scholarly journals Evapotranspiration from Remote Sensing to Improve the Swat Model in Eastern Amazonia

2015 ◽  
Vol 22 (4) ◽  
pp. 456-464 ◽  
Author(s):  
Adriano Marlison Leão de Sousa ◽  
Maria Isabel Vitorino ◽  
Nilza Maria dos Reis Castro ◽  
Marcel do Nascimento Botelho ◽  
Paulo Jorge Oliveira Ponte de Souza
Keyword(s):  
Hydrological Modeling ◽  
Swat Model ◽  
Assessment Tools ◽  
Flow Data ◽  
Remote Sensors ◽  
Araguaia River ◽  
Moderate Resolution ◽  
Model Adjustment ◽  
Daily Scale ◽  
Moderate Resolution Imaging Spectroradiometer

ABSTRACT In this study, we estimated the evapotranspiration from orbital images - MODIS (Moderate Resolution Imaging Spectroradiometer) for assimilation in the hydrological modeling of the SWAT (Soil Water Assessment Tools) model. The data used include the period between October 2003 and December 2006 of the sub-basin of the Lajeado River, located in the Tocantins-Araguaia River basin in Tocantins state. Overall, the results of the use of heat flows estimated by remote sensors in the SWAT model can be considered satisfactory. The values of the COE (coefficient of efficiency of Nash-Sutcliffe) ranged from -0.40 to 0.91 in the comparison with the daily flow data and from 0.17 to 0.77 with the monthly flow data, with the assimilation of evapotranspiration from orbital images. These results indicate benefit to the model adjustment due to improvement in the data assimilated of approximately 0.91 in the COE on daily scale and 0.60 in the CEO on monthly scale.

scholarly journals Evaluation of hydrological modeling using climatic station and gridded precipitation dataset

MAUSAM ◽  
2021 ◽  
Vol 71 (4) ◽  
pp. 717-728
Author(s):  
KHAN WISAL ◽  
KHAN ASIF ◽  
KHAN AFED ULLAH ◽  
KHAN MUJAHID
Keyword(s):  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Indus Basin ◽  
Gridded Data ◽  
Flow Data ◽  
Rainfall Events ◽  
Station Data ◽  
Measured Flow ◽  
Water Assessment

The conventional rainfall data estimates are relatively accurate at some points of the region. The interpolation of such type of data approximates the actual rainfield however in data scarce regions; the resulted rainfield is the rough estimate of the actual rainfall events. In data scarce regions like Indus basin Pakistan, the data obtained through remote sensing can be very useful. This research evaluates two types of gridded data i.e., European Reanalysis (ERA) interim and Japanese Reanalysis 55 years (JRA-55) along with the climatic station data for three small dams in Pakistan. Since no measured flow data is available at these dams, the nearest possible catchments where flow data is available are calibrated and the calibrated parameters of these catchments are then used in actual dams for simulating the flow from all the three types of data using Soil and Water Assessment Tool (SWAT). The results of the comparison of gridded and rainguage precipitation shows that gridded data highly overestimates the climatic station data. Similar results were observed in the comparison of flow simulated by SWAT model. The Peak flood calculated from JRA-55 overestimates while the Era-Interim peak floods are comparable to that of climatic stations in two of the three catchments.

scholarly journals Assessment of the aerosol optical depths measured by satellite-based passive remote sensors in the Alberta oil sands region

2017 ◽  
Vol 17 (3) ◽  
pp. 1931-1943 ◽  
Author(s):  
Christopher E. Sioris ◽  
Chris A. McLinden ◽  
Mark W. Shephard ◽  
Vitali E. Fioletov ◽  
Ihab Abboud
Keyword(s):  
Oil Sands ◽  
Mass Density ◽  
Positive Trend ◽  
Remote Sensors ◽  
Mining Region ◽  
Alberta Oil Sands ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Along Track

