Improvement of SWAT2000 Modelling to Assess the Impact of Dams and Sluices on Streamflow in the Huai River Basin of China

HYDROLOGICAL PROCESSES Hydrol. Process. 24, 1455–1471 (2010) Published online 17 February 2010 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/hyp.7606

Improvement of SWAT2000 modelling to assess the impact of dams and sluices on streamﬂow in the Huai River basin of China

Gangsheng Wang1,2*andJunXia1 1 Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 2 Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164-6120, USA

Abstract: Hydrological simulation and assessment in a dam–sluice regulated river basin are a complex and challenging issue. In this article, an improved SWAT2000 modelling system was developed that incorporated the Shuffled complex evolution (SCE- UA) optimization algorithm and the multi-site and multi-objective calibration strategy. The implication of multi-objective is different for different types of outlets, i.e. streamflow for an ordinary outlet, inflow for a sluice, and water storage for a reservoir. Model parameters were redefined to improve model simulations. The surface runoff lag time (SURLAG) was extended as a spatially distributed parameter, and a correction coefficient was introduced to modify the saturated hydraulic conductivity. The modelling system was then applied to the Huai River basin of China under various climatic conditions, including a very dry year (1999), a dry year (1981), an average year (1971), and wet year (1991). In all, 26 dams and 35 sluices were considered, among which about 20 dams/sluices were used for model calibration. The impact assessment primarily focused on the very dry year (1999). The results indicated that the released water from large reservoirs was blocked in the river channels by sluices located downstream. In the very dry year, the dam–sluice operations could result in an increase of the runoff volume during the non-flood season and a decrease in runoff during the flood season, but the changing magnitude during the non-flood season was much greater. An important conclusion of this case study is that the sluices in the Sha-Yin branch located in the north region and the dams in the southern mountainous region above the Wangjiaba Hydrological Station have played the most significant role in regulating the streamflow of the entire river basin. The methods addressed in this article can simulate hydrological regime in the river basins regulated by dams and sluices under different climatic conditions at the whole-watershed scale. Copyright  2010 John Wiley & Sons, Ltd.

KEY WORDS dams and sluices; impact assessment; modelling; SCE-UA; SWAT2000 Received 30 March 2009; Accepted 21 December 2009

INTRODUCTION water system characterized by numerous river reaches Dams and sluices are important management means in and reservoirs. A river system controlled by many dams the exploitation and utilization of water resources (Gross and sluices are usually designed and planned to meet and Moglen, 2007; Lopez-Moreno et al., 2009). Today, with the need in flood control and water withdrawal. there are more than 45 000 large dams (more than 15 m These dams/sluices might be planned and constructed high) in the world, with more than half of these are by stages. Moreover, the planning might be conducted in China alone (ICOLD, 1998). Both dams and sluices from the point of view of a local region, and not the serve the objectives of regulating water artificially. There entire river basin. Hydrological modelling at the whole- are also some differences between dams and sluices that watershed scale is necessary and useful for the design- are addressed in this article. A dam and its associated ers/planers/administrators to evaluate the influence of reservoirs are usually constructed in mountainous regions local dams/sluices on water quantity/quality in other parts to form a huge water body with a large water surface, and or the entire watershed. Hence, a dam/sluice-controlled its primary function is to generate electric power besides river basin complicates steps taken to implement hydro- storage and flood control. A sluice, on the other hand, is logical modelling of the system. Regarding this kind of usually located in a river channel within an environment modelling, two important issues are needed to be con- characterized by relatively gentle terrain, and is primarily sidered carefully. One is the model development that used for flood control and water supply. considers the roles of dams and sluices, and the other Due to the influences of dams and sluices, the water is the model calibration and water resources applica- in a river is not a natural water system, but a complex tion. It is obvious that a lumped hydrological model is incapable of expressing the spatially distributed features of dams and sluices. Therefore, a suitable distributed * Correspondence to: Gangsheng Wang, Department of Biological Sys- tems Engineering, Washington State University, Pullman, WA 99164- model coupling dams and sluices represents a better 6120, USA. E-mail: gangsheng [email protected] choice.

The Soil and Water Assessment Tool (SWAT) is a rel- change the value of a given parameter by a fixed percent- atively ideal model to consider for basin scale water age of the initial value (Lenhart et al., 2002; White and resources applications, because of its reservoir mod- Chaubey, 2005), and the other was to vary it by a fixed ule (Neitsch et al., 2002a,c). SWAT has been widely percentage of the valid parameter range (Lenhart et al., used in a variety of investigations, such as hydrological 2002). In both sensitivity analysis approaches, the great- simulations and assessment, non-point pollution, climate est importance was attributed to soil parameters. In other change impact, parameter sensitivity, model calibration studies (Kannan et al., 2007; Wu and Johnston, 2007), and uncertainty analysis, model comparisons, and inter- sensitivity analyses were carried out by using those model faces of SWAT with other models (Borah and Bera, 2004; parameters identified from the instructions for the cal- Arnold and Fohrer, 2005; Gassman et al., 2007). ibration of the SWAT model, as given in the user’s In terms of hydrological simulations and assessment, manual (Neitsch et al., 2002a). A model-independent very few applications focus on influences of dams and non-linear parameter estimator, PEST (Parameter ESTi- sluices, especially the impacts of a large number of dams mation) (Doherty, 2004), has also been used to cali- and sluices. The following studies illustrate various ways brate SWAT, in which PEST implemented a particu- in which the model has been employed to investigate larly robust variant of the Gauss–Marquardt–Levenberg the impact of dams and sluices. Srinivasan et al. (1996) method of parameter estimation (Govender and Everson, applied SWAT to the Texas Gulf Basin, and 18 of the 2005; Wang and Melesse, 2005). Bekele and Nicklow 22 hydrologic unit areas (HUAs) were selected for mod- (2007) developed an automatic routine to calibrate daily elling. Average monthly results from two HUAs (Segiun streamflow and sediment concentration in SWAT using and Naches) were reported in this article, where two the Non-dominated Sorting Genetic Algorithm II (NSGA- reservoirs were considered in the Segiun river basin and II). NSGA-II is capable of incorporating multiple objec- one considered in the Naches river basin. The three reser- tives into the calibration process as well as employing voirs are located in the middle of these two adjacent parameterization to help reduce the number of calibra- HUAs, which are situated in the southeast of the Texas tion parameters. Muleta and Nicklow (2005) adapted a Gulf Basin. The results showed close agreement between Genetic Algorithm (GA) for single-objective evaluations, simulated and observed data, partially due to average and a Strength Pareto Evolutionary Algorithm for multi- monthly measured USGS streamflow data from the three objective optimization. The Shuffled complex evolution reservoir outlets that were used as input to the model. (SCE-UA) algorithm (Duan et al., 1992, 1994) has also Hotchkiss et al. (2000) incorporated complex operational been applied to calibrate SWAT in several cases (van rules into SWAT model, where six main stem dams on Griensven and Bauwens, 2003; Van Liew et al., 2005; the Missouri River were considered. Van Liew et al. Cao et al., 2006). (2003) used SWAT to investigate the impacts of retarding The aforementioned model calibrations were devel- structures on streamflow characteristics in southwestern oped in a progression from single-site to multi-site, and Oklahoma, where 13 flood retarding impoundment structures were represented as uncontrolled reservoirs with from single-objective to multi-objective. However, few of principal and emergency spillways. In a case study of a these calibrations deal with hydrological simulations in a small watershed (17 km2) of India conducted by Mishra dam/sluice regulated river basin. As for this kind of spe- et al. (2007), SWAT was used to assess sediment trans- cific and complicated application, the concept of multi- port characterized by three on-stream sediment control site not only refers to multiple control points, but also structures called check dams. In these modelling studies refers to various types of outlets (hydrological station, involving dams, the reservoir module of SWAT becomes dam, or sluice) with different characteristics and calibra- a sensitive component affecting hydrological processes. tion variables. In addition, the type of an outlet cannot be The reservoir module in SWAT is a water body with changed after the model input files have been generated inflow, outflow, and change in storage. Although it cannot by AVSWAT in the original version of SWAT2000. This be directly used for real-time reservoir operation, it pro- limitation does not meet with the requirement for impact vides sufficient accuracy for water balance analysis and assessment using scenario analysis, where a dam/sluice water resources assessment, especially when the outflow may be switched to an ordinary outlet with continuous data through a dam/sluice are available. flow and vice versa. To best represent field conditions simulated by SWAT, The major objective of this study is to improve it requires accurate estimation of parameters that gov- SWAT2000 in hydrological modelling and assessment for ern hydrological processes in the model. This process a dam–sluice regulated river basin. The main approaches of calibration of SWAT, especially auto-calibrating algo- include modifying the reservoir module, integrating SCE- rithms, including the sensitivity analysis of parameters, UA optimization into SWAT2000, and developing a has been the subject of many hydrological studies (Eck- comprehensive multi-site and multi-objective calibration hardt and Arnold, 2001; Benaman et al., 2005; White and strategy and a scenario analysis tool. The article is Chaubey, 2005; Cao et al., 2006; Bekele and Nicklow, organized as follows: Section on Methodology describes 2007; Kannan et al., 2007). For example, Lenhart et al. the above-mentioned approaches. The following section (2002) conducted a sensitivity analysis in SWAT whereby introduces the study area, data collection, and site-specific two approaches were considered as equivalent: one was to model setup procedure. Then the results and discussion

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1457 on a case study in the Huai River basin of China are presented.

