The frequency and intensity of flood events have been increasing recently under the warming climate, with snowmelt floods being a significant part. As an effective manner of simulating snowmelt flood, snowmelt models have attracted more and more attention. Through comprehensive analysis of the literature, this paper reviewed the characteristics and current status of different types of snowmelt models, as well as the different coupling methods of models for runoff generation and confluence. We then discussed key issues in snowmelt modelling, including blowing snow model, frozen ground model, and rain-on-snow model. Finally, we give some perspectives from four aspects: data, model structure, forecast and early warning, and forecast and estimation. At present, most of the snowmelt models do not have blowing snow or frozen ground modules. Explicit consideration of blowing snow and soil freezing/thawing processes can improve the accuracy of snowmelt runoff simulations. With climate warming, rain-on-snow events have increased, but the mechanism of enhanced rain and snow mixed flooding is still unclear, particularly for the mechanism of rain-snow-ice mixed runoff generation. The observation and simulation of rain and snow processes urgently need further study. A distributed physical snowmelt model based on energy balance is an advanced tool for snowmelt simulation, but the model structure and parameter schemes still need further improvements. Moreover, the integration of satellite-based snow products, isotopes, and terrestrial water storage change, monitored by gravity satellites, can help improve the calibration and validation of snowmelt models.
Evaluation of the long-term effect of ecosystem recovery projects is critical for future ecological management and sustainable development. The Three-North Shelterbelt (TNS) is a large-scale afforestation project in a crucial region of China. Numerous researchers have evaluated the vegetation ecological quality (VEQ) of the TNS using a single vegetation indicator. However, vegetation ecosystems are complex and need to be evaluated through various indicators. We constructed the vegetation ecological quality index (VEQI) by downscaling net primary productivity, leaf area index, fractional vegetation cover, land surface temperature, vegetation moisture, and water use efficiency of vegetation. The spatiotemporal characteristics and main contributing factors of VEQ in the TNS from 2000 to 2020 were investigated using SEN+Mann‒Kendall, Hurst exponent, geographical detector, and residual trend analysis testing. The results suggest that VEQ in the TNS showed an improving trend over the 21-year study period. The areas with significant improvements were concentrated in the central and eastern parts of the TNS. Significant deterioration occurred only sporadically in various urban areas. Characteristics of future unsustainable VEQ trends could be detected across the TNS. Precipitation, vegetation type, soil type, elevation, and solar radiation exhibited the greatest impact on VEQ throughout the TNS. Human activities (e.g., afforestation and government investments) were the dominant factors and had a relative contribution of 65.24% to vegetation area change. Our results provide clues for assessing environmental recovery and sustainable development in other regions.
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