Examining the inﬂuence of river–lake interaction on the drought
Journal of Hydrology 522 (2015) 510–521 Contents lists available at ScienceDirect Journal of Hydrology journal homepage: www.elsevier.com/locate/jhydrol Examining the inﬂuence of river–lake interaction on the drought and water resources in the Poyang Lake basin Zengxin Zhang a,b,⇑, Xi Chen c, Chong-Yu Xu d,e, Yang Hong f, Jill Hardy f,g, Zhonghua Sun h a Joint Innovation Center for Modern Forestry Studies, College of Biology and the Environment, Nanjing Forestry University, Nanjing, Jiangsu 210037, China Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, 210044, China c State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering, Hohai University, Nanjing 210098, China d Department of Geosciences, University of Oslo, Norway e Department of Earth Sciences, Uppsala University, Sweden f School of Civil Engineering and Environmental Sciences, The University of Oklahoma, Norman, OK 73019, USA g School of Meteorology, The University of Oklahoma, Norman, OK 73019, USA h Network and Information Center, Changjiang Water Resources Commission, Wuhan 430010, China b a r t i c l e i n f o Article history: Received 9 April 2013 Received in revised form 2 January 2015 Accepted 4 January 2015 Available online 13 January 2015 This manuscript was handled by Konstantine P. Georgakakos, Editor-in-Chief, with the assistance of Michael Bruen, Associate Editor Keywords: Extreme droughts Poyang Lake Yangtze River The Three Gorges Dam River–lake interaction s u m m a r y In recent years, the Poyang Lake basin is in a prolonged drought which has placed immense pressure on the water resources utilization. In this paper, we explore the spatial and temporal distributions of extreme droughts in the Poyang Lake basin by using the methods of SPI (Standardized Precipitation Index) and EOF (Empirical Orthogonal Function) for the period of 1956–2009, which are inﬂuenced by regional precipitation anomalies and river–lake interaction due to water impounding of the Three Gorges Dam (TGD). The results show that: (1) the Poyang Lake basin experienced six extreme droughts during the past 60 years, which lead to decreases in streamﬂow from ﬁve tributary rivers down to the Poyang Lake. The droughts in the 1960s and the 2000s were the most serious ones. However, there was an increasing trend of streamﬂow in the upper and middle Yangtze in the 1960s, and a decreasing trend appeared in the 2000s. The decline of streamﬂow in the upper Yangtze reaches has lowered the water level of lower Yangtze River which has caused more outﬂow from the Poyang Lake to the Yangtze River; (2) the operation of the Three Gorges Dam (TGD) has altered the seasonal pattern of ﬂow regimes in the Poyang Lake and signiﬁcantly reduced the water level in the lower Yangtze River during the TGD impounding period from late September to early November; and (3) the conjunction of extreme droughts in the Poyang Lake and the upper Yangtze reaches coincided with the impounding of the TGD is the main cause of the low water level in the Poyang Lake. Although the impact of the recent droughts in the Poyang Lake and upper Yangtze reaches has played a crucial role in the low water level of Poyang Lake, more attention should be paid to its sensitivity to the inﬂuence of the large dam-induced changes in the interaction between river and lake, particularly during impounding periods. Ó 2015 Elsevier B.V. All rights reserved. 1. Introduction ‘‘Drought’’ as a natural hazard is mainly caused by large-scale climatic variability while water scarcity is more a result of human inﬂuence. Making the distinction between them is not trivial because they often occur simultaneously (Van Loon and Van Lanen, 2013). Evaluation of drought conditions in a particular area is the key step for planning water resources. Numerous drought ⇑ Corresponding author at: Joint Innovation Center for Modern Forestry Studies, College of Biology and the Environment, Nanjing Forestry University, Nanjing, Jiangsu 210037, China. Tel./fax: +86 25 85428963. E-mail address: [email protected] (Z. Zhang). http://dx.doi.org/10.1016/j.jhydrol.2015.01.008 0022-1694/Ó 2015 Elsevier B.V. All rights reserved. indices have been developed to monitor droughts (Rossi et al., 2007), including the worldwide used indices of the Standardized Precipitation Index (SPI, e.g. Mckee et al., 1993; Zhang et al., 2012; Portela et al., 2015), the Normalised Flow Index (NFI, e.g. Gosling, 2014), the Reconnaissance Drought Index (RDI, e.g. Takiris and Vangelis, 2005; Rahmat et al., 2015), and the Palmer Drought Severity Index (PDSI, e.g. Palmer, 1965). These indices have been developed to evaluate the water supply deﬁcit in relation to the time duration of precipitation shortage. However, the characteristics of drought in different climate zones may be different. A standardized index is often used to compare drought conditions in different areas. For example, the Standardized Precipitation Index (SPI) is one of the most powerful indices which can be Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 computed on different time scales (Bordi and Sutera, 2007). The SPI has been used in many studies (e.g., Hayes et al., 1999; Bordi et al., 2004; Chen et al., 2009; Zhang et al., 2011b) and it has proved to be a useful tool in the estimation of the intensity and duration of drought events (Bordi et al., 2004). SPI was also applied to examine the effects of large dam on hydrological droughts by comparing the drought index before and after the dam construction (Cancelliere et al., 1998; López-Moreno et al., 2009; Lorenzo-Lacruz et al., 2010). Poyang Lake, China’s largest freshwater lake, is located on the southern bank of the lower Yangtze River. The water level of the Poyang Lake depends on watershed runoff from