The Capacity of the Hydrological Modeling for Water Resource Assessment under the Changing Environment in Semi-Arid River Basins in China

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.

Evaluation of Precipitation Products by Using Multiple Hydrological Models over the Upper Yellow River Basin, China

“…In this model, monthly precipitation is divided into rainfall and snowfall with the upper and lower temperature criteria, using the linear partitioning method. The model calculation flowchart and formula are detailed in Guan et al [33]. Normally, in previous studies, the upper and lower temperatures were preset as 4 • C and −4 • C without calibration in flow simulation.…”

“…The GR4J model, developed by the research group at the CEMAGREF (now IRSTEA) [35], is an empirical and parsimonious, reservoir-based model. The description of the model parallels that of Guan et al [33]. Initially, this model had only 4 parameters (shown in Table 3), and most secondary processes are represented by empirical constants, which was widely used in Europe and Australia [36,37].…”

“…Li et al [39] found that little improvement was acquired when the GR4J was incorporated with the SWAT snowmelt module than the original 4 parameters GR4J model in runoff prediction in ungauged catchments. Guan, et al [33] applied the GR4J model excluding snowmelt module in 6 typical watersheds in the Yellow River basin including the UYRB, and found that the GR4J performed well in streamflow simulation under the changing environment. Therefore, in this study, the effects of the snowmelt module were incorporated into the 3 conceptual models in hydrological evaluation of SDFE or the RA precipitation products.…”

Operating Small Hydropower Plants in Greece under Intermittent Flow Uncertainty: The Case of Tsiknias River (Lesvos)

“…The adaptation of non-conventional water resources measures (i.e., the construction of a reservoir to serve the operation of a small hydropower plant), riverbank protection measures to control flood-prone areas and the high energy demands of the area, and the effect of CC on the environment are subjects of continuous discussion at community and municipality levels. Using hydrological modeling to simulate climate change scenarios at the level of specific river catchments can be indispensable in guiding management strategy [18].…”

Deep Learning for Forecasting Runoffs over China under Climate Changes

“…The same trend was given by Wang et al (2019), who found that precipitation and temperature is projected to increase in the Upper Yangze River Basin. In Yellow River Basin, Guan et al (2019) found the temperature presented a significant rising trend, but precipitation had a decline trend.…”