Soil Evaporation Compensation Factor Research Articles

Insights to the water balance of a Boreal watershed using a SWAT model

The hydrological characteristics of a watershed play a crucial role in shaping ecosystems within the Boreal zone and have a significant impact on regional environments. Knowing these characteristics, such as the distinctive topography, vegetation, soil composition, and climatic conditions in the Canadian Boreal ecozone, is essential for implementing sustainable water management. This study focuses on assessing the hydrological dynamics of the Upper Humber River Watershed (UHRW) in western Newfoundland, Canada, using the Soil and Water Assessment Tool (SWAT) model. The UHRW includes sub-basins and hydrological response units (HRUs), with diverse land uses, soil types, and slope characteristics. Key parameters influencing streamflow simulation were identified through sensitivity analysis, including the runoff curve number, the effective hydraulic conductivity, the temperature lapse rate, the soil evaporation compensation factor, and the available water capacity of the soil layer. The SWAT model, using data from the Reidville hydrometric station, shows favorable performance metrics, with R2 values of 0.79 and 0.83 during the calibration and evaluation periods, respectively. The model effectively captures seasonal and monthly flow patterns, displaying right-skewed distributions and seasonal variations. The analyzed hydrological parameters, such as precipitation, evaporation, transpiration, surface runoff, and groundwater flow, reveal their significant contributions to the water balance. The flow duration curve analysis indicates the model’s capability to estimate peak and low flows, with slight under-prediction during the recession phase. Seasonal analysis further supports the model’s performance, with positive Nash-Sutcliffe Efficiency (NSE) values ranging from 0.65 to 0.91. The study concludes that the SWAT model is suitable for simulating the hydrological processes in the studied watershed providing valuable insights for sustainable water resource management and decision-making in the UHRW. The results can be useful for other Boreal ecozone watersheds.

A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+

Abstract. Parameter sensitivity analysis plays a critical role in efficiently determining main parameters, enhancing the effectiveness of the estimation of parameters and uncertainty quantification in hydrologic modeling. In this paper, we demonstrate an uncertainty and sensitivity analysis technique for the holistic Soil and Water Assessment Tool (SWAT+) model coupled with new gwflow module, spatially distributed, physically based groundwater flow modeling. The main calculated groundwater inflows and outflows include boundary exchange, pumping, saturation excess flow, groundwater–surface water exchange, recharge, groundwater–lake exchange and tile drainage outflow. We present the method for four watersheds located in different areas of the United States for 16 years (2000–2015), emphasizing regions of extensive tile drainage (Winnebago River, Minnesota, Iowa), intensive surface–groundwater interactions (Nanticoke River, Delaware, Maryland), groundwater pumping for irrigation (Cache River, Missouri, Arkansas) and mountain snowmelt (Arkansas Headwaters, Colorado). The main parameters of the coupled SWAT+gwflow model are estimated utilizing the parameter estimation software PEST. The monthly streamflow of holistic SWAT+gwflow is evaluated based on the Nash–Sutcliffe efficiency index (NSE), percentage bias (PBIAS), determination coefficient (R2) and Kling–Gupta efficiency coefficient (KGE), whereas groundwater head is evaluated using mean absolute error (MAE). The Morris method is employed to identify the key parameters influencing hydrological fluxes. Furthermore, the iterative ensemble smoother (iES) is utilized as a technique for uncertainty quantification (UQ) and parameter estimation (PE) and to decrease the computational cost owing to the large number of parameters. Depending on the watershed, key identified selected parameters include aquifer specific yield, aquifer hydraulic conductivity, recharge delay, streambed thickness, streambed hydraulic conductivity, area of groundwater inflow to tile, depth of tiles below ground surface, hydraulic conductivity of the drain perimeter, river depth (for groundwater flow processes), runoff curve number (for surface runoff processes), plant uptake compensation factor, soil evaporation compensation factor (for potential and actual evapotranspiration processes), soil available water capacity and percolation coefficient (for soil water processes). The presence of gwflow parameters permits the recognition of all key parameters in the surface and/or subsurface flow processes, with results substantially differing if the base SWAT+ models are utilized.

