Assessing the impact of Danjiangkou reservoir on ecohydrological conditions in Hanjiang river, China

Ecological Engineering 81 (2015) 41–52

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Assessing the impact of Danjiangkou reservoir on ecohydrological conditions in Hanjiang river, China Yuankun Wang * , Dong Wang, Jichun Wu Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, Department of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, PR China

A R T I C L E I N F O

A B S T R A C T

Article history: Received 30 September 2014 Received in revised form 10 February 2015 Accepted 5 April 2015 Available online xxx

Natural flow variability is the primary driver of riverine ecosystem function and structure. Alterations in hydrologic regimes modify habitat attributes and impair ecosystem connectivity. The indicators of hydrologic alteration and range of variability approach methods are used to investigate the hydrologic alterations due to Danjiangkou reservoir in the middle stream of Hanjiang river, China, over the past five decades. The results show that Danjiangkou reservoir has significantly changed the ecohydrological flow regime downstream of the dam, especially in the spawning time of the famous four major carps. To minimize the negative ecological impacts, it is necessary to optimize the current operation rules of Danjiangkou reservoir for river ecosystem health protection. We hope the results of the current study could support ecosystem management and restoration plans and provide key ecohydrological parameters for the Danjiangkou reservoir ecological operations in the Hanjiang river. ã 2015 Elsevier B.V. All rights reserved.

Keywords: Danjiangkou reservoir Hydrological alterations Ecohydrological condition Hanjiang river

1. Introduction Natural flow regimes play a vital role in maintaining the health of river, wetland, estuarine and floodplain ecosystems. Maintaining natural hydrologic variability is essential in conserving native riverine biota and river ecosystem integrity. However, the construction of reservoirs, weirs and other hydraulic structures to sustain human activities has significantly altered the natural flows of rivers worldwide (Poff et al., 1997, 2007; Shiau and Wu, 2004; Nilsson et al., 2005; Wang et al., 2011, 2012). Modification of both river and riparian habitats can range from relatively localized effects of small-scale grazing to broader effects of impoundment. As a result, many originally defining physical and ecological features of these systems have been profoundly altered (Poff et al., 1997; Choi et al., 2005; Timme et al., 2005; Li and Zhang 2008; Yang et al., 2008; Chen et al., 2010). River flow regimes are considered to be primary drivers of riverine ecosystems. A number of ecologically important streamflow characteristics constitute the natural flow regime, including the seasonal patterning of flows; timing of extreme flows; frequency, predictability, and duration of floods, droughts, and

* Corresponding author at: Department of Hydro-sciences, School of Earth Sciences and Engineering, Nanjing 210023, PR China. Tel.: +86 25 89680850. E-mail address: [email protected] (Y. Wang). http://dx.doi.org/10.1016/j.ecoleng.2015.04.006 0925-8574/ ã 2015 Elsevier B.V. All rights reserved.

intermittent flows; daily, seasonal, and annual flow variability; and rates of change (Poff et al., 1997; Yang et al., 2012b). Assessment of these streamflow characteristics is essential for understanding and predicting the biological impact of both natural and altered flow regimes on riverine biota. Numerous researchers have developed and applied a number of hydrologic indices with the aim of quantifying the hydrologic alterations which were believed to be sensitive to various human perturbations. According to Olden and Poff (2003), more than 170 hydrologic metrics have been developed in attempting to describe different components of flow regime and capture the ecologically relevant streamflow attributes during the past decade. The early studies mainly focused on the minimum or suitable flows, mean daily flow, flood frequency, skewness of streamflow, peak discharge, seasonal disturbance of monthly flow and annual series analysis. In fact, these hydrologic variations only describe some characteristic. However, the full range of natural flows other than certain flows is essential for ecosystem health. To quantitatively evaluate the degree to which human activities impact the hydrologic regimes within an ecosystem, Richter et al. (1996) proposed an approach referred to as ‘indicators of hydrologic alteration’ (IHA). This technique is based on either hydrologic data available within an ecosystem or model-generated data. It considered a full range of natural flow variability, including magnitude, frequency, timing, duration and rate of change (Richter

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Y. Wang et al. / Ecological Engineering 81 (2015) 41–52

Fig. 1. Location of the Hanjiang River and Xiangyang hydrological station, China. Note: SNWDP is the South-to-North Water Diversion Project.

