Agricultural water use represents more than 70% of the world’s freshwater through irrigation wate... more Agricultural water use represents more than 70% of the world’s freshwater through irrigation water inputs that are poorly known at the field scale. Irrigation monitoring is thus an important issue for optimizing water use in particular with regards to the water scarcity that the semi-arid regions are already facing. In this context, the aim of this study is to develop and evaluate a new approach to predict seasonal to daily irrigation timing and amounts at the field scale. The method is based on surface soil moisture (SSM) data assimilated into a simple land surface (FAO-56) model through a particle filter technique based on an ensemble of irrigation scenarios. The approach is implemented in three steps. First, synthetic experiments are designed to assess the impact of the frequency of observation, the errors on SSM and the a priori constraints on the irrigation scenarios for different irrigation techniques (flooding and drip). In a second step, the method is evaluated using in situ...
Over semi-arid agricultural areas, the surface energy balance and its components are largely depe... more Over semi-arid agricultural areas, the surface energy balance and its components are largely dependent on the soil water availability. In such conditions, the land surface temperature (LST) retrieved from the thermal bands has been commonly used to represent the high spatial variability of the surface evaporative fraction and associated fluxes. In contrast, however, the soil moisture (SM) retrieved from microwave data has rarely been used thus far due to the unavailability of high-resolution (field scale) SM products until recent times. Soil evaporation is controlled by the surface SM. Moreover, the surface SM dynamics is temporally related to root zone SM, which provides information about the water status of plants. The aim of this work was to assess the gain in terms of flux estimates when integrating microwave-derived SM data in a thermal-based energy balance model at the field scale. In this study, SM products were derived from three different methodologies: the first approach i...
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
The soil evaporation is under atmospheric conditions non-limited in energy-strongly linked to the... more The soil evaporation is under atmospheric conditions non-limited in energy-strongly linked to the near-surface soil moisture sensed by microwave radiometers. This has been the rationale for developing the DisPATCh (Disaggregation based on Physical And Theoretical scale Change) method, which relies on thermal-derived evaporation to improve the spatial resolution of SMOS (Soil Moisture and Ocean Salinity) like data. In practice, the disaggregation scheme estimates the 0–5 cm soil moisture at 1 km resolution by combining 40 km SMOS soil moisture, 1 km resolution MODIS (MODerate resolution Imaging Spectroradiometer) data, and a multi-scale soil evaporation model. This paper provides an overview of 1) the current status and main assumptions of DisPATCh, 2) the DisPATCh-based processor implemented in the Centre Aval de Traitement des Données SMOS (CATDS), and 3) related ongoing research including advanced modeling of soil evaporation and the prospect of coupling thermal- and radar-based s...
<p>In the south Mediterranean region already facing water scarcity, up to 80% of available ... more <p>In the south Mediterranean region already facing water scarcity, up to 80% of available water is used by irrigated agriculture. This work focuses on the analysis of the C-band response of a tree crop with in situ data acquired with a time step of 15 mns in the final objective of developing water stress detection approaches based on radar data. Focus is put on the daily cycle of the radar-backscattering coefficient and of the interferometric coherence. The site is located in the Chichaoua region (Morocco) was equipped in May 2019 with 6 C-band radar antennas installed on a 20 m tower. In parallel, automatic acquisitions at a half hourly time step of latent and sensible heat fluxes, sapflow, soil moisture and temperature profile together with manual &#160;measurements of LAI, soil roughness and above ground biomass every 15 days were carried out. The preliminary results show a strong daily cycle of the interferometric coherence with a significant drop of the coherence during daytime. The coherence loss at dawn occurred concurrently with the start of the sapflow while minimum values were observed in the afternoon when wind speed is maximum. A significant daily cycle of the backscattering coefficient is also prominent. The amplitude of the daily cycle decreased from the dormancy period in winter from up to 2dB to less than 1dB in summer when physiologic activity of the trees is at its maximum. These first results open perspectives for the monitoring of the hydric status of crops within the frame of future radar missions in geostationary orbit.</p>
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
Optimizing irrigation (timing and amount) is a worldwide requirement for water resource managemen... more Optimizing irrigation (timing and amount) is a worldwide requirement for water resource management, especially in semi-arid regions suffering already from limited water supply. In this study, an approach for estimating daily to seasonal irrigation amount is developed. The approach assimilates the surface soil moisture (SSM) estimated from Sentinel-1 radar data using a particle filter algorithm into the FAO-56 double coefficient model. The approach is tested over a drip irrigated wheat field located in the center of Morocco during two successive growing seasons. It is evaluated using in situ SSM measurements and using Sentinel-1 SSM products. Assimilation of Sentinel-1 SSM products, available every 6 days, yielded accurate irrigation estimates. The seasonal amounts are estimated with a maximum difference of 28 mm (8%) and 15-days cumulative irrigation amounts are reasonable with R=0.64, RMSE=28.78 mm and bias=1.99 mm.