Performance of HEC-HMS and SWAT to simulate streamflow in the sub-humid tropical Hemavathi catchment

Abstract The present study was conducted to examine the accuracy and applicability of the hydrological models Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center (HEC)- Hydrologic Modeling System (HMS) to simulate streamflows. Models combined with the ArcGIS interface have been used for hydrological study in the humid tropical Hemavathi catchment (5,427 square kilometer). The critical focus of the streamflow analysis was to determine the efficiency of the models when the models were calibrated and optimized using observed flows in the simulation of streamflows. Daily weather gauge stations data were used as inputs for the models from the 2014–2020 period. Other data inputs required to run the models included land use/land cover (LU/LC) classes resulting from remote sensing satellite imagery, soil map and digital elevation model (DEM). For evaluating the model performance and calibration, daily stream discharge from the catchment outlet data were used. For the SWAT model calibration, available water holding capacity by soil (SOL_AWC), curve number (CN) and soil evaporation compensation factor (ESCO) are identified as the sensitive parameters. Initial abstraction (Ia) and lag time (Tlag) are the significant parameters identified for the HEC-HMS model calibration. The models were subsequently adjusted by autocalibration for 2014–2017 to minimize the variations in simulated and observed streamflow values at the catchment outlet (Akkihebbal). The hydrological models were validated for the 2018–2020 period by using the calibrated models. For evaluating the simulating daily streamflows during calibration and validation phases, performances of the models were conducted by using the Nash-Sutcliffe model efficiency (NSE) and coefficient of determination (R2). The SWAT model yielded high R2 and NSE values of 0.85 and 0.82 for daily streamflow comparisons for the catchment outlet at the validation time, suggesting that the SWAT model showed relatively good results compared to the HEC-HMS model. Also, under modified LU/LC and ungauged streamflow conditions, the calibrated models can be later used to simulate streamflows for future predictions. Overall, the SWAT model seems to have done well in streamflow analysis for hydrological studies.

Hydrological Modelling of Small Gauged and Ungauged Mountainous Watersheds Using SWAT—A Case of Western Ghats in India

Mountainous forested watersheds are important hydrologic systems that are responsible for much of the water supply and run-of-the-river hy-dropower schemes in many parts of the world. In India, the Western Ghats are one of such important hydrologic systems located in southern peninsular region. Several of these watersheds are ungauged. The Soil and Water Assessment Tool (SWAT) has been used to model streamflows for two mountainous forested watersheds, namely, Gurupur (699 km2) (a gauged watershed) and Upper Payaswini (44.6 km2) (an ungauged wa-tershed). Model calibration and validation are performed using monthly and daily streamflow data for the gauged watershed. Sample flow values obtained over a limited period were used for validation of ungauged wa-tershed. Flow duration curves (FDCs) have been derived to assess per-centile flow distributions. Model performance is evaluated using Nash-Sutcliffe coefficient (ENS), percent bias (PBIAS), coefficient of de-termination (R2) and comparison of percentile flow values obtained from observed and simulated FDCs. Sensitivity analysis with Latin Hypercube One-factor-At-a-Time (LH-OAT) indicates five soil-land use related pa-rameters namely, soil available water capacity (SOL_AWC), soil evapora-tion compensation factor (ESCO), soil depth (SOL_Z) and layers, groundwater baseflow (ALPHA_BF), and curve number (CN2 (forest & agriculture)), to be sensitive for simulating both gauged and ungauged wet mountainous forested watersheds. Study shows that lateral flows from dynamic sub-surface zones in such watersheds contribute substan-tially to the total water yield.

