Water resources carrying capacity (WRCC) is a recently proposed management concept, which aims to support sustainable socio-economic development in a region or basin. However, the calculation of future WRCC is not well considered in most studies, because water resources and the socio-economic development mode for one area or city in the future are quite uncertain. This paper focused on the limits of traditional methods of WRCC and proposed a new concept, water resources design carrying capacity (WRDCC), which incorporated the concept of design. In WRDCC, the population size that the local water resources can support is calculated based on the balance of water supply and water consumption, under the design water supply and design socio-economic development mode. The WRDCC of Chengdu city in China is calculated. Results show that the WRDCC (population size) of Chengdu city in development modeI (II, III) will be 997 ×10⁴ (770 × 10⁴, 504 × 10⁴) in 2020, and 934 × 10⁴ (759 × 10⁴, 462 × 10⁴) in 2030. Comparing the actual population to the carrying population (WRDCC) in 2020 and 2030, a bigger gap will appear, which means there will be more and more pressure on the society-economic sustainable development.

Hydrological time series data (1988–2008) of the Hei River, the main water source to Zoige wetland in the Eastern Tibetan Plateau, were investigated. Results showed that the runoff distribution of Hei River varies with the relative change in amplitude (Cm=15.9) and the absolute change in amplitude (ΔQ=37.1 m³/s) during the year. There was a significant decreasing trend since 1988 with annual runoff of 20.0 m³/s (1988–1994), 19.0 m³/s (1995–2000), and 15.2 m³/s (2001–2008). There were double peaks in runoff during the water year: the highest peak in the period of 1988–2000 occurred in July while in the period of 2001–2008 it occurred in October. Shifting peak flow means less water quantity in wetland during growing season. Nearest neighbor bootstrapping regressive method was used to predict daily runoff of the Hei River. Model results show that it was fitted with 94.23% ofR2for daily time series, which can provide a basis for the development and utilization of regional water resources.

The Nearest Neighbour Method (NNM) is a data-driven and non-parametric scheme established on the similarity characteristics of hydrological phenomena. One of the important parts of NNM is to choose a proper distance measure. The Euclidean distance (EUD) is a commonly used distance measure, which represents the absolute distance of a spatial point and is directly related to the coordinate of the point, but is not sensitive to the direction of the feature vector. This paper used the cosine angle distance (CAD) for the similarity measure, which reflects more differences in the direction, and compared it to EUD. This technique is applied to annual runoff at YiChang station on the Yangtze River. The results show the NNM with CAD has a better performance than that of EUD.