METHODOLOGY Modification of reservoir module in SWAT In this study, the source code as written in the FOR- TRAN language for SWAT2000 (Neitsch et al., 2002a,c) was directly used with some modification. SWAT models four types of water bodies: ponds, wetlands, depres- sions/potholes, and reservoirs. In this study, considerable attention was given to the reservoir module in the model, because a large number of dams and sluices were located in the study area, where the model was employed. The outflow from a dam or sluice in SWAT may be calculated

using one of the following four methods (Neitsch et al., or moisture condition II Surface Runoff nsation factor Evapotranspiration 2002c): (1) average annual release rate for uncontrolled Definition Impact ation factor Evapotranspiration reservoir, (2) measured monthly outflow, (3) controlled t of saturated hydraulic conductivity Soil water outflow with target release, and (4) measured daily out-

flow. ’ value for main channel Flow routing To satisfy the objective of the study, the option (1) of n the reservoir component is modified to ‘uncontrolled reservoir’ in the following way. When the method ‘uncontrolled reservoir’ is assigned to a dam or sluice, it means the streamflow is completely uncontrolled, i.e. the outflow equals the inflow at the outlet. This modification changes the function of option (1). In the original option (1) of SWAT, a constant discharge (i.e. file Subroutine average annual water release rate) is used. However, Hydroinit.f Surface runoff lag time (days) Flow routing

in the modified option (1), a ‘uncontrolled reservoir’ is b equivalent to a natural river channel without dam/sluice. Such a modification is especially useful during scenario .rte.rte Readrte.f Readrte.f Manning’s ‘ Effective hydraulic conductivity (mm/h) Baseflow .sol res.f Available water capacity of the soil layer Soil water .gw Readgw.f Baseflow alpha factor (days) Baseflow .hru.hru Readhru.f Readhru.f Soil evaporation compe Plant uptake compens file .mgt Readmgt.f Initial SCS curve number f Ł Ł Ł Ł Ł Ł Ł analysis where an outlet with dam/sluice is switched to SWAT an ordinary river outlet with continuous flow. Otherwise, it is difficult to realize such a switch once the model has 3 been setup by placing a dam/sluice on the outlet of a Ð

sub-basin in AVSWAT2000. Upper bound Integration of SCE-UA algorithm into SWAT 5 101 Subsurlag.lag 500 .sol Readsol.f Correction coefﬁcien Ð Ð Table I. Parameters and related SWAT ﬁles for model calibration bound

To determine the model parameter values, the SCE-UA Lower global optimization algorithm (Duan et al., 1992) is used. 26 0 1 94 0 150 200 0 1 490 0 1 86 40 98 050 0 1 0 0 50 Subsurlag.lag — Correction coefﬁcient of water use Water use 060 0 0 36 0 00 Ð Ð Ð Ð Ð Ð Ð Ð Generally, SCE-UA is a kind of stochastic optimizing Ð Ð 5 1 value strategy developed from the GA (Zou et al., 2009). The Initial most important features for SCE-UA is the combination of competitive evolution and complex shufﬂing, which enhance the survival ability of offspring in the population a a (Duan et al., 1992; Wang et al., 2009). The original BF 0 N2K2 0 135

source code of SCE-UA was also written in FORTRAN, for Type 1/2 1 name a which makes it easy to be embedded into the source Variable code of SWAT2000. Herein, the method is to edit the subroutines (Table I) including the value assignment of CWUS the calibrated parameters. For example, the value of the well-known parameter CN2 (initial SCS curve number for moisture condition II) can be assigned in the subroutine file ‘readmgt.f’ of SWAT2000. in coding Selected and redefined parameters for calibration On the basis of the parameter sensitivity analysis ‘Subsurlag.lag’ is a data file created by the author. Redefined variables added into SWAT for model calibration. 9 par(9) bKsat 2 par(2) ESCO 0 8 par(8) bAWC for Type 0 0 5 par(5) CH 7 par(7) Surlag 6 par(6) CH No. Parameter name 1 par(1) CN2a b 56 3 par(3) EPCO 0 by the aforementioned studies, the instructions for the 4 par(4) Alpha

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) 1458 G. WANG AND J. XIA calibration of the SWAT2000 model (Neitsch et al., regulated river basin, a multi-site and multi-objective 2002a), and various trials undertaken in this case study, calibration strategy is proposed herein. The ‘multi-site’ nine parameters are employed for model calibration. means that the calibration is conducted at many sites, The first six parameters are selected from the original and usually begins from the most upperstream. For each SWAT2000 model, and the other three parameters are calibration, the outlet of such a site is either an ordinary redefined in this study. outlet or a sluice/dam, and includes all of upstream of The six original parameters include the following. that site. The term ‘multi-objective’ refers to two items: (1) Initial SCS curve number for moisture condition II (1) different objectives are used for different types of (CN2), which has an impact on surface runoff; (2) soil outlets, i.e. streamflow for an ordinary outlet, inflow for a evaporation compensation factor (ESCO), accounting sluice and water storage for a dam (reservoir); and (2) for for evapotranspiration (ET); (3) plant uptake compen- each type of outlet, at least two objectives are considered sation factor (EPCO), accounting for ET; (4) baseflow in the calibration. alpha factor (Alpha BF, days), related to baseflow; For this study, the following three formulas were used (5) Manning’s ‘n’ value for main channel (CH N2), here: related to flow routing; and (6) effective hydraulic conductivity (CH K2, mm/h), related to baseflow. The redefined three parameters are related to the Runoff coefficient : RC D R/P 1 spatially distributed flow routing and the sensitive soil Ratio of simulated water volume to observed parameters (Lenhart et al., 2002). They are described as follows. (1) Surface runoff lag time (SURLAG), accounts water volume: RSO D VOLsim/VOLobs 2 for flow routing. SURLAG controls the fraction of the Nash–Sutcliffe efficiency criterion (NSEC) : NSEC total available water allowed to enter the reach on any 2 one day. For a given time of concentration, this fraction [Qobs i Qsim i] D 1 3 increases as SURLAG increases. The original ‘SURLAG’ 2 [Qobs i Qobs] is a spatial-invariant parameter, i.e. a constant for the whole-watershed read from the data file ‘basins.bsn’, and used in the coding file ‘hydroinit.f’. However, SURLAG where R and P are simulated total runoff and observed should be a spatial distribution parameter especially in a precipitation expressed as a depth (mm), respectively; large watershed. Therefore, SURLAG is calibrated for VOLsim and VOLobs are simulated and observed water a set of sub-basins in this research. A new data file volume (m3, e.g. runoff volume, sluice inflow volume, or ‘subsurlag.lag’ is created to store the calibrated spatially reservoir storage at a specific time), respectively; Qobsi distributed SURLAG values, and then this data file is and Qsimi are observed and simulated data at time i, used in the later model runs. (2) available water capacity respectively; and Qobs is the average of the observed (AWC) of the soil layer (bAWC) is assigned for Type data series [e.g. streamflow discharge or sluice inflow 0 (ordinary outlet) and correction coefficient of water discharge (m3 s1) or reservoir storage (m3)]. use (CWUS) for Type 1/Type 2 (sluice/dam). When it The overall objective function (OBF) is the combina- is an ordinary outlet, the same AWC for all the soil tion of these three objectives: layers is calibrated. When it is an outlet controlled by a sluice/dam, CWUS is calibrated, and the water use OBF D w Ð NSEC C w Ð RSO C 1 w w Ð RC is multiplied by CWUS. (3) A correction coefficient of 1 2 1 2 4 saturated hydraulic conductivity (bKsat) is also a new where, w and w are weighting factors, 0 w C w variable added into SWAT2000 for model calibration. The 1 2 1 2 1. absolute value of saturated hydraulic conductivity (Ksat) RC is used for those sites without observed data except for each layer was multiplied by bKsat, but the relative runoff coefficient. For those sites with observed data, value of Ksat for each layer remained unchanged. good fits of Nash–Sutcliffe efficiency criterion (NSEC) These nine parameters described above have a domi- (White and Chaubey, 2005; Wang et al., 2009) and RSO nant influence on hydrological processes, such as surface also mean good fits of RC; thus we set w C w D 1. The runoff, baseflow, soil water, ET, flow routing, and water 1 2 types of outlets and their corresponding data requirements use in the Huai River basin. In particular, a change in and objectives are shown in Table II. the SURLAG from a constant to a spatially distributed Besides NSEC and RSO, the correlation coefficient parameter represents a significant improvement in model (CC) was also selected as a performance criterion to simulations for a very large river basin, such as the Huai River basin. evaluate model calibration. CC is also used to assess model performances, but it is not included in OBF, because NSEC has been involved in OBF to measure the Calibration strategy and objective function fitness between the simulated and observed data series. Model calibration is usually conducted by comparing CC is the measure of correlation degree between the simulated data with available observed data. Due to observed and simulated data series. The closer the three the complexity and characteristics of the dam–sluice assessment criteria are to 1Ð0, the better the goodness of

