evaluating functions of reservoirs storage capacities and...

Chin. Geogra. Sci. 2016 Vol. 26 No. 6 pp. 789–802 Springer Science Press

doi: 10.1007/s11769-016-0838-6 www.springerlink.com/content/1002-0063

Received date: 2016-01-18; accepted date: 2016-05-02 Foundation item: Under the auspices of Commonwealth and Specialized Programs for Scientific Research, Ministry of Water Resources

of China (No. 200901042) Corresponding author: XU Chongyu. E-mail: [email protected] © Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag Berlin Heidelberg 2016

Evaluating Functions of Reservoirs′ Storage Capacities and Locations on Daily Peak Attenuation for Ganjiang River Basin Using Xinanjiang Model

DU Jinkang1, 2, ZHENG Dapeng3, XU Youpeng1, HU Shunfu4, XU Chongyu5, 6

(1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China; 2. Jiangsu Center for Collabora-tive Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China; 3. Anhui Electric Power Design Institute of China Energy and Electricity Construction Group, Hefei 230601, China; 4. Department of Geography, Southern Illinois University Edwardsville, Edwardsville IL 62026, USA; 5. State Key Laboratory of Water Resources and Hydropower Engineer-ing Science, Wuhan University, Wuhan 430072, China; 6. Department of Geosciences, University of Oslo, N-0316 Oslo 1047 Blindern, Norway)

Abstract: Flooding is the most prevalent and costly natural disaster in the world and building reservoirs is one of the major structural

measures for flood control and management. In this paper, a framework was proposed to evaluate functions of reservoirs′ locations and

magnitudes on daily peak flow attenuation for a large basin of China, namely Ganjiang River Basin. In this study, the Xinanjiang model

was adopted to simulate inflows of the reservoirs and flood hydrographs of all sub-catchments of the basin, and simple reservoir opera-

tion rules were established for calculating outflows of the reservoirs. Four reservoirs scenarios were established to analyze reservoirs′

locations on daily peak flow attenuation. The results showed that: 1) reservoirs attenuated the peak discharges for all simulated floods,

when the flood storage capacities increase as new reservoirs were built, the peak discharge attenuation by reservoirs showed an increas-

ing tendency both in absolute and relative measures; 2) reservoirs attenuated more peak discharge relatively for small floods than for

large ones; 3) reservoirs reduced the peak discharge more efficiently for the floods with single peak or multi peaks with main peak oc-

curred first; and 4) effect of upstream reservoirs on peak attenuation decreased from upper reaches to lower reaches; upstream and mid-

stream reservoirs played important roles in decreasing peak discharge both at middle and lower reaches, and downstream reservoirs had

less effect on large peak discharge attenuation at outlet of the basin. The proposed framework of evaluating functions of multiple reser-

voirs′ storage capacities and locations on peak attenuation is valuable for flood control planning and management at basin scale.

Keywords: reservoir; peak flow; Xinanjiang model; reservoir operation; Ganjiang River Basin

Citation: Du Jinkang, Zheng Dapeng, Xu Youpeng, Hu Shunfu, Xu Chongyu, 2016. Evaluating functions of reservoirs′ storage capaci-

ties and locations on daily peak attenuation for Ganjiang River Basin using Xinanjiang model. Chinese Geographical Science, 26(6):

789–802. doi: 10.1007/s11769-016-0838-6

1 Introduction

Flooding is the most prevalent and costly natural disas-ter in the world. Floods can cause major damage to hu-man lives, properties, and livestock. Floods can also cause traffic problems, population displacement, inter-

ruption of economic activities, partial or total suspen-sion of basic infrastructure services, and spread of epi-demic diseases (Schultz, 2002; Cheng and Chau, 2004; De Paes and Brandão, 2013). Today, there are a large number of strategies and methods to relieve flood haz-ards and disasters (Simonovic, 2002). Among them, res-

790 Chinese Geographical Science 2016 Vol. 26 No. 6

ervoirs, as major structural measures for better flood management, can be effectively used to reduce flood hazards by temporarily storing the flood water and re-leasing it later. Flood control has been a significant purpose for many of the existing reservoirs and contin-ues to be a main purpose for some of the major dams of the world currently under construction (Schultz, 2002; Hickey et al., 2003).

