Predicting rootzone soil moisture from surface observations in cropland using an exponential filter

2021 ◽  
Author(s):  
Pedro Rossini ◽  
Andres Patrignani
Keyword(s):  
Soil Moisture ◽  
Surface Observations

scholarly journals Simulation of Convective Initiation during IHOP_2002 Using the Flux-Adjusting Surface Data Assimilation System (FASDAS)

2006 ◽  
Vol 134 (1) ◽  
pp. 134-148 ◽  
Author(s):  
Peter P. Childs ◽  
Aneela L. Qureshi ◽  
Sethu Raman ◽  
Kiran Alapaty ◽  
Robb Ellis ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Soil Temperature ◽  
Experimental Simulation ◽  
Convective Initiation ◽  
Control Simulation ◽  
Surface Data ◽  
Data Assimilation System ◽  
Surface Observations ◽  
Assimilation System

Abstract The Flux-Adjusting Surface Data Assimilation System (FASDAS) uses the surface observational analysis to directly assimilate surface layer temperature and water vapor mixing ratio and to indirectly assimilate soil moisture and soil temperature in numerical model predictions. Both soil moisture and soil temperature are important variables in the development of deep convection. In this study, FASDAS coupled within the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) was used to study convective initiation over the International H2O Project (IHOP_2002) region, utilizing the analyzed surface observations collected during IHOP_2002. Two 72-h numerical simulations were performed. A control simulation was run that assimilated all available IHOP_2002 measurements into the standard MM5 four-dimensional data assimilation. An experimental simulation was also performed that assimilated all available IHOP_2002 measurements into the FASDAS version of the MM5, where surface observations were used for the FASDAS coupling. Results from this case study suggest that the use of FASDAS in the experimental simulation led to the generation of greater amounts of precipitation over a more widespread area as compared to the standard MM5 FDDA used in the control simulation. This improved performance is attributed to better simulation of surface heat fluxes and their gradients.

scholarly journals Estimating root zone soil moisture using near-surface observations from SMOS

2013 ◽  
Vol 10 (6) ◽  
pp. 8325-8364 ◽  
Author(s):  
T. W. Ford ◽  
E. Harris ◽  
S. M. Quiring
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Root Zone ◽  
Strong Relationship ◽  
The United States ◽  
Filter Method ◽  
Near Surface ◽  
Cross Correlation Analysis ◽  
Surface Observations

Abstract. Satellite-derived soil moisture provides more spatially and temporally extensive data than in situ observations. However, satellites can only measure water in the top few centimeters of the soil. Therefore estimates of root zone soil moisture must be inferred from near-surface soil moisture retrievals. The accuracy of this inference is contingent on the relationship between soil moisture in the near-surface and at greater depths. This study uses cross correlation analysis to quantify the association between near-surface and root zone soil moisture using in situ data from the United States Great Plains. Our analysis demonstrates that there is generally a strong relationship between near-surface (5 to 10 cm) and root zone (25 to 60 cm) soil moisture. An exponential decay filter is applied to estimate root zone soil moisture from near-surface observations. Reasonably skillful predictions of root zone soil moisture can be made using near-surface observations. The same method is then applied to evaluate whether soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to accurately estimate root zone soil moisture. We conclude that the exponential filter method is a useful approach for accurately predicting root zone soil moisture from SMOS surface retrievals.

PROTOTIPE APLIKASI PENYIRAMAN TANAMAN MENGGUNAKAN SENSOR KELEMBABAN TANAH BERBASIS MICRO CONTOLLER ATMEGA 328

2019 ◽  
Vol 5 (1) ◽  
pp. 97-106
Author(s):  
Rudi Budi Agung ◽  
Muhammad Nur ◽  
Didi Sukayadi
Keyword(s):  
Soil Moisture ◽  
Growth And Development ◽  
Large Scale ◽  
Simple Method ◽  
Moisture Sensor ◽  
Sensor Development ◽  
Soil Moisture Sensor ◽  
Application Systems ◽  
Harvesting Systems ◽  
Working Principle

The Indonesian country which is famous for its tropical climate has now experienced a shift in two seasons (dry season and rainy season). This has an impact on cropping and harvesting systems among farmers. In large scale this is very influential considering that farmers in Indonesia are stilldependent on rainfall which results in soil moisture. Some types of plants that are very dependent on soil moisture will greatly require rainfall or water for growth and development. Through this research, researchers tried to make a prototype application for watering plants using ATMEGA328 microcontroller based soil moisture sensor. Development of application systems using the prototype method as a simple method which is the first step and can be developed again for large scale. The working principle of this prototype is simply that when soil moisture reaches a certainthreshold (above 56%) then the system will work by activating the watering system, if it is below 56% the system does not work or in other words soil moisture is considered sufficient for certain plant needs.

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