Selection of alfalfa water and nitrogen management regimes based on the DSSAT model
Abstract Forage crop production globally faces challenges of low water and nitrogen use efficiency alongside increased environmental pressures, particularly in arid and semi-arid regions. The Hetao Irrigation District, a representative area of such regions, is characterized by limited rainfall, high...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-92058-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Forage crop production globally faces challenges of low water and nitrogen use efficiency alongside increased environmental pressures, particularly in arid and semi-arid regions. The Hetao Irrigation District, a representative area of such regions, is characterized by limited rainfall, high evaporation, insufficient water, and severe soil salinization, which significantly hinder agricultural development. The findings from this study not only address local challenges but also provide insights applicable to other regions facing similar climatic and environmental constraints. This study aimed to optimize water and nitrogen management strategies for alfalfa production in the Hetao Irrigation District by calibrating and validating the DSSAT-FORAGES-Alfalfa model using field experimental data collected during 2022–2023. The calibration involved adjusting key parameters to minimize discrepancies between simulated and observed values, and validation was performed using an independent dataset, evaluated based on metrics such as MAE, RMSE, and R2. The novelty of this research lies in its comprehensive calibration and validation process, which provides a robust framework for simulating alfalfa growth under diverse management scenarios. Various management scenarios were simulated, including six nitrogen application rates (0, 50, 100, 150, 200, and 250 kg ha−1) and seven irrigation levels (45, 55, 65, 75, 85, 95, and 105 mm), to comprehensively evaluate their impacts on alfalfa yield and quality. These scenarios were designed to cover a wide range of practices, from deficit to excessive irrigation and fertilization, providing a robust assessment of optimal management strategies. Results indicated high predictive accuracy, with all performance metrics (e.g., MAE, RMSE, and R2) demonstrating the model’s reliability in simulating alfalfa growth under varying management conditions. Specifically, the normalized RMSE was below 10%, and the coefficient of determination (R2) exceeded 0.9, confirming the model’s robustness. Optimal management involving 260–340 mm of irrigation and 100–150 kg ha−1 nitrogen application over the full growth cycle not only maximizes water use efficiency, but also achieves over 9% water saving and more than 25% reduction in nitrogen fertilizer application, compared to traditional local practices. These findings demonstrate the potential of optimized management strategies to significantly reduce ecological pressures while maintaining high crop productivity. |
|---|---|
| ISSN: | 2045-2322 |