Land use and land cover change (LUCC) and water resource utilization behavior and policy (WRUBAP) affect the hydrological cycle in different ways. Their effects on streamflow and hydrological balance components were analyzed in the Yiluo River Basin using the delta method and the Soil and Water Assessment Tool (SWAT). The multivariable (runoff and actual evapotranspiration) calibration and validation method was used to reduce model uncertainty. LUCC impact on hydrological balance components (1976–2015) was evaluated through comparison of simulated paired land use scenarios. WRUBAP impact on runoff was assessed by comparing natural (simulated) and observed runoff. It showed that urban area reduction led to decreased groundwater, but increased surface runoff and increased water area led to increased evaporation. LUCC impact on annual runoff was found limited; for instance, the difference under the paired scenarios was <1 mm. Observed runoff was 34.7–144.1% greater than natural runoff during November–June because of WRUBAP. The effect of WRUBAP on wet season runoff regulation was limited before the completion of the Guxian Reservoir, whereas WRUBAP caused a reduction in natural runoff of 21.6–35.0% during the wet season (July–October) after its completion. The results suggest that WRUBAP has greater influence than LUCC on runoff in the Yiluo River Basin. Based on existing drought mitigation measures, interbasin water transfer measures and deep groundwater exploitation could reduce the potential for drought attributable to predicted future climate extremes. In addition to reservoir regulation, conversion of farmland to forestry in the upstream watershed could also reduce flood risk.

With the change of climate and the impacts of human activities, the water resources crisis of the Yellow River is becoming increasingly serious. How and why did the streamflows of the Yellow River basin change? Based on observed annual runoff data (1956–2016) of 10 main hydrological stations along the Yellow River, the linear regression method, the Spearman rank correlation method and the Mann-Kendall test method are used to analyze runoff trend. The orderly clustering method, the sliding t test method and the Lee-Heghinian Method are used to identify the abrupt change point. Finally, the wavelet analysis method is used to identify runoff time series period. The results show that: (1) With the exception of the streamflow of Tangnaihai, the streamflows of all examined stations have significantly declining trends. The decrease of the streamflow from the upper to the middle to the lower reaches is becoming more and more obvious; (2) The runoff of the Yellow River has changed greatly. The abrupt change point at Tangnaihai occurred in 1989. The abrupt change points of the other stations took place in 1985; (3) The runoff along the Yellow River presents multi-time scale changes. The streamflows appear to have strongest periods of 25–40 years with a 40-year scale, which indicate the alternate oscillations of the high and the low water periods. The periods of <6 and 7–24 years are not stable and are complicated. The first main period of runoff in the Yellow River is 30 years; (4) The streamflow upstream of Tangnaihai station is mainly affected by the climate. The streamflows downstream of Tangnaihai station are influenced by human activities, especially water extraction and diversion and the operations of the large reservoirs. These research results have important practical guiding significance for hydrological forecasting, evaluation and management of water resources, construction of water conservancy projects and sustainable utilization of water resources in the region.

Identifying implicit periodicities in hydrological data is significant for managing river–basin water resources and establishing flood forecasting systems. However, the complexity and randomness of hydrological systems make it difficult to detect hidden oscillatory characteristics. This study discusses the performance and applicability of five period identification methods, namely periodograms, autocorrelation analysis (AA), maximum entropy spectral analysis (MESA), wavelet analysis (WA), and the Hilbert–Huang transform (HHT). The annual and monthly runoff data are sampled from two stations (Huayuankou and Lijin on the Yellow River in China) in the years 1949–2015. The conclusions are as follows: (i) All methods identify the significant periods of 6 months, 12 months, and 18–19 months, which have relatively high energy of peaks; (ii) WA and HHT perform best when dealing with nonstationary time series, but they are ineffective for identifying large-scale periods; (iii) MESA has high resolution and stability but is prone to oscillate at small-scale periods when applied to monthly series; and (iv) periodograms and AA are relatively simple, but their results lack stability and are significantly affected by the data length—the resolution of AA is too low when applied to annual data, and periodograms can easily produce “false peaks”. Generally, it is better to apply multiple methods comprehensively than each method singularly, and this can be effective in reducing subjective influences.

In the published article [1], the authors noticed some errors in Equation (1), and wish to make the following correction to their paper [1]: Equation (1) should be corrected to $S{W}_t=S{W}_0+{{\displaystyle \sum }}_{i=1}^t\left(R_{day}-Q_{surf}-ET-W_{seep}-Q_{gw}\right)$

To understand the intricate runoff-sediment relationship in the middle Yellow River basin (MYRB), the Toudaoguai, Longmen, Tongguan and Huayuankou sites in the MYRB were selected to analyze the deterministic equilibrium and uncertainty relations of runoff-sediment based on 55-year hydrological data at multi-time scales. The Johansen test and wavelet neural network were used to verify the cointegration relationship among hydrological series. Runoff-sediment uncertain statistical relations and dynamics in the MYRB were also analyzed based on rating curves and hysteresis loops. The results showed that the logarithmic sequences of sediment load (SL), runoff and suspended sediment concentration (SSC) conformed to a linear cointegration relationship at the Toudaoguai station or in spring, winter or under small flow at other stations, but a nonlinear cointegration relationship was observed in other cases at other stations. Regarding runoff-sediment uncertain relationships, the rating curves, and hysteresis loops differed in stations (Toudaoguai and the other stations), as well as discharge (threshold: 1000 m³/s), season (ice-flood and rainy season) and saturation of flow at flood and monthly scales. At the annual scale, phased and unsynchronized characteristics of runoff and sediment load were evident with a decreasing trend. This study on the runoff-sediment relationship can rationally provide a theoretical basis for the management and development of the Yellow River and other similar rivers with sufficient sediment, especially for areas with serious soil erosion.