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The long-term water level dynamics during urbanization in plain catchment in Yangtze River Delta
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The long-term water level dynamics during urbanization in plain catchment in Yangtze River Delta S. Song, Y.P. Xu ∗ , J.X. Zhang, G. Li, Y.F. Wang School of Geographic and Oceanographic Science, Nanjing University, Nanjing, China
a r t i c l e
i n f o
Article history: Received 4 September 2015 Received in revised form 10 January 2016 Accepted 12 January 2016 Available online xxx Keywords: Water level Urbanization Yangtze River Delta Range of variability approach
a b s t r a c t Numerous aquatic problems have been produced by the extensive urbanization especially in last decades in eastern China. This paper presents an evaluation of water level alteration induced by urbanization in the Lower Qinhuai river basin, Yangtz River delta in the last half century. Analyses were conducted using Range of Variability Approach, based on the indicator system of hydrologic alteration including 31 water level related parameters. By contrasting the overall alteration range and that of each parameter in 1960–1979 (pre-impact period) and 1980–2008 (post-impact period) the hydrological impact of urbanization was revealed. The results indicate that, 1 the urbanization in 1980s-2010s lead to an expansion of impervious area by 8 times and a sever simplification of river network structure; 2 the average monthly water level increased considerably from the pre-impact to post-impact period due to the urbanization; 3 the low water level is more sensitive to the interference of urbanization, both the magnitude of water level in dry season and minimum low water pulse increased distinctly; 4the Lower Qinhuai river basin was changed with moderate intensity by the urbanization process, with and overall change degree of 42.5%. In conclusion, water level is a remarkable indicator of the river regime response to urbanization in plain river network area. The results of the study would provide support in water resources management in urban development, opening new perspective of the hydrological process evaluation in high urbanized plain catchment. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Hydrological deterioration and environment degradation caused by urbanization have been recognized as one of the most important factors for global environmental change (Braud et al., 2013). Aquatic system in plain river network is confronted with more critical and tremendous threaten, due to the barrier free expansion of urban construction and the underlying surface dominated hydrological environment provided by the broad flat geomorphology (Chen, 2007; Wang et al., 2008). The regulation of aquatic systems by impervious area and hydraulic constructions during urbanization is necessary to support key human activities including hydropower production, agricultural production, industrial and civil uses, and flood risk mitigation (Bizzi et al., 2012; Nilsson et al., 2005). Hydrological impacts of the alteration of underlying surface and river networks together with countermeasures are primarily studied (Burns et al., 2012; Chung et al., 2011; Hibbs and Sharp, 2012).
∗ Corresponding author. E-mail address: Happysong [email protected] (Y.P. Xu).
The expansion of impervious area such as roads, buildings, and other paved area, can reduce the filtration rate and leads to more efficient runoff processes (Burns et al., 2015; Valtanen et al., 2014). The alteration of river networks, such as river landfill, channelization, curve cut-off, accelerates the flood process by shortening and smoothening the flood routes. The majority research focused on the rainfall runoff process and flood process demonstrated the higher frequency, magnitude and peak flow of the flood event in the urbanized catchment than the less or non urbanized catchment (Miller et al., 2014; Rose and Peters, 2001; Sheng and Wilson, 2008; Suriya and Mudgal, 2012). However, the hydrological alteration of river regime under normal condition, such as daily river discharge, flow velocity and water depth were seldom addressed in hydrological effects study. The range of variability approach (RVA), which considers the alteration of frequency distributions of relevant indicators during the pre-impact and post-impact periods (Richter et al., 1996, 1997, 1998), is the most widely used approach to evaluate the long-term river regime alteration. In the RVA, two sets of flow data, representing pre-impact and post-impact conditions, are examined using 31 hydrologically relevant indicators known as indicators of hydrological alteration (IHAs) to assess the alteration of flow. Each IHA
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has one range of variability, which is determined by the 25th and 75th percentiles of the pre-impact IHA annual values. As soon as this range is established, the frequency (or ratio) of pre-impact and post-impact IHA values that fall into this range is calculated separately. Then, the relative change of the post-impact frequency to the pre-impact frequency will be considered as the hydrological alteration in the RVA (Yang et al., 2014). In this study, we took the highly urbanized catchment in plain river network area-Lower Qinhuai river catchment, Yangtze River Delta—as a case area. The main objectives of this research were to analyze the underlying surface and river structure variations during the urbanization process based on multi-period satellite images, to extensively discuss and set up appropriate IHAs system to evaluate hydrological alteration between a more-natural reference condition and post-urbanized conditions with real measured gauge data, and to reveal the water level alteration due to the rapid urbanization. The results would help improve the understanding of the controlling mechanisms of river system and their mutual influence on each other and on catchment storage capacity. 2. Material and methods 2.1. Study area Lower Qinhuai River basin located between 118◦ 39 to 119 19 E and 31 34 to 32 10 N, in south-west of Jiangsu province in China (Fig. 1). Draining an area of 410 km2 , the main Qinhuai River flows across the urban area of Nanjing before emptying into Yangtze River. The basin is dominated by the humid climatic region, with an annual averaged precipitation approximately 1047 mm and averaged temperature around 15.4 ◦ C. The rainy season extends from April to September, while the precipitation intensively concentrates in summer (June to August) due to the affection of southeast monsoon. Lower Qinhuai catchment is a typical flat terrain. The lowland polders cover the wide bank of the Lower Qinhuai river with the elevation varied from 6 to 8 m.a.s.l. The altitude of the 80% of the catchment was lower than 40 m.a.s.l., while the rest 20% was occupied by the low hills and mountains lower than 300 m.a.s.l. Due to the low topography, serious flood and waterlogging problem especially during summer threaten this area, which is then intensified by the urbanization process. The main soil types consist of yellow-brown soil, purple soil, limestone soil, paddy soil, and gray fluvo-aquic soil. The land use pattern mainly includes paddy field, woodland, impervious surface, water, and dry land. Associated with the expanding of the impervious area, the water area shrunk severely due to the dramatic urbanization over the past decades. The water storage capacity and the regulation capacity are, therefore, severely affected by the decline of the infiltration rate and the simplification of the river system. 2.2. Methodology 2.2.1. River network structure Urban expansion significantly altered the river network structure. The linear river network were extracted and its structure variation were analyzed. We selected 5 parameters, including river length (L), river density (Rd), water surface ratio (WSr), river complexity (CR) and river structure stability (SR), to represent the river network spatial distribution in the catchment. The meaning and the calculation formulas of each parameter are as follows, River length (L): the totally length of the line river network; River density (Rd): the length of the river network on unit basin area (S), Rd =
L S
(1)
Water surface ratio (WSr): the water surface area (Sw ) on unit basin area, WSr =
Sw S
(2)
River complexity (CR): the ration of total river length (L) and main stream length (Lm ), CR = Nc × (
L ) Lm
(3)
River stability (SR): SR =
