Enhanced hydrologic simulation may not improve downscaled soil moisture patterns without improved soil characterization

2020 ◽  
Vol 84 (3) ◽  
pp. 672-689 ◽  
Author(s):  
Matthew J. Pauly ◽  
Jeffrey D. Niemann ◽  
Joseph Scalia ◽  
Timothy R. Green ◽  
Robert H. Erskine ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Characterization ◽  
Hydrologic Simulation

scholarly journals Ensemble long-term soil moisture forecast using hydrological modeling

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Bibiana Rodrigues Colossi ◽  
Carlos Eduardo Morelli Tucci
Keyword(s):  
Soil Moisture ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Computing Time ◽  
Ensemble Member ◽  
Lead Times ◽  
Hydrologic Simulation ◽  
The Mean ◽  
Group B

ABSTRACT Long-term soil moisture forecasting allows for better planning in sectors as agriculture. However, there are still few studies dedicated to estimate soil moisture for long lead times, which reflects the difficulties associated with this topic. An approach that could help improving these forecasts performance is to use ensemble predictions. In this study, a soil moisture forecast for lead times of one, three and six months in the Ijuí River Basin (Brazil) was developed using ensemble precipitation forecasts and hydrologic simulation. All ensemble members from three climatologic models were used to run the MGB hydrological model, generating 207 soil moisture forecasts, organized in groups: (A) for each model, the most frequent soil moisture interval predicted among the forecasts made with each ensemble member, (B) using each model’s mean precipitation, (C) considering a super-ensemble, and (D) the mean soil moisture interval predicted among group B forecasts. The results show that long-term soil moisture based on precipitation forecasts can be useful for identifying periods drier or wetter than the average for the studied region. Nevertheless, estimation of exact soil moisture values remains limited. Forecasts groups B and D performed similarly to groups A and C, and require less data management and computing time.

Long term hydrologic simulations for the meso-scale catchments Rur and Bode in Germany by TSMP

2020 ◽  
Author(s):  
Zhenlei Yang ◽  
Wolfgang Kurtz ◽  
Sebastian Gebler ◽  
Lennart Schüler ◽  
Stefan Kollet ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Groundwater Recharge ◽  
Soil Moisture Content ◽  
Systems Modeling ◽  
Hydrologic Simulation ◽  
Grid Coarsening ◽  
Simulation Results ◽  
Meso Scale

<p>Integrated terrestrial systems modeling is important for the comprehensive investigation of the coupled terrestrial water, energy and biogeochemical cycles. In this work, we applied the Terrestrial Systems Modeling Platform (TSMP) to the two meso-scale catchments in Germany (Rur and Bode) to conduct a long time hydrologic simulation with a focus on variables such as soil moisture, evapotranspiration (ET) and groundwater recharge. Simulations for the Rur and Bode catchments were performed at three different spatial horizontal model resolutions (1000, 500, and 200m) with CLM and CLM-PF in TSMP. Each of the three resolution models was run for 24 years (1995-2018) with transient atmospheric forcings derived from COSMO-REA6 data. The long term simulation results show that the summer of 2018 resulted in the lowest soil moisture content over the time series that is around 0.20, lower than the dry summers of 1995 and 2003. ET was more reduced in July-August 2018 due to the decrease of soil moisture content during this period. Nevertheless, actual evapotranspiration was even in the summer of 2018 often not limited by soil moisture content. For these catchments ET is most of the time energy limited. In addition, the vegetation evaporation (resulting from interception) accounts for the smallest percentage of the ET (ca. 20%), whereas the vegetation transpiration and soil evaporation account for almost the same percentage of the total ET (each 40% approximately). Both the CLM and CLM-PF simulation results indicate that grid coarsening (lower model resolution) leads to larger ET and soil moisture content, which is related to the decreasing slope gradient with grid coarsening. The analysis of groundwater recharge is underway.</p>

Long-term hydrologic simulation using SCS-CN-based improved soil moisture accounting procedure

2010 ◽  
Vol 25 (4) ◽  
pp. 561-579 ◽  
Author(s):  
Dilip G. Durbude ◽  
Manoj K. Jain ◽  
Surendra K. Mishra
Keyword(s):  
Soil Moisture ◽  
Hydrologic Simulation ◽  
Soil Moisture Accounting ◽  
Scs Cn ◽  
Accounting Procedure

scholarly journals SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia

2015 ◽  
Vol 168 ◽  
pp. 146-162 ◽  
Author(s):  
H. Lievens ◽  
S.K. Tomer ◽  
A. Al Bitar ◽  
G.J.M. De Lannoy ◽  
M. Drusch ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Hydrologic Simulation ◽  
Murray Darling Basin

scholarly journals A Framework for Diagnosing Factors Degrading the Streamflow Performance of a Soil Moisture Data Assimilation System

2019 ◽  
Vol 20 (1) ◽  
pp. 79-97 ◽  
Author(s):  
Yixin Mao ◽  
Wade T. Crow ◽  
Bart Nijssen
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Systematic Error ◽  
Land Surface ◽  
Large Scale ◽  
Surface Model ◽  
Random Errors ◽  
Hydrologic Simulation ◽  
Diagnostic Framework

Abstract Data assimilation (DA) techniques have been widely applied to assimilate satellite-based soil moisture (SM) measurements into hydrologic models to improve streamflow simulations. However, past studies have reached mixed conclusions regarding the degree of runoff improvement achieved via SM state updating. In this study, a synthetic diagnostic framework is designed to 1) decompose the random error components in a hydrologic simulation, 2) quantify the error terms that originate from SM states, and 3) assess the effectiveness of SM DA to correct these random errors. The general framework is illustrated through a case study in which surface Soil Moisture Active Passive (SMAP) data are assimilated into a large-scale land surface model in the Arkansas–Red River basin. The case study includes systematic error in the simulated streamflow that imposes a first-order limit on DA performance. In addition, about 60% of the random runoff error originates directly from rainfall and cannot be corrected by SM DA. In particular, fast-response runoff dominates in much of the basin but is relatively unresponsive to state updating. Slow-response runoff is strongly controlled by the bottom-layer SM and therefore only modestly improved via the assimilation of surface measurements. Combined, the total runoff improvement in the synthetic analysis is small (<10% over the basin). Improvements in the real SMAP-assimilated case are further limited due to systematic error and other factors such as inaccurate error assumptions and SMAP rescaling. Findings from the diagnostic framework suggest that SM DA alone is insufficient to substantially improve streamflow estimates in large basins.

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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