scholarly journals An alternative deterministic method for the spatial interpolation of water retention parameters

2009 ◽  
Vol 13 (4) ◽  
pp. 453-465 ◽  
Author(s):  
H. Saito ◽  
K. Seki ◽  
J. Šimůnek
Keyword(s):  
Spatial Distribution ◽  
Spatial Interpolation ◽  
Water Retention ◽  
Interpolation Method ◽  
Sampling Location ◽  
Model Parameters ◽  
Retention Data ◽  
Retention Models ◽  
Split Sample ◽  
Retention Parameters

Abstract. There are two approaches available for mapping water retention parameters over the study area using a spatial interpolation method. (1) Retention models can be first fitted to retention curves available at sampling locations prior to interpolating model parameters over the study area (the FI approach). (2) Retention data points can first be interpolated over the study area before retention model parameters are fitted (the IF approach). The current study compares the performance of these two approaches in representing the spatial distribution of water retention curves. Standard geostatistical interpolation methods, i.e., ordinary kriging and indicator kriging, were used. The data used in this study were obtained from the Las Cruces trench site database, which contains water retention data for 448 soil samples. Three standard water retention models, i.e., Brooks and Corey (BC), van Genuchten (VG), and Kosugi (KSG), were considered. For each model, standard validation procedures, i.e., leave-one-out cross-validation and split-sample methods were used to estimate the uncertainty of the parameters at each sampling location, allowing for the computation of prediction errors (mean absolute error and mean error). The results show that the IF approach significantly lowered mean absolute errors for the VG model, while also reducing them moderately for the KSG and BC models. In addition, the IF approach resulted in less bias than the FI approach, except when the BC model was used in the split-sample approach. Overall, IF outperforms FI for all three retention models in describing the spatial distribution of retention parameters.

scholarly journals Geostatistical modeling of spatial variability of water retention curves

2008 ◽  
Vol 5 (4) ◽  
pp. 2491-2522 ◽  
Author(s):  
H. Saito ◽  
K. Seki ◽  
J. Šimůnek
Keyword(s):  
Water Retention ◽  
Cross Validation ◽  
Sampling Location ◽  
Retention Data ◽  
Prediction Errors ◽  
Parametric Approach ◽  
Data Set ◽  
Retention Models ◽  
Validation Procedure ◽  
Non Parametric

Abstract. This study compares the performance of two geostatistical approaches, parametric and non-parametric, to evaluate the spatial distribution of water retention curves. Data used in this study were obtained from the Las Cruces trench site database that contains water retention data for 448 soil samples. In a commonly used parametric approach, three standard water retention models, i.e. Brooks and Corey (BC), van Genuchten (VG), and log-normal (LN), were first fitted to each data set. For each model, a cross validation procedure was used to estimate parameters at each sampling location, allowing computation of prediction errors. In a rarely used non-parametric approach, a cross validation procedure was first used to directly estimate water content values for eleven pressure heads at each sampling location and then the three water retention models were fitted using the same automated procedure to compute prediction errors. The results show that the non-parametric approach significantly lowered prediction errors for the VG model, while moderately reducing them also for the LN and BC models.

Spatial Simulation of Precipitation Resources in Chongqing

2012 ◽  
Vol 518-523 ◽  
pp. 4261-4265
Author(s):  
Xiao Song Lin ◽  
Sha Sha Yu ◽  
Hai Yan Wang
Keyword(s):  
Spatial Distribution ◽  
Spatial Interpolation ◽  
Regional Difference ◽  
Interpolation Method ◽  
Annual Precipitation ◽  
Regression Equations ◽  
Spatial Simulation ◽  
Simulation Data ◽  
Spatial Interpolation Method ◽  
Precise Simulation

Years’ precipitation data of Chongqing from 101 metrological stations has been adopted in the paper and the regression equations between annual precipitation and altitude, longitude, and height have been obtained by the use of SPSS, then elaborate simulation of Chongqing’s precipitation resources based on regression analysis was completed through the 1km×1km grid system and fitted equation. Elaborated simulation of precipitation resources was realized by best spatial interpolation method with the support of GIS; then the results of two different simulation methods were coupled in the form of linear combination to obtain the coupling simulation of spatial distribution of Chongqing’s precipitation resources, finally the precipitation resources were summed up and distributed according to different administration areas at county level and thus obtain precise simulation data of precipitation resources in each county of Chongqing. The results showed that there is a remarkable regional difference in the spatial distribution of precipitation resources of Chongqing, and it decreases from the southeast to the northwest in general, with the annual precipitation higher than 1270mm in southeast and lower than 1080mm in northwest.

