Multiple Changes in the Hydrologic Regime of the Yangtze River and the Possible Impact of Reservoirs

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Article Multiple Changes in the Hydrologic Regime of the Yangtze River and the Possible Impact of Reservoirs

Feng Huang 1,2,*, Nan Zhang 3, Xirong Ma 4, Dayong Zhao 1,2, Lidan Guo 5, Li Ren 1,2, Yao Wu 1,2 and Ziqiang Xia 1,2

1 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China; [email protected] (D.Z.); [email protected] (L.R.); [email protected] (Y.W.); [email protected] (Z.X.) 2 Department of City Resources and Environment, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China 3 Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China; [email protected] 4 The Pearl River Hydraulic Research Institute, Guangzhou 510611, China; [email protected] 5 International River Research Centre, Hohai University, Nanjing 210098, China; [email protected] * Correspondence: [email protected]; Tel./Fax: +86-25-8378-6845

Academic Editor: Y. Jun Xu Received: 19 July 2016; Accepted: 14 September 2016; Published: 20 September 2016

Abstract: This paper investigates hydrologic changes in the Yangtze River using long-term daily stream flow records (1955–2013) collected from four flow gauging stations located from the upper to the lower reaches of the river. The hydrologic regime is quantified using the Indicators of Hydrologic Alteration, which statistically characterize hydrologic variation within each year. Scanning t-test is applied to analyze multiple changes in the hydrologic regime at different time scales. Then, coherency analysis is applied to identify common changes among different hydrologic indicators and across different reaches of the Yangtze River. The results point to various change patterns in the five components of hydrologic regime, including the magnitude of monthly water conditions, magnitude and duration of annual extreme water conditions, timing of annual extreme water conditions, frequency and duration of high and low pulses, and rate and frequency of water condition changes. The 32 hydrologic indicators feature multiple temporal-scale changes. Spatial variations can be observed in the hydrologic changes of the upper, middle, and lower reaches of the river. Common changes in different reaches consist of hydrologic indicators including the monthly flow in October and the low-flow indicators. The monthly flow in October is dominated by decreasing trends, while the monthly flows between January and March, the annual minimum 1/3/7/30/90-day flows, and the base flow index are characterized by increasing trends. Low pulse duration and total days of low pulses feature downward trends. The coherency analysis reveals significant relationships between the monthly flow in October and the low-flow indicators, indicating that reservoir regulation is an important factor behind the hydrologic changes.

Keywords: multiple changes; scanning t-test; hydrologic regime; reservoir impacts; Yangtze River

1. Introduction The hydrologic regime, which is crucial to riverine ecosystems, sets a template for ecological processes, evolutionary adaptations, and native biodiversity maintenance [1]. The concept of “natural flow regime,” which has emerged as a paradigm for river conservation and restoration [2], recognizes the full range of natural flow variability as a primary driving force for sustaining the ecological health of a river. The hydrologic regime is influenced by both climate and anthropogenic activities, and many studies of worldwide hydrologic changes have considered these two factors [3–8]. Anthropogenic

Water 2016, 8, 408; doi:10.3390/w8090408 www.mdpi.com/journal/water Water 2016, 8, 408 2 of 20 activities that influence the hydrologic regime include land use [9], water diversion [10], and especially dam construction [11]. Dams provide numerous socio-economic benefits in terms of flood control, power generation, water supply, navigation, and recreation; however, dams disrupt river continuity and influence river hydrology, primarily by changing the timing, magnitude, and frequency of low and high flows. Ultimately, dams produce a hydrologic regime that differs significantly from the natural flow regime [6]. The altered hydrologic regime may influence riverine ecosystems by changing the natural habitat of native aquatic organisms, thereby affecting species structure and biodiversity; over time, these factors can influence the sustainable development of human society [12]. The Yangtze River, an important source of water, hydropower, and biological resources, plays a vital role in China’s economic development and ecological environmental conservation. Hydrologic changes in the Yangtze River and their associated ecological implications have attracted considerable attention from hydrologists, geomorphologists, and policy-makers. Huang et al. [13] documented flow complexity loss in the upper Yangtze River, attributing it to underlying surface condition changes influenced by human activities, especially reservoir construction. Yu et al. [14] analyzed the influence of the Gezhouba Reservoir and Three Gorges Reservoir, considering alterations in annual, seasonal, monthly, and daily flow. Gao et al. [15] further investigated the impact of the Three Gorges Reservoir on the flow regime in the middle and lower Yangtze River based on the Indicators of Hydrologic Alteration (IHA). The years when the reservoir began to store water were artificially designated as change points, and subsequent hydrologic changes were analyzed by comparing the regimes between the pre- and post-dam periods. Zhang et al. [16] applied scanning t-test to detect change points in monthly streamflow, ignoring variations in other hydrologic components like the magnitude, duration, and timing of annual extreme water conditions; the frequency and duration of high and low pulses; and the rate and frequency of water condition changes. Based on these previous studies, the present study aims to accomplish the following objectives: (1) to investigate abrupt changes at different time scales in the hydrologic regime of the Yangtze River and discuss the implications of these changes; and (2) to investigate the possible impacts of reservoirs. One improvement over previous studies is the systematic analysis of multiple changes in the hydrologic regime, as characterized by the IHA. This study identifies spatial variations in the hydrologic changes by analyzing the streamflow in the upper, middle, and lower reaches. Common changes in the hydrologic regimes of the different reaches are then investigated using an improved coherency analysis method. The impacts of reservoirs are revealed through the changing features of hydrologic indicators and the coherency between related hydrologic indicators. The novelty of this study is embodied in the improved coherency analysis method, which can detect common changes in different hydrologic indicators and different reaches, thereby revealing possible impacts of reservoirs.

2. Study Area and Data The Yangtze River (Figure1), located from 91 ◦ E to 122◦ E and 25◦ N to 35◦ N, is the longest river in China and the third longest river in the world. It originates in the Qinghai-Tibet Plateau, ﬂows about 6300 km eastwards to the East China Sea, and drains an area of approximately 1.8 million km2. The Yangtze River basin lies in the monsoon region of East Asia’s subtropical zone, and it experiences mean annual precipitation of approximately 1090 mm [17]. Generally, spring lasts from March to May, summer lasts from June to August, autumn lasts from September to November, and winter lasts from December to February of the following year. Over 50,000 dams have been constructed in the Yangtze River basin, with many located in the upper reaches [18]. The dams’ total storage capacity is almost 180 billion m3, representing approximately 20% of the river’s annual runoff. The total reservoir volume has transitioned through four clear stages since the 1950s: (1) Total volume increased slowly until 1970; (2) Volume increased rapidly from 1970 to 1980; (3) Volume increased slowly from 1980 to 1995; and (4) Volume increased rapidly after 1995 [19]. Noticeably, the Three Gorges Reservoir, with a total storage capacity of 39.3 billion m3, began to operate in 2003. For more information about the distribution of major reservoirs in the Yangtze River basin, refer to Wang et al. [20]. Water 2016, 8, 408 3 of 20 Water 2016, 8, 408 3 of 20

FigureFigure 1. 1.Locations Locations ofof thethe Yangtze River and the the flow ﬂow gauging gauging stations. stations.

