Real Time WWW Broadcasting of Soil Moisture Index for Drought Response

2007 ◽  
Author(s):  
Won Ho Nam ◽  
Jin Yong Choi ◽  
Min Won Jang ◽  
Seung Hwan Yoo ◽  
Bernard A Engel
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Drought Response ◽  
Moisture Index ◽  
Soil Moisture Index

A real-time online drought broadcast system for monitoring soil moisture index

2012 ◽  
Vol 16 (3) ◽  
pp. 357-365 ◽  
Author(s):  
Won-Ho Nam ◽  
Jin-Yong Choi ◽  
Seung-Hwan Yoo ◽  
B. A. Engel
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Moisture Index ◽  
Soil Moisture Index

scholarly journals A global near-real-time soil moisture index monitor for food security using integrated SMOS and SMAP

2020 ◽  
Vol 246 ◽  
pp. 111864 ◽  
Author(s):  
Sara Sadri ◽  
Ming Pan ◽  
Yoshihide Wada ◽  
Noemi Vergopolan ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Food Security ◽  
Real Time ◽  
Moisture Index ◽  
Soil Moisture Index

scholarly journals Tools for Communicating Agricultural Drought over the Brazilian Semiarid Using the Soil Moisture Index

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1421 ◽  
Author(s):  
Marcelo Zeri ◽  
Regina S. Alvalá ◽  
Rogério Carneiro ◽  
Gisleine Cunha-Zeri ◽  
José Costa ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Real Time ◽  
Agricultural Drought ◽  
Drought Risk ◽  
Continuous Exposure ◽  
Short Term ◽  
Moisture Index ◽  
Brazilian Semiarid ◽  
Soil Moisture Index

Soil moisture over the Brazilian semiarid region is presented in different visualizations that highlight spatial, temporal and short-term agricultural risk. The analysis used the Soil Moisture Index (SMI), which is based on a normalization of soil moisture by field capacity and wilting point. The index was used to characterize the actual soil moisture conditions into categories from severe drought to very wet. In addition, the temporal evolution of SMI was implemented to visualize recent trends in short-term drought and response to rainfall events at daily time steps, as new data are available. Finally, a visualization of drought risk was developed by considering a critical value of SMI (assumed as 0.4), below which water stress is expected to be triggered in plants. A novel index based on continuous exposure to critical SMI was developed to help bring awareness of real time risk of water stress over the region: the Index of Stress in Agriculture (ISA). The index was tested during a drought over the region and successfully identified locations under water stress for periods of three days or more. The monitoring tools presented here help to describe the real time conditions of drought over the region using daily observations. The information from those tools support decisions on agricultural management such as planting dates, triggering of irrigation, or harvesting.

A real-time drought monitoring method: cropland soil moisture index (CSMI) and application

2009 ◽  
Author(s):  
Huailiang Chen ◽  
Hongwei Zhang ◽  
Shuang-he Shen ◽  
Weidong Yu ◽  
Chunhui Zou
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Drought Monitoring ◽  
Moisture Index ◽  
Monitoring Method ◽  
Soil Moisture Index

A Real-time Ensemble Hydrological Forecasting System over Germany at Sub-seasonal to Seasonal Time Range

2020 ◽  
Author(s):  
Husain Najafi ◽  
Stephan Thober ◽  
Friedrich Boeing ◽  
Oldrich Rakovec ◽  
Matthias Kelbling ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Time Scale ◽  
Hydrologic Model ◽  
Ensemble Prediction ◽  
Time Range ◽  
Moisture Index ◽  
Hydrological Forecasting ◽  
Soil Moisture Index ◽  
Forecasting System

<p>Real-time hydrological forecasting provides valuable information to mitigate the impact of extreme hydrological events such as flood and drought. An ensemble hydrological forecasting system is developed to investigate the hydrological predictability at sub-seasonal to seasonal (S2S) time scale over Germany. The ensemble hydrological simulations are performed with the mesoscale hydrologic model (mHM) which benefits from a multiscale parameter regionalization module (MPR). The model is forced by the operational ensemble prediction System from the European Center for Medium-range Weather Forecast (ECMWF). 51 hydrological ensemble forecasts are generated in real-time (twice a week) for up to 45 days in advance. We used the initial condition records from the German Drought Monitor (GDM, www.ufz.de/duerremonitor) which provides daily up-to-date high resolution drought information at a spatial resolution of 4 km. The performance of the system is evaluated for three consecutive years started from 2016 for Soil Moisture Index (SMI) and real-time streamflow records (222 based in Zink et al 2017). Comparison between forecasted Soil Moisture Index (SMI) and the one derived by the GDM suggested promising results for certain areas over the study area at S2S time scale. The predictability of the ensemble forecasting system is evaluated against that generated with the Ensemble Streamflow Prediction (ESP) method. This research is one of the first attempts to investigate the hydrological forecasting skill at S2S time scale in Europe. The study is supported as a part of the Modular Observation Solutions for Earth System (MOSES) project.</p>

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.

Mapping of Soil Moisture Index Using Optical and Thermal Remote Sensing

2021 ◽  
pp. 759-767
Author(s):  
Jeenu John ◽  
R. Jaganathan ◽  
D. S. Dharshan Shylesh
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Moisture Index ◽  
Thermal Remote Sensing ◽  
Soil Moisture Index

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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