the ﬁve tributary river basins and the water exchanges with the Yangtze River (Li et al., 2015a; Zhang et al., 2014). It varies greatly both in area and volume with seasonal and inter-annual changes. The lake level is elevated to the extent that all ﬂoodplains are inundated, thus forming a vast lake. In the drier season, lake level declines and lake water recedes into sublacustrine channels and the ﬂoodplains are exposed, resulting in the lake surface almost dwindling to a meandering line. At the moment, the Poyang Lake is effectively just a river channel (http://www.jxsl.gov.cn/). The impact of climate variability and change on the Poyang Lake outﬂows, particularly on the ﬂoods, has been extensively studied (e.g., Jiang and Shi, 2003; Shankman et al., 2006; Guo et al., 2008; Zhang et al., 2011a; Zhao et al., 2010; Li et al., 2015b). Different conclusions have been drawn by previous studies which were undertaken at different time and used different methods and data. The river–lake interaction related to ﬂood storage ability of the lake and TGD was investigated by Nakayama and Shankman. (2013a), and they pointed out that the TGD will increase ﬂood risk during the early summer monsoon, in contrast to the original justiﬁcations for building the dam, due to complex river–lake– groundwater interactions. Hu et al. (2007) reported that basin effect (basin discharge generated by rainfall) has played a primary role inﬂuencing the water level of Poyang Lake and development of severe ﬂoods, while the Yangtze River played a complementary role of blocking outﬂows from the lake. Zhang et al. (2011a) also found that the occurrence of water intrusion from the Yangtze River to the Poyang Lake was heavily inﬂuenced by hydrological processes of the Poyang Lake basin. Guo et al. (2011) found that the Poyang Lake has the largest outﬂow to the Yangtze River and exerts a strong pressure on the mainstream during April–June, and the Yangtze River’s blocking and/or reversed ﬂow to the Poyang Lake are the strongest during July–September. Currently, the most severe droughts in the Poyang Lake basin have drawn people’s attention to the water resources shortage problem along the lower reaches of the Yangtze River. The lower reaches of the Yangtze River, covering eight provinces of both Central and Southern China, are usually considered to be an area with relatively abundant water resources. However, the continuous droughts in this region have changed this situation and the Poyang Lake is facing the danger of water shortage. The precipitation in this region during November 2010–May 2011 was the lowest in the past 60 years. The Poyang Lake shrank to its smallest area of 1326 km2 in May 2011, reducing about two-thirds of its normal surface area of 3585 km2. Meanwhile, the prolonged drought in the Yangtze River basin coincides with the water level rising of the Three Gorges Dam (TGD) from 135 to 175 m. Recently, low water levels in the drier season of the lower Yangtze River have started earlier and lasted longer, which aroused a debate over whether the TGD contributed to the decrease in water level of the Poyang Lake (Zhang et al., 2014). Some researchers suggested the TGD, along with the droughts, had caused the water level decline in the Poyang Lake in the drier season (Dai et al., 2008; Guo et al., 2011, 2012). Guo et al. (2011) reported that the inﬂuence of the TGD has resulted in less than 10% of the variation in 511 the Yangtze River ﬂow in most of the seasons. Dai et al. (2008) pointed out that 54% of the water ﬂux was lost at Datong station during September 20–October 27, 2006, in comparison with the same period in 2005. It can be estimated that the impounding of TGD and the extreme drought in 2006 contributed 9% and 45% of this loss, respectively. Meanwhile, Guo et al. (2012) suggested that the impacts of large dams in the Yangtze River should alter from the previous studies in the dam-river setting to a new damriver–lake construction. Nevertheless, Lai et al. (2014) also suggested that the effects of the TGD on downstream rivers and lakes will be intensiﬁed in the foreseeable future when many ongoing and planned large-scale dams located in the upstream tributaries in the Yangtze River, with a combined water storage capacity far larger than the TGD, will be put into operation in the near future. On the other hand, the Government of Jiangxi province situated in Poyang Lake area has stirred up another controversy by pushing to build a dam at the outlet of the Poyang Lake to prevent water from ﬂowing into the Yangtze River. So water shortage is becoming one of the most serious problems in the Poyang Lake. Although there are some studies about the inﬂuences of drought and TGD impounding on the lower Yangtze River (e.g. Chen et al., 2001; Dai et al., 2008; Guo et al., 2011), question like, ‘‘How do the droughts in the Poyang Lake basin together with the associated streamﬂow of the upper Yangtze River affect the water resources of Poyang Lake?’’, has not yet been analyzed thoroughly, which is of great scientiﬁc merit in understanding the causes of current water shortage in the Poyang Lake. The scientiﬁc problems to be investigated in this paper include: (1) Are there any regularity of the extreme droughts in the Poyang Lake basin and how do they affect the water resources? (2) To what extent does the low streamﬂow of the Yangtze River affect the water resources in the Poyang Lake? (3) Are there any differences in the interaction of the Yangtze River and the Poyang Lake before and after the impoundment of the TGD? In this study, we attempt to address these problems based on a thorough analysis of long-term hydrological and precipitation datasets across the Yangtze River basin. This study is of importance in further understanding the impacts of the droughts