"A XGBOOST ERROR CORRECTION MODEL FOR IMPROVING MONTHLY LAKE WATER LEVEL ESTIMATION ON QIANGTANG PLATEAU"

"Accurate and consistent monitoring of lake water levels is essential for understanding hydrological dynamics and climate-driven variability in remote and data-scarce regions. Satellite altimetry provides high-precision lake level observations, but its limited spatial and temporal coverage constrain large-scale monitoring. Combining Digital Elevation Model (DEM) and remote sensing imagery offers an alternative, but the accuracy of resultant water level is affected by the uncertainties of inherent elevation and image processing. This study proposes an XGBoost model for correcting systematic errors in inconsistent DEM-derived water levels. Twelve error-influencing parameters were incorporated, spanning lake boundary uncertainty, terrain accuracy, and area-elevation fitting errors. The results achieve a high accuracy (RMSE = 2.99 m, R2 = 0.99, MAE = 0.84 m), and demonstrate robust correction performance across lakes of different sizes. We reconstructed monthly water level time-series (2000-2021) for 965 lakes on the Qiangtang Plateau (QP) using this method. The dataset unravels divergent change trends in lake water levels on QP: a significant rise (0.12 m\/y) in lakes monitored by altimetry and a slight decline (-0.028 m\/y) in lakes without altimetry coverage. This suggests that relying solely on altimetry data may overestimate regional lake expansion. We found both lake types are clustered into three intra-annual variation patterns, reflecting distinct hydrological and climatic influences. Uncertainties in water body extraction during frozen periods significantly reduce the accuracy of lake water level estimations. This study provides the first plateau-scale assessment of monthly lake water level dynamics and may offer a foundation for future research on regional hydrological changes. "

搜集汇总

背景与挑战

背景概述

该数据集基于XGBoost误差校正模型，旨在提高青藏高原湖泊月水位估算的准确性，通过整合12个误差参数校正DEM和遥感数据中的系统误差。它重建了2000-2021年间965个湖泊的月水位时间序列，揭示了湖泊水位的变化趋势和季节模式，为区域水文研究提供了基础。