2. Study area and data The Hanjiang river is the largest branch of the Yangtze river; it passes through the provinces of Shanxi and Hubei of China, and merges into the Yangtze river at Wuhan city. The river’s length is 1570 km, and its basin area covers 170, 400 km2. The annual mean temperature is 15–16
C. Annual precipitation varies from 700 mm to 1100 mm, of which 70–80% of the total amount occurs in the wet season from May to September. The Danjiangkou reservoir is the key hydraulic project in the Hanjiang river basin, with total storage capacity to 17.4 billion m3 (Fig. 1). It started to impound water and became functional in 1967 and finished in 1974. The Danjiangkou reservoir has the comprehensive functions of flood control, power

generation, navigation and irrigation. The annual power generation is 3.4 GW (Yang et al., 2012a). The Hanjiang river is one of the most important freshwater fishery areas in the Yangtze river basin. The famous four major carps (FFMC), named the black carp (Mylopharyngodon piceus), the grass carp (Ctenopharyngodon idellus), the silver carp (Hypophthalmichthys molitrix) and the big-head carp (Aristichyths nobilis), which have the most importance to the freshwater fishery in China. After Danjiangkou reservoir construction, the route to the spawning sites for the migratory fishes obstructed (Yu 1982). Flow regime alterations caused by Danjiangkou reservoir threaten the biodiversity and ecosystem functions of rivers. According to Xie et al. (2009), the population of FFMC reduced sharply from 1970s. The daily flow discharge (m3/s) from 1950 to 2006 (data of 1983 missed) at Xiangyang station was collected from the Changjiang Water Resources Commission, China. Xiangyang station is located at the middle stream of the Hanjiang river,

30000 Pre-impact

Construction period

Post-impact

25000

20000 Discharge (m3/s)

et al., 1997). As a set of the proposed hydrologic indices, IHA has been commonly used worldwide (Shiau and Wu, 2004; Magilligan and Nislow, 2005; Hu et al., 2008; Zhang et al., 2009; Chen et al., 2010; Yang et al., 2012b). Olden and Poff (2003) reviewed of 170 available hydrologic indices (including IHA), and found that IHA can adequately characterize flow regimes with ecological knowledge. All of these studies indicated that IHA, addressing full range of flow regimes indicators, can be applied in assessing the variation of hydrologic alteration and will be helpful in understanding the interaction between flow regimes and riverine ecosystem (Yang et al., 2012b). The approach for assessing hydrologic alteration is based on the differences in streamflow regime characteristics between two defined time periods at a given streamgauge. If the years of record at a streamgauge can be divided into a period of more natural or less altered (e.g., pre-impact) streamflow conditions and a period of more altered (e.g., post-impact) conditions, then it is possible to measure the degree of alteration in the streamflow regime that has taken place between these two periods (Richter et al., 1996, 1997, 1998; Hu et al., 2008; Yang et al., 2012b). The goals of our study are: (1) to assess the hydrologic alteration caused by Danjiangkou reservoir operation by comparing the hydrologic regimes from pre-impact and post-impact periods, and (2) to analyze the impacts of hydrologic alterations on ecohydrological conditions of the Hanjiang river. All of these will be helpful to provide more suitable water regulations to maintain the ecosystem health in the Hanjiang river, China.

15000

10000

5000

0

Fig. 2. Daily discharge series at Xiangyang station in the Hanjiang river from 1950 to 2006.

Y. Wang et al. / Ecological Engineering 81 (2015) 41–52

111 km below the Danjiangkou reservoir. To assess the impact of Danjiangkou reservoir on eco-hydrological conditions in Hanjiang river, 1950–1966 is taken as pre-impact period and 1975-2006 is taken as post-impact period. The construction period (1967–1974) is not considered (Fig. 2). 3. Methodology 3.1. Indicators of hydrologic alteration Indicators of hydrologic alteration (IHA) method was developed to enable rapid processing of daily hydrologic records to characterize natural flow conditions and facilitate evaluations of human-induced changes to flow regimes (Richter et al., 1996). The program was designed to calculate the values of 33 hydrologic parameters that characterize the intra and inter-annual variability in water conditions, including the magnitude, frequency, duration, timing and rate of change of flows or water levels (Richter et al., 1996; Hu et al., 2008). The IHA indicators can be divided into five groups: monthly flow indices, extreme flow indices, timing indices, high-flow and low-flow indices, and rising and falling indices (Table 1). 3.2. Range of variability approach Richter et al. (1997) established the range of variability approach (RVA) method to assess the hydrologic regime alterations and as a management tool for regulated or developed rivers based on the IHA. The method uses 33 hydrologic parameters to evaluate the flow characteristics before and after a change point (Richter et al., 1998). The ecologically relevant hydrologic parameters can be categorized into five groups: magnitude, timing, frequency, duration and rate of change of the parameters. The RVA target range for each hydrologic parameter is usually based upon selected percentile levels or a simple multiple of the parameter standard deviations for the natural or pre-development streamflow regime. The management objective is not to have the river attain the targeted range every year; rather, it is to