This study selected four flow gauging stations (Table 1), namely Cuntan, Yichang, Hankou, and This study selected four flow gauging stations (Table1), namely Cuntan, Yichang, Hankou, and Datong, as data‐gathering points for analyzing hydrologic changes. The Cuntan station is located Datong,upstream as data-gatheringfrom the Gezhouba points Dam for and analyzing the Three hydrologic Gorges Dam. changes. Located at The the Cuntan confluence station of the is upper located upstreamand middle from reaches the Gezhouba of the Yangtze Dam and River, the the Three Yichang Gorges station Dam. is Located located 44 at thekm confluencedownstream of from the upper the andThree middle Gorges reaches Dam ofand the 6 Yangtzekm downstream River, the from Yichang the Gezhouba station is Dam, located at a 44point km where downstream the hydrologic from the Threeregime Gorges is directly Dam andaffected 6 km by downstream the cascade from reservoirs. the Gezhouba The Hankou Dam, station at a point is located where in the the hydrologic middle regimereaches, is directly1.2 km below affected the by confluence the cascade of the reservoirs. Yangtze TheRiver Hankou and its stationlargest tributary, is located the in theHanjiang middle reaches,River. 1.2The km Datong below station the confluence is located ofin thethe Yangtzelower reaches, River and and its it occupies largest tributary, a position the at Hanjiang which it River.can Themonitor Datong the station runoff is and located sediment in the load lower from reaches, the Yangtze and River it occupies to the aEast position China atSea. which Daily it streamflow can monitor thedata runoff for andthe sedimentfour stations load from from 1 the January Yangtze 1955, River to to 31 the December East China 2013, Sea. were Daily collected streamflow from data the for theChangjiang four stations Water from Resources 1 January Commission 1955, to 31 December(China). No 2013, data were is missing collected from from the streamflow the Changjiang series. Water Resources Commission (China). No data is missing from the streamflow series. Table 1. Flow gauging stations at the main stem of the Yangtze River. Table 1. Flow gauging stations at the main stem of the Yangtze River. Drainage Area Distance to Estuary Flow Gauging Station Location Period of Record (104 km) (km) Drainage Area Distance to Estuary Flow Gauging Station Location Period of Record Cuntan (106.6° E, 29.6° N) (1086.664 km) (km)2495 1955–2013 Yichang (111.3° E, 30.7° N) 100.55 1837 1955–2013 Cuntan (106.6◦ E, 29.6◦ N) 86.66 2495 1955–2013 Hankou (114.3° E, 30.6° N) 148.80 1136 1955–2013 Yichang (111.3◦ E, 30.7◦ N) 100.55 1837 1955–2013 DatongHankou (114.3(117.6°◦ E,E, 30.6 30.8°◦ N) N) 148.80170.54 1136624 1955–20131955–2013 Datong (117.6◦ E, 30.8◦ N) 170.54 624 1955–2013 3. Methods 3. Methods 3.1. Indicators of Hydrologic Alteration 3.1. Indicators of Hydrologic Alteration The widely used Indicators of Hydrologic Alteration (IHA) contain a total of 33 hydrologic parametersThe widely (Table used 2), Indicatorswhich are ofcategorized Hydrologic into Alteration five groups (IHA) of hydrologic contain a features total of [21]. 33 hydrologic The five parametersgroups consist (Table of2), the which magnitude are categorized of monthly into fivewater groups conditions, of hydrologic magnitude features and [duration21]. The fiveof annual groups consistextreme of water the magnitude conditions, of timing monthly of annual water extreme conditions, water magnitude conditions, and frequency duration and of duration annual of extreme high waterand low conditions, pulses, and timing rate ofand annual frequency extreme of water water condition conditions, changes. frequency The parameter and duration “number of of high zero and‐ lowflow pulses, days” and is not rate used and in frequency this study of because water conditionno zero‐flow changes. event occurred The parameter in the Yangtze “number River of zero-flow during days”the study is not period. used in Periods this study during because which no the zero-flow daily flow event is above occurred the 75th in and the below Yangtze the River 25th percentile during the studyare labeled period. Periodshigh and during low pulses, which therespectively. daily flow isThe above IHA the parameters 75th and beloware calculated the 25th percentileusing non are‐ labeledparametric high and(median/percentile) low pulses, respectively. statistics, Thewhich IHA are parameters useful because are calculated of the skewed using non-parametric(non‐normal) nature of many hydrologic datasets. The hydrologic year is defined as lasting from April to March of (median/percentile) statistics, which are useful because of the skewed (non-normal) nature of many the following year, according to the hydrologic features of the Yangtze River where the rainy season hydrologic datasets. The hydrologic year is defined as lasting from April to March of the following begins in April. Each IHA parameter is calculated for every hydrologic year and the results are further year, according to the hydrologic features of the Yangtze River where the rainy season begins in April. analyzed by scanning t‐test to reveal multi‐scale abrupt behaviors. Each IHA parameter is calculated for every hydrologic year and the results are further analyzed by scanning t-test to reveal multi-scale abrupt behaviors.

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Table 2. Indicators of Hydrologic Alteration.

IHA Group Hydrologic Parameter (units) Abbreviation Median flow of April (m3/s) April Median flow of May (m3/s) May Median flow of June (m3/s) June Median flow of July (m3/s) July Median flow of August (m3/s) August Group 1: Magnitude of Median flow of September (m3/s) September monthly flows Median flow of October (m3/s) October Median flow of November (m3/s) November Median flow of December (m3/s) December Median flow of January (m3/s) January Median flow of February (m3/s) February Median flow of March (m3/s) March Annual 1-day minimum flow (m3/s) 1-day minimum Annual 3-day minimum flow (m3/s) 3-day minimum Annual 7-day minimum flow (m3/s) 7-day minimum Annual 30-day minimum flow (m3/s) 30-day minimum Annual 90-day minimum flow (m3/s) 90-day minimum 3 Group 2: Magnitude Annual 1-day maximum flow (m /s) 1-day maximum 3 and duration of annual Annual 3-day maximum flow (m /s) 3-day maximum 3 extreme flows Annual 7-day maximum flow (m /s) 7-day maximum Annual 30-day maximum flow (m3/s) 30-day maximum Annual 90-day maximum flow (m3/s) 90-day maximum Number of zero-flow days Base flow index (annual 7-day minimum flow Base flow index divided by annual mean flow) Group 3: Timing of Julian date of annual 1-day minimum flow Date of minimum annual extreme flows Julian date of annual 1-day maximum flow Date of maximum Number of low pulses in each hydrologic year Low pulse count Group 4: Frequency Median duration of low pulses (days) Low pulse duration and duration of high Number of high pulses in each hydrologic year High pulse count and low pulses Median duration of high pulses (days) High pulse duration Rise rate (Median of all positive differences 3 Rise rate Group 5: Rate and between consecutive daily values) (m /s/day) frequency of Fall rate (Median of all negative differences 3 Fall rate flow changes between consecutive daily values) (m /s/day) Number of flow reversals Number of reversals

