Evaluation and simulation of spatial variability of soil property effects on deep percolation and nitrate leaching within a large-scale field in arid Northwest China
Copyright © 2020 Elsevier B.V. All rights reserved..
Variability of soil properties within large-scale fields not only exists in the horizontal domain, but also in the vertical direction, causing spatial variability in yield. Three yield zones were delineated based on measured yield in 2017 and 2018 within a large field in northwest China. The Soil Water Heat Carbon Nitrogen Simulator (WHCNS) model was calibrated and used to simulate yield, nitrogen uptake (Nu), water use efficiency (WUE), fertilizer N (nitrogen) use efficiency (FNUE), deep percolation (DP), nitrate leaching (NL) and residual nitrate (RN) at each sampling point in different yield zones. Based on the simulations, there were significant differences in Nu, WUE, FNUE, DP, NL and RN in 0-100 cm and 100-160 cm soil layers among the three yield zones. DP, NL and RN in the layers were strongly determined by the interaction of zone and year (p < 0.05), thus yielding consistent patterns mainly determined by soil properties and meteorological factors. The modelled ranges of DP, NL, and RN (0-160 cm) were 25-119 mm, 15-94 kg ha-1, and 178-476 kg·ha-1 respectively, across the field. Soil texture in the maize main root zone (0-100 cm) has a great influence on yield and Nu, and in the 100-160 cm layer upon DP and NL. RN was abundant after harvest and should be taken into account to determine the nitrogen fertilization demand for the following crop. The study showed that the process of delineating zones can be based on historical yield, making it feasibly easier than mapping soil properties. In view of the fact that there were large losses of water and nitrogen with uniform irrigation and fertilization management, the effects of vertically variable soil properties should be considered in future precision agriculture research, to achieve higher economic benefits and utilization efficiency.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:732 |
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| Enthalten in: |
The Science of the total environment - 732(2020) vom: 25. Aug., Seite 139324 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Chen, Shichao [VerfasserIn] |
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| Links: |
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| Themen: |
Deep percolation |
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| Anmerkungen: |
Date Completed 12.06.2020 Date Revised 12.06.2020 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.scitotenv.2020.139324 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM310204194 |
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| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Copyright © 2020 Elsevier B.V. All rights reserved. | ||
| 520 | |a Variability of soil properties within large-scale fields not only exists in the horizontal domain, but also in the vertical direction, causing spatial variability in yield. Three yield zones were delineated based on measured yield in 2017 and 2018 within a large field in northwest China. The Soil Water Heat Carbon Nitrogen Simulator (WHCNS) model was calibrated and used to simulate yield, nitrogen uptake (Nu), water use efficiency (WUE), fertilizer N (nitrogen) use efficiency (FNUE), deep percolation (DP), nitrate leaching (NL) and residual nitrate (RN) at each sampling point in different yield zones. Based on the simulations, there were significant differences in Nu, WUE, FNUE, DP, NL and RN in 0-100 cm and 100-160 cm soil layers among the three yield zones. DP, NL and RN in the layers were strongly determined by the interaction of zone and year (p < 0.05), thus yielding consistent patterns mainly determined by soil properties and meteorological factors. The modelled ranges of DP, NL, and RN (0-160 cm) were 25-119 mm, 15-94 kg ha-1, and 178-476 kg·ha-1 respectively, across the field. Soil texture in the maize main root zone (0-100 cm) has a great influence on yield and Nu, and in the 100-160 cm layer upon DP and NL. RN was abundant after harvest and should be taken into account to determine the nitrogen fertilization demand for the following crop. The study showed that the process of delineating zones can be based on historical yield, making it feasibly easier than mapping soil properties. In view of the fact that there were large losses of water and nitrogen with uniform irrigation and fertilization management, the effects of vertically variable soil properties should be considered in future precision agriculture research, to achieve higher economic benefits and utilization efficiency | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Deep percolation | |
| 650 | 4 | |a Fertilizer N use efficiency | |
| 650 | 4 | |a Nitrate leaching | |
| 650 | 4 | |a Residual nitrate | |
| 650 | 4 | |a Spatial variability of soil texture | |
| 650 | 4 | |a Water use efficiency | |
| 700 | 1 | |a Du, Taisheng |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Sufen |e verfasserin |4 aut | |
| 700 | 1 | |a Parsons, David |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Di |e verfasserin |4 aut | |
| 700 | 1 | |a Guo, Xiuwei |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Donghao |e verfasserin |4 aut | |
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