Bhuyan Md Isfatuzzaman, Supit Iwan, Mia Shamim, Mulder Martin, Ludwig Fulco
Water Systems and Global Change Group, Wageningen University and Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands.
Department of Agronomy, Faculty of Agriculture, Patuakhali Science and Technology University, Patuakhali 8602, Bangladesh.
Heliyon. 2023 Aug 19;9(8):e19180. doi: 10.1016/j.heliyon.2023.e19180. eCollection 2023 Aug.
Salinity varies with location and time of the year. It can significantly impact crop production. The level of negative impacts depends on the salt concentration and time of its occurrence, which, however, has not been studied for many crops, especially for rice grown in the coastal area of Bangladesh. Our study explored the impact of spatio-temporal fluctuations in soil and water salinity on rice production in the south-central coast of Bangladesh. Here, we simulated the soil salinity from November 2020 to May 2021 for fourteen locations classes using the SWAP-WOFOST model. The model was calibrated and validated with measured secondary data. Next, the yield of two salt-tolerant rice varieties ( and ) was simulated using the customized soil, weather, and crop data. We also simulated the yield by adopting agronomic management practices ( changing planting time and using fresh irrigation water). Our results showed that salinity levels varied with different soil textural classes, soil depth, location, and time of the year, and that had a significant influence on rice production, giving spatial variability. Specifically, rice had a higher yield in coarse texture soil than in fine texture soil. Simulated yields in areas proximate to the sea ranged from 668 to 1239 kg ha, yields that are significantly lower than those simulated in moderate (2098-4843 kg ha) and low salinity zones (4213-4843 kg ha). Moreover, the simulation of yield with sowing/planting rice earlier by fifteen days provided a higher yield than the current planting practice since it could avoid salinity at later stages of growth. For a similar reason, growing rice inside the polder provided a higher yield than outside the polder. The insights gained from our study carry significant implications for contemporary crop-level adaptation strategies and policy-making in coastal districts.
盐度随地点和一年中的时间而变化。它会对作物产量产生重大影响。负面影响的程度取决于盐分浓度及其出现的时间，然而，对于许多作物，尤其是孟加拉国沿海地区种植的水稻，尚未对此进行研究。我们的研究探讨了土壤和水盐度的时空波动对孟加拉国中南部海岸水稻生产的影响。在此，我们使用SWAP-WOFOST模型模拟了2020年11月至2021年5月期间14个地点类别的土壤盐度。该模型通过实测的二级数据进行了校准和验证。接下来，使用定制的土壤、天气和作物数据模拟了两个耐盐水稻品种（和）的产量。我们还通过采用农艺管理措施（改变种植时间和使用新鲜灌溉水）来模拟产量。我们的结果表明，盐度水平因不同的土壤质地类别、土壤深度、地点和一年中的时间而异，并且对水稻生产有显著影响，呈现出空间变异性。具体而言，在质地较粗的土壤中种植的水稻产量高于质地较细的土壤。靠近大海地区的模拟产量在668至1239公斤/公顷之间，这些产量显著低于中度盐度区（2,098 - 4,843公斤/公顷）和低盐度区（4,213 - 4,843公斤/公顷）模拟的产量。此外，提前15天播种/种植水稻的产量模拟结果比当前的种植方式更高，因为这样可以避免生长后期的盐害。出于类似原因，在内圩内种植水稻的产量高于圩外。我们的研究获得的见解对沿海地区当代作物层面的适应策略和政策制定具有重要意义。
