scholarly journals Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study

Water ◽  
2017 ◽  
Vol 9 (11) ◽  
pp. 850 ◽  
Author(s):  
Alessandro Chiaudani ◽  
Diego Di Curzio ◽  
William Palmucci ◽  
Antonio Pasculli ◽  
Maurizio Polemio ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Central Italy ◽  
Alluvial Plain ◽  
Long Time Series ◽  
Long Time ◽  
Relationship Assessment

scholarly journals Long time series spatialized data for urban climatological studies: A case study of Paris, France

2020 ◽  
Vol 40 (7) ◽  
pp. 3567-3584
Author(s):  
Benjamin Le Roy ◽  
Aude Lemonsu ◽  
Raphaëlle Kounkou‐Arnaud ◽  
Denis Brion ◽  
Valéry Masson
Keyword(s):  
Time Series ◽  
Long Time Series ◽  
Long Time

scholarly journals Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study

2017 ◽  
Author(s):  
Alessandro Chiaudani ◽  
Diego Di Curzio ◽  
William Palmucci ◽  
Antonio Pasculli ◽  
Maurizio Polemio ◽  
...  
Keyword(s):  
Time Series ◽  
Central Italy ◽  
Field Work ◽  
Return Time ◽  
Rain Gauge ◽  
Level Gauge ◽  
Piezometric Level ◽  
River Level ◽  
Long Time Series ◽  
Long Time

In this research, univariate and bivariate statistical methods were applied to rainfall, river and piezometric level datasets belonging to 24 years long time series (1986-2009). These methods, that often are used to understand the effects of precipitation on rivers and karstic springs discharge, have been used to assess, piezometric level response to rainfall and river level fluctuations in a porous aquifer. A rain gauge, a river level gauge and three wells, located in Central Italy along the lower Pescara river valley in correspondence of its important alluvial aquifer, provided the data. The statistical analysis has been used within a known hydrogeological framework, which has been refined by mean of a photo-interpretation and a GPS survey. Water-groundwater relationships were identified following the autocorrelation and cross-correlation analyses; the spectral analysis and mono-fractal features of time series were assessed, in order to provide information on multy-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical-mathematical results were interpreted through field work that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.

scholarly journals Using long time series of Landsat data to monitor impervious surface dynamics: a case study in the Zhoushan Islands

2013 ◽  
Vol 7 (1) ◽  
pp. 073515 ◽  
Author(s):  
Xiaoping Zhang ◽  
Delu Pan ◽  
Jianyu Chen ◽  
Yuanzeng Zhan ◽  
Zhihua Mao
Keyword(s):  
Time Series ◽  
Impervious Surface ◽  
Landsat Data ◽  
Surface Dynamics ◽  
Long Time Series ◽  
Long Time

scholarly journals Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2174
Author(s):  
Lijian Shi ◽  
Sen Liu ◽  
Yingni Shi ◽  
Xue Ao ◽  
Bin Zou ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ocean Circulation ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Atmospheric Effects ◽  
Observation Data ◽  
Long Time Series ◽  
Ice Concentration ◽  
Long Time

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.

scholarly journals Performance stability of the MODIS and VIIRS LAI algorithms inferred from analysis of long time series of products

2021 ◽  
Vol 260 ◽  
pp. 112438
Author(s):  
Kai Yan ◽  
Jiabin Pu ◽  
Taejin Park ◽  
Baodong Xu ◽  
Yelu Zeng ◽  
...  
Keyword(s):  
Time Series ◽  
Long Time Series ◽  
Long Time
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