Uncertainty analysis of parameters in non‐point source pollution simulation: case study of the application of the Soil and Water Assessment Tool model to Yitong River watershed in northeast China

AbstractUncertainty analysis of the model parameters in non‐point source pollution (NPSP) simulation is important because of its great effects on predictions and decision‐making. Understanding the main parameters that effect the uncertainty of NPSP is necessary to provide the basis for formulating control measures. In this study, two methods were applied to conduct parameter uncertainty analysis for Soil and Water Assessment Tool (SWAT). Sobol’ method was used to screen out the model parameters with great effects on the runoff, sediment, total nitrogen (TN) and total phosphorus (TP). The results obtained by sensitivity analysis were used subsequent model calibration and further uncertainty analysis. Monte Carlo (MC) method was employed to analyse the effects of parameter uncertainty on the model outputs. However, such problems are time‐consuming because the MC method required to invoke simulation model thousands of times. To address this challenge, a kriging surrogate model was developed to improve the overall calculation efficiency. The results obtained by sensitivity analysis showed that curve number value (CN2), soil evaporation compensation factor (ESCO), universal soil loss equation support practice factor (USLE_P) and initial organic nitrogen concentration in soil layer (SOL_ORGN) had significant effects on the SWAT outputs. The uncertainty analysis results showed that the uncertainty of runoff is the lowest, followed by TP and TN, and the uncertainty of sediment was the greatest. The kriging surrogate model has the ability to solve this time‐consuming problem rapidly with a high degree of accuracy, and thus it is very robust.

Parameter Sensitivity Test of SWAT Hydrological Model On Two Different Resolutions (A Case Study of Upper Cisadane Subbasin, West Java)

A sensitivity analysis of SWAT parameters was conducted on different spatial resolutions. The sensitivity analysis aimed to determine the input parameters that have the most impact on the of output of the model. Resolution of different inputs in the SWAT analysis can produce different input parameters that can affect the output. The purpose of this study was to identify the level of sensitivity of the parameters used in the SWAT model simulated on two different resolutions, i.e. 1: 100,000 and 1: 250,000. A sensitivity test was conducted manually using the absolute sensitivity method, i.e. a method to test the sensitivity of the parameters of SWAT model that can change (either increase or decrease) one by one while the other parameters are constant. The results show that the Nash-Sutcliffe Efficiency (NSE) coefficients derived after calibration of the SWAT models on both resolutions of maps indicate similar performance of the models, with the category for the daily simulation of excellent (NSE coefficients of 0.55 and 0.54), while the monthly simulation is categorized as very satisfactory (NSE coefficients of 0.80 and 0.82). The sensitive parameters of the SWAT model identified in the current study include CN2 (initial SCS runoff curve number for moisture condition II), Alpha_BNK (flow recession constant or recession proportional to the banks of the river), CH_K2 (effective hydraulic conductivity in main channel alluvium), CH_N2 (Manning’s “n” value for the main channel), ESCO (soil evaporation compensation factor), GW_Delay (groundwater delay), and GW_Revap (groundwater “revap” coefficient).

Hydrological modeling of Amaravila watershed in neyyar river basin using soil and water assessment tool (SWAT)

A hydrological model was developed using Soil and Water Assessment Tool (SWAT) for runoff estimation in Amaravila watershed of Neyyar river basin in the state of Kerala. 19 years (1991–2009) runoff data was used for the study in which 9 year (1991–1999) data was employed to develop and calibrate the model. However, 10 years monthly data (2000–2009) was used for the evaluation purpose. The entire watershed area was divided into five sub-basins comprising 142 hydrological response units through SWAT. Sensitivity analysis of SWAT model indicated most sensitive parameters influencing runoff are curve number (CN), soil evaporation compensation factor (ESCO), available water capacity of the soil layer (SOL_AWC) and threshold depth of water in the shallow aquifer to cause revamp (REVAPMN). Performance evaluation indicators were coefficient of determination (R2), Pearson correlation coefficient (r), Nash-Sutcliff efficiency (ENS) and root mean square error (RMSE). These were 0.89, 0.88, 0.72 and 0.14 respectively for calibration and 0.83, 0.88, 0.77 and 0.17, respectively for evaluation purpose. Water balance indicated that about 58 percent of rainfall flows out of the basin as surface runoff. It was observed that average annual groundwater flow is 2% of average annual rainfall and the annual evapotranspiration is 38% of the average annual rainfall in the watershed.