It is well-known that reservoirs can reduce the size and frequency of flood peaks in downstream reaches by storing flood water to attenuate flood peaks and to avoid the coincidence of floods from downstream tributaries of the same river (Xu, 1990; Lee et al., 2001; Cheng and Chau, 2004; De Paes and Brandão, 2013; Chen et al., 2014). There is a lot of research to quantitatively assess the role of reservoirs on flood control. De Paes and Brandão (2013), for example, evaluated the influence of the Manso Reservoir on the attenuation of downstream flooding in the metropolitan area of Cuiabá in Brazil. They used level-pool routing method to simulate flood routing of the reservoir and one-dimensional hydrody-namic model to calculate flood wave translation during floodplain passage. The results showed that the reservoir reduced the frequency of flood risk to downstream communities for return periods between 50 and 100 years. Wang and Xu (2011) coupled a grid-based dis-tributed hydrological model and a reservoir operation module to evaluate the function of reservoirs for flood control during typhoon seasons in the Upper Tone River Catchment of Japan. They discovered that the reservoirs attenuated the peak flood discharge by 423 m3/s for a typhoon-induced flood event. Wu et al. (2007) investi-gated hydrologic effects of Xinfengjiang Reservoir of the East River Basin in southern China using the Soil and Water Assessment Tool (SWAT) and two other res-ervoir operation modules. They found that the reservoir operation reduced the river peak flow and seasonal fluctuations greatly. The average standard deviation and coefficient of variation of outflow were reduced by about 55% and 48%, respectively comparing with those of inflow for the period of January 1965 to December 1974. López-Moreno et al. (2002) investigated the role of the Yesa Reservoir in reducing floods in the Upper Aragón River of central Spanish Pyrenees by comparing the inflow and outflow series of the reservoir. The re-sults confirmed that the frequency of floods downstream of the dam decreased and the reduction mainly de-

pended on the water storage level and the season of the year.

Not only large reservoirs that have a certain storage capacity reserved for flood control can significantly re-duce the peak flow in the downstream rivers during floods (Cheng and Chau, 2004), but small reservoirs can also play a role of reducing the peak flow. Jenicek (2008) used Hydrologic Engineering Center-Hydrology Modeling System (HEC-HMS) to simulate the impact of uncontrolled small reservoirs system on flood flow re-duction in the Chomutovka River Basin in the Czech Republic. The results showed that small uncontrolled water reservoirs have sufficient function of decreasing flood peaks. Ayalew et al. (2013) adopted stochastic rainfall model (modified Bartlett-Lewis pulse model), simple rainfall-runoff model (the linear-reservoir method) and reservoir routing model to investigate the effect of flood control reservoirs on downstream flood frequency of a small catchment within the Clear Creek Watershed near Iowa City, Iowa. Their results revealed that the reservoir can attenuate peak discharges of floods with high-probability occurrence and have no effect on peak discharges of low-probability flood events.

The operating rules for a reservoir can play an im-portant role on the flood reduction as well (Connaugh-ton et al., 2014; Chou and Wu, 2015). The optimal op-eration rules derived from the mathematical models, such as linear programming, dynamic programming, and multi-objective optimization can lead to maximum at-tenuation of floods (Ford and Killen, 1995; Cheng and Chau, 2001; Ngo et al., 2008; Dittmann et al., 2009; Kumar et al., 2010; Luo et al., 2015). In addition, the accurate forecast of flooding events can also help reduce the downstream flood peak effectively (Cheng and Chau, 2004).

However, few researches have reported the relative roles of factors, such as the storage capacities and the locations of reservoirs in reducing the peak flows of floods at different reaches of a large river basin. The objective of our research was to quantitatively assess the effects of reservoirs′ storage capacities, and the loca-tions of reservoirs on floods with different magnitudes at upper, middle, and lower reaches of Ganjiang River Basin, China. In this study, an integrated framework was proposed to achieve the objective, which combines three approaches: 1) the Xinanjiang model was adopted to simulate inflows of reservoirs and flood hydrographs of

DU Jinkang et al. Evaluating Functions of Reservoirs′ Storage Capacities and Locations on Daily Peak Attenuation for… 791

different reaches of the basin; 2) simple reservoir opera-tion rules were established to calculate the outflows of reservoirs; and 3) different scenarios of reservoirs′ loca-tions were built to identify the function of the reservoirs′ locations and flood storage capacities on peak flow at-tenuation.

2 Materials and Methods

2.1 Study area The Ganjiang River Basin is located in Jiangxi Prov-ince, China, with a drainage area of 83 500 km2 and with the main reach length of 750 km (Fig. 1). It is the largest tributary of the Poyang Lake Basin. The basin lies in the subtropical region with a warm and humid climate char-acterized by a mean annual precipitation of 1543 mm and

an annual average temperature of 17.5℃. The front-type

and typhoon-type rainfalls are two important phenom-ena in the basin. Precipitation across the basin mainly concentrates in April–June (rainy season), which ac-counts for 44.33% of annual precipitation (Zhang et al., 2015). Average annual runoff is about 6.80 × 1010 m3 in the period from 1959 to 2004, and the average runoff coefficient is 0.53. The streamflow in the rainy season accounts for about 60% of the total annual streamflow. The floods occur mostly during May and June and they often last 15 to 20 days. The topography varies from high mountainous (maximum elevation of about 2200 m above mean sea level) to alluvial plains in the lower reaches of the primary watercourses.