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1459

Table II. Type of outlets and objectives for model calibration

Type ID Type of outlet Data requirement Objectives

RSO NSEC

0 Ordinary outlet Observed discharge The ratio of simulated runoff Calculated using simulated volume to observed runoff and observed streamflow volume processes 1 Sluice Observed outflow, water The ratio of simulated inflow Calculated using simulated level, water volume to observed inflow and observed inflow level–storage curve volume processes 2 Dam Observed outflow, water The ratio of simulated storage Calculated using simulated level, water to observed storage at the end and observed storage level–storage curve of simulation period processes

RSO, ratio of simulated to observed water volume; NSEC, Nash–Sutcliffe efﬁciency criterion.

fit is. Table III. Scenarios for the impact assessment at the Bengbu Sluice [Q i Ð Q i] obs sim 1 Scenario Relevant dams and sluices [ Qobs i][ Qsim i] CC D n 5 S0 (DSa) All the dams and sluices above the Bengbu 2 1 2 [Qobs i] [ Qobs i] Ð Sluice n S1 (NDSb) Dams in southern mountainous region above 2 1 2 [Qsim i] n[ Qsim i] Wangjiaba S2 (NDS) Dams in southern mountainous region between When the outlet is controlled by a sluice, the calibrat- Wangjiaba and Bengbu ing data is the inflow into the river channel before the S3 (NDS) Dams and sluices in Hong-Ru River S4 (NDS) Dams in Sha-Yin River sluice, and the inflow rate can be derived from a water S5 (NDS) Sluices in Sha-Yin River balance as: S6 (NDS) Dams in southern mountainous region (S1 C S2) S7 (NDS) Dams and sluices above Wangjiaba (S1 C S3) Qin i D Qout i C [Si C 1 Si]/t C Qu i 6 S8 (NDS) Dams and sluices in Hong-Ru River, and dams in southern mountainous region (S1 C S2 C where Qini and Qouti are calculated inflow rate and S3) the observed outflow rate, respectively (m3 s1); Si and S9 (NDS) Dams and sluices in Sha-Yin River (S4 C S5) S10 (NDS) Dams and sluices above Lutaizi (S8CS9) Si C 1) are the water storage at the beginning and at the 3 end of the time interval (t)(m); and Qui represents a DS represents the scenario with dams and sluices. the water use rate during t (m3 s1). The water storages b NDS represents the scenario without dams and sluices. can be calculated from the water stage–storage curve and the observed water stages. all the dams/sluices above an outlet on the discharge Impact assessment of dam–sluice on streamflow processes at this outlet. The second step is to assess Basic scenarios. The procedure to assess the impact of the impact of a group of dams/sluices on the discharge dams/sluices on streamflow is to compare the streamflow processes at the outlet (the Bengbu Sluice) of the under two basic scenarios: the scenario with actual study area. In order to assess the impacts of various dam–sluice operations (DS) and the scenario without combinations of dams/sluices on the streamflow at the dam–sluice operations (NDS). DS refers to the scenario Bengbu Sluice, 11 scenarios (Table III) were designed wherein one single dam/sluice or all the dams and sluices to investigate the changes in the inflow of the Bengbu in a sub-watershed are operated as the actual conditions Sluice. All the scenarios belong to the NDS scenario during the study periods. NDS refers to switch from except scenario S0, which is a DS scenario with all one single dam/sluice or a group of dams/sluices to an the dams and sluices above the Bengbu Sluice. These ‘uncontrolled reservoir’. NDS can include various sets of scenarios were selected based on the category of the dams and sluices. For instance, along the river, all the outlets (i.e. dam or sluice) and the major branches of dams operating with all the sluices completely opened the river system (southern mountainous region, Hong- (i.e. outflow equals inflow) is one NDS scenario. All the Ru River, Sha-Yin River, and the Lutaizi Hydrological sluices working with all the dams completely opened is Station in the mainstream). Thus, the scenarios S6–S10 another NDS scenario. were the combination of the first five scenarios (S1–S5): Two steps are carried out to quantitatively assess NDS of dams in the southern mountainous region above the impacts of dams and sluices on streamflow under the Wangjiaba Station (S1), NDS of dams in the southern various climatic conditions, especially under relatively mountainous region between the Wangjiaba Station and dry conditions. The first step involves the impact of the Bengbu Sluice (S2), NDS of dams and sluices in the

Table IV. Statistic criteria for the impacts of dam–sluice on the executable files for SWAT calibration and SWAT streamflow simulation; (4) readily transferring three main SWAT No. Meaning of criterion Criterion Unit output files (basins.bsb, basins.rch, and basins.rsv) from text format to a database; (5) querying and graphing 1 Annual runoff volume RVY 108 m3 simulation results, and generating resultant statistics; and 2 Runoff volume during RVF 108 m3 (6) conducting scenario analysis: readily switching an flood season outlet between two states (DS and NDS). 3 Runoff volume during RVNF1 108 m3 non-flood season Ia 4 Runoff volume during RVNF2 108 m3 non-flood season IIb STUDY AREA, DATA COLLECTION, AND MODEL 5 Flood peak discharge QP m3/s SETUP 6 Flood peak time QPT mm-dd Study area 7 Mean annual QAV m3/s discharge The Huai River basin (30°550 –36°360N, 111°550 – 8 Standard deviation of QSD m3/s 121°250E) is located between the Yangtze River basin discharge and the Yellow River basin of China (Figure 1). It is 9 Coefficient of QCV — variation of one of the seven major rivers in China, and known for discharge its 11 000 dams and sluices (Ning, 2003). It drains an area of 270 000 km2. The upstream region of the Huai a Non-flood season I: the non-flood months before the flood season, e.g. River refers to that area above the river mouth of the January–May. 2 b Non-flood season II: the non-flood months after the flood season, e.g. Hong River, with an area of 30 000 km and a slope of October–December. 0Ð2‰; the area between the river mouth of the Hong River and the outlet of the Hongze Lake belongs to the Hong-Ru River (S3), NDS of dams in the Sha-Yin River middle stream region, with an area of 130 000 km2 and (S4), and NDS of sluices in the Sha-Yin River (S5). a gentle slope of 0Ð03‰(HRC, 2004). The major tributaries within the middle stream region lead to complexi- Statistic criteria and impact assessment index. The ties in flooding water routing, which in turn accentuates statistic criteria of the streamflow involve annual runoff the importance of watershed management in the middle volume (RVY), runoff volume during the flood season stream reach. Due to serious flood disasters and flood (RVF), runoff volume during the antecedent non-flood control requirement in the Huai River, around 11 000 months and the months following the flood season dams and sluices were built by the year 2000. Construc- (represented by RVNF1 and RVNF2, respectively), flood tion of hydraulic structures has brought tremendous eco- peak discharge and its occurring time (designated as QP nomic benefits for flooding control, irrigation, and power and QPT), mean annual discharge (QAV), and coefficient generation in the basin. However, major contradicting of variation of discharge (QCV) (Table IV). Although arguments have been raised for many years regarding QAV corresponds to RVY, both of them are employed to the benefits of building dams and sluices, and their detri- present intuitive quantitative descriptions of one physical mental impacts on the environment. quantity in two different units. The flood season varies In this article, the study area is limited to the not only between different river basins, but also between upper–middle stream region of the Huai River basin sub-basins within a river basin. However, the dominant above the Hongze Lake, herein still referred to as the flood season will be adopted for this study in a river Huai River basin (Figure 1). The river basin, with an basin. Furthermore, the non-flood season is divided into area of 13Ð79 ð 104 km2, includes the mainstream, the two periods, i.e. the antecedent non-flood months and the large reservoirs (dams) in the southern mountainous months following the flood season. region, and four major tributaries in the northern region: The impact assessment index (i.e. the influencing Sha-Yin River, Hong-Ru River, Guo River, and Hui degrees of NDS compared with DS) is calculated by the River (Figures 1 and 2). The most important outlet is the quantity of NDS/DS, i.e. the ratio of the statistic criterion Bengbu Sluice (32°5703400N, 117°1701700E) in the main- of NDS to that of DS, except for the statistic criterion stream, with a drainage area of 12Ð13 ð 104 km2,which QPT, where, NDS/DS D QPTNDS QPTDS. is regarded as the outlet of the study area.

