Soil Moisture: From Observations to Reanalysis and Remote Sensing

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Soil and Hydrology".

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 3387

Special Issue Editors


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Guest Editor
Department of Geography, Maynooth University, Maynooth, Co. Kildare, Ireland
Interests: hydrology; remote sensing; modeling; extreme events; precipitation; soil moisture

E-Mail Website
Guest Editor
Department of Water Resources Research, Water Research Institute, Tehran, Iran
Interests: remote sensing; climate change; natural hazard; soil moisture; evapotranspiration; dust storms; glaciers

Special Issue Information

Dear Colleagues,

I am editing a special issues for open-access MDPI journal Hydrology. The topic is “Soil moisture: From observations to reanalysis and remote sensing”.

Besides other variables such as precipitation, vegetation, Evapotranspiration and streamflow, soil moisture (SM) is an important variable in land surface hydrology which governs the partitioning of the mass and energy fluxes between the land and the atmosphere. Soil moisture is an important variable for agriculture, drought and flood monitoring and assessment, numerical weather prediction, soil erosion and slope failure, reservoir management, geotechnical engineering, water quality and landslide modeling.

However observations of soil moisture at point scale are very sparse and observing networks are expensive to maintain. Reanalysis data from land-surface models and remote sensing data can provide measurements at large scales. Remote sensing techniques are based on active and passive microwave-based products but different bands of electromagnetic spectrum can be used in this regard.

Hydrological and land surface models differ with respect to the spatial (horizontal and vertical) and temporal discretization, to the simulated physical processes and to the corresponding parameterization. The quality of input meteorological inputs and accuracy of the models and their structure and parametrization plays important role in simulation of soil moisture.

Different researches/studies on soil moisture content, from ground measurements and measuring networks to developing new models/sensors for reanalysis and remote sensing soil moisture measurements are welcome to be submitted in this special issue. Application of present soil moisture data and products, their intercomparison and downscaling methods to refine the spatial/temporal resolution of soil moisture data are also welcomed.

With your distinguished expertise in this area, I hereby invite you to submit a paper to these special issues.

Dr. Saeed Golian
Dr. Neamat Karimi
Guest Editors

Manuscript Submission Information

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Keywords

  • Soil moisture
  • Observation
  • Remote sensing
  • Reanalysis
  • Downscaling

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Published Papers (1 paper)

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Research

19 pages, 941 KiB  
Article
Analysis of the 2014 Wet Extreme in Bulgaria: Anomalies of Temperature, Precipitation and Terrestrial Water Storage
by Biliana Mircheva, Milen Tsekov, Ulrich Meyer and Guergana Guerova
Hydrology 2020, 7(3), 66; https://doi.org/10.3390/hydrology7030066 - 9 Sep 2020
Viewed by 2748
Abstract
Impact on the hydrology cycle is projected to be one of the most noticeable consequences of climate change. An increase in regional dry and wet extremes has already been observed, resulting in large socioeconomic losses. The 2014 wet conditions in Bulgaria present a [...] Read more.
Impact on the hydrology cycle is projected to be one of the most noticeable consequences of climate change. An increase in regional dry and wet extremes has already been observed, resulting in large socioeconomic losses. The 2014 wet conditions in Bulgaria present a valuable case study for analyzing the interaction between multiple drivers that are essential for early forecasting and warning of flood events. In this paper, time series analysis of temperature, precipitation and Terrestrial Water Storage Anomaly (TWSA) is performed and cross-correlations between observations and climate variability indices are computed for a 12-year period. In Bulgaria, a positive linear temperature trend was found with precipitation and TWSA exhibiting negative trends for the period 2003–2014. The year 2014 started with a drier and warmer than usual winter followed by five consecutive wet months from March to July. We found the following long-term variations: (1) temperature showing a local minimum in November 2014, (2) precipitation peaks in July 2014 and (3) a local TWSA maximum in December 2014. Over a 12-year period, weak to moderate negative correlations were observed between the long-term components of temperature, precipitation and TWSA. Moderate positive correlations with a 3 to 6-month lag were obtained between precipitation and TWSA long-term components. The long-term trends of temperature and precipitation from surface observations and atmospheric reanalysis showed very good alignment. Very large subseasonal precipitation residuals from observations and atmospheric reanalysis were obtained for April and September 2014. Two oscillation indices showed: (1) weak correlations with precipitation and (2) weak to moderate correlations with TWSA. Full article
(This article belongs to the Special Issue Soil Moisture: From Observations to Reanalysis and Remote Sensing)
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