Retrieving Root-Zone Soil Moisture Profile From P-Band Radar via Hybrid Global and Local Optimization

2020 ◽  
Vol 58 (8) ◽  
pp. 5400-5408 ◽  
Author(s):  
Aslan Etminan ◽  
Alireza Tabatabaeenejad ◽  
Mahta Moghaddam
Keyword(s):  
Soil Moisture ◽  
Root Zone ◽  
Local Optimization ◽  
Moisture Profile ◽  
Global And Local Optimization ◽  
Global And Local ◽  
Soil Moisture Profile

scholarly journals Design and Automated Optimization of an Internal Turret Mooring System in the Frequency and Time Domain

2021 ◽  
Vol 9 (6) ◽  
pp. 581
Author(s):  
Hongrae Park ◽  
Sungjun Jung
Keyword(s):  
System Design ◽  
Time Domain ◽  
Initial Conditions ◽  
Minimum Weight ◽  
Optimization Algorithms ◽  
Local Optimization ◽  
Mooring System ◽  
Floating Offshore Wind Turbines ◽  
Global And Local Optimization ◽  
Global And Local

A cost-effective mooring system design has been emphasized for traditional offshore industry applications and in the design of floating offshore wind turbines. The industry consensus regarding mooring system design is mainly inhibited by previous project experience. The design of the mooring system also requires a significant number of design cycles. To take aim at these challenges, this paper studies the application of an optimization algorithm to the Floating Production Storage and Offloading (FPSO) mooring system design with an internal turret system at deep-water locations. The goal is to minimize mooring system costs by satisfying constraints, and an objective function is defined as the minimum weight of the mooring system. Anchor loads, a floating body offset and mooring line tensions are defined as constraints. In the process of optimization, the mooring system is analyzed in terms of the frequency domain and time domain, and global and local optimization algorithms are also deployed towards reaching the optimum solution. Three cases are studied with the same initial conditions. The global and local optimization algorithms successfully find a feasible mooring system by reducing the mooring system cost by up to 52%.

scholarly journals Enhanced Estimation of Root Zone Soil Moisture at 1 km Resolution Using SMAR Model and MODIS-Based Downscaled AMSR2 Soil Moisture Data

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5211
Author(s):  
Maedeh Farokhi ◽  
Farid Faridani ◽  
Rosa Lasaponara ◽  
Hossein Ansari ◽  
Alireza Faridhosseini
Keyword(s):  
Soil Moisture ◽  
Prediction Models ◽  
Surface Soil ◽  
Root Zone ◽  
Analytical Relationship ◽  
Moisture Profile ◽  
Essential Variable ◽  
Potential Benefits ◽  
Spatio Temporal ◽  
Hydrological Prediction

Root zone soil moisture (RZSM) is an essential variable for weather and hydrological prediction models. Satellite-based microwave observations have been frequently utilized for the estimation of surface soil moisture (SSM) at various spatio-temporal resolutions. Moreover, previous studies have shown that satellite-based SSM products, coupled with the soil moisture analytical relationship (SMAR) can estimate RZSM variations. However, satellite-based SSM products are of low-resolution, rendering the application of the above-mentioned approach for local and pointwise applications problematic. This study initially attempted to estimate SSM at a finer resolution (1 km) using a downscaling technique based on a linear equation between AMSR2 SM data (25 km) with three MODIS parameters (NDVI, LST, and Albedo); then used the downscaled SSM in the SMAR model to monitor the RZSM for Rafsanjan Plain (RP), Iran. The performance of the proposed method was evaluated by measuring the soil moisture profile at ten stations in RP. The results of this study revealed that the downscaled AMSR2 SM data had a higher accuracy in relation to the ground-based SSM data in terms of MAE (↓0.021), RMSE (↓0.02), and R (↑0.199) metrics. Moreover, the SMAR model was run using three different SSM input data with different spatial resolution: (a) ground-based SSM, (b) conventional AMSR2, and (c) downscaled AMSR2 products. The results showed that while the SMAR model itself was capable of estimating RZSM from the variation of ground-based SSM data, its performance increased when using downscaled SSM data suggesting the potential benefits of proposed method in different hydrological applications.

scholarly journals Frozen soil parameterization in a distributed biosphere hydrological model

2009 ◽  
Vol 6 (6) ◽  
pp. 6895-6928
Author(s):  
L. Wang ◽  
T. Koike ◽  
K. Yang ◽  
R. Jin ◽  
H. Li
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Hydrological Model ◽  
Frozen Soil ◽  
Surface Radiation ◽  
Moisture Profile ◽  
Flood Peak ◽  
Radiation Fluxes ◽  
Soil Moisture Profile ◽  
The Web

Abstract. In this study, a frozen soil parameterization has been modified and incorporated into a distributed biosphere hydrological model (WEB-DHM). The WEB-DHM with the frozen scheme was then rigorously evaluated in a small cold area, the Binngou watershed, against the in-situ observations from the WATER (Watershed Allied Telemetry Experimental Research). In the summer 2008, land surface parameters were optimized using the observed surface radiation fluxes and the soil temperature profile at the Dadongshu-Yakou (DY) station in July; and then soil hydraulic parameters were obtained by the calibration of the July soil moisture profile at the DY station and by the calibration of the discharges at the basin outlet in July and August that covers the annual largest flood peak of 2008. The calibrated WEB-DHM with the frozen scheme was then used for a yearlong simulation from 21 November 2007 to 20 November 2008, to check its performance in cold seasons. Results showed that the WEB-DHM with the frozen scheme has given much better performance than the WEB-DHM without the frozen scheme, in the simulations of soil moisture profile at the DY station and the discharges at the basin outlet in the yearlong simulation.

Sign in / Sign up

Export Citation Format

Share Document