) rivers. Around 12% (2.40×10<sup>8</sup> t/year) of SS loads reaching the rivers are stored in the floodplains, showing the importance of these regions.  </p>

scholarly journals Investigating the Drivers of Total Suspended Sediment Regime in the Senegal River Basin Using Landsat 8 Satellite Images

2020 ◽  
Vol 13 (1-2) ◽  
pp. 31-42
Author(s):  
Cheikh Faye ◽  
Manuela Grippa ◽  
Laurent Kergoat ◽  
Elodie Robert
Keyword(s):  
Temporal Dynamics ◽  
Time Lag ◽  
Suspended Sediments ◽  
Spatiotemporal Variability ◽  
Landsat 8 ◽  
Senegal River ◽  
In Situ Data ◽  
Spatio Temporal ◽  
Solid Transport

AbstractBecause total suspended sediments (TSS) influence the penetration of light into the water column and are likely to carry pollutants and nutrients, their study is essential for understanding the functioning of African river ecosystems. If the estimation of solid transport is important in the context of hydro-agricultural developments, its quantification often poses a problem. In addition, in situ data for these areas are rare and, as a result, the environmental factors responsible for the variability of TSS can hardly be understood. This work aims to evaluate the spatiotemporal variability of TSS in the surface waters of the Senegal River using satellite data over the 2014-2018 period. The spatio-temporal dynamics of TSS is reconstructed using a relationship established on several West African sites between in situ data from TSS and satellite reflectances from Landsat 8. These data allow analyzing the relationship between TSS and factors such as rainfall and discharge. We found that the TSS peaks in Bakel coincide with the arrival of the first rains and are followed by peaks in discharge with a lag of 2 months. A time lag between TSS and discharge peaks is also observed on its tributaries like the River Falémé. Concerning the spatial variability, TSS generally increase from the river upstream to the downstream and decrease in the Senegal delta after the Diama dam. The analysis of the TSS upstream and downstream of the Manantali dam, in the upstream area, confirms the relatively low sediment deposits in the dam lake.

scholarly journals Biogeomorphic modeling to assess resilience of tidal marsh restoration to sea level rise and sediment supply

2021 ◽  
Author(s):  
Olivier Gourgue ◽  
Jim van Belzen ◽  
Christian Schwarz ◽  
Wouter Vandenbruwaene ◽  
Joris Vanlede ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Tidal Marsh ◽  
Model Performance ◽  
Suspended Sediments ◽  
Sediment Supply ◽  
Tidal Marshes ◽  
Marsh Restoration ◽  
Tidal Marsh Restoration ◽  
Increasing Demand

Abstract. There is an increasing demand for creation and restoration of tidal marshes around the world, as they provide highly valued ecosystem services. Yet, tidal marshes are strongly vulnerable to factors such as sea level rise and declining sediment supply. How fast the restored ecosystem develops, how resilient it is to sea level rise, and how this can be steered by restoration design, are key questions that are typically challenging to assess. In this paper, we apply a biogeomorphic model to a planned tidal marsh restoration by dike breaching. Our modeling approach integrates tidal hydrodynamics, sediment transport and vegetation dynamics, accounting for relevant fine-scale flow-vegetation interactions (less than 1 m2) and their impact on vegetation and landform development at the landscape scale (several km2) and on the long term (several decades). Our model performance is positively evaluated against observations of vegetation and geomorphic development in adjacent tidal marshes. Model scenarios demonstrate that the restored tidal marsh can keep pace with realistic rates of sea level rise and that its resilience is more sensitive to the availability of suspended sediments than to the rate of sea level rise. We further demonstrate that restoration design options can steer marsh resilience, as it affects the rates and spatial patterns of biogeomorphic development. By varying the width of two dike breaches, which serve as tidal inlets to the restored marsh, we show that a larger difference in the width of the two inlets leads to more diversity in restored habitats. This study showcases that biogeomorphic modeling can support management choices in restoration design to optimize tidal marsh development towards sustainable restoration goals.

The limitations of in situ data for validating satellite-derived spatio-temporal ocean products.