3.2. Scanning t-Test Conventional methods such as the Mann-Kendall and Pettitt tests search for a single abrupt change in a time series. In contrast, the scanning t-test, which is the Student’s t-test grafted by the wavelet technique, can detect signiﬁcant changes in sub-series averages on different time scales within a long time series [22]. The Student’s t-test assumes that the time series has a normal distribution; therefore, the IHA data are log-transformed to be normally distributed before the scanning t-test is applied. Statistic t(n, j) is deﬁned as the difference in the sub-sample averages between every two adjoining sub-series with equal sub-series size (n), expressed as follows:

1/2 2 2 −1/2 t(n, j) = (xj2 − xj1) × n × (sj2 + sj1) (1) where:  j−1 j−1  = 1 ( ) 2 = 1 ( ( ) − )2  xj1 n ∑ x i , sj1 n−1 ∑ x i xj1  i=j−n i=j−n j+n−1 j+n−1 (2)  1 2 1 2  xj2 = n ∑ x(i), sj2 = n−1 ∑ (x(i) − xj2)  i=j i=j Water 2016, 8, 408 5 of 20 where: j = n + 1, n + 2, ... , N − n + 1 serves as the reference time point. The sub-sample size may vary as n = 10, 11, ... , < N/2, or it may be selected at suitable intervals. The significance level is set as 0.05(t0.05). Since the significance level varies with n and j, the test statistic is normalized as follows to make values comparable: tr(n, j) = t(n, j)/t0.05 (3) when |tr(n, j)| ≥ 1.0, the abrupt change is significant at the 95% confidence level. Meanwhile, tr(n, j) ≥ 1.0 denotes significant increases, and tr(n, j) ≤ −1.0 denotes significant decreases.

3.3. Coherency Analysis The coherency of abrupt changes between two series is originally deﬁned as follows [23]:

1/2 trc(n, j) = sign[tr1(n, j)tr2(n, j)] {|tr1(n, j)tr2(n, j)|} (4)

The coherency of abrupt changes between more than two series (m ≥ 2) is improved as

i f sign[tr1(n, j)] = sign[tr2(n, j)] = ... = sign[trm(n, j)] t (n, j) = |t (n, j)t (n, j) ... t (n, j)|1/m rc r1 r2 rm (5) else 1/m trc(n, j) = − |tr1(n, j)tr2(n, j) ... trm(n, j)|

Equation (5) yields the same results as Equation (4) when m = 2. The series have signiﬁcant changes in the same direction when trc(n, j) ≥ 1, and they have signiﬁcant changes in opposite (increasing or decreasing) directions when trc(n, j) ≤ −1.

4. Results

4.1. Changes in Hydrologic Regime at the Cuntan Station Figure2 shows the IHA results at the Cuntan station, which are further analyzed by scanning t-test to reveal multi-scale changes. Figure3 shows multiple changes on different time scales in the hydrologic regime at the Cuntan station. Red lines indicate increasing trends after change points, and blue lines indicate decreasing trends after change points. Thick red and blue lines denote significant change points. The meanings of the line styles are the same for all subsequent figures. The x-axis denotes the year, and the y-axis denotes the time scales, in units of years. The time scales and the time at which the change point occurs can be identified by the regions circled with thick red or blue contours. The change patterns are different across different hydrologic indicators. Figure3(1)–(12) display change points for the magnitude of monthly flows. Different change properties for monthly flow can be identified during different time intervals. The tendency of the monthly flow in October is dominated by a decreasing trend. A significant decrease can be detected around 1970 on a short time scale of 10 years. Another significant decrease can be identified around the mid-1990s at all time scales, implying reduced streamflow in October after the change points. Meanwhile, change patterns for monthly flows in January, February, and March are similar. A decreasing tendency dominates before 1980, and an increasing tendency dominates after 1980. For January’s monthly flow, a significant reduction can be detected around 1970 at all time scales. Significant increases appear in both the mid-1980s and 2000, at time scales below 15 years. Regions at time scales above 15 years after the mid-1980s are characterized by a significant increasing trend. For the monthly flows of the remaining months, including April through September as well as November and December, significant change points are distributed sporadically within time scales versus time space. Water 2016, 8, 408 6 of 20 both the mid‐1980s and 2000, at time scales below 15 years. Regions at time scales above 15 years after the mid‐1980s are characterized by a significant increasing trend. For the monthly flows of the Waterremaining2016, 8, 408months, including April through September as well as November and December,6 of 20 significant change points are distributed sporadically within time scales versus time space.

Figure 2. IHA series of the Cuntan station. Figure 2. IHA series of the Cuntan station.

