Using High Spatio-Temporal Optical Remote Sensing to Monitor Dissolved Organic Carbon in the Arctic River Yenisei
نویسندگان
چکیده
In Arctic regions, a major concern is the release of carbon from melting permafrost that could greatly exceed current human carbon emissions. Arctic rivers drain these organic-rich watersheds (Ob, Lena, Yenisei, Mackenzie, Yukon) but field measurements at the outlets of these great Arctic rivers are constrained by limited accessibility of sampling sites. In particular, the highest dissolved organic carbon (DOC) fluxes are observed throughout the ice breakup period that occurs over a short two to three-week period in late May or early June during the snowmelt-generated peak flow. The colored fraction of dissolved organic carbon (DOC) which absorbs UV and visible light is designed as chromophoric dissolved organic matter (CDOM). It is highly correlated to DOC in large arctic rivers and streams, allowing for remote sensing to monitor DOC concentrations from satellite imagery. High temporal and spatial resolutions remote sensing tools are highly relevant for the study of DOC fluxes in a large Arctic river. The high temporal resolution allows for correctly assessing this highly dynamic process, especially the spring freshet event (a few weeks in May). The high spatial resolution allows for assessing the spatial variability within the stream and quantifying DOC transfer during the ice break period when the access to the river is almost impossible. In this study, we develop a CDOM retrieval algorithm at a high spatial and a high temporal resolution in the Yenisei River. We used extensive DOC and DOM spectral absorbance datasets from 2014 and 2015. Twelve SPOT5 (Take5) and Landsat 8 (OLI) images from 2014 and 2015 were examined for this investigation. Relationships between CDOM and spectral variables were explored using linear models (LM). Results demonstrated the capacity of a CDOM algorithm retrieval to monitor DOC fluxes in the Yenisei River during a whole open water season with a special focus on the peak flow period. Overall, future Sentinel2/Landsat8 synergies are promising to monitor DOC fluxes in Arctic rivers and advance our understanding of the Earth’s carbon cycle.
منابع مشابه
Spatio-temporal distribution of off-shore ships in the Pars Special Economic Energy Zone based on satellite imagery
Special Economic Zones (SEZs) are areas controlled by specific legislations so as toattain economic prosperity. These zones are commonly established and controlled bygovernment officials and are primarily characterized by growing population and developingtransport infrastructure. One relevant case is the Pars Special Economic Energy Zone(PSEEZ) situated in the south of Iran, on the northern sho...
متن کاملSpatio-temporal analysis of diurnal air temperature parameterization in Weather Stations over Iran
Diurnal air temperature modeling is a beneficial experimental and mathematical approach which can be used in many fields related to Geosciences. The modeling and spatio-temporal analysis of air Diurnal Temperature Cycle (DTC) was conducted using data obtained from 105 synoptic stations in Iran during the years 2013-2014 for the first time; the key variable for controlling the cosine term i...
متن کاملSpatio-temporal changes of water quality variables in a highly disturbed river
Quality of river varies widely depending on the land use in the catchment and environmental factors. Many rivers in developing countries are unhealthy because they contain harmful physical, chemical and biological agents. Zanjanrud River, located in Zanjan Province, Iran, where recently faced human intervention needs a regular monitoring from upstream to downstream for sustainable management. H...
متن کاملPan-Arctic distributions of continental runoff in the Arctic Ocean
Continental runoff is a major source of freshwater, nutrients and terrigenous material to the Arctic Ocean. As such, it influences water column stratification, light attenuation, surface heating, gas exchange, biological productivity and carbon sequestration. Increasing river discharge and thawing permafrost suggest that the impacts of continental runoff on these processes are changing. Here, a...
متن کاملComparative analysis of remote sensing water indexes for wetland water body monitoring using Landsat images and the Google Earth Engine Platform0 (A Case study: Meighan Wetland, Iran)
Wetlands are dynamic and complex aquatic ecosystems that play an important role in the survival of many plant and animal species. This study modeled the spatio-temporal changes of the Arak Meighan wetland during 1985–2020 using the multi-temporal Landsat images. In doing so, the applicability of different satellite-derived indexes including NDVI, NDWI, MNDWI, AWEIsh , AWEInsh , and WRI was inve...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 8 شماره
صفحات -
تاریخ انتشار 2016