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
Surface soil moisture (SM) is an essential component for crop water stress detection and irrigati... more Surface soil moisture (SM) is an essential component for crop water stress detection and irrigation management. It controls soil evaporation and plant transpiration. SM dynamics is temporally related to root zone soil moisture which is the primary measure of the plant's water status. The aim of this work is to assess the robustness of high-resolution SM product derived from remote sensing on the energy balance based latent and sensible heat fluxes. Radar SM products retrieved from Sentinel-1 data only combined with Landsat Normalized Difference Vegetation index and land surface temperature are used together to feed the energy balance model TSEB-SM to estimate turbulent fluxes. The model estimates have been evaluated against the Eddy-covariance measurements over an irrigated wheat field situated in the Haouz plain in the center of Morocco. The results are very encouraging, with few observed anomalies meanly linked to the retrieved Priestley Taylor coefficient that is affected by SM.
In this study, a simple model, based on a light-use-efficiency model, was developed in order to e... more In this study, a simple model, based on a light-use-efficiency model, was developed in order to estimate growth and yield of the irrigated winter wheat under semi-arid conditions. The originality of the proposed method consists in (1) the modifying of the expression of the conversion coefficient (εconv) by integrating an appropriate stress threshold (ksconv) for triggering irrigation, (2) the substitution of the product of the two maximum coefficients of interception (εimax) and conversion (εconv_max) by a single parameter εmax, (3) the modeling of εmax as a function of the Cumulative Growing Degree Days (CGDD) since sowing date, and (4) the dynamic expression of the harvest index (HI) as a function of the CGDD and the final harvest index (HI0) depending on the maximum value of the Normalized Difference Vegetation Index (NDVI). The calibration and validation of the proposed model were performed based on the observations of wheat dry matter (DM) and grain yield (GY) which were collec...
&amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;Irrigation is the largest consumer of water in t... more &amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;Irrigation is the largest consumer of water in the world, with more than 70% of the world&amp;amp;amp;#39;s fresh water dedicated to agriculture. In this context, we developed and evaluated a new method to predict daily to seasonal irrigation timing and amounts at the field scale using surface soil moisture (SSM) data assimilated into a simple&amp;amp;amp;amp;amp;#160; land surface model through a particle filter technique. The method is first tested using in situ SSM before using SSM products retrieved from Sentinel-1. Data collected on different wheat fields grown &amp;amp;amp;amp;amp;#160;in Morocco, for both flood and drip irrigation techniques, are used to assess the performance of the proposed method. With in situ data, the results are good. Seasonal amounts are retrieved with R &amp;amp;amp;amp;gt; 0.98, RMSE &amp;amp;amp;amp;lt;42 mm and bias&amp;amp;amp;amp;lt;2 mm. Likewise, a good agreement is observed at the daily scale for flood irrigation where more than 70% of the irrigation events are detected with a time difference from actual irrigation events shorter than 4 days, when assimilating SSM observation every 6 days to mimics Sentinel-1 revisit time. Over the drip irrigated fields, the statistical metrics are R = 0.70, RMSE =28.5 mm and bias= -0.24 mm for irrigation amounts cumulated over 15 days. The approach is then evaluated using SSM products derived from Sentinel-1 data; statistical metrics are R= 0.64, RMSE= 28.78 mm and bias = 1.99 mm for irrigation amounts cumulated over 15 days. In addition to irrigated fields, the applicationof the developed methodover rainfed fieldsdid not detect any irrigation. This study opens perspectives for the regional retrieval of irrigation amounts and timing at the field scale and for mapping irrigated/non irrigated areas.&amp;amp;amp;amp;lt;/p&amp;amp;amp;amp;gt;
