DSpace at VNU: Impact of climate and land-use changes on hydrological processes and sediment yield-a case study of the Be River catchment, Vietnam

DSpace at VNU: Impact of climate and land-use changes on hydrological processes and sediment yield-a case study of the B...

This article was downloaded by: [NUS National University of Singapore] On: 03 June 2014, At: 22:40 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Hydrological Sciences Journal Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/thsj20 Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment, Vietnam a Dao Nguyen Khoi & Tadashi Suetsugi b a Faculty of Environmental Science, University of Science, Vietnam National University, Ho Chi Minh City, Vietnam b Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Kofu, Yamanashi 400-8511, Japan Accepted author version posted online: 04 Jul 2013.Published online: 29 Apr 2014 To cite this article: Dao Nguyen Khoi & Tadashi Suetsugi (2014) Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment, Vietnam, Hydrological Sciences Journal, 59:5, 1095-1108, DOI: 10.1080/02626667.2013.819433 To link to this article: http://dx.doi.org/10.1080/02626667.2013.819433 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content This article may be used for research, teaching, and private study purposes Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions Hydrological Sciences Journal – Journal des Sciences Hydrologiques, 59 (5) 2014 http://dx.doi.org/10.1080/02626667.2013.819433 1095 Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment, Vietnam Dao Nguyen Khoi1 and Tadashi Suetsugi2 Faculty of Environmental Science, University of Science, Vietnam National University, Ho Chi Minh City, Vietnam dnkhoi86@gmail.com Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Kofu, Yamanashi 400-8511, Japan Received June 2012; accepted May 2013; open for discussion until November 2014 Editor Z.W Kundzewicz; Associate editor Q Zhang Citation Khoi, D.N and Suetsugi, T., 2014 Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment, Vietnam Hydrological Sciences Journal, 59 (5), 1095–1108 Abstract The impact of climate and land-use changes on hydrological processes and sediment yield is investigated in the Be River catchment, Vietnam, using the Soil and Water Assessment Tool (SWAT) hydrological model The sensitivity analysis, model calibration and validation indicated that the SWAT model could reasonably simulate the hydrology and sediment yield in the catchment From this, the responses of the hydrology and sediment to climate change and land-use changes were considered The results indicate that deforestation had increased the annual flow (by 1.2%) and sediment load (by 11.3%), and that climate change had also significantly increased the annual streamflow (by 26.3%) and sediment load (by 31.7%) Under the impact of coupled climate and land-use changes, the annual streamflow and sediment load increased by 28.0% and 46.4%, respectively In general, during the 1978–2000 period, climate change influenced the hydrological processes in the Be River catchment more strongly than the land-use change Key words climate change; hydrology; land-use change; sediment yield; SWAT model; Be River catchment, Vietnam Impact des changements climatiques et de l’utilisation des terres sur les processus hydrologiques et la production de sédiments—étude de cas du bassin versant de la rivière Be, Vietnam Résumé L’impact des changements du climat et de l’utilisation des terres sur les processus hydrologiques et l’apport de sédiments dans le bassin versant de la rivière Be (Vietnam) a été étudié en utilisant le modèle hydrologique SWAT L’analyse de sensibilité, l’étalonnage et la validation des modèles indique que le modèle SWAT peut raisonnablement simuler l’hydrologie et la charge sédimentaire dans le bassin versant C’est donc avec cet outil que les réponses de l’hydrologie et des sédiments au changement climatique et au changement d’utilisation des terres ont été étudiées Les résultats indiquent que la déforestation a augmenté l’écoulement annuel (1,2%) et la charge sédimentaire (11,3%), et que le changement climatique a également augmenté de manière significative le débit annuel (26,3%) et la charge sédimentaire (31,7%) Sous l’impact couplé du changement climatique et du changement d’utilisation des terres, l’écoulement annuel et la charge de sédiments ont respectivement augmenté de 28% et 46,4% En général, le changement climatique a eu une influence plus importante sur les processus hydrologiques que le changement d’utilisation des terres dans le bassin versant de la rivière Be durant la période 1978–2000 Mots clefs changement climatique ; hydrologie ; changement d’utilisation des terres ; production de sédiments ; modèle SWAT ; bassin versant de la rivière Be, Vietnam INTRODUCTION The principal influences on hydrological processes and soil erosion include not only climate change but also land-use/land-cover change Climate change is likely to affect the hydrological cycle with changes in temperature and precipitation, and this may lead to changes in © 2014 IAHS Press water availability, as well as the transformation and transport characteristics of pollutants (Tu 2009) Changes in land use as a result of deforestation, agricultural expansion and urbanization have altered surface runoff generation, and have then affected the hydrological processes and the transport of pollutants Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 1096 Dao Nguyen Khoi and Tadashi Suetsugi As a result, climate and land use are identified as key factors controlling the hydrological and sediment behaviours of catchments (Elfert and Bormann 2010) It is important to understand the hydrological and sediment responses to these changes in order to develop strategies for land-use planning and water resource management Studies of the hydrological and water quality impacts of climate change and land-use change are desirable (Tong et al 2012) Many studies have considered the impact of climate change and land-use change on hydrology (Li et al 2009, 2012, Ma et al 2009, 2010, Mango et al 2011, Zhang et al 2011) However, few studies have investigated changes in hydrological processes and water quality as well as sediment yield under the impact of climate and land-use changes on a basin scale (Ward et al 2009, Tong et al 2012) To assess the hydrological and sediment impacts of environmental change, the common methods used are the paired catchment approach, statistical analysis and hydrological modelling (Li et al 2009, 2012) Among these approaches, the hydrological method is an appealing option, because it is most suitable to be used as a