Li+n /RAi+n (Li /RAi )
(4)
Here, Nc is the maximum channel order; L and Lm refer to the total river length and the length of the main river individually; Li+n and Li present the total river length of the (i + n)th year and the ith year; RAi+n and RAi refer to the water surface of the river in the (i + n)th year and the ith year. 2.2.2. Indicators of hydrologic alteration (IHAs) IHA compares water regime such as discharge, water level, flow velocity etc., before and after the impact from human activities. Due to the low gradients of Lower Qinhuai catchment and the widespread river regulating gate, the flow velocity and discharge of most rivers are quite low except during flood time. Based on such fact, we set up IHAs systems including 31 indicators using long term water level elevation, to perform integrated calculation before and after urbanization. According to the basic characteristics of hydrological condition, such as quantity, occurrence time, occurrence frequency, time duration, and rate of variation, these 31 indicators were then divided into 5 groups (Table 1). The following Eq. (5) was used to quantify the alteration degree of IHA affected by urbanization. D=
N0 − Ne × 100% Ne
(5)
Here, D is the change degree of each IHA indicator; N0 is the observed number of years in post-impacted period with IHA values fall within the RVA target; Ne is expected number of years in post-impacted period whose IHA values are anticipated within the RVA target; may use r*NT to assess; r is the ratio of IHA values within the RVA target before urbanization. When the threshold of the range are set to 75% and 25%, r can be valued at 50%; NT is the total years of flow series in pre-impacted period. When D valued from 0 to 33%, the hydrological indicator was altered with low intensity, and when D ranged from 34% to 66% and 67% to 100%, the indicator was considered to be altered with moderate and high intensity. The total alteration degree of the river system in the post-impact period due to the urbanization were also calculated in this research,
D0 =
1 2 Di 32 32
1⁄2 (6)
1
Here, D0 is the total alteration degree of the post-impact period; Di is the alteration degree of the indicator i. 2.2.3. Range of variability approach (RVA) The range of variability approach (RVA) was proposed by Richter et al. (1997). The central insight of RVA lies in the comparison of the IHAs values within the RVA target in the pre-impact period and post-impact period. A similar frequency in pre and post impact period indicate a low impact from urbanization. Higher or lower
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Table 1 The system of hydrologic alteration indicators (IHAs). Group
IHAs-number
IHAs-indicators
Chatacteristic
1 2 3 4
1–12 13–22 23–24 25–26 27–28 29–30 31
Monthly averaged water level from January to December Annually maximum and minimum water lever of 1-day, 3-days,7-days, 30-days and 90-days Occurrence date of the annual maximum/minimum 1-daywater level Count and frequency of the high/low water level
Quantity Quantity, duration Occurrence date Frequency, duration
Rise/fall rare of the water level Count of water level reversal annually
Frequency Variation rate
5
frequency suggest that the urbanization have brought intensive disturbance to the river system, and the potential unfavorable environment effects would be unavoidable. 2.3. Data acquiration and processing 2.3.1. Long term water level data The long-term daily averaged water elevation data were collected from Dongshan station from 1960 to 2008. Earlier research has pointed out that, the pre-impact or the so called reference period shouldn’t be less than 20 years, in order to decrease or eliminate the interannual hydrological change caused by climate etc. MK test to the analysis of time series suggest that the data from1980 showed distinct discontinuity. As a result, 1960–1979 was selected as pre-impact period (20 years), and the 1980–2008 was processed as post-impact period (29 years) in this study. On one hand, the high speed social and economic development have been starting and induce urban expansion since 1980s. On the other hand, the hydraulic engineering construction lasted 5 years – Qinhuaixinhe – was completed and came into use in 1980. The land use and river network change due to these anthropologic activities changed the hydrological process profoundly. 2.3.2. Land use and river network pattern The development in multi-temporal remote sensing technology has been accelerating the increase of the data availability, and promoting the multi spatial scale study (DeVries et al., 2015; Kovalskyy and Roy, 2013; Sexton et al., 2013). The land use cover change was monitored by the interpreted Thematic Mapper (TM) and Multispectral Scanner (MSS) images covered the study area. In total 14 sciences of images were adopted, including 7 scenes of TM images from 2006 and 7 scenes of MSS images from 1979, with the resolution of 30 m and 60 m respectively. The information source of drainage pattern is based on 1:50000 paper topographic map in 1979 and digital topographic map in 2006. The land use maps, river networks map were also used in the image processing. River systems for both periods were extracted through map digitization using Arcgis tool combined with the interpretion of remote sensing images. 2.3.3. Methodology framework The methodology framework of our study is shown in Fig. 2. We first set up the IHAs system based on the water level data, and then analyzed the range of variation of the water level related hydrological indicators during 1960–1979, and 1980–2008 respectively. The alteration degree of the overall river system and each individual
IHA indicator were studied by contrasting the RVA of pre-impact period (1960–1979) and post-impact period (1980–2008). Coupling analysis of underlying surface change and river alteration degree would provide interest results about interaction mechanism between underlying surface and the water level variation. 3. Analysis and results 3.1. Underlying surface and urbanization 3.1.1. Land use cover change (LUCC) The land use condition and the area of each type were extracted from TM images and shown in Figs. 3 and 4. The urban land use expanded significantly in the last 30years. The urban area was only 17.2 km2 in 1980s, which increased by 8 times to 158.81 km2 in 2010s. During the same period, the area of forest decreased by 73.52% from 242.26 km2 in 1980s to 64.15 km2 in 2010s. According to the transfer matrix (Table 2), the new built urban land were mainly from forest, wetland and dry land. Nearly 1/3 of the disappeared forest and wetland, together with more than 40% of the disappeared dry land were convert into urban area. In additional to urban land, around 1/5 of the decreased forest and wetland were changed into dry land. The water area increased by 1.9 km2 , while the area of paddy field and dry land decreased a little. 3.1.2. River network change According to Table 3 and Fig. 5, the river length and river density decreased by nearly one third, although the river surface ratio increased by one quarter in the last 30 years. The river complexity decreased by around 35%, which leads to the stability of river network decreased by 27.88%. 3.2. The RVA the gauged water elevation 3.2.1. Monthly averaged water level The RVA Table of the gauged water elevation is given in the following (Table 4). As shown in Table 4 and Fig. 6, the monthly averaged water level of Lower Qinhuai area increased in 1980–2008, in contrast with 1960–1979. The increase range was relatively lower in moderate water level season (April–June, October–November) than that in dry season (December–March) and flood season (July-September). The CV of the monthly averaged water level tends to be smaller in post-impact period. The change degrees of the water level in flood season were normally in positive direction and with moderate intensity.
Table 2 Land use transfer matrix from 1980s to 2010s. 2010s1980s
Forest
Water area
Paddy field
Urban land
Dry land
Forest Water area Paddy field Urban land Dry land
28.11% 11.90% 17.32% 10.87% 15.87%
1.73% 28.36% 3.46% 5.12% 1.18%
13.78% 18.74% 22.48% 19.95% 12.64%
34.38% 27.50% 34.72% 55.60% 43.03%
21.99% 13.49% 22.02% 8.47% 27.28%
Table 3 River network structure change from 1980s to 2010s. Period
L/km
Rd/km/km2
WSr/%
CR
SR
1980s 2010s Change/%
720.11 497.04 −30.98
1.45 1.00 −31.03
5.53 6.94 25.50
29.12 18.82 −35.38
1.04 0.75 −27.88
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Fig. 1. The location of Lower Qinhuai River basin.
