Calibration of snow parameters in SWAT: comparison of three approaches in the Upper Adige River basin (Italy)

The Soil and Water Assessment Tool (SWAT) model is generally applied in alpine catchments using a unique set of snow parameters for the entire basin, and calibration is based on discharge records only. This technical note presents three calibration procedures for snow parameters of SWAT considering snow water equivalent (SWE) values computed using a dense network of snow depth measurement stations available in the Upper Adige River basin, Italy. The first two procedures calibrate snow parameters according to the average sub-basin SWE: the first one defines a unique set of parameters for the entire basin, while the second allows for sub-basin variability. The last approach includes the elevation band SWE output in the calibration for each sub-basin and qualitatively compares it to the SWE computed from the available snow depth monitoring stations. This last method provides the best agreement between SWAT model results and SWE data.     

Hydrologic comparison between a forested and a wetland/lake dominated watershed using SWAT

The Soil and Water Assessment Tool (SWAT) is a physically‐based hydrologic model developed for agricultural watersheds, which has been infrequently validated for forested watersheds, particularly those with deep overwinter snow accumulation and abundant lakes and wetlands. The goal of this study was to determine the applicability of SWAT for modelling streamflow in two watersheds of the Ontonagon River basin of northern Michigan which differ in proportion of wetland and lake area. The forest‐dominated East Branch watershed contains 17% wetland and lake area, whereas the wetland/lake‐dominated Middle Branch watershed contains 26% wetland and lake area. The specific objectives were to: (1) calibrate and validate SWAT models for the East Branch and Middle Branch watersheds to simulate monthly stream flow, and (2) compare the effects of wetland and lake abundance on the magnitude and timing of streamflow. Model calibration and validation was satisfactory, as determined by deviation of discharge D and Nash and Sutcliffe coefficient values E that compared simulated monthly mean discharge versus measured monthly mean discharge. Streamflow simulation discrepancies occurred during summer and fall months and dry years. Several snow melting parameters were found to be critical for the SWAT simulation: TIMP (snow temperature lag factor) and SMFMX and SMFMN (melting factors). Snow melting parameters were not transferable between adjacent watersheds. Differences in seasonal pattern of long‐term monthly streamflow were found, with the forest‐dominated watershed having a higher peak flow during April but a lower flow during the remainder of the year in comparison to the wetland and lake‐dominated watershed. The results suggested that a greater proportion of wetland and lake area increases the capacity of a watershed to impound surface runoff and to delay storm and snow melting events. Representation of wetlands and lakes in a watershed model is required to simulate monthly stream flow in a wetland/lake‐dominated watershed. Copyright © 2007 John Wiley & Sons, Ltd.     

Evaluating the SWAT's snow hydrology over a Northern Quebec watershed

The snow treatment becomes an important component of Soil and Water Assessment Tool (SWAT)’s hydrology when spring flows are dominated by snow melting. However, little is known about SWAT's snow hydrology performance because most studies using SWAT were conducted in rainfall‐driven catchments. To fill this gap, the present study aims to evaluate the ability of SWAT in simulating snow‐melting‐dominated streamflow in the Outardes Basin in Northern Quebec. SWAT performance in simulating snowmelt is evaluated against observed streamflow data and compared to simulations from the operationally used Streamflow Synthesis and Reservoir Regulation (SSARR) model over that catchment. The SWAT 5‐year calibration showed a satisfactory performance at the daily and seasonal time scales with low volume biases. The SWAT validation was conducted over two (17‐year and 15‐year) periods. Performances were similar to the calibration period in simulating the daily and seasonal streamflows again with low model biases. The spring‐snowmelt‐generated peak flow was accurately simulated by SWAT both in magnitude and timing. When SWAT's results are compared to SSARR, similar performances in simulating the daily discharges were observed. SSARR simulates more accurately streamflow generated at the snowmelt onset whereas SWAT better predicts streamflow in summer, fall and winter. SWAT provided reasonable streamflow simulations for our snow‐covered catchment, but refinement of the process‐driven baseflow during the snowmelt onset could improve spring performances. Therefore, SWAT becomes an attractive tool for evaluating water resources management in Nordic environments when a distributed model is preferred or when water quality information (e.g. temperature) is required. Copyright © 2013 John Wiley & Sons, Ltd.     