part of scenario studies There are numerous hydrological models, such as the Water Erosion Prediction Project (WEPP), Hydrologic Simulation Program Fortran (HSPF), the Soil and Water Assessment Tool (SWAT) and the physically-based distributed hydrological model Système Hydrologique Européen TRANsport (SHETRAN), that could be used in simulating the runoff and transport of sediment and pollutants in the catchment The SWAT model has been selected for the current study because it is widely used to assess hydrology and water quality in agricultural catchments around the world (see the SWAT literature database: https://www.card.iastate.edu/swat_articles/) Another reason for its selection is its availability and user-friendliness in terms of handling input data (Arnold et al 1998) Vietnam has experienced climate changes, including rising air temperature and more variable precipitation (MONRE 2009) In addition, rapid agricultural and industrial development, as well as population growth have occurred in recent decades (Trinh 2007) These changes have affected soil erosion and the availability of water resources in Vietnam However, no studies have investigated the effects of climate change and human activities on hydrological cycles and sediment yield in Vietnam Moreover, Wang et al (2012) emphasized that the local impacts of climate change and human activities on hydrology and sediment yield vary from place to place and need to be investigated on a regional scale The overall objective of this study was to quantify the impacts of past land-use change and climate change on hydrological processes and sediment yield in a case study of a catchment in Vietnam The specific objectives were: (a) to calibrate and validate the SWAT model in terms of streamflow and sediment load in the Be River catchment; (b) to evaluate the separate impacts of climate and land-use changes on hydrology and sediment yield; and (c) to assess the impacts of combined climate change and land-use change on hydrological processes and sediment yield The results achieved through this study provide decision-makers with a comprehensive understanding of the interactions among hydrological processes, landuse change and climate change, which are required to assist with water resource planning efforts and sustainable development STUDY AREA The catchment selected for study lies in the Dong Nai River basin in south Vietnam between latitudes 11°10′– 12°16′N and longitudes 106°36′–107°30′E (Fig 1) It is located in Dak Nong, Binh Phuoc, Binh Duong and Dong Nai provinces, and has a catchment area of about 7500 km2 The altitude varies from 1000 m a.m s.l in the highland area to 100 m a.m.s.l in the plain area, in a northeast to southwest and south direction The origin of the branched-tree drainage system of the Be River lies in Tuy Duc on the international border between Vietnam and Cambodia, in Dak Nong province The study area is located in the steep area The degree of slope can be divided into three levels: slopes of 0% to 7% account for 45% of the total area, slopes of 8–15% account for 33% of the area, and slopes greater than 15% account for 22% of the area The climate is tropical monsoon The annual rainfall varies between 1800 and 2800 mm, with an average of 2400 mm year-1 The area has two seasons: the rainy season and the dry season The rainy season lasts from May to November and accounts for 85–90% of the total annual precipitation The average temperature is about 25.9°C, the maximum temperature is 36.6°C and the minimum temperature is 17.3°C The area has relatively fertile land (75% basalt soil), consistent with agricultural development The main land-use types in this catchment are forest and agricultural lands The total population in 2010 was approximately one million inhabitants The mean annual flow of the catchment is about 7.51 × 109 m3 Similar to the distribution of rainfall, the flow is distinguished by two distinct seasons: the flood season (accounting for 67% of the total annual 1097 Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Impact of climate and land-use changes on hydrological processes Fig Location map of the Be River catchment flow) and the low-flow season (accounting for 33% of the total annual flow) The Be River catchment has been assessed as having the most abundant water resources in the Dong Nai River basin and significant hydropower potential < ỵ1 xj À xi > 0 xj À xi ¼ sgn xj À xi ¼ : À1 xj À xi < nn 1ị2n ỵ 5ị varSị ẳ METHODOLOGY The Mann-Kendall test (Mann 1945, Kendall 1975) is a non-parametric test for identifying trends in hydro-meteorological time series The MannKendall test statistic is calculated as follows: S >0 S¼0 S < varS ị Zc ẳ > : pSỵ1 ffiffiffiffiffiffiffiffiffi m P (3) where n is the length of the data set, xi and xj are the sequential data values, m is the number of tied groups (a tied group is a set of sample data with the same value), and t is the number of data points in the mth group The null hypothesis H0 (there is no trend) is accepted if –Z1–α/2 ≤ Zc ≤ Z1–α/2, where α is the significant level A positive value of Zc indicates an increasing trend, and a negative value indicates a decreasing trend In the Mann-Kendall test, the Kendall slope is another very useful index that estimates the magnitude of the monotonic trend and is given by:   xj À xi "i < j β ¼ Median jÀi (5) 1098 Dao Nguyen Khoi and Tadashi Suetsugi where < i < j < n The estimator β is calculated as the median of all slopes between data pairs for the entire data set The Pettitt test (Pettitt 1979) is a non-parametric approach used for detecting the change point There are two samples (x1, x2, …, xt) and (xt+1, xt+2, …, xN) that come from the same population (x1, x2, …, xN) The test statistic Ut,N is given by: Ut;N ¼ t X N X À Á sgn xi À xj (6) Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 iẳ1 jẳtỵ1 6K p ẳ exp t N ỵN 0:56 sed ẳ 11:8  Qsurf  qpeak  areaHRU  KUSLE  CUSLE  PUSLE  LSUSLE The null hypothesis of the Pettitt test is the absence of a change point Its statistic Kt and associated probabilities are given as:   (7) Kt ¼ maxUt;N   method (Monteith 1965), the Priestley-Taylor method (Priestley and Taylor 1972) and the Hargreaves method (Hargreaves et al 1985) Channel routing is simulated using the variable storage coefficient method (William 1969) and the Muskingum method (Chow 1959) The SWAT model uses the Modified Universal Soil Loss Equation (MUSLE) to simulate the sediment yield for each HRU The MUSLE (William 1995) is given as:  (8) When p is smaller than the specific significance level, the null hypothesis is not accepted The time t when Kt occurs is the change point time These methods have been commonly