The land-use types are woodland, cropland, grass-land, water body, and built-up land. Among those, woodland is the main land use type. The main soil types are red soil, paddy soil, reddish soil, and purple soil. Approximately 3700 reservoirs with a total storage ca-pacity of 1.05 × 1010 m3 have been constructed in the basin for the purpose of flood control, hydropower gen-eration, irrigation and water supplies. The main purpose of building large number of reservoirs is to protect the lower areas from flooding and to relieve the flood risk. Therefore, it is very important to assess flood control functions of the reservoirs with different volumes and at different locations for floods with varied magnitudes and characteristics.

2.2 Data sets In this study, ten heavy floods were selected to simulate

the daily rainfall runoff process (Table 1). The major data used for flood simulation included DEMs, daily precipitation, daily maximum and minimum air tem-perature from 14 national meteorological stations inside and near the catchment, and the daily discharge of streamflow gauging station at the outlet of the basin during ten flood events.

The DEMs with a spatial resolution of 86 meters were used to extract sub-catchments and stream net-works. River networks and 27 sub-catchments were cre-ated (Fig. 1), and hydrologic parameters, such as slope, flow direction, flow accumulation, stream length and sub-catchment area were calculated using MapWinGIS.

Reservoirs with total storage greater than 1.0 × 108 m3 were selected in this study for computational efficiency. Table 2 shows the characteristics of selected reservoirs located in the catchment.

2.3 Xinanjiang model The Xinanjiang rainfall-runoff model used in this study was developed by Zhao et al. (1980) and Zhao (1992). The model is a semi-distributed conceptual rain-fall-runoff model and has been successfully and widely applied to large number of river basins in the humid and semi-humid regions of China for flood forecasting, wa-ter resources estimation, hydrological station planning, and hydrological assessment due to climate change (Li et al., 2009; Yao et al., 2009; Bao et al., 2011, Shi et al., 2011; Li et al., 2012).

The main feature of the model is the concept of run-off generation on repletion of storage, which means that runoff is not produced until the soil moisture content of the aeration zone reaches field capacity, and thereafter runoff equals the rainfall excess without further loss. This hypothesis was first proposed in China in the 1960s, and much subsequent experience supports its validity for humid and semi-humid regions. Two para-bolic curves are adopted to account for the spatial het-erogeneities of tension water and free water storage ca-pacities throughout the sub-catchments. Based on those curves, the partial-area runoff generation and surface flow, interflow and groundwater flow could be calcu-lated (Zhao, 1980).

The Xinanjiang model consists of three components: the evapotranspiration component (evapotranspiration of three soil layers), the runoff generating component (runoff production and separation of the runoff into


Fig. 1 Map of study area and locations of meteorological and hydrological stations

Table 1 Characteristics of ten floods Flood no. Duration Rainfall (mm) Flood volume (108 m3) Daily peak discharge (m3/s) Peak occurrence

1 1961-05-31–1961-06-29 331 192 15 400 1961-06-14

2 1962-05-01–1962-07-15 900 496 19 700 1962-06-20

3 1970-05-01–1970-05-24 259 176 15 200 1970-05-10

4 1973-03-30–1973-05-03 443 244 15 400 1973-04-11

5 1978-05-14–1978-06-01 168 75 8290 1978-05-23

6 1981-04-01–1981-05-10 380 240 15 100 1981-04-11

7 1998-02-16–1998-04-06 428 284 16 900 1998-03-11

8 1998-06-12–1998-07-11 362 196 16 800 1998-06-26

9 2002-06-12–2002-07-16 336 197 13 800 2002-06-19

10 2006-05-20–2006-06-24 359 210 11 900 2006-06-10


Table 2 Characteristics of reservoirs in Ganjiang River Basin Reservoir Location Constructed year Drainage area (km2) Total storage (108 m3) Flood storage (108 m3) Maximal discharge (m3/s)

Shangyoujiang Upstream 1957 4565 8.22 3.51 5870

Changgang Upstream 1970 848 3.65 2.07 5900

Longtan Upstream 1996 150 1.16 0.53 6000

Youluokou Upstream 1981 557 1.16 0.62 4030

Tuanjie Upstream 1984 412 1.68 0.99 4451

Nanche Midstream 1998 459 1.53 1.00 4000

Baiyunshan Midstream 1988 464 1.25 0.24 1710

Wan′an Midstream 1990 36 900 22.16 10.19 22 600

Sheshang Midstream 1975 427 2.14 1.07 3460

Laoyingpan Midstream 1983 172 1.07 0.53 1163

Shangyou Downstream 1960 140 1.83 0.38 2000

Feijiantan Downstream 1961 180 1.01 0.43 1254

Jiangkou Downstream 1961 3900 8.90 1.02 2000

Xiajiang Downstream 2013 62 710 11.87 6.00 24 800

surface water, interflow and ground water), and the flow routing component (surface water, interflow and ground water routing and channel flow routing).