Assessment of SWAT Model Applicability and Performance for Predicting Surface Runoff in an Ungauged Watershed in the Philippines

The Soil and Water Assessment Tool (SWAT) model, owing to its robustness and wide applicability, was tested in Mabacan watershed in Laguna, Philippines, with the objective of developing a model for predicting surface runoff or streamflow in ungauged watersheds under conditions of limited hydrologic data. Model parameterization was performed based on the physical characteristics of the watershed and guided by sensitivity analysis. SWAT-predicted monthly surface runoff values for a 7-year period were then compared with manually computed values obtained using water balance and SCS-Curve Number methods. Agreement between runoff values was evaluated using the coefficient of determination (R2) and Nash-Sutcliffe model efficiency (NSE). Correlation analysis between SWAT-simulated monthly runoff and observed monthly rainfall was also performed to further assess the plausibility of simulation results. Sensitivity analysis showed that that the curve number (CN2), soil evaporation compensation factor (ESCO), and soil depth (SOL_Z) are the most sensitive parameters with sensitivity index (I) of 2.92, 0.08, and 0.04, respectively. Comparison between SWAT-predicted surface runoff with those obtained using water balance and SCS-CN methods yielded R2 values of 0.95 and 0.94, and NSE values of 0.70 and 0.63, respectively. The SWAT-simulated runoff series also proved to be well-correlated with observed rainfall series (R2=0.82). Results of this study suggest that the SWAT model is highly applicable for predicting surface runoff or streamflow in ungauged watersheds in the Philippines even with limited hydrologic data and that familiarity with the physical characteristics of the watershed area is essential in enhancing model parameterization and performance.

Application of SWAT Model to the Olifants Basin: Calibration, Validation and Uncertainty Analysis

The application of the Soil and Water Assessment Tool (SWAT) to the Olifants Basin in South Africa was the focus of our study with emphasis on calibration, validation and uncertainty analysis. The Basin was discretized into 23 sub-basins and 226 Hydrologic Response Units (HRUs) using 3 arc second (90 m × 90 m) pixel resolution SRTM DEM with stream gauge B7H015 as the Basin outlet. Observed stream flow data at B7H015 were used for model calibration (1988-2001) and validation (2002-2013) using the split sample approach. Relative global sensitivity analysis using SUFI-2 algorithm was used to determine sensitive parameters to stream flow for calibration of the model. Performance efficiency of the Olifants SWAT model was assessed using Nash-Sutcliffe (NSE), coefficient of determination (R2), Percent Bias (PBIAS) and Root Mean Square Error-Observation Standard deviation Ratio (RSR). Sensitivity analysis revealed in decreasing order of significance, runoff curve number (CN2), alpha bank factor (ALPHA_BNK), soil evaporation compensation factor (ESCO), soil available water capacity (SOIL_AWC, mm H2O/mm soil), groundwater delay (GW_ DELAY, days) and groundwater “revap” coefficient (GW_REVAP) to be the most sensitive parameters to stream flow. Analysis of the model during the calibration period gave the following statistics; NSE = 0.88; R2 = 0.89; PBIAS = -11.49%; RSR = 0.34. On the other hand, statistics during the validation period were NSE = 0.67; R2 = 0.79; PBIAS = -20.69%; RSR = 0.57. The observed statistics indicate the applicability of the SWAT model in simulating the hydrology of the Olifants Basin and therefore can be used as a Decision Support Tool (DST) by water managers and other relevant decisions making bodies to influence policy directions on the management of watershed processes especially water resources.