scholarly journals Modelling of soil-water retention curve considering the effects of existing salt solution in the pore fluid

2021 ◽  
Vol 337 ◽  
pp. 02001
Author(s):  
Hamed Sadeghi ◽  
Ali Golaghaei Darzi
Keyword(s):  
Soil Water ◽  
Osmotic Potential ◽  
Water Retention ◽  
Pore Fluid ◽  
Water Retention Curve ◽  
Model Parameters ◽  
Retention Data ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve

Soil-water retention curve (SWRC) has a wide application in geoenvironmental engineering from the predication of unsaturated shear strength to transient two-phase flow and stability analyses. Although various SWRC models have been proposed to take into account some influencing factors, less attention has been given to consider the effects of pore fluid osmotic potential. Therefore, the key objective of this study is to extend van Genchten’s model so that osmotic potential is considered as an independent factor governing the SWRC behavior. The new model comprises only six variables, which can be calibrated through minimal experimental measurements. More importantly, most of the model parameters have physical meaning by correlating macroscopic volumetric behavior and general trends of SWRC to osmotic potential. The results of validation tests revealed that the new osmotic-dependent SWRC model can predict the retention data in terms of both total and matric suction for two different soils and various molar concentrations very good. The proposed modeling approach does not require any advanced mercury intrusion porosimetry (MIP) tests, yet it can deliver excellent predictions by calibrating only six parameters which are far less than those incorporated into similar models for saline water permeating through the pore structure.

scholarly journals Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: II. Evaluation of Parametric Pedotransfer Functions Against Direct Fits

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 896 ◽  
Author(s):  
Amir Haghverdi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Water Retention ◽  
Organic Matter Content ◽  
Pedotransfer Functions ◽  
Model Parameters ◽  
Retention Data ◽  
Soil Water Retention ◽  
Data Set ◽  
Free Parameters

A high-resolution soil water retention data set (81 repacked soil samples with 7729 observations) measured by the HYPROP system was used to develop and evaluate the performance of regression parametric pedotransfer functions (PTFs). A total of sixteen soil hydraulic models were evaluated including five unimodal water retention expressions of Brooks and Corey (BC model), Fredlund and Xing (FX model), Kosugi (K model), van Genuchten with four free parameters (VG model) and van Genuchten with five free parameters (VGm model). In addition, eleven bimodal, Peters–Durner–Iden (PDI) and bimodal-PDI variants of the original expressions were studied. Six modeling scenarios (S1 to S6) were examined with different combinations of the following input predictors: soil texture (percentages of sand, silt and clay), soil bulk density, organic matter content, percent of stable aggregates and saturated water content (θs). Although a majority of the model parameters showed low correlations with basic soil properties, most of the parametric PTFs provided reasonable water content estimations. The VGm parametric PTF with an RMSE of 0.034 cm3 cm−3 was the best PTF when all input predictors were considered. When averaged across modeling scenarios, the PDI variant of the K model with an RMSE of 0.045 cm3 cm−3 showed the highest performance. The best performance of all models occurred at S6 when θs was considered as an additional input predictor. The second-best performance for 11 out of the 16 models belonged to S1 with soil textural components as the only inputs. Our results do not recommend the development of parametric PTFs using bimodal variants because of their poor performance, which is attributed to their high number of free parameters.

scholarly journals Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: I. Direct Model Fit Using the Extended Evaporation and Dewpoint Methods

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 900 ◽  
Author(s):  
Amir Haghverdi ◽  
Mohsen Najarchi ◽  
Hasan Sabri Öztürk ◽  
Wolfgang Durner
Keyword(s):  
High Resolution ◽  
Soil Water ◽  
Water Retention ◽  
The United States ◽  
Retention Data ◽  
Soil Water Retention ◽  
Retention Models ◽  
Direct Model ◽  
Free Parameters ◽  
Measured Water