2021 ◽  
Author(s):  
Rory Scarrott ◽  
Fiona Cawkwell ◽  
Mark Jessopp ◽  
Caroline Cusack
Keyword(s):  
Surface Temperature ◽  
Surface Heterogeneity ◽  
Ocean Surface ◽  
Bias Reduction ◽  
Data Validation ◽  
Near Surface ◽  
In Situ Data ◽  
Spatio Temporal ◽  
Image Pixels

<p>The Ocean-surface Heterogeneity MApping (OHMA) algorithm is an objective, replicable approach to map the spatio-temporal heterogeneity of ocean surface waters. It is used to processes hypertemporal, satellite-derived data and produces a single-image surface heterogeneity (SH) dataset for the selected parameter of interest. The product separates regions of dissimilar temporal characteristics. Data validation is challenging because it requires In-situ observations at spatial and temporal resolutions comparable to the hyper-temporal inputs. Validating this spatio-temporal product highlighted the need to optimise existing vessel-based data collection efforts, to maximise exploitation of the rapidly-growing hyper-temporal data resource.</p><p>For this study, the SH was created using hyper-temporal 1km resolution satellite derived Sea Surface Temperature (SST) data acquired in 2011. Underway ship observations of near surface temperature collected on multiple scientific surveys off the Irish coast in 2011 were used to validate the results. The most suitable underway ship SST data were identified in ocean areas sampled multiple times and with representative measurements across all seasons.</p><p>A 3-stage bias reduction approach was applied to identify suitable ocean areas. The first bias reduction addressed temporal bias, i.e., the temporal spread of available In-situ ship transect data across each satellite image pixel. Only pixels for which In-situ data were obtained at least once in each season were selected; resulting in 14 SH image pixels deemed suitable out of a total of 3,677 SH image pixels with available In-situ data. The second bias reduction addressed spatial bias, to reduce the influence of over-sampled areas in an image pixel with a sub-pixel approach. Statistical dispersion measures and statistical shape measures were calculated for each of the sets of sub-pixel values. This gave heterogeneity estimates for each cruise transit of a pixel area. The third bias reduction addressed bias of temporally oversampled seasons. For each transit-derived heterogeneity measure, the values within each season were averaged, before the annual average value was derived across all four seasons in 2011.</p><p>Significant associations were identified between satellite SST-derived SH values, and In-situ heterogeneity measures related to shape; absolute skewness (Spearman’s Rank, n=14, ρ[12]= +0.5755, P<0.05), and kurtosis (Spearman’s Rank, n=14, ρ[12] = 0.5446, P < 0.05). These are a consequence of (i) locally-extreme measurements, and/or (ii) increased presence of sharp transitions detected spatially by In-situ data. However, the number and location of suitable In-situ validation sites precluded a robust validation of the SH dataset (14 pixels located in Irish waters, for a dataset spanning the North Atlantic). This requires more targeted data. The approach would have benefited from more samples over the winter season, which would have enabled more offshore validation sites to be incorporated into the analysis. This is a challenge that faces satellite product developers, who want to deliver spatio-temporal information to new markets. There is a significant opportunity for dedicated, transit-measured (e.g. Ferry box data), validation sites to be established. These could potentially synergise with key nodes in global shipping routes to maximise data collected by vessels of opportunity, and ensure consistent data are collected over the same area at regular intervals.</p>

scholarly journals Impact of Satellite and In Situ Data Assimilation on Hydrological Predictions

2020 ◽  
Vol 12 (5) ◽  
pp. 811 ◽  
Author(s):  
Jude Lubega Musuuza ◽  
David Gustafsson ◽  
Rafael Pimentel ◽  
Louise Crochemore ◽  
Ilias Pechlivanidis
Keyword(s):  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Potential Evapotranspiration ◽  
Model Performance ◽  
Filter Method ◽  
Ensemble Size ◽  
In Situ Data ◽  
Predictive Skill ◽  
Reservoir Inflow

The assimilation of different satellite and in situ products generally improves the hydrological model predictive skill. Most studies have focused on assimilating a single product at a time with the ensemble size subjectively chosen by the modeller. In this study, we used the European-scale Hydrological Predictions for the Environment hydrological model in the Umeälven catchment in northern Sweden with the stream discharge and local reservoir inflow as target variables to objectively choose an ensemble size that optimised model performance when the ensemble Kalman filter method is used. We further assessed the effect of assimilating different satellite products; namely, snow water equivalent, fractional snow cover, and actual and potential evapotranspiration, as well as in situ measurements of river discharge and local reservoir inflows. We finally investigated the combinations of those products that improved model predictions of the target variables and how the model performance varied through the year for those combinations. We found that an ensemble size of 50 was sufficient for all products except the reservoir inflow, which required 100 members and that in situ products outperform satellite products when assimilated. In particular, potential evapotranspiration alone or as combinations with other products did not generally improve predictions of our target variables. However, assimilating combinations of the snow products, discharge and local reservoir without evapotranspiration products improved the model performance.

