No abstract

No abstract

No abstract

Model parameter calibration is a fundamentally important stage that must be completed before applying a model to address practical problems. In this study, we describe an automatic calibration framework that combines sensitivity analysis (SA) and an adaptive surrogate modeling-based optimization (ASMO) algorithm. We use this framework to calibrate catchment-specific sensitive parameters for streamflow simulation in the variable infiltration capacity (VIC) model with a 0.25°spatial resolution over 10 major river basins of China from 1960 to 1979. We found that three parameters-the infiltration parameter (B) and two of the soil depth parameters (D 1 , D 2 )-are highly sensitive in most basins, while other parameter sensitivities are strongly related to the dynamic environment of the basin. Compared with directly calibrating the seven parameters recommended for the default calibration procedure, our framework not only reduced the computing time by two thirds through opting out of insensitive parameters (type I error) but also improved the Nash-Sutcliffe model efficiency coefficient (NSE) for optimized results when it identified a missing sensitive parameter (type II error) in the case study river basins. Results show that the SA-based ASMO framework is an effective and efficient model-optimization technique for matching simulated streamflow with observations across China. The NSE for monthly streamflow ranged from 0.75 to 0.97 and from 0.71 to 0.97 during the validation and calibration periods, respectively. The calibrated parameters can be applied directly in streamflow simulations across China, and the proposed calibration framework holds important implications for relevant simulation studies in other regions.

Drought is the most recurrent and destructive hazard in arid and semiarid regions and will only become more complex under climate change. It is vital to characterize the various types of drought, to investigate the potential factors affecting different types of drought, and to assess the relationship between drought types. In this study, the Standardized Precipitation Index and the Standardized Runoff Index were used to characterize meteorological and hydrological drought, respectively, to investigate drought characteristics and mechanisms in 17 catchments on the Loess Plateau from 1961 to 2013. Furthermore, the propagation time from meteorological to hydrological drought was explored and the potential factors influencing drought propagation time were investigated. The results indicate that the Loess Plateau has experienced an increased tendency toward both meteorological and hydrological droughts over the period 1961-2013, with hydrological drought more serious than meteorological drought at various drought assessment time scales. Moreover, average drought duration and severity were greater for hydrological drought than meteorological drought. Maximum 5-day precipitation (Rx5day) was the dominant extreme climate index for explaining variance in meteorological drought at the annual time scale. Owing to the greater complexity underlying hydrological drought, Rx5day, the number of warm days (Tx90p), and the number of warm nights (Tn90p) all contribute to the variance in hydrological drought. Furthermore, the percentage of forested land had a significant positive association (p < 0.001) with propagation time, whereas the percentage of land given over to pasture had a significant negative association (p < 0.001) with propagation time. Key Points:• Loess Plateau has experienced an increased tendency toward both meteorological and hydrological droughts over the period 1961-2013 • Average drought duration and severity were greater for hydrological drought than meteorological drought • Changes in land use and land cover can alter the propagation time from meteorological to hydrological drought Supporting Information:• Supporting Information S1 Journal of Geophysical Research: AtmospheresWU ET AL. 11,581 catchments) and summer (1-3 months) were shorter than in the autumn (1-6 months in northwestern catchments and more than 12 months in the remain regions) and winter (1-4 months in the western and central region and more than 10 months in the remaining regions).

No abstract

No abstract

Abstract. We applied Gravity Recovery and Climate Experiment (GRACE) Tellus products in combination with Global Land Data Assimilation System (GLDAS) simulations and data from reports, to analyze variations in terrestrial water storage (TWS) in China as a whole and eight of its basins from 2003 to 2013. Amplitudes of TWS were well restored after scaling, and showed good correlations with those estimated from models at the basin scale. TWS generally followed variations in annual precipitation; it decreased linearly in the Huai River basin (−0.56 cm yr −1 ) and increased with fluctuations in the Changjiang River basin (0.35 cm yr −1 ), Zhujiang basin (0.55 cm yr −1 ) and southeast rivers basin (0.70 cm yr −1 ). In the Hai River basin and Yellow River basin, groundwater exploitation may have altered TWS's response to climate, and TWS kept decreasing until 2012. Changes in soil moisture storage contributed over 50 % of variance in TWS in most basins. Precipitation and runoff showed a large impact on TWS, with more explained TWS in the south than in the north. North China and southwest rivers region exhibited long-term TWS depletions. TWS has increased significantly over recent decades in the middle and lower reaches of Changjiang River, southeastern coastal areas, as well as the Hoh Xil, and the headstream region of the Yellow River in the Tibetan Plateau. The findings in this study could be helpful to climate change impact research and disaster mitigation planning.