scholarly journals Technical Note: Comparing and ranking soil-moisture indices performance over Europe, through remote-sensing of vegetation

2009 ◽  
Vol 6 (5) ◽  
pp. 6247-6264 ◽  
Author(s):  
E. Peled ◽  
E. Dutra ◽  
P. Viterbo ◽  
A. Angert
Keyword(s):  
Soil Moisture ◽  
External Validation ◽  
Technical Note ◽  
Temperate Climate ◽  
Validation Dataset ◽  
Moisture Index ◽  
Analysis Technique ◽  
Global Soil ◽  
Soil Moisture Index

Abstract. Climate change induces long-term changes in soil-moisture. These changes can have important effects on the terrestrial biosphere, which can feedback into the climate system. In the past years there have been many attempts to produce and improve global soil-moisture datasets, however, comparing and validating these various datasets is not an easy task. Here, interannual variations in indices of soil moisture are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which soil moisture index provides the most reliable soil moisture representation. We showed that NDVI can be used as an external validation dataset to soil moisture indices, in areas that are classified as warm temperate climate with hot or warm dry summers. Using the best performing index, NSM (Normalizes Soil Moisture), and the ICA (Independent Component Analysis) technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

scholarly journals Technical Note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation

2010 ◽  
Vol 14 (2) ◽  
pp. 271-277 ◽  
Author(s):  
E. Peled ◽  
E. Dutra ◽  
P. Viterbo ◽  
A. Angert
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Technical Note ◽  
Temperate Climate ◽  
Drought Indices ◽  
Soil Drought ◽  
The Past ◽  
Analysis Technique ◽  
Global Soil ◽  
Warm Temperate

Abstract. In the past years there have been many attempts to produce and improve global soil-moisture datasets and drought indices. However, comparing and validating these various datasets is not straightforward. Here, interannual variations in drought indices are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which drought index describes most realistically the actual changes in vegetation. Strong correlation between NDVI and the drought indices were found in areas that are classified as warm temperate climate with hot or warm dry summers. In these areas we ranked the PDSI, PSDI-SC, SPI3, and NSM indices, based on the interannual correlation with NDVI, and found that NSM outperformed the rest. Using this best performing index, and the ICA (Independent Component Analysis) technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

scholarly journals Drought Propagation in Semi-Arid River Basins in Latin America: Lessons from Mexico to the Southern Cone

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1564 ◽  
Author(s):  
Melanie Oertel ◽  
Francisco Meza ◽  
Jorge Gironás ◽  
Christopher A. Scott ◽  
Facundo Rojas ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Drought Monitoring ◽  
Moisture Index ◽  
Data Set ◽  
Basin Scale ◽  
Soil Moisture Index ◽  
Streamflow Data ◽  
Governmental Institutions ◽  
Negative Impacts ◽  
Combined Data

Detecting droughts as early as possible is important in avoiding negative impacts on economy, society, and environment. To improve drought monitoring, we studied drought propagation (i.e., the temporal manifestation of a precipitation deficit on soil moisture and streamflow). We used the Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Streamflow Index (SSI), and Standardized Soil Moisture Index (SSMI) in three drought-prone regions: Sonora (Mexico), Maipo (Chile), and Mendoza-Tunuyán (Argentina) to study their temporal interdependence. For this evaluation we use precipitation, temperature, and streamflow data from gauges that are managed by governmental institutions, and satellite-based soil moisture from the ESA CCI SM v03.3 combined data set. Results confirm that effective drought monitoring should be carried out (1) at river-basin scale, (2) including several variables, and (3) considering hydro-meteorological processes from outside its boundaries.

scholarly journals Soil moisture obtained through remote sensing to assess drought events

2020 ◽  
Vol 24 (9) ◽  
pp. 575-580 ◽  
Author(s):  
Tiago de M. Inocêncio ◽  
Alfredo Ribeiro Neto ◽  
Alzira G. S. S. Souza
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Condition Index ◽  
Semiarid Region ◽  
Moisture Index ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Northeast Region ◽  
Promising Tool ◽  
Soil Moisture Index

ABSTRACT The sequence of drought events in the Northeast of Brazil in recent decades raises attention to the importance of studying this phenomenon. The objective of this study was to evaluate the duration and severity of drought events from 1988 to 2018 in hydrographic basins of the state of Pernambuco, Brazil, using two drought indexes: Standardized Soil Moisture Index and Soil Moisture Condition Index, calculated based on data of the Soil Moisture Project of the European Space Agency’s Climate Change Initiative. The duration of the droughts was determined considering the months between their beginning and end, and their severity was based on the area formed in the graph between the curve of the index and the x-axis. The soil moisture database showed to be a promising tool for the analysis and monitoring of drought events in the Northeast region of Brazil, mainly for analysis and monitoring of drought events. The indexes allowed the evaluation of the drought phenomenon over the 30-year period, showing increases from 2012, which were more pronounced in the Semiarid region. The hydrographic basins responded differently to a same event, depending on the climate characteristics of the region in which they are located. Consecutive years with rainfall below the historical mean increased the magnitude of the droughts, as found for the 2012-2017 period, in which the indexes presented delays to return to more favorable values, showing the effect that one drought year has on the following year.

scholarly journals Development of the Soil Moisture Index to Quantify Agricultural Drought and Its “User Friendliness” in Severity-Area-Duration Assessment

2008 ◽  
Vol 9 (4) ◽  
pp. 660-676 ◽  
Author(s):  
Venkataramana Sridhar ◽  
Kenneth G. Hubbard ◽  
Jinsheng You ◽  
Eric D. Hunt
Keyword(s):  
Soil Moisture ◽  
Agricultural Drought ◽  
Extreme Drought ◽  
Weather Data ◽  
Moisture Index ◽  
Drought Duration ◽  
Available Water ◽  
Soil Moisture Index ◽  
The Difference ◽  
Wilting Point

Abstract This paper examines the role of soil moisture in quantifying drought through the development of a drought index using observed and modeled soil moisture. In Nebraska, rainfall is received primarily during the crop-growing season and the supply of moisture from the Gulf of Mexico determines if the impending crop year is either normal or anomalous and any deficit of rain leads to a lack of soil moisture storage. Using observed soil moisture from the Automated Weather Data Network (AWDN), the actual available water content for plants is calculated as the difference between observed or modeled soil moisture and wilting point, which is subsequently normalized with the site-specific, soil property–based, idealistic available water for plants that is calculated as the difference between field capacity and wilting point to derive the soil moisture index (SMI). This index is categorized into five classes from no drought to extreme drought to quantitatively assess drought in both space and time. Additionally, with the aid of an in-house hydrology model, soil moisture was simulated in order to compute model-based SMI and to compare the drought duration and severity for various sites. The results suggest that the soil moisture influence, a positive feedback process reported in many earlier studies, is unquestionably a quantitative indicator of drought. Also, the severity and duration of drought across Nebraska has a clear gradient from west to east, with the Panhandle region experiencing severe to extreme drought in the deeper soil layers for longer periods (>200 days), than the central and southwestern regions (125–150 days) or the eastern regions about 100 days or less. The anomalous rainfall years can eliminate the distinction among these regions with regard to their drought extent, severity, and persistence, thus making drought a more ubiquitous phenomenon, but the recovery from drought can be subject to similar gradations. The spatial SMI maps presented in this paper can be used with the Drought Monitor maps to assess the local drought conditions more effectively.

Soil Moisture Index

1917 ◽  
Vol 63 (2) ◽  
pp. 151-152
Author(s):  
Francis Ramaley
Keyword(s):  
Soil Moisture ◽  
Moisture Index ◽  
Soil Moisture Index
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