Development of integrated modelling system Data collection In order to manage numerous input data files, outputs, The data requirement for SWAT modelling primarily and model analysis for SWAT calibrated by SCE-UA, an includes: the Digital Elevation Model (DEM), the digital integrated modelling system and interface is developed river network, the land use and soil data, the information using CCC. The functions of the integrated system for dams and sluices, and the hydrometeorological data include: (1) managing, identifying, and editing numerous (precipitation, pan evaporation, water level, and stream- data files generated from AVSWAT2000, with most of the flow). DEM data (raster resolution: 90 m ð 90 m) and files being grouped by sub-basins; (2) initializing SWAT land use data (scale D 1:106) were collected from model calibration of SWAT by SCE-UA; (3) running Institute of Geographic Sciences and Natural Resources

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1461

Figure 1. Locations of major dams and sluices in the Huai River basin above the Hongze Lake

Research (IGSNRR) of Chinese Academy of Sciences 4 sluices, and 6 ordinary outlets; and (4) 17 outlets for the (CAS). Soil data (scale D 1:4ð 106) was obtained from wet year (1991), with 10 sluices and 7 ordinary outlets. the Institute of Soil Science (ISS) of CAS. The digital The special category named fabric dam is also classified river network data (scale D 1:2Ð5 ð 105), the informa- as sluice in this study, because fabric dams are located tion for dams and sluices, and the hydrometeorological across the river channel with lower height like sluices. data were obtained from the Huaihe River Commission For those dams/sluices without daily data, the method (HRC, China). of ‘measured monthly outflow’ or ‘controlled outflow Four representative years selected from a 45-year with target release’ (Neitsch et al., 2002c) was adopted period of record (1956–2000) were used for model to simulate their outflow. simulation: a very dry year (1999), a dry year (1981), Model setup an average year (1971), and a wet year (1991), with annual precipitation of 676, 744, 924, and 1095 mm, Because most of the study area is located in the plain respectively. region with gentle slope, the digital river network was employed to delineate the Huai River basin. Otherwise, The flood season varies in different regions of the Huai the river network generated by AVSWAT2000 using only River basin. For example, it is from May to August in the the DEM would stray from the actual field conditions. southern mountainous region, and June–September for Due to the unavailability of detailed temperature data, the other regions. As most of the study area and control observed pan evaporation data were directly used as the sections are located in the north and the mainstream, the model input. The land use data were reclassified into period from June to September is defined as the flood six types: forest, grassland, water body, residential land, season. Correspondingly, the non-flood season I refers paddy land, and dry land, which were represented by the to January–May and the non-flood season II refers to code FRST, RNGE, WATR, URHD, RICE, and AGRR October–December. in AVSWAT, respectively. Finally, the study area was Because detailed reservoir operation rules are difficult delineated into 212 sub-basins, with the elevation ranging to simulate for so many dams/sluices, daily measured from 12 to 2092 m. The relationship between sub-basins streamflow data from the outlets of reservoirs or sluices and dams/sluices is shown in Figure 2, where 26 dams were used as an input to the model. Based on data and 35 sluices were depicted in the study. availability, measured daily data required in Table II for An ideal hydrological calibration set would include about 20 dams/sluices and ordinary outlets were used combined climatic conditions (Wu and Johnston, 2007). for model calibration (Table V): (1) 26 outlets for the Among the four representative years, 3 years (very dry, very dry year (1999), including 14 dams, 5 sluices, and dry, and average year) were calibrated independently; 7 ordinary outlets; (2) 20 outlets for the dry year (1981), and the wet year (1991) was used as verification by including 7 dams, 7 sluices, and 6 ordinary outlets; (3) 17 using the same parameters as the very dry year (1999). outlets for the average year (1971), consisting of 7 dams, Not only were the discharge processes at a number

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) 1462 G. WANG AND J. XIA Figure 2. Relationship between sub-basins and dams/sluices in the SWAT model

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1463

Table V. Dams, sluices, and ordinary outlets for calibration and veriﬁcation (marked by ×)

Category Dam/sluice Sub-basin Dam or 1971 1981 1999 1991 ID sluice ID (17) (20) (26) (17)

Dams in southern mountainous region Nanwan Reservoir 190 55 × above Wangjiaba Shishankou Reservoir 191 56 × Wuyue Reservoir 192 57 × Pohe Reservoir 184 49 × Dams in southern mountainous region Nianyushan Reservoir 193 58 × betweenWangjiaba and Bengbu Meishan Reservoir 173 39 ××× Xianghongdian Reservoir 194 59 ××× Fuziling Reservoir 212 61 ××× Dams in Hong-Ru River Banqiao Reservoir 140 9 × Shimantan Reservoir 186 51 ×× Sluices in Hong-Ru River Ruhe Fabric Dam 141 10 × Bantai Sluice 139 8 × Yangzhuang Sluice 136 5 × Dams in Sha-Yin River Gushitan Reservoir 148 16 ×× Zhaopingtai Reservoir 144 13 ××× Baiguishan Reservoir 155 21 ××× Baisha Reservoir 158 24 ××× Sluices in Sha-Yin River Dachen Sluice 147 15 × Shahe-Zhoukou Sluice 166 32 × Shahe Fabric Dam 156 22 × Mawan Sluice 154 20 ×× Huaidian Sluice 168 34 ×× Fuyang Sluice 169 35 ×××× Sluices in Guo River Guoyang Sluice 180 45 ×× Mengcheng Sluice 181 46 ××× Sluice in mainstream Bengbu Sluice 135 4 ×××× Sluice in Hui River Guzhen Sluice 183 48 ×× × Ordinary outlets Dapoling 129 ×××× Changtaiguan 123 ×× Xixian 204 ×××× Huaibin 203 ×××× Wangjiaba 205 ×××× Lutaizi 200 ×××× Hengpaitou 198 ×××× of hydrological stations (ordinary outlets) along the than 0Ð70, respectively. Moreover, 36% of the values mainstream evaluated, but also many dams/sluices were for NSEC are even greater than 0Ð80 in the 3 years. used for model calibration. For the 3-year calibration period, about 84% of the values for CC are greater than 0Ð70, and 65% of them are greater than 0Ð80. Meanwhile, the calibration RESULTS AND DISCUSSION performances for dams (reservoirs) and ordinary outlets Because the dam/sluice impacts are much more substan- are much better than that of the sluices. Because the tial during a drought year, particular attention was given reservoirs are usually located in the mountainous region, to assessing the hydrological regime in the very dry year the influencing factors (e.g. inflow and water use) are (1999). not as complicated as those of the sluices. Therefore, the total runoff volume is the primary criterion for the Model calibration simulation of the sluices. The NSECs of the Fuziling The performance results of SWAT model calibration Reservoir are negative in both 1999 and 1971, which by SCE-UA are shown in Table VI. For such a large is mainly caused by the utilization of monthly data as river regulated by many dams/sluices, it is virtually the outflow variable from the Mozitan Reservoir located impossible to achieve good performances at all outlets. upstream (Figure 1). Comparisons between observed and However, performance results in Table VI imply that simulated hydrographs for the Banqiao Reservoir, the the calibrations of the model are satisfactory at most Nanwan Reservoir, the Lutaizi Hydrological Station, and of the outlets. There are 76, 80, and 69% of the the Benbu Sluice are shown in Figure 3. values for RSO between 0Ð95 and 1Ð05 for the years The calibrated parameter values for the year 1999 1971, 1981, and 1999, respectively. For these same are shown in Table VII. It is noted that calibration years, 47, 40, and 54% of values for NSEC are greater of these parameter values was applied to the outlet