coincided with the dam-induced river–lake interaction on hydrological processes of the Poyang Lake. 2. Data and methodology 2.1. Study area and data Poyang Lake basin, located in Jiangxi province, has an area of 162,200 km2, occupying 9% of the Yangtze River basin. The water balance at the Poyang Lake is mainly dominated by ﬁve main tributary rivers: Ganjiang River, Fuhe River, Xinjiang River, Raohe River and Xiushui River, and several smaller rivers (as shown in Fig. 1). In addition, inﬂow from the Yangtze River to the Poyang Lake also plays an important supplementary role in maintaining the water resources stability of the Poyang Lake (Hu et al., 2007). Thus, the inﬂow of the Poyang Lake should include two parts: the inﬂow from the ﬁve tributary rivers and inﬂow from the Yangtze River. The Hukou station is the junction of the Poyang Lake basin with the Yangtze River, and streamﬂow from this station is regarded as the outﬂow of the Poyang Lake. The highest recorded lake level at Hukou hydrological station is 22.59 m. The corresponding lake area is approximately 4500 km2 with the lake volume reaching 34 billion m3. The lowest lake level at the same station is 5.90 m, and its corresponding lake area and lake volume are 146 km2 and 450 million m3, or rather, 1/32 and 1/76 of the largest area and volume, respectively. Daily mean streamﬂow and water level data from 16 hydrological stations during the period of 1956–2009 and 215 daily 512 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 Fig. 1. Location of the study area and concerned hydro-meteorological stations ((a) the location of the Yangtze River basin; (b) the location of the Poyang Lake basin). precipitation stations (of which 83 stations are located in the Poyang Lake basin) from 1957 to 2009 in the Yangtze River basin are used in this study. A few missing precipitation data are interpolated by the average value of its adjacent stations. The sum of the ﬁve tributary rivers in the Poyang Lake River basin was chosen as the inﬂow to the Poyang Lake. The key hydrological stations of Cuntan, Yichang, Hankou, Jiujiang and Datong in the main Yangtze River were selected to analyze the streamﬂow variabilities of the Yangtze River, and the Hukou station was selected to analyze the water exchange between the Poyang Lake and the Yangtze River (Referring to Fig. 1 and Table 1 for the location and basic data of the Poyang Lake basin and the gauging stations). 2.2. Methodology The SPI is a drought index based on the probability of an observed precipitation deﬁcit occurring over a given prior time period (McKee et al., 1993). It is a useful tool for monitoring dry and wet periods on multiple time scales and for comparing climatic conditions of areas governed by different hydrological regimes. The assessment periods are considered to range from 1 to 36 months where the shorter time scales may represent agricultural drought and the longer time scales relate to hydrological drought. The SPI at a 24-month time scale is used in this work and it is usually considered as a hydrological drought index which can be used to monitor surface water resources, e.g., river 513 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 Table 1 Characteristics of the hydrologic records of stations at the Poyang Lake River basin and the main stream of Yangtze River basin. River Sub-basins Station Poyang Lake Xiushui R. Qiujin Wangjiabu Waizhou Lijiadu Meigang Dufengkeng Hushan Xingzi Duchang Ganjiang R. Fuhe R. Xinjiang R Raohe R. Lake Region Control station of Poyang Lake Hukou Mainstream Cuntan Yichang Hankou Jiujiang Datong Upper Yangtze Middle Yangtze Lower Yangtze Area (104 km2) 9914 3548 80,948 15,811 15,535 5013 6374 265 107 1986 379 543 147 220 Annual mean water level (m) 22.90 18.43 25.98 19.30 22.49 20.79 13.43 13.84 162,200 4593 12.77 866,559 1,010,000 1,488,036 1,523,000 1,705,383 10,964 13,752 22,163 23,125 27,876 156.80 42.99 18.97 13.49 8.58 ﬂows (Hayes et al., 1999). A clear and detailed description of the steps required to calculate the SPI is provided in Lloyd-Hughes and Saunders (2002). The SPI calculation for any location is based on the long-term precipitation record for a desired period. This long-term record is ﬁtted to a probability distribution, which is then transformed into a standard normal distribution so that the mean SPI for the location and desired period is zero (Edwards and McKee, 1997) (http://drought.mssl.ucl.ac.uk/spi. html). The gamma distribution was tested to be a good candidate probability distribution function for the precipitation amount in the Yangtze River (result not shown) and it is used for calculation of SPI in this paper. The drought is classiﬁed into four categories – mild, moderate, severe and extreme drought (Mckee et al., 1993; Chen et al., 2009). Standardized Runoff Index (SRI) is also adopted in this research to calculate the hydrologic droughts (Gosling, 2014). To compare the drought characteristics between different drought periods in the Poyang Lake, the drought duration (D) and drought magnitude (M) are adopted in this study. The drought duration (D) can be deﬁned as the cumulative months when a continuous drought occurs (SPI (i)< 1.0 is used at the beginning and ending of a drought and SPI (i)< 2.0 is regarded as an extreme drought event). The drought magnitude (M) is deﬁned as: D X M ¼ SPIðiÞ Annual mean stremaﬂow (m3/s) 3. Results 3.1. The impacts of extreme droughts on the Poyang Lake’s water resources The aspects of drought over the Poyang Lake basin during the last several decades have been evaluated by computing the SPI and SRI on a 24-month time scale using the observed monthly precipitation and runoff datasets. Fig. 2a shows the temporal ð1Þ i¼1 where SPI(i) is the SPI value, and i is the sequential month of a time series of a drought (Chen et al., 2009). To examine more details on temporal variability of hydrological time series, cumulative curve analysis is performed. The cumulative curve method was ﬁrst used by Hurst (1951) to determine the storage capacity of reservoirs on the Nile River. The cumulative departure is used in this paper to detect the streamﬂow and water level variability in different regions for a long time. The Empirical Orthogonal Function (EOF) method is used to analyze the main drought features of spatial and temporal variability in the Poyang Lake basin. The EOF analysis is a statistical technique that linearly transforms an original set of variables into a substantially small set of uncorrelated variables representing most of the information of the original set of variables (North, 1984; von Storch, 1995,1999). Basically, the goal of EOF analysis is to reduce the dimensionality of the original data set (Jolliffe, 2002; Wilks, 2006; Hannachi et al., 2007). Fig. 2. The SPI and SRI in the Poyang Lake basin and Yangtze River basin during 1957–2009 ((a) the ﬁrst PC of the SPI-24 in the Poyang Lake and the SRI-24 of Waizhou station; (b) the SRI-24 of Yichang and Hankou station; (c) the ﬁrst PC of the SPI-24 in the Poyang Lake basin and the SRI-24 in Yichang station). 514 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 Table 2 The drought characteristics for six extreme droughts in the Poyang Lake basin during the past 60 years (D, drought duration, unit: month; M, drought magnitude, unit: SPI value). D M M/D 1963/5–1967/2 1971/8–1973/1 1978/3–1980/10 1985/3–1988/4 2004/3–2005/11 2007/1–2009/11 45 172 3.8 17 51 3 31 105 3.4 37 118 3.2 21 60 2.9 35 129 3.7 Fig. 3. The amount of accumulated lake inﬂow and lake outﬂow anomalies compared to the reference period of 1956–2009 for six different extreme drought events in the Poyang Lake basin. distributions of the dryness and wetness of SPI in the Poyang Lake basin by using the EOF method. It is noted that the ﬁrst principal component (PC1) explains more than 60% of the total variation of the SPI-24. The PC1 can present the long-term features of dryness and wetness in the Poyang Lake basin as a whole. The Ganjiang River basin is the biggest tributary river in the Poyang Lake basin with an area of 80,948 km2, occupying 49.9% of the Poyang Lake basin. This is much greater than the second biggest tributary river, the Fuhe River basin, with an area of 15,811 km2, occupying 9.8% of the Poyang Lake basin. So the SRI of Waizhou station at the control hydrological station of Ganjiang River basin might present the main hydrologic droughts of the Poyang Lake to a great extent. Fig. 2a also shows that the SRI-24 of Waizhou station has a similar pattern of extreme dryness and wetness to that of the SPI-24 in the Poyang Lake basin. In other words, it indicates that the SPI can be used in the calculation of extreme droughts in the Poyang Lake basin by comparison of the SPI and SRI (Fig. 2a). From this ﬁgure, six continuous extreme drought events are found in the Poyang Lake basin during the past 60 years (Fig. 2a). Table 2 shows the drought characteristics of the six extreme drought events. Four continuous extreme drought events in the Poyang Lake basin exceed 30 months during the past 60 years. The droughts in the 515 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 Table 3 The amount of lake inﬂow, lake outﬂow and water level of Poyang Lake in October during the droughts of the 1960s and 2000s (DQ, lake inﬂow minus lake outﬂow). Year Lake streamﬂow (108 m3) Inﬂow Water level (m) Outﬂow DQ Hukou Jiujiang Datong 1960s 1964 1965 1966 35 45 23 91 91 60 56 46 37 17.7 15.9 13.2 17.3 17.1 15.7 12.5 11.1 8.8 2000s 2007 2008 2009 27 38 22 116 120 46 89 82 24 12.3 12.7 9.7 16.7 17.5 14.8 8.4 8.7 6.4 1960s 2010s 34 29 81 94 47 65 15.6 11.6 16.7 16.3 10.8 7.8 3.2. The impacts of Yangtze river–lake interaction on the Poyang Lake’s water resources Fig. 4 shows the percentage of monthly mean streamﬂow in the upper Yangtze (Yichang station), middle Yangtze (Hankou station) and Poyang Lake basin (Hukou station) to the whole Yangtze basin (Datong station). The amount of annual mean streamﬂow in the upper and middle Yangtze and Poyang Lake basin are 46.1%, 79.5% and 15.6% of the whole Yangtze basin, respectively, for 1957–2009. Fig. 4a indicated that the seasonal percentage of the streamﬂow in the upper and middle Yangtze to the whole Yangtze basin varies greatly and the higher proportion appears in July, August and September while the lower proportion occurs in February, March and April. However, the percentages of the streamﬂow in the Poyang Lake to the whole Yangtze basin are opposite, the higher proportion appears in spring (MAM) and lower proportion can be found in August, September and October. Fig. 4b shows the correlations between the streamﬂow at Yichang, Hankou and Datong stations and water level at Hukou station. Higher correlations can also be found between the streamﬂow in the upper 100 Hukou Yichang Hankou (a) Percent (%) 80 60 40 20 0 1 2 3 4 5 6 7 8 9 10 Nov 11 12 13 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Dec Ann Yichang Hankou Datong (b) 1.0 Correlations 1960s and 2000s were the most severe ones, with the longest drought duration (D) records of 45 and 56 months, and the largest drought magnitude (M) of 172 and 189, respectively. The extreme droughts in the 2000s occurred during 2004/3–2005/11 and 2007/1–2009/11. As mentioned above the characteristics of droughts during the 2000s are similar to those of the 1960s in terms of the drought magnitude (M), drought duration (D) and drought intensity (M/D) (Table 2). However, there is an interval of one year between the two extreme droughts in the 2000s, while the extreme droughts occur consecutively in the 1960s. The annual and seasonal