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Spatio-temporal variability of soil moisture in a cropped agricultural plot within the Ganga Basin, India
Agricultural Water Management ( IF 5.9 ) Pub Date : 2020-05-01 , DOI: 10.1016/j.agwat.2020.106108
Ephrem Yetbarek , Richa Ojha

Abstract Soil moisture dynamics in response to rainfall and irrigation events were examined using data obtained from continuous point measurements carried out under rice and wheat crops for an agricultural plot located within the Ganga Basin, India. Soil moisture data were collected using SM100 and SMEC300 sensors at 18 subplots and at four different depths (0−80 cm) during the period from 5 August 2018 to 31 March 2019. Soil moisture was decomposed into temporal mean and temporal anomalies components, and its variability was characterized considering both absolute soil moisture and temporal anomalies. They exhibited similar patterns at all the depths under rice crop cover. However, it varies with depth under wheat crop cover due to periodic wetting and drying conditions and temporally variable atmospheric demand. Similarly, the spatial variance of absolute soil moisture was decomposed into time-invariant and time-variant components. The results revealed that the time-invariant component contribution was dominant at all the depths (72.49–101.46 %) and the contribution of each component varies with soil wetness and land cover. In addition, temporal stability analysis of soil moisture was carried out. It was observed that the spatial pattern at surface depth cannot be preserved for subsurface depths, and similar subplots were found to be temporally stable at the surface and bottom depths under different crop covers. The results are expected to help improve the understanding of the nature of soil water dynamics in agricultural fields.

中文翻译:

印度恒河盆地耕地土壤水分的时空变异性

摘要 使用从水稻和小麦作物下对印度恒河盆地内的农田进行的连续点测量获得的数据,研究了响应降雨和灌溉事件的土壤水分动态。2018 年 8 月 5 日至 2019 年 3 月 31 日期间,使用 SM100 和 SMEC300 传感器在 18 个小区和四个不同深度(0-80 厘米)收集土壤水分数据。土壤水分被分解为时间平均和时间异常分量,及其考虑到绝对土壤水分和时间异常,变异性被表征。它们在水稻作物覆盖下的所有深度都表现出相似的模式。然而,由于周期性的干湿条件和随时间变化的大气需求,它随着小麦作物覆盖下的深度而变化。相似地,将土壤绝对水分的空间方差分解为时不变分量和时变分量。结果表明,时不变分量的贡献在所有深度(72.49-101.46%)都占主导地位,并且每个分量的贡献随土壤湿度和土地覆盖而变化。此外,还进行了土壤水分的时间稳定性分析。观察到地表深度的空间格局不能保留为地下深度,并且发现类似的子地块在不同作物覆盖下的地表和底部深度在时间上是稳定的。预计这些结果将有助于提高对农田土壤水动力学性质的理解。结果表明,时不变分量的贡献在所有深度(72.49-101.46%)都占主导地位,并且每个分量的贡献随土壤湿度和土地覆盖而变化。此外,还进行了土壤水分的时间稳定性分析。观察到地表深度的空间格局不能保留为地下深度,并且发现类似的子地块在不同作物覆盖下的地表和底部深度在时间上是稳定的。预计这些结果将有助于提高对农田土壤水动力学性质的理解。结果表明,时不变分量的贡献在所有深度(72.49-101.46%)都占主导地位,并且每个分量的贡献随土壤湿度和土地覆盖而变化。此外,还进行了土壤水分的时间稳定性分析。观察到地表深度的空间格局不能保留为地下深度,并且发现类似的子地块在不同作物覆盖下的地表和底部深度在时间上是稳定的。预计这些结果将有助于提高对农田土壤水动力学性质的理解。观察到地表深度的空间格局不能保留为地下深度,并且发现类似的子地块在不同作物覆盖下的地表和底部深度在时间上是稳定的。预计这些结果将有助于提高对农田土壤水动力学性质的理解。观察到地表深度的空间格局不能保留为地下深度,并且发现类似的子地块在不同作物覆盖下的地表和底部深度在时间上是稳定的。预计这些结果将有助于提高对农田土壤水动力学性质的理解。
更新日期:2020-05-01
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