In this study, the Xinanjiang model was used to simulate floods at a daily time step. The surface water routing was simplified by Recession Formula and the channel flow routing was simplified by the Lag and Route Method. The model structure is shown in Fig. 2 (Zhao, 1992; Song et al., 2012).

The model has 16 parameters: evapotranspiration pa-rameters, K, Um, Lm, Dm, C; runoff production parame-ters, B, IMP; runoff separation parameters, Sm, Ex, Kg, Ki; and runoff routing parameters, Cg, Ci, Cs, Cl , L. The output is more sensitive to seven parameters, including

K, Sm, Cs, Ci, Cg, Cl, and L. The model parameters are explained in Table 3.

The model inputs include daily precipitation and daily potential evapotranspiration. The model outputs are surface flow, interflow, groundwater flow of every sub-basins and main outlet of the basin, and evapotran-spiration. The state variables are areal mean tension wa-ter contents of upper, lower and deeper layers, different water storages of free water, surface water, interflow and groundwater, as well as surface runoff generation from impervious area. The internal variable is the ratio of runoff generation area with whole area of the basin.

The BlaneyCriddle equation was used to estimate potential evapotranspiration (Xu and Singh, 2001):

Fig. 2 Schematic description of Xinanjiang model


Table 3 Parameters of Xinanjiang model (Cheng et al., 2006) Notation Description

Um (mm) Areal mean tension water capacity of upper soil layer

Lm (mm) Areal mean tension water capacity of lower soil layer

Dm (mm) Areal mean tension water capacity of deeper soil layer

B Exponential parameter with a single parabolic curve, which represents the non-uniformity of the spatial distribution of the tension water capac-ity over the catchment

IMP (%) Percentage of impervious and saturated areas in the catchment

K Ratio of potential evapotranspiration to pan evaporation or evaporation obtained by other methods

C Coefficient of the deep layer, used to calculate evapotranspiration from deeper layer, which depends on the proportion of the basin area covered by vegetation with deep roots

Sm (mm) Areal mean free water capacity of the surface soil layer, which represents the maximum possible deficit of free water storage

Ex Exponent of the free water capacity curve influencing the development of the saturated area

Kg Outflow coefficients of the free water storage to groundwater relationships

Ki Outflow coefficients of the free water storage to interflow relationships

Cg Recession constants of the groundwater storage

Ci Recession constants of the interflow storage

Cs Recession constants of the surface water storage

Cl Recession constants in the lag and route method for channel routing within each sub-basin

L Lag in time of channel routing

m t a(0.46 8.13)PET K P T (1)

where PET is potential evapotranspiration rate (mm/d),

Ta is mean air temperature (℃), Pt is percentage of total

daytime hours for the period used out of total daytime hours of the year (365 × 12), and Km is a monthly con-sumptive use coefficient, depending on vegetation type, location and season, 0.75 was adopted in this study.

2.4 Reservoir operation The storage function approach is used to simulate the changes in reservoir volume. The basic equation is given by

d

d

VINF OF

t (2)

where INF is inflow (m3/s), OF is release (m3/s) and V is reservoir storage (m3), t is time (s). Once the inflow, initial conditions, and the relationship between vol-ume/storage and discharge of a reservoir, and the opera-tion rules are known, the release from a reservoir can be simulated (Wang and Xu, 2011). In this research, a sim-ple form of finite difference equation was used as the storage function (Yang et al., 2004):

11 2

t tt t t

INF INFV V OF t

(3)

where t is time step (s); Vt and Vt+1 are reservoir storages at the beginning and the end of time step t, respectively; INFt and INFt+1 are inflows at the beginning and the end of time step t, respectively (m3/s), which are estimated by Xinanjiang model; OFt is the release during time step t (m3/s).

In order to evaluate the effects of reservoir location and size on the flood attenuation, simple operational rules were adopted as follows. If the storage at the be-ginning of time step (i.e., Vt ) is equal to the flood con-trol volume, the release is equal to the inflow; if the storage at the beginning of time step is less than the flood control volume, the release will be determined by the relationship between storage and discharge; and if the estimated Vt+1 is larger than flood control volume, the difference between them can be counted as addi-tional release.

2.5 Flood simulation The Xinanjiang model was used to simulate the inflows of the reservoirs and outflows of all sub-catchments. A trial-and-error method was used to calibrate the model in the basin. The performance of the model was evalu-ated using statistical analysis of model outputs. Statisti-cal parameters, such as determination coefficient (R2) and Nash-Sutcliffe efficiency (Ens) (Nash and Sutcliffe, 1970), were used to measure the capability and reliabil-


ity of the model in describing the observed flood proc-esses. In addition, the relative errors of daily peak dis-charge and flood volume, and absolute peak time error were also used for the evaluation of flood simulation.