&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp... more &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;Over semi-arid agricultural regions, detecting the crop water need at the onset of water stress is of paramount importance for optimizing the use of irrigation water. Evapotranspiration (ET) is a crucial component of the water cycle, it strongly impacts the water resource management, drought monitoring, and climate. Remote sensing observations provide very relevant information to feed ET models. In particular, the microwave-derived surface (0-5 cm) soil moisture (SM), which is the main controlling factor of soil evaporation, the visible/near-infratred-derived vegetation cover fraction (fc), which provides an essential structural constraint on the fractioning between vegetation transpiration and soil evaporation, and - thermal-derived land surface temperature (LST), which is a signature of both available energy and evapotranspiration (ET) rate. The aim of this work is to integrate those independent and complementary information on total ET within an energy balance model. As a state-of-the-art and commonly used model, we chose the TSEB modelling as a basis for developments. An innovative calibration procedure is proposed to retrieve the main parameters of soil evaporation (soil resistance, r&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;ss&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;) and plant transpiration (Priestly Taylor coefficient, &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#945;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;PT&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;) based on a threshold on fc. The procedure is applied over an irrigated wheat field in the Tensift basin, central Morocco. Overall, the coupling of the soil resistance formulation with the TSEB formalism improves the estimation of soil evaporation, and consequently, improves the partitioning of ET. Analysis of the retrieved time series indicates that the daily &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#945;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;PT&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; mainly follows the phenology of winter wheat crop with a maximum value coincident with the full development of green biomass and a minimum value reached at harvest. The temporal variations of &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#945;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;PT&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; before senescence are attributed to the dynamics of both the root zone soil moisture and the amount of green biomass.&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;
Agricultural water use represents more than 70% of the world’s freshwater through irrigation wate... more Agricultural water use represents more than 70% of the world’s freshwater through irrigation water inputs that are poorly known at the field scale. Irrigation monitoring is thus an important issue for optimizing water use in particular with regards to the water scarcity that the semi-arid regions are already facing. In this context, the aim of this study is to develop and evaluate a new approach to predict seasonal to daily irrigation timing and amounts at the field scale. The method is based on surface soil moisture (SSM) data assimilated into a simple land surface (FAO-56) model through a particle filter technique based on an ensemble of irrigation scenarios. The approach is implemented in three steps. First, synthetic experiments are designed to assess the impact of the frequency of observation, the errors on SSM and the a priori constraints on the irrigation scenarios for different irrigation techniques (flooding and drip). In a second step, the method is evaluated using in situ...
Over semi-arid agricultural areas, the surface energy balance and its components are largely depe... more Over semi-arid agricultural areas, the surface energy balance and its components are largely dependent on the soil water availability. In such conditions, the land surface temperature (LST) retrieved from the thermal bands has been commonly used to represent the high spatial variability of the surface evaporative fraction and associated fluxes. In contrast, however, the soil moisture (SM) retrieved from microwave data has rarely been used thus far due to the unavailability of high-resolution (field scale) SM products until recent times. Soil evaporation is controlled by the surface SM. Moreover, the surface SM dynamics is temporally related to root zone SM, which provides information about the water status of plants. The aim of this work was to assess the gain in terms of flux estimates when integrating microwave-derived SM data in a thermal-based energy balance model at the field scale. In this study, SM products were derived from three different methodologies: the first approach i...