used to detect changes in hydro-meteorological data (Ma et al 2008, Zhang et al 2009, Zhang et al 2011) 3.2 SWAT model The SWAT model is a physically based, distributed, continuous time model that is designed to predict the effects of land management on the hydrology, sediment and agricultural chemical yields in agricultural watersheds with varying soils, land-use and management conditions (Arnold et al 1998) In the SWAT model, a catchment is divided into a number of sub-watersheds or sub-basins Sub-basins are further partitioned into hydrological response units (HRUs) based on soil types, land-use and slope classes that allow a high level of spatial detail simulation The model predicts the hydrology at each HRU using the water balance equation, comprising precipitation, surface runoff, evapotranspiration, infiltration and subsurface flow The SWAT model provides two methods for estimating surface runoff: the SCS curve number procedure (USDA-SCS 1972) and the Green and Ampt infiltration method (Green and Ampt 1911) SWAT calculates the peak runoff rate using a modified rational method The potential evapotranspiration is estimated in the SWAT model using three methods: the Penman-Monteith (9)  CFRG where sed is the sediment yield on a given day (t), Qsurf is the surface runoff volume (mm ha-1), qpeak is the peak runoff rate (m3 s-1), areaHRU is the area of the HRU (ha), KUSLE is the USLE soil erodibility factor, CUSLE is the USLE cover and management factor, PUSLE is the USLE support practice factor, LSUSLE is the USLE topographic factor and CFRG is the coarse fragment factor The channel sediment-routing model consists of deposition and degradation, which operate simultaneously In the channel, deposition or degradation can occur, depending on the sediment loads from upland areas and the transport capacity of the channel network If the sediment entering a channel is larger than its sediment transport capacity, channel deposition will occur Otherwise, channel degradation will be the dominant process Further details of hydrological and sediment transport processes can be found in the SWAT Theoretical Documentation (Neitsch et al 2011) 3.3 SWAT model set-up The input data required for the SWAT model include weather data, a land-use map, a soil map and a digital elevation map (DEM), as listed in Table The land-use data were generated from Landsat satellite images— Landsat Thematic Mapper (TM) image in 1990 and Landsat Enhanced Thematic Mapper Plus (ETM +) image in 2001—obtained from the US Geological Survey Earth Resources Observation and Science Center Land-use maps were generated using supervised classification based on the maximum likelihood algorithm in the ENVI Version 4.4 image processing software Overall accuracy and kappa statistic (κ) were used to assess classification accuracy based on 256 ground control points selected from the referenced land-use map Impact of climate and land-use changes on hydrological processes 1099 Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Table Spatial model input data for the Be River catchment Data type Description Resolution Source Topographic map Land-use map Soil map Weather Digital elevation map (DEM) Land-use classification Soil types Daily precipitation, minimum and maximum temperature 90 m km 10 km stations for 2001, which was obtained from the Southern Institute for Water Resources Planning (SIWRP 2002) Land-use types were classified into the following categories: forest, rangeland, agricultural land, urban area and water Daily river flow data measured at Phuoc Long (1981–1993) and Phuoc Hoa (1981–2000) gauging stations (Fig 1) were used for the model calibration and validation of flow simulation Monthly sediment load data measured at Phuoc Hoa station (07/1999–2004) were used for the calibration and validation of sediment simulation Streamflow and sediment load data were provided by the Hydro-Meteorological Data Center of Vietnam The model set-up consists of five steps: (a) data preparation, (b) sub-basin discretization, (c) HRU definition, (d) parameter sensitivity analysis, and (e) calibration and validation Sensitivity analysis was carried out to identify the most sensitive parameters for the model calibration using Latin hypercube and one-factor-at-a-time (LH-OAT), an automatic sensitivity analysis tool implemented in SWAT (Van Griensven et al 2006) Those sensitive parameters were calibrated using the auto-calibration tool that is currently available in the SWAT interface (Van Liew et al 2005) 3.4 Performance evaluation of the SWAT model The model performance was evaluated using statistical analysis to compare the quality and reliability of the simulated discharge with the observed data In this study, the model evaluation methods used included: the Nash-Sutcliffe (1970) efficiency criterion, NSE; per cent bias, PBIAS; and the ratio of the root mean square error (RMSE) to the standard deviation (STDEV) of measured data, RSR The RSR is calculated as (Moriasi et al 2007): sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi N P Oi Pi ị2 RSR ẳ iẳ1 RMSE ẳ s STDEVobs N P  ị2 Oi O iẳ1 (10) SRTM Landsat TM, ETM+ (USGS/GLOVIS) FAO Hydro-Meteorological Data Center (HMDC) where Oi is the observed value Pi is the simulated  is the mean of the observed data, and N is value, O the total number of observations According to Moriasi et al (2007) and Rossi et al (2008), model simulation can be judged as satisfactory if NSE > 0.5, RSR ≤ 0.70 and PBIAS = ±25% for streamflow simulation, and NSE > 0.5, RSR ≤ 0.70 and PBIAS = ±55% for sediment simulation RESULTS AND DISCUSSION 4.1 Land-use changes Based on the Landsat images, land-use maps were generated for 1990 and 2001, as illustrated in Fig An accuracy assessment of land-cover classification, obtained by computing the confusion matrix in ENVI 4.4 software, showed an overall accuracy value of 98.2% for 1990 and 98.1% for 2001 The κ coefficients for 1990 and 2001 were 0.96 and 0.97, respectively The dominant land-use types in the Be River catchment were agricultural land and forest (Table 2), which accounted, respectively, for 40.28% and 50.69% in 1990 and 55.18% and 36.62% in 2001 Range land, urban and water covered about 8.89%, 0.03% and 0.11%, respectively, of the total catchment area for 1990, and 6.85%, 0.13% and 1.22%, respectively, of the total area for 2001 In general, there were two main trends of land-use change: a decrease in the forest (deforestation) and an increase in agricultural land (agricultural expansion) Compared with 1990, the forest decreased by 14.07% and cropland increased by 14.89% of the catchment area Aside from this, there were slight changes in the range land (–2.03%), water (1.11%), and urban area (0.11%) These changes were likely caused by a population increase, which led to the expansion of settlements and agricultural land, and ineffective forest management that led to excessive forest exploitation (SIWRP 2002, 2008) The population of the Be River catchment was about 680 000 in 2000 compared to 400 000 in 1990 (SIWRP 2002) This represents a population increase of about 170% Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 1100 Dao Nguyen Khoi and Tadashi Suetsugi Fig Land-use maps of the Be River catchment Table Statistics for land-use changes in the Be River catchment for the period of 1978–2007 Land-use types Agricultural land Range land Forest Urban Water Total 1990 2001 2 (km ) (%) (km ) (%) (km2) (%) 3015 665 3794 7484 40.28 8.89 50.69 0.03 0.11 100 5129 513 2741 10 91 7484 55.18 6.85 36.62 0.13 1.22 100 1114 –152 –1053 83 14.89 –2.03 –14.07 0.11 1.11 4.2 Change detection for hydro-meteorological data Annual temperature, precipitation and streamflow were tested using the Mann-Kendall and Pettitt methods, as reported in Table and illustrated in Fig The results showed rises in annual temperature, precipitation and streamflow (by 0.035°C year-1, Table Summary of Mann-Kendall trend test and Pettitt test statistics for annual rainfall, temperature and streamflow in the Be River catchment Mann-Kendall test Precipitation Temperature Streamflow Pettitt test for change point Zc β p KT t p 2.27 3.16 1.74 20.613 0.035 3.142 * * * 88 102 78 1989 1986 1989 * * * *indicates significant at p < 0.05 Change 20.613 mm year-1 and 3.142 m3 s-1 year-1, respectively) at the 5% significance level In other words, the null hypothesis H0 was not accepted for the annual temperature, rainfall and streamflow time series Change points in the annual rainfall and streamflow were detected as occurring around 1989, with a significance level of 5%, while the change point in annual temperature was statistically significant in 1986 The Mann-Kendall test was also applied to the data series for monthly precipitation and temperature, as summarized in Table There are no significant trends in most of the monthly precipitation time series, except for October and December The precipitation in October and December showed significant increasing trends of 2.24 and 1.73 mm year-1, respectively In the case of the monthly temperature, significant increasing trends were detected for most of the monthly temperature time series, except for February, March, April and May 1101 Impact of climate and land-use changes on hydrological processes Table Summary of Mann-Kendall trend test statistics for monthly rainfall and temperature in the Be River catchment Month Precipitation Zc Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 January February March April May June July August September October November December 0.66 1.58 0.63 0.58 1.85 –0.48 1.40 –1.11 –0.16 2.27 0.53 2.09 β 0.208 0.589 0.762 0.741 3.313 –2.740 2.783 –3.676 –0.233 2.244 1.325 1.733 Temperature P * * Zc 2.82 1.50 0.37 –0.62 0.06 2.51 2.37 3.10 3.21 2.51 2.51 3.59 β 0.108 0.041 0.010 –0.021 0.001 0.051 0.024 0.043 0.042 0.048 0.050 0.085 p * * * * * * * * *indicates significant at p < 0.05 catchment scale The meteorological data were divided into two periods, 1978–1989 and 1990– 2000, based on the change point analysis, and each period included one land-use map The land-use map for 1990 was used to represent the 1978–1989 period, and that for 2001 was used to represent the 1990–2000 period The following four scenarios were investigated: – – – – Fig Variations of mean values in (a) annual precipitation, (b) annual temperature and (c) annual discharge in the Be River catchment (1978–2000) 4.3 Hydrological and sediment responses to land-use and climate changes To investigate the impacts of climate change and land-use change on hydrological processes and sediment yield, the approach of one factor at a time was used (Li et al 2009) The change point of precipitation is selected as the change point in climate data, because rainfall plays a key role in hydrology and is the most fundamental meteorological variable on the Scenario (Baseline): Land-use in 1990 and climate data for the 1978–1989 period Scenario (Climate change): Land-use in 1990 and climate data for the 1990–2000 period Scenario (Land-use change): Land-use in 2001 and climate data for the 1978–1989 period Scenario (Climate and land-use changes): Landuse in 2001 and climate data for the 1990–2000 period 4.4 Model calibration and validation The LH-OAT parameter sensitivity analysis procedure showed that the most sensitive parameters for flow simulation were curve number (CN2), soil evaporation compensation factor (ESCO), threshold water depth in the shallow aquifer for flow (GQWMN), baseflow alpha factor (ALPHA_BF), soil depth (SOL_Z), available water capacity (SOL_AWC), channel effective hydraulic conductivity (CH_K2), groundwater ‘revap’ coefficient (GW_REVAP), Manning’s value for the main channel (CH_N2), and saturated hydraulic conductivity (SOL_K) The most sensitive parameters for sediment simulation were the linear re-entrainment parameter for channel sediment routing (SPCON), the exponent of re- 1102 Dao Nguyen Khoi and Tadashi Suetsugi Table SWAT sensitivity parameters and calibrated values Simulation Parameter Flow Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Sediment CN2 ESCO GQWMN ALPHA_BF SOL_Z SOL_AWC CH_K2 GW_REVAP CH_N2 SOL_K SPCON SPEXP USLE_P Description of parameter Range Initial SCS CN II value*** Soil evaporation compensation factor* Threshold water depth in the shallow aquifer for flow** Baseflow alpha factor* Soil depth*** Available water capacity*** Channel effective hydraulic conductivity** Groundwater ‘revap’ coefficient** Manning’s value for main channel* Saturated hydraulic conductivity*** Linear re-entrainment parameter for channel sediment routing* Exponent of re-entrainment parameter for channel sediment routing* USLE support practice factor* ±0.5 0 ±0.5 ±0.5 –0.01 0.02 –0.01 ±0.5 0.0001 Calibrated value –1 – 5000 –1 – 500 – 0.2 – 0.3 – 0.01 Phuoc Long Phuoc Hoa –0.29 0.95 456 0.11 0.03 0.23 184 0.17 0.04 –0.06 0.001 –0.36 0.42 2356 0.61 0.28 0.40 184 0.17 0.04 0.07 – 1.5 1.01 0–1 0.42 *Parameter value is replaced by given value **Parameter value is added by given value ***Parameter value is multiplied by (1 + a given value) entrainment parameter for channel sediment routing (SPEXP), and the USLE support practice factor (USLE_P) These sensitive parameters were optimized using the auto-calibration extension of ArcSWAT 2009 to calibrate the model The daily streamflow for 1981– 1989 at the Phuoc Long and Phuoc Hoa stations and