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attain the targeted range at the same frequency as occurred in the natural or pre-development flow regime. For example, attainment of an RVA target range defined by the 25th and 75th percentile values of a particular parameter would be expected in only 50% of years. The degree to which the RVA target range is not attained is a measure of hydrologic alteration. This measure of hydrologic alteration, expressed as a percentage, can be calculated as:   ðObserved  ExpectedÞ  100 Expected wherein observed is the count of years in which the observed value of the hydrologic parameter fell within the targeted range; ‘expected’ is the count of years for which the value is expected to fall within the targeted range. Hydrologic alteration is equal to zero when the observed frequency of post-development annual values falling within the RVA target range equals the expected frequency. A positive deviation indicates that annual parameter values fell inside the RVA target window more often than expected; negative values indicate that annual values fell within the RVA target window less often than expected. In the RVA analysis, parameters can be calculated using parametric (mean/standard deviation) or non-parametric (percentile) statistics. Also, parameters can be produced as mean or median from daily data, depending on which methods are chosen. For most situations non-parametric statistics are a better choice, because of the skewed nature of many hydrologic datasets (a key assumption of parametric statistics is that the data are normally distributed). In China, the median is better than the mean to properly represent the hydrological series characteristics (Yang et al., 2008). Then we compute the expected frequency with which the “post-impact” values of the IHA parameters should fall within each category (in the non-parametric, this would be 33% for each of the three categories). To map hydrologic alteration, Richter et al. (1998) divided the ranges of hydrologic alteration (0–100%) into three classes of equal range and assigned each class a distinct pattern: (1) 0–33% (L) represents little or no alteration; (2) 34–67% (M) represents

Table 1 Summary of IHA parameters. Parameter group

Regime characteristics

Hydrologic parameters

1. Magnitude of monthly discharge conditions 2. Magnitude and duration of annual extreme discharge conditions

Magnitude, timing Magnitude, duration

3. Timing of annual extreme discharge conditions

Timing

4. Frequency and duration of high, low flow pulses

Magnitude, frequency duration

5. Rate/frequency of hydrograph changes

Frequency, rate of change

Median discharge for each calendar month Annual maxima one-day medians Annual minima one-day medians Annual minima 3-day medians Annual maxima 3-day medians Annual minima 7-day medians Annual maxima 7-day medians Annual minima 30-day medians Annual maxima 30-day medians Annual minima 90-day medians Annual maxima 90-day medians Number of zero-flow days 7-day minimum flow divided by median flow for year (‘base flow’) Julian date of each annual one-day maximum discharge Julian date of each annual one-day minimum discharge No. of high pulses each year No. of low pulses each year Median duration of high pulse within each year Median duration of low pulses within each year Medians of all positive differences between consecutive daily values Medians of all negative differences between consecutive daily values No. of flow reversals

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Table 2 Nonparametric RVA scores at the Xiangyang gauging station. 5 groups

Pre-impact period: 1950–1966

Post-impact period: 1975–2006

RVA targets

Hydrologic alteration

Medians

Coeff. of dispersion

Medians

Coeff. of dispersion

Low

High

(%)

Parameter Group #1 January February March April May June July August September October November December

354 463 629 979 1130 774 1878 1635 1425 1340 1040 567

0.8178 0.5842 0.6963 0.4898 0.4836 0.7707 0.7966 1.392 1.281 0.5619 0.6541 1.205

807 851.5 775 843.5 998 1100 1400 1520 1500 810 741.5 733

0.6406 0.6565 0.769 0.6194 0.4679 0.4005 0.4643 0.3618 0.6007 0.6926 0.7134 0.5443

330 313.2 446.3 719.7 1043 682.7 1698 1256 1134 1089 673.8 421.6

528.9 550.3 697.5 1107 1310 914.8 2717 2928 1808 1392 1195 761

66(M) 53(M) 45(M) 14(L) 38(M) 61(M) 37(M) 65(M) 6(L) 69(H) 18(L) 2(L)

Parameter Group #2 1-day minimum 3-day minimum 7-day minimum 30-day minimum 90-day minimum 1-day maximum 3-day maximum 7-day maximum 30-day maximum 90-day maximum Number of zero days Base flow index

288 294 301 340.9 497.2 13000 10430 8916 4255 2586 0 0.2705

0.8594 0.8413 0.8092 0.7378 0.6155 0.7163 0.6329 0.4878 0.5765 0.9219 0 0.7602

428 487.7 512.3 564.2 633.3 5380 3457 3106 2035 1687 0 0.4539

0.5935 0.5202 0.5719 0.5704 0.6322 1.305 1.618 1.603 1.182 0.9287 0 0.4578

227.2 233.7 238.6 282 369.5 11560 9353 7430 3881 2237 0 0.1674

453 453 454.2 469.9 596.5 15500 13200 9817 5706 3882 0 0.2973

17 (L) 3(L) 10(L) 14(L) 29(L) 77 (H) 77(H) 77(H) 69(H) 22(L) – 53(M)

Parameter Group #3 Date of minimum Date of maximum

65 231

0.265 0.1585

42 205

0.3279 0.265

56.22 208.5

171.3 253.1

22(L) 53(M)

Parameter Group #4 Low pulse count Low pulse duration High pulse count High pulse duration

3 7 9 6

1.833 1.643 0.5556 0.9167

3 2.25 5 3.25

2 2.278 1.4 2.654

2 6 6.94 3.97

4.06 12.36 11 7

45(M) 54(M) 51(M) 59(M)

Parameter Group #5 Rise rate Fall rate Number of reversals

61 40 77

1.23 0.775 0.1494

47.5 44.5 171

0.5263 0.6404 0.1579

52.17 55.24 75.76

102.2 30.47 83

37(M) 10(L) 100(H)

Hydrologic alteration degree, L = (0–33)%, M = (34–66)%, H = (67–100)%.

