Performance Of SWAT Model Research Articles

Improve the capability of physical model for runoff and sediment yield modelling with a hybrid artificial intelligence-based error updating system

Uncertainty of physical models is caused by the model's complexity as well as the accuracy of input variables. In present study, an error update model was developed based on artificial intelligence, namely Wavelet Multilayer Perceptron (WMLP), Wavelet Support Vector Machine (WSVM), Wavelet Multilayer Perceptron-Genetic Algorithm (WMLP-GA), and Wavelet Support Vector Machine-Genetic Algorithm (WSVM-GA). Sensitivity findings demonstrate that groundwater recession factor (ALPHA_BF), plant uptake compensation factor (EPCO), and curve number were the most sensitive for runoff in the Shivnath River basin, India, as well as four distinctparameters were shown to be highly sensitive to sediment yield at the Sigma station. During the calibration and validation phase, the SWAT model overpredicts runoff at the Simga and Pathardhi stations while underpredicting it at the Kotni station. SWAT model performance for runoff modelling is enhanced via the use of statistical indicators like as Percent of Bias (PBIAS) decreased from −35.355 to −20.503, Root Mean Square Error (RMSE) decreased from 319.905 to 25.191 m3/sec, and coefficient of determination increase from 0.712 to 0.904. At Simga station, the Nash–Sutcliffe efficiency (NSE) increase from 0.315 to 0.745, the PBIAS decreased from −39.502 to –22.946, the RMSE decreased from 186.711 to 24.432 m3/sec, and the coefficient of determination increased from 0.733 to 0.996. Further, NSE increased from 0.305 to 0.985 at Kotni station and PBIAS reduced from −114.026 to −9.214, RMSE reduced from 82.205 to 31.082 m3/sec, coefficient of determination increased from 0.779 to 0.976, NSE increased from 0.523 to 0.927 at Pathardhi station after applying an error update model. For sediment yield prediction, similar outcomes to runoff were obtained. The WSVM-GA model was reported to be the optimum error update model both