scholarly journals Prototype Spatio-temporal Predictive System of pest development of the codling moth, Cydia pomonella, in Kazakhstan

2020 ◽  
Vol 13 (1) ◽  
pp. 1-12
Author(s):  
A. Afonin ◽  
B. Kopzhassarov ◽  
E. Milyutina ◽  
E. Kazakov ◽  
A. Sarbassova ◽  
...  
Keyword(s):  
Land Surface ◽  
Cydia Pomonella ◽  
Codling Moth ◽  
Moth Population ◽  
Development Stages ◽  
In Situ Data ◽  
Weather Stations ◽  
Spatio Temporal ◽  
Accumulated Degree Days

SummaryA prototype for pest development stages forecasting is developed in Kazakhstan exploiting data from the geoinformation technologies and using codling moth as a model pest in apples. The basic methodology involved operational thermal map retrieving based on MODIS land surface temperature products and weather stations data, their recalculation into accumulated degree days maps and then into maps of the phases of the codling moth population dynamics. The validation of the predicted dates of the development stages according to the in-situ data gathered in the apple orchards showed a good predictivity of the forecast maps. Predictivity of the prototype can be improved by using daily satellite sensor datasets and their calibration with data received from a network of weather stations installed in the orchards.

scholarly journals An update to the traditional water mass (trans)formation framework.

2021 ◽  
Author(s):  
Aqeel Piracha ◽  
Antonio Turiel ◽  
Estrella Olmedo ◽  
Marcos Portabella
Keyword(s):  
Water Mass ◽  
Deep Convection ◽  
Sea Surface ◽  
Future Directions ◽  
In Situ Data ◽  
Water Mass Formation ◽  
Alternative Approach ◽  
Spatio Temporal ◽  
Ocean Convection

<p>Traditional estimates of convection/water mass formation at the sea surface rely on measurements of air-sea fluxes of heat and freshwater<br>(evaporation minus precipitation), that are estimated by combining in-situ data with meteorological modelisation. Satellite-based estimates of ocean convection are thus largely impacted by the relatively high uncertainties and low space-time resolution of those fluxes. However, direct satellite measurements of the ocean surface offer a unique opportunity to study convection (upwelling, downwelling) events with unprecedented spatio-temporal resolution compared to in-situ measurements. In this work, we propose an alternative approach to the traditional framework for estimating ocean convection using satellites. Instead of combining high-resolution ocean data of sea surface temperature and salinity with the much less precise, less resolved air-sea interaction data, we estimate the air-sea fluxes by computing the material derivatives (using satellite ocean currents) of the satellite sea surface variables. We therefore obtain estimates at the same resolution of the satellite products, and with much better accuracy than what was estimated before. We present some examples of application in the Atlantic ocean and in the Mediterranean sea. Future directions of this work is the study of the seasonal and interannual variability of ocean convection, and the potential changes on deep convection associated to climate variability at different time scales.</p>

Validation studies of EUMETSAT's active fire monitoring product over Turkey

2009 ◽  
Vol 18 (5) ◽  
pp. 517 ◽  
Author(s):  
Ahmet Emre Tekeli ◽  
İbrahim Sönmez ◽  
Erdem Erdi ◽  
Fatih Demir
Keyword(s):  
Temporal Distribution ◽  
Fire Detection ◽  
Burnt Area ◽  
Pixel Resolution ◽  
European Organization ◽  
Fire Monitoring ◽  
In Situ Data ◽  
Active Fire ◽  
Spatio Temporal