the land-use map for 1990 were used for model calibration The daily streamflow for 1990–1993 for the Phuoc Long station and 1990–2000 for the Phuoc Hoa station and land-use map for 2001 were used for the model validation of flow simulation This approach was used in the study undertaken by Li et al (2009) Because of the lack of observed sediment load, these data were only available from 07/1999 to 2004 at monthly levels They were divided into two periods for calibration (07/1999–2001) and validation (2002–2004) using the land-use map for 2001 The flow calibration and validation was conducted first, and then the sediment calibration and validation As a result of the calibration, the most sensitive flowrelated parameter of CN2 was adjusted to have values of –0.29 for Phuoc Long and –0.36 for Phuoc Hoa, and the most sensitive sediment-related parameter SPCON was adjusted to have a value of 0.001 This value of SPCON found here was similar to that in the study conducted by Phan et al (2011) in the Cau River watershed in northern Vietnam The details of the calibrated parameters are presented in Table The SWAT flow simulations were calibrated against the daily flow from 1981 to 1989 and validated from 1990 to 1993 at the Phuoc Long gauging station, as shown in Fig The simulated daily flow fit the Fig Observed and simulated daily flow hydrograph at the Phuoc Long station: (a) calibration and (b) validation observed data for the calibrated period well, with NSE, PBIAS and RSR values of 0.77, 1.60% and 0.47, respectively For the validation period, the values of NSE = 0.79, PBIAS = 3.30% and RSR = 0.45 suggest that there was good agreement between the simulated and observed streamflow during this period, based on 1103 Impact of climate and land-use changes on hydrological processes Table Model performance for the simulation of runoff Period Calibration (1981–1989) Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Validation (1990–1993) Phuoc Long station Phuoc Hoa station Time step NSE PBIAS RSR Period Time step NSE PBIAS RSR Daily Monthly Daily Monthly 0.77 0.87 0.79 0.91 1.60% 1.60% 3.30% 3.30% 0.48 0.36 0.45 0.30 Calibration (1981–1989) Daily Monthly Daily Monthly 0.86 0.94 0.71 0.79 –1.90% –1.90% –6.20% –6.20% 0.37 0.25 0.54 0.46 the performance criteria given by Moriasi et al (2007) The aggregated monthly average flow values from the daily flow values improved the fit between the model predictions and observed flows More detail can be seen in Table Figure shows a hydrograph of the simulated and observed daily flow for the calibration and validation periods at the Phuoc Hoa station The statistical evaluations shown in Table also suggest that there was good agreement between the daily measured and simulated streamflow during these periods, according to Moriasi et al (2007) This agreement is shown by values of NSE = 0.86, RSR = 0.37 and PBIAS = –1.90% for the calibration period and NSE = 0.71, RSR = 0.54 and PBIAS = –6.20% for the validation period In the case of the aggregated monthly average flow, the match between the simulated flow values and the observed values was improved Validation (1990–2000) This match is shown in Table Although the simulated and observed streamflow followed the same trend, the peak flow was overestimated for Phuoc Long station and underestimated for Phuoc Hoa station This may have resulted from the uneven spatial distribution of the rain gauges In the study area, eight rain gauges are located in the lower area of the catchment; however, only one rain gauge located in the upper area of the catchment has long-term records (Fig 1) A further reason can be attributed to the CN2, which is used to simulate the surface runoff The CN2 method assumes a unique relationship between cumulative rainfall and cumulative runoff for the same antecedent moisture conditions (Betrie et al 2011) Generally speaking, these results reveal that the hydrological processes in SWAT are modelled realistically for the Be River catchment, which is important for the simulation of sediment The simulated sediment load values were calibrated against monthly observed data from 07/1999 to 2001 and validated from 2002 to 2004 at the Phuoc Hoa station, as presented in Fig The fit between the simulated and observed sediment loads was acceptable, according to Moriasi et al (2007) The fit was indicated by the values of NSE = 0.74, RSR = 0.51 and PBIAS = –1.10% for the calibration period and NSE = 0.55, RSR = 0.66 and PBIAS = 33.77% for the validation period (Table 7) Although an underestimation of the monthly sediment yield by the model for the validation period was within the satisfactory level of acceptance, it can generally be said that the simulated result was relatively satisfactory From the results of the calibration and validation, it is reasonable to conclude that the SWAT model could simulate the hydrology and sediment yield in this catchment well The calibrated parameters were accepted for the scenario simulations 4.5 Response to climate change Fig Observed and simulated daily flow hydrograph at the Phuoc Hoa station: (a) calibration and (b) validation In order to investigate the impact of climate change on hydrological processes and sediment yield, the simulation was carried out using the land-use Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 1104 Dao Nguyen Khoi and Tadashi Suetsugi Fig Change in temperature and precipitation in the Be River catchment between period (1978–1989) and period (1990–2000) Fig Observed and simulated monthly sediment load hydrograph at the Phuoc Hoa station: (a) calibration and (b) validation Table Model performance for the simulation of sediment at the Phuoc Hoa station Period Time step NSE PBIAS Calibration (07/1999–2001) Monthly Validation (2002–2004) Monthly 0.74 0.55 Fig Annual changes of hydrological components under the impact of climate and land-use changes RSR –1.10% 0.51 33.77% 0.66 conditions of the 1990s and the climate data of two different periods: 1978–1989 and 1990–2000 Figure shows the absolute changes in the monthly climate variables between the two periods Compared with the 1978–1989 period, the annual temperature increased by 0.4°C and the annual precipitation increased by 292.3 mm (12.8%) The increases in temperature and precipitation were higher in the dry season (0.5°C and 44.8%) than in the wet season (0.4°C and 10.1%) In the case of water balance components, climate change caused increases in all water balance components, including a 7.9% increase in actual evapotranspiration, a 19.5% increase in groundwater discharge, a 34.2% increase in surface runoff and a 56.1% increase in soil water content (Fig 8) These increases could be a