Fig. 2. The methodology of the our study.
300 Area(km2)
250
242.26 184.85
200 150
108.85
101.74
100 50
124.17111.91 77.86
11.71 13.61
17.2
0 forest
water area paddy field Land use type
urban land
dry land
Fig. 3. The area of each land use type in Lower Qinhuai catchment in 1980s (grey) and 2010s (black).
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Fig. 4. The land use cover condition of Lower Qinhuai catchment in 1980s (left) and 2010s (right).
Fig. 5. The river network change of the study area in 1980s (left) and 2010s (right).
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Table 4 The RVA Table of the daily average water level of Dongshan gauge station. IHA
Pre-impact period Median
CV
Post-impact period Range Min
Median
CV
Max
Range of Variability Range Min
Lowerlimit
D
Change*
Upperlimit
Max
Monthly averaged water level January February March April May June July August September October November December
5.66 5.65 5.67 6.13 6.83 7.03 7.68 7.34 7.30 6.93 6.36 5.58
0.15 0.12 0.11 0.11 0.09 0.08 0.09 0.07 0.05 0.05 0.07 0.13
4.22 4.53 5.05 5.41 5.55 5.57 6.42 6.36 6.74 6.42 5.36 4.40
7.09 7.16 7.39 7.59 7.94 7.83 9.09 8.12 8.48 7.58 7.27 7.19
6.02 6.10 6.28 6.46 6.86 7.34 8.10 7.98 7.85 7.23 6.58 6.11
0.09 0.08 0.08 0.07 0.05 0.03 0.08 0.06 0.05 0.05 0.07 0.10
5.30 5.43 5.58 5.46 6.31 7.01 7.45 7.10 7.20 6.55 5.72 5.17
7.43 7.38 7.41 7.45 7.78 7.86 9.68 9.26 8.72 8.06 7.55 7.37
4.96 5.10 5.40 5.73 6.45 6.80 7.14 7.03 7.08 6.64 6.26 5.24
6.37 6.03 6.22 6.57 7.25 7.25 8.10 7.72 7.47 7.26 6.67 6.27
0.36 -0.14 -0.21 0.10 0.45 -0.45 -0.10 -0.52 -0.52 -0.03 -0.38 0.31
+, M −, L −, L +, L +, M −, M −, L −, M −, M −, L -, M +, L
Annual-max water level 1-day 3-days 7-days 30-days 90-days
8.79 8.73 8.50 7.97 7.51
0.10 0.10 0.09 0.07 0.05
7.42 7.38 7.34 7.11 6.78
10.45 10.39 10.29 9.55 8.45
8.95 8.80 8.71 8.33 7.96
0.08 0.08 0.08 0.07 0.05
7.58 7.58 7.55 7.46 7.28
10.49 10.40 10.22 9.70 9.27
8.25 8.12 8.05 7.69 7.30
9.47 9.40 9.20 8.40 7.79
0.24 0.45 0.31 -0.03 -0.59
+, L +, M +, L -, L -, M
4.75 4.85 4.96 5.24 5.65 87.00 187.50 4.50 19.58 5.50 14.52 1.45 −1.09 120.50
0.08 0.09 0.09 0.10 0.10 0.83 0.24 0.43 0.42 0.39 0.56 0.23 −0.16 0.17
4.11 4.15 4.17 4.21 4.74 4.00 84.00 2.00 8.09 2.00 8.40 0.75 −1.40 90.00
5.46 5.60 5.65 5.85 6.70 365.00 276.00 11.00 45.50 10.00 45.50 1.94 −0.74 166.00
5.52 5.60 5.66 5.75 6.11 81.00 202.00 7.00 13.14 5.00 18.40 1.07 −0.93 134.00
0.08 0.08 0.08 0.08 0.07 0.89 0.14 0.45 0.56 0.46 0.65 0.19 −0.19 0.14
4.85 5.07 5.09 5.17 5.54 1.00 152.00 2.00 6.43 1.00 9.89 0.85 −1.36 95.00
6.66 6.66 6.69 7.01 7.18 365.00 276.00 14.00 45.50 9.00 91.00 1.77 −0.64 155.00
4.58 4.65 4.74 5.00 5.28 44.25 175.75 4.00 14.25 4.00 12.54 1.26 −1.14 111.75
5.09 5.19 5.35 5.57 6.09 343.75 207.00 5.25 22.75 7.00 22.63 1.53 −0.89 143.50
−0.86 −0.86 −0.66 −0.31 −0.10 0.10 0.17 −0.86 −0.31 −0.52 0.03 −0.52 −0.24 0.10
-, H -, H -, M -, L -, L +, L +, L −, H −, L −, M +, L −, M −, L +, L
Annual-min water level 1-day 3-days 7-days 30-days 90-days Date of annual minimum # Date of annual maximum Low pulse counts Low pulse duration High pulse counts High pulse duration Rise rate Fall rate Annual Count of Revers
Note: CV refers to coefficient of variation; * + means the value of the indicator increased in the post-impact period compared with the pre-impact period, while—means decreased; L, M and H refers to the low, moderate and high intensity of change; # the date is Julian date, for each year take 1st Jan as the 1st day, and so forth.
3.2.2. Change of extreme water levels According to the second group of hydrological indicators in Table 4, the minimum annual water levels were more sensitive to the urbanization interference than the annual maximum water levels. The minimum water level was changed with moderate to high intensity, while the maximum water level was affected with low intensity. The short-duration low water levels indicated a higher increase than the long-duration low water level. Annual minimum water levels of 1-day, 3-days and 7-days in post-impact period
increased by nearly 15% compared with that in pre-impact period (Fig. 7).
3.2.3. The occurrence date of the extreme water levels As shown in Table 4, the occurrence date of the extreme water levels has the similar CV, Median and value range both in pre and post-impact period, which demonstrated the relatively low sensitivity of this indicator to the urbanization. The minimum annually water level of 1 day occurred in March and the maximum one occurred in June in both periods. The CV of the occurrence date of
Fig. 6. The monthly averaged water level of pre-impact and post-impact period in Lower Qinhuai basin.
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Fig. 7. The annual minimum water levels in Lower Qinhuai basin.
the annual 1-day minimum water level increased by 7.23%, while that of annual 1-day maximum water level decreased by 40%. 3.2.4. Count and durations of the extreme water levels The counts of low water levels pulse increased from 4.5 times to 7 times, and its averaged duration decreased from 20.75 days to 13 days, from the pre-impact period to the post-impact period. The high water level pulse was on the other hand decreased in counts but increase in the averaged duration. In earlier period the counts and duration were 5.5 and 14.5 respectively, which decreased to 5 and raised to 18.5 with the interference of urbanization in the later period. The CV of the count and durations of the extreme pulse valued between 40%–70%, increased by 4.65%, 28.57%, 17.95%, and 16.07% respectively in the later period, much higher than that of other indicators. These findings suggest the intensive affection of anthropologic activity to the extreme flow events, especially to the time duration and its uncertainty. 3.2.5. The of rise/fall rate and its frequency change Both the rise rate and fall rate of water level were on decline trend. The rise rate decreased by 25%, and the fall rate decreased by 15%. Although the range of annual reverse counts were decreasing, the annual counts of water level reverse increased from 120 times in pre-impact period to 134 times in post-impact period. When it comes to the variation range and CV, the water level rise range and CV decreased, while the fall range and its CV increased (Fig. 8). At the same time, the CV of the annual water level reverse counts also decreased. The rise rate was with moderate change degree, while the fall rate and reverse count were with low change degree.