Sensitivity analysis of a GIS-based model: A case study of a large semi-arid catchment

Water resource and hydrologic modeling studies are intrinsically related to spatial processes of hydrologic cycle. Due to generally sparse data, and high rainfall variability, the accurate prediction of water availability in complex semi-arid catchment depends to a great extent on how well spatial input data describe realistically the relevant characteristics. The Geographic Information System (GIS) provides the framework within which spatially distributed data are collected and used to prepare model input files. Despite significant recent developments in distributed hydrologic modeling, the over-parameterization is usually a critical issue that can complicate calibration process. Sensitivity analysis methods reducing the number of parameters to be adjusted during calibration are important for simplifying the use of these models. The objective of this paper is to perform a sensitivity analysis for flow in a semi-arid catchment (1,491 km2), located in northwestern of Tunisia, using the Soil and Water Assessment Tool (SWAT) model. The simulation results revealed that among eight selected parameters, curve number (CN2), soil evaporation compensation factor (ESCO), soil available water capacity (SOL_AWC) and threshold depth of water in the shallow aquifer required for return flow (GWQMN) were found to be the most sensitive parameters. Calibration of hydrology, facilitated by the sensitivity analysis, was performed for the period 2001 through 2003. Results of calibration showed that the model accurately predict runoff and performed well with a monthly Nash Sutcliffe efficiency (NSE) of 0,78, a coefficient of determination (R2) of 0,85 and a percent of bias (PBIAS) equal to −13,22 %.

Assessment of land-use change on streamflow using GIS, remote sensing and a physically-based model, SWAT

Abstract. This study aims to assess the impact of the land-use changes between the periods 1967−1974 and 1997−2008 on the streamflow of Tapacurá catchment (northeastern Brazil) using the Soil and Water Assessment Tool (SWAT) model. The results show that the most sensitive parameters were the baseflow, Manning factor, time of concentration and soil evaporation compensation factor, which affect the catchment hydrology. The model calibration and validation were performed on a monthly basis, and the streamflow simulation showed a good level of accuracy for both periods. The obtained R2 and Nash-Sutcliffe Efficiency values for each period were respectively 0.82 and 0.81 for 1967−1974, and 0.93 and 0.92 for the period 1997−2008. The evaluation of the SWAT model response to the land cover has shown that the mean monthly flow, during the rainy seasons for 1967−1974, decreased when compared to 1997−2008.

Application of SWAT Model for Hydrologic and Water Quality Modeling in Thachin River Basin, Thailand

The Soil and Water Assessment Tool (SWAT) model was examined for its applicability in modeling flow, sediments and water quality parameters in upper Thachin River Basin, Thailand covering an area of 5,693 km2. The calibration of flow, sediments, and water quality parameter have shown satisfactory results with R 2=0.77 and E NS coefficient = 0.78 for monthly flow calibration. The monthly flow validation values for R 2 and E NS were 0.8 and 0.79, respectively. Calibration of sediments and water quality parameter were poor due to the non-availability of time series data. Sensitivity analysis showed that curve number is the most sensitive parameter to surface runoff, evapotranspiration and sediment yield and consequently to total water yield. Soil evaporation compensation factor and average slope length (SLSUBBSN) were most sensitive to evapotranspiration and sediment routing, respectively. Muskingum routing factors (MSK_X, MSK_CO1 and MSK_CO2) were also found sensitive to average monthly flows. The study concluded that SWAT model has huge potential in studying hydrology of watersheds even under data scarcity. An adequately calibrated model can be employed for studying land use change scenarios and probable climate change impacts on basin hydrology depending on availability of data.

