L-band passive microwave remote sensing is currently considered a robust technique for global monitoring of soil moisture. However, soil roughness complicates the relationship between brightness temperature and soil moisture, with current soil moisture retrieval algorithms typically assuming a constant roughness parameter globally, leading to a potential degradation in retrieval accuracy. This current investigation established a tower-based experiment site in Victoria, Australia. P-band (~40-cm wavelength/0.75 GHz) was compared with L-band (~21-cm wavelength/1.41 GHz) over random and periodic soil surfaces to determine if there is an improvement in brightness temperature simulation and soil moisture retrieval accuracy for bare soil conditions, due to reduced roughness impact when using a longer wavelength. The results showed that P-band was less impacted by random and periodic roughness than L-band, evidenced by more comparable statistics across different roughness conditions. The roughness effect from smooth surfaces (e.g., 0.8-cm root-mean-square height and 11.1-cm correlation length) could be potentially ignored at both P- and L-band with satisfactory simulation and retrieval performance. However, for rougher soil (e.g., 1.6-cm root-mean-square height and 6.8-cm correlation length), the roughness impact needed to be accounted for at both P- and L-band, with P-band observations showing less impact than L-band. Moreover, a sinusoidal soil surface with 10-cm amplitude and 80-cm period substantially impacted the brightness temperature simulation and soil moisture retrieval at both P- and L-band, which could not be fully accounted for using the SMOS and SMAP default roughness parameters. However, when retrieving roughness parameters along with soil moisture, the ubRMSE at P-band over periodic soil was improved to a similar level (0.01‐0.02 m³/m³) as that of smooth flat soil (0.01 m³/m³), while L-band showed higher ubRMSE over the periodic soil (0.03‐0.04 m³/m³) than over smooth flat soil (0.01 m³/m³). Accordingly, periodic roughness effects were reduced by using observations at P-band.

L 波段无源微波遥感目前被认为是全球土壤水分监测的有力技术。然而，土壤粗糙度使亮温和土壤水分之间的关​​系变得复杂，当前的土壤水分反演算法通常假设全局粗糙度参数恒定，导致反演精度的潜在下降。目前的调查在澳大利亚维多利亚建立了一个基于塔的实验场地。将 P 波段（~40 厘米波长/0.75 GHz）与随机和周期性土壤表面上的 L 波段（~21 厘米波长/1.41 GHz）进行比较，以确定亮温模拟和土壤水分反演是否有改进由于使用较长波长时粗糙度影响减小，因此对裸土条件的准确性。结果表明，与 L 波段相比，P 波段受随机和周期性粗糙度的影响较小，不同粗糙度条件下更具可比性的统计数据证明了这一点。光滑表面的粗糙度影响（例如，0.8 厘米均方根高度和 11.1 厘米相关长度）在 P 和 L 波段都可能被忽略，并具有令人满意的模拟和检索性能。然而，对于较粗糙的土壤（例如，1.6 厘米均方根高度和 6.8 厘米相关长度），需要同时考虑 P 和 L 波段的粗糙度影响，P 波段观测显示影响较小比L波段。此外，振幅为 10 厘米、周期为 80 厘米的正弦土壤表面显着影响了 P 和 L 波段的亮温模拟和土壤水分反演，使用 SMOS 和 SMAP 默认粗糙度参数无法完全说明这一点。然而，当检索粗糙度参数和土壤水分时，周期性土壤上 P 波段的 ubRMSE 提高到相似的水平（0.01-0.02 m³ /m ³ ) 与光滑平坦土壤 (0.01 m ³ /m ³ ) 相同，而 L 波段在周期性土壤 (0.03-0.04 m ³ /m ³ ) 上的ubRMSE高于光滑平坦土壤 (0.01 m ^{3 )} /米³）。因此，通过使用 P 波段的观察减少了周期性粗糙度影响。