The source region of Yellow river is an alpine river sensitive to climate changes, but the potential effects of climate change on hydrological regime characteristics and ecological implications are less understood. This study aims to assess the response of the alterations in the flow regimes over the source region of Yellow river to climate change using Soil and Water Integrated Model driven by different Global Circulation Models (GFDL-ESM2M, IPSL-CM5A-LR and MIROC-ESM-CHEM) under three Representative Concentration Pathway emission scenarios (RCP2.6, RCP4.5 and RCP8.5). Indicators of hydrological alteration and River impact index are employed to evaluate streamflow regime alterations at multiple temporal scales. Results show that the magnitude of monthly and annual streamflow except May, the magnitude and duration of the annual extreme, and the number of reversals are projected to increase in the near future period (2020–2049) and far future period (2070–2099) compared to the baseline period (1971–2000). The timing of annual maximum flows is expected to shift backwards. The source region of Yellow river is expected to undergo low change degree as per the scenarios RCP2.6 for both two future periods and under the scenarios RCP4.5 for the near future period, whereas high change degree under RCP4.5 and RCP8.5 in the far period on the daily scale. On the monthly scale, climate changes mainly have effects on river flow magnitude and timing. The basin would suffer an incipient impact alteration in the far period under RCP4.5 and RCP8.5, while low impact in other scenarios. These changes in flow regimes could have several positive impacts on aquatic ecosystems in the near period but more detrimental effects in the far period.
One‐time or short‐term lake water isotopic surveys are often employed to evaluate regional lake water balance. However, it can be difficult to determine the optimal time‐window for sampling to obtain a representative long‐term perspective of lake water balance in settings influenced by seasonal variations in precipitation, evaporative loss, glacial/snow meltwater, and larger seasonal shifts in isotopic composition of precipitation. This is especially true for areas of the Tibetan Plateau that are influenced by the summer Indian monsoon. Although high‐frequency sampling is always preferred as the most rigorous approach to characterize the water budget of lakes or watersheds, this may be impractical in remote regions and over large spatial scales. To assess the potential sensitivity of isotope balance characterization to seasonal variability, we used a weekly lake water isotope data set acquired over a period of 3 years on the Tibetan Plateau to evaluate the potential inaccuracies that might have arisen from using isotopic data collected during narrower time‐windows. For this assessment, we use weekly isotopic data collected during the study and assume that these sampling events were stand‐alone one‐time surveys. We then demonstrate the sensitivity of the isotope balance method in this setting, particularly for the rainy season that significantly underestimated the evaporation/inflow. In contrast, isotopic composition of the lake water was found to be more representative of long‐term conditions when sampled in October on the Tibetan Plateau. To broaden our evaluation of seasonality effects over a range of climatic zones, published high‐frequency isotopic data were also compiled, and a similar assessment was carried out for selected regions of the world. The synthesized data and model outputs, which confirm pronounced variations in lake water isotopic composition and evaporation/inflow across a range of seasonal climates, were used to determine optimal sampling windows for these specific regions. 相似文献
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