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
The soil evaporation is under atmospheric conditions non-limited in energy-strongly linked to the... more The soil evaporation is under atmospheric conditions non-limited in energy-strongly linked to the near-surface soil moisture sensed by microwave radiometers. This has been the rationale for developing the DisPATCh (Disaggregation based on Physical And Theoretical scale Change) method, which relies on thermal-derived evaporation to improve the spatial resolution of SMOS (Soil Moisture and Ocean Salinity) like data. In practice, the disaggregation scheme estimates the 0–5 cm soil moisture at 1 km resolution by combining 40 km SMOS soil moisture, 1 km resolution MODIS (MODerate resolution Imaging Spectroradiometer) data, and a multi-scale soil evaporation model. This paper provides an overview of 1) the current status and main assumptions of DisPATCh, 2) the DisPATCh-based processor implemented in the Centre Aval de Traitement des Données SMOS (CATDS), and 3) related ongoing research including advanced modeling of soil evaporation and the prospect of coupling thermal- and radar-based s...
<p>In the south Mediterranean region already facing water scarcity, up to 80% of available ... more <p>In the south Mediterranean region already facing water scarcity, up to 80% of available water is used by irrigated agriculture. This work focuses on the analysis of the C-band response of a tree crop with in situ data acquired with a time step of 15 mns in the final objective of developing water stress detection approaches based on radar data. Focus is put on the daily cycle of the radar-backscattering coefficient and of the interferometric coherence. The site is located in the Chichaoua region (Morocco) was equipped in May 2019 with 6 C-band radar antennas installed on a 20 m tower. In parallel, automatic acquisitions at a half hourly time step of latent and sensible heat fluxes, sapflow, soil moisture and temperature profile together with manual &#160;measurements of LAI, soil roughness and above ground biomass every 15 days were carried out. The preliminary results show a strong daily cycle of the interferometric coherence with a significant drop of the coherence during daytime. The coherence loss at dawn occurred concurrently with the start of the sapflow while minimum values were observed in the afternoon when wind speed is maximum. A significant daily cycle of the backscattering coefficient is also prominent. The amplitude of the daily cycle decreased from the dormancy period in winter from up to 2dB to less than 1dB in summer when physiologic activity of the trees is at its maximum. These first results open perspectives for the monitoring of the hydric status of crops within the frame of future radar missions in geostationary orbit.</p>
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
Optimizing irrigation (timing and amount) is a worldwide requirement for water resource managemen... more Optimizing irrigation (timing and amount) is a worldwide requirement for water resource management, especially in semi-arid regions suffering already from limited water supply. In this study, an approach for estimating daily to seasonal irrigation amount is developed. The approach assimilates the surface soil moisture (SSM) estimated from Sentinel-1 radar data using a particle filter algorithm into the FAO-56 double coefficient model. The approach is tested over a drip irrigated wheat field located in the center of Morocco during two successive growing seasons. It is evaluated using in situ SSM measurements and using Sentinel-1 SSM products. Assimilation of Sentinel-1 SSM products, available every 6 days, yielded accurate irrigation estimates. The seasonal amounts are estimated with a maximum difference of 28 mm (8%) and 15-days cumulative irrigation amounts are reasonable with R=0.64, RMSE=28.78 mm and bias=1.99 mm.
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
Surface soil moisture (SM) is an essential component for crop water stress detection and irrigati... more Surface soil moisture (SM) is an essential component for crop water stress detection and irrigation management. It controls soil evaporation and plant transpiration. SM dynamics is temporally related to root zone soil moisture which is the primary measure of the plant's water status. The aim of this work is to assess the robustness of high-resolution SM product derived from remote sensing on the energy balance based latent and sensible heat fluxes. Radar SM products retrieved from Sentinel-1 data only combined with Landsat Normalized Difference Vegetation index and land surface temperature are used together to feed the energy balance model TSEB-SM to estimate turbulent fluxes. The model estimates have been evaluated against the Eddy-covariance measurements over an irrigated wheat field situated in the Haouz plain in the center of Morocco. The results are very encouraging, with few observed anomalies meanly linked to the retrieved Priestley Taylor coefficient that is affected by SM.