Simulation of stream flow components in a mountainous catchment in northern Thailand with SWAT,using the ANSELM calibration approach

Highland agriculture is intensifying rapidly in South‐East Asia, leading to alarmingly high applications of agrochemicals. Understanding the fate of these contaminants requires carefully planned monitoring programmes and, in most cases, accurate simulation of hydrological pathways into and through water bodies. We simulate run‐off in a steep mountainous catchment in tropical South‐East Asia. To overcome calibration difficulties related to the mountainous topography, we introduce a new calibration method, named A Nash–Sutcliffe Efficiency Likelihood Match (ANSELM), that allows the assignment of optimal parameters to different hydrological response units in simulations of stream discharge with the Soil and Water Assessment Tool (SWAT) hydrological model. ANSELM performed better than the Parasol calibration tool built into SWAT in terms of model efficiency and computation time. In our simulation, the most sensitive model parameters were those related to base flow generation, surface run‐off generation, flow routing and soil moisture change. The coupling of SWAT with ANSELM yielded reasonable simulations of both wet‐season and dry‐season storm hydrographs. Nash–Sutcliffe model efficiencies for daily stream flow during two validation years were 0.77 and 0.87. These values are in the upper range or even higher than those reported for other SWAT model applications in temperate or tropical regions. The different flow components were realistically simulated by SWAT, and showed a similar behaviour in all the study years, despite inter‐annual climatic differences. The realistic partitioning of total stream flow into its contributing components will be an important factor for using this hydrological model to simulate solute transport in the future. Copyright © 2014 John Wiley & Sons, Ltd.     

Quantitative evaluation of different hydrological modelling approaches in a partly glacierized Swiss watershed

Mountain water resources management often requires hydrological models that need to handle both snow and ice melt. In this study, we compared two different model types for a partly glacierized watershed in central Switzerland: (1) an energy‐balance model primarily designed for snow simulations; and (2) a temperature‐index model developed for glacier simulations. The models were forced with data extrapolated from long‐term measurement records to mimic the typical input data situation for climate change assessments. By using different methods to distribute precipitation, we also assessed how various snow cover patterns influenced the modelled runoff. The energy‐balance model provided accurate discharge estimations during periods dominated by snow melt, but dropped in performance during the glacier ablation season. The glacier melt rates were sensitive to the modelled snow cover patterns and to the parameterization of turbulent heat fluxes. In contrast, the temperature‐index model poorly reproduced snow melt runoff, but provided accurate discharge estimations during the periods dominated by glacier ablation, almost independently of the method used to distribute precipitation. Apparently, the calibration of this model compensated for the inaccurate precipitation input with biased parameters. Our results show that accurate estimates of snow cover patterns are needed either to correctly constrain the melt parameters of the temperature‐index model or to ensure appropriate glacier surface albedos required by the energy‐balance model. Thus, particularly when only distant meteorological stations are available, carefully selected input data and efficient extrapolation methods of meteorological variables improve the reliability of runoff simulations in high alpine watersheds. Copyright © 2011 John Wiley & Sons, Ltd.     

Sensitivity and identifiability of stream flow generation parameters of the SWAT model

Implementation of sensitivity analysis (SA) procedures is helpful in calibration of models and also for their transposition to different watersheds. The reported studies on SA of Soil and Water Assessment Tool (SWAT) model were mostly focused on identifying parameters for pruning or modifying during the calibration process. This paper presents a sensitivity and identifiability analysis of model parameters that influence stream flow generation in SWAT. The analysis was focused on evaluating the sensitivity of the parameters in different climatic settings, temporal scales and flow regimes. The global sensitivity analysis (GSA) technique based on classical decomposition of variance, Sobol', was employed in this study. The results of the study indicate that modeled stream flow show varying sensitivity to parameters in different climatic settings. The results also suggest that the identifiability of a parameter for a given watershed is a major concern in calibrating the model for the specific watershed, as it might lead to equifinality of parameters. The SWAT model parameters show varying sensitivity in different years of simulation suggesting the requirement for dynamic updation of parameters during the simulation. The sensitivity of parameters during various flow regimes (low, medium and high flow) is also found to be uneven, which suggests the significance of a multi‐criteria approach for the calibration of models. Copyright © 2010 John Wiley & Sons, Ltd.     

