Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Hydrol. Earth Syst. Sci. Discuss., 12, 12911–12945, 2015 www.hydrol-earth-syst-sci-discuss.net/12/12911/2015/ doi:10.5194/hessd-12-12911-2015 © Author(s) 2015. CC Attribution 3.0 License. This discussion paper is/has been under review for the journal Hydrology and Earth System Sciences (HESS). Please refer to the corresponding final paper in HESS if available. Dominant climatic factor driving annual runoff change at catchments scale over China Z. Huang1,2,3 and H. Yang1 1State Key Laboratory of Hydro-Science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing, 100084, China 2Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China 3University of Chinese Academy of Sciences, Beijing, 100049, China Received: 13 November 2015 – Accepted: 5 December 2015 – Published: 15 December 2015 Correspondence to: H. Yang ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. 12911 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract With global climate changes intensifying, the hydrological response to climate changes has attracted more attentions. It is beneficial not only for hydrology and ecology but also for water resources planning and management to reveal the impacts of climate 5 change on runoff. It is of great significance of climate elasticity of runoff to estimate the impacts of climatic factors on runoff. In addition, there are large spatial variations in climate type and geography characteristics over China. To get a better understand- ing the spatial variation of runoff response to climate variables change and detect the dominant climatic factor driving annual runoff change, we chose the climate elastic- 10 ity method proposed by Yang and Yang (2011), where the impact of the catchment characteristics on runoff was represented by a parameter n. The results show that the dominant climatic factor driving annual runoff is precipitation in the most part of China, net radiation in the lower reach of Yangtze River Basin, the Pearl River Basin, the Huai River Basin and the southeast area, and wind speed in part of the northeast China. 15 1 Introduction Climate change has become increasingly significant, and it has important impacts on hydrology cycle and the water resource management. Changes in climatic factors and runoff have been observed in many different regions of China. The reduction of pre- cipitation occurred in the Hai River Basin, the upper reach of the Yangtze River Basin 20 and the Yellow River Basin, and the increase occurred in the in the western China (Yang et al., 2014). A 29 % decline of surface wind speed occurred in China during 1966 to 2011, which would have lead to a 1–6 % increase in runoff and a 1–3 % de- crease in evapotranspiration at most regions in China (Liu et al., 2014). Most of the river basins in north China have exhibited obvious decline in mean annual runoff, such 25 as the Shiyang River Basin (Ma et al., 2008), the Yellow River Basin (Yang et al., 2004; Tang et al., 2007; Cong et al., 2009), and the Hai River Basin (Ma et al., 2010). The 12912 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | hydrologic processes have been influenced by different climatic factors. For example, decline in land surface wind speed could lead to decrease in evapotranspiration and changes in precipitation may affect water generation and concentration. However, the dominant climatic factor driving annual runoff change is still unknown in many catch- 5 ments of China. There are several approaches to investigate the feedback of annual runoff to climate change, such as the hydrologic models (Yang et al., 1998, 2000; Arnold et al., 1998; Arnold and Fohrer, 2005), the climate elasticity method (Schaake, 1990; Sankarasubra- manian et al., 2001) and the statistics method (Vogel et al., 1999). Therein, the climate 10 elasticity method was widely used in quantifying the effects of climatic factors on runoff, such as in the Yellow River Basin (Zheng et al., 2009; Yang and Yang, 2011), the Luan River Basin (Xu et al., 2013), the Chao–Bai Rivers Basin (Ma et al., 2010), and the Hai River Basin (Ma et al., 2008; Yang and Yang, 2011). A simple climate elasticity method was firstly defined by Schaake (1990) to estimate 15 the impacts of precipitation (P ) on annual runoff (R): dR dP = ε (P ,R) , (1) R P P where εP is the precipitation elasticity. To consider the effects of precipitation and air temperature on runoff, Fu et al. (2007) calculated the runoff change as: dR dP dT = ε + ε , (2) R a P b T 20 where εa and εb are