Figure 3(13)–(23) portray multiple abrupt behaviors in the magnitude and duration of annual extremeFigure water3(13)–(23) conditions portray at the multiple Cuntan station. abrupt behaviorsChange patterns in the magnitudeof the low‐flow and indicators duration ofare annual similar, extremeincluding water the 1 conditions‐day minimum, at the 3 Cuntan‐day minimum, station. Change7‐day minimum, patterns of30 the‐day low-flow minimum, indicators 90‐day minimum, are similar, includingand base flow the 1-day index. minimum, The low‐ 3-dayflow indicators minimum, increase 7-day minimum, significantly 30-day after minimum, 1980 at time 90-day scales minimum, greater andthan base 20 years. flow index.Change The characteristics low-flow indicators at time scales increase of less significantly than 15 years after are 1980 relatively at time scales complicated, greater thanand two 20 years. significant Change increases characteristics can be at detected time scales around of less 1985 than and 15 years2000. are For relatively the high complicated,‐flow indicators, and twoincluding significant the 1 increases‐day maximum, can be detected 3‐day maximum, around 1985 7‐ andday 2000. maximum, For the 30 high-flow‐day maximum, indicators, and including 90‐day themaximum, 1-day maximum, no significant 3-day change maximum, point emerges 7-day maximum, at time scales 30-day greater maximum, than 20 and years. 90-day Increasing maximum, and nodecreasing significant changes change are point intermittent emerges in at different time scales years greater at time than scales 20 years. of less Increasing than 15 years. and decreasing changesFigure are 3(24),(25) intermittent show in differentchanges yearsin the at timing time scalesof annual of less extreme than 15 water years. conditions at the Cuntan station.Figure Change3(24),(25) points show are distributed changes in sparsely the timing at oftime annual scales extreme of less than water 15 conditions years, and at no the significant Cuntan station.change is Change detectable points at longer are distributed time scales. sparsely Figure at 3(26)–(29) time scales show of less multi than‐scale 15 changes years, and in the no significantfrequency changeand duration is detectable of high at and longer low time pulses. scales. Low Figure pulse3(26)–(29) count and show low multi-scale pulse duration changes are in thealso frequency low‐flow and duration of high and low pulses. Low pulse count and low pulse duration are also low-flow indicators. After the mid-1980s, the low pulse count experiences an increasing trend, while low pulse duration is characterized by a decreasing trend. A low pulse with a long duration can be disrupted Water 2016, 8, 408 7 of 20 Water 2016, 8, 408 7 of 20 indicators. After the mid‐1980s, the low pulse count experiences an increasing trend, while low pulse duration is characterized by a decreasing trend. A low pulse with a long duration can be disrupted toto form form several several low low pulses with with short short durations, durations, and and this this may may result result in in a a reduction reduction in in the the total total days ofof low pulses, as shown in Figure 44.. TheThe totaltotal daysdays ofof lowlow pulsespulses decreasesdecreases afterafter thethe latelate 1980s1980s andand furtherfurther decrease afterafter the the late late 1990s 1990s at at short short time time scales scales of lessof less than than 15 years.15 years. Regions Regions with with longer longer time timescales scales are dominated are dominated by decreasing by decreasing change change points points after after the late the 1980s. late 1980s. High High pulse pulse count count and highand highpulse pulse duration duration are high-flow are high indicators,‐flow indicators, which do which not dramatically do not dramatically change. Only change. a few Only intermittent a few intermittentsignificant change significant points change can be points identified can be at identified short time at scales. short time scales.

FigureFigure 3. 3. ChangeChange points points on on different different time time scales scales of of the the hydrologic hydrologic regime at the Cuntan station.

The last three sub‐figures in Figure 3 show different trends in the rate and frequency of water The last three sub-ﬁgures in Figure3 show different trends in the rate and frequency of water condition changes. The rise rate is characterized by decreasing changes, and the number of reversals condition changes. The rise rate is characterized by decreasing changes, and the number of reversals is is characterized by increasing changes. The fall rate features intermittent downward and upward characterized by increasing changes. The fall rate features intermittent downward and upward trends. trends. Factors affecting the rate and frequency of changes in water conditions are complex, including Factors affecting the rate and frequency of changes in water conditions are complex, including the the intensity and duration of precipitation, land surface, the regulation of river channels, and the intensity and duration of precipitation, land surface, the regulation of river channels, and the inﬂuence influence of reservoirs. of reservoirs.

Water 2016, 8, 408 8 of 20 Water 2016, 8, 408 8 of 20

Figure Figure4. Changes 4. inChanges total days in of total low days pulses of at low the pulsesCuntan at station: the Cuntan (a) annual station: values; (a ()b) annual abrupt values; behaviors. (b) abrupt behaviors. 4.2. Changes in Hydrologic Regime at the Yichang Station 4.2. Changes in Hydrologic Regime at the Yichang Station The Gezhouba Reservoir is a run‐of‐river reservoir, and its influences on downstream sediment and flowThe regimes Gezhouba are limited; Reservoir in contrast, is a run-of-river the effects reservoir, of the andThree its Gorges influences Reservoir on downstream are prominent sediment due to itsand large flow storage regimes capacity are limited; [14,24]. in contrast, Any differences the effects ofbetween the Three the Gorges changes Reservoir in hydrologic are prominent regimes due at the toYichang its large and storage Cuntan capacity stations [14 should,24]. Any be differencesmainly attributable between to the the changes streamflow in hydrologic from the regimes tributaries at locatedthe Yichang between and the Cuntan two stations, stations the should storage be mainly capacity attributable of the river to thechannel streamflow between from the the two tributaries stations, andlocated the influence between of the the two Three stations, Gorges the Reservoir. storage capacity of the river channel between the two stations, andIHA the results influence for of the the Yichang Three Gorges station Reservoir. are shown in Figure 5, and the change points of the hydrologicIHA regime results foron thedifferent Yichang time station scales are shownare shown in Figure in Figure5, and the 6. changeSome obvious points of changes the hydrologic can be regime on different time scales are shown in Figure6. Some obvious changes can be observed in observed in the monthly flow series. The monthly flow in September exhibits a significant reduction the monthly flow series. The monthly flow in September exhibits a significant reduction after 1990. after 1990. Similarly, the monthly flow in October shows signs of a significant reduction after the late Similarly, the monthly flow in October shows signs of a significant reduction after the late 1990s. 1990s. No significant change point is identifiable after 2000 in the monthly flow for October at the No significant change point is identifiable after 2000 in the monthly flow for October at the Cuntan Cuntan station. Therefore, any streamflow reduction after 2000 at the Yichang station can be station. Therefore, any streamflow reduction after 2000 at the Yichang station can be attributed to the attributed to the impoundment of the Three Gorges Reservoir. Comparatively, patterns in the impoundment of the Three Gorges Reservoir. Comparatively, patterns in the distribution of change distributionpoints for of the change monthly points flows for from the January monthly through flows March from atJanuary the Yichang through station March are in at approximate the Yichang stationagreement are in approximate with those at theagreement Cuntan station.with those at the Cuntan station. TheThe low low-flow‐flow indicators indicators for for the the magnitude magnitude and and duration duration of of annual annual extreme waterwater conditions conditions are are characterizedcharacterized by byan anincreasing increasing trend, trend, especially especially after after 2000. 2000. No No significant significant change isis detecteddetected in in the the datedate of maximum, of maximum, while while an an obvious obvious change change can can be be found found in in the the date ofof minimum.minimum. BothBoth decreases decreases andand increases increases in the in thedate date of minimum of minimum imply imply that that the 1 the‐day 1-day annual annual minimum minimum flow flow occurs occurs earlier. earlier. The dataThe show data that show the that 1‐day the annual 1-day annual minimum minimum flow usually flow usually occurs occurs between between January January and March and March in years in beforeyears 2006, before while 2006, it occurs while itin occurs December in December in the last in theyear last after year 2006, after implying 2006, implying an earlier an earlierdate than date in previousthan in years previous (Figure years 5(24)). (Figure Low5(24)). pulse Low count pulse and count low andpulse low duration pulse duration are characterized are characterized by upward by andupward downward and downward trends, respectively, trends, respectively, after 1980. after Figure 1980. 7 Figure shows7 shows the changes the changes in the in total the total days days of low of pulseslow at pulses the Yichang at the Yichang station. station. The total The total low low-pulse‐pulse days days decrease decrease after after the the late late 1980s andand further further decreasedecrease after after 2000. 2000. The The rise rise rate rate is characterized is characterized by by a adownward downward change, change, and the number of of reversals reversals is characterizedis characterized by by an an upward upward change.change. The The fall fall rate rate remains remains relatively relatively stable, stable, and sparse and sparse change pointschange pointscan can be detected. be detected.

