In a changing environment, changes in terrestrial water storage (TWS) in basins have a significant impact on potential floods and affect flood risk assessment. Therefore, we aimed to study the impact of TWS on potential floods. In this study, we reconstructed the TWS based on precipitation and temperature, evaluated the reconstructed TWS data based on Gravity Recovery and Climate Experiment (GRACE)-TWS data, and analyzed and calculated the flood potential index (FPI) in the Yangtze River Basin (YRB). The related influencing factors were analyzed based on the Global Land Data Assimilation System (GLDAS) data and Granger’s causality test. The main conclusions are as follows: (1) although the GRACE-TWS anomaly (GRACE-TWSA) in the YRB showed an increasing trend for the averaged TWSA over all grids in the whole basin (i.e., 0.31 cm/a, p < 0.05), the variable infiltration capacity-soil moisture anomalies (VIC-SMA) showed a decreasing trend (i.e., −0.048 cm/a, p > 0.05) during April 2002–December 2019; (2) a larger relative contribution of detrended precipitation to FPI was found in the Jialingjiang River Basin (JRB), Wujiang River Basin (WRB), Dongting Lake Rivers Basin (DLRB), YinBin-Yichang reaches (YB-YC), and Yichang-Hukou reaches (YC-HK), while the contribution of detrended TWS to FPI in the Poyang Lake Rivers Basin (PLRB) was larger than that in other basins; and (3) the original and detrended soil moisture (SM) and TWS in the YRB showed a significant positive correlation (p < 0.05), while the significant effect of SM on TWS caused a change in FPI in the YRB and its sub-basins. This study is of great significance for the correct understanding of the FPI and the accurate assessment of flood risk.

Flash flood is a significant threat to those who live in China and beyond. Reproducing them with distributed hydrological models is an effective measure for preventing flash floods. This paper introduces the China flash flood hydrological model (CNFF-HM); explores its principles, key steps, and applicability; and validates its simulation effects in two typical, small ungauged catchments (UCs), namely, Tiezhuling and Qianyangxi. First, the applicability of the model and the portability of the parameters were verified in Qianyangxi. Then, in Tiezhuling, the model parameters were comprehensively determined based on the measured values and simulation results, and the influence of the reservoir on the simulation effect was analyzed. Using the model’s different parameters in different catchments, the characteristics of the basin were compared and analyzed from the aspects of evapotranspiration, runoff, water distribution, and confluence. Finally, the early warning effect was evaluated. The results indicated the following: (1) The reservoir has a significant impact on model simulation. (2) The two UCs have similarities in evapotranspiration, runoff, and water source, and the difference in convergence is obvious. (3) With better early warning effect, the warning can achieve full coverage. These positive results suggest that this method should be further developed and tested.

卫星降水产品因其覆盖范围广、时空连续性强，已广泛用于弥补地面站点覆盖率不足的问题，但在下垫面变化明显的区域仍存在系统性误差。现有降水校正方法未充分考虑土地利用等地表特征的影响，忽略了相邻站点间的空间自相关性，难以准确刻画区域地形和气候的空间异质性。论文通过融合土地利用类型、邻近站降水信息，以及传统气象因子(相对湿度、气温和风速)和地形因子(高程、经纬度)，构建了空间增强型XGBoost降水校正模型，并以海河流域为例进行应用研究。结果表明：XGBoost模型明显提升了IMERG卫星降水产品在海河流域山区和平原区的精度，校正降水的空间分布和日降水过程与气象站吻合较好，捕捉了局地强降水事件变化过程，降低了IMERG产品存在的系统性高估现象；土地利用对降水校正精度提升起主导作用(57.8%~66.7%)，邻近区域的土地利用、降水和气象因子等特征因子的贡献率高于单站局地信息，尤其是土地利用贡献率偏高9.7%~14.5%。研究可为区域降水校正模型改进和多源降水信息融合应用提供技术和信息支持。

准确辨识和预测山区小流域洪水行为变化特性对山洪灾害风险管理具有重要意义。论文以7个洪水行为特征指标刻画山洪事件的量级、时间、形态和变率特性，利用主成分分析、围绕中心点分区(partitioning around medoids，PAM)聚类算法、随机森林和五折交叉验证法相结合，辨识了典型山洪类型及其行为特性变化的驱动因素，评估了不同山洪类型行为特征指标的预测性能，并以不同水文气象和下垫面特征的6个山区小流域94场次山洪事件开展应用研究。结果表明：① 所有山洪事件可划分为3种典型山洪类型，即洪峰强度低、峰现早、峰腰宽、涨落洪快的类型(类型1，占50.0%)，峰现晚、过程不集中且变化平缓的类型(类型2，占31.9%)，洪峰强度高、峰腰窄、过程集中且变化剧烈类、涨落洪慢的类型(类型3，占18.1%)；② 类型1和类型3的洪水行为特征变化受降雨和流域特征的综合影响，主导因素分别为降雨变差系数和森林覆盖率，类型2中57.1%的洪水行为特征变化主要受降雨集中度等降雨变化影响；③ 类型3洪水行为特征指标的总体预测性能精度最高，类型1和类型2次之，三种山洪类型的量级、时间和形态指标的预测精度均优于变率指标。研究可为山洪灾害差异化防治和风险管理提供技术支撑和参考。