Runoff conditions in the Fuping Basin under an ensemble of climate change scenarios
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摘要: 径流变化对于水资源管理至关重要, 然而, 未来气候变化对阜平流域径流的影响仍未知。本文基于实测数据及4个区域气候模式(RCMs)的集合数据, 使用MIKE11-NAM模型模拟了阜平流域(大清河流域上游的子流域)当前(2008—2017年)及在SSP1-2.6、SSP2-4.5和SSP5-8.5 3种情景下的未来(2025—2054年)径流变化情况。结果表明, MIKE11-NAM模型在日径流模拟中表现良好, R²和NSE在校准期分别为0.82和0.81, 在验证期分别为0.87和0.87。偏差校正后, 观测数据和RCM数据间的相关性提高。与基准期(1985—2014年)相比, 未来的降水量和气温均呈现增加趋势。在SSP5-8.5和SSP2-4.5情景下, 年均温和降水量将分别增加2.45 ℃和124 mm。预计夏季降水量增加幅度较大, 特别是在7—8月; 而各季节的气温将上升, 其中冬季气温上升幅度最大。在SSP2-4.5情景下, 预计年径流量将增加3.5 mm; 而在SSP1-2.6和SSP5-8.5情景下, 预计年径流量将分别减少12.0 mm和11.0 mm。季节尺度上, 在SSP1-2.6、SSP2-4.5和SSP5-8.5情景下, 未来春季径流量将分别减少2.3 mm、1.2 mm和1.9 mm, 夏季径流量将分别减少9.0 mm、7.1 mm和12.9 mm。研究结果可为该地区水资源综合管理和规划提供科学参考。
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关键词:
- MIKE11-NAM /
- 大清河流域 /
- 模拟 /
- 径流 /
- 气候变化
Abstract: Changes in runoff are of great significance for water resources management, especially under the changing climate. In the Fuping Basin, one of the basins in the upper reaches of the Daqinghe Basin, the water resources are facing changes which show great importance of further studies on runoff conditions in the future in this basin. Hence, in this paper, MIKE11-NAM model was applied to simulate daily runoff (2008−2017) and future runoff conditions under a changing climate in the near future (2025−2054) in the Fuping Basin. After bias correction, an ensemble of four regional climate models (RCMs) was used to develop future climate data under three shared socio-economic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) scenarios. The obtained results showed a good performance of the MIKE11-NAM model in simulating daily runoff. R2 and Nash-Sutcliffe efficiency coefficient (NSE) were 0.82 and 0.81 for calibration, 0.87 and 0.87 for validation, respectively. Although uncertainties remain, the correlation between observed and simulated RCM data was improved after bias correction for all models. Precipitation and temperature were projected to increase under all scenarios compared to the baseline period (1985−2014). Annual temperature and precipitation will increase by 2.45 ℃ and 124 mm under the SSP5-8.5 and SSP2-4.5 scenarios, respectively. However, precipitation is expected to mainly increase in summer while temperature will increase in all the seasons. The projected annual runoff will increase under SSP2-4.5 while decreasing under SSP1-2.6 and SSP5-8.5 scenarios. Seasonally, the future runoff will decrease during spring and summer under all the scenarios. Generally, the changes in runoff conditions will be more obvious in the future. Our findings can be important for integrated water resources management and planning in this region.-
Key words:
- MIKE11-NAM /
- Daqinghe Basin /
- Simulation /
- Runoff /
- Climate change
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Figure 2.
MIKE11-NAM structure (DHI, 2009) QOF: overland flow; QIF: interflow; GWPUMP: groundwater pumping; GWL: maximum groundwater depth; CAFLUX: capillar flux; Sy: specific yield; BF: baseflow.
Table 1. Parameters used in the MIKE11-NAM model during simulation
Parameter Description Value range Final value Umax (mm) Maximum water content in the surface storage 10−20 12.3 Lmax (mm) Maximum water content in root zone storage 50−300 50.5 CQOF Overland flow runoff coefficient 0−1 0.894 CKIF (h) Time constant for routing interflow 200−1000 449.4 CK1,2 (h) Time constant for routing overland flow 3−48 40.5 TOF Root zone threshold value for overland flow 0−0.99 0.685 TIF Root zone threshold value for interflow 0−0.99 0.0121 TG Root zone threshold value for groundwater recharge 0−0.99 0.154 CKBF (h) Time constant for routing base flow 1−5000 2761 Table 2. Trends of temperature, precipitation and runoff from 1980 to 2017 in the Fuping Basin based on the Mann-Kendall test
Time Temperature Precipitation Runoff ℃∙decade−1 P-value mm∙decade−1 P-value mm∙decade−1 P-value Annual 0.4 <0.001 8.0 0.33 −2.2 0.36 Spring 0.6 <0.001 −3.0 0.30 0.4 0.29 Summer 0.3 <0.05 −2.4 0.38 −3.0 0.19 Autumn 0.3 <0.05 17.5 <0.001 0.8 0.34 Winter 0.7 <0.001 1.0 0.09 −0.3 0.32 Table 3. Bias correction performance of four regional climate models for monthly precipitation and temperature estimation compared to the observed data
Variable Model Before correction After correction R2 RMSE R2 RMSE Temperature ACCESS_ESM1_5 0.97 2.18 ℃ 0.97 1.83 Can_ESM5 0.95 4.30 ℃ 0.95 2.40 EC_EARTH3 0.95 2.69 ℃ 0.96 2.27 MPI_ESM1_2HR 0.96 2.17 ℃ 0.97 2.05 Precipitation ACCESS_ESM1_5 0.43 50.71 mm 0.43 49.00 Can_ESM5 0.35 51.45 mm 0.45 49.73 EC_EARTH3 0.46 50.15 mm 0.47 48.62 MPI_ESM1_2HR 0.41 50.51 mm 0.47 49.85 Table 4. Precipitation and temperature change comparison between historical observed data (1985−2014) and future data (2025−2054) based on four regional climate models (RCM) and multimodel ensemble under 3 scenarios
Variable Scenario Historical
(1985−2014)RCM model (2025−2054) Multi-model
ensemble (MME)ACCESS-ESMI-5 Can-ESM5 EC-Earth3 MPI-ESMI-2HR Temperature (℃) SSP1-2.6 7.8 +1.96 +2.06 +2.54 +0.93 +1.87 SSP2-4.5 +1.97 +2.43 +2.44 +0.83 +1.92 SSP5-8.5 +2.52 +2.97 +2.92 +1.37 +2.45 Precipitation (mm) SSP1-2.6 670 +72 +142 +104 +70 +97 SSP2-4.5 +99 +187 +121 +89 +124 SSP5-8.5 +23 +194 +129 +51 +99 “+” means the increase. -
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