Water 2016, 8, 408 9 of 20 Water 2016, 8, 408 9 of 20

FigureFigure 5. 5. IHAIHA series series of the Yichang station.station.

Water 2016, 8, 408 10 of 20 Water 2016, 8, 408 10 of 20

Water 2016, 8, 408 10 of 20

FigureFigure 6. 6. ChangeChange points points on on different different time time scales scales of of the the hydrologic hydrologic regime at the Yichang station. Figure 6. Change points on different time scales of the hydrologic regime at the Yichang station.

Figure 7. Changes in total days of low pulses at the Yichang station: (a) annual values; (b) abrupt Figure 7. 7. ChangesChanges in total in total days days of low of pulses low pulsesat the Yichang at the Yichangstation: ( station:a) annual (avalues;) annual (b) abrupt values; behaviors. behaviors.(b) abrupt behaviors. The distribution of significant change points for October’s monthly flow is similar to that of the lowThe‐flow distribution distribution indicators, of of like significant significant the monthly change change flow pointsin points February, for for October’s October’sannual extreme monthly monthly low flow water flow is similarconditions, is similar to thatbase to that of the of lowthe‐ low-flowflowflow index, indicators, indicators, low pulse like duration, the like monthly the and monthly total flow days flowin ofFebruary, low in February, pulses. annual Figure annual extreme8 displays extreme low the coherencywater low water conditions, between conditions, base flowbaseOctober’s index, flow index, low monthly pulse low flowduration, pulse and duration, the and low total‐flow and days totalindicators. of days low Redpulses. of low lines Figure pulses. show positive8 Figuredisplays 8correlations, displays the coherency the and coherency blue between October’slines indicate monthly negative flow and correlations. the low ‐Thickflow indicators.lines denote Red significance. lines show The positivecoherency correlations, analysis reveals and blue lines indicate negative correlations. Thick lines denote significance. The coherency analysis reveals

Water 2016, 8, 408 11 of 20 between October’s monthly flow and the low-flow indicators. Red lines show positive correlations, andWater blue 2016 lines, 8, 408 indicate negative correlations. Thick lines denote significance. The coherency analysis11 of 20 reveals significant negative correlations between the monthly flow in October and the monthly flow in significant negative correlations between the monthly flow in October and the monthly flow in February, 1-day minimum flow, 3-day minimum flow, 7-day minimum flow, 30-day minimum flow, February, 1‐day minimum flow, 3‐day minimum flow, 7‐day minimum flow, 30‐day minimum flow, and base flow index after 2000 at time scales of less than 15 years. The coherency analysis also reveals and base flow index after 2000 at time scales of less than 15 years. The coherency analysis also reveals significant positive correlations between the monthly flow in October and both low pulse duration significant positive correlations between the monthly flow in October and both low pulse duration and total days of low pulses at time scales of less than 15 years. The hydrologic regime at the Yichang and total days of low pulses at time scales of less than 15 years. The hydrologic regime at the Yichang station is affected directly by the Three Gorges Reservoir, which stores water in October and supplies station is affected directly by the Three Gorges Reservoir, which stores water in October and supplies waterwater in in the the dry dry season. season. The The coherency coherency analysis analysis reveals reveals the the influence influence of of the the Three Three Gorges Gorges Reservoir Reservoir on theon downstream the downstream hydrologic hydrologic regime. regime.

Figure 8. Coherency between monthly flow in October and low‐flow relevant indicators at the Figure 8. Coherency between monthly ﬂow in October and low-ﬂow relevant indicators at the Yichang station. Yichang station.

4.3. Changes in Hydrologic Regime at the Hankou Station 4.3. Changes in Hydrologic Regime at the Hankou Station Differences in patterns of hydrologic changes at the Hankou station, in contrast to those at the YichangDifferences station, in are patterns mainly of caused hydrologic by the changesstreamflow at thefrom Hankou the Hanjiang station, River, in contrast runoff regulation to those at at the Yichangthe Dongting station, Lake, are mainlyand the causedriver channels by the between streamflow the Yichang from the and Hanjiang Hankou River, stations. runoff IHA regulation results for at thethe Dongting Hankou station Lake, and are shown the river in Figure channels 9, and between multiple the changes Yichang in the and hydrologic Hankou stations. regime on IHA different results fortime the scales Hankou are stationshown in are Figure shown 10. in A Figuresignificant9, and reduction multiple in changesApril’s monthly in the hydrologic flow can be regime detected on differentin the late time 1990s scales at all are time shown scales. in For Figure the monthly 10. A significant flow in May, reduction significant in decreases April’s monthly can be detected flow can bearound detected 1980 in at the all late time 1990s scales, at alland time significant scales. increases For the monthly can be detected flow in in May, the significantlate 1980s at decreases a time canscale be of detected 10 years. around No significant 1980 at change all time point scales, is identifiable and significant in the increasesmonthly flows can be for detected June and in August. the late 1980sFor July’s at a time monthly scale offlow, 10 years.a significant No significant increase is change identified point around is identifiable 1980 at time in the scales monthly exceeding flows 15 for Juneyears, and and August. a significant For July’s decrease monthly is identified flow, a significantafter 2000 at increase shorter istime identified scales. The around tendency 1980 of at the time scalesmonthly exceeding flow in 15October years, is and dominated a significant by a downward decrease trend, is identified while the after tendency 2000 at of shorter the monthly time flow scales. Thebetween tendency January of the and monthly March flow is characterized in October isby dominated an upward by trend. a downward Some sporadic trend, significant while the tendencychange ofpoints the monthly can also flow be detected between in January the monthly and March flow isof characterized the other months, by an implying upward trend.flow fluctuations Some sporadic at significantdifferent changetime scales. points can also be detected in the monthly flow of the other months, implying flow fluctuationsFor the at magnitude different time and duration scales. of annual extreme water conditions, the low‐flow indicators are characterizedFor the magnitude by increasing and duration trends. For of the annual high extreme‐flow indicators, water conditions, significant the increasing low-flow change indicators points are characterizedare detected byin the increasing 1980s at different trends. For time the scales, high-flow and significant indicators, decreasing significant change increasing points changeare detected points arein detected 2000 at a in time the scale 1980s of at about different 12 years. time For scales, the date and of significant minimum, decreasing a significant change decrease points at time are detected scales of less than 12 years is detected around 1970, while a significant increase at time scales exceeding 15 in 2000 at a time scale of about 12 years. For the date of minimum, a significant decrease at time scales years is found around 1990. As stated in Section 4.2, both the decrease and increase of the date of of less than 12 years is detected around 1970, while a significant increase at time scales exceeding minimum imply that the 1‐day annual minimum flow occurs earlier. The 1‐day annual minimum 15 years is found around 1990. As stated in Section 4.2, both the decrease and increase of the date of flow usually occurs between January and March before 1990 and sometimes occurs in December of minimum imply that the 1-day annual minimum flow occurs earlier. The 1-day annual minimum the last year after 1990, indicating an earlier date than in previous years (Figure 9(24)). For the date flow usually occurs between January and March before 1990 and sometimes occurs in December of of maximum, positive changes imply that the 1‐day annual maximum flow occurs earlier, while the last year after 1990, indicating an earlier date than in previous years (Figure9(24)). For the date of negative changes imply that the 1‐day annual maximum flow occurs later. The late 1960s and 1970s maximum,feature a significant positive changes decrease imply and thatincrease, the 1-day respectively, annual maximumat time scales flow of occursless than earlier, 12 years. while negative changes imply that the 1-day annual maximum flow occurs later. The late 1960s and 1970s feature a significant decrease and increase, respectively, at time scales of less than 12 years.