Fig. 3. The monthly median flow for October at Xiangyang station before and after Danjiangkou reservoir construction in the Hanjiang river.

Y. Wang et al. / Ecological Engineering 81 (2015) 41–52

Fig. 4. Hydrological alterations of 1-, 3-, 7-, and 30-day maximum flow before and after Danjiangkou reservoir construction in the Hanjiang river.

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moderate alteration; (3) 68–100% (H) represents a high degree of alteration. 4. Results and discussion 4.1. Hydrologic impacts of Danjiangkou reservoir The alteration degrees of the post-impact parameters against that of the pre-impact parameters were computed (Table 2). The results can be summarized as follows: Moderate and high degrees of hydrological alteration were observed for most months, whereas highest degree was observed in October. The January, February, March, May, June and August deviations exceeded 40%, the middle degree. The alteration degree of October median of monthly flow reached 69%, the highest degree of deviation. The monthly median flow for October is 39.6% lower than the pre-impact value (Fig. 3). According to regulation rules of Danjiangkou reservoir, the starting time of impoundment is 1 October. In general, Danjiangkou reservoir reaches the normal pool level at the end of October. It can be inferred that the sharp decrease of flow in October was mainly caused by impoundment of Danjiangkou reservoir. The dispersion coefficients of monthly flow in the post-impact period (ranging from 0.36 to 0.77) were generally lower than those in the preimpact period (ranging from 0.48 to 1.39), indicating the lower fluctuation of monthly flow of the post-impact period due to regulation by the reservoir. The medians of annual 1-, 3-, 7-, 30-, 90-day minimum for the post-impact period increased greatly. It can be seen from Table 2 that significantly differences were observed in the annual maxima flows between the two periods. The medians of annual 1-, 3-, 7-, 30- and 90-day maximum decreased greatly. Except for low alteration in the annual maxima 90-day, the others were rather high. The hydrological alteration of annual 1-, 3-, 7-day maxima medians reached 77%, which means most values of these four parameters fell out of the RVA target range (Fig. 4). The dispersion coefficients of the annual minima and maxima flows in the postimpact period (ranging from 0.52 to 1.62) are generally higher than those in the pre-impact period (ranging from 0.49 to 0.92). The results indicated that the daily, weekly, monthly and quarterly maximal/minimal flow cycles were negatively influenced by Danjiangkou reservoir regulation. The median Julian dates of annual 1-day minimum moved forward from the 65th day in the pre-impact period to the 42nd day in the post-impact period, with the low alteration of 22%. The median Julian dates of annual 1-day maximum moved forward from the 231st day in the pre-impact period to the 205th

day in the post-impact period, with the moderate alteration of 53% (Fig. 5). Low pulse count, low pulse duration, high pulse count and high pulse duration have been greatly changed, with alterations of 45%, 54%, 51% and 59%, respectively. The medians of low pulse duration, high pulse count and high pulse duration in the post-impact period were lower than those in the pre-impact period (Fig. 6). The coefficients of dispersion of all these parameters were higher those in the earlier period. Reservoir operation altered the original hydrologic processes, changed the original water level fluctuation process, smoothened the peak of swelling, and increased dry season discharge of river. Reservoir operation changed the natural flow regime and made it more smooth in the post-period. It indicated that frequency and duration of high and low flow pulses had been greatly influenced by Danjiangkou reservoir. The median of rise rate decreased severely from 61 in preimpact to 47.5 in post-impact, with hydrological alteration of 37%. By contrast, no significant difference was observed in the fall rate between the two periods. The median of number of reversals also has been altered significantly, increasing from 77 in pre-impact to 171 in post-impact, with high hydrological alteration of 100%, indicating no values of the parameter fell within the RVA target range. The highest hydrologic alteration factors of Danjiangkou reservoir are October (69), 1-, 3-, 7-day maximum (77), 30-day maximum (69), and number of reversals (100) when considering all 33 parameters. In summary, the hydrologic regime of Xiangyang station has been altered drastically after Danjiangkou reservoir construction. 4.2. Non-parametric analysis of hydrologic alteration The 33 hydrologic alteration values at Xiangyang hydrological station on the Hanjiang river (Fig. 7 and Table 2) were analyzed to investigate the order of indicators of hydrologic alteration caused by the reservoir using a non-parametric statistical method. From Fig. 7, it can be observed that the number of reversals ranks first in all hydrologic alteration values followed by 1-day maximum, 3-day maximum, 7-day maximum, October, 30-day maximum, January, August, June, high pulse duration and low pulse duration, all with IHA percentiles exceeding 67% (IHA  0.22) and 67th percentiles were computed for all 33 hydrologic alteration indicators as the lower and upper limits of the RVA target range (Fig. 7). Reversals ranks, 1-day maximum, 3-day maximum, 7-day maximum, October, 30-day maximum, January, August, June, high pulse duration, and low pulse duration are assumed to be strongly

Fig. 5. The median Julian dates changes of annual 1-day maximum before and after Danjiangkou reservoir construction in the Hanjiang river.