3.3. The overall alteration of river system Based on formula (6), the total alteration degree of the river system in the post-impact period was estimated to be 43%, involving alteration degree of each IHAs. This indicated that the river system was altered with moderate intensity during 1980–2008 due to the urbanization process. In general, all five groups of indicators changed distinctly in the post-impact period. 14 indicators changed with moderate to high intensity, accounting 45% of the total amounts. The monthly averaged water level, together with the quantity, frequency and duration of annually extreme water level were affected with moderate to high intensity. Low water level was more sensitive to the urban expansion, and the change degree of quantity and frequency of low water levels fell into high intensity. 4. Discussion 4.1. Water level in plain river catchment Similar as discharge and flow velocity, water level is a critical information used for urban hydraulic engineering and flood management, such as in embankment height decision and urban zone planning etc. (Yamazaki et al., 2012). Water level was more often adopted as indicator in lake, wetland and floodplain areas, where the flow is diffusive and regulated by water level gradient (García Molinos et al., 2015; Gronewold and Stow, 2013; Yamazaki et al., 2012). River hydrodynamic research models have traditionally focused on the river discharge, flood process, and run off process (Notebaert et al., 2011; Sheng and Wilson, 2008; Villarini et al., 2009), while discussion on the river water level was gener-
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Fig. 8. The rise and fall rate of the annually averaged water level.
ally limited. Lower Qinhuai catchment is located in Yangtze River Delta with low elevation and consistent geomorphology condition. Due to the low gradient of the river bed and the construction of the control gates, the velocity of the rivers is very slow and the flow direction is uncertain. Based on such fact, water level is selected as the indicator of hydrodynamic of the rivers and water bodies inside this area.
The water level increased range under different hydrological conditions varied. The variation under low level condition and in dry seasons were more sensitive to the urbanization development, with much higher increased range. The research focused on hydrological response to urbanization based on SWAT model in nearby area with data series from 1985 to 2008 revealed a similar trend in wet and dry years. It pointed out that the increase of annual stream flow in the dry years was much higher than that in the average or wet year (Zhou et al., 2013a,b).
4.2. The urbanization and water level 4.3. Sea level rise and hydraulic engineering affection The urbanization affects the water levels by altering the underlying surface and the structure of river network. In our study, the monthly averaged water level increased with the expansion of impervious area and the simplification of the river networks (Fig. 9). The value range of high water level and the its duration increased distinctly, while the duration of annual low water level declined in the post urbanization period. The alteration will bring higher pressure for watershed managers, planners and decision makers. These findings is consistent with the earlier research related to hydrological impacts of urbanization (Jacobson, 2011; Rose and Peters, 2001; Suriya and Mudgal, 2012). For example, the integrated modeling results of Qinhuai catchment indicated that when impervious ratios change from 3% (1988) to 14% (2006), the mean annual runoff depth would rise by 5 mm, which would then increase the water level of the river network system (Du et al., 2012).
The sea level rise rate was around 5 mm/a in Yangtze River Estuary according to the estimation based on worldwide sample and satellite observation (Ericson et al., 2006; Zhou et al., 2013a,b). Due to the backwater effect of the sea level rise, the water level of costal water system present various rise range. The water level records of Taihu Lake, the biggest lake on Yangtze River Delta, implied that the monthly-averaged rates of lake level rise in the non-flood season (November, December and January) was 0.4 mm/year at western inlet station and 1.1 mm/year at eastern outlet station since 1950s (Chen and Wang, 1999). The eastern outlet station of Taihu Lake located in the middle estuary of Yangtze River Delta, while Dongshan station located in the upper part (Guo et al., 2015). The water level of Dongshan station would response to sea level rise, but with lower rate compared with that of Taihu.
Fig. 9. Water levels against impervious area from 1979 to 2006.
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The hydraulic engineering, such as embanking, regulation gate, dam and reservoir construction might be another reason for the water level rise. Comprehensive countermeasures, including levee reinforcement and reservoir risk elimination were organized by the local government to decrease the flood threaten since 1991. Statistically, earthwork and rockwork cumulative to 0.5 km3 size and 35.4 km length was constructed, 160 embanking buildings and 76 reservoirs were restored in Qinhuai catchment from 1991 to 2003. Remarkable achievements were made by the catchmentwide engineering practice. For example, compared the flood hazard in typical flood year, there were 23 failure cases of the levee in 1991, while none failure was found in 2003. The design standard of the Qinhuai river levee reached to defending flood with recurrence time of 50 year in 2003 (Wang et al., 2004). Apart from that, the hydrological Qinhuaixinhe gate and Wudingmen gate hinder substantially the expulsion of excess river water to the coast shortly after rainfall event during dry season. That’s why the water level rise significantly from December to March. These tow gates, and the embanking practices effectively reduce the flood risk by keeping more water, as well as the sediment carried inside water, inside the river course. However, the sedimentation leads to an increase of the river bed elevation, which then feed back to the water level rise too.
5. Conclusion and outlook The data source of this study included TM images from 1980s and 2009, thematic maps, and long-term water level series from 1960 to 1979 of Dongshan station. The urbanization process after 1980 was extracted with spatial analysis tools of ArcGis, and its water level response was analyzed with Range of Variability Approach. The pre-impact period and post-impact period was divided by 1980 according to the MK test. The main findings are as follows,
1. The construction land expanded by eight times from 1980s to 2010s, during the same period, the river network simplification leading to the decline of complexity and stability; 2. Distinct increase of the average monthly water level from preimpact to post-impact period was induced by the urbanization. The duration of low water level pulse and high water level pulse declined and raised considerably. The alteration degree of quantity and frequency of low water levels belongs to high intensity. 3. The low water level is more sensitive to the interference of urbanization. Monthly averaged water level increase during dry season reach to 40 cm. Annual minimum water levels of 1-day, 3-days and 7-days in post-impact period increased by nearly 15% individually; 4. The water level condition of Lower Qinhuai river basin was altered with a moderate intensity during the post-impact period. The overall change degree of 42.5%.
Urbanization is one of the major factors affecting the aquatic system environment, and the expansion of this process is projected to continue in the near future in our study area. A suite of alterations in hydraulic design and management should be made to maintain and adapt the urban areas to provide environmentally livable habitats with adequate water resource. More accurate water level variation information during the different urbanization period, as well as future scenario should be an interesting direction for the further investigate.
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Acknowledgments This research was financially supported by the key program of Jiangsu Natural Science Foundation (Grant No. BK20131276, BK20150584), the National Natural Science Foundation of China (Grant No. 41371046, 41401035), the Water Conservancy Science and Technology Foundation of Jiangsu Province (Grant No. 2015003), the Commonweal and Specialized Programs for Scientific Research, Ministry of Water Resources of China (Grant No. 201201072, 201501041).