The interpolation of precipitation was calculated by Thiessen polygon method based on the point rainfall values observed at the rain gauge stations, the precipita-tion of each sub-catchment was the sum of area- weighted rainfall values of Thiessen polygons occupied in the sub-catchment. The temperature used for PET calculation was the average values from all the mete-orological stations.

In this study, the appropriate values of the parameters were first specified based on the previous studies (Cheng et al., 2006; Zhang et al., 2012), which showed successful application of the Xinanjiang model for flood simulation in China. Only sensitive parameters were calibrated for each flood event simulation. The initial state variables, such as the initial soil tension water storage, the initial surface flow, interflow, and ground-water flow should be determined in advance. Due to the lack of those data, they were adjusted iteratively until the estimated flood volume reflected the observed flood volume as closely as possible.

In addition, the purpose of the study was to evaluate the functions of reservoirs on flood peak reduction, the sensitive parameters for each flood event were allowed to change, so that the flood events could be simulated more accurately.

Prior to outflow calculation, inflows of reservoirs needed to be split from the single unregulated flow se-ries of the sub-basin estimated by the Xiananjiang model. These flow-splits were performed by multiplying the full unregulated hydrograph of the sub-basin by a constant percentage based on drainage area ratios. The inflow series of reservoir were the sum of the split flows of the sub-basin and upstream flows to the reservoir.

2.6 Flood peak attenuation assessment In order to examine flood control functions of the reser-voirs, the simulations under real conditions and different

scenarios were carried out by assuming that the reservoirs have or do not have full flood storage capacities at the beginning of the simulation. In the latter case, the reser-voirs release water at the rate of inflow. The effects of reservoirs on flood peak discharge (real conditions) were first analyzed, and then four scenarios were designed to evaluate all existing reservoirs, upstream, midstream and downstream reservoirs on flood peak attenuation.

3 Results and Analyses

3.1 Model calibration The calibrated model parameters and initial state vari-ables are listed in Table 4 and Table 5. It can be seen from Table 4 that 10 of 16 parameters and two initial state variables are stable. In Table 5, the variation of K can attribute to the errors of the simple potential evapotranspiration method. Ki holds 0.49 for almost all flood events except for Flood 2. The runoff routing pa-rameters, including Cg, Ci, Cs, and Cl, vary with the greatest range of 0.15 for all flood events. The initial state variables vary for each flood event, reflecting dif-ferent antecedent soil moisture and runoff conditions.

Statistical results of model performance are summa-rized in Table 6. It can be seen that the Ens ranges from 0.62 to 0.95 and six simulated floods have Ens larger than 0.80; the R2 ranges from 0.77 to 0.97 and nine simulated floods have R2 greater than 0.80. In addition, the simulated relative flood volume errors are within –8% to 10%, the relative peak flow errors are within –18% to 1%, and eight simulated floods have relative peak flow errors less than or equal to 10%. The absolute peak time errors are within ±1 day.

The simulated and observed hydrographs of the ten major flood events are shown in Fig. 3.

It can be seen from Table 6 and Fig. 3 that the Xinan-jiang model and reservoir operation rules simulated the runoff processes well for the selected flood events at the discharge gauge station of Waizhou, which indicates that the models can be used for flood peak reduction as-sessment of the reservoirs.

Table 4 Calibrated model parameters and initial state variables (same for all floods)

Parameter Initial state variable

C Um (mm) Lm (mm) Dm (mm) B IMP (%) Sm (mm) Ex Kg L

Si (mm) FRi (%)

0.16 15 80 25 0.30 0.15 20 1.5 0.49 0 10 10

Notes: Si is initial surface free water storage (mm); FRi is initial area saturated with tension water (%); The descriptions of parameters are shown in Table 3


Table 5 Calibrated model parameters and initial state variables Parameter Initial state variable

Flood no. K Ki Cs Ci Cg Cl Ti (%) Qsi (m

3/s) Qii (m3/s) Qgi (m

3/s)

1 0.48 0.49 0.75 0.75 0.98 0.29 71 30 60 100

2 0.52 0.21 0.70 0.70 0.90 0.31 70 50 50 200

3 0.35 0.49 0.70 0.70 0.90 0.36 84 120 110 310

4 0.32 0.49 0.70 0.70 0.90 0.29 70 90 90 150

5 0.39 0.49 0.70 0.70 0.90 0.31 82 100 100 150

6 0.23 0.49 0.60 0.60 0.98 0.33 90 50 60 90

7 0.31 0.49 0.65 0.65 0.98 0.28 55 100 100 150

8 0.62 0.49 0.70 0.70 0.90 0.31 69 50 60 90

9 0.30 0.49 0.70 0.70 0.86 0.35 70 200 200 300

10 0.30 0.49 0.70 0.70 0.90 0.39 80 100 100 200

Notes: Ti is initial tension water (%); Qsi is initial surface water flow (m3/s); Qii is initial interflow (m3/s); Qgi is initial groundwater flow (m3/s); The descriptions of parameters are shown in Table 3