Table VI. Performance results of model calibration Dam/sluice 1971 1981 1999

CC NSEC RSO CC NSEC RSO CC NSEC RSO

Nanwan Reservoir 1Ð00 1Ð00 1Ð06 Shishankou Reservoir 1Ð00 0Ð99 1Ð01 Wuyue Reservoir 0Ð99 1Ð00 1Ð00 Pohe Reservoir 0Ð95 0Ð80 1Ð02 Nianyushan Reservoir 0Ð93 0Ð80 1Ð33 Meishan Reservoir 0Ð85 0Ð72 0Ð99 0Ð99 0Ð95 1Ð10 0Ð72 0Ð45 1Ð04 Xianghongdian Reservoir 0Ð96 0Ð93 1Ð00 1Ð00 0Ð99 1Ð00 0Ð85 0Ð71 1Ð03 Fuziling Reservoir 0Ð47 1Ð63 0Ð84 0Ð82 0Ð59 0Ð96 0Ð08 5Ð04 0Ð95 Banqiao Reservoir 0Ð95 0Ð89 1Ð04 Shimantan Reservoir 0Ð95 0Ð88 1Ð01 0Ð88 0Ð53 1Ð01 Gushitan Reservoir 0Ð72 0Ð03 1Ð03 0Ð49 0Ð19 1Ð03 Zhaopingtai Reservoir 0Ð96 0Ð92 0Ð98 0Ð94 0Ð89 0Ð99 0Ð96 0Ð91 1Ð00 Baiguishan Reservoir 0Ð95 0Ð90 1Ð00 0Ð96 0Ð92 1Ð31 0Ð82 0Ð08 1Ð04 Baisha Reservoir 0Ð93 0Ð33 1Ð01 0Ð96 0Ð92 1Ð31 0Ð99 0Ð91 0Ð93 Mawan Sluice 0Ð96 0Ð91 1Ð00 0Ð79 0Ð62 1Ð02 Huaidian Sluice 0Ð43 0Ð06 1Ð02 0Ð60 0Ð06 1Ð10 Fuyang Sluice 0Ð77 0Ð51 1Ð05 0Ð73 0Ð46 1Ð00 0Ð63 0Ð32 1Ð01 Guoyang Sluice 0Ð77 0Ð56 1Ð07 0Ð43 0Ð18 1Ð00 Mengcheng Sluice 0Ð83 0Ð69 0Ð97 0Ð95 0Ð91 1Ð01 Bengbu Sluice 0Ð93 0Ð85 0Ð97 0Ð74 0Ð54 1Ð02 0Ð84 0Ð71 0Ð99 Guzhen Sluice 0Ð71 0Ð50 0Ð98 0Ð21 1Ð89 1Ð01 Dapoling 0Ð60 0Ð22 1Ð43 0Ð90 0Ð79 0Ð96 0Ð90 0Ð71 0Ð99 Changtaiguan 0Ð80 0Ð14 1Ð38 Xixian 0Ð84 0Ð70 1Ð02 0Ð85 0Ð66 0Ð68 0Ð73 0Ð42 1Ð00 Huaibin 0Ð82 0Ð61 1Ð14 0Ð69 0Ð37 0Ð96 0Ð79 0Ð32 1Ð04 Wangjiaba 0Ð84 0Ð69 1Ð05 0Ð82 0Ð67 1Ð01 0Ð83 0Ð51 1Ð02 Lutaizi 0Ð91 0Ð82 1Ð04 0Ð78 0Ð61 0Ð99 0Ð89 0Ð77 1Ð11 Hengpaitou 0Ð71 0Ð42 0Ð97 0Ð96 0Ð91 1Ð00 0Ð96 0Ð91 0Ð86

CC, correlation coefﬁcient; NSEC, Nash–Sutcliffe efﬁciency criterion; RSO, ratio of simulated to observed water volume.

(a) Banqiao Reservoir (1999) 16000 14000 ] 3 m

12000 4 10000 8000 Observed storage 6000 Simulated storage 4000 Water storage [10 2000 0 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd) (b) Nanwan Reservoir (1999) 70000

] 60000 3 m

4 50000

40000

30000 Observed storage

20000 Simulated storage

Water storage [10 10000

0 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd) Figure 3. Comparison between observed and simulated hydrographs in 1999. (a) Banqiao Reservoir, (b) Nanwan Reservoir, (c) Lutaizi Hydrological Station, and (d) Bengbu Sluice

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1465

50 2000 Precipitation 100 ]

1 Observed streamflow − s

3 1500 Simulated streamflow 150 200

1000 250 Precipitation [mm] Discharge [m 300 500 350

0 400 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd)

(d) Bengbu Sluice (1999) 2500 0

Precipitation 50 2000 Observed inflow

] 100 1 − Simulated inflow s 3 1500 150 200

1000 250 Precipitation [mm] Discharge [m 300 500 350

0 400 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd) Figure 3. (Continued)

Table VII. Calibrated parameter values for the year of 1999

Outlet CN2 ESCO EPCO Alpha BF CH N2 CH K2 Surlag AWC CWUS Ksat

Nanwan Reservoir 61Ð60Ð65 1Ð00 0Ð97 0Ð16 129Ð01Ð80Ð13 2Ð027Ð8 Shishankou Reservoir 55Ð10Ð80 0Ð60 0Ð83 0Ð23 57Ð69Ð40Ð13 12Ð7 318Ð6 Wuyue Reservoir 88Ð40Ð49 0Ð20 0Ð65 0Ð04 47Ð15Ð50Ð13 16Ð0 214Ð9 Pohe Reservoir 61Ð70Ð99 0Ð90 0Ð45 0Ð26 100Ð65Ð00Ð13 2Ð8 211Ð3 Nianyushan Reservoir 96Ð20Ð80 0Ð28 0Ð58 0Ð19 125Ð44Ð60Ð13 0Ð44Ð8 Meishan Reservoir 87Ð10Ð30 0Ð79 0Ð47 0Ð06 119Ð89Ð10Ð13 1Ð6 308Ð1 Xianghongdian Reservoir 56Ð90Ð20 0Ð05 0Ð49 0Ð06 135Ð95Ð40Ð13 0Ð34Ð8 Fuziling Reservoir 98Ð00Ð93 0Ð57 0Ð20 0Ð30 53Ð74Ð20Ð13 0Ð14Ð8 Banqiao Reservoir 76Ð00Ð42 0Ð40 0Ð78 0Ð01 79Ð41Ð50Ð13 4Ð64Ð8 Shimantan Reservoir 42Ð90Ð01 0Ð06 0Ð01 0Ð14 119Ð01Ð00Ð13 1Ð6 488Ð8 Gushitan Reservoir 47Ð80Ð39 0Ð30 0Ð76 0Ð20 119Ð33Ð10Ð13 2Ð4 436Ð1 Zhaopingtai Reservoir 92Ð10Ð14 0Ð95 0Ð58 0Ð15 90Ð46Ð70Ð13 1Ð04Ð8 Baiguishan Reservoir 94Ð10Ð37 0Ð61 0Ð04 0Ð12 60Ð05Ð50Ð13 5Ð4 375Ð8 Baisha Reservoir 61Ð60Ð36 0Ð96 0Ð75 0Ð07 84Ð95Ð30Ð13 1Ð03Ð1 Mawan Sluice 79Ð30Ð84 0Ð57 0Ð94 0Ð02 143Ð45Ð70Ð13 1Ð2 465Ð3 Huaidian Sluice 49Ð10Ð71 0Ð40 0Ð76 0Ð01 77Ð08Ð70Ð32 15Ð0 185Ð4 Fuyang Sluice 49Ð10Ð71 0Ð40 0Ð76 0Ð01 77Ð08Ð70Ð32 8Ð4 185Ð4 Mengcheng Sluice 49Ð10Ð71 0Ð40 0Ð76 0Ð01 77Ð08Ð70Ð32 36Ð0 185Ð4 Bengbu Sluice 87Ð10Ð71 0Ð36 0Ð79 0Ð01 68Ð40Ð50Ð13 11Ð0 324Ð7 Dapoling 70Ð10Ð27 0Ð91 0Ð21 0Ð01 48Ð24Ð90Ð10 1Ð0 314Ð5 Changtaiguan 76Ð50Ð89 0Ð60 0Ð58 0Ð01 10Ð43Ð00Ð45 1Ð0 373Ð6 Xixian 96Ð50Ð44 0Ð52 0Ð05 0Ð02 37Ð92Ð60Ð66 9Ð2 278Ð9 Huaibin 95Ð40Ð34 0Ð31 0Ð81 0Ð01 122Ð64Ð00Ð78 11Ð0 466Ð7 Wangjiaba 94Ð10Ð42 0Ð72 0Ð29 0Ð01 83Ð78Ð30Ð41 1Ð02Ð0 Lutaizi 86Ð10Ð26 0Ð32 0Ð01 0Ð25 0Ð02Ð90Ð46 10Ð02Ð0 Hengpaitou 81Ð90Ð36 0Ð70 0Ð43 0Ð01 0Ð03Ð80Ð36 1Ð0 342Ð8