result of the increases in temperature and precipitation in the 1990–2000 period compared with those in the 1978–1989 period Generally, the pattern of changes in water balance components is mainly determined by the changes in precipitation and temperature Under the impact of climate change, the annual streamflow and sediment load increased by 26.3% and 31.7%, respectively (Fig 9) The increases in flow and sediment load can be explained by increases in precipitation and runoff in the 1990–2000 period compared with the 1978–1989 period Considering the seasonal change, the streamflow and sediment load increased significantly, by 26.8% and 31.1% in the wet season and 21.8% and 56.4% in the dry season, respectively In general, the changes in the streamflow and sediment load occur in the same direction, which is similar to the findings of the study on the impacts of climate change on the discharge and sediment load in the Cau River catchment, conducted by Phan et al (2011) The Phan et al (2011) study indicated that an increase in the Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Impact of climate and land-use changes on hydrological processes Fig Changes in annual and seasonal (a) streamflow and (b) sediment load under the impact of climate and landuse changes streamflow will increase the sediment load, while a decrease in the streamflow will decrease the sediment load 4.6 Response to land-use change The impact of land-use change on the water balance components is illustrated in Fig Under the impact of land-use change, surface runoff, soil water content and sediment yield increased considerably, by 18.4%, 10.4% and 12.8%, respectively, while actual evapotranspiration and water yield increased slightly, by approximately 1.3% and 1.1%, respectively Aside from this, the other water balance components decreased, including a 5.8% decrease in groundwater discharge, a 4.6% decrease in lateral flow, and a 4% decrease in the amount of water percolating out of the root zone Deforestation and agricultural expansion could be the cause of these changes This is because forest vegetation intercepts more water than other land-use types (Ma et al 2009), and the infiltration rate of forest land is large compared with the other 1105 land-use types (Bruijnzeel 1990) Therefore, it is likely that deforestation in the Be River catchment caused an increase in runoff and decreases in groundwater discharge and lateral flow Under the impact of land-use change, deforestation and the increase in agricultural land resulted in an increase in annual streamflow (1.2%) and sediment load (11.3%) Considering the seasonal change, the streamflow decreased by 4.6% in the dry season and increased by 1.8% in the wet season In the case of sediment load, it increased significantly in both the dry and wet seasons by approximately 25.4% and 11.0%, respectively The effect of land-use change on the hydrology and sediment yield in the different regions of Vietnam has been investigated by several authors For instance, Phan et al (2010) investigated the impact of land-use change on discharge and sediment yield in the Cau River catchment, and reported that the conversion of 11.07% of forest land to agricultural land had caused increases in streamflow and sediment load of 3.93% and 8.94%, respectively Ranzi et al (2012) conducted a study of the landuse change effect on the sediment load in the Lo River, and indicated that a 35% decrease in forest area results in a 28% increase in sediment load In general, the changes in streamflow and sediment yield under the land-use change in the Be River catchment are fairly similar to the findings of the studies by Phan et al (2010) and Ranzi et al (2012) 4.7 Response to combined climate and land-use changes To investigate the combined impact of climate and land-use changes, the simulated streamflow, sediment load and water balance components under Scenario (land-use in 2001 and climate data in the 1990–2000 period) were compared to those during the baseline period (land-use in 1990 and climate data in the 1978–1989 period) The results are displayed in Figs and The combined impact of land-use and climate changes caused increases in streamflow and sediment load, as well as in all water balance components When the changes caused by climate change alone and land-use change alone occur in the same direction, the change is intensified, as climate change and land-use change occur simultaneously In contrast, when the directions of the changes affected by climate change alone and land-use change alone are opposite, the change is reduced when climate change and land-use change occur concurrently 1106 Dao Nguyen Khoi and Tadashi Suetsugi Table Simulated streamflow at the Phuoc Hoa station under the impacts of climate and land-use changes Scenario Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Land-use 1990 1990 2001 2001 Climate 1978–1989 1990–2000 1978–1989 1990–2000 Streamflow (m3 s-1) Changes in observed flow Sim (m s ) (%) (m3 s-1) (%) 208 – – 254 213 267 216 270 – – – 46 – – – 22.1 – 54 57 – 25.4 1.4 26.8 4.8 Limitations and recommendations The SWAT hydrological model was successfully applied in this study to the Be River catchment to assess the impact of climate and land-use changes on hydrology and sediment yield However, there are limitations in both the data and the model, which are described as follows One of the limitations in this study comes from the unavailability of data Because of the lack of sediment load data, sediment simulation is calibrated and validated in monthly time steps for only a short period of time, whereas hydrological modelling is calibrated and validated in daily time steps for a long period of time Aside from this, the calibration and validation of streamflow and sediment simulations are not for the same period of time, because the observed sediment data not allow for the same period to be applied, so it is required to extrapolate -1 Changes in simulated flow Obs Table shows the details of the annual streamflow simulated by the SWAT model under the different climate and land-use changes Compared with Scenario 1, the simulated streamflow in Scenario increased by 57m3 s-1 (26.8%), which represents the combined impacts of climate and land-use changes, while the increase in observed streamflow caused by both climate and land-use changes was 46 m3 s-1 (22.1%) The slight difference of the increases in simulated and observed streamflow could be explained by the overestimation in simulation results of the SWAT model, but the simulation results were within the performance criteria given by Moriasi et al (2007) Aside from this, the simulation results showed that both