Modelling the rainfall–runoff process of the Mara River basin using the Soil and Water Assessment Tool

The delicate balance between human utilization and sustaining its pristine biodiversity in the Mara River basin (MRB) is being threatened because of the expansion of agriculture, deforestation, human settlement, erosion and sedimentation and extreme flow events. This study assessed the applicability of the Soil and Water Assessment Tool (SWAT) model for long‐term rainfall–runoff simulation in MRB. The possibilities of combining/extending gage rainfall data with satellite rainfall estimates were investigated. Monthly satellite rainfall estimates not only overestimated but also lacked the variability of observed rainfall to substitute gage rainfall in model simulation. Uncertainties related to the quality and availability of input data were addressed. Sensitivity and uncertainty analysis was reported for alternative model components and hydrologic parameters used in SWAT. Mean sensitivity indices of SWAT parameters in MRB varied with and without observed discharge data. The manual assessment of individual parameters indicated heterogeneous response among sub‐basins of MRB. SWAT was calibrated and validated with 10 years of discharge data at Bomet (Nyangores River), Mulot (Amala River) and Mara Mines (Mara River) stations. Model performance varied from satisfactory at Mara Mines to fair at Bomet and weak at Mulot. The (Nash–Sutcliff efficiency, coefficient of determination) results of calibration and validation at Mara Mines were (0.68, 0.69) and (0.43, 0.44), respectively. Two years of moving time window and flow frequency analysis showed that SWAT performance in MRB heavily relied on quality and abundance of discharge data. Given the 5.5% area contribution of Amala sub‐basin as well as uncertainty and scarcity of input data, SWAT has the potential to simulate the rainfall runoff process in the MRB. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling snow water equivalent and spring runoff in a boreal watershed,James Bay,Canada

The hydrology of boreal regions is strongly influenced by seasonal snow accumulation and melt. In this study, we compare simulations of snow water equivalent (SWE) and streamflow by using the hydrological model HYDROTEL with two contrasting approaches for snow modelling: a mixed degree‐day/energy balance model (small number of inputs, but several calibration parameters needed) and the thermodynamic model CROCUS (large number of inputs, but no calibration parameter needed). The study site, in Northern Quebec, Canada was equipped with a ground‐based gamma ray sensor measuring the SWE continuously for 5 years in a small forest clearing. The first simulation of CROCUS showed a tendency to underestimate SWE, attributable to bias in the meteorological inputs. We found that it was appropriate to use a threshold of 2 °C to separate rain and snow. We also applied a correction to account for snowfall undercatch by the precipitation gauge. After these modifications to the input dataset, we noticed that CROCUS clearly overestimated the SWE, likely as a result of not including loss in SWE because of blowing snow sublimation and relocation. To correct this, we included into CROCUS a simple parameterisation effective after a certain wind speed threshold, after which the thermodynamic model performed much better than the traditional mixed degree‐day/energy balance model. HYDROTEL was then used to simulate streamflow with both snow models. With CROCUS, the main peak flow could be captured, but the second peak because of delayed snowmelt from forested areas could not be reproduced due to a lack of sub‐canopy radiation data to feed CROCUS. Despite the relative homogeneity of the boreal landscape, data inputs from each land cover type are needed to generate satisfying simulation of the spring runoff. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessing the impact of distributed snow water equivalent calibration and assimilation of Copernicus snow water equivalent on modelled snow and streamflow performance