(a) Banqiao Reservoir (1999, QAVNDS/QAVDS = 0.49) 160 0 140 10 20 ]

1 120 −

s Precipitation 30 3 100 Streamflow-DS 40 80 Streamflow-NDS 50 60 60 70 Discharge [m 40 Precipitation [mm] 80 20 90 0 100 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd)

(b) Nanwan Reservoir (1999, QAVNDS/QAVDS = 0.07) 70 0 10 60 20 ] 1

− 50 s Precipitation 30 3 40 Streamflow-DS 40 Streamflow-NDS 50 30 60 70

Discharge [m 20 Precipitation [mm] 80 10 90 0 100 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd) Figure 4. Comparison between the DS and NDS scenario above an outlet in 1999. (a) Banqiao Reservoir, (b) Nanwan Reservoir, (c) Lutaizi Hydrological Station, and (d) Bengbu Sluice; see Table VIII for the meanings of DS, NDS, and QAVNDS/QAVDS sub-basin as well as those upstream sub-basins of that point. The NDS scenario refers that all the dams and outlet. For example, for the Bengbu Sluice outlet, all sluices above this outlet are set to that scenario. Taking the sub-basins between the Lutaizi Hydrological Station the Banqiao Reservoir, the Nanwan Reservoir, the Lutaizi (Sub-basin 200) and the Bengbu Sluice (Sub-basin 135) Hydrologic Station, and the Bengbu Sluice in the very along the mainstream were included in the calibration dry year (1999) as examples, the comparisons of the (Figure 2). The default value for the parameter SURLAG discharge process between two scenarios (NDS vs DS) is 4Ð0inSWAT(Neitschet al., 2002b). After multi-site can be seen in Figure 4. calibration, the spatially distributed SURLAG parameter values ranged from 0Ð5to9Ð4 with an average of 4Ð7. Banqiao Reservoir. The Banqiao Reservoir is located Moreover, 56% of the total number of sub-basins (212) in the source area of the Hong-Ru River (Figure 1). has a SURLAG between 2 and 4, 20% between 4 and 6, The reservoir was built in 1951, and the dam had and 16% between 8 and 9Ð4. been collapsed in 1975 by the devastating summer The hydrological processes of the wet year 1991 flooding. The reconstruction of this dam with a height were also simulated using the calibrated parameters of of 50Ð5 m was completed in 1993. Since then, the the very dry year 1999, where the dams and sluices Banqiao Reservoir, with a drainage area of 768 km2,has were assumed to be totally opened during the flood a maximum volume of 0Ð675 ð 109 m3 and surface water season of this flooding year. The NSECs of the major area of 75Ð4 ð 106 m2. The impact assessment above the hydrological stations (Dapoling, Changtaiguan, Xixian, Banqiao Reservoir means that this reservoir is regarded as Huaibin, and Wangjiaba) are 0Ð71, 0Ð65, 0Ð61, 0Ð63, and NDS. The ratio of mean annual discharge of NDS to that 0Ð66, respectively; and the RSOs are 1Ð04, 1Ð00, 1Ð00, of DS (QAVNDS/QAVDS)is0Ð49, which means that the 0Ð98, and 1Ð00, respectively. outflow of DS at the outlet of the dam was increased by the water storage in the previous years. Such a conclusion Impact assessment regarding all dams/sluices above an can be verified by the water storage process given outlet in Figure 3a, where the water storage in the reservoir The calibrated model at the very dry year (1999) was decreased from 1Ð51 ð 108 m3 to 0Ð93 ð 108 m3 during used to investigate the impact of all the dams/sluices the year, and the released water was used to compensate above an outlet on the discharge processes at that outlet water shortage during the very dry year. Figure 4a also

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1467

3 1500 Streamflow-DS 40 Streamflow-NDS 50 1000 60 70 Discharge [m

500 80 Precipitation [mm] 90 0 100 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd)

(d) Bengbu Sluice (1999, QAVNDS / QAVDS= 1.13) 2500 0 50 2000 Precipitation

] 100 1

− Streamflow-DS s

3 1500 Streamflow-NDS 150 200 1000 250 Precipitation [mm]

Discharge [m 300 500 350 0 400 01-01 02-01 03-01 04-01 05-01 06-01 07-01 08-01 09-01 10-01 11-01 12-01 Date (mm-dd)

Figure 4. (Continued) indicates that the dam greatly reduces the discharge of the operation of this dam also produced much higher the flood peaks. discharge of the flood peaks in this very dry year. The simulated water storage presented a consistent In fact, most of the large reservoirs released more water trend, i.e. under predicting for the period of 1 January to than was generated as runoff (QAVNDS/QAVDS D 0Ð07 13 May, over predicting for 14 May to 8 July, and then 0Ð96), except for the Shimantan Reservoir (QAVNDS/ under predicting for 9 July to 3 September, and over QAVDS D 2Ð32) in the Hong-Ru River and the Gushi- predicting for 3 September to 31 December. The three tan Reservoir (QAVNDS/QAVDS D 1Ð40) in the Sha-Yin transition points (i.e. 14 May, 9 July, and 3 September) River. Water release from the reservoirs in the south- corresponded to the big rainstorm events (Figure 4a) in ern mountainous region above the Wangjiaba Hydrologic that year. When the measured discharge data from the Station was the most significant during the year, with reservoir outlet were used as input to the model, the over QAVNDS/QAVDS ratios of 0Ð07, 0Ð08, 0Ð15, and 0Ð65, predicting or under predicting of recharging water from respectively. upper reaches of Banqiao Reservoir resulted in a sudden increase or decrease in reservoir water storage. Lutaizi Hydrological Station. The Lutaizi Hydrological Station monitors streamflow from the southern moun- Nanwan Reservoir. The Nanwan Reservoir is situated tainous region, the Hong-Ru River, and the Sha-Yin in the southern mountainous region above the Wangjiaba River over a drainage area of 88 630 km2 (Figure 2). The Hydrological Station (Figure 1). The reservoir became NDS scenario above the Lutaizi Station signifies that all operational in 1955. It has a maximum volume of the reservoirs and sluices above it become completely 1Ð63 ð 109 m3 and surface water area of 130Ð8 ð 106 m2. uncontrolled. These reservoirs and sluices include the This dam controls a drainage area of 1100 km2.The large reservoirs in the southern mountainous region and ratio of mean annual discharge of NDS to that of DS the dams/sluices in the Hong-Ru River and the Sha-Yin (QAVNDS/QAVDS) is only 0Ð07, which means the outflow River. Figure 4c shows that the mean annual discharge of DS at the outlet of the dam was greatly increased by the of NDS is greater than that of DS (QAVNDS/QAVDS D water storage in the reservoir. This is consistent with the 1Ð25). This means, although the large reservoirs in the fact that water storage was reduced from 0Ð6 ð 109 m3 source head regions could release more water under the (1 January 1999) to 0Ð25 ð 109 m3 (31 December 1999) DS scenario than under the NDS scenario, the released during the year (Figure 3b). Figure 4b suggests that water from large reservoirs was eventually blocked and

