Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows
A suitable nitrogen (N) application rate (NAR) and ideal planting period could improve upland rice productivity, enhance the soil water utilization, and reduce N losses. This study was conducted for the assessment and application of the EPIC model to simulate upland rice productivity, soil water, an...
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MDPI AG
2023-09-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/13/9/2379 |
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| author | Tajamul Hussain Hero T. Gollany David J. Mulla Zhao Ben Muhammad Tahir Syed Tahir Ata-Ul-Karim Ke Liu Saliha Maqbool Nurda Hussain Saowapa Duangpan |
| author_facet | Tajamul Hussain Hero T. Gollany David J. Mulla Zhao Ben Muhammad Tahir Syed Tahir Ata-Ul-Karim Ke Liu Saliha Maqbool Nurda Hussain Saowapa Duangpan |
| author_sort | Tajamul Hussain |
| collection | DOAJ |
| description | A suitable nitrogen (N) application rate (NAR) and ideal planting period could improve upland rice productivity, enhance the soil water utilization, and reduce N losses. This study was conducted for the assessment and application of the EPIC model to simulate upland rice productivity, soil water, and N dynamics under different NARs and planting windows (PWs). The nitrogen treatments were 30 (N30), 60 (N60), and 90 (N90) kg N ha<sup>−1</sup> with a control (no N applied −N0). Planting was performed as early (PW1), moderately delayed (PW2), and delayed (PW3) between September and December of each growing season. The NAR and PW impacted upland rice productivity and the EPIC model predicted grain yield, aboveground biomass, and harvest index for all NARs in all PWs with a normalized good–excellent root mean square error (RMSEn) of 7.4–9.4%, 9.9–12.2%, and 2.3–12.4% and <i>d</i>-index range of 0.90–0.98, 0.87–0.94, and 0.89–0.91 for the grain yield, aboveground biomass, and harvest index, respectively. For grain and total plant N uptake, RMSEn ranged fair to excellent with values ranging from 10.3 to 22.8% and from 6.9 to 28.1%, and a <i>d</i>-index of 0.87–0.97 and 0.73–0.99, respectively. Evapotranspiration was slightly underestimated for all NARs at all PWs in both seasons with excellent RMSEn ranging from 2.0 to 3.1% and a <i>d</i>-index ranging from 0.65 to 0.97. A comparison of N and water balance components indicated that PW was the major factor impacting N and water losses as compared to NAR. There was a good agreement between simulated and observed soil water contents, and the model was able to estimate fluctuations in soil water contents. An adjustment in the planting window would be necessary for improved upland rice productivity, enhanced N, and soil water utilization to reduce N and soil water losses. Our results indicated that a well-calibrated EPIC model has the potential to identify suitable N and seasonal planting management options. |
| first_indexed | 2024-03-10T23:07:21Z |
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| id | doaj.art-5bd5781330ab4c8a8e946aee83097c97 |
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| language | English |
| last_indexed | 2024-03-10T23:07:21Z |
| publishDate | 2023-09-01 |
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| spelling | doaj.art-5bd5781330ab4c8a8e946aee83097c972023-11-19T09:11:27ZengMDPI AGAgronomy2073-43952023-09-01139237910.3390/agronomy13092379Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting WindowsTajamul Hussain0Hero T. Gollany1David J. Mulla2Zhao Ben3Muhammad Tahir4Syed Tahir Ata-Ul-Karim5Ke Liu6Saliha Maqbool7Nurda Hussain8Saowapa Duangpan9Agricultural Innovation and Management Division, Faculty of Natural Resources, Prince of Songkla University, Hat Yai 90112, Songkhla, ThailandUnited States Department of Agriculture, Agricultural Research Service (USDA-ARS), Columbia Plateau Conservation Research Center, Pendleton, OR 97810, USADepartment of Soil, Water, & Climate, University of Minnesota, 506 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN 55108, USAAgricultural Innovation and Management Division, Faculty of Natural Resources, Prince of Songkla University, Hat Yai 90112, Songkhla, ThailandDepartment of Soil, Water, & Climate, University of Minnesota, 506 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN 55108, USAGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo 113-8654, JapanTasmanian Institute of Agriculture, University of Tasmania, Newnham Drive, Launceston, TAS 7248, AustraliaDepartment of Soil, Water, & Climate, University of Minnesota, 506 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN 55108, USAAgricultural Innovation and Management Division, Faculty of Natural Resources, Prince of Songkla University, Hat Yai 90112, Songkhla, ThailandAgricultural Innovation and Management Division, Faculty of Natural Resources, Prince of Songkla University, Hat Yai 90112, Songkhla, ThailandA suitable nitrogen (N) application rate (NAR) and ideal planting period could improve upland rice productivity, enhance the soil water utilization, and reduce N losses. This study was conducted for the assessment and application of the EPIC model to simulate upland rice productivity, soil water, and N dynamics under different NARs and planting windows (PWs). The nitrogen treatments were 30 (N30), 60 (N60), and 90 (N90) kg N ha<sup>−1</sup> with a control (no N applied −N0). Planting was performed as early (PW1), moderately delayed (PW2), and delayed (PW3) between September and December of each growing season. The NAR and PW impacted upland rice productivity and the EPIC model predicted grain yield, aboveground biomass, and harvest index for all NARs in all PWs with a normalized good–excellent root mean square error (RMSEn) of 7.4–9.4%, 9.9–12.2%, and 2.3–12.4% and <i>d</i>-index range of 0.90–0.98, 0.87–0.94, and 0.89–0.91 for the grain yield, aboveground biomass, and harvest index, respectively. For grain and total plant N uptake, RMSEn ranged fair to excellent with values ranging from 10.3 to 22.8% and from 6.9 to 28.1%, and a <i>d</i>-index of 0.87–0.97 and 0.73–0.99, respectively. Evapotranspiration was slightly underestimated for all NARs at all PWs in both seasons with excellent RMSEn ranging from 2.0 to 3.1% and a <i>d</i>-index ranging from 0.65 to 0.97. A comparison of N and water balance components indicated that PW was the major factor impacting N and water losses as compared to NAR. There was a good agreement between simulated and observed soil water contents, and the model was able to estimate fluctuations in soil water contents. An adjustment in the planting window would be necessary for improved upland rice productivity, enhanced N, and soil water utilization to reduce N and soil water losses. Our results indicated that a well-calibrated EPIC model has the potential to identify suitable N and seasonal planting management options.https://www.mdpi.com/2073-4395/13/9/2379yieldevapotranspirationrunoffN mineralizationnitrate leachingvolatilization |
| spellingShingle | Tajamul Hussain Hero T. Gollany David J. Mulla Zhao Ben Muhammad Tahir Syed Tahir Ata-Ul-Karim Ke Liu Saliha Maqbool Nurda Hussain Saowapa Duangpan Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows Agronomy yield evapotranspiration runoff N mineralization nitrate leaching volatilization |
| title | Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows |
| title_full | Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows |
| title_fullStr | Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows |
| title_full_unstemmed | Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows |
| title_short | Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows |
| title_sort | assessment and application of epic in simulating upland rice productivity soil water and nitrogen dynamics under different nitrogen applications and planting windows |
| topic | yield evapotranspiration runoff N mineralization nitrate leaching volatilization |
| url | https://www.mdpi.com/2073-4395/13/9/2379 |
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