mean inﬂow (the sum of the streamﬂow from the ﬁve tributary river basins) agrees well with the outﬂow (Hukou station) in the Poyang Lake basin. To reveal the difference between the inﬂow and outﬂow of the Poyang Lake during different drought periods, the accumulated inﬂow and outﬂow departures compared with the average over 1956–2009 were further analyzed (Fig. 3). It shows a decline of lake inﬂow and lake outﬂow during the six extreme drought events. The amount of accumulated decrease in the inﬂow of Poyang Lake is over 3 billion m3 for both major droughts in the 1960s and 2000s (Fig. 3a and f). However, there are distinct dissimilarities between them. Although the amount of accumulated lake inﬂow anomalies in the droughts of the 2000s is somewhat similar to that of the 1960s, the amount of accumulated lake outﬂow anomalies in the 1960s are larger than that of the 2000s, which indicates the water remaining in the Poyang Lake during the droughts of the 2000s is less than that of the 1960s. Similar results can be found in Table 3. The much lower water level at Hukou station in October during the droughts of the 2000s led to a signiﬁcant increase of the Poyang Lake outﬂow compared with that of the 1960s. 0.8 0.6 0.4 0.2 0.0 1 2 3 4 5 6 7 8 9 10 Nov 11 12 13 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Dec Ann Yichang Hankou Datong (c) 1.0 Correlations Average 0.8 0.6 0.4 0.2 0.0 1 2 3 4 5 6 7 8 9 10 Nov 11 12 13 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Dec Ann Months Fig. 4. Correlations of monthly streamﬂow and water level between different hydrological stations in the Poyang Lake and main stream of Yangtze River. The red dotted line indicates the trend is statistically signiﬁcant at the 5% signiﬁcance level. (a) the percentage of monthly and annual mean streamﬂow at Yichang, Hankou and Hukou stations to the streamﬂow at Datong station; (b) the correlations between the streamﬂow of Yichang, Hankou, Datong and water level at Hukou station; (c) same as (b) but for Duchang station). Yangtze and the water level at Hukou station in summer (JJA) and autumn (SON). The correlations between the streamﬂow in the upper-middle Yangtze (Yichang and Hankou in Fig. 4b) and the water level at Hukou station are the highest with less seasonal variations. Similar results can be obtained for the correlation 516 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 Fig. 5. The composite monthly mean higher water level (L P 18 m, n = 16 years), lower water level (L 6 16.5 m, n = 17 years) and middle water level (16.5 < L < 18 m, n = 20 years) at the Poyang Lake during 1957–2009 and the corresponding water level variability at (a) Jiujiang, (b) Hukou, (c) Xingzi and (d) Duchang (stations. (n is the years, L is the monthly mean water level in August). Fig. 6. The accumulated monthly streamﬂow anomalies compared with the average over 1956–2009 in the Yangtze River basin. The inﬂow and outﬂow of Lake represent the water balance of the Poyang Lake. between the streamﬂow at Yichang, Hankou and Datong stations and water level at Duchang station (Fig. 4c). The composite analysis of higher water level, middle water level and lower water level at Jiujiang station, which is very close to that of Hukou station (32 km upstream), was made to uncover the impacts of the Yangtze River on the Poyang Lake’s water resources. The highest water level at Jiujiang station appears in July and August, where the water level L P 18 m in August was regarded as the highest water level year, L 6 16.5 m was the lowest water level year, and a level of 16.5 < L < 18 m was a middle water level year. Statistical results during the period of 1957–2009 indicate that there are 16, 20 and 17 of the highest, middle and lowest water level years, respectively. For the higher water level years, the average water level at Jiujiang station in July and August is over 19 m and then falls slowly to a minimum water level of 9 m in January. For the lower water level years, the average water level is reduced to approximately 17 and 15 m in July and August, respectively. The averaged water level for the middle water level years is between the higher water level and lower water level from July to December (Fig. 5a). For the higher water level years at Jiujiang station, the composite monthly averaged water level at Hukou and Xingzi stations (Xingzi station is quite close to the Hukou station in the Poyang Lake) from July to December is also higher than that of lower water level years (Fig. 5b and c). Furthermore, the changing pattern of water level at Hukou and Xingzi stations are very close to that of Jiujiang station. However, there is a little difference between the composite higher water level years and lower water level years at Duchang station located in the central area of Poyang Lake, which indicates that the inﬂuences of the Yangtze River on the Poyang Lake’s water level reduce gradually with distance away from the Yangtze River (Fig. 5d). Fig. 6 shows the accumulated streamﬂow anomalies in the Poyang Lake basin and the upper and middle Yangtze River basin at Cuntan, Yichang and Hankou stations, respectively. The trends of streamﬂow in the upper and middle Yangtze reaches show a similar tendency: streamﬂow anomalies increase in the 1960s, 1980s and at the turn of the 21th century, and decrease in the 1970s, the early and middle of 1990s and the latter half of the 2000s. However, the inﬂow and outﬂow of the Poyang Lake basin are opposite to the upper Yangtze reaches in the 1960s. During the droughts of the 1960s, the inﬂow and outﬂow of the Poyang Lake decreased sharply; however, there was a marked increase in the streamﬂow in the upper and middle Yangtze reaches. As for the 517 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 Precipitation Anomalies (mm) <= -700 -400 - -699 - 200 - -399 -100 - -199 -99 - 99 100 - 199 200 -300 >=300 Precipitation Anomalies (mm) <= -700 -400 - -699 - 200 - -399 -100 - -199 -99 - 99 100 - 199 200 -300 >=300 Fig. 7. The accumulated monthly precipitation anomalies during the drought period of (a) 1963–1967 and (b) 2007–2009, compared with the average over 1956–2009 in the Yangtze River basin. droughts in the 2000s, the situation was completely different from that in the 1960s. The streamﬂow decreased obviously in the Poyang Lake and also decreased in the upper and middle Yangtze reaches. Similar results can also be found in comparison between the extreme droughts and pluvials in the Poyang Lake and in the upper and lower Yangtze reaches by using the methods of SPI and SRI (Fig. 2). The accumulated precipitation anomalies during the droughts of the 1960s and 2000s might partly explain the difference between them (Fig. 7). Greater negative precipitation anomalies can be found both of them in the Poyang Lake basin, while in the upper and middle Yangtze, positive precipitation anomalies can be found in the 1960s and negative precipitation anomalies appear in the 2000s. The inconsistent variation of streamﬂow in the Poyang Lake basin to the upper Yangtze reaches during the droughts of the 1960s increased the blocking and/or reversing ﬂow from the Yangtze River to the Poyang Lake. During the droughts of the 1960s, the blocking and/or reversing ﬂow lasted 181 days with the amount of water intrusion from Yangtze River to the Poyang Lake was 24.9 billion m3, and the largest monthly amount of water intrusion was detected in September 1964 with a value of over 7.1 billion m3. For the droughts of the 2000s, the blocking and/or reversing ﬂow was only 69 days with the amount of 7.8 billion m3 water intrusion from the Yangtze River to the Poyang Lake in the years of 2007 and 2008, and almost no water intrusion from the Yangtze River to the Poyang Lake in 2009. 3.3. The impacts of TGD on the Poyang Lake’s water resources The operation of the TGD has changed the seasonal variations of the Poyang Lake and the Yangtze River forcing. The strongest inﬂuence of the TGD on the lower Yangtze reaches occurs mainly from Table 4 Reservoir inﬂow and outﬂow of the Three Gorges Dam (TGD) in October during the period of 2006–2009 (4Q, TGD outﬂow minus TGD inﬂow, QJj is the streamﬂow at Jiujiang station, DQ/QJj means the impoundment of TGD account for the streamﬂow loss in the lower Yangtze. The reservoir inﬂow and outﬂow of the TGD data comes from: China Three Gorges Corporation, http://www.ctgpc.com.cn/). Year 2006 2007 2008 2009 Reservoir streamﬂow (108 m3) Percentage DQ/QJj (%) Inﬂow Outﬂow DQ 350 358 398 330 283 308 300 222 66 50 97 108 19 11 20 31 September to October when the TGD impounds each year. The TGD inﬂuence can be seen from the following evidence: (1) the impounding of water by the Three Gorges Projects (TGP) lasted from September 20 to October 28, 2006, which raised the water level in the front of the dam from 135 to 156 m over this period. The total impounded water in the TGD was around 66 108, 50 108, 97 108 and 108 108 m3 in October during the years of 2006, 2007, 2008 and 2009, respectively; and the total impounded water by TGD in October 2008 and 2009 might contribute around 20% and 31%, respectively, of the streamﬂow at Jiujiang station (Table 4). The impounding of the TGD caused over 3 billion m3 water ﬂow from the Poyang Lake to the Yangtze River in October 2008 which is more than that of 1958 and 1991; (2) Cumulative probabilities of streamﬂow and water levels for the Poyang Lake and lower Yangtze River in October during the preTGD (1957–2002) and the post-TGD (2003–2009) periods demonstrate impacts of the TGD on the Poyang Lake outﬂow (Fig. 8). Although the Poyang Lake inﬂow of the pre-TGD period is larger than that of the post-TGD period, the lake outﬂow of the postTGD period is signiﬁcantly larger than that of the pre-TGD period 518 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 14000 14000 (a) Inflow of Poyang Lake Streamflow (m /s) 10000 3 3 Streamflow (m /s) 12000 8000 6000 4000 P (pre-TGD) P (post-TGD) 10000 8000 6000 4000 2000 0 P (pre-TGD) P (post-TGD) -2000 2000 0 (b) Outflow of Poyang Lake (Hukou) 12000 -4000 0 20 40 60 80 100 0 20 40 P (%) 24 (c) Xingzi 22 22 20 20 Water level (m) Water level (m) 24 60 18 16 14 12 10 100 (d) Hukou 18 16 14 12 10 P (pre-TGD) P (post-TGD) 8 P (pre-TGD) P (post-TGD) 8 6 6 0 20 40 60 80 100 0 20 40 P (%) 24 60 24 (e) Jiujiang 22 22 20 20 18 16 14 12 10 P (pre-TGD) P (post-TGD) 8 18 16 14 12 10 P (pre-TGD) P (post-TGD) 6 20 40 100 (f) Datong 8 6 0 80 P (%) Water level (m) Water level (m) 80 P (%) 60 80 100 0 20 40 60 80 100 P (%) P (%) Fig. 8. Cumulative probabilities of streamﬂow and water levels for pre-TGD (1957–2002) and post-TGD (2003–2009) period in the Poyang Lake and lower Yangtze River. Table 5 Observed streamﬂow and water level of the Poyang Lake, and simulated water level at Hukou station in October for the selected drought years. The selected years before and after TGP are with similar lake inﬂow and streamﬂow of middle and lower Yangtze River, and similar water level at Hukou, Jiujiang and Datong stations in October (Obs, observed water level; Scenario-1, simulated water level at Hukou station using the observed streamﬂow at Datong station according to the correlations between the streamﬂow at Datong station and water level at Hukou station; Scenario-2, same as Scenario-1, but using the streamﬂow of Datong plus the impoundment of TGD; DH, water level of Scenario-2 minus that of Scenario-1). Year Streamﬂow (108 m3) Lake inﬂow 2007 1960 2008 2001 2009 1978 27 24 38 33 22 16 Hukou 116 77 120 80 46 27 Water level (m) Hankou 538 568 583 696 389 453 Datong 700 703 737 802 470 501 for the extreme drought years (P < 20% in Fig. 8b). Moreover, the backward ﬂow from the Yangtze River to the Poyang Lake (negative value in Fig. 8b) was found during the pre-TGD period but it Jiujiang 12.8 13.5 13.2 14.4 10.4 11.8 Datong 8.4 8.5 8.7 9.4 6.4 7.0 Hukou Obs Scenario-1 Scenario-2 DH 12.3 12.6 12.7 13.7 9.7 10.8 12.8 13.0 13.3 14.1 10.5 10.8 13.3 0.5 13.8 0.5 12.0 1.5 disappeared for the post-TGD period. The cumulative probabilities of the water levels at the Poyang Lake (Xingzi station), outlet of the Poyang Lake (Hukou station) and the lower Yangtze (Jiujiang and 519 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 Fig. 9. The correlations between daily water level at Hukou station and streamﬂow at Datong station during the recession period (from 1st August to 31st December) of 1957–2009. 