Guangwen Shao

The Hailiutu River basin is a typical area of semi-arid sandy land with relatively flat topography, the surface of which is covered by undulating dunes and the development of the river system is not obvious. The dominant hydrological cycle is precipitation infiltration through dunes to aquifers followed by discharge to rivers. Therefore, the baseflow is an important component of the streamflow in this basin, but few studies for the baseflow characteristics have been conducted. The isotope tracer technique was applied to investigate the contributions of groundwater, soil water, and surface water to streamflow during the flood period. The results showed that the contributions of these components to streamflow were approximately 70%, 27%, and 3% respectively. Several automatic baseflow separation methods including filtering and recursive digital filtering (RDF) techniques were adopted to separate the baseflow from the streamflow and the adaptabilities of these methods were evaluated. All the filtering methods including Hydrograph Separation Program (HYSEP) and UK Institute of Hydrology’s method (UKIH) clearly underestimated the baseflow when compared with the standard baseflow results which were provided by the previous study using the tracer-based method in this basin, while the recursive digital filtering with Eckhardt filter technique (RDF-E) produced better performance. In the nonprecipitation period, the RDF-E method misidentified quick flow values which caused deviations between the separated baseflow and the above standard value. Hence, we proposed a modified automatic baseflow separation method called RDF-M by introducing the precipitation information into RDF-E. In comparison with the above standard, the RDF-M method provided similar baseflow results which were consistent with the actual situation of the Hailiutu River basin.

In the original soil and water assessment Tool (SWAT) model (SWAT-O), the contributions of shallow aquifers and deep aquifers to streamflow are simulated using the linear reservoir method. The movement of groundwater was limited in the hydrological response unit which is a minimum calculation unit in the SWAT. However, this computational method may not be suitable for the areas where a groundwater system is complicated, and the river is predominately recharged by groundwater. In this paper, we proposed an enhanced groundwater module which divides shallow aquifers into upper and lower aquifers, integrates all the deep aquifers of a sub-basin into a regional aquifer, and simulates interactive water amount between lower aquifer and deep aquifer using water depth difference. The modified groundwater module was introduced to the original SWAT model, hereby referred to as SWAT-MG. The SWAT-MG and SWAT-O models were applied to the Hailiutu River catchment, which is a semi-arid wind sandy grass shoal catchment. Results showed that both models underestimated streamflow in peak flow, while the simulated streamflow of SWAT-MG was closer the observed values than that of SWAT-O. Three evaluation criteria (NSE, RSR, PBIAS) were applied to evaluate the performance of the models and the results showed that SWAT-MG had a better performance than SWAT-O. The baseflow index of Hailiutu River which was calculated by the results of SWAT-MG was 96.78%, which means the streamflow is predominately recharged by groundwater, and this conforms to the actual situation of Hailiutu River catchment. This indicates that a SWAT model with a modified groundwater module could better represent the groundwater flow behavior in the study area.

The Hailiutu River basin is a typical semi-arid wind sandy grass shoal watershed in northwest China. Climate and land use have changed significantly during the period 1970–2014. These changes are expected to impact hydrological processes in the basin. The Mann–Kendall (MK) test and sequential t-test analysis of the regime shift method were used to detect the trend and shifts of the hydrometeorological time series. Based on the analyzed results, seven scenarios were developed by combining different land use and/or climate situations. The Soil Water Assessment Tool (SWAT) model was applied to analyze the impacts of climate variability and land use change on the values of the hydrological components. The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) was applied to enhance the spatial expressiveness of precipitation data in the study area during the period 2008–2014. Rather than solely using observed precipitation or CMADS precipitation, the precipitation values of CMADS and the observed precipitation values were combined to drive the SWAT model for better simulation results. From the trend analysis, the annual streamflow and wind speed showed a significant downward trend. No significant trend was found for the annual precipitation series; however, the temperature series showed upward trends. With the change point analysis, the whole study period was divided into three sub-periods (1970–1985, 1986–2000, and 2001–2014). The annual precipitation, mean wind speed, and average temperature values were 316 mm, 2.62 m/s, and 7.9 °C, respectively, for the sub-period 1970–1985, 272 mm, 2.58 m/s, and 8.4 °C, respectively, for the sub-period 1986–2000, and 391 mm, 2.2 m/s, and 9.35 °C, respectively, for the sub-period 2001–2014. The simulated mean annual streamflow was 35.09 mm/year during the period 1970–1985. Considering the impact of the climate variability, the simulated mean annual streamflow values were 32.94 mm/year (1986–2000) and 36.78 mm/year (2001–2014). Compared to the period 1970–1985, the simulated mean annual streamflow reduced by 2.15 mm/year for the period 1986–2000 and increased by 1.69 mm/year for the period 2001–2014. The main variations of land use from 1970 to 2014 were the increased area of shrub and grass land and decreased area of sandy land. In the simulation it was shown that these changes caused the mean annual streamflow to decrease by 0.23 mm/year and 0.68 mm/year during the periods 1986–2000 and 2001–2014, respectively. Thus, the impact of climate variability on the streamflow was more profound than that of land use change. Under the impact of coupled climate variability and land use change, the mean annual streamflow decreased by 2.45 mm/year during the period 1986–2000, and the contribution of this variation to the decrease in observed streamflow was 27.8%. For the period 2001–2014, the combined climate variability and land use change resulted in an increase of 0.84 mm/year in annual streamflow. The results obtained in this study could provide guidance for water resource management and planning in the Erdos plateau.

This study aims to investigate trends in streamflow and precipitation in the period 1954–2010 in a semiarid region of the Yellow River watershed, Huangfuchuan basin, China. The combination of the wavelet transform and different Mann-Kendall (MK) tests were employed to figure out the basic trends structure in streamflow and precipitation and what time scales are affecting the observed trends. The comparative analysis with five MK test methods showed that the modified MK tests with full serial correlation structure performed better when significant autocorrelations exhibited for more than one lag. Three criteria were used to determine the optimal smooth mother wavelet, the decomposition level and the extension mode used in the discrete wavelet transform (DWT) procedure. The first criteria referred to the relative error of the wavelet approximated component and the original series. The second one was the relative error of MK Z-values of approximation component and the original series. Additionally, a new criterion (Er), based on the relative error of energy between the approximate component and the original series, was proposed in this study, with better performance than the previous two criteria. Further, a new powerful index, the energy of the hydrological time series, was proposed to verify the dominant periodic components for the observed trends. The analysis indicated that all monthly, seasonal and annual streamflow showed significant decreasing trends, while no significant trends were found in precipitation. Results from the DWT and MK tests revealed that the main factors influencing the trends in the monthly and seasonal series in Huangfuchuan watershed are intra-annual cycles, while the leading factors affecting the trends in the annual series are decadal events. Different driving factors (e.g., seasonal cycles, solar activities, etc.) related to the periodicities identified in these data types resulted in this discrepancy.