Application of semi‐distributed hydrological model for basin level water balance of the Ken basin of Central India

AbstractIn the present study, a semi‐distributed hydrological model soil and water assessment tool (SWAT) has been employed for the Ken basin of Central India to predict the water balance. The entire basin was divided into ten sub basins comprising 107 hydrological response units on the basis of unique slope, soil and land cover classes using SWAT model. Sensitivity analysis of SWAT model was performed to examine the critical input variables of the study area. For Ken basin, curve number, available water capacity, soil depth, soil evaporation compensation factor and threshold depth of water in the shallow aquifer (GWQ_MN) were found to be the most sensitive parameters. Yearly and monthly calibration (1985–1996) and validation (1997–2009) were performed using the observed discharge data of the Banda site in the Ken basin. Performance evaluation of the model was carried out using coefficient of determination, Nash–Sutcliffe efficiency, root mean square error‐observations standard deviation ratio, percent bias and index of agreement criterion. It was found that SWAT model can be successfully applied for hydrological evaluation of the Ken basin, India. The water balance analysis was carried out to evaluate water balance of the Ken basin for 25 years (1985–2009). The water balance exhibited that the average annual rainfall in the Ken basin is about 1132 mm. In this, about 23% flows out as surface run‐off, 4% as groundwater flow and about 73% as evapotranspiration. Copyright © 2013 John Wiley & Sons, Ltd.

제주도 남부지역의 유출 특성

Abstract For Kangjeong stream and Akgeun stream in the central part of the southern Jeju Island, on-site discharge estimation was carried out for approximately 10 months (July 2011-April 2012) twice a month on a regular basis by using ADCP (acoustic doppler current profiler) and long term rate of discharge was calculated by using SWAT (soil and water assessment tool) model. The discharge was 0.28-1.30 m 3 /sec for Kangjeong stream and 0.10-1.54 m 3 /sec for Akgeun stream. It showed the maximum in the summer and the minimum in the winter. As a result of parameter sensitivity analysis of SWAT model, CN (NRCS runoff curve number for moisture condition Ⅱ), SOL_AWC (available water capacity of the soil layer), and ESCO (soil evaporation compensation factor) showed sensitive responses. By using the result, the model was corrected and the rate of discharge was calculated. As a result, the annual discharge rate was 27.12-31.86(%) at the Akgeun basin and 23.55-28.43(%) at the Kangjeong basin.Key words: ADCP, SWAT, Sensitivity analysis, Jeju Island

How to improve the representation of hydrological processes in SWAT for a lowland catchment – temporal analysis of parameter sensitivity and model performance

AbstractModel diagnostic analyses help to improve the understanding of hydrological processes and their representation in hydrological models. A detailed temporal analysis detects periods of poor model performance and model components with potential for model improvements, which cannot be found by analysing the whole discharge time series.In this study, we aim to improve the understanding of hydrological processes by investigating the temporal dynamics of parameter sensitivity and of model performance for the Soil and Water Assessment Tool model applied to the Treene lowland catchment in Northern Germany. The temporal analysis shows that the parameter sensitivity varies temporally with high sensitivity for three groundwater parameters (groundwater time delay, baseflow recession constant and aquifer fraction coefficient) and one evaporation parameter (soil evaporation compensation factor). Whereas the soil evaporation compensation factor dominates in baseflow and resaturation periods, groundwater time delay, baseflow recession constant and aquifer fraction coefficient are dominant in the peak and recession phases. The temporal analysis of model performance identifies three clusters with different model performances, which can be related to different phases of the hydrograph. The lowest performance, when comparing six performance measures, is detected for the baseflow cluster. A spatially distributed analysis for six hydrological stations within the Treene catchment shows similar results for all stations.The linkage of periods with poor model performance to the dominant model components in these phases and with the related hydrological processes shows that the groundwater module has the highest potential for improvement. This temporal diagnostic analysis enhances the understanding of the Soil and Water Assessment Tool model and of the dominant hydrological processes in the lowland catchment. Copyright © 2013 John Wiley & Sons, Ltd.

