scholarly journals Quantifying river form variations in the Mississippi Basin using remotely sensed imagery

2014 ◽  
Vol 11 (3) ◽  
pp. 3599-3636 ◽  
Author(s):  
Z. F. Miller ◽  
T. M. Pavelsky ◽  
G. H. Allen

Abstract. Geographic variations in river form are often estimated using the framework of downstream hydraulic geometry (DHG), which links spatial changes in discharge to channel width, depth, and velocity through power-law models. These empirical relationships are derived from limited in situ data and do not capture the full variability in channel form. Here, we present a dataset of 1.2 × 106 river widths in the Mississippi Basin measured from the Landsat-derived National Land Cover Dataset that characterizes width variability observationally. We construct DHG for the Mississippi drainage by linking DEM-estimated discharge values to each width measurement. Well-developed DHG exists over the entire Mississippi Basin, though individual sub-basins vary substantially from existing width-discharge scaling. Comparison of depth predictions from traditional depth–discharge relationships with a new model incorporating width into the DHG framework shows that including width improves depth estimates by, on average, 24%. Results suggest that channel geometry derived from remotely sensed imagery better characterizes variability in river form than do the assumptions of DHG.

2014 ◽  
Vol 18 (12) ◽  
pp. 4883-4895 ◽  
Author(s):  
Z. F. Miller ◽  
T. M. Pavelsky ◽  
G. H. Allen

Abstract. Geographic variations in river form are often estimated using the framework of downstream hydraulic geometry (DHG), which links spatial changes in discharge to channel width, depth, and velocity through power-law models. These empirical relationships are developed from limited in situ data and do not capture the full variability in channel form. Here, we present a data set of 1.2 ×106 river widths in the Mississippi Basin measured from the Landsat-derived National Land Cover Dataset that characterizes width variability observationally. We construct DHG for the Mississippi drainage by linking digital elevation model (DEM)-estimated discharge values to each width measurement. Well-developed DHG exists over the entire Mississippi Basin, though individual sub-basins vary substantially from existing width–discharge scaling. Comparison of depth predictions from traditional depth–discharge relationships with a new model incorporating width into the DHG framework shows that including width improves depth estimates by, on average, 24%. Results suggest that channel geometry derived from remotely sensed imagery better characterizes variability in river form than do estimates based on DHG.


2008 ◽  
Vol 8 (1) ◽  
pp. 1549-1588 ◽  
Author(s):  
R. Macatangay ◽  
T. Warneke ◽  
C. Gerbig ◽  
S. Körner ◽  
R. Ahmadov ◽  
...  

Abstract. A framework that allows validating CO2 column averaged volume mixing ratios (VMRs) retrieved from ground-based solar absorption measurements using Fourier transform infrared spectrometry (FTS) against measurements made in-situ (such as from aircrafts and tall towers) has been developed. Since in-situ measurements are done frequently and at high accuracy on the global calibration scale, linking this scale with FTS total column retrievals ultimately provides a calibration scale for remote sensing. FTS, tower and aircraft data were analyzed from measurements during the CarboEurope Regional Experiment Strategy (CERES) from May to June 2005 in Biscarrosse, France. Carbon dioxide VMRs from the MetAir Dimona aircraft, the TM3 global transport model and Observations of the Middle Stratosphere (OMS) balloon based experiments were combined and integrated to compare with FTS measurements. The comparison agrees fairly well with differences resulting from the spatial variability of CO2 around the FTS as measured by the aircraft. Additionally, the Stochastic Time Inverted Lagrangian Transport (STILT) model served as a "transfer standard" between the in-situ data measured at a co-located tower and the remotely sensed data from the FTS. The variability of carbon dioxide VMRs was modeled well by STILT with differences coming partly from uncertainties in the spatial variation of carbon dioxide.


2018 ◽  
Vol 10 (11) ◽  
pp. 1772 ◽  
Author(s):  
Estrella Olmedo ◽  
Carolina Gabarró ◽  
Verónica González-Gambau ◽  
Justino Martínez ◽  
Joaquim Ballabrera-Poy ◽  
...  

This paper aims to present and assess the quality of seven years (2011–2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans ( 50 ∘ N– 90 ∘ N). The SMOS SSS maps presented in this work are an improved version of the preliminary three-year dataset generated and freely distributed by the Barcelona Expert Center. In this new version, a time-dependent bias correction has been applied to mitigate the seasonal bias that affected the previous SSS maps. An extensive database of in situ data (Argo floats and thermosalinograph measurements) has been used for assessing the accuracy of this product. The standard deviation of the difference between the new SMOS SSS maps and Argo SSS ranges from 0.25 and 0.35. The major features of the inter-annual SSS variations observed by the thermosalinographs are also captured by the SMOS SSS maps. However, the validation in some regions of the Arctic Ocean has not been feasible because of the lack of in situ data. In those regions, qualitative comparisons with SSS provided by models and the remotely sensed SSS provided by Aquarius and SMAP have been performed. Despite the differences between SMOS and SMAP, both datasets show consistent SSS variations with respect to the model and the river discharge in situ data, but present a larger dynamic range than that of the model. This result suggests that, in those regions, the use of the remotely sensed SSS may help to improve the models.


2017 ◽  
Vol 17 (15) ◽  
pp. 9379-9398 ◽  
Author(s):  
Karen E. Cady-Pereira ◽  
Vivienne H. Payne ◽  
Jessica L. Neu ◽  
Kevin W. Bowman ◽  
Kazuyuki Miyazaki ◽  
...  

Abstract. The Aura Tropospheric Emission Spectrometer (TES) is collecting closely spaced observations over 19 megacities. The objective is to obtain measurements that will lead to better understanding of the processes affecting air quality in and around these cities, and to better estimates of the seasonal and interannual variability. We explore the TES measurements of ozone, ammonia, methanol and formic acid collected around the Mexico City metropolitan area (MCMA) and in the vicinity of Lagos (Nigeria). The TES data exhibit seasonal signals that are correlated with Atmospheric Infrared Sounder (AIRS) CO and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD), with in situ measurements in the MCMA and with Goddard Earth Observing System (GEOS)-Chem model output in the Lagos area. TES was able to detect an extreme pollution event in the MCMA on 9 April 2013, which is also evident in the in situ data. TES data also show that biomass burning has a greater impact south of the city than in the caldera where Mexico City is located. TES measured enhanced values of the four species over the Gulf of Guinea south of Lagos. Since it observes many cities from the same platform with the same instrument and applies the same retrieval algorithms, TES data provide a very useful tool for easily comparing air quality measures of two or more cities. We compare the data from the MCMA and Lagos, and show that, while the MCMA has occasional extreme pollution events, Lagos consistently has higher levels of these trace gases.


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