Water 2016, 8, 408 12 of 20 Water 2016, 8, 408 12 of 20

FigureFigure 9. IHAIHA series of the Hankou station.station.

Some significant positive changes appear in low pulse count, and some significant negative Some significant positive changes appear in low pulse count, and some significant negative changes are found in low pulse duration. Figure 11 charts the changes in total days of low pulses at changes are found in low pulse duration. Figure 11 charts the changes in total days of low pulses at the Hankou station. A significant reduction in the total days of low pulses can be detected in 1980 at the Hankou station. A significant reduction in the total days of low pulses can be detected in 1980 at all time scales. High pulse count is characterized by a decreasing trend in the late 1980s at time scales all time scales. High pulse count is characterized by a decreasing trend in the late 1980s at time scales larger than 20 years, and no significant change affects high pulse duration. The tendency of the rise larger than 20 years, and no significant change affects high pulse duration. The tendency of the rise rate is dominated by a decreasing trend. For the fall rate, a significant positive change point at time rate is dominated by a decreasing trend. For the fall rate, a significant positive change point at time scales of 10 years is only detected in 1970, with no change point occurring after that time. Two scales of 10 years is only detected in 1970, with no change point occurring after that time. Two primary primarychanges changes are detected are detected in the number in the of number reversals, of reversals, a significant a significant increase after increase 1970 andafter a significant1970 and a significantdecrease after decrease 1990. after 1990.

Water 2016, 8, 408 13 of 20 Water 2016, 8, 408 13 of 20

Water 2016, 8, 408 13 of 20

FigureFigure 10.10. ChangeChange points on different time scales of the hydrologic hydrologic regime regime at at the the Hankou Hankou station. station. Figure 10. Change points on different time scales of the hydrologic regime at the Hankou station.

Figure 11. Changes in total days of low pulses at the Hankou station: (a) annual values; (b) abrupt Figure 11. Changes in total days of low pulses at the Hankou station: (a) annual values; Figure behaviors.11. Changes in total days of low pulses at the Hankou station: (a) annual values; (b) abrupt (b) abrupt behaviors. behaviors. 4.4. Changes in Hydrologic Regime at the Datong Station 4.4.4.4. Changes ChangesThe in in HydrologicHydrologicIHA results RegimeforRegime the Datong atat thethe Datongstation are Station displayed in Figure 12, and the multi‐scale change features are shown in Figure 13. Significant decreases are detected around 2000 and 1980 in the The IHA results for the Datong station are displayed in Figure 12, and the multi-scale change Themonthly IHA resultsflows of forApril the and Datong May, respectively. station are No displayed significant changein Figure can be12, found and inthe June’s multi monthly‐scale change featuresfeaturesflow. areare The shownshown monthly inin Figure flowFigure in July1313.. firstSignificant Significant increases decreasesafter decreases 1990 and are are then detected detected decreases around around after 2000. 2000 2000 Intermittent and and 1980 1980 in in the the monthlymonthly flows flows of of AprilApril andand May, respectively.respectively. No significantsignificant change can can be be found found in in June’s June’s monthly monthly flow.flow. The The monthly monthly flowflow inin JulyJuly firstfirst increasesincreases after 1990 and then decreases after after 2000. 2000. Intermittent Intermittent

Water 2016, 8, 408 14 of 20 Water 2016, 8, 408 14 of 20 significantsignificant increases increases and and decreases decreases can can be be identified identified at different timetime scalesscales inin thethe monthlymonthly flows flows of of AugustAugust through through September September and and November November through December. TheThe tendencytendency ofof thethe monthlymonthly flow flow in in OctoberOctober is is dominated by by a downwarda downward trend, trend, while while the tendency the tendency of the of monthly the monthly flows between flows between January Januaryand March and is March dominated is dominated by an upward by an upward trend. trend.

FigureFigure 12. 12. IHAIHA series series of the Datong station.

For the magnitude and duration of annual extreme water conditions, all of the low‐flow For the magnitude and duration of annual extreme water conditions, all of the low-flow indicators indicators are characterized by significant positive changes. For all of the high‐flow indicators, are characterized by significant positive changes. For all of the high-flow indicators, significant significant increases are detected around 1990 and significant decreases are detected around 2000. At increases are detected around 1990 and significant decreases are detected around 2000. At time scales time scales of less than 13 years, a significant increase in the date of minimum is detected in the late of less than 13 years, a significant increase in the date of minimum is detected in the late 1980s, 1980s, and a significant decrease is detected in the late 1990s; this finding implies that the 1‐day and a significant decrease is detected in the late 1990s; this finding implies that the 1-day annual annual minimum flow occurs earlier. A significant increase in the date of maximum can be identified minimum flow occurs earlier. A significant increase in the date of maximum can be identified in the in the late 1970s, indicating that the 1‐day annual maximum flow occurs later. No significant change late 1970s, indicating that the 1-day annual maximum flow occurs later. No significant change is is detected in low pulse count, but a significant decrease can be found in low pulse duration. The detected in low pulse count, but a significant decrease can be found in low pulse duration. The change change in low pulse duration is approximately in line with that of the total days of low pulses, with in low pulse duration is approximately in line with that of the total days of low pulses, with a significant areduction significant appearing reduction after appearing 1980 (Figure after 14 1980). Sparse (Figure significant 14). Sparse change significant points can change be detected points in can high be detected in high pulse count and high pulse duration. The rise rate remains relatively stable, but the fall rate obviously fluctuates with significant positive and negative changes. The number of reversals is characterized by a significant reduction after the mid‐1980s.

