Performance evaluation of commonly used infiltration models

The research was conducted on the field and models of vertisol soil types under varied land in southern Ethiopia's semi-arid Arba Minch university research centre site to measure infiltration and determine infiltration rates. The infiltration rate and model performance evaluation of the specific land use conditions affect the design and evaluation of surface and sub-surface irrigation methods. The infiltration rate is investigated on two different types of land (vegetable-covered land and bare land) and two different types of models (Horton and Kostiakov models). The experimental infiltration depth of the above soil conditions is measured using a double-ring infiltrometer. The research aims to figure out the field-measured infiltration rate, model infiltration rates, and basic infiltration rate, identify the impact of infiltration factors on infiltration rate, and find the best-fitted infiltration model. The findings from multiple infiltration models were compared with actual field data. The graphs of infiltration were generated to find the best fitting model for a certain vertisol soil type and two lands. The determination, correlation coefficient, bias, root mean square error (RMSE), model efficiency, determination coefficient (R2), slope, correlation coefficient (r), average percentage error, and the gradient were the performance indicators examined for the optimum fitting of the model. The Kostiakov model's results are the best fit to observe field data for estimating infiltration rates at any given period in the research region by taking into account the infiltration numerical software performance indicators. The vegetable cover land infiltration rate is higher than un-disturbed bare land.

Water retention and hydraulic properties of undisturbed tropical soils collected from many regions of Indonesia were analyzed to estimate infiltration characteristics of the soils. Soil texture was classified based on International Society of Soil Science (ISSS) classification. The van-Genuchten model was used to estimate the relationship between water content and matrix potential at pF=1, pF=2, pF=2.54, pF=4.2. The 165 soil water retention data were used to optimize parameters of the model and to find the air entry value. Green-Ampt and Philip's infiltration models were applied to characterize soil infiltrability of each textural type. The Nash and Sutcliffe's efficiency was used to evaluate numerical simulation of cumulative infiltration of Green-Ampt's infiltration model compared to the results of laboratory experiments. The 165 soil samples were classified and were optimized into 10 ISSS textural types: heavy clay, sandy clay, sandy clay loam, sandy loam, sand, light clay, clay loam, loam, silty clay, and silty clay loam. The results of performance evaluation of Green-Ampt's infiltration model showed that Green-Ampt's infiltration model can describe infiltration characteristics by using soil water retention and hydraulic properties data. The tropical soils based on soil texture exhibit contrasting infiltration characteristics as indicated by infiltration rate, length of wetting front and sorptivity. The characteristics of soil infiltrability are mainly influenced by hydraulic conductivity, initial water content, and matrix potential at the wetting front.

Four infiltration models were investigated for their capacity to describe water infiltration into hydromorphic (gleysol) soil. The Models were Kostiakov\'s (1932), Philip\'s (1957) Kostiakov- Lewis\'(1982) and Modified Kostiakov (1978). Field measurement of infiltration was made using double ring infiltrometers on an hydromorphic soil of the flood plain in Zango village, Samaru, Zaria, Nigeria. Infiltration tests were carried out in a land area of 80 m by 240 m divided into four strips of 20 m by 240 m, with the top strip located 90 m away from the main watercourse of the area. A total of 16 infiltration tests were carried out over the area. A set of the field-measured cumulative infiltration depths were used for estimation of parameters of the models studied, and the other set was used to evaluate the performance of the infiltration models in simulating cumulative infiltration depths. All four models studied provided good overall agreement with field-measured data. However, Kostiakov and Modified kostiakov models provided the best fit with experimental data for the hydromorphic soil. Keywords: Infiltration, Hydromorphic soil, Ring Infiltrometer, Infiltration models. Nigerian Journal of Soil and Environmental Research Vol. 7 2007: pp. 53-59