land-use change and climate change increased the streamflow, with the percentage contribution of 1.4% for land-use change and 25.4% for climate change In general, the simulation results showed that the hydrological processes have stronger responses to climate change compared to land-use change (Figs and 9, Table 8) the streamflow beyond the time period of observed sediment data using the calibrated SWAT model for streamflow simulation in order to calibrate and validate the sediment simulation These decrease the accuracy of the model performance in sediment simulation Therefore, to improve the simulation results, collecting additional data on sediment load should be considered to improve the model performance in streamflow and sediment yield simulations Another limitation comes from the SWAT model The SWAT model uses a number of empirical and quasiphysical equations that were developed based on the climate conditions in the United States, and those equations may not be appropriate for the tropical climate in Vietnam For example, the CN2 equation was a product of more than 20 years of studies involving rainfall–runoff relationships in small rural watersheds across the United States (Neitsch et al 2011) In addition, the MUSLE was also developed based on the hydrological conditions throughout the United States In the tropical area, the heavy rainfall that may accompany a storm has the potential to erode as much surface soil in the catchment as the subsequent runoff, but the MUSLE does not account for such factors (Phomcha et al 2011) It is suggested that some parameters in the empirical equation should be modified to suit the tropical climate area in order to improve the simulation results The use of oversimplified sediment routing algorithms to simulate both landscape and in-stream erosion is a further limitation of the SWAT model Aside from this, the SWAT model allows all the soil eroded by runoff to reach the channel directly, without considering sediment deposition remaining on surface catchment areas (Oeurng et al 2011) Even though the SWAT model has some limitations, the simulation results were within the performance criteria provided by Moriasi et al (2007) CONCLUSION The SWAT model was applied to the Be River catchment to model the impacts of environmental changes, including climate and land-use changes, on the Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 Impact of climate and land-use changes on hydrological processes hydrological processes and sediment yield The results of model calibration and validation showed that the SWAT model could be a useful tool for evaluating the impact of climate and land-use changes on hydrological processes and sediment yield in the Be River catchment Climate change in this study led to significantly increased streamflow, sediment load and water balance components in the 1990–2000 period compared to the 1978–1989 period Increases in temperature and precipitation caused these increases in the course of the period The land-use change in the study area caused increases in streamflow, sediment load, actual evapotranspiration, surface runoff and soil water, and decreases in groundwater discharge, lateral flow and amount of water percolating out of the root zone These changes are attributed to deforestation and agricultural expansion that happened in the 1990–2001 period (SIWRP 2002, 2008) Under the impact of coupled land-use and climate changes, the streamflow, sediment yield and water balance components increased in the 1990–2000 period compared with those in the 1978– 1989 period These changes would raise concern regarding the increase of soil erosion in the Be River catchment In general, climate variability influenced hydrological processes and sediment yield more strongly than the land-use change in the catchment during the 1978–2000 period Therefore, when planning and managing for water resources, the importance of increasing adaptation to climate change is emphasized However, with the considerable changes in the surface runoff and sediment load under the impact of land-use change, the effect of land-use change should be accounted for in water resource management in the Be River catchment Investigating not only the separate but also the combined impacts of climate and land-use changes helps to enhance our understanding of these impacts on hydrological processes and soil erosion in the catchment The results obtained from this study could be of value to managers/decision-makers in integrated river basin management, as well as to the development of adaptation and mitigation strategies regarding climate and land-use changes Acknowledgement The authors thank their colleagues in Vietnam for assisting with the data They are grateful for the comments of two anonymous reviewers, which greatly enhanced the quality of the manuscript 1107 Funding The authors acknowledge the Global Center of Excellence (GCOE) program of the University of Yamanashi, which funded this study REFERENCES Arnold, J.G., et al., 1998 Large area hydrologic modeling and assessment part I: model development Journal of the American Water Resources Association, 34, 73–89 doi:10.1111/j.1752-1688.1998.tb05961.x Betrie, G.D., et al., 2011 Sediment management modelling in the Blue Nile basin using SWAT model Hydrology and Earth System Sciences, 15, 807–818 doi:10.5194/hess-15-8072011 Bruijnzeel, L.A., 1990 Hydrology of moist tropical forests and effects of conversion: a state of knowledge review Paris: UNESCO International Hydrological Programme Chow, V.T., 1959 Open channel hydraulics New York: McGraw-Hill Elfert, S and Bormann, H., 2010 Simulated impact of past and possible future land use changes on the hydrological response of the Northern German lowland ‘Hunte’ catchment Journal of Hydrology, 383, 245–255 doi:10.1016/j.jhydrol.2009.12.040 Green, W.H and Ampt, G.A., 1911 Studies on soil physics Journal of Agricultural Sciences, 4, 11–24 Hargreaves, G.L., Hargreaves, G.H., and Riley, J.P., 1985 Agricultural benefits for Senegal River basin Journal of Irrigation and Drainage Engineering, 111 (2), 113–124 doi:10.1061/(ASCE)0733-9437(1985)111:2(113) Kendall, M.G., 1975 Rank correlation measures London: Charles Griffin Li, H., et al., 2012 Separating effects of vegetation change and climate variability using hydrological modelling and sensitivity-based approaches Journal of Hydrology, 420–421, 403–418 doi:10.1016/j.jhydrol.2011.12.033 Li, Z., et al., 2009 Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China Journal of Hydrology, 377, 35–42 doi:10.1016/j.jhydrol.2009.08.007 Ma, H., et al., 2010 Impact of climate variability and human activity on streamflow decrease in the Miyun