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The long-term water level dynamics during urbanization in plain catchment in Yangtze River Delta S. Song, Y.P. Xu ∗ , J.X. Zhang, G. Li, Y.F. Wang School of Geographic and Oceanographic Science, Nanjing University, Nanjing, China
a r t i c l e
i n f o
Article history: Received 4 September 2015 Received in revised form 10 January 2016 Accepted 12 January 2016 Available online xxx Keywords: Water level Urbanization Yangtze River Delta Range of variability approach
a b s t r a c t Numerous aquatic problems have been produced by the extensive urbanization especially in last decades in eastern China. This paper presents an evaluation of water level alteration induced by urbanization in the Lower Qinhuai river basin, Yangtz River delta in the last half century. Analyses were conducted using Range of Variability Approach, based on the indicator system of hydrologic alteration including 31 water level related parameters. By contrasting the overall alteration range and that of each parameter in 1960–1979 (pre-impact period) and 1980–2008 (post-impact period) the hydrological impact of urbanization was revealed. The results indicate that, 1 the urbanization in 1980s-2010s lead to an expansion of impervious area by 8 times and a sever simplification of river network structure; 2 the average monthly water level increased considerably from the pre-impact to post-impact period due to the urbanization; 3 the low water level is more sensitive to the interference of urbanization, both the magnitude of water level in dry season and minimum low water pulse increased distinctly; 4the Lower Qinhuai river basin was changed with moderate intensity by the urbanization process, with and overall change degree of 42.5%. In conclusion, water level is a remarkable indicator of the river regime response to urbanization in plain river network area. The results of the study would provide support in water resources management in urban development, opening new perspective of the hydrological process evaluation in high urbanized plain catchment. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Hydrological deterioration and environment degradation caused by urbanization have been recognized as one of the most important factors for global environmental change (Braud et al., 2013). Aquatic system in plain river network is confronted with more critical and tremendous threaten, due to the barrier free expansion of urban construction and the underlying surface dominated hydrological environment provided by the broad flat geomorphology (Chen, 2007; Wang et al., 2008). The regulation of aquatic systems by impervious area and hydraulic constructions during urbanization is necessary to support key human activities including hydropower production, agricultural production, industrial and civil uses, and flood risk mitigation (Bizzi et al., 2012; Nilsson et al., 2005). Hydrological impacts of the alteration of underlying surface and river networks together with countermeasures are primarily studied (Burns et al., 2012; Chung et al., 2011; Hibbs and Sharp, 2012).
∗ Corresponding author. E-mail address: Happysong [email protected] (Y.P. Xu).
The expansion of impervious area such as roads, buildings, and other paved area, can reduce the filtration rate and leads to more efficient runoff processes (Burns et al., 2015; Valtanen et al., 2014). The alteration of river networks, such as river landfill, channelization, curve cut-off, accelerates the flood process by shortening and smoothening the flood routes. The majority research focused on the rainfall runoff process and flood process demonstrated the higher frequency, magnitude and peak flow of the flood event in the urbanized catchment than the less or non urbanized catchment (Miller et al., 2014; Rose and Peters, 2001; Sheng and Wilson, 2008; Suriya and Mudgal, 2012). However, the hydrological alteration of river regime under normal condition, such as daily river discharge, flow velocity and water depth were seldom addressed in hydrological effects study. The range of variability approach (RVA), which considers the alteration of frequency distributions of relevant indicators during the pre-impact and post-impact periods (Richter et al., 1996, 1997, 1998), is the most widely used approach to evaluate the long-term river regime alteration. In the RVA, two sets of flow data, representing pre-impact and post-impact conditions, are examined using 31 hydrologically relevant indicators known as indicators of hydrological alteration (IHAs) to assess the alteration of flow. Each IHA
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has one range of variability, which is determined by the 25th and 75th percentiles of the pre-impact IHA annual values. As soon as this range is established, the frequency (or ratio) of pre-impact and post-impact IHA values that fall into this range is calculated separately. Then, the relative change of the post-impact frequency to the pre-impact frequency will be considered as the hydrological alteration in the RVA (Yang et al., 2014). In this study, we took the highly urbanized catchment in plain river network area-Lower Qinhuai river catchment, Yangtze River Delta—as a case area. The main objectives of this research were to analyze the underlying surface and river structure variations during the urbanization process based on multi-period satellite images, to extensively discuss and set up appropriate IHAs system to evaluate hydrological alteration between a more-natural reference condition and post-urbanized conditions with real measured gauge data, and to reveal the water level alteration due to the rapid urbanization. The results would help improve the understanding of the controlling mechanisms of river system and their mutual influence on each other and on catchment storage capacity. 2. Material and methods 2.1. Study area Lower Qinhuai River basin located between 118◦ 39 to 119 19 E and 31 34 to 32 10 N, in south-west of Jiangsu province in China (Fig. 1). Draining an area of 410 km2 , the main Qinhuai River flows across the urban area of Nanjing before emptying into Yangtze River. The basin is dominated by the humid climatic region, with an annual averaged precipitation approximately 1047 mm and averaged temperature around 15.4 ◦ C. The rainy season extends from April to September, while the precipitation intensively concentrates in summer (June to August) due to the affection of southeast monsoon. Lower Qinhuai catchment is a typical flat terrain. The lowland polders cover the wide bank of the Lower Qinhuai river with the elevation varied from 6 to 8 m.a.s.l. The altitude of the 80% of the catchment was lower than 40 m.a.s.l., while the rest 20% was occupied by the low hills and mountains lower than 300 m.a.s.l. Due to the low topography, serious flood and waterlogging problem especially during summer threaten this area, which is then intensified by the urbanization process. The main soil types consist of yellow-brown soil, purple soil, limestone soil, paddy soil, and gray fluvo-aquic soil. The land use pattern mainly includes paddy field, woodland, impervious surface, water, and dry land. Associated with the expanding of the impervious area, the water area shrunk severely due to the dramatic urbanization over the past decades. The water storage capacity and the regulation capacity are, therefore, severely affected by the decline of the infiltration rate and the simplification of the river system. 2.2. Methodology 2.2.1. River network structure Urban expansion significantly altered the river network structure. The linear river network were extracted and its structure variation were analyzed. We selected 5 parameters, including river length (L), river density (Rd), water surface ratio (WSr), river complexity (CR) and river structure stability (SR), to represent the river network spatial distribution in the catchment. The meaning and the calculation formulas of each parameter are as follows, River length (L): the totally length of the line river network; River density (Rd): the length of the river network on unit basin area (S), Rd =
L S
(1)
Water surface ratio (WSr): the water surface area (Sw ) on unit basin area, WSr =
Sw S
(2)
River complexity (CR): the ration of total river length (L) and main stream length (Lm ), CR = Nc × (
L ) Lm
(3)
River stability (SR): SR =
Li+n /RAi+n (Li /RAi )
(4)