2004 20 Datong stations) during the post-TGD period (Fig. 8c–f) are always lower than those of the pre-TGD period; (3) the lake inﬂow and water level for the six drought years with similar streamﬂow of middle and lower Yangtze River, and similar water level at Hukou, Jiujiang and Datong stations in October represent different behaviors before and after the TGP impounding (e.g. 2007 vs. 1960, 2008 vs. 2001, 2009 vs. 1978 in Table 5). Although the amount of lake inﬂow in October for the post-TGD years was larger than that of the pre-TGD period, the lake level (Obs. at Hukou station in Table 5) for the post-TGP period was lower than that of the pre-TGP period due to the increased Poyang Lake outﬂow. The inﬂuence of the TGD impounding on the water level of the Poyang Lake is further estimated by correlation analysis. As shown in Fig. 9, a good relationship between water level at Hukou station and streamﬂow at Datong station can be found during the past several decades. Therefore, the correlation between them during the recession period (from 1st August to 31st December) is adopted to reveal the impacts of the TGD impounding on the water level of Poyang Lake (Fig. 9). Fig. 10 shows the observed and simulated water levels at the outlet of Poyang Lake (Hukou station) during 12 Aug 1 Observed Scenario 1 Scenario 2 Sep 1 Oct 1 Nov 1 Dec 1 14 12 10 Aug 1 18 18 16 16 Observed Scenario 1 Scenario 2 14 12 8 Aug 1 Oct 1 Nov 1 Dec 1 2008 20 Oct 1 Dec 1 2007 10 (d) Observed Scenario 1 Scenario 2 Sep 1 Oct 1 Nov 1 Dec 1 2009 20 (e) Nov 1 12 Aug 1 (f) 18 Water level (m) 18 16 14 12 8 Observed Scenario 1 Scenario 2 Aug 1 Sep 1 10 Sep 1 14 8 Sep 1 Observed Scenario 1 Scenario 2 20 (c) 10 Water level (m) 16 8 2006 20 Water level (m) Water level (m) 14 Water level (m) Water level (m) 16 8 (b) 18 18 10 2005 20 (a) 16 14 12 10 8 Oct 1 Nov 1 Month/Day Dec 1 Aug 1 Observed Scenario 1 Scenario 2 Sep 1 Oct 1 Nov 1 Dec 1 Month/Day Fig. 10. The observed and simulated water levels in two scenarios with and without the TGD impounding at the outlet of the Poyang Lake during the recession period of 2004–2009 (Scenario-1, the water level at Hukou station with the impounding of TGD; Scenario-2, the water level at Hukou station without the impounding of TGD). 520 Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 the recession period of 2004–2009 for the two scenarios with and without the TGD impounding. For Scenario-1, the water level at Hukou station with the impounding of TGD was simulated by the observed streamﬂow at Datong station using the relationship between the streamﬂow at Datong station and water level at Hukou station. For Scenario-2, the water level at Hukou station without the impounding of TGD was simulated by the reconstructed streamﬂow at Datong station using the same relationship. Because the distance between Datong station and TGD is approximately 1,129 km, it takes 12 days for the water ﬂowing from TGD to Datong station (http://www.cjw.com.cn/). The reconstructed streamﬂow at Datong station was estimated as the total of the impounding of TGD (TGD inﬂow minus TGD outﬂow) and the streamﬂow of Datong with a lag of 12 days. The reliability of the simulated results by the correlation analysis was tested by comparison of the simulated and observed water levels at Hukou station. The simulated water levels agree well with the observed water levels at Hukou for the years of 2004–2009 (Scenario-1 vs. observation in Fig. 10). The simulated water levels were quietly close to the observed water levels in October for the selected drought years before and after the TGP operation periods (Scenario-1 vs. observation in Table 5). Therefore, the correlation analysis is reliable to estimate the inﬂuence of the impounding of the TGD on the water level of the Poyang Lake. Fig. 10 shows that the simulated water levels in Scenario-2 without the impounding of TGD are higher than those of the Scenario-1 with the impounding of TGD during the period of 2006–2009. The difference of the simulated water levels between Scenarios-1 and Scenarios-2 at the outlet of Poyang Lake (Hukou station in Table 5) indicates that the water level in October declined from 0.5 m in 2007 and 2008 to 1.5 m in 2009 due to the impounding of TGD. 4. Discussions and conclusions Severe water shortages of Poyang Lake have aroused wide concern recently and raised the possibility of the TGD being responsible for the low water level at the Poyang Lake. Despite various studies revealing the considerable effects on the water level of Poyang Lake (Dai et al., 2008; Guo et al., 2011; Lai et al., 2014), the TGD’s impact needs to be further assessed combined with the extreme droughts in the Poyang Lake basin and the upper Yangtze reaches. It remains unknown whether the shortage of water in the Poyang Lake is a trend or a regime shift, and how the TGD operation contributes it, which is of high importance for policymakers as it may lead to different decisions. This work quantiﬁes the extreme drought events and the TGD’s contributions