Abstract. Several satellite aerosol optical depth (AOD) products are assessed in terms of their data quality in the Alberta oil sands region. The instruments consist of MODIS (Moderate Resolution Imaging Spectroradiometer), POLDER (Polarization and Directionality of Earth Reflectances), MISR (Multi-angle Imaging SpectroRadiometer), and AATSR (Advanced Along-Track Scanning Radiometer). The AOD data products are examined in terms of multiplicative and additive biases determined using local Aerosol Robotic Network (AERONET) (AEROCAN) stations. Correlation with ground-based data is used to assess whether the satellite-based AODs capture day-to-day, month-to-month, and spatial variability. The ability of the satellite AOD products to capture interannual variability is assessed at Albian mine and Shell Muskeg River, two neighbouring sites in the northern mining region where a statistically significant positive trend (2002–2015) in PM2.5 mass density exists. An increasing trend of similar amplitude (∼  5 % year−1) is observed in this northern mining region using some of the satellite AOD products.

Retrieval of Cirrus Microphysical Properties with a Suite of Algorithms for Airborne and Spaceborne Lidar, Radar, and Radiometer Data

2006 ◽  
Vol 45 (12) ◽  
pp. 1665-1689 ◽  
Author(s):  
Yuying Zhang ◽  
Gerald G. Mace
Keyword(s):  
Satellite Observation ◽  
Sensor Data ◽  
Regional Study ◽  
Remote Sensors ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Atmospheric Radiation Measurement ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Water

Abstract Algorithms are developed to convert data streams from multiple airborne and spaceborne remote sensors into layer-averaged cirrus bulk microphysical properties. Radiometers such as the Moderate-Resolution Imaging Spectroradiometer (MODIS) observe narrowband spectral radiances, and active remote sensors such as the lidar on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the millimeter radar on CloudSat will provide vertical profiles of attenuated optical backscatter and radar reflectivity. Equivalent airborne remote sensors are also routinely flown on the NASA WB-57F and ER-2 aircraft. Algorithms designed to retrieve cirrus microphysical properties from remote sensor data must be able to handle the natural variability of cirrus that can range from optically thick layers that cause lidar attenuation to tenuous layers that are not detected by the cloud radar. An approach that is adopted here is to develop an algorithm suite that has internal consistency in its formulation and assumptions. The algorithm suite is developed around a forward model of the observations and is inverted for layer-mean cloud properties using a variational technique. The theoretical uncertainty in the retrieved ice water path retrieval is 40%–50%, and the uncertainty in the layer-mean particle size retrieval ranges from 50% to 90%. Two case studies from the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) field campaign as well as ground-based cases from the Atmospheric Radiation Measurement Program (ARM) are used to show the efficacy and error characteristics of the algorithms.

scholarly journals Assessment of the aerosol optical depths measured by satellite-based passive remote sensors in the Alberta oil sands region

2016 ◽  
Author(s):  
Christopher E. Sioris ◽  
Chris A. McLinden ◽  
Mark W. Shephard ◽  
Vitali E. Fioletov ◽  
Ihab Abboud
Keyword(s):  
Oil Sands ◽  
Mass Density ◽  
Positive Trend ◽  
Remote Sensors ◽  
Mining Region ◽  
Alberta Oil Sands ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Along Track

Abstract. Several satellite aerosol optical depth (AOD) products are assessed in terms of their data quality in the Alberta oil sands region. The instruments consist of MODIS (Moderate resolution Imaging Spectroradiometer), POLDER (Polarization and Directionality of Earth Reflectances), MISR (Multi-angle Imaging SpectroRadiometer), and AATSR (Advanced Along-Track Scanning Radiometer). The AOD data products are examined in terms of multiplicative and additive biases determined using local AERONET (AEROCAN) stations. Correlation with ground-based data is used to assess whether the satellite-based AODs capture day-to-day, month-to-month, and spatial variability. The ability of the satellite AOD products to capture interannual variability is assessed at Albian Mine and Shell Muskeg River, two neighbouring sites in the northern mining region where a statistically significant positive trend (2002–2015) in PM2.5 mass density exists. An increasing trend of similar amplitude is observed in this northern mining region using some of the satellite AOD products.