Accuracy of the Copernicus snow water equivalent (SWE) product and the impact of SWE calibration and assimilation on modelled SWE and streamflow was evaluated. Daily snowpack measurements were made at 12 locations from 2016 to 2019 across a 4104 km² mixed-forest basin in the Great Lakes region of central Ontario, Canada. Sub-basin daily SWE calculated from these sites, observed discharge, and lake levels were used to calibrate a hydrologic model developed using the Raven modelling framework. Copernicus SWE was bias corrected during the melt period using mean bias subtraction and was compared to daily basin average SWE calculated from the measured data. Bias corrected Copernicus SWE was assimilated into the models using a range of parameters and the parameterizations from the model calibration. The bias corrected Copernicus product agreed well with measured data and provided a good estimate of mean basin SWE demonstrating that the product shows promise for hydrology applications within the study region. Calibration to spatially distributed SWE substantially improved the basin scale SWE estimate while only slightly degrading the flow simulation demonstrating the value of including SWE in a multi-objective calibration formulation. The particle filter experiments yielded the best SWE estimation but moderately degraded the flow simulation. The particle filter experiments constrained by the calibrated snow parameters produced similar results to the experiments using the upper and lower bounds indicating that, in this study, model calibration prior to assimilation was not valuable. The calibrated models exhibited varying levels of skill in estimating SWE but demonstrated similar streamflow performance. This indicates that basin outlet streamflow can be accurately estimated using a model with a poor representation of distributed SWE. This may be sufficient for applications where estimating flow is the primary water management objective. However, in applications where understanding the physical processes of snow accumulation, melt and streamflow generation are important, such as assessing the impact of climate change on water resources, accurate representations of SWE are required and can be improved via multi-objective calibration or data assimilation, as demonstrated in this study.     

Information content of snow hydrological signatures based on streamflow,precipitation and air temperature

Hydrological signatures that represent snow processes are valuable to gain insights into snow accumulation and snow melt dynamics. We investigated five snow signatures. Considering inter-annual average of each calendar day, two slopes derived from the relation between streamflow and air temperature for different periods and streamflow peak maxima are used as signatures. In addition, two different approaches are used to compute inter-annual average and yearly snow storage estimates. We evaluated the ability of these signatures to characterize average (a) snow melt dynamics and (b) snow storage. They were applied in 10 Critical Zone Observatory catchments of the Southern Sierra mountains (USA) characterized by a Mediterranean climate. The relevance and information content of the signatures are evaluated using snow depth and snow water equivalent measurements as well as inter-catchment differences in elevation. The slopes quantifying the relations between streamflow and air temperature and the date of streamflow peak were found to characterize snow melt dynamics in terms of snow melt rates and snow melt affected areas. Streamflow peak dates were linked to the period of highest snow melt rates. Snow storage could be estimated both on average, considering all years, and for each year. Snow accumulation dynamics could not be characterized due to the lack of streamflow response during the snow accumulation period. The signatures were found potentially valuable to gain insights into catchment scale snow processes. In particular, when comparing catchments or observed and simulated data, they could provide insights into differences in terms of (a) snow melt rate and/or snow melt affected area over the snow melt season and (b) average or yearly snow storage. Requiring only widely available data, these hydrological signatures can be valuable for snow processes characterization, catchment comparison/classification or model development, calibration or evaluation.     

The comparative study of multi‐site uncertainty evaluation method based on SWAT model

With the recent development of distributed hydrological models, the use of multi‐site observed data to evaluate model performance is becoming more common. Distributed hydrological model have many advantages, and at the same time, it also faces the challenge to calibrate over‐do parameters. As a typical distributed hydrological model, problems also exist in Soil and Water Assessment Tool (SWAT) parameter calibration. In the paper, four different uncertainty approaches – Particle Swarm Optimization (PSO) techniques, Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting algorithm (SUFI‐2) and Parameter Solution (PARASOL) – are taken to a comparative study with the SWAT model applied in Peace River Basin, central Florida. In our study, the observed river discharge data used in SWAT model calibration were collected from the three gauging stations at the main tributary of the Peace River. Behind these approaches, there is a shared philosophy; all methods seek out many parameter set to fit the uncertainties due to the non‐uniqueness in model parameter evaluation. On the basis of the statistical results of four uncertainty methods, difficulty level of each method, the number of runs and theoretical basis, the reasons that affected the accuracy of simulation were analysed and compared. Furthermore, for the four uncertainty method with SWAT model in the study area, the pairwise correlation between parameters and the distributions of model fit summary statistics computed from the sampling over the behavioural parameter and the entire model calibration parameter feasible spaces were identified and examined. It provided additional insight into the relative identifiability of the four uncertainty methods Copyright © 2014 John Wiley & Sons, Ltd.     