Table 6 Simulated results of ten floods

Flood volume Peak discharge Peak time Flood no. Ens R2 Simulated

(109 m3) Relative error (%)

Simulated (m3/s)

Relative error (%)

Simulated

Absolute error (day)

1 0.88 0.92 213 10 14 579 –5 1961-06-14 –1

2 0.66 0.81 468 –6 17 480 –11 1962-06-20 0

3 0.62 0.83 167 –6 15 327 1 1970-05-10 0

4 0.76 0.77 246 1 12 689 –18 1973-04-11 –1

5 0.85 0.88 78 5 7873 –5 1978-05-23 1

6 0.89 0.91 244 1 14 290 –5 1981-04-11 –1

7 0.83 0.86 290 2 17 029 1 1998-03-10 –1

8 0.95 0.97 182 –7 16 377 –3 1998-06-26 0

9 0.82 0.85 215 9 12 451 –10 2002-06-19 0

10 0.73 0.85 192 –8 11 954 0 2006-06-10 0

3.2 Effect of reservoirs on flood peak attenuation The peak discharges were calculated from the ten se-lected major flood events under the assumption of with and without flood storage capacities of built reservoirs (real conditions) using the same parameters and initial state variables as calibrated. The simulated daily peak discharges and peak attenuations by reservoirs at the gauge station of the basin outlet, Waizhou, are provided below (Table 7).

The results in Table 7 show that the reservoirs have attenuated the simulated peak discharges for all ten flood events. Generally, when the flood storage capaci-ties increased (the reservoirs were built continually), the attenuations of peak discharges showed an increasing tendency both in absolute and relative measures, even

though the peak flow reduction of each flood depended on rainfall characteristics, flood features, real-time op-eration of the reservoirs, and other factors.

It can also be seen from Table 7 that with the same to-tal flood storage capacity of 22.58 × 108 m3, the reser-voirs can reduce relatively more peak flows of normal floods, such as Floods 9 and 10, than heavy floods, such as Floods 7 and 8. Flood 5 had a short duration and a relatively small single peak, the reservoirs reduced peak discharge of the flood by 13%, which means the smaller the flood peak, the bigger the reservoirs′ impact on re-ducing peak discharge, confirming the results of Acreman et al. (2000), López-Moreno et al. (2002), and Ayalew et al. (2013). They found flood peaks were clearly reduced but to a lesser extent for extreme hydrological events.


Fig. 3 Observed and simulated hydrographs of flood events

The flood characteristics have important impact on peak discharge attenuation of the reservoirs. In general, reservoirs could reduce the peak discharge more effi-ciently for the floods with single peak or multiple peaks with main peak occurred first. For example, the reser-voirs with the same total flood control capacity in the basin reduced peak discharge by 15% for Flood 9 with

main peak occurred first and 10% for Flood 10 with single peak. However, the reduction was only 6% for Floods 7 and 8, which had multiple peaks but the main peak occurred lately. In such cases, the real-time flood forecasting would be very important because the flood control capacities can be emptied before the main peak arrives.


Table 7 Effects of reservoirs on simulated daily peak discharges

Flood no. Discharges with reservoirs

(m3/s) Discharges without reservoirs

(m3/s) Absolute reduction

(m3/s) Relative reduction

(%) Total flood storage capacity

(108 m3)

1 14 579 14 738 159 1 5.34

2 17 480 17 592 112 1 5.34

3 15 327 15 674 347 2 7.41

4 12 689 13 011 322 3 7.41

5 7873 9031 1158 13 8.48

6 14 290 15 010 720 5 9.10

7 17 029 18 080 1051 6 22.58

8 16 377 17 321 944 6 22.58

9 12 451 14 658 2207 15 22.58

10 11 954 13 243 1289 10 22.58

3.3 Effect of different reservoir scenarios on flood peak attenuation Four scenarios were built for flood peak simulation: all reservoirs, upstream reservoirs with water released to Ganzhou station, midstream reservoirs with water re-leased to Ji′an station, and downstream reservoirs with water released to Waizhou station. The four scenarios can help figure out the functions of reservoirs′ location on flood peak reduction.

Floods 2, 5, 6, 8, and 10 were selected for the simula-tion under different reservoir scenarios. The selection was based on the calibrated results and the flood mag-nitudes and characteristics. Flood 2 had the largest peak discharge and multiple peaks, Flood 5 had the smallest peak discharge, Flood 6 was simulated well and had moderate peak discharge, Flood 8 had two peaks with second peak larger, and Flood 10 had moderate peak discharge.

