Climate change and instrumental disturbance make accurate identification of hydrometeorological period challenging. This study presents the hierarchical discrete-continuous wavelet decomposition (HDCWD) model to identify period with considering climate and instrumental disturbance. The method provides a three-layer identification framework of detrending, denoising and mining by combining discrete wavelet transform and continuous wavelet transform. The dominating periods and their spatiotemporal features of precipitation in the Yellow River Basin are identified by HDCWD. Results show the following: (1) Precipitation in the Yellow River Basin has the dominating periods of 2–4 years and 7–9 years (1956–1984), and period of 2 years from (1998–2002). (2) The periods of catchments in higher latitude exhibit longer and those in the lower east exhibit shorter. The results illustrate that although the precipitation in the Yellow River Basin differs in space and time, there is a certain evolution law. The results can provide information for water resources management.

中文翻译：

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考虑气候和仪器干扰的黄河流域降水时空变化


气候变化和仪器扰动给水文气象周期的准确识别带来了挑战。本研究提出了分层离散连续小波分解（HDCWD）模型来识别考虑气候和仪器干扰的时期。该方法结合离散小波变换和连续小波变换，提供了去趋势、去噪和挖掘的三层识别框架。利用HDCWD识别了黄河流域降水的主导时段及其时空特征。结果表明：（1）黄河流域降水的主导期为2~4年和7~9年（1956~1984年），2年为主导期（1998~2002年）。 (2)高纬度流域的周期较长，低东流域的周期较短。结果表明，黄河流域降水虽然存在时空差异，但存在一定的演化规律。研究结果可为水资源管理提供信息。