This study focuses on the reliable parametrization of the full Soil Water Retention Curve (SWRC) from saturation to oven-dryness using high resolution but limited range measured water retention data by the Hydraulic Property Analyzer (HYPROP) system. We studied the performance of five unimodal water retention models including the Brooks and Corey model (BC model), the Fredlund and Xing model (FX model), the Kosugi model (K model), the van Genuchten constrained model with four free parameters (VG model), and the van Genuchten unconstrained model with five free parameters (VGm model). In addition, eleven alternative expressions including Peters–Durner–Iden (PDI), bimodal, and bimodal-PDI variants of the original models were evaluated. We used a data set consisting of 94 soil samples from Turkey and the United States with high-resolution measured data (a total of 9264 measured water retention data pairs) mainly via the HYPROP system and supplemented for some samples with measured dry-end data using the WP4C instrument. Among unimodal expressions, the FX and the K models with the Mean Absolute Error (MAE) values equal to 0.005 cm3 cm−3 and 0.015 cm3 cm−3 have the highest and the lowest accuracy, respectively. Overall, the alternative variants provided a better fit than the unimodal expressions. The unimodal models, except for the FX model, fail to provide reliable dry-end estimations using HYPROP data (average MAE: 0.041 cm3 cm−3, average r: 0.52). Our results suggested that only models that account for the zero water content at the oven dryness and properly shift from the middle range to dry-end (i.e., the FX model and PDI variants) can adequately represent the full SWRC using typical data obtained via the HYPROP system.

Simulation of mechanically stirred two-phase liquid-gas flow

1986 ◽  
Vol 51 (5) ◽  
pp. 1001-1015 ◽  
Author(s):  
Ivan Fořt ◽  
Vladimír Rogalewicz ◽  
Miroslav Richter
Keyword(s):  
Spatial Distribution ◽  
Velocity Field ◽  
Gas Flow ◽  
Liquid Velocity ◽  
Model Parameters ◽  
Two Phase ◽  
Mean Velocity ◽  
Rushton Turbine ◽  
Low Viscosity ◽  
Volumetric Gas Flow Rate

The study describes simulation of the motion of bubbles in gas, dispersed by a mechanical impeller in a turbulent low-viscosity liquid flow. The model employs the Monte Carlo method and it is based both on the knowledge of the mean velocity field of mixed liquid (mean motion) and of the spatial distribution of turbulence intensity ( fluctuating motion) in the investigated system - a cylindrical tank with radial baffles at the wall and with a standard (Rushton) turbine impeller in the vessel axis. Motion of the liquid is then superimposed with that of the bubbles in a still environment (ascending motion). The computation of the simulation includes determination of the spatial distribution of the gas holds-up (volumetric concentrations) in the agitated charge as well as of the total gas hold-up system depending on the impeller size and its frequency of revolutions, on the volumetric gas flow rate and the physical properties of gas and liquid. As model parameters, both liquid velocity field and normal gas bubbles distribution characteristics are considered, assuming that the bubbles in the system do not coalesce.

scholarly journals Species diversity and spatial distribution of CL/VL vectors: assessing bioclimatic effect on expression plasticity of genes possessing vaccine properties isolated from wild-collected sand flies in endemic areas of Iran

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ali Bordbar ◽  
Parviz Parvizi
Keyword(s):  
Gene Expression ◽  
Spatial Distribution ◽  
Interpolation Method ◽  
Diversity Index ◽  
Fold Change ◽  
Control Measures ◽  
Pcr Analysis ◽  
Physiological Status ◽  
Sand Flies ◽  
Risk Maps

Abstract Background Leishmaniasis is one of the ten most important neglected tropical diseases worldwide. Understanding the distribution of vectors of visceral and cutaneous leishmaniasis (VL/CL) is one of the significant strategic frameworks to control leishmaniasis. In this study, the extent of the bioclimatic variability was investigated to recognize a rigorous cartographic of the spatial distribution of VL/CL vectors as risk-maps using ArcGIS modeling system. Moreover, the effect of bioclimatic diversity on the fold change expression of genes possessing vaccine traits (SP15 and LeIF) was evaluated in each bioclimatic region using real-time PCR analysis. Methods The Inverse Distance Weighting interpolation method was used to obtain accurate geography map in closely-related distances. Bioclimatic indices were computed and vectors spatial distribution was analyzed in ArcGIS10.3.1 system. Species biodiversity was calculated based on Shannon diversity index using Rv.3.5.3. Expression fold change of SP15 and LeIF genes was evaluated using cDNA synthesis and RT-qPCR analysis. Results Frequency of Phlebotomus papatasi was predominant in plains areas of Mountainous bioclimate covering the CL hot spots. Mediterranean region was recognized as an important bioclimate harboring prevalent patterns of VL vectors. Semi-arid bioclimate was identified as a major contributing factor to up-regulate salivary-SP15 gene expression (P = 0.0050, P < 0.05). Also, Mediterranean bioclimate had considerable effect on up-regulation of Leishmania-LeIF gene in gravid and semi-gravid P. papatasi population (P = 0.0109, P < 0.05). Conclusions The diversity and spatial distribution of CL/VL vectors associated with bioclimatic regionalization obtained in our research provide epidemiological risk maps and establish more effectively control measures against leishmaniasis. Oscillations in gene expression indicate that each gene has its own features, which are profoundly affected by bioclimatic characteristics and physiological status of sand flies. Given the efficacy of species-specific antigens for vaccine production, it is essential to consider bioclimatic factors that have a fundamental role in affecting the regulatory regions of environmentally responsive loci for genes used in vaccine design.

