Attribution of Runoff Reduction in the Juma River Basin to Climate Variation, Direct Human Intervention, and Land Use Change
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Collection
2.3. Hydro-Climatic Trend Analysis
2.4. SWAT Model Set Up and Calibration
2.4.1. Model Description
2.4.2. Model Calibration and Validation
2.4.3. Evaluating the Relative Contribution of Climate, Land Use Change, and Direct Human Intervention
3. Results
3.1. Changing Trends of Observed Runoff
3.2. Model Valuation
3.3. Contributions of Different Factors to Runoff Change
4. Discussion
4.1. The Effects of Climate Change on Runoff
4.2. The Effects of Land Use Change on Runoff
4.3. The Combined Effects of Climate Change and Human Direct Intervention on Runoff
4.4. Uncertainty Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Station | Period | Change Rate (°C/year) | The Significance Level |
---|---|---|---|
Yuxian | Annual | 0.05 | 0.001 |
Hot-day | 0 | - | |
Frost-day | −0.54 | 0.001 | |
Beijing | Annual | 0.04 | 0.001 |
Hot-day | 0.01 | 0.05 | |
Frost-day | −0.43 | 0.001 | |
Baoding | Annual | 0.03 | 0.001 |
Hot-day | 0 | - | |
Frost-day | −0.50 | 0.001 | |
Huailai | Annual | 0.03 | 0.001 |
Hot-day | 0 | - | |
Frost-day | −0.44 | 0.001 |
Station | Change Rate (mm/year) | The Significance Level | Month | Change Rate (mm/year) | The Significance Level |
---|---|---|---|---|---|
Xinggezhuang | −2.121 | 0.1 | January | −0.002 | - |
Zijingguan | −3.681 | 0.05 | February | −0.044 | 0.1 |
Yangjiaping | −2.314 | 0.05 | March | −0.062 | - |
Shimen | −1.547 | - | April | 0.015 | - |
Aihecun | −1.566 | - | May | 0.379 | 0.05 |
Dongtuanbao | −3.061 | 0.05 | June | 0.499 | - |
Qizhongkou | 1.558 | - | July | −0.806 | - |
Mangshikou | −2.080 | 0.05 | August | −1.330 | 0.05 |
Piandaozi | −0.760 | - | September | 0.300 | - |
Shidu | −0.612 | - | October | −0.076 | - |
Zhaojiapeng | 0.390 | - | November | −0.069 | 0.1 |
Chajianling | −2.830 | 0.1 | December | 0.007 | - |
Wanganzhen | −1.722 | - | |||
Tuanyuancun | −2.100 | 0.1 |
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Types | Area (% of Total Area) | Wilting Point (% Vol) | Field Capacity (% Vol) | Saturation (% Vol) | Sat Hydraulic Cond (mm/h) | Matric Bulk Density (g/cm3) |
---|---|---|---|---|---|---|
Cambisols | 21.54 | 6.2–26.3 | 12.9–38.7 | 39.6–47.1 | 1.49–50.9 | 1.4–1.6 |
Luvisols | 59.95 | 6.6–14.4 | 11.8–30.9 | 39.6–42.9 | 3.59–49.88 | 1.51–1.59 |
Leptosols | 4.98 | 13.3–13.9 | 26.1–29.5 | 43.8–49.6 | 9.9–16.8 | 1.33–1.49 |
Regosols | 10.96 | 11.4–15.6 | 22.7–28.5 | 40.4–48.3 | 4.99–15.3 | 1.37–1.58 |
Fluvisols | 2.58 | 11.6–11.8 | 25.9–26.7 | 41.2–42.2 | 8.49–8.81 | 1.53–1.56 |
Parameter Name | Description | Initial Range | Zijingguan | Zhangfang | ||
---|---|---|---|---|---|---|
Final Range | Calibrated Value | Final Range | Calibrated Value | |||
r__CN2 | Initial SCS runoff curve number for moisture condition II | (−0.3, 0.3) | (−0.190, 0.108) | −0.162 | (−0.172, 0) | −0.12 |