Spatial GR4J conceptualization of the Tamor glaciated alpine catchment in Eastern Nepal: evaluation of GR4JSG against streamflow and MODIS snow extent

Snow and glacial melt processes are an important part of the Himalayan water balance. Correct quantification of melt runoff processes is necessary to understand the region's vulnerability to climate change. This paper describes in detail an application of conceptual GR4J hydrological model in the Tamor catchment in Eastern Nepal using typical elevation band and degree‐day factor approaches to model Himalayan snow and glacial melt processes. The model aims to provide a simple model that meets most water planning applications. The paper contributes a model conceptualization (GR4JSG) that enables coarse evaluation of modelled snow extents against remotely sensed Moderate Resolution Imaging Spectroradiometer snow extent. Novel aspects include the glacial store in GR4JSG and examination of how the parameters controlling snow and glacial stores correlate with existing parameters of GR4J. The model is calibrated using a Bayesian Monte Carlo Markov Chain method against observed streamflow for one glaciated catchment with reliable data. Evaluation of the modelled streamflow with observed streamflow gave Nash Sutcliffe Efficiency of 0.88 and Percent Bias of <4%. Comparison of the modelled snow extents with Moderate Resolution Imaging Spectroradiometer gave R² of 0.46, with calibration against streamflow only. The contribution of melt runoff to total discharge from the catchment is 14–16% across different experiments. The model is highly sensitive to rainfall and temperature data, which suffer from known problems and biases, for example because of stations being located predominantly in valleys and at lower elevations. Testing of the model in other Himalayan catchments may reveal additional limitations. © 2016 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.     

Parameter identification and uncertainty analysis for simulating streamflow in a river basin of Eastern India

Uncertainty is inherent in modelling studies. However, the quantification of uncertainties associated with a model is a challenging task, and hence, such studies are somewhat limited. As distributed or semi‐distributed hydrological models are being increasingly used these days to simulate hydrological processes, it is vital that these models should be equipped with robust calibration and uncertainty analysis techniques. The goal of the present study was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for simulating streamflow in a river basin of Eastern India, and to evaluate the performance of salient optimization techniques in quantifying uncertainties. The SWAT model for the study basin was developed and calibrated using Parameter Solution (ParaSol), Sequential Uncertainty Fitting Algorithm (SUFI‐2) and Generalized Likelihood Uncertainty Estimation (GLUE) optimization techniques. The daily observed streamflow data from 1998 to 2003 were used for model calibration, and those for 2004–2005 were used for model validation. Modelling results indicated that all the three techniques invariably yield better results for the monthly time step than for the daily time step during both calibration and validation. The model performances for the daily streamflow simulation using ParaSol and SUFI‐2 during calibration are reasonably good with a Nash–Sutcliffe efficiency and mean absolute error (MAE) of 0.88 and 9.70 m³/s for ParaSol, and 0.86 and 10.07 m³/s for SUFI‐2, respectively. The simulation results of GLUE revealed that the model simulates daily streamflow during calibration with the highest accuracy in the case of GLUE (R² = 0.88, MAE = 9.56 m³/s and root mean square error = 19.70 m³/s). The results of uncertainty analyses by SUFI‐2 and GLUE were compared in terms of parameter uncertainty. It was found that SUFI‐2 is capable of estimating uncertainties in complex hydrological models like SWAT, but it warrants sound knowledge of the parameters and their effects on the model output. On the other hand, GLUE predicts more reliable uncertainty ranges (R‐factor = 0.52 for daily calibration and 0.48 for validation) compared to SUFI‐2 (R‐factor = 0.59 for daily calibration and 0.55 for validation), though it is computationally demanding. Although both SUFI‐2 and GLUE appear to be promising techniques for the uncertainty analysis of modelling results, more and more studies in this direction are required under varying agro‐climatic conditions for assessing their generic capability. Copyright © 2015 John Wiley & Sons, Ltd.     

