Abstract
Conducting water resource assessment and forecasting at a basin scale requires effective and accurate simulation of the hydrological process. However, intensive, complex human activities and environmental changes are constraining and challenging the hydrological modeling development and application by complicating the hydrological cycle within its local contexts. Six sub-catchments of the Yellow River basin, the second-largest river in China, situated in a semi-arid climate zone, have been selected for this study, considering hydrological processes under a natural period (before 1970) and under intensive human disturbance (2000–2013). The study aims to assess the capacity and performance of the hydrological models in simulating the discharge under a changing environment. Four well-documented and applied hydrological models, i.e., the Xin’anjiang (XAJ) model, GR4J model, SIMHYD model, and RCCC-WBM (Water Balance Model developed by Research Center for Climate Change) model, were selected for this assessment. The results show that (1) the annual areal temperature of all sub-catchments presented a significant rising trend, and annual precipitation exhibited insignificant decline trend; (2) as a result of climate change and intensive human activities, the annual runoff series showed a declining trend with abrupt changes mostly occurring in the 1980s with the exception of the Tangnaihai station; (3) the four hydrological models generally performed well for runoff simulation for all sub-catchments under the natural period. In terms of Nash–Sutcliffe efficiency coefficient, the XAJ model worked better in comparison to other hydrological models due to its detailed representations and complicated mechanism in runoff generation and flow-routing scheme; (4) environmental changes have impacted the performance of the four hydrological models under all sub-catchments, in particularly the Pianguan River catchment, which is could be attributed to the various human activities that in turn represent more complexity for the regional hydrological cycle to some extent, and reduce the ability to predict the runoff series; (5) the RCCC-WBM model, well known for its simple structure and principles, is considered to be acceptable for runoff simulation for both natural and human disturbance periods, and is recommended for water resource assessment under changing environments for semi-arid regions.
Highlights
Hydrological models are essential for river flow forecasting, regional water resource assessment, and climate change impact analysis, owing to their consistent simulation capacity of hydrological series [1,2]
This conclusion can be attributed to a lower anthropic impact on the hydrological regime in the Upper Yellow River basin even though the upper basin of Huayuankou station encompasses complex and variable climate zones and underlying conditions, whose area occupies over 97% of the whole Yellow River basin
Variation trends in annual and seasonal hydro-climatic variables (e.g., discharge, precipitation, and variation trends andcatchments seasonal hydro-climatic variables overinsixannual selected of the Yellow River basin were investigated to assess the temperature) over six selected catchments of the
Summary
Hydrological models are essential for river flow forecasting, regional water resource assessment, and climate change impact analysis, owing to their consistent simulation capacity of hydrological series [1,2]. With rapid socio-economic development, most areas or river basins have been highly regulated with intensive human activities, such as large-scale soil and water conservation measures in arid or semi-arid climatic zones, water conservancy projects (e.g., reservoirs, water intake projects, etc.), and urbanization, etc. These human activities can influence or change the regional hydrological cycle and, more importantly, change the natural relationship between rainfall and runoff [3]. E.g., rank-sum test [11], Mann–Kendall rank correlation test [12], rescaled-range (R/S) analysis [13], Brown–Forsythe test [14] and Bayesian methods [15]
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