Reservoir catchment Journal of Hydrology, 389, 317–324 doi:10.1016/j jhydrol.2010.06.010 Ma, X., et al., 2009 Response of hydrological processes to landcover and climate changes in Kejie watershed, South-West China Hydrological Processes, 23, 1179–1191 doi:10.1002/ hyp.7233 Ma, Z., et al., 2008 Analysis of impacts of climate variability and human activity on streamflow for a river basin in arid region of Northwest China Journal of Hydrology, 352, 239–249 doi:10.1016/j.jhydrol.2007.12.022 Mango, L.M., et al., 2011 Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management Hydrology and Earth System Sciences, 15, 2245–2258 doi:10.5194/hess-15-2245-2011 Mann, H.B., 1945 Non-parametric tests against trend Econometrica, 13, 245–259 doi:10.2307/1907187 MONRE (Ministry of Natural Resources and Environment), 2009 Climate change, sea level rise scenarios for Vietnam Hanoi: Ministry of Natural Resources and Environment Monteith, J.L., 1965 Evaporation and the environment In: G.E Fogg, ed The state and movement of water in living organisms XIXth symposium on the society of experimental biology (Swansea, UK) Cambridge: Cambridge University Press, 205–234 Downloaded by [NUS National University of Singapore] at 22:40 03 June 2014 1108 Dao Nguyen Khoi and Tadashi Suetsugi Moriasi, D.N., et al., 2007 Model evaluation guidelines for systematic quantification of accuracy in watershed simulations Transactions of the American Society of Agricultural and Biological Engineers, 50, 885–900 Nash, J.E and Sutcliffe, J.V., 1970 River flow forecasting through conceptual models part I—a discussion of principles Journal of Hydrology, 10 (3), 282–290 doi:10.1016/0022-1694(70) 90255-6 Neitsch, S.L., et al., 2011 Soil and water assessment tool theoretical documentation version 2009 College Station: Texas Water Resources Institute, Technical Report no 406, 647 Oeurng, C., Sauvage, S., and Sánchez-Pérez, J.M., 2011 Assessment of hydrology, sediment and particulate organic carbon yield in a large agricultural catchment using the SWAT model Journal of Hydrology, 401, 145–153 doi:10.1016/j.jhydrol.2011.02.017 Pettitt, A.N., 1979 A non-parametric approach to the change-point problem Applied Statistics, 28, 126–135 doi:10.2307/2346729 Phan, D.B., Wu, C.C., and Hsieh, S.C., 2010 Land-use change effects on discharge and sediment yield of Cau River catchment in Northern Vietnam In: N.-W Kim and R Srinivasan, eds Proceedings of 2010 international SWAT conference, 4–8 August 2010 Seoul, 350–361 Phan, D.B., Wu, C.C., and Hsieh, S.C., 2011 Impact of climate change on stream discharge and sediment yield in northern Vietnam Water Resources, 38 (6), 827–836 doi:10.1134/ S0097807811060133 Phomcha, P., et al., 2011 Predicting sediment discharge in an agricultural watershed: a case study of the Lam Sonthi watershed, Thailand Science Asia, 37, 43–50 doi:10.2306/scienceasia1513-1874.2011.37.043 Priestley, C.H.B and Taylor, R.J., 1972 On the assessment of surface heat flux and evaporation using large-scale parameters Monthly Weather Review, 100, 81–92 doi:10.1175/1520-0493 (1972)1002.3.CO;2 Ranzi, R., Le, T.H., and Rulli, M.C., 2012 A RUSLE approach to model suspended sediment load in the Lo River (Vietnam): effects of reservoirs and land-use changes Journal of Hydrology, 422– 423, 17–2929 doi:10.1016/j.jhydrol.2011.12.009 Rossi, C.G., et al., 2008 Hydrologic calibration and validation of the soil and water assessment tool for the Leon River watershed Journal of Soil and Water Conservation, 63, 533–541 doi:10.2489/jswc.63.6.533 SIWRP (Southern Institute for Water Resources Planning), 2002 Integrated water resources planning for Be River catchment Ho Chi Minh city: SIWRP (in Vietnamese) SIWRP (Southern Institute for Water Resources Planning), 2008 Integrated water resources planning for Dong Nai River basin Ho Chi Minh city: SIWRP Tong, S.T.Y., et al., 2012 Predicting plausible impacts of sets of climate and land use change scenarios on water resources Applied Geography, 32, 477–489 doi:10.1016/j.apgeog.2011.06.014 Trinh, M.V., 2007 Soil erosion and nitrogen leaching in northern Vietnam—experimentation and modeling Thesis (PhD) Wageningen University Tu, J., 2009 Combined impact of climate and land use changes on streamflow and water quality in eastern Massachusetts, USA Journal of Hydrology, 379, 268–283 doi:10.1016/j jhydrol.2009.10.009 USDA-SCS (US Department of Agriculture—Soil Conservation Service), 1972 National engineering handbook Section 4: hydrology Washington, DC: US Department of Agriculture, United State Van Griensven, A., et al., 2006 A global sensitivity analysis tool for the parameters of multi-variable catchment models Journal of Hydrology, 324, 10–23 doi:10.1016/j jhydrol.2005.09.008 Van Liew, M.W., Arnold J.G., and Bosch, D.D., 2005 Problems and potential of auto-calibrating a hydrologic model Transactions of the ASAE, 48 (3), 1025–1040 doi:10.13031/2013.18514 Wang, W., et al., 2012 Quantitative assessment of the impact of climate variability and human activities on runoff changes: a case study in four catchments of the Haihe River basin, China Hydrological Processes doi:10.1002/hyp.9299 Ward, P.J., et al., 2009 The impact of land use and climate change on late Holocene and future suspended sediment yield of the Meuse catchment Geomorphology, 103, 389–400 doi:10.1016/j.geomorph.2008.07.006 William, J.R., 1969 Flood routing with variable travel time or variable storage coefficients Transactions of the ASAE, 12, 100–10333 doi:10.13031/2013.38772 William, J.R., 1995 Chapter 25: The EPIC model In: V.P Singh, ed Computer models of watershed hydrology Littleton, CO: Water Resources Publications, 909–1000 Zhang, W., et al., 2009 Temporal and spatial variability of annual extreme water level in the Pearl River Delta region, China Global and Planetary Change, 69, 35–47 doi:10.1016/j gloplacha.2009.07.003 Zhang, Y., et al., 2011 Analysis of impacts of climate variability and human activity on streamflow for a river basin in northeast China Journal of Hydrology, 410, 239–247 doi:10.1016/j jhydrol.2011.09.023  ... The impact of climate and land-use changes on hydrological processes and sediment yield is investigated in the Be River catchment, Vietnam, using the Soil and Water Assessment Tool (SWAT) hydrological. .. streamflow and sediment load in the Be River catchment; (b) to evaluate the separate impacts of climate and land-use changes on hydrology and sediment yield; and (c) to assess the impacts of combined climate. .. Limitations and recommendations The SWAT hydrological model was successfully applied in this study to the Be River catchment to assess the impact of climate and land-use changes on hydrology and sediment