Here, Nc is the maximum channel order; L and Lm refer to the total river length and the length of the main river individually; Li+n and Li present the total river length of the (i + n)th year and the ith year; RAi+n and RAi refer to the water surface of the river in the (i + n)th year and the ith year. 2.2.2. Indicators of hydrologic alteration (IHAs) IHA compares water regime such as discharge, water level, flow velocity etc., before and after the impact from human activities. Due to the low gradients of Lower Qinhuai catchment and the widespread river regulating gate, the flow velocity and discharge of most rivers are quite low except during flood time. Based on such fact, we set up IHAs systems including 31 indicators using long term water level elevation, to perform integrated calculation before and after urbanization. According to the basic characteristics of hydrological condition, such as quantity, occurrence time, occurrence frequency, time duration, and rate of variation, these 31 indicators were then divided into 5 groups (Table 1). The following Eq. (5) was used to quantify the alteration degree of IHA affected by urbanization. D=
N0 − Ne × 100% Ne
(5)
Here, D is the change degree of each IHA indicator; N0 is the observed number of years in post-impacted period with IHA values fall within the RVA target; Ne is expected number of years in post-impacted period whose IHA values are anticipated within the RVA target; may use r*NT to assess; r is the ratio of IHA values within the RVA target before urbanization. When the threshold of the range are set to 75% and 25%, r can be valued at 50%; NT is the total years of flow series in pre-impacted period. When D valued from 0 to 33%, the hydrological indicator was altered with low intensity, and when D ranged from 34% to 66% and 67% to 100%, the indicator was considered to be altered with moderate and high intensity. The total alteration degree of the river system in the post-impact period due to the urbanization were also calculated in this research,
D0 =
1 2 Di 32 32
1⁄2 (6)
1
Here, D0 is the total alteration degree of the post-impact period; Di is the alteration degree of the indicator i. 2.2.3. Range of variability approach (RVA) The range of variability approach (RVA) was proposed by Richter et al. (1997). The central insight of RVA lies in the comparison of the IHAs values within the RVA target in the pre-impact period and post-impact period. A similar frequency in pre and post impact period indicate a low impact from urbanization. Higher or lower
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Table 1 The system of hydrologic alteration indicators (IHAs). Group
IHAs-number
IHAs-indicators
Chatacteristic
1 2 3 4
1–12 13–22 23–24 25–26 27–28 29–30 31
Monthly averaged water level from January to December Annually maximum and minimum water lever of 1-day, 3-days,7-days, 30-days and 90-days Occurrence date of the annual maximum/minimum 1-daywater level Count and frequency of the high/low water level
Quantity Quantity, duration Occurrence date Frequency, duration
Rise/fall rare of the water level Count of water level reversal annually
Frequency Variation rate
5
frequency suggest that the urbanization have brought intensive disturbance to the river system, and the potential unfavorable environment effects would be unavoidable. 2.3. Data acquiration and processing 2.3.1. Long term water level data The long-term daily averaged water elevation data were collected from Dongshan station from 1960 to 2008. Earlier research has pointed out that, the pre-impact or the so called reference period shouldn’t be less than 20 years, in order to decrease or eliminate the interannual hydrological change caused by climate etc. MK test to the analysis of time series suggest that the data from1980 showed distinct discontinuity. As a result, 1960–1979 was selected as pre-impact period (20 years), and the 1980–2008 was processed as post-impact period (29 years) in this study. On one hand, the high speed social and economic development have been starting and induce urban expansion since 1980s. On the other hand, the hydraulic engineering construction lasted 5 years – Qinhuaixinhe – was completed and came into use in 1980. The land use and river network change due to these anthropologic activities changed the hydrological process profoundly. 2.3.2. Land use and river network pattern The development in multi-temporal remote sensing technology has been accelerating the increase of the data availability, and promoting the multi spatial scale study (DeVries et al., 2015; Kovalskyy and Roy, 2013; Sexton et al., 2013). The land use cover change was monitored by the interpreted Thematic Mapper (TM) and Multispectral Scanner (MSS) images covered the study area. In total 14 sciences of images were adopted, including 7 scenes of TM images from 2006 and 7 scenes of MSS images from 1979, with the resolution of 30 m and 60 m respectively. The information source of drainage pattern is based on 1:50000 paper topographic map in 1979 and digital topographic map in 2006. The land use maps, river networks map were also used in the image processing. River systems for both periods were extracted through map digitization using Arcgis tool combined with the interpretion of remote sensing images. 2.3.3. Methodology framework The methodology framework of our study is shown in Fig. 2. We first set up the IHAs system based on the water level data, and then analyzed the range of variation of the water level related hydrological indicators during 1960–1979, and 1980–2008 respectively. The alteration degree of the overall river system and each individual
IHA indicator were studied by contrasting the RVA of pre-impact period (1960–1979) and post-impact period (1980–2008). Coupling analysis of underlying surface change and river alteration degree would provide interest results about interaction mechanism between underlying surface and the water level variation. 3. Analysis and results 3.1. Underlying surface and urbanization 3.1.1. Land use cover change (LUCC) The land use condition and the area of each type were extracted from TM images and shown in Figs. 3 and 4. The urban land use expanded significantly in the last 30years. The urban area was only 17.2 km2 in 1980s, which increased by 8 times to 158.81 km2 in 2010s. During the same period, the area of forest decreased by 73.52% from 242.26 km2 in 1980s to 64.15 km2 in 2010s. According to the transfer matrix (Table 2), the new built urban land were mainly from forest, wetland and dry land. Nearly 1/3 of the disappeared forest and wetland, together with more than 40% of the disappeared dry land were convert into urban area. In additional to urban land, around 1/5 of the decreased forest and wetland were changed into dry land. The water area increased by 1.9 km2 , while the area of paddy field and dry land decreased a little. 3.1.2. River network change According to Table 3 and Fig. 5, the river length and river density decreased by nearly one third, although the river surface ratio increased by one quarter in the last 30 years. The river complexity decreased by around 35%, which leads to the stability of river network decreased by 27.88%. 3.2. The RVA the gauged water elevation 3.2.1. Monthly averaged water level The RVA Table of the gauged water elevation is given in the following (Table 4). As shown in Table 4 and Fig. 6, the monthly averaged water level of Lower Qinhuai area increased in 1980–2008, in contrast with 1960–1979. The increase range was relatively lower in moderate water level season (April–June, October–November) than that in dry season (December–March) and flood season (July-September). The CV of the monthly averaged water level tends to be smaller in post-impact period. The change degrees of the water level in flood season were normally in positive direction and with moderate intensity.
Table 2 Land use transfer matrix from 1980s to 2010s. 2010s1980s
Forest
Water area
Paddy field
Urban land
Dry land
Forest Water area Paddy field Urban land Dry land
28.11% 11.90% 17.32% 10.87% 15.87%
1.73% 28.36% 3.46% 5.12% 1.18%
13.78% 18.74% 22.48% 19.95% 12.64%
34.38% 27.50% 34.72% 55.60% 43.03%
21.99% 13.49% 22.02% 8.47% 27.28%
Table 3 River network structure change from 1980s to 2010s. Period
L/km
Rd/km/km2
WSr/%
CR
SR
1980s 2010s Change/%
720.11 497.04 −30.98
1.45 1.00 −31.03
5.53 6.94 25.50
29.12 18.82 −35.38
1.04 0.75 −27.88
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Fig. 1. The location of Lower Qinhuai River basin.
