Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Accurate estimation of infiltration rates is crucial for effective irrigation system design and evaluation by optimizing irrigation scheduling, preventing soil erosion, and enhancing water use efficiency. This study evaluates and compares selected infiltration models for estimating water infiltration rates in the Shillanat-iv irrigation scheme in northern Ethiopia. Soil samples were collected to determine textural classes using hydrometer soil texture analysis and the United States Department of Agriculture (USDA) textural triangle. The soil textural map of the study was created using the inverse distance weight interpolation technique in ArcGIS version 10.4. Infiltration rates were measured using the double-ring infiltrometer for five soil textures: clay loam, loam, sandy clay loam, clay, and sandy loam. Six infiltration models (Kostiakov, Modified Kostiakov, Revised Modified Kostiakov, Philip, Horton, and Novel) were employed and evaluated using statistical parameters. Model calibration and validation were conducted using data from 38 points within the study area. The parameter values of the infiltration models were optimized using SPSS statistical software using least-squares errors. The results showed that, Revised Modified Kostiakov, Modified Kostiakov, and Novel infiltration models demonstrated superior capability in estimating infiltration rates for clay loam, loam, and sandy loam soil textures, respectively. Horton's model outperformed other models in estimating infiltration rates for both sandy clay loam and clay soil textures. The appropriately fitted infiltration models can be utilized in designing the irrigation system to estimate the infiltration rate of soil textures within the selected irrigation scheme and at similar sites with comparable soil textures.
Accurate estimation of infiltration rates is crucial for effective irrigation system design and evaluation by optimizing irrigation scheduling, preventing soil erosion, and enhancing water use efficiency. This study evaluates and compares selected infiltration models for estimating water infiltration rates in the Shillanat-iv irrigation scheme in northern Ethiopia. Soil samples were collected to determine textural classes using hydrometer soil texture analysis and the United States Department of Agriculture (USDA) textural triangle. The soil textural map of the study was created using the inverse distance weight interpolation technique in ArcGIS version 10.4. Infiltration rates were measured using the double-ring infiltrometer for five soil textures: clay loam, loam, sandy clay loam, clay, and sandy loam. Six infiltration models (Kostiakov, Modified Kostiakov, Revised Modified Kostiakov, Philip, Horton, and Novel) were employed and evaluated using statistical parameters. Model calibration and validation were conducted using data from 38 points within the study area. The parameter values of the infiltration models were optimized using SPSS statistical software using least-squares errors. The results showed that, Revised Modified Kostiakov, Modified Kostiakov, and Novel infiltration models demonstrated superior capability in estimating infiltration rates for clay loam, loam, and sandy loam soil textures, respectively. Horton's model outperformed other models in estimating infiltration rates for both sandy clay loam and clay soil textures. The appropriately fitted infiltration models can be utilized in designing the irrigation system to estimate the infiltration rate of soil textures within the selected irrigation scheme and at similar sites with comparable soil textures.
Determination of infiltration capacity is a very important parameter during the design and evaluation of irrigation systems. Accurate estimation of infiltration rates helps in optimizing irrigation scheduling, preventing soil erosion, and improving water use efficiency. This study was conducted to evaluate and compare selected infiltration models for estimating water infiltration rates of five soil textures in the Shillanat-iv- irrigation scheme in northern Ethiopia. Soil samples were taken from selected sites in the irrigation scheme for determining soil textural classes using the hydrometer texture laboratory analysis and the USDA textural triangle. Soil textural map of the irrigation area was prepared using inverse distance weight interpolation technique in ArcGIS version 10.4. The double ring infiltrometer was used to measure the infiltration rates of different soil textures in the irrigation scheme. Six selected infiltration models namely Kostiakov, Modified Kostiakov, Revised Modified Kostiakov, Philip, Horton, and Novel models were used to estimate infiltration rates for five soil textural classes namely, clay loam, loam, sandy clay loam, clay and sandy loam soils. To evaluate the performance of the models, infiltration rate was measured in 38 points of the study area, out of which 70% of the data was calibrating model parameters and 30% of the data was used for model validation. Parameters values of the infiltration models were optimized using the least-squares errors in SPSS statistical software. Five statistical parameters including the Coefficient of determination (R2), Maximum absolute error (MAE), Bias, Root mean square error (RMSE) and Percentage average error (PAE) were used to evaluate the performance of the infiltration models. Results indicated that the Revised Modified Kostiakov’s, Modified Kostiakov’s, and Novel’s infiltration models had better capability in estimating infiltration rates for clay loam, loam and sandy loam soil textures respectively. Similarly, the Hortons’s model had better performances in estimating infiltration rates of both sandy clay loam and clay soil textures compared to other models. In the design of the irrigation system, the best fitted infiltration models can be used for estimating the infiltration rate of soil textures in the selected irrigation scheme and other sites with similar soil textures.
Determination of infiltration capacity is a very important parameter during the design and evaluation of irrigation systems. Accurate estimation of infiltration rates helps in optimizing irrigation scheduling, preventing soil erosion, and improving water use efficiency. This study was conducted to evaluate and compare selected infiltration models for estimating water infiltration rates of five soil textures in the Shillanat-iv- irrigation scheme in northern Ethiopia. Soil samples were taken from selected sites in the irrigation scheme to determine soil textural classes using the hydrometer texture laboratory analysis and the USDA textural triangle. A soil textural map of the irrigation area was prepared using the inverse distance weight interpolation technique in ArcGIS version 10.4. The double-ring infiltrometer was used to measure the infiltration rates of different soil textures in the irrigation scheme. Six selected infiltration models namely Kostiakov, Modified Kostiakov, Revised Modified Kostiakov, Philip, Horton, and Novel models were used to estimate infiltration rates for five soil textural classes namely, clay loam, loam, sandy clay loam, clay and sandy loam soils. To evaluate the performance of the models, infiltration rate was measured in 38 points of the study area, out of which 70% of the data was calibrating model parameters and 30% of the data was used for model validation. Parameter values of the infiltration models were optimized using the least-squares errors in SPSS statistical software. Five statistical parameters including the Coefficient of determination (R2), Maximum absolute error (MAE), Bias, Root mean square error (RMSE) and Percentage average error (PAE) were used to evaluate the performance of the infiltration models. Results indicated that the Revised Modified Kostiakov’s, Modified Kostiakov’s, and Novel’s infiltration models had better capability in estimating infiltration rates for clay loam, loam and sandy loam soil textures respectively. Similarly, the Hortons’s model had better performances in estimating infiltration rates of both sandy clay loam and clay soil textures compared to other models. In the design of the irrigation system, the best-fitted infiltration models can be used for estimating the infiltration rate of soil textures in the selected irrigation scheme and other sites with similar soil textures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.