## 5 Discussion  
### Drought Monitoring Capability of TVMPDI in Southeastern Tibet  
In the southeast of TAR, the TVMPDI was moderately correlated with the SPEL which was similar to the correlation between the TVPDI and SPEI [28]. When these drought indexes are positively correlated with the TVPDI, their monitoring results are consistent. This strong positive correlation implies that the TVMPDI can describe the dryness of the atmosphere in the study area. The authors of [18] showed that alternations  
Figure 8: Simulation drought distribution by three models from May to July 2009 and 2010: (**a**) drought simulation in May 2009; (**b**) drought simulation in June 2009; (**c**) drought simulation in July 2009; (**d**) drought simulation in May 2010; (**e**) drought simulation in June 2010; (**f**) drought simulation in July 2009. Figure 7: Spatial distribution of the TVMPDI trend level from 2003 to 2018; (**a**) interannual variation; (**b**) variation in March; (**c**) variation in June; (**d**) variation in September; (**e**) variation in December. between precipitation and evapotranspiration depend on the altitude blazon and the time of fondescence, becoming increasingly divided in the altered regions. However, drought conditions on the QTP, where the study area is located, are also affected by its altitude. Global warming is melting glaciers, which will increase groundwater at lower altitudes in the study area [33]. Glaciers are a different antecedent of drought-resistant water brought about by special terrain. They are lowering dry season resistance, and investigations on this phenomenon are still rare [53]. Therefore, the analysis of glaciers regarding drought in lower reach of regions could be included in future research plans, as it can help us to better understand the process of this drought pattern, and thus provide guidance for the development of drought resistance strategies. In addition, the TVMPDI has a general correlation with the TVPDI and SMCI, which may be because the TVMPDI adds soil information on the basis of the TVPDI. Generally, agricultural drought index based on soil moisture can represent the available water for plants in the region. For example, SMCI believes that drought patterns are based on the available water content in the soil [54], but the TVMPDI adds atmospheric information, such as precipitation and temperature, which makes them less relevant than other drought indices. Due to the complex reaction between soil and atmospheric moisture, it seems impossible to directly express plant water stress and atmospheric drought at the same time [55; 5]. However, the TVMPDI, a new remote sensing index combined with SM, has a good correlation with other drought indexes. Due to the joint characteristics of soil and climate balance, the TVMPDI can capture the changes in SM and atmospheric dryness at the same time. This indicates that the TVMPDI is of great significance in delineating droughts. In Figure 3c, the temporal correlation between drought and the SMCI shows an east-west gradient change, which is due to the different drought patterns in the east and west. The eastern part has more precipitation, which is generally attributed to the abnormal precipitation, while the western part is more affected by temperature. Both of these change soil moisture in the region and cause drought. [PERSON] et al. [56] compared the spatial correlation of various drought indices at different time scales and found that drought in arid and humid regions of the United States had similar east-west gradients. As can be seen from Figure 5, the correlation between TVMPDI and meteorological drought index (SPI and SPI) was not as good as that between TVPI and them, while the correlation between TVMPDI and GPP, which represents agricultural drought, was better than that between TVPI and GPP.