Fig. 2. The methodology of the our study.
300 Area(km2)
250
242.26 184.85
200 150
108.85
101.74
100 50
124.17111.91 77.86
11.71 13.61
17.2
0 forest
water area paddy field Land use type
urban land
dry land
Fig. 3. The area of each land use type in Lower Qinhuai catchment in 1980s (grey) and 2010s (black).
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Fig. 4. The land use cover condition of Lower Qinhuai catchment in 1980s (left) and 2010s (right).
Fig. 5. The river network change of the study area in 1980s (left) and 2010s (right).
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Table 4 The RVA Table of the daily average water level of Dongshan gauge station. IHA
Pre-impact period Median
CV
Post-impact period Range Min
Median
CV
Max
Range of Variability Range Min
Lowerlimit
D
Change*
Upperlimit
Max
Monthly averaged water level January February March April May June July August September October November December
5.66 5.65 5.67 6.13 6.83 7.03 7.68 7.34 7.30 6.93 6.36 5.58
0.15 0.12 0.11 0.11 0.09 0.08 0.09 0.07 0.05 0.05 0.07 0.13
4.22 4.53 5.05 5.41 5.55 5.57 6.42 6.36 6.74 6.42 5.36 4.40
7.09 7.16 7.39 7.59 7.94 7.83 9.09 8.12 8.48 7.58 7.27 7.19
6.02 6.10 6.28 6.46 6.86 7.34 8.10 7.98 7.85 7.23 6.58 6.11
0.09 0.08 0.08 0.07 0.05 0.03 0.08 0.06 0.05 0.05 0.07 0.10
5.30 5.43 5.58 5.46 6.31 7.01 7.45 7.10 7.20 6.55 5.72 5.17
7.43 7.38 7.41 7.45 7.78 7.86 9.68 9.26 8.72 8.06 7.55 7.37
4.96 5.10 5.40 5.73 6.45 6.80 7.14 7.03 7.08 6.64 6.26 5.24
6.37 6.03 6.22 6.57 7.25 7.25 8.10 7.72 7.47 7.26 6.67 6.27
0.36 -0.14 -0.21 0.10 0.45 -0.45 -0.10 -0.52 -0.52 -0.03 -0.38 0.31
+, M −, L −, L +, L +, M −, M −, L −, M −, M −, L -, M +, L
Annual-max water level 1-day 3-days 7-days 30-days 90-days
8.79 8.73 8.50 7.97 7.51
0.10 0.10 0.09 0.07 0.05
7.42 7.38 7.34 7.11 6.78
10.45 10.39 10.29 9.55 8.45
8.95 8.80 8.71 8.33 7.96
0.08 0.08 0.08 0.07 0.05
7.58 7.58 7.55 7.46 7.28
10.49 10.40 10.22 9.70 9.27
8.25 8.12 8.05 7.69 7.30
9.47 9.40 9.20 8.40 7.79
0.24 0.45 0.31 -0.03 -0.59
+, L +, M +, L -, L -, M
4.75 4.85 4.96 5.24 5.65 87.00 187.50 4.50 19.58 5.50 14.52 1.45 −1.09 120.50
0.08 0.09 0.09 0.10 0.10 0.83 0.24 0.43 0.42 0.39 0.56 0.23 −0.16 0.17
4.11 4.15 4.17 4.21 4.74 4.00 84.00 2.00 8.09 2.00 8.40 0.75 −1.40 90.00
5.46 5.60 5.65 5.85 6.70 365.00 276.00 11.00 45.50 10.00 45.50 1.94 −0.74 166.00
5.52 5.60 5.66 5.75 6.11 81.00 202.00 7.00 13.14 5.00 18.40 1.07 −0.93 134.00
0.08 0.08 0.08 0.08 0.07 0.89 0.14 0.45 0.56 0.46 0.65 0.19 −0.19 0.14
4.85 5.07 5.09 5.17 5.54 1.00 152.00 2.00 6.43 1.00 9.89 0.85 −1.36 95.00
6.66 6.66 6.69 7.01 7.18 365.00 276.00 14.00 45.50 9.00 91.00 1.77 −0.64 155.00
4.58 4.65 4.74 5.00 5.28 44.25 175.75 4.00 14.25 4.00 12.54 1.26 −1.14 111.75
5.09 5.19 5.35 5.57 6.09 343.75 207.00 5.25 22.75 7.00 22.63 1.53 −0.89 143.50
−0.86 −0.86 −0.66 −0.31 −0.10 0.10 0.17 −0.86 −0.31 −0.52 0.03 −0.52 −0.24 0.10
-, H -, H -, M -, L -, L +, L +, L −, H −, L −, M +, L −, M −, L +, L
Annual-min water level 1-day 3-days 7-days 30-days 90-days Date of annual minimum # Date of annual maximum Low pulse counts Low pulse duration High pulse counts High pulse duration Rise rate Fall rate Annual Count of Revers
Note: CV refers to coefficient of variation; * + means the value of the indicator increased in the post-impact period compared with the pre-impact period, while—means decreased; L, M and H refers to the low, moderate and high intensity of change; # the date is Julian date, for each year take 1st Jan as the 1st day, and so forth.
3.2.2. Change of extreme water levels According to the second group of hydrological indicators in Table 4, the minimum annual water levels were more sensitive to the urbanization interference than the annual maximum water levels. The minimum water level was changed with moderate to high intensity, while the maximum water level was affected with low intensity. The short-duration low water levels indicated a higher increase than the long-duration low water level. Annual minimum water levels of 1-day, 3-days and 7-days in post-impact period
increased by nearly 15% compared with that in pre-impact period (Fig. 7).
3.2.3. The occurrence date of the extreme water levels As shown in Table 4, the occurrence date of the extreme water levels has the similar CV, Median and value range both in pre and post-impact period, which demonstrated the relatively low sensitivity of this indicator to the urbanization. The minimum annually water level of 1 day occurred in March and the maximum one occurred in June in both periods. The CV of the occurrence date of
Fig. 6. The monthly averaged water level of pre-impact and post-impact period in Lower Qinhuai basin.
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Fig. 7. The annual minimum water levels in Lower Qinhuai basin.
the annual 1-day minimum water level increased by 7.23%, while that of annual 1-day maximum water level decreased by 40%. 3.2.4. Count and durations of the extreme water levels The counts of low water levels pulse increased from 4.5 times to 7 times, and its averaged duration decreased from 20.75 days to 13 days, from the pre-impact period to the post-impact period. The high water level pulse was on the other hand decreased in counts but increase in the averaged duration. In earlier period the counts and duration were 5.5 and 14.5 respectively, which decreased to 5 and raised to 18.5 with the interference of urbanization in the later period. The CV of the count and durations of the extreme pulse valued between 40%–70%, increased by 4.65%, 28.57%, 17.95%, and 16.07% respectively in the later period, much higher than that of other indicators. These findings suggest the intensive affection of anthropologic activity to the extreme flow events, especially to the time duration and its uncertainty. 3.2.5. The of rise/fall rate and its frequency change Both the rise rate and fall rate of water level were on decline trend. The rise rate decreased by 25%, and the fall rate decreased by 15%. Although the range of annual reverse counts were decreasing, the annual counts of water level reverse increased from 120 times in pre-impact period to 134 times in post-impact period. When it comes to the variation range and CV, the water level rise range and CV decreased, while the fall range and its CV increased (Fig. 8). At the same time, the CV of the annual water level reverse counts also decreased. The rise rate was with moderate change degree, while the fall rate and reverse count were with low change degree.