Fire detection and monitoring are challenging tasks that require continuous, early and quick responses that are as accurate as possible. Satellite-based systems are indispensable tools for operational and research agencies to accomplish such a demanding task. The frequent and continuous imagery capability of the geostationary satellites makes them the best candidate for early fire detection systems. The main purpose of the present paper is to analyze the spatio-temporal distribution of active fire monitoring (FIR) products of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT)’s Meteosat Second Generation (MSG) satellite with in situ data for the summer of 2006 over Turkey. In situ data were obtained from the fire reports of the Ministry of Environment and Forestry, Turkey. The main shortcomings of the MSG active fire monitoring product validation arise from the pixel resolution and fire coverage, which are examined on the basis of some recent examples. The diurnal cycle of active fires identified well with the product. The burnt area effects on the accuracy of hit ratios were also analyzed. It is seen that the possibility for the fire to be detected by MSG increases with increasing burnt area. Even with the present anomalies, remote sensing may provide a consistent systematic way of monitoring fires, removing human biases and enabling a long-term dataset, which has been a goal of Global Observation of Forest and Land Cover Dynamics (GOFC/GOLD).

scholarly journals Data assimilation of in-situ and satellite remote sensing data to 3D hydrodynamic lake models

2019 ◽  
Author(s):  
Theo Baracchini ◽  
Philip Yifei Chu ◽  
Jonas Šukys ◽  
Gian Lieberherr ◽  
Stefan Wunderle ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Assimilation ◽  
Satellite Remote Sensing ◽  
Three Dimensional ◽  
Model Performance ◽  
Remote Sensing Data ◽  
Temporal Scales ◽  
Localization Scheme ◽  
Spatio Temporal

Abstract. The understanding of lakes physical dynamics is crucial to provide scientifically credible information for ecosystem management. We show how the combination of in-situ data, remote sensing observations and three-dimensional hydrodynamic numerical simulations is capable of delivering various spatio-temporal scales involved in lakes dynamics. This combination is achieved through data assimilation (DA) and uncertainty quantification. In this study, we present a flexible framework for DA into lakes three-dimensional hydrodynamic models. Using an Ensemble Kalman Filter, our approach accounts for model and observational uncertainties. We demonstrate the framework by assimilating in-situ and satellite remote sensing temperature data into a three-dimensional hydrodynamic model of Lake Geneva. Results show that DA effectively improves model performance over a broad range of spatio-temporal scales and physical processes. Overall, temperature errors have been reduced by 54 %. With a localization scheme, an ensemble size of 20 members is found to be sufficient to derive covariance matrices leading to satisfactory results. The entire framework has been developed for the constraints of operational systems and near real-time operations (e.g. integration into http://meteolakes.ch).

scholarly journals Coupling bioturbation activity to metal (Fe and Mn) profiles in situ

2013 ◽  
Vol 10 (4) ◽  
pp. 2365-2378 ◽  
Author(s):  
L. R. Teal ◽  
E. R. Parker ◽  
M. Solan
Keyword(s):  
Statistical Modelling ◽  
Time Lapse ◽  
Simulation Modelling ◽  
Sediment Profile ◽  
Infaunal Community ◽  
In Situ Data ◽  
Fe And Mn ◽  
Spatio Temporal ◽  
Mechanistic Basis

Abstract. The relative contributions that species assemblages, abiotic variables, and their interactions with one another make to ecosystem properties are recognised but are seldom considered simultaneously, within context, and at the appropriate spatio-temporal scales. Here, we combine fluorescent time-lapse sediment profile imaging (f-SPI) and diffusion gradient thin gels (DGT) to examine, in situ, the link between an important benthic ecosystem process (bioturbation) and the availability (profiles) of Fe and Mn. Whilst the combination of these methodologies (fg-SPI) was successful in gathering high-resolution in situ data of bioturbation activity and Fe/Mn profiles simultaneously, we show that the mechanistic basis of how the infaunal community mediate Fe and Mn is difficult to reconcile because of the spatio-temporal differences between particle and porewater mixing. This mismatch means that the consideration of these mechanistic processes in isolation is likely to limit our interpretative capacity of how infaunal communities mediate various biogeochemical processes in the natural environment. Moreover, the combination of multiple technologies, process based simulation modelling and generalised additive statistical modelling achieved here, emphasises the importance of simultaneously considering additional factors that influence benthic chemistry, in particular bioirrigation and tidal flushing of the sediment profile. Our findings highlight a pressing need to determine how the relative importance of multiple abiotic and biotic factors act in concert to alter major biogeochemical pathways across a variety of contexts and habitats.

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