v__ALPHA_BF | Baseflow alpha factor (1/days) | (0, 1) | (0.016, 0.43) | 0.39 | (0.036, 0.318) | 0.19 |
v__GW_DELAY | Groundwater delay time (days) | (0, 500) | (150.84, 391.96) | 195.11 | (140.84, 264.65) | 255.36 |
v__GWQMN | Threshold depth of water in the shallow aquifer required for return flow to occur (mm H2O) | (20, 5000) | (150.49, 584.01) | 478.45 | (273.05, 581.89) | 427.5 |
v__GW_REVAP | Groundwater “revap” coefficient. | (0.02, 0.2) | (0.109, 0.2) | 0.18 | (0.11, 0.16) | 0.14 |
v__ESCO | Soil evaporation compensation factor | (0, 1) | (0.494, 0.887) | 0.84 | (0.429, 0.756) | 0.47 |
v__CH_K2 | Effective hydraulic conductivity in tributary channel alluvium (mm/h) | (0.02, 150) | (69.31, 109.89) | 74.04 | (72.11, 112.89) | 78.46 |
r__SOL_AWC | Available water capacity of the soil layer (mm H2O/mm soil) | (−0.5, −0.5) | (−0.040, 0.154) | 0.057 | (−0.081, −0.120) | 0.03 |
r__SOL_K | Saturated hydraulic conductivity (mm/h) | (−0.5, 0.5) | (−0.0.34, 0.169) | 0.067 | (−0.154, 0.061) | −0.04 |
Station | Period | Monthly Discharge (m3/s) | Ens | R2 | Re | |
---|---|---|---|---|---|---|
Simulated | Measured | |||||
Zijingguan | calibration | 7.38 | 8.04 | 0.89 | 0.86 | 8.2% |
Validation | 7.59 | 8.64 | 0.84 | 0.86 | 12.15% | |
Zhangfang | calibration | 20.24 | 19.02 | 0.88 | 0.89 | −6.4% |
Validation | 19.42 | 20.07 | 0.86 | 0.87 | 3.21% |
Types | Late 1970s | Late 1980s | 1995 | 2000 | 2005 | 2010 |
---|---|---|---|---|---|---|
Agriculture | 565.4 | 565.5 | 560.7 | 561.4 | 559.6 | 556.5 |
Dense Forest | 1653.1 | 1653.7 | 1756.3 | 1670.7 | 1671.0 | 1670.1 |
Shrubwood | 1138.6 | 1139.6 | 1103.6 | 1136.0 | 1136.2 | 1135.2 |
Open Forest | 301.7 | 301.8 | 225.9 | 252.8 | 253.2 | 253.1 |
Grass | 1011.4 | 1011.8 | 1021.3 | 1047.1 | 1046.1 | 1046.2 |
Water Bodies | 34.0 | 34.0 | 34.1 | 34.1 | 34.1 | 34.1 |
Urban | 29.5 | 29.5 | 34.0 | 34.2 | 36.6 | 41.0 |
Unused Land | 1.5 | 1.5 | 1.5 | 1.5 | 1.5 | 1.5 |
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Bu, J.; Lu, C.; Niu, J.; Gao, Y. Attribution of Runoff Reduction in the Juma River Basin to Climate Variation, Direct Human Intervention, and Land Use Change. Water 2018, 10, 1775. https://doi.org/10.3390/w10121775
Bu J, Lu C, Niu J, Gao Y. Attribution of Runoff Reduction in the Juma River Basin to Climate Variation, Direct Human Intervention, and Land Use Change. Water. 2018; 10(12):1775. https://doi.org/10.3390/w10121775
Chicago/Turabian StyleBu, Jingyi, Chunxia Lu, Jun Niu, and Yanchun Gao. 2018. "Attribution of Runoff Reduction in the Juma River Basin to Climate Variation, Direct Human Intervention, and Land Use Change" Water 10, no. 12: 1775. https://doi.org/10.3390/w10121775
APA StyleBu, J., Lu, C., Niu, J., & Gao, Y. (2018). Attribution of Runoff Reduction in the Juma River Basin to Climate Variation, Direct Human Intervention, and Land Use Change. Water, 10(12), 1775. https://doi.org/10.3390/w10121775