潜在蒸散发（Potential Evapotranspiration, PET）是水文和能量循环的重要组成部分，对全球干旱研究、农业灌溉和水资源管理至关重要。水汽（Precipitable Water Vapor, PWV）是影响PET变化的主要驱动力之一，也是极端天气事件发生和演变的重要因素。近年来，全球导航卫星系统（Global Navigation Satellite System, GNSS）飞速发展，所获取的高精度、高时间分辨率水汽被广泛应用于改善站点PET精度。然而，现有面状PET获取方法并未充分利用水汽优势。因此，本文首先提出基于GNSS水汽的面状PET获取方法；然后，为了进一步改善面状PET精度，提出两步面状高精度PET融合方法，并探究该方法所获取的PET及标准化降水蒸散发指数（Standardized Precipitation Evapotranspiration Index, SPEI）在干旱监测方面的应用潜力。本文的主要研究内容如下：

（1）针对现有PET方法未利用水汽优势来获取面状PET的缺陷，提出基于GNSS水汽获取面状PET的方法（HPET）。首先，基于GNSS反演的PWV，对ERA-Interim所提供的格网PWV进行校正；其次，在并址站上分析了桑斯维特（Thornthwaite, TH）和彭曼（Penman-Monteith, PM）方法反演PET的差值和PWV/温度（Temperature, T）间存在的关系；最后，根据所判断的分段线性关系在站点建模，并根据多项式方法将站点模型系数拟合至整个区域，从而获取面状PET。本文提出的HPET方法为利用水汽反演面状PET提供了新手段，同时为后续面状高精度PET的获取提供了理论依据。

（2）针对HPET方法获取面状PET精度仍有待进一步改善的现状，提出两步面状高精度PET融合方法（MPF）。首先，基于HPET方法计算不同空间分辨率的格网PET；其次，综合考虑位置、PWV和T确定PET的建模项和方程；最后，通过赫尔默特方差分量估计方法确定格网和站点PET数据的最优权比，进一步获取高精度面状PET，为后续干旱监测研究提供了数据支持。

（3）由于黄土高原的独特地貌和生态环境脆弱特征，选择黄土高原对MPF方法进行应用分析。首先，根据HPET和MPF方法分别计算黄土高原站点和区域上的PET和SPEI，以及其他三种常用的干旱指数：标准化降水指数（Standardized Precipitation Index, SPI）、降水平滑指数（Precipitation Smoothing Index, PSI）、标准化降水转换指数（Standardized Precipitation Conversion Index, SPCI）；其次，在黄土高原的84个气象站分别对PM、TH、HPET和MPF模型反演的SPEI的长时序和空间变化进行应用分析，并计算站点MPF模型反演的SPEI与SPI、PSI、SPCI三种干旱指数的相关系数；最后，在黄土高原对TH、HPET和MPF模型反演的面状SPEI分别进行特定时间多尺度和长时序单/多尺度应用分析。相对于传统TH模型，MPF模型所反演SPEI的RMS改善率在1、3、6和12月尺度分别为64.3%、69.0%、68.1%和8.2%。证明了本文提出的MPF方法反演的SPEI能有效应用于干旱监测，具有良好的鲁棒性和适用性，为干旱监测提供了新方法。

Potential Evapotranspiration (PET) is a crucial component of the hydrological and energy cycles, which is crucial for global drought research, agricultural irrigation, and water resource management. Precipitable Water Vapor (PWV) is a major driver of PET variations and a significant factor in the occurrence and evolution of extreme weather events. In recent years, the rapid development of the Global Navigation Satellite System (GNSS) has led to the widespread application of high-precision, high-temporal resolution PWV to improve the accuracy of station-based PET. However, existing surface-based PET acquisition methods have not fully utilized the advantages of PWV. Therefore, this study first proposes a method for obtaining surface-based PET based on GNSS-derived PWV. Subsequently, to further enhance the accuracy of surface-based PET, a two-step surface-based high-precision PET fusion method (MPF) is proposed, and the application of PET and the Standardized Precipitation Evapotranspiration Index (SPEI) obtained through this method in drought monitoring is explored. The main research contents of this paper are as follows:

(1) Aiming at the defect that the existing PET method underutilization the advantage of water vapor to obtain surface-based PET, a method for obtaining surface-based PET based on GNSS-derived PWV (HPET) is proposed. Firstly, the grid-based PWV provided by ERA-Interim is corrected using GNSS-derived PWV. Secondly, the relationship between the PWV/ Temperature (T) and PET differences by Thornthwaite (TH) and Penman-Monteith (PM) methods is analyzed on the collocated stations. Finally, models are established in stations based on the identified piecewise linear relationship, and the coefficients of these models are fitted to the whole region using polynomial method, so as to obtain surface-based PET. The HPET method proposed in this study provides a novel method for obtaining surface-based PET using GNSS-derived PWV and serves a theoretical basis for the subsequent acquisition of surface-based high-precision PET.

(2) Aiming at the current situation where the accuracy of surface-based PET obtained using the HPET method still needs further improvement, a two-step surface-based high-precision PET fusion method (MPF) is proposed. Firstly, HPET-derived PET is obtained at different spatial resolutions. Secondly, the modeling data and equations of PET are determined by comprehensively considering factors such as location, PWV, and T. Finally, the optimal weight ratio between grid-, and station-based PET is determined through the Helmert variance component estimation method, enabling the further acquisition of high-precision surface-based PET, which provides data support for subsequent drought monitoring studies.

(3) Aiming at the unique geomorphology and fragile ecological environment of the Loess Plateau, this region is selected for the application analysis of the MPF method. Firstly, HPET- and MPF-derived PET and SPEI at stations and grid points on the Loess Plateau were calculated, compared with other three commonly used drought indices: the Standardized Precipitation Index (SPI), Precipitation Smoothing Index (PSI), and Standardized Precipitation Conversion Index (SPCI). Secondly, long temporal and spatial variations PM-, TH-, HPET-, and MPF-derived SPEI are analyzed at 84 meteorological stations on the Loess Plateau. The correlation coefficients between MPF-derived SPEI and the three drought indices of SPI, PSI, and SPCI are also calculated at stations. Finally, the TH-, HPET-, and MPF-derived SPEI are analyzed for specific time at multiple scales and long-term single/multi-scale applications on the Loess Plateau. The RMS improvement rates of SPEI calculated using the MPF-derived PET are 64.3%, 69.0%, 68.1%, and 8.2%, respectively, when compared with the TH-derived SPEI at 1-, 3-, 6-, and 12-month scales, respectively. It is found that the MPF-derived SPEI in this study can be effectively applied to drought monitoring, demonstrating good robustness and applicability, and providing a new method for drought monitoring.

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