Variation of Aridity Index and the Role of Climate Variables in the Southwest China
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. Data
3. Methods
3.1. Calculation of Aridity Index
3.2. Attribution Analysis
3.3. Statistical Analysis
4. Results
4.1. Variation of AI
4.2. Sensitivity of AI to Climate Variables
4.3. Attribution of the Variation in Aridity Index
5. Discussion
5.1. Uncertainties
5.2. Impacts of Change in Aridity Index on Drought
5.3. Impact of Change in Aridity Index on Water Resource
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Notations
AI | aridity index. |
ET0 | potential evapotranspiration(mm). |
Pre | precipitation (mm). |
ETpan | pan evaporation (mm). |
Tmax, Tmin, Ta | daily maximum, minimum and air temperature (°C). |
Tmax,k, Tmin,k | daily maximum, minimum in kelvin temperature (°C). |
es, ea | saturation and actual vapor pressure (kPa). |
U2 | wind speed at 2 m (m s−1). |
Pc | corrected precipitation. |
Pg | precipitation measured from the gauge station. |
ΔPw | wetting loss. |
CR | ratio of gauge measured precipitation to the true precipitation. |
G | soil heat flux density (MJ m−2 d−1). |
Rs | incoming solar radiation (MJ m−2 d−1). |
Rn | net radiation (MJ m−2 d−1). |
Rns | net shortwave radiation (MJ m−2day−1). |
Rnl | net long-wave radiation (MJ m−2day−1). |
∆ | slope of saturated vapor pressure (kPa °C−1). |
γ | psychrometric constant (kPa °C−1). |
α | albedo (α = 0.23). |
n | actual duration of sunshine. |
N | maximum possible duration of sunshine. |
as, bs | parameters in calculating Rs (as = 0.25, bs = 0.50). |
S(x) | sensitivity coefficient of AI to x variable. |
L_AI | detected aridity index trend by linear regression. |
C_AI | total contribution of variables. |
ε | error between C_AI and L_AI. |
RC(xi) | relative contribution of each climate variable. |
Cr(xi) | contribution of each climate variable. |
ETa | actual evapotranspiration. |
R | streamflow. |
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Differential Items | Formula |
---|---|
Pre | Tmax | Tmin | ea | U2 | Rs | ET0 | AI | ρ(ε)% | |
---|---|---|---|---|---|---|---|---|---|
Trend | −2.9474 | 0.0460 ** | 0.0346 ** | −0.0004 | 0.0039 | 0.0127 | 3.3135 | 0.0053 * | - |
−0.0007 | 0.0416 | 0.0129 | −0.2769 | 0.0656 | 0.0211 | 0.0009 | - | - | |
S(xi) | −1.00 | 1.11 | 0.19 | −0.56 | 0.10 | 0.33 | 1.00 | ||
Cr(xi) | 0.0021 | 0.0019 | 0.0004 | 0.0001 | 0.0003 | 0.0003 | 0.0029 | - | −6.12 |
RC(xi) | 38.98 | 36.26 | 8.49 | 2.27 | 4.83 | 5.10 | 56.95 | 95.93 | - |
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Li, Y.; Feng, A.; Liu, W.; Ma, X.; Dong, G. Variation of Aridity Index and the Role of Climate Variables in the Southwest China. Water 2017, 9, 743. https://doi.org/10.3390/w9100743
Li Y, Feng A, Liu W, Ma X, Dong G. Variation of Aridity Index and the Role of Climate Variables in the Southwest China. Water. 2017; 9(10):743. https://doi.org/10.3390/w9100743
Chicago/Turabian StyleLi, Yanzhong, Aiqing Feng, Wenbin Liu, Xieyao Ma, and Guotao Dong. 2017. "Variation of Aridity Index and the Role of Climate Variables in the Southwest China" Water 9, no. 10: 743. https://doi.org/10.3390/w9100743