Five simulations were performed for each flood under no reservoirs and above mentioned four scenarios. The simulated peak discharges and peak attenuations of four scenarios at Ganzhou, Ji′an, and Waizhou stations are listed in Table 8. 3.3.1 Effect of all reservoirs on flood peak attenuation It can be seen from Table 8 that all peak discharges of the five flood events at three gauge stations were at-tenuated by all reservoirs. In relative term, average peak flow attenuation at three gauge stations increased from 6.2% to 20.0% when simulated peak discharges without reservoirs at Waizhou station decreased from 17 592 to 9031 m3/s, which also agrees with the literature report-ing that reservoirs can attenuate relatively more peak discharge for small floods than for large ones (López-Moreno et al., 2002; Ayalew et al., 2013). But

there was an exception, the average peak flow attenua-tion of reservoirs for Flood 6 was larger than that for Flood 10, while simulated peak discharges without res-ervoirs at Waizhou station of Flood 6 was larger than that of Flood 10. The reason was probably that Food 6 had single peak, so the reservoirs could have more space

Table 8 Effects of different reservoir scenarios on flood peak attenuation

Flood no.

Gauge station

Peak (m3/s)

P-all (%) P-up (%) P-mid (%)P-down

(%)

2 Ganzhou 6813 3.7 3.7 0.0 0.0

Ji′an 8405 10.2 2.9 6.5 0.0

Waizhou 17 592 4.6 0.6 4.0 0.0

Average 6.2 2.4 5.3 0.0

5 Ganzhou 7538 20.9 20.9 0.0 0.0

Ji′an 8464 18.7 15.6 7.0 0.0

Waizhou 9031 20.4 11.7 8.5 6.0

Average 20.0 16.1 7.8 6.0

6 Ganzhou 8045 10.4 10.4 0.0 0.0

Ji′an 12 247 13.5 6.7 8.3 0.0

Waizhou 15 010 15.7 5.3 11.7 2.8

Average 13.2 7.5 10.0 2.8

8 Ganzhou 6369 6.4 6.4 0.0 0.0

Ji′an 9645 9.9 4.7 5.5 0.0

Waizhou 17 321 5.5 2.7 4.0 0.0

Average 7.3 4.6 4.8 0.0

10 Ganzhou 6888 5.6 5.6 0.0 0.0

Ji′an 8847 10.1 0.4 9.6 0.0

Waizhou 13 243 9.7 0.5 4.3 4.9

Average 8.5 2.2 7.0 4.9

Notes: Peak is simulated peak discharge without reservoirs; P-all is peak dis-charge attenuation by all reservoirs; P-up is peak discharge attenuation by upstream reservoirs; P-mid is peak discharge attenuation by midstream reser-voirs; P-down is peak discharge attenuation by downstream reservoirs; Zero is not included in calculating averages


to restore incoming peak flows, while Flood 10 had more than one peak, and the main peak did not occur first. When the main flood peaks occurred, the reser-voirs had no space to restore incoming peak flows, which revealed that the attenuation extent of reservoirs was depended not only on flood magnitude but also on flood characteristics, such as the number of peaks and the occurrence of the main peak. 3.3.2 Effect of up-, mid-, and down-stream reservoirs on flood peak attenuation From Table 8 it also can be seen that the effect of up-stream reservoirs on peak attenuation for each flood decreased relatively from upper reaches (Ganzhou sta-tion) to middle reaches (Ji′an station), and to lower reaches (Waizhou station). One reason is that the flood wave will attenuate from upstream to downstream, and the effect of peak reduction by the upstream reservoirs will attenuate correspondingly. The other reason is that additional water also flows into Ji′an and Waizhou sta-tions, making peak discharge increased and conse-quently the relative peak reduction decreased.

The midstream reservoirs can attenuate flood peaks both at Ji′an and Waizhou stations. The attenuation ex-tent decreased for Floods 2, 8 and 10 from Ji′an station to Waizhou station, but increased for Floods 5 and 6.

The downstream reservoirs have no effects on flood peak attenuation for Floods 2 and 8, and have only small effects (2.8%–6.0%) for other three floods at Waizhou station. This is mainly caused by the drainage area and flood storage of the reservoirs, i.e., the Shangyou, Fei-jiantan, and Jiangkou reservoirs have less drainage area and flood storage, and most drainage area of the Xiaji-ang Reservoir is from upper and middle reaches. For the two heavy Floods 2 and 8, almost half of the flood peaks at Waizhou station were from the downstream of the basin, which is significantly larger than that for the other three floods, resulting in no effect on flood peak at-tenuation. 3.3.3 Effect of reservoirs on flood peak attenuation in middle and lower reaches For Ji′an station (middle reaches), the peak attenuation for Floods 2 and 10 was mainly contributed by mid-stream reservoirs, and that for Floods 5, 6, and 8 by both up- and mid-stream reservoirs, meaning that the up- and mid-stream reservoirs play an important role in de-creasing peak flow at the station.

