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The Chinese Loess Plateau is known as one of the most severe soil erosion regions in the world. Two ecological restoration projects, i.e., the integrated soil conservation project since the 1970s and the ''Grain for Green'' project since 1999, have been progressively implemented to control the soil erosion in this area. Ecological restoration has greatly changed flow regime over the past five decades. However, the mechanism of how flow regime responds to ecological restoration among landforms remains poorly understood. In this study, we investigated the temporal dynamics of flow regime in three catchments, i.e., Wuqi, Honghe and Huangling hydrological stations, respectively representing the loess hilly-gully, loess table-gully and rocky mountain (covered by secondary forest) areas in the Chinese Loess Plateau, using daily hydrological data during the 1960s-2010s. The nonparametric Mann-Kendall test, Pettitt's test and daily flow series were used to investigate the changes of flow regime. Significantly negative trends of annual streamflow were detected at the Wuqi and Honghe stations, except for the Huangling station. The annual baseflow at the Wuqi station showed a significantly positive trend whereas a significantly negative trend was observed at the Honghe station, and there was no significant trend at the Huangling station. It was interesting that baseflow index significantly increased during the whole period in all catchments. However, the trends and change points of daily flow series derived by different percentages of exceedance and extreme series in different consecutive days varied among individuals. Based on the change points analysis of annual streamflow, we divided data series into three periods, i.e., the baseline period (from 1959(from and 1963(from to 1979, the integrated soil conservation period (1980( -1999 and the ''Grain for Green '' period (2000'' period ( -2011. We found that streamflow decreased due to the reduction of high streamflow (exceeding 5% of time within a year) and median streamflow (50%) in PII and PIII at the Wuqi and Honghe stations. However, low flow (95%) increased in PII and PIII at the Wuqi station while decreased at the Honghe station. Streamflow change at the Huangling station was more stable, thus potentially resulting in much less soil erosion in the forestry area than in the other areas. The great improvement in ecological environment on the Chinese Loess Plateau revealed the advantages of ecological restoration in reducing flood amount and compensating streamflow at a regional scale.Citation: LUO Zhidong, LIU Erjia, QI Shi, ZHAO Nan, SUN Yun. 2020. Flow regime changes in three catchments with different landforms following ecological restoration in the Chinese Loess Plateau. Journal of Arid Land, 12(1): 44-57.

We evaluated the performance of three global evapotranspiration (ET) models at local, regional, and global scales using the multiple sets of leaf area index (LAI) and meteorological data from 1982 to 2017 and investigated the uncertainty in ET simulations from the model structure and forcing data. The three ET models were the Simple Terrestrial Hydrosphere model (SiTH) developed by our team, the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), and the MODerate Resolution Imaging Spectroradiometer (MODIS) ET algorithm (MOD16). Comparing the observed with simulated monthly ET by the three models over 43 Fluxnet sites, we found that SiTH overestimated ET for forests with mean slope from 1.25 to 1.67, but it performed better than the other two models over short vegetation. MOD16 and PT-JPL models simulated well for forests but poorly in dryland biomes (slope = 0.25~0.55; R2 = 0.02~0.46). At the catchment scale, all models performed well, except for some tropical and high latitudinal catchments, with NSE values lower than 0 and RMSE and MAE values far beyond their mean values. At the global scale, SiTH highly overestimated ET in tropics, while PT-JPL slightly underestimated ET between 30°N and 60°N and MOD16 underestimated ET between 15°S and 30°S. Generally, the PT-JPL provided the better performance than SiTH and MOD16 models. This study also revealed that the estimated ET by SiTH and especially PT-JPL model were influenced by the uncertainty in meteorological data, and the estimated ET was performed better using MERRA-2 datasets for PT-JPL and using ERA5 datasets for SiTH. While the estimated ET by MOD16 were relatively sensitive to LAI data. In addition, our results suggested that the GLOBMAP and GIMMS datasets were more suitable for long-term ET simulations than the GLASS dataset.