scholarly journals Temporal-spatial Distribution Characteristics of Air Pollutants in Chengdu Economic Region, China

2019 ◽  
Vol 118 ◽  
pp. 04027
Author(s):  
Hongjin Tong ◽  
Sha Liu ◽  
Ruixue Liao ◽  
Xiaomei Wei ◽  
Kangli Che ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Temporal Variation ◽  
Air Pollutants ◽  
Interpolation Method ◽  
Central Area ◽  
Average Concentration ◽  
Distribution Characteristics ◽  
Economic Region ◽  
Spatial Distribution Characteristics ◽  
Variation Characteristics

The previous characteristics researches of air pollution were almost based on data from national environmental monitoring stations in 2015. The temporal variation curves of air pollutants and the ArcGIS grid interpolation method were used to analyze the spatial-temporal variation of air pollutants in five cities of Chengdu economic region. In 2015, the monthly change trends of PM2.5, PM10, CO, NO2 and NO of air pollutants in Chengdu economic region were basically the same. The maximum monthly average concentration was in January or December, and the minimum was in May to September. The temporal variation of SO2 was characterized by little fluctuation of monthly concentration. The temporal variation characteristics of O3 were opposite to other pollutants. The spatial distribution of PM10 and PM2.5 was characterized by the largest concentration in Chengdu and the southwest of Meishan, in which they were mainly concentrated in the central area of Chengdu in winter. The average concentration of CO in Chengdu was the largest, followed by Deyang and Mianyang, and Meishan and Ziyang was the smallest. The concentrations of NO2 and NO in Chengdu were the largest, while those in Ziyang were the smallest. The spatial distribution characteristics of O3 were different from other pollutants. The areas with the largest concentration of O3 were Ziyang and a small part of west in Chengdu. The spatial distribution of SO2 was characterized by the largest concentration of SO2 in Ziyang, the lowest concentration in Mianyang and Deyang.

scholarly journals Development and Validation of Retention Models in Supercritical Fluid Chromatography for Impregnation Process Design

2021 ◽  
Vol 11 (15) ◽  
pp. 7106
Author(s):  
Miaotian Sun ◽  
Zeynep Ülker ◽  
Zhixing Chen ◽  
Sivaraman Deeptanshu ◽  
Monika Johannsen ◽  
...  
Keyword(s):  
Supercritical Fluid ◽  
Supercritical Fluid Chromatography ◽  
Stationary Phases ◽  
Retention Factor ◽  
Retention Mechanism ◽  
Retention Data ◽  
Retention Models ◽  
Retention Factors ◽  
Polar Solutes ◽  
Porous Matrices

The retention factor is the key quantity for the thermodynamic analysis of the retention mechanism in chromatographic experiments. In this work, we measure retention factors for moderately polar solutes on four silica-based porous matrices as stationary phases by supercritical fluid chromatography. Elution of the solutes is only possible with binary mixtures of supercritical carbon dioxide (sc-CO2) and modifier (methanol) due to the low polarity of pure sc-CO2. The addition of modifiers makes the retention mechanism more complex and masks interactions between solute and stationary phase. In this work, we develop and validate several retention models that allow the obtaining of retention factors in modifier-free sc-CO2. Such models pave the way for quantifying adsorption interactions between polar solutes and non-swellable porous matrices in pure sc-CO2 based on retention data obtained in sc-CO2/modifier mixtures. The obtained information will thereby facilitate the understanding and design of impregnation processes, which are often performed in modifier-free conditions.

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