to recent low water levels at the Poyang Lake by using a ﬁve-decade record of the streamﬂow and precipitation data in the Yangtze River basin. Continuous low water levels at the Poyang Lake in recent years are relevant to the conjunction of extreme droughts in the Poyang Lake basin and the upper Yangtze River basin. Comparison between the droughts of the Poyang Lake in the 1960s and 2000s explains how the extreme droughts affect the water resource in the Poyang Lake. Both of the droughts in the 1960s and 2000s in the Poyang Lake basin have caused an obvious decrease of streamﬂow from ﬁve tributary river basins to the Poyang Lake. However, the streamﬂow in the upper Yangtze reaches sharply decreased during the droughts of the 2000s while it increased obviously in the droughts of the 1960s compared to the period of 1957–2009. The decline of streamﬂow in the upper Yangtze reaches has lowered the water level in the lower Yangtze River. As an overﬂow lake with the seasonal characteristic pattern of taking in and sending out water, the water level in the lower Yangtze River plays a major role in the lake outﬂow of the Poyang Lake during the recession period. Less water ﬂows backward into the Poyang Lake from the Yangtze River during the drought of the 2000s compared to that of the 1960s. As a result, the outﬂow from Poyang Lake to the Yangtze River increases greatly in the droughts of the 2000s with the amount of 195 billion m3 compared to that of the 1960s (138 billion m3). These results agree well with the research of Lai et al. (2014) who pointed out that the recent extremely low water levels at lower Yangtze River were mainly because of the remarkable decline in streamﬂow from the middle and upper Yangtze reaches resulting from precipitation changes and possible human activities by using a newly developed hydrodynamic model. Guo et al. (2008) also pointed out that the interaction between the Poyang Lake and the Yangtze River strongly affects the Poyang Lake water resources and drought potentials in the lake basin. The TGD’s operation has altered the seasonal pattern of ﬂow regimes and signiﬁcantly reduced the water level mainly in the drought period of October when the TGD is impounding each year (Guo et al., 2012; Lai et al., 2014). This study demonstrates that the lake outﬂow for the post-TGP period is higher than that of pre-TGP period for the corresponding drought years before and after TGP impounding (e.g. 2007 vs. 1960, 2008 vs. 2001, and 2009 vs. 1978) although the lake inﬂow from the ﬁve tributaries of the watershed for the post-TGP period is less than that of the preTGP period. It was proven by the cumulative probabilities that the lake outﬂow in October for the post-TGD period was signiﬁcantly larger than that of the pre-TGD period for the extremely drought years. This larger outﬂow from the Poyang Lake during the post-TGP period results from the decline of water levels in the lower Yangtze reaches due to the TGD impounding. The TGD impounding induced water level declines in 0.5, 0.5 and 1.5 m at Hukou station in October in 2007, 2008 and 2009, respectively, according to correlation analysis in this study. This study shows that, although the operation of TGD has altered the seasonal pattern of ﬂow regimes in the lower Yangtze reaches, the conjunction of extreme droughts in the Poyang Lake basin and lack of rain in the upper Yangtze River basin is the main cause of the low water level in the Poyang Lake. Some researches show that groundwater also affects this hydrologic change, in particular, in drought seasons and after construction of TGD (Dai et al., 2010; Nakayama and Shankman, 2013b). With more and more big dams have been and are being built in China and other countries, dams have major impacts on river hydrology and produce a hydrologic regime differing signiﬁcantly from the pre-impoundment natural ﬂow regime. Interaction between large rivers and reservoirs as well as natural lakes directly connecting to the rivers is an issue of international signiﬁcance. For example, Al-Faraj and Scholz (2014) found that the upstream dams and large-scale water withdrawal have made great impacts on temporal river ﬂow regimes for the downstream countries in West Asia. Peters and Buttle (2010) also pointed out that the strength of the relationships between the Lake Athabasca and Peace River, Canada has been signiﬁcantly changed because the runoff from the Peace River headwaters has been stored in the man-made Williston Lake since 1968. The estimated average duration of obstruction was shortened more than two weeks and reverse ﬂow volume was reduced largely under a regulated regime compared to the simulated natural ﬂow. Therefore, the research methods of this paper might be applied for the above mentioned areas and other relevant areas. The results of this study also call for more attention on the conjunction of dam impounding and abnormal climate for a river regime. Acknowledgements This paper is ﬁnancially supported by the State Key Development Program for Basic Research of China (Grant No. Z. Zhang et al. / Journal of Hydrology 522 (2015) 510–521 2012CB417006), Project supported by the State Key Program of National Natural Science of China (Grant No. 40930635), National Natural Science Foundation of China (Grant Nos. 41171020, 51190090). The project supported by the Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology (KLM101) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). The third author was also supported by the Program of Introducing Talents of Discipline to Universities—the 111 Project of Hohai University. We would like to thank the National Climate Centre in Beijing for providing valuable climate datasets. References Al-Faraj, F.A.M., Scholz, M., 2014. 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