Hydrology Evaluation of the Soil and Water Assessment Tool Considering Measurement Uncertainty for a Small Watershed in Southern Brazil

<abstract> Abstract. Areas under tobacco crop cultivation have impacted the water balance and have become sources of environmental contamination in Southern Brazil. Correct determination of the area’s hydrology is essential since it is the driving force of sediment and nutrient loading dynamics. The Soil and Water Assessment Tool (SWAT), version 2009, was used to evaluate hydrological processes for the Arroio Lino watershed, located in the Brazilian state of Rio Grande do Sul. The measured discharge at the watershed outlet was used to evaluate model streamflow sensitivity to selected parameters, and for calibration and validation from 2001 to 2005. A Latin Hypercube (LH) and One-factor-At-a-Time (OAT) sensitivity analysis was performed. Model calibration was performed with the Shuffled Complex Evolution Algorithm-Uncertainty Analysis (SCE-UA) combined with manual adjustment on model simulation results. Time series plots and standard statistical measures were used to verify model predictions. The statistical indicators were modified to reflect measurement uncertainty. The most sensitive parameters were curve number (CN2), soil evaporation compensation factor (ESCO), and baseflow alpha factor (ALPHA_BF). The predicted monthly streamflow matched the observed values with a Nash-Sutcliffe coefficient of 0.87 and 0.76 during calibration and validation, respectively. Daily indicators of goodness of fit were lower but improved when uncertainty of measured data was taken into account. The results suggest that the SWAT model is a promising tool to evaluate hydrology in Brazilian watersheds. However, especially in those watersheds with limited data availability, the evaluation of model goodness-of-fit needs to consider the uncertainty related to data measurements.

Evaluation of SWAT sub-daily runoff estimation at small agricultural watershed in Korea

A study was undertaken for the prediction of runoff flow from 0.8 ha field-sized agricultural watershed in South Korea using Soil and Water Assessment Tool (SWAT) sub-daily. The SWAT model with sub-daily configuration predicted flow from the watershed within the range of acceptable accuracy. The SWAT sub-daily simulations were carried out for a total of 18 rainfall events, 9 each for calibration and validation. Overall trend and extent of matching simulated flow for the rainfall events in 2007–2008 with measured data during the calibration process were coefficient of determination (R 2) value of 0.88 and Nash and Sutcliffe Efficiency (E NS) value of 0.88. For validation, R 2 and E NS values were 0.9 and 0.84, respectively. Whereas R 2 and E NS values for simulation results using daily rainfall data were 0.79 and −0.01, respectively, that were observed to be out of acceptable limits for the model simulation. The importance of higher time resolution (hourly) precipitation records for flow simulation were evaluated by comparing R 2 and E NS with 15 min, 2 h, 6 h and 12 h precipitation data, which resulted in lower statistics with increases in time resolution of precipitation data. The SWAT sub-daily sensitivity analysis was performed with the consideration of hydraulic parameter and was found as in the rank order of CN2 (curve number), ESCO (soil evaporation compensation factor), GW_DELAY (ground water delay time), ALPHA_BF (base flow alpha factor), GWQMN (a threshold minimum depth of water in the shallow aquifer required for return flow to occur), REVAPMN (minimum depth of water in shallow aquifer for re-evaporation to occur), LAT_TIME (lateral flow travel time) respectively. These sensitive parameters were evaluated at 10% higher and lower values of the parameters, corresponding to 70.5% higher and 23.2% lower in simulated flow out from the SWAT model. From the results obtained in this study, hourly precipitation record for SWAT sub-daily with Green-Ampt infiltration method was proven to be efficient for runoff estimation at field sized watershed with higher accuracies that could be efficiently used to develop sitespecific Best Management Practices (BMPs) considering rainfall intensity, rather than simply using daily rainfall data.

Influence of Scale on SWAT Model Calibration for Streamflow in a River Basin in the Humid Tropics

The Soil Water Assessment Tool (SWAT) was applied to the 2,530 km2 Chaliyar river basin in Kerala, India to investigate the influence of scale on the model parameters. The study was carried out in this river basin at two scales. Parameters such as land use, soil type, topography and management practices are similar at these scales. The model was initially calibrated for streamflow and then validated. Critical parameters were the curve number (CN2), soil evaporation compensation factor (ESCO), available water holding capacity (SOL_AWC), average slope length (SLSUBBSN), and base flow alpha factor (ALPHA_BF). Using the optimized value of various parameters, stream flow was estimated from parts of the basin at two different scales—an area of 2,361.58 km2 and an area of 1,013.15 km2. The streamflow estimates at both these scales were statistically analysed by computing the coefficient of determination (R 2) and the Nash–Sutcliffe efficiency (ENS). Results indicate that the SWAT model could simulate streamflow at both scales reasonably well with very little difference between the observed and computed values. However, the results also indicate that there may be greater uncertainty in SWAT streamflow estimates as the size of the watershed increases.

Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model

AbstractThe Soil and Water Assessment Tool (SWAT) was used to simulate the transport of runoff and sediment into the Miyun Reservoir, Beijing in this study. The main objective was to validate the performance of SWAT and the feasibility of using this model as a simulator of runoff and sediment transport processes at a catchment scale in arid and semi‐arid area in North China, and related processes affecting water quantity and soil erosion in the catchment were simulated. The investigation was conducted using a 6‐year historical streamflow and sediment record from 1986 to 1991; the data from 1986 to 1988 was used for calibration and that from 1989 to 1991 for validation. The SWAT generally performs well and could accurately simulate both daily and monthly runoff and sediment yield. The simulated daily and monthly runoff matched the observed values satisfactorily, with a Nash‐Sutcliffe coefficient of greater than 0·6, 0·9 and a coefficient of determination 0·75, 0·9 at two outlet stations (Xiahui and Zhangjiafen stations) during calibration. These values were 0·6, 0·85 and 0·6, 0·9 during validation. For sediment simulation, the efficiency is lower than that for runoff. Even so, the Nash‐Sutcliffe coefficient and coefficient of determination were greater than 0·48 and 0·6 for monthly sediment yield during calibration, and these values were greater than 0·84 and 0·95 during validation. Sensitivity analysis shows that sensitive parameters for the simulation of discharge and sediment yield include curve number, base flow alpha factor, soil evaporation compensation factor, soil available water capacity, soil profile depth, surface flow lag time and channel re‐entrained linear parameter, etc. Copyright © 2009 John Wiley &amp; Sons, Ltd.

Evaluation of SWAT Manual Calibration and Input Parameter Sensitivity in the Little River Watershed

The watershed-scale effects of agricultural conservation practices are not well understood. A baseline calibration and an input parameter sensitivity analysis were conducted for simulation of watershed-scale hydrology in the Little River Experimental Watershed (LREW) in the Coastal Plain near Tifton, Georgia. The Soil and Water Assessment Tool (SWAT) was manually calibrated to simulate the hydrologic budget components measured for the 16.9 km2 subwatershed K of the LREW from 1995 to 2004. A local sensitivity analysis was performed on 16 input variables. The sum of squares of the differences between observed and simulated annual averages for baseflow, stormflow, evapotranspiration, and deep percolation was 19 mm2; average annual precipitation was 1136 mm. The monthly Nash-Sutcliffe model efficiency (NSE) for total water yield (TWYLD) was 0.79 for the ten-year period. Daily NSE for TWYLD was 0.42. The monthly NSE for three years with above-average rainfall was 0.89, while monthly NSE was 0.59 for seven years with below annual average rainfall, indicating that SWAT's predictive capabilities are less well-suited for drier conditions. Monthly average TWYLD for the high-flow winter to early spring season was underpredicted, while the low-flow late summer to autumn TWYLD was overpredicted. Results were negatively influenced when seasonal tropical storms occurred during a dry year. The most sensitive parameters for TWYLD were curve number for crop land (CN2(crop)), soil available water content (SOL_AWC), and soil evaporation compensation factor (ESCO). The most sensitive parameters for stormflow were CN2(crop), curve number for forested land (CN2(forest)), soil bulk density (SOL_BD), and SOL_AWC. The most sensitive parameters for baseflow were CN2(crop), CN2(forest), ESCO, and SOL_AWC. Identification of the sensitive SWAT parameters in the LREW provides modelers in the Coastal Plain physiographic region with focus for SWAT calibration.