scholarly journals Evaluation and Hydrological Utility of the GPM IMERG Precipitation Products over the Xinfengjiang River Reservoir Basin, China

2021 ◽  
Vol 13 (5) ◽  
pp. 866
Author(s):  
Xue Li ◽  
Yangbo Chen ◽  
Xincui Deng ◽  
Yueyuan Zhang ◽  
Lingfang Chen
Keyword(s):  
Hydrological Modeling ◽  
Assessment Tool ◽  
Southern China ◽  
Swat Model ◽  
Rain Gauge ◽  
Observation Data ◽  
Prediction Ability ◽  
River Reservoir ◽  
Daily Scale ◽  
Reservoir Basin

As a supplement to gauge observation data, many satellite observations have been used for hydrology and water resource research. This study aims to analyze the quality of the Integrated Multisatellite Retrieval for Global Precipitation Measurement (GPM IMERG) products and their hydrological utility in the Xinfengjiang River reservoir basin (XRRB), a mountainous region in southern China. The grid-based soil and water assessment tool (SWAT) model was used to construct a hydrological model of the XRRB based on two scenarios. The results showed that on a daily scale, the IMERG final run (FR) product was more accurate than the others, with Pearson’s correlation coefficients (CORR) of 0.61 and 0.71 on the grid accumulation scale and the average scale, respectively, and a relative bias (BIAS) of 0.01. In Scenario I (the SWAT model calibrated by rain gauge data), the IMERG-based simulation showed acceptable hydrologic prediction ability on the daily scale and satisfactory hydrological performance on the monthly scale. In Scenario II (the SWAT model calibrated by the FR), the hydrological performances of the FR on the daily and monthly scales were slightly better than those in Scenario I (the CORR was 0.64 and 0.85, the BIAS was 0.01 and −0.02, and the NSE was 0.43 and 0.84). These results showed the potential of the FR for hydrological modeling in tropical mountain watersheds in areas where information is scarce. This study is useful for hydrological, meteorological, and disaster studies in developing countries or remote areas with sparse or low-quality networks of ground-based observation stations.

scholarly journals Warm Island Effect in the Lake Region of the Tengger Desert Based on MODIS and Meteorological Station Data

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1157
Author(s):  
Nan Meng ◽  
Nai’ang Wang ◽  
Liqiang Zhao ◽  
Zhenmin Niu ◽  
Xiaoyan Liang ◽  
...  
Keyword(s):  
Land Surface ◽  
Tengger Desert ◽  
The North ◽  
Island Effect ◽  
Air Temperatures ◽  
Moderate Resolution ◽  
Daily Scale ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Annual Scale ◽  
The Tengger Desert

The northeastern part of the Tengger Desert accommodates several lakes. The effect of these lakes on local temperatures is unclear. In this study, the effects of the lakes were investigated using land surface temperature (LST) from MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2003 to 2018 and air temperatures from meteorological stations in 2017. LST and air temperatures are compared between the lake-group region and an area without lakes to the north using statistical methods. Our results show that the lake-group region is found to exhibit a warm island effect in winter on an annual scale and at night on a daily scale. The warm island effect is caused by the differing properties of the land and other surfaces. Groundwater may also be an important heat source. The results of this study will help in understanding the causative factors of warm island effects and other properties of lakes.

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

scholarly journals A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data

2021 ◽  
Vol 13 (15) ◽  
pp. 2895
Author(s):  
Maria Gavrouzou ◽  
Nikolaos Hatzianastassiou ◽  
Antonis Gkikas ◽  
Christos J. Lolis ◽  
Nikolaos Mihalopoulos
Keyword(s):  
Mediterranean Basin ◽  
Eastern Mediterranean ◽  
Mean Value ◽  
Early Spring ◽  
Dust Aerosol ◽  
Ozone Monitoring Instrument ◽  
Central Mediterranean ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.

scholarly journals 250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  
Keyword(s):  
Mixing Model ◽  
Blue Band ◽  
Aerosol Retrieval ◽  
Aerosol Distribution ◽  
Medium Resolution ◽  
Fine Spatial Resolution ◽  
Yearly Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

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