In this study, a simple model, based on a light-use-efficiency model, was developed in order to e... more In this study, a simple model, based on a light-use-efficiency model, was developed in order to estimate growth and yield of the irrigated winter wheat under semi-arid conditions. The originality of the proposed method consists in (1) the modifying of the expression of the conversion coefficient (εconv) by integrating an appropriate stress threshold (ksconv) for triggering irrigation, (2) the substitution of the product of the two maximum coefficients of interception (εimax) and conversion (εconv_max) by a single parameter εmax, (3) the modeling of εmax as a function of the Cumulative Growing Degree Days (CGDD) since sowing date, and (4) the dynamic expression of the harvest index (HI) as a function of the CGDD and the final harvest index (HI0) depending on the maximum value of the Normalized Difference Vegetation Index (NDVI). The calibration and validation of the proposed model were performed based on the observations of wheat dry matter (DM) and grain yield (GY) which were collec...
&amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;Irrigation is the largest consumer of water in t... more &amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;Irrigation is the largest consumer of water in the world, with more than 70% of the world&amp;amp;amp;#39;s fresh water dedicated to agriculture. In this context, we developed and evaluated a new method to predict daily to seasonal irrigation timing and amounts at the field scale using surface soil moisture (SSM) data assimilated into a simple&amp;amp;amp;amp;amp;#160; land surface model through a particle filter technique. The method is first tested using in situ SSM before using SSM products retrieved from Sentinel-1. Data collected on different wheat fields grown &amp;amp;amp;amp;amp;#160;in Morocco, for both flood and drip irrigation techniques, are used to assess the performance of the proposed method. With in situ data, the results are good. Seasonal amounts are retrieved with R &amp;amp;amp;amp;gt; 0.98, RMSE &amp;amp;amp;amp;lt;42 mm and bias&amp;amp;amp;amp;lt;2 mm. Likewise, a good agreement is observed at the daily scale for flood irrigation where more than 70% of the irrigation events are detected with a time difference from actual irrigation events shorter than 4 days, when assimilating SSM observation every 6 days to mimics Sentinel-1 revisit time. Over the drip irrigated fields, the statistical metrics are R = 0.70, RMSE =28.5 mm and bias= -0.24 mm for irrigation amounts cumulated over 15 days. The approach is then evaluated using SSM products derived from Sentinel-1 data; statistical metrics are R= 0.64, RMSE= 28.78 mm and bias = 1.99 mm for irrigation amounts cumulated over 15 days. In addition to irrigated fields, the applicationof the developed methodover rainfed fieldsdid not detect any irrigation. This study opens perspectives for the regional retrieval of irrigation amounts and timing at the field scale and for mapping irrigated/non irrigated areas.&amp;amp;amp;amp;lt;/p&amp;amp;amp;amp;gt;
&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp... more &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;Over semi-arid agricultural regions, detecting the crop water need at the onset of water stress is of paramount importance for optimizing the use of irrigation water. Evapotranspiration (ET) is a crucial component of the water cycle, it strongly impacts the water resource management, drought monitoring, and climate. Remote sensing observations provide very relevant information to feed ET models. In particular, the microwave-derived surface (0-5 cm) soil moisture (SM), which is the main controlling factor of soil evaporation, the visible/near-infratred-derived vegetation cover fraction (fc), which provides an essential structural constraint on the fractioning between vegetation transpiration and soil evaporation, and - thermal-derived land surface temperature (LST), which is a signature of both available energy and evapotranspiration (ET) rate. The aim of this work is to integrate those independent and complementary information on total ET within an energy balance model. As a state-of-the-art and commonly used model, we chose the TSEB modelling as a basis for developments. An innovative calibration procedure is proposed to retrieve the main parameters of soil evaporation (soil resistance, r&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;ss&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;) and plant transpiration (Priestly Taylor coefficient, &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#945;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;PT&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;) based on a threshold on fc. The procedure is applied over an irrigated wheat field in the Tensift basin, central Morocco. Overall, the coupling of the soil resistance formulation with the TSEB formalism improves the estimation of soil evaporation, and consequently, improves the partitioning of ET. Analysis of the retrieved time series indicates that the daily &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#945;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;PT&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; mainly follows the phenology of winter wheat crop with a maximum value coincident with the full development of green biomass and a minimum value reached at harvest. The temporal variations of &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#945;&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;PT&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/sub&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt; before senescence are attributed to the dynamics of both the root zone soil moisture and the amount of green biomass.&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;
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