Y. Wang et al. / Ecological Engineering 81 (2015) 41–52

Fig. 6. Hydrological parameters changes of frequency and duration of high and low pulses caused by Danjiangkou reservoir operation in the Hanjiang river.

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120

Degree of IHA (%)

100

80

RVA targets

60

67% Percentile IHA

40 33% Percentile IHA 20

Number of reversals 1-day maximum 3-day maximum 7-day maximum October 30-day maximum January August June High pulse duration Low pulse duration February Base flow index Date of maximum High pulse count March Low pulse count May July Rise rate 90-day minimum 90-day maximum Date of minimum November 1-day minimum April 30-day minimum 7-day minimum Fall rate September 3-day minimum December Number of zero days

0

Fig. 7. Ranked median absolute degrees and percentile value of 33 indicators of hydrologic alteration at Xiangyang gauge in the Hanjiang river.

Table 3 Nonparametric RVA score at the Xiangyang gauging station during FMCC spawning season. 5 groups

Pre-impact period: 1950–1966

Post-impact period: 1975–2006

RVA targets

Medians

Coeff. of dispersion

Medians

Coeff. of dispersion

Low

High

(%)

Parameter Group #1 April May June

979 1130 774

0.4898 0.4836 0.7707

843.5 998 1100

0.6194 0.4679 0.4005

719.7 1043 682.7

1107 1310 914.8

14 (L) 38(M) 61(M)

Parameter Group #2 1-day minimum 3-day minimum 7-day minimum 30-day minimum 90-day minimum 1-day maximum 3-day maximum 7-day maximum 30-day maximum 90-day maximum Number of zero days Base flow index

414 421.7 438.1 776.7 1149 5422 4140 2831 1745 1151 0 0.3848

0.6377 0.6269 0.5574 0.4822 0.5393 1.002 0.8026 0.9071 0.7456 0.5461 0 0.5626

591 680 725.6 817.7 968.1 1590 1443 1359 1167 968.8 0 0.7616

0.6041 0.5559 0.5125 0.5534 0.3958 0.4277 0.388 0.3144 0.321 0.3929 0 0.1862

293.2 319.7 416.4 622.6 1049 2770 2120 1886 1370 1055 0 0.3097

504.1 515.2 534 926.4 1345 6298 4751 3709 1889 1380 0 0.4847

45(M) 61(M) 69(H) 14(L) 45(M) 69(H) 53(M) 61(M) 69(H) 29(L) – 92(H)

Parameter Group #3 Date of minimum Date of maximum

163 145

0.1858 0.1339

117 154

0.1148 0.1093

125.3 128

171.3 158.1

45(M) 18(L)

Parameter Group #4 Low pulse count Low pulse duration High pulse count High pulse duration

2 6.5 3 3

1 0.8846 0.6667 1.167

0 1 1 2

0 2 2 4.5

2 4 3 2

3 8.525 5 4.06

70(H) 93(H) 83(H) 68(H)

125 71 22

1.378 1.049 0.3182

58 47.5 42

0.431 0.6316 0.2381

78.88 94 20

174 52.2 25.06

77(H) 14(L) 100(H) 56

Parameter Group #5 Rise rate Fall rate Number of reversals Overall

Hydrologic alteration

Hydrologic alteration degree, L = (0–33)%, M = (34–66)%, H = (67–100)%. Overall degree means the average value of all degrees of alteration.

Y. Wang et al. / Ecological Engineering 81 (2015) 41–52

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Fig. 8. Hydrologic alterations of flow rise rate during FFMC spawning season in the Hanjiang river.