Testing a spatially distributed tracer‐aided runoff model in a snow‐influenced catchment: Effects of multicriteria calibration on streamwater ages

Integrating stable isotope tracers into rainfall‐runoff models allows investigation of water partitioning and direct estimation of travel times and water ages. Tracer data have valuable information content that can be used to constrain models and, in integration with hydrometric observations, test the conceptualization of catchment processes in model structure and parameterization. There is great potential in using tracer‐aided modelling in snow‐influenced catchments to improve understanding of these catchments' dynamics and sensitivity to environmental change. We used the spatially distributed tracer‐aided rainfall‐runoff (STARR) model to simulate the interactions between water storage, flux, and isotope dynamics in a snow‐influenced, long‐term monitored catchment in Ontario, Canada. Multiple realizations of the model were achieved using a combination of single and multiple objectives as calibration targets. Although good simulations of hydrometric targets such as discharge and snow water equivalent could be achieved by local calibration alone, adequate capture of the stream isotope dynamics was predicated on the inclusion of isotope data in the calibration. Parameter sensitivity was highest, and most local, for single calibration targets. With multiple calibration targets, key sensitive parameters were still identifiable in snow and runoff generation routines. Water ages derived from flux tracking subroutines in the model indicated a catchment where runoff is dominated by younger waters, particularly during spring snowmelt. However, resulting water ages were most sensitive to the partitioning of runoff sources from soil and groundwater sources, which was most realistically achieved when isotopes were included in the calibration. Given the paucity of studies where hydrological models explicitly incorporate tracers in snow‐influenced regions, this study using STARR is an important contribution to satisfactorily simulating snowpack dynamics and runoff generation processes, while simultaneously capturing stable isotope variability in snow‐influenced catchments.     

Studying the effect of different approaches to estimating model parameters on the accuracy of river runoff simulation by SWAP model

Different approaches to estimating the parameters of SWAP physically based model, which describes heat and water transfer processes in the soil-vegetaion (snow) cover-atmosphere system are examined. In particular, two methods of a priori estimation of parameter values and two variants of their calibration are discussed. The parameter sets obtained by different methods were used to simulate the runoff from 12 experimental catchments in the eastern USA. The calculations were conducted for a 39-year period (1960–1998) with a 3-hour step. The results of calculations were compared with each other and with measured river runoff values in order to identify the parameter set that is optimal for runoff evaluation. A strategy is proposed for a priori parameter estimation in the case of basins where observational data are too poor to enable parameter calibration.     

Multi‐site evaluation of hydrology component of SWAT in the coastal plain of southwest Georgia

Simulation of watershed scale hydrologic and water quality processes is important for watershed assessments. Proper characterization of the accuracy of these simulations, particularly in cases with limited observed data, is critical. The Soil & Water Assessment Tool (SWAT) is frequently used for watershed scale simulation. The accuracy of the model was assessed by extrapolating calibration results from a well studied Coastal Plain watershed in Southwest Georgia, USA, to watersheds within the same geographic region without further calibration. SWAT was calibrated and validated on a 16.7‐km² subwatershed within the Little River Experimental Watershed by varying six model parameters. The optimized parameter set was then applied to a watershed of similar land use and soils, a smaller watershed with different land use and soils and three larger watersheds within the same drainage system without further calibration. Simulation results with percent bias (PB) ±15% ≤ PB < ±25% and Nash–Sutcliffe efficiency (NSE) 0.50 < NSE ≤ 0.65 were considered to be satisfactory, whereas those with PB < ±10% and 0.75 < NSE ≤ 1.00 were considered very good. With these criteria, simulation results for the five non‐calibration watersheds were satisfactory to very good. Differences across watersheds were attributed to differences in soils, land use, and surficial aquifer characteristics. These results indicate that SWAT can be a useful tool for predicting streamflow for ungauged watersheds with similar physical characteristics to the calibration watershed studied here and provide an indication of the accuracy of hydrologic simulations for ungauged watersheds. Copyright © 2012 John Wiley & Sons, Ltd.     