The application of several infiltration models in evaluating the infiltration rate of soil is subject to the spatial variability of soil. Infiltration plays an important role in designing and evaluating surface irrigation systems as well as subsurface groundwater recharge systems. The main theme of this paper is to compare the empirical equation‐based models which are used to estimate the infiltration rate of various locations in Kurukshetra, India. Infiltration experiments were conducted at 20 different locations using a mini disc infiltrometer. The least square fitting method was used for each location separately to estimate the equation parameters and infiltration rate of three different empirical models, namely Kostiakov, modified Kostiakov and Novel models. The performance of these empirical infiltration models was further compared with the machine learning‐based adaptive neuro‐fuzzy inference system (ANFIS) and random forest regression (RF) techniques. Statistical performance evaluation parameters (R2, CC, RMSE and MAE) are used for the performance comparison of various models. The Novel infiltration model was observed to be the most reasonable amongst the empirical models tested. However, for machine‐learning methods, the RF approach is observed to be the most appropriate technique for the estimation of the infiltration data. © 2019 John Wiley & Sons, Ltd.

Technoeconomic comparison of optimised bioreactor-filtration systems for mAb production

Performance evaluation of commonly used infiltration models

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.

Soil’s infiltration characteristics remain important variables of consideration in irrigation systems designs as well as in soil and water management. This work was conducted to evaluate the performances of three different infiltration models (Kostiakov, Horton and Philip) in order to select a suitable model for use in determination of infiltration characteristics of soils neighbouring Bayero University, Kano-Nigeria. Experiments were conducted in three different locations within the study area and the performance of each model was analysed and compared against a direct measurement using double ring infiltrometer. The results showed no significant difference (Least significant difference = 0.29 @ 0.05 level of significance) between the direct measurement on field and the result obtained using Kostiakov and Horton’s model having mean infiltration rate of 1.05 and 1.04cm per minutes respectively, while the Philip’s model showed a significant difference in means (1.76cm/min) indicating higher sensitivity of its measurement. There was no significance difference (p=0.19 @ 0.05 level of significance) on replicating the experiment for the 3 different locations. Thus, the Kostiakov’s and Horton’s models were recommended for the infiltration characteristics measurement in Kano and elsewhere with similar environmental conditions.

Performance evaluation of infiltration models under different tillage operations in a tropical climate

Capillary barriers consisting of tilted fine-over-coarse layers have been suggested as landfill covers as a means to divert water infiltration away from sensitive underground regions under unsaturated flow conditions, especially for arid and semi-arid regions. Typically, the HELP code is used to evaluate landfill cover performance and design. Unfortunately, due to its simplified treatment of unsaturated flow and its essentially one-dimensional nature, HELP is not adequate to treat the complex multidimensional unsaturated flow processes occurring in a tilted capillary barrier. In order to develop the necessary mechanistic code for the performance evaluation of tilted capillary barriers, an efficient and comprehensive unsaturated flow code needs to be selected for further use and modification. The present study evaluates a number of candidate mechanistic unsaturated flow codes for application to tilted capillary barriers. Factors considered included unsaturated flow modeling, inclusion of evapotranspiration, nodalization flexibility, ease of modification, and numerical efficiency. A number of unsaturated flow codes are available for use with different features and assumptions. The codes chosen for this evaluation are TOUGH2, FEHM, and SWMS{_}2D. All three codes chosen for this evaluation successfully simulated the capillary barrier problem chosen for the code comparison, although FEHM used a reduced grid. The numerical results are a strong function of the numerical weighting scheme. For the same weighting scheme, similar results were obtained from the various codes. Based on the CPU time of the various codes and the code capabilities, the TOUGH2 code has been selected as the appropriate code for tilted capillary barrier performance evaluation, possibly in conjunction with the infiltration, runoff, and evapotranspiration models of HELP. 44 refs.