affected by construction and operation of the reservoir located upstream. 4.3. Influence on the river ecosystem and carps habitat Dams often result in hydrologic “fragmentation” or disconnection of the fluvial system, decoupling the affected river reach and its biotic systems from its natural flow regime and causing spatial disconnection, longitudinally of upstream and downstream reaches, and laterally of the river from its floodplain (Stanford et al., 1996). Natural flow provides the required spawning conditions for fishes. Flow regime alterations threaten the biodiversity and ecosystem functions of rivers and streams. In the downstream Hanjiang river, aquatic biodiversity and the population of migratory fishes (e.g., black carp, grass carp, and silver carp) have been greatly reduced since the 1970s (Liu and Cao, 1992). Due to dam construction, the routes of migratory fish have been blocked, such as Anguilla japonica and Rhinogobio typus. Population of the migratory fish reduced sharply. Natural flow plays a profound role in the lives of fish with critical life events linked to hydrological regime (e.g., spawning behavior, eggs hatching). Flow alteration changes the magnitude and frequency of high and low flows, often reducing variability, which are important to fish spawning behavior. From Fig. 5 and Table 2, it can be seen that reservoir regulation result in the reduction of flow variability, and alteration of the timing of rising flows. As a result, parent fish could not receive the enough stimulation of flow. According to Xie et al. (2009) major economic species resources in the Hanjiang river reduced severely. The egg production of FFMC significantly decreased from almost 5.0  108 ind at the end of 1970s to 0.32  108 ind in 2007. Hydrological connectivity between the river channel, floodplain, and groundwater structures the spatio-temporal heterogeneity of floodplain habitats, leading to characteristic high biodiversity (Ward and Stanford, 1995; Hu et al., 2008). During the wet season, the floodplain habitats create important spawning, nursery, and foraging areas for many fish species (Junk et al., 1989), and also determine whether and for how long fish can gain access to nursery habitats and food (Heiler et al., 1995). Reduction of high flow and river flooding duration result in decrease of available habitat spawning areas. Short-term flow fluctuations lead to a reduction in both the natural diversity and abundance of many native fishes and invertebrates (Poff et al., 1997; Poff and Zimmerman, 2010). Figs. 4 and 6, it can be seen that reservoir regulation result in the reduction of flood peak and high flow duration variability. In Hanjiang river, three spawning sites of FFMC disappeared (Xie et al., 2009). In comparison with the data in

1970s, Li et al. (2006) found that the fish with pelagic eggs decreased by 9 species, 8 of which belonged to important economic fish species. In certain years, there have been no parent fishes on the spawning ground, such as Ochetobibus elongatus, Elopichthys bambusa, Luciobramamacr ocephalus, Coreius heterodon, and Erythroculter mongolicus. The FFMC are the main economic fishes in the Hanjiang river basin, also play an important role in Yangtze river freshwater fishery. The ecological hydrological conditions required by FFMC during the spawning times are more complex than other fishes (Yu, 1982; Xie et al., 2009). After the impoundment of the Danjiangkou reservoir, the hydrological regime of river was changed. The FFMC populations have gradually declined. In the present study, we take FFMC as target fish to assess hydrological alteration of Danjiangkou reservoir on fish species. From Table 3 it can be observed that monthly flows during FFMC spawning season (April–June) have been greatly altered by Danjiangkou reservoir. Except for April, the hydrological alterations are relatively high in FFMC spawning time. The May and June alterations reached 38% and 61%, respectively, belonging to the middle degree. The consecutive flow rise in the spawning time is a necessary condition for the spawning of FFMC (Yi et al., 1988; Chen et al., 2009; Wan et al., 2011). Danjiangkou reservoir imposed great alteration on flow rise rate, with high degree of 77% (Fig. 8). The low pulse duration, low pulse count, high pulse count and high pulse duration decreased greatly by Danjiangkou reservoir, with hydrological alterations of 74%, 93%, 83% and 68%, respectively, reaching high degree (Table 3 and Fig. 9). The negative alteration value means that the rise rate fell within the RVA target range less often than expected. According to Table 3 we can know that absolute hydrological alteration value caused by Danjiangkou reservoir for FFMC during the spawning season is 56%. Ecohydrological condition required by FFMC has been severely influenced by Danjiangkou reservoir operation. Approx-natural flow rise conditions should be guaranteed when Danjiangkou reservoir optimal operation rules are designed. Spawning conditions for the FFMC are affected not only by flow conditions but also by a range of other variables including water temperature, sediment load and deposition, and so on. A comprehensive characterization of the living, resting and spawning requirements of the FFMC in the Hanjiang river should therefore take into account a wide range of variables. This will be the focus of our future research. The Danjiangkou reservoir is the source of water for the middle route of the South-to-North Water Diversion Project (SNWDP) in China. The first task of the middle route of SNWDP is to enlarge the storage capacity to 29.05 billion m3 from the current level of 17.4 billion m3. The expanded Danjiangkou Reservoir will provide

50 Y. Wang et al. / Ecological Engineering 81 (2015) 41–52

Fig. 9. Hydrologic alterations of frequency and duration of high and low pulses during FFMC spawning season in the Hanjiang river.