3.3. The overall alteration of river system Based on formula (6), the total alteration degree of the river system in the post-impact period was estimated to be 43%, involving alteration degree of each IHAs. This indicated that the river system was altered with moderate intensity during 1980–2008 due to the urbanization process. In general, all five groups of indicators changed distinctly in the post-impact period. 14 indicators changed with moderate to high intensity, accounting 45% of the total amounts. The monthly averaged water level, together with the quantity, frequency and duration of annually extreme water level were affected with moderate to high intensity. Low water level was more sensitive to the urban expansion, and the change degree of quantity and frequency of low water levels fell into high intensity. 4. Discussion 4.1. Water level in plain river catchment Similar as discharge and flow velocity, water level is a critical information used for urban hydraulic engineering and flood management, such as in embankment height decision and urban zone planning etc. (Yamazaki et al., 2012). Water level was more often adopted as indicator in lake, wetland and floodplain areas, where the flow is diffusive and regulated by water level gradient (García Molinos et al., 2015; Gronewold and Stow, 2013; Yamazaki et al., 2012). River hydrodynamic research models have traditionally focused on the river discharge, flood process, and run off process (Notebaert et al., 2011; Sheng and Wilson, 2008; Villarini et al., 2009), while discussion on the river water level was gener-
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Fig. 8. The rise and fall rate of the annually averaged water level.
ally limited. Lower Qinhuai catchment is located in Yangtze River Delta with low elevation and consistent geomorphology condition. Due to the low gradient of the river bed and the construction of the control gates, the velocity of the rivers is very slow and the flow direction is uncertain. Based on such fact, water level is selected as the indicator of hydrodynamic of the rivers and water bodies inside this area.
The water level increased range under different hydrological conditions varied. The variation under low level condition and in dry seasons were more sensitive to the urbanization development, with much higher increased range. The research focused on hydrological response to urbanization based on SWAT model in nearby area with data series from 1985 to 2008 revealed a similar trend in wet and dry years. It pointed out that the increase of annual stream flow in the dry years was much higher than that in the average or wet year (Zhou et al., 2013a,b).
4.2. The urbanization and water level 4.3. Sea level rise and hydraulic engineering affection The urbanization affects the water levels by altering the underlying surface and the structure of river network. In our study, the monthly averaged water level increased with the expansion of impervious area and the simplification of the river networks (Fig. 9). The value range of high water level and the its duration increased distinctly, while the duration of annual low water level declined in the post urbanization period. The alteration will bring higher pressure for watershed managers, planners and decision makers. These findings is consistent with the earlier research related to hydrological impacts of urbanization (Jacobson, 2011; Rose and Peters, 2001; Suriya and Mudgal, 2012). For example, the integrated modeling results of Qinhuai catchment indicated that when impervious ratios change from 3% (1988) to 14% (2006), the mean annual runoff depth would rise by 5 mm, which would then increase the water level of the river network system (Du et al., 2012).
The sea level rise rate was around 5 mm/a in Yangtze River Estuary according to the estimation based on worldwide sample and satellite observation (Ericson et al., 2006; Zhou et al., 2013a,b). Due to the backwater effect of the sea level rise, the water level of costal water system present various rise range. The water level records of Taihu Lake, the biggest lake on Yangtze River Delta, implied that the monthly-averaged rates of lake level rise in the non-flood season (November, December and January) was 0.4 mm/year at western inlet station and 1.1 mm/year at eastern outlet station since 1950s (Chen and Wang, 1999). The eastern outlet station of Taihu Lake located in the middle estuary of Yangtze River Delta, while Dongshan station located in the upper part (Guo et al., 2015). The water level of Dongshan station would response to sea level rise, but with lower rate compared with that of Taihu.
Fig. 9. Water levels against impervious area from 1979 to 2006.
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The hydraulic engineering, such as embanking, regulation gate, dam and reservoir construction might be another reason for the water level rise. Comprehensive countermeasures, including levee reinforcement and reservoir risk elimination were organized by the local government to decrease the flood threaten since 1991. Statistically, earthwork and rockwork cumulative to 0.5 km3 size and 35.4 km length was constructed, 160 embanking buildings and 76 reservoirs were restored in Qinhuai catchment from 1991 to 2003. Remarkable achievements were made by the catchmentwide engineering practice. For example, compared the flood hazard in typical flood year, there were 23 failure cases of the levee in 1991, while none failure was found in 2003. The design standard of the Qinhuai river levee reached to defending flood with recurrence time of 50 year in 2003 (Wang et al., 2004). Apart from that, the hydrological Qinhuaixinhe gate and Wudingmen gate hinder substantially the expulsion of excess river water to the coast shortly after rainfall event during dry season. That’s why the water level rise significantly from December to March. These tow gates, and the embanking practices effectively reduce the flood risk by keeping more water, as well as the sediment carried inside water, inside the river course. However, the sedimentation leads to an increase of the river bed elevation, which then feed back to the water level rise too.
5. Conclusion and outlook The data source of this study included TM images from 1980s and 2009, thematic maps, and long-term water level series from 1960 to 1979 of Dongshan station. The urbanization process after 1980 was extracted with spatial analysis tools of ArcGis, and its water level response was analyzed with Range of Variability Approach. The pre-impact period and post-impact period was divided by 1980 according to the MK test. The main findings are as follows,
1. The construction land expanded by eight times from 1980s to 2010s, during the same period, the river network simplification leading to the decline of complexity and stability; 2. Distinct increase of the average monthly water level from preimpact to post-impact period was induced by the urbanization. The duration of low water level pulse and high water level pulse declined and raised considerably. The alteration degree of quantity and frequency of low water levels belongs to high intensity. 3. The low water level is more sensitive to the interference of urbanization. Monthly averaged water level increase during dry season reach to 40 cm. Annual minimum water levels of 1-day, 3-days and 7-days in post-impact period increased by nearly 15% individually; 4. The water level condition of Lower Qinhuai river basin was altered with a moderate intensity during the post-impact period. The overall change degree of 42.5%.
Urbanization is one of the major factors affecting the aquatic system environment, and the expansion of this process is projected to continue in the near future in our study area. A suite of alterations in hydraulic design and management should be made to maintain and adapt the urban areas to provide environmentally livable habitats with adequate water resource. More accurate water level variation information during the different urbanization period, as well as future scenario should be an interesting direction for the further investigate.
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Acknowledgments This research was financially supported by the key program of Jiangsu Natural Science Foundation (Grant No. BK20131276, BK20150584), the National Natural Science Foundation of China (Grant No. 41371046, 41401035), the Water Conservancy Science and Technology Foundation of Jiangsu Province (Grant No. 2015003), the Commonweal and Specialized Programs for Scientific Research, Ministry of Water Resources of China (Grant No. 201201072, 201501041).
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