Knowledge of cumulative infiltration of soil is necessary for irrigation, surface flow, groundwater recharge and many other hydrological processes. In the present study, the Support Vector Machine (SVM), artificial neural network (ANN) and adaptive Neuro-fuzzy inference system (ANFIS) were employed to estimate the cumulative infiltration of soil. For this study, a data set containing 106 experimental observations were analyzed. Out of 106, 70 % of data was selected for preparing different algorithms whereas rest 30% data was selected to test the models. The models accuracy was depended upon the two performance evaluation parameter which is correlation coefficient (CC) and root mean square error (RMSE). Results of performance evaluation parameters suggest that triangular membership function-based ANFIS model works well than SVM and ANN models. While SVM and ANN models also give a good estimation performance. Sensitivity analysis concludes that the parameter, time (t) is the most influencing parameter for the modeling of cumulative infiltration of soil for this data set.

Treatment of food processing industries wastewaters using a new clay-based inorganic membrane: Performance evaluation and fouling analysis

To guide the selection of gas phase filtration media in the air cleaning devices, it is important to understand and estimate the media performance under usage concentrations. Filters for improving indoor air quality are typically subject to low volatile organic compounds (VOCs) concentration levels (e.g., ∼50 ppb), while the current standard tests per ASHRAE 145.1 (ANSI/ASHRAE 2008). are performed at relatively high challenge concentrations (∼1–100 ppm level). The primary objective of this study was to determine if media that perform well at the high concentration test condition would also perform well under the low concentration. The secondary objective was to investigate if and how existing models of filtration by media bed can be applied to extrapolate the results from the high concentration tests to the low concentration condition. Experiments and simulations were carried out at both high concentrations (100 ppm for toluene and 1 ppm for formaldehyde) and low concentrations (0.05 ppm for toluene and formaldehyde) for six selected filtration media. The results show that (1) the high concentration test data were able to differentiate the relative performance among the media at the low concentration properly, confirming the validity of using ASHRAE 145.1 (ANSI/ASHRAE 2008) for relative performance comparison; (2) significant initial breakthrough observed at high concentration tests of large pellet media was not present at the low concentration tests, indicating the dependency of the adsorption capability of the sorbent media on the concentration level as well as the possible “by-pass” effects (i.e., not all the VOC molecules in the air stream had the same chance to contact with the sorbent media); and (3) existing models need to be improved by incorporating the concentration dependency of the partition coefficient and the by-pass effect in order to predict the breakthrough curve at low concentrations properly. Such an improved model was proposed, evaluated with the measured data, and was found to be promising for physical sorbent, but requires further development for chemical, catalytic sorbent and large pellet sorbent. The study provides previously unavailable experimental data and new insight into the behavior of the filtration media for volatile organic compounds as well as evidence in support of the application of ASHRAE Standard 145.1 (ANSI/ASHRAE 2008) for media performance evaluation.

The potential impacts of future climate change on the evolution of groundwater recharge are examined at a local scale for a 546-km2 watershed in eastern Canada. Recharge is estimated using the infiltration model Hydrologic Evaluation of Landfill Performance (HELP), with inputs derived from five climate runs generated by a regional climate model in combination with the A2 greenhouse gas emissions scenario. The model runs project an increase in annual recharge over the 2041–2070 period. On a seasonal basis, however, a marked decrease in recharge during the summer and a marked increase during the winter are observed. The results suggest that increased evapotranspiration resulting from higher temperatures does not offset the large increase in winter infiltration. In terms of individual water budget components, clear differences are obtained for the different climate change scenarios. Monthly recharge values are also found to be quite variable, even for a given climate scenario. These findings are compared with results from two regional-scale studies.Editor D. Koutsoyiannis; Associate editor M. BesbesCitation Rivard, C., Paniconi, C., Vigneault, H., and Chaumont, D., 2014. A watershed-scale study of climate change impacts on groundwater recharge (Annapolis Valley, Nova Scotia, Canada). Hydrological Sciences Journal, 59 (8), 1437–1456. http://dx.doi.org/10.1080/02626667.2014.887203

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