Water 2016, 8, 408 15 of 20 pulse count and high pulse duration. The rise rate remains relatively stable, but the fall rate obviously ﬂuctuates with signiﬁcant positive and negative changes. The number of reversals is characterized by

Watera signiﬁcant 2016, 8, 408 reduction after the mid-1980s. 15 of 20

Water 2016, 8, 408 15 of 20

FigureFigure 13. 13. ChangeChange points points on on different different time time scales of the hydrologic regime at the Datong station. Figure 13. Change points on different time scales of the hydrologic regime at the Datong station.

Figure 14. Changes in total days of low pulses at the Datong station: (a) annual values; (b) abrupt Figure 14. 14. ChangesChanges in total in total days days of low of pulses low pulses at the Datong at the Datongstation: ( station:a) annual ( avalues;) annual (b) abrupt values; behaviors. behaviors.(b) abrupt behaviors. 4.5. Common Changes in Hydrologic Regimes of the Four Stations 4.5. Common Changes in Hydrologic Regimes of the Four Stations Some anthropogenic activities like reservoir construction may result in common changes in the hydrologicSome anthropogenic regimes of the activities upper, middle, like reservoir and lower construction Yangtze River. may Coherency result in analysis common of thechanges results in the hydrologicdisplayed regimes in Figure of the2 through upper, Figure middle, 14 andreveals lower common Yangtze changes River. in Coherencythe hydrologic analysis regimes of ofthe the results displayedCuntan, in Yichang, Figure 2Hankou, through and Figure Datong 14 revealsstations common(Figure 15). changes Significant in the positive hydrologic relationships regimes at of the Cuntan, Yichang, Hankou, and Datong stations (Figure 15). Significant positive relationships at

Water 2016, 8, 408 16 of 20

4.5. Common Changes in Hydrologic Regimes of the Four Stations Some anthropogenic activities like reservoir construction may result in common changes in the hydrologic regimes of the upper, middle, and lower Yangtze River. Coherency analysis of the results displayed in Figure2 through Figure 14 reveals common changes in the hydrologic regimes Water 2016, 8, 408 16 of 20 of the Cuntan, Yichang, Hankou, and Datong stations (Figure 15). Significant positive relationships variousat various time time scales scales among among the the four four stations stations are areprimarily primarily evident evident in the in monthly the monthly flow flow in October in October and inand the in thelow low-flow‐flow indicators, indicators, including including the the monthly monthly flows flows between between January January and and March, March, annual minimum 1/3/7/30/90-day1/3/7/30/90‐day flows, flows, base base flow flow index, index, low low pulse pulse duration, duration, and and total total days days of of low low pulses. pulses. The monthlymonthly flow flow in in October October and and the low-flowthe low‐flow indicators indicators follow follow opposite opposite change change patterns; patterns; the monthly the monthlyflow in October flow in is October characterized is characterized by a decreasing by a trend, decreasing but the trend, low-flow but indicators the low‐ areflow characterized indicators are by characterizedan increasing trend.by an These increasing change trend. patterns These are change the expected patterns results are of the reservoir expected regulation. results of Most reservoir of the regulation.reservoirs in Most the Yangtzeof the reservoirs River basin in the store Yangtze water atRiver the endbasin of store the flood water season at the withend of low the flood flood risk season and withrelease low water flood in risk the and dry season.release water Climate in changethe dry isseason. another Climate important change factor is another affecting important the hydrologic factor affectingregime. The the flowshydrologic in October regime. from The the flows Dongting in October Lake from and the the Poyang Dongting Lake Lake also and decrease, the Poyang mainly Lake as alsoa result decrease, of reduced mainly precipitation as a result of caused reduced by precipitation climate change caused [15]. by climate change [15].

Figure 15. CoherencyCoherency between hydrologic regimes of the four stations.

Negative coherency can only be detected in the number of reversals, implying different change Negative coherency can only be detected in the number of reversals, implying different change properties among the four stations in terms of this indicator. Significant increases can be identified properties among the four stations in terms of this indicator. Significant increases can be identified after the late 1980s in the Cuntan and Yichang stations, while significant decreases can be found after after the late 1980s in the Cuntan and Yichang stations, while significant decreases can be found after the late 1980s in the Hankou and Datong stations. The factors affecting the number of reversals are the late 1980s in the Hankou and Datong stations. The factors affecting the number of reversals are relatively complex, including the characteristics of precipitation, the regulations of river channels, the relatively complex, including the characteristics of precipitation, the regulations of river channels, influence of reservoirs, and the buffering effect of lake systems. the influence of reservoirs, and the buffering effect of lake systems. 5. Discussion This study demonstrates that the strategy of coupling IHA data and scanning t‐test is effective in analyzing various changes to the hydrologic regime of the Yangtze River at different time scales. The improved coherency analysis method is effective in detecting common changes across different hydrologic series, like the coherency among the hydrologic regimes of the upper, middle, and lower reaches of the Yangtze River. This method resolves the limitation of the original algorithm, which can only detect common changes between two hydrologic series. Combining the IHA method, scanning