For Waizhou station (lower reaches), the peak at-

tenuation for Flood 2 was mainly contributed by mid-stream reservoirs, for Flood 10 by mid- and down-stream reservoirs, for Floods 6 and 8 by up- and mid-stream reservoirs, and for Flood 5 by all the reser-voirs, which reflects that the midstream reservoirs also play an important role in decreasing peak flow. Mean-while, the role of upstream reservoirs cannot be ignored in peak flow attenuation. The downstream reservoirs may reduce the downstream peak flow effectively at local scale, but have less effect on lower reaches at basin scale, especially for the basin like Ganjiang River Basin with long and narrow shape, where the peak flows were contributed mainly by up- and mid-basin.

The above results demonstrated the recognition that the most effective structural measure at basin scale is restoring storm water in the upper basin and draining storm water in the down basin.

4 Discussion

4.1 Calibration of Xinanjiang model In general, a hydrological model could be used to simu-late or predict hydrological process after calibration and verification. Normally, simulation or predication is per-formed based on calibrated parameters, which can not be allowed to change. But for the purpose of evaluating the functions of reservoirs on flood peak reduction, the sensitive parameters of Xinanjiang model adopted in this study were allowed to change in order to simulate each flood event more precisely. Due to lack of ob-served data, initial state variables of each flood were also adjusted until the estimated flood volume matched the observed flood volume as closely as possible. In order to better catching the features of each flood, the reservoirs′ regulation for the flood was also considered when calibrating model parameters. By such calibration, the floods with better model performance can be used for evaluating the functions of reservoirs.

4.2 Factors affecting reservoirs′ function on flood peak attenuation This study evaluated the impact of both flood storage capacities and locations of the reservoirs under different scenarios. Four scenarios were built, and different floods with varied magnitudes and features were selected and simulated using the Xinanjiang model. The results indi-cated that flood peaks are reduced but to a lesser extent


for extreme hydrological events, which shows a good agreement with the literature (Acreman et al., 2000, López-Moreno et al., 2002, Ayalew et al., 2013). But other result, such as the flood characteristics can alter the function of reservoirs on peak attenuation, showed that the conclusion can not be drawn in a simple way.

In fact, the effect of a reservoir on the flood peak re-duction depends on a number of factors, such as the na-ture of flood, the location of reservoir, the available flood storage capacity, the operation rules of reservoir, spillway configuration, the areal extent of reservoir, the flood endangered locations, the ability and accuracy of flood/storm forecast, and the size of the uncontrolled drainage area (WMO, 2006; Jordan et al., 2012; Ayalew et al., 2013). Therefore, assessing the effect of reservoirs on flood attenuation is complicated and, even more diffi-cult in separating the relative role of each factor.

It should be noted that the present study was carried out based on the simple reservoir operation rules and under the assumption that the reservoirs have full flood storage capacities at the beginning of flood events. The effects of joint operation of multiple reservoirs to pre-vent meeting of flood peaks from main stream and tributaries (Seibert et al., 2014; Zhou et al., 2014), and different initial reservoir storages on peak attenuation were not taken into consideration in the study.

It should also be noted that we just selected 14 large reservoirs in the evaluation for feasibility of calculation. The other small and medium reservoirs (about 3700) were omitted. How to evaluate all reservoirs′ effects on flood attenuation should be considered in future studies.

5 Conclusions

The effects of reservoirs on daily peak flow attenuation were evaluated in Ganjiang River Basin of China. The Xinanjiang model and simple reservoir operation rules were adopted to simulate the inflows and outflows of reservoirs and flood hydrographs of all sub-basins. Dif-ferent scenarios of the reservoirs were built to identify the function of the reservoirs at varied locations for flood control for a varied of flood events with different magnitudes and characteristics. The following conclu-sions are drawn from this study:

Xinanjiang model and the simple reservoir operation rules simulated the runoff processes well for the selected flood events, which could be used for the assessment of

reservoirs′ effects on daily peak attenuation. Reservoirs attenuated the simulated peak discharges at the outlet of the basin for all ten flood events by 1%–15%. Generally, when the flood storage capacities increased as new res-ervoirs were built, the attenuations of peak discharges by reservoirs showed an increasing tendency in both absolute and relative measures. The attenuation extent of reservoirs was dependent not only on the flood mag-nitude but also on the flood characteristics, reservoirs could attenuate more peak discharge for small floods than for large ones, and they could reduce the peak dis-charge more efficiently for the floods with single peak or multiple peaks with main peak occurred first. The effects of reservoirs′ locations on flood peak attenuation were different, the up-, and mid-stream reservoirs play an important role in decreasing peak flow both in mid-dle and lower reaches, the downstream reservoirs have less effect on large peak flow attenuation at the outlet of the basin. The effects of reservoirs on peak attenuation varied in different reaches, the reservoirs attenuated peak discharge decreasingly from upstream to down-stream.

It is worth to mention that the proposed framework of evaluating functions of multiple reservoirs′ storage ca-pacities and the locations of the reservoirs on peak at-tenuation is valuable both for flood control planning and management at basin scale.

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