Climate Changes and Associated Multiscale Impacts on Watershed Discharge over the Upper Reach of Yarlung Zangbo River Basin, China

Abstract

Watershed discharge (WD) in the alpine regions, such as the upper reach of Yarlung Zangbo River Basin (YZRB), China, could have changed severely in response to climate changes. Yet, how hydrometeorological variables varied at different time scales and how WD varied in response to hydrometeorological variables in the alpine regions remained questions to be answered. The ensemble empirical mode decomposition (EEMD) method was employed in this study to investigate the nonlinear climate change trends (averaged and extreme states) and the associated multiscale impacts on WD variations over the upper reach of the YZRB during 1961–2009. All investigated hydroclimatic variables, i.e., precipitation, temperature, and WD, were found to be varied nonlinearly with clear multiscale oscillations characterizing great differences in the oscillation periods, corresponding significance levels, and variance contribution rates, among which precipitation posed a weak impact on WD variations, while temperature played a significant role in WD fluctuations. Furthermore, among all temperature extremes, the dominant index affecting WD variations was TXm (annual mean of the daily maximum temperature) but not TXx (annual maximum of the daily maximum temperature) at both interannual and interdecadal scales, which might be caused by that TXx increased evapotranspiration and reduced WD. A significant correlation between temperature (both averaged and partial extreme states) and annual WD at both interannual and interdecadal scales indicated that a synchronous change existed between them. The present study provided first insight into how hydrometeorological variables varied at different time scales and how WD fluctuated in response to hydrometeorological variables over the upper reach of the YZRB, China.

Application of Informer Model Based on SPEI for Drought Forecasting

“…where p(k j | q i ) = k(q i , k j ) /(∑ l k(q i , k l )), and k(q i , k j ) selects the asymmetric exponential kernel exp (q i k T j )/ √ d [23]. To measure the sparsity of Query, Informer uses Kullback-Leibler divergence.…”

“…Through a comparison of the forecasting results of various models with actual observations, the study found that the models based on the integration methods have higher accuracy and stability relative to the single models. Xu et al [22] combined Complementary Ensemble Empirical Mode Decomposition (CEEMD) and ARIMA, and they showed that the CEEMD-ARIMA model was applicable to drought prediction; the model could also identify multiple modalities of drought variability on diverse timescales [23], improving the comprehensiveness and accuracy of the prediction.…”

Investigating Whether the Ensemble Average of Multi-Global-Climate-Models Can Necessarily Better Project Seasonal Drought Conditions in China

“…It is worth noting that all the observations used in CPAP have undergone strict quality control (QC), including extrema detection, internal consistency check, and spatial consistency check, before applying the OI technique [60,61]. In recent years, the CPAP has been widely used in precipitation-related (e.g., drought and runoff) investigations in China [62][63][64], particularly as reference data to validate high temporal and spatial resolution satellite-based precipitation products [59,65,66]. As a result, this research used it as a benchmark for comparing precipitation measurements with GCMs from 1961-2014.…”