the precipitation elasticity and air temperature elasticity, respec- tively. Five categories of methods can be used to estimate climate elasticity (Sankarasub- ramanian et al., 2001), and the analytical derivation method has been widely used in many studies because it is not only clear in theory but also does not need a large 25 amount of historical observed data. Arora (2002) projected a equation to calcuated the response of runoff to precipitation and potential evaporation change: 12913 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ∆R φF 0(φ) ∆P φF 0(φ) ∆E = 1 + 0 0 , (3) R 1 F (φ) P − 1 F (φ) E " − 0 # − 0 where φ = E/P and F0(φ) is a Budyko formula and F00(φ) is the derivation to φ. The climate elasticity of runoff was evaluated in the upper reach of the Yellow River Basin by using Eq. (3) (Zheng et al., 2009). To evaluate the impact from other climatic factors, 5 Yang and Yang (2011) proposed an analytical method, which was based on the Pen- man equation and the annual water balance equation, to quality the runoff change to changes in different climatic factors. By taking advantage of the mean annual climatic factors in the study period, the runoff elasticity to precipitation (P ), mean air tempera- ture (T ), net radiation (Rn), relative humidity (RH), and wind speed (U2) were derived, 10 and the runoff change can be expressed as follows: dR dP dR dU dRH = ε + ε n + ε dT + ε 2 + ε , (4) P Rn T U2 RH R P Rn U2 RH where ε , ε , ε , ε , and ε are the runoff elasticity to precipitation (P ), net ra- P Rn T U2 RH diation (Rn), mean air temperature (T ), wind speed (U), and relative humidity (RH), respectively. However, this method was only tested in several catchments of the non- 15 humid Northern China. There are large spatial variations in both geography characteristics and climate type over China, which would result in a large variation in the hydrologic response to cli- mate change. Therefore, the current study aims to: (1) further validating the method proposed by Yang and Yang (2011), (2) evaluating the climate elasticity of climatic fac- 20 tors to runoff at catchments scale over China, and (3) estimating the impact of climate variation on runoff and then detecting the dominant climatic factor driving annual runoff change. 12914 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 Climate elasticity method based on the Budyko hypothesis At catchment scale, there is abvious relationship between evaporation, precipitation and potential evaporation, which is referred as the Budyko hypothesis (Budyko, 1961). An analytical equation of the Budyko hypothesis was inferred by Yang et al. (2008): E0P 5 E = , (5) n n 1/n P + E0 where the parameter n represents the characteristics of the catchment, for exam- ple land use and coverage change, vegetation, slope and climate seasonality (Yang et al., 2014). The water balance equation can be simplified as P = E + R at catchment scale for the long term, so runoff can be expressed as follows: E0P 10 R = P . (6) − n n 1/n E0 + P To attribute the contribution of changes in P and E0 to runoff, Yang and Yang (2011) derived a new equation: dR dP dE0 = ε1 + ε2 , (7) R P E0 where ε1 and ε2 are the climate elasticity of runoff to P and E0, respectively; and they (1 ∂E/∂P )P ∂E/∂E0E0 15 − can be estimated as ε1 = P E and ε2 = P E . The potential evaporation E0 1 − − − (mmday− ) can be evaluatedby the Penman equation (Penman, 1948): ∆ γ E = (R G)/λ + 6.43(1 + 0.536U )(1 RH)e /λ, (8) 0 ∆ + γ n − ∆ + γ 2 − s and the physical meaning of these symbols were shown in Table 1. 12915 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Similar to Eq. (7), the response of potential evaporation to climatic factors can be estimated as: dE0 dRn dU2 dRH = ε3 + ε4dT + ε5 + ε6 , (9) E0 Rn U2 RH where ε3,ε4,ε5,ε6 are the elasticity of potential evaporation to net radiation, air temper- Rn ∂E0 1 ∂E0 5 ature, wind speed and relative humidity, respectively. Therein, ε3 = , ε4 = , E0 ∂Rn E0 ∂T U2 ∂E0 RH ∂E0 ε5 = , and ε6 = . Due to the complex relationship between E0 and T , the E0 ∂U2 E0 ∂RH value of ∂E0 was calculated by finite difference method, while ∂E , ∂E , ∂E0 , ∂E0 and ∂T ∂P ∂E0 ∂Rn ∂U2 ∂E0 ∂RH were calculated by finite differential method. Substitution of Eq. (9) into Eq. (7) leads to: dR dP dRn dU2 dRH 10 = ε1 + ε2ε3 + ε2ε4dT + ε2ε5 + ε2ε6 . (10) R P Rn U2 RH Denoted Eq. (10) as follows: R∗ = P ∗ + Rn∗ + T ∗ + U2∗ + RH∗, (11) where P ∗, Rn∗, T ∗, U2∗ and RH∗ symbolize the runoff changes caused by the changing in P , Rn, T , U2 and RH, respectively.