Water 2016, 8, 408 17 of 20

5. Discussion This study demonstrates that the strategy of coupling IHA data and scanning t-test is effective in analyzing various changes to the hydrologic regime of the Yangtze River at different time scales. The improved coherency analysis method is effective in detecting common changes across different hydrologic series, like the coherency among the hydrologic regimes of the upper, middle, and lower reaches of the Yangtze River. This method resolves the limitation of the original algorithm, which can only detect common changes between two hydrologic series. Combining the IHA method, scanning t-test and improved coherency analysis can also help to analyze multiple changes in the hydrologic regimes of other large rivers. The different patterns of hydrologic changes at the Cuntan, Yichang, Hankou, and Datong stations may be a result of the uneven spatial distribution of precipitation changes, as well as the hydraulic regulation of river channels and lakes like the Dongting Lake and the Poyang Lake. Analysis of precipitation trends for the upper, middle, and lower Yangtze River basin and of runoff trends for the Yichang, Hankou, and Datong stations indicates that the runoff trends are strongly correlated with the precipitation trends [25]. Both climate change and anthropogenic activities, such as reservoir construction, water withdrawal, and inter-basin water transfer, may also affect the hydrologic regime of the Yangtze River [26,27]. The individual roles that climate change and anthropogenic activities play in hydrologic alteration need to be further analyzed in future research. The common changes identified in the hydrologic regimes of the upper, middle, and lower Yangtze River are decreased monthly flow in October and increased low-flow indicators, both of which are strongly affected by reservoir regulation. Reservoirs function by impounding water to create a supply for the dry season, and this process unavoidably reduces flow during impoundment. Maintaining a water supply during the dry season is beneficial for socio-economic development and ecological environmental protection. The impacts of reservoir regulation on the hydrologic regime will become more significant as more reservoirs are constructed in the Yangtze River basin. The indicators that characterize the hydrologic regime during the seasons of reservoir impoundment and water supply may also experience more significant alterations. Furthermore, the high-flow indicators, including the monthly flows during flood seasons, annual maximum 1/3/7/30/90-day flows, and high pulse count and duration may experience significant changes because of the increased flood-control capacity of reservoirs. Reservoir-induced alterations in the hydrologic regime of the Yangtze River unavoidably influence water allocation among different water users. In stream ecological water requirements may not be guaranteed during some months, particularly during the time in which reservoirs store water [28]. One example of the ecological challenges posed by reservoir construction is the dilemma of Acipensersinensis, or the Chinese sturgeon, an anatropous species of fish that spawns in the Yangtze River and the Pearl River in China. Historically, the species’ spawning habitats were distributed in the lower reaches of the Jinsha River and the upper reaches of the Yangtze River [29]. However, the migration route of the adult fish is now blocked by the Gezhouba Dam; as a result, Chinese sturgeon are forced to propagate in a new spawning ground less than 7 km long, located in the main stem of the Yangtze River, downstream from the Gezhouba Dam. The species’ population has declined dramatically since the construction of the Gezhouba Dam in 1981, and it experienced a further decline with the 2003 impoundment of the Three Gorges Reservoir, which stores water and changes the downstream hydrologic regime during the spawning period [30]. These changes in hydrologic conditions negatively influence the Chinese sturgeon’s spawning and hatching conditions [31]. Adjusting the impoundment schedule of the Three Gorges Reservoir to restore the hydrologic regime over the spawning habitat in October is a crucial step that can be taken to improve habitat suitability for the Chinese sturgeon, particularly in dry years [29,32]. Water 2016, 8, 408 18 of 20

6. Conclusions This paper’s analysis of daily streamflow data from four flow gauging stations along the main stem of the Yangtze River reveals multiple changes over time to the hydrologic regime. These findings indicate the effectiveness of coupling the IHA method and scanning t-test. The following conclusions can be drawn from this analysis: (1) Various change patterns can be identified in the five components of the hydrologic regime, which are the magnitude of monthly water conditions, magnitude and duration of annual extreme water conditions, timing of annual extreme water conditions, frequency and duration of high and low pulses, and rate and frequency of water condition changes. The 32 hydrologic indicators are characterized by different changes in different time scales. Spatial variations can be observed in the hydrologic changes across the Cuntan, Yichang, Hankou, and Datong stations. 1a. At the Cuntan station, the monthly flow in October decreased around 1970 at a time scale of 10 years and in the mid-1990s at all time scales. The monthly flows in January, February, and March increased after 1980. The low-flow indicators increased after 1980 at time scales exceeding 20 years. For the high-flow indicators, increasing and decreasing changes occurred intermittently during different years at time scales of less than 15 years. After the mid-1980s, low pulse count increased and low pulse duration decreased. The total days of low pulses decreased after the late 1980s, and they were further reduced after the late 1990s at time scales of less than 15 years. The rise rate was characterized by decreasing changes, and the number of reversals was characterized by increasing changes. The fall rate featured intermittent downward and upward trends. 1b. At the Yichang station, September’s monthly flow experienced a significant reduction after 1990, and October’s monthly flow experienced a significant reduction after the late 1990s. The magnitude and duration of annual extreme water conditions increased, especially after 2000. After 1980, low pulse count and low pulse duration were characterized by upward and downward trends, respectively. The total days of low pulses decreased after the late 1980s and decreased further after 2000. The rise rate was characterized by a downward change, and the number of reversals was dominated by an upward change. The fall rate remained relatively stable, and few change points were detected. 1c. At the Hankou station, the monthly flow in April decreased in the late 1990s at all time scales, while the monthly flow in May decreased around 1980 at all time scales and increased in the late 1980s at a time scale of 10 years. The monthly flow in July increased around 1980 at time scales exceeding 15 years and decreased after 2000 at shorter time scales. The monthly flow tendency in October was dominated by a downward trend, while the monthly flow tendencies between January and March were characterized by upward trends. The low-flow indicators showed increasing trends. The high-flow indicators increased during the 1980s at different time scales and decreased in 2000 at a time scale of about 12 years. The total days of low pulses decreased in 1980 at all time scales, and high pulse count decreased in the late 1980s at time scales exceeding 20 years. The tendency of the rise rate was dominated by a decreasing trend. 1d. At the Datong station, significant decreases were detected around 2000 and 1980 in the monthly flows of April and May, respectively. The monthly flow in July increased after 1990 and decreased after 2000. The tendency of the monthly flow in October was dominated by a downward trend, while the tendencies of the monthly flows between January and March were dominated by upward trends. The low-flow indicators were characterized by significant positive changes, and the high-flow indicators increased around 1990 and decreased around 2000. The change in low pulse duration approximately aligned with that of total days of low pulses, with a significant reduction occurring after 1980. The number of reversals decreased after the mid-1980s. (2) The improved coherency analysis method is effective in detecting common changes across different hydrologic series. Some common changes in the hydrologic regimes of the upper, middle, and lower reaches of a river can be revealed through coherency analysis. This study identified similar change patterns at different points in the Yangtze River in hydrologic indicators including the monthly flow in October and the low-flow indicators, which comprise the monthly flows between January and Water 2016, 8, 408 19 of 20

March, annual minimum 1/3/7/30/90-day flows, base flow index, low pulse duration, and total days of low pulses. The monthly flow in October decreased, but the low-flow indicators increased. (3) The influence of reservoirs represents an important factor behind hydrologic changes. The monthly flow in October and the low-flow indicators followed opposite change patterns due to reservoir regulation. The reservoirs store water in October, reducing downstream runoff. The impounded water is then supplied in the dry season, leading to the increased base flow and the decreased low pulse duration.

Acknowledgments: This work is supported by the National Natural Science Foundation Projects of China (grant numbers 41401011, 41401010, 51309107, 41371098 and 51409091); Science and Technology Projects of Water Resources Department of Jiangxi Province (grant number KT201538); Major Program of National Social Science Foundation of China (grant number 11&ZD168); and Program for Changjiang Scholars and Innovative Research Team in University (grant number IRT13062). The authors acknowledge constructive comments from the editor and anonymous reviewers, which lead to improvement of the paper. Author Contributions: The authors designed and performed the research together. Feng Huang wrote the draft of the paper. Nan Zhang, Xirong Ma, Dayong Zhao, Lidan Guo, Li Ren, Yao Wu and Ziqiang Xia made some comments and corrections. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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