(a) Bengbu Sluice (1999) 100 1.80 DS NDS ] 3 75 1.40 m NDS/DS 8

50 1.00 NDS/DS

25 0.60 Runoff Volume [10

0 0.20 RVY RVF RVNF1 RVNF2

(b) Bengbu Sluice 16000 1.80 DS 14000 NDS ]

-1 12000 1.40 s NDS/DS 3 10000

8000 1.00

6000 NDS/DS

4000 0.60 Peak discharge[m 2000

0 0.20 1971 1981 1999 1991 Figure 5. Impact assessment of the Bengbu Sluice: (a) runoff volume in 1999, and (b) peak discharge for different years. RVY, annual runoff volume; RVF, runoff volume during ﬂood season; RVNF1 and RVNF2, runoff volume during non-ﬂood season I and II; see Table VIII for the meanings of DS, NDS, and NDS/DS

Table VIII. Assessment of the impacts of dam–sluice on streamﬂow at the Bengbu Sluice

ID Criteriona 1971 1981 1999

DSb NDSc NDS/DSd DS NDS NDS/DS DS NDS NDS/DS

1 RVY 251Ð95 271Ð58 1Ð08 124Ð46 151Ð06 1Ð21 64Ð56 72Ð95 1Ð13 2 RVF 163Ð27 176Ð35 1Ð08 55Ð85 55Ð78 1Ð00 35Ð74 32Ð96 0Ð92 3 RVNF1 32Ð53 32Ð09 0Ð99 26Ð01 27Ð60 1Ð06 5Ð11 8Ð12 1Ð59 4 RVNF2 56Ð14 63Ð14 1Ð12 42Ð60 67Ð68 1Ð59 23Ð71 31Ð87 1Ð34 5 QP 3949Ð77 3712Ð78 0Ð94 1391Ð78 1690Ð10 1Ð21 2058Ð11 1537Ð32 0Ð75 6 QPT 06–16e 06-18 2 07-15 07-15 0 07-04 07-04 0 7 QAV 798Ð92 861Ð18 1Ð08 394Ð65 479Ð01 1Ð21 204Ð70 231Ð33 1Ð13 8 QSD 813Ð74 902Ð34 1Ð11 332Ð93 441Ð13 1Ð32 309Ð39 295Ð60 0Ð96 9QCV1Ð02 1Ð05 1Ð03 0Ð84 0Ð92 1Ð09 1Ð51 1Ð28 0Ð85 a See Table IV for the meaning of each criterion. b DS represents the scenario with dams and sluices. c NDS means the scenario without dams and sluices. d For the criterion QPT, NDS/DS D QPTNDS QPTDS; for the other criteria, NDS/DS D QPTNDS/QPTDS. e ‘06–16’ has the format of ‘MM-DD’. stored in the sluice-controlled river channels for water become completely uncontrolled. The assessment results use. In other words, under NDS conditions, the stream- are shown in Figures 4d and 5, and Table VIII. The flow passing the Lutaizi Station increases because of hydrological processes during the four representative no-interception by the upperstream sluices. years were assessed for the Bengbu Sluice. (1) In the very dry year (1999), compared with the DS statistic Bengbu Sluice. The Bengbu Sluice lies downstream criterion, the annual runoff volume (RVY) of the NDS of the Lutaizi Hydrological Station as well as the Guo will increase by 13%, while the runoff volume during River (Figure 2). The NDS scenario above the Bengbu the flood season (RVF) will decrease by 8%. The runoff Sluice means that all the reservoirs and sluices above it volumes during the non-flood season I and II (RVNF1

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1469

(a) Bengbu Sluice (1999, annual runoff volume) 80 1.6 ] Runoff Volume 3

m NDS/DS

8 60 1.3

40 1.0 NDS / DS 20 0.7 Runoff Volume [10 0 0.4 S0 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Scenario

(b) Bengbu Sluice (1999, flood season) 48 1.6

] Runoff Volume 3

m NDS/DS

8 36 1.3

24 1.0 NDS / DS 12 0.7 Runoff Volume [10 0 0.4 S0 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Scenario

Figure 6. Inflow runoff volume under different scenarios at the Bengbu Sluice in 1999. (a) annual runoff volume, (b) flood season, (c) non-flood season I, and (d) non-flood season II; NDS/DS equals to the ratio of runoff volume under each scenario to runoff volume under S0; see Table III for the definitions of all scenarios and RVNF2) will increase by 59 and 34%, respectively; and the dams in the southern mountainous region above the flood peak discharge (QP) will reduce by 25% with Wangjiaba Station contributed significantly to streamflow the flood peak time (QPT) unchanged and the CV of regulation in the very dry year (1999): the operation of discharge (QCV) will become smaller. (2) In the dry year the dams increased the inflow into the Bengbu Sluice; (1981), compared with DS, the increment of the RVY on the contrary, the operation of the sluices reduced the of the NDS will reach 21%; RVNF1 and RVNF2 will inflow into the Bengbu Sluice. increase by 6 and 59%, respectively. However, RVF will Figure 6 also shows the impacts of dam–sluice on be almost invariant and QP will increase by 21%. (3) In streamflow are more significant during the flood season the average year (1971), compared with DS, the RVY of and the non-flood season I. Four scenarios (S2, S6, S8, the NDS will increase by 8% with RVF adding 8% and and S10) will lead to an increase in runoff during the non- RVNF2 gaining 12%, whereas QP will decrease by 6%. flood season I. These four scenarios will also result in (4) In the wet year (1991), compared with DS, the RVY both less runoff volume and lower peak discharge during of the NDS almost remains unchanged, while RVF will the flood season. Therefore, under actual conditions (i.e. diminish by 16%, and RVNF1 and RVNF2 will increase the DS scenario), the reservoirs in the southern moun- by 44 and 39%, respectively. QP will increase by 59% tainous region between Wangjiaba Station and Bengbu with QPT advanced by 13 days and the CV of discharge Sluice stored water during the non-flood season to later (QCV) will become greater. meet the large water demand in the summer. Impact assessment of a group of dams/sluices The histograms in Figure 6 are generated from the runoff volume during four periods: the whole year, SUMMARY AND CONCLUSION the flood season (June–September), the non-flood season I (January–May), and the non-flood season II Hydrological simulation and assessment in a dam–sluice (October–December). The lines in Figure 6 refer to the regulated river basin is complex and challenging for normalized data of runoff volume under each scenario as hydrological practitioners. In this article, an improved referenced to the S0 runoff volume, where NDS/DS for version of the SWAT2000 model was developed to deal S0 always equals 1Ð0. with this type of problem. The main characteristics of this Six scenarios (S3, S5, S7, S8, S9, and S10), especially model are summarized as follows. (1) The first option in S5 and S9 (where RVY increases by about 13%), will the reservoir module of SWAT was modified to ‘uncon- result in greater annual runoff volume (RVY) than that trolled reservoir’, which describes the condition wherein of S0; whereas two scenarios (S1 and S6) can lead to less the outflow equals the inflow at the outlet. Such a RVY by about 3%. Both the sluices in the Sha-Yin River modification facilitates impact assessment using scenario

] Runoff Volume 3 m

NDS/DS 8 9 1.3

6 1.0 NDS / DS 3 0.7 Runoff Volume[10 0 0.4 S0 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Scenario

(d) Bengbu Sluice (1999, non-flood season II) 40 1.6

] Runoff Volume 3

m NDS/DS

8 30 1.3

20 1.0 NDS / DS 10 0.7 Runoff Volume[10 0 0.4 S0 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Scenario