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9.5 billion m3 of water annually to Beijing, Tianjin, and cities in Hebei, Henan and Hubei provinces since 2015. It will be able to provide 13–14 billion m3 by 2030. The water transfer project, after being diverted to the North, will alter the Danjiangkou reservoir’s discharge and its distribution. The change will further affect ecological hydrological regimes in the middle-lower Hanjiang river. Combined influences by Danjiangkou reservoir and SNWDP should be addressed in ongoing research. Impact of large dams on the environment was expressed as degradation of the river continuity, which influences the hydrological regime below the dam. Nevertheless, the dams/reservoirs really provide great benefits, such as flood protection and hydropower (Duflo and Pande, 2007). Danjiangkou reservoir also play important roles in flood control, drinking water supply, irrigation, power generation, recreation, and navigation and other important benefits. Besides, as the source of the middle route of the SNWDP, it has begun to provide water to north China since December, 2014 (SNWDP, 2015). With climate change, dams/ reservoirs may also play an increasingly important role in protecting water resources and thus contributing to human development (WCD, 2000). In addition, the dam/ reservoir can contribute to the water quality improvement. According to Urbaniak et al. (2012), the concentration and the transfer of the nutrients and pollutants along the river continuum might be diminished by anthropogenic retention through construction of the Sulejow reservoirs. 5. Conclusion The impacts of Danjiangkou reservoir on eco-hydrological conditions in the Hanjiang river were investigated by using RVA method. Danjiangkou reservoir reduced annual peak discharges, decreased the ratio of annual maximum flow, increased the ratio of annual minimum flow, decreased the number of reversals in discharge, reduced the timing of high and low flow, and changed the flow rise. Danjiangkou reservoir significantly changed the natural flow regimes in the downstream reach after its enclosure. Ecohydrological conditions of river ecosystem and habitat have been drastically influenced by Danjiangkou reservoir operation. Hydrological alteration caused by reservoir construction greatly reduced the aquatic biodiversity and fish community population. Key eco-hydrological indices have been severely altered, especially for FFMC. To minimize the negative ecological impacts, it is necessary to optimize the operation rules of Danjiangkou reservoir for river ecosystem health protection. In addition to the operation of Danjiangkou reservoir, SNWDP, with the function of diverting water from Danjiangkou reservoir to northern China should be considered in ongoing research. The results of this study will be greatly helpful for the future management of water resources and will be greatly important for further understanding of the human impacts (e.g., hydroelectric-dam) on hydrological regimes in the Hanjiang river. Acknowledgments This project was supported by the National Natural Science Fund of China (No. 51309131, 41071018 and 41030746),China Doctoral Program of Higher Education (20100091120059), the Skeleton Young Teachers Program and Excellent Disciplines Leaders in Midlife-Youth Program of Nanjing University. References Chen, Y., Liao, W., Peng, Q., Chen, D., Gao, Y., 2009. A summary of hydrology and hydrodynamics conditions of four Chinese carp’s spawning. J. Hydroecol. 2, 130–133 (in Chinese with English abstract).