A parameter allocation approach for flow simulation using the WetSpa-Python model

Hydrologic models are simplified representations of natural hydrologic systems. Since these models rely on assumptions and simplifications to capture some aspects of hydrological processes, calibration of parameters is unavoidable. However, utilizing the philosophy of a recent modelling framework proposed by Bahremand (2016), we show how calibration of most model parameters can be avoided by allocating or presetting these parameters utilizing knowledge gained from sensitivity analyses, field observations and a priori specifications as a part of a parameter allocation procedure. This paper details the simulation of daily river flow of the Shemshak-Roudak watershed performed using the Python version of the WetSpa model. The WetSpa-Python model is a distributed model of hydrological processes applied at the watershed scale. The model was applied to the Shemshak-Roudak watershed of Iran with parameter allocation. Model calibration involved only two parameters. Straightforward methods were proposed for allocating model parameters, including three baseflow-related parameters and the determination of maximum active groundwater storage using a mass curve technique. Also, the Budyko curve was used to constrain a correction factor for potential evapotranspiration. The WetSpa-Python model was extended to include the influence of snowmelt. A failure to include snow in the hydrological processes of the WetSpa-Python model creates a significant discrepancy between the observed and simulated hydrographs during the spring. The results of daily simulations for 12 years (2002–2014) are in good agreement with observations of discharge (Kling-Gupta Efficiency = 0.84). These results demonstrate that it is feasible to simulate hydrographs with limited calibration given a knowledge of hydrological processes and an understanding of relationships between catchment characteristics and model parameters.     

Hydrological modelling of Ethiopian catchments using limited data

The hydrological component of the soil and water assessment tool (SWAT) model is adapted for two Ethiopian catchments based on primary knowledge of the coherence spectrum between rainfall and stream flow data. Spectrum analysis using the available nearby climatic data is made to limit the temporal and spatial scales (inverse rate coefficients) subject to the calibration of compartmentalized runoff models. The exclusion of unwarranted time scales in the calibration implies that the model efficiency (r² values) decrease only moderately between calibration and validation, and the optimization is focused on warranted problems. On the basis of the available data for the two Ethiopian catchments, the implication is that only periods longer than about 50 days can be reliably evaluated in the model. The model structure of SWAT for the surface runoff and groundwater flow response is modified to make the time scales consistent with the results of the spectrum analysis. An optimization algorithm is developed to constrain and combine the model parameters with the spectrum analysis results. Copyright © 2009 John Wiley & Sons, Ltd.     

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

The 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 & Sons, Ltd.     

SWAT-based runoff and sediment simulation in a small watershed,the loessial hilly-gullied region of China:capabilities and challenges

Model calibration and validation are necessary before applying it for scenario assessment and watershed management.This study presented the methodology of evaluating Soil and Water Assessment Tool(SWAT) and tested the feasibility of SWAT on runoff and sediment load simulation in the Zhifanggou watershed located in hilly-gullied region of China.Daily runoff and sediment event data from 1998-2008 were used in this study;data from 1998-2003 were used for calibration and 2004-2008 for validation.The evaluation statistics for the daily runoff simulation showed that the model results were acceptable,but the model underestimated the runoff for high-flow events.For sediment load simulation,the SWAT performed well in capturing the trend of sediment load,while the model tended to underestimate sediment load during both the calibration and validation periods. The disparity between observed and simulated data most likely resulted from limitations of the existing SCS-CN and MUSLE methods in the model.This study indicated that the modification of SWAT components is needed to take rainfall intensity and its duration into account to enhance the model performance on peak flow and sediment load simulation during heavy rainfall season.