Figure 6. (Continued) analysis. (2) The optimizing algorithm SCE-UA was inte- indicates the relative importance of dams/sluices located grated into SWAT2000 for model calibration. Considering in different regions. The sluices in the Sha-Yin River and the spatial distribution and the different characteristics the dams (reservoirs) in the southern mountainous region of dams and sluices, a multi-site and multi-objective above the Wangjiaba Station contributed significantly to calibration strategy was proposed in this study. (3) Six streamflow regulation in the very dry year (1999). parameters from the original SWAT model and three rede- From the point of view of the whole river basin, if fined parameters were calibrated. These nine adjustable there were no dams, streamflow could only originate from parameters are related to various processes including sur- precipitation without extra water supplied by the water face runoff, baseflow, soil water, ET, flow routing, and storage in the reservoirs. If there were no sluices in the water use. (4) The impact assessment method based on river channels, the water would directly flow downstream, the improved SWAT2000 modelling was employed for which could result in flood risk during flooding years water resources investigation. The basic scenarios con- as well as less water available for water use during sist of two categories: the scenario with dams and sluices drought years. For a local river channel, the existence (DS), and the scenario without dams and sluices (NDS). of a sluice increases the water in the upperstream river NDS refers to switching one single dam/sluice or a group channel as well as decreases the water downstream. Thus, of dams/sluices into an ‘uncontrolled reservoir’. a large number of sluices have been built along the Major conclusions of this study include the following. river to meet various water use need within respective (1) For the average and dry years in the Huai River basin, reaches of the river. Therefore, the integrated operation most of the large reservoirs released more water than that of dams and sluices should be undertaken carefully to was generated as runoff (QAVNDS/QAVDS D 0Ð07 0Ð96 ensure beneficial management of water resources within during 1999). However, the released water from large the basin. reservoirs was blocked and stored in the river channels controlled by sluices. Under NDS conditions with all the upperstream dams and sluices, the streamflow passing ACKNOWLEDGEMENTS the Bengbu Sluice increased by 13% in 1999. In the very dry year, the DS could result in an increase of the The research was supported by the Natural Science runoff volume during the non-flood season and a decrease Foundation of China (No. 40721140020), the National in runoff during the flood season, but the changing Key Water Project for the Huai River (No.2009ZX07210- magnitude during the non-flood season was greater than 006), and the Special Fund of Chinese Academy of that during the flood season. (2) For the wet year Sciences (CAS) for the Winner of the CAS President’s (1991), the DS greatly reduced the flood peak discharge Award. The authors wish to thank Dr Shulin Chen for (QPDS/QPNDS D 0Ð63), and delayed the time to peak by his constructive comments. The authors also thank the 13 days. (3) The comparison study on multiple scenarios unselfish helps on model debugging from Dr Aizhong Ye,

Copyright  2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 1455–1471 (2010) SWAT MODELLING IN WATERSHED WITH DAM/SLUICE 1471

Dr Zhonggen Wang, PhD student Lu Li, Dr Yongyong Kannan N, White SM, Worrall F, Whelan MJ. 2007. Sensitivity analysis Zhang, Dr Changsheng Zhao, and Dr Yan Jiang. We and identification of the best evapotranspiration and runoff options for hydrological modelling in SWAT-2000. Journal of Hydrology greatly thank the data support from Mr Hong Shen, Mr 332(3–4): 456–466. Yanzhai Zhang, and the other staff in the Huaihe River Lenhart T, Eckhardt K, Fohrer N, Frede HG. 2002. Comparison of two different approaches of sensitivity analysis. Physics and Chemistry of Commission of China. The authors are also grateful for the Earth 27(9–10): 645–654. the valuable review comments and suggestions from the Lopez-Moreno JI, Vicente-Serrano SM, Begueria S, Garcia-Ruiz JM, two anonymous reviewers. Portela MM. 2009. Dam effects on droughts magnitude and duration in a transboundary basin: the Lower River Tagus, Spain and Portugal. Water Resources Research 45: W02405. Mishra A, Froebrich J, Gassman PW. 2007. Evaluation of the SWAT REFERENCES model for assessing sediment control structures in a small watershed in India. Transactions of the ASABE 50(2): 469–477. Arnold JG, Fohrer N. 2005. SWAT2000: current capabilities and research Muleta MK, Nicklow JW. 2005. Decision support for watershed opportunities in applied watershed modelling. Hydrological Processes management using evolutionary algorithms. Journal of Water 19(3): 563–572. Resources Planning and Management-ASCE 131(1): 35–44. Bekele EG, Nicklow JW. 2007. Multi-objective automatic calibration of Neitsch SL, Arnold JG, Kiniry JR, Srinivasan R, Williams JR. 2002a. SWAT using NSGA-II. Journal of Hydrology 341: 165–176. Soil and water assessment tool user’s manual. Version 2000 . Texas Benaman J, Shoemaker CA, Haith DA. 2005. Calibration and validation Water Resources Institute: College Station; 412 p. of soil and water assessment tool on an agricultural watershed in upstate Neitsch SL, Arnold JG, Kiniry JR, Williams JR, King KW. 2002b. Soil New York. Journal of Hydrologic Engineering 10(5): 363–374. and water assessment tool theoretical documentation. Version 2000 . Borah DK, Bera M. 2004. Watershed-scale hydrologic and nonpoint- Texas Water Resources Institute: College Station; 458 p. source pollution models: review of applications. Transactions of the Neitsch SL, Arnold JG, Kiniry JR, Williams JR, King KW. 2002c. Soil ASAE 47(3): 789–803. and water assessment tool theoretical documentation. Version 2000 . Cao WZ, Bowden WB, Davie T, Fenemor A. 2006. Multi-variable and Texas Water Resources Institute: College Station; 458 p. multi-site calibration and validation of SWAT in a large mountainous Ning Y. 2003. Water resources handbook of the Huai River basin (in catchment with high spatial variability. Hydrological Processes 20(5): Chinese). Science Press: Beijing. 1057–1073. Srinivasan R, Arnold J, Rosenthal W, Muttiah RS. 1996. Hydrological Doherty J. 2004. PEST: model-independent parameter estimation user modeling of Texas gulf Basin using GIS. In GIS and environmental manual, 5th edn. Brisbane: Australia. modeling: progress and research issues, Goodchild MF, Steyaert LT, Duan QY, Sorooshian S, Gupta V. 1992. Effective and efficient global Parks BO, Johnston C, Maidment D, Crane M, Glendinning S (eds). optimization for conceptual rainfall-runoff models. Water Resources GIS World Book: Fort Collins; 213–217. Research 28(4): 1015–1031. Van Liew MW, Arnold JG, Bosch DD. 2005. Problems and potential of Duan QY, Sorooshian S, Gupta VK. 1994. Optimal use of the SCE-UA autocalibrating a hydrologic model. Transactions of the ASABE 48(3): global optimization method for calibrating watershed models. Journal 1025–1040. of Hydrology 158(3–4): 265–284. Van Liew MW, Garbrecht JD, Arnold JG. 2003. Simulation of the Eckhardt K, Arnold JG. 2001. Automatic calibration of a distributed impacts of flood retarding structures on streamflow for a watershed catchment model. Journal of Hydrology 251(1–2): 103–109. in southwestern Oklahoma under dry, average, and wet climatic Gassman PW, Reyes MR, Green CH, Arnold JG. 2007. The soil and conditions. Journal of Soil and Water Conservation 58(6): 340–348. water assessment tool: historical development, applications, and future Wang X, Melesse AM. 2005. Evaluation of the swat model’s snowmelt research directions. Transactions of the ASABE 50(4): 1211–1250. hydrology in a northwestern Minnesota watershed. Transactions of the Govender M, Everson CS. 2005. Modelling streamflow from two small ASABE 48(4): 1359–1376. South African experimental catchments using the SWAT model. Wang G, Xia J, Chen J. 2009. Quantification of effects of climate Hydrological Processes 19(3): 683–692. variations and human activities on runoff by a monthly water balance van Griensven A, Bauwens W. 2003. Multiobjective autocalibration model: a case study of the Chaobai River basin in northern China. for semidistributed water quality models. Water Resources Research Water Resources Research 45: W00A11. 39(12): 1348–1357. White KL, Chaubey I. 2005. Sensitivity analysis, calibration, and Gross EJ, Moglen GE. 2007. Estimating the hydrological influence of validations for a multisite and multivariable SWAT model. Journal Maryland state dams using GIS and the HEC-1 model. Journal of of the American Water Resources Association 41(5): 1077–1089. Hydrologic Engineering 12: 690–693. Wu KS, Johnston CA. 2007. Hydrologic response to climatic variability Hotchkiss RH, Jorgensen SF, Stone MC, Fontaine TA. 2000. Regulated in a Great Lakes Watershed: a case study with the SWAT model. river modeling for climate change impact assessment: The Missouri Journal of Hydrology 337(1–2): 187–199. River. Journal of the American Water Resources Association 36(2): Zou R, Lung W-S, Wu J. 2009. Multiple-pattern parameter identification 375–386. and uncertainty analysis approach for water quality modeling. HRC. 2004. Water resources assessment of the Huai River basin and Ecological Modelling 220(5): 621–629. Shandong Peninsula (in Chinese). Huaihe River Commission of China: Bengbu; 200 p. ICOLD. 1998. World register of dams 1998 . International Commission on Large Dams: Paris.