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Chen, Y., Yang, T., Xu, C.Y., Zhang, Q., Chen, X., Hao, Z.C., 2010. Hydrologic alteration along the Middle and Upper East River (Dongjiang) basin, South China: a visually enhanced mining on the results of RVA method. Stochastic Env. Res. Risk Assess. 24, 9–18. Choi, S.-U., Yoon, B., Woo, H., 2005. Effects of dam-induced flow regime change on downstream river morphology and vegetation cover in the Hwang River, Korea. River Res. Appl. 21, 315–325. Duflo, E., Pande, R., 2007. Dams. Quat. J. Econ. 122, 601–646. Heiler, G., Hein, T., Schiemer, F., 1995. Hydrological connectivity and flood pulses as the central aspects for the integrity of a river-floodplain system. Regul. Rivers: Res. Manage. 11, 351–361. Hu, W.W., Wang, G.X., Deng, W., Li, S.N., 2008. The influence of dams on ecohydrological conditions in the Huaihe River basin, China. Ecol. Eng. 33, 233–241. Junk, W.J., Bayley, P.B., Sparks, R.E., 1989. The flood pulse concept in river-floodplain systems. In: Dodge, D.P. (Ed.), Proceedings of the International Large River Symposium (LARS). Canadian Journal of Fisheries and Aquatic Sciences Special Publication, 106, pp. 110–127. Li, X., Huang, D., Xie, W., 2006. Current status of spawning grounds of fish with pelagic eggs in the middle reaches of Hanjiang River. J. Dalian Fish. Univ. 21, 105–111 (in Chinese with English abstract). Li, Z.W., Zhang, Y.K., 2008. Multi-scale entropy analysis of Mississippi River flow. Stochastic Env. Res. Risk Assess. 22, 507–512. Liu, J.K., Cao, W.X., 1992. Fish resources of the Yangtze River basin and the tactics for their conservation. Resources and Environment in the Yangtze Basin 1, 17–22. Magilligan, F.J., Nislow, K.H., 2005. Changes in hydrologic regime by dams. Geomorphology 71, 61–78. Nilsson, C., Reidy, C.A., Dynesius, M., Revenga, C., 2005. Fragmentation and flow regulation of the world’s large river systems. Science 308, 405–408. Olden, J.D., Poff, N.L., 2003. Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River Res. Appl. 19, 101–121. Poff, N.L., Allan, J.D., Bain, M.D., Karr, J.R., Prestegaard, K.L., Richter, B.L., Sparks, R.E., Stromberg, J.C., 1997. The natural flow regime: a paradigm for river conservation and restoration. Bioscience 47, 769–784. Poff, N.L., Zimmerman, J.K.H., 2010. Ecological responses to altered flow regimes: a literature review to inform environmental flows science and management. Freshwater Biol 55, 194–205. Poff, N.L., Olden, J.D., Merrit, D.M., Pepin, D.M., 2007. Homogenization of regional river dynamics by dams and global biodiversity implications. Proc. Natl. Acad. Sci. U. S. A. 104, 5732–5737. Richter, B.D., Baumgartner, J.V., Powell, J., Braun, D.P., 1996. A method for assessing hydrologic alteration within ecosystems. Conserv. Biol. 10, 1163–1174. Richter, B.D., Baumgartner, J.V., Wigington, R., Braun, D.P., 1997. How much water does a river need? Freshwater Biol. 37, 231–249. Richter, B.D., Baumgartner, J.V., Braun, D.P., Powell, J., 1998. A spatial assessment of hydrologic alteration within a river network. Regul. Rivers: Res. Manage. 14, 329–340. Shiau, J.T., Wu, F.C., 2004. Assessment of hydrologic alterations caused by Chi-Chi diversion weir in Chou-Shui Creek, Taiwan: opportunities for restoring natural flow conditions. Regul. Rivers: Res. Manage. 20, 401–412. SNWDP, 2015. http://www.nsbd.gov.cn/zx/zxdt/201501/t20150115_366599.html. Stanford, J.A., Ward, J.V., Liss, W.J., Frissell, C.A., Williams, R.N., Lichatowich, J.A., Coutant, C.C., 1996. A general protocol for restoration of regulated rivers. Regul. Rivers: Res. Manage. 12, 391–413. Timme, H.D., Friederike, W., Henk, V., 2005. Quantification strategies for humaninduced and natural hydrological changes in wetland vegetation southern Florida, USA. Quat. Res. 64, 333–342. Urbaniak, M., Kiedrzynska, E., Zalewski, M., 2012. The role of a lowland reservoir in the transport of micropollutants, nutrients and the suspended particulate matter along the river continuum. Hydrol. Res. 43 (4), 400–411. Wan, L., Cai, Y., Tang, H., Yang, Z., 2011. Preliminary study on the larval resources of fishes spawning drifting eggs in the middle and lower reaches of the Hanjiang River. J. Hydroecol. 32, 53–57 (in Chinese with English abstract). Wang, Y., Xia, Z., Wang, D., 2011. Assessing the effect of Separation Levee Project on Chinese sturgeon (Acipensor sinensis) spawning habitat suitability in Yangtze River, China. Aquat. Ecol. 45, 255–266. Wang, Y., Xia, Z., Wang, D., 2012. A transitional region concept for assessing the effects of reservoirs on river habitats: a case of Yangtze River, China. Ecohydrology 5, 28–35. Ward, J.V., Stanford, J.A., 1995. Ecological connectivity in alluvial river ecosystems and its disruption by flow regulation. Regul. Rivers: Res. Manage. 11, 105–120. World Commission on Dams (WCD), 2000. Dams and Development: A New Framework for Decision-Making. Earthscan, London, pp. 64–65. Xie, W., Huang, D., Xie, S., Yang, H., 2009. The early evolution of the four major Chinese carps resources in the middle and lower reaches of Hanjiang River after the construction and operation of Danjiangkou Reservoir. J. Hydroecol. 2, 44–89 (in Chinese with English abstract). Yang, N., Mei, Y., Zhou, C., 2012a. An optimal reservoir operation model based on ecological requirement and its effect on electricity generation. Water. Resour. Manage. 26, 4019–4028. Yang, T., Zhang, Q., Chen, Y.Q.D., Tao, X., Xu, C.Y., Chen, X., 2008. A spatial assessment of hydrologic alteration caused by dam construction in the middle and lower Yellow River, China. Hydrol. Processes 22, 3829–3843. Yang, Z., Yan, Y., Liu, Q., 2012b. Assessment of the flow regime alterations in the Lower Yellow River, China. Ecol. Inf. 10, 56–64.

52

Y. Wang et al. / Ecological Engineering 81 (2015) 41–52

Yi, P.L., Yu, Z.T., Liang, Z.S., 1988. Gezhouba Dam and the Yangtze Four Major Chinese Carps. Hubei Technology Publishing Company, Wuhan, China (in Chinese with English abstract). Yu, Z.T., 1982. Fish resources investigation in the middle and lower reaches of Hanjiang River and assessment of impacts of Dangjiangkou reservoir on fish

resources in Hanjiang River. Reservoir Fish. 1, 19–24 (in Chinese with English abstract). Zhang, Q., Xu, C.Y., Chen, Y.D., Yang, T., 2009. Spatial assessment of hydrologic alteration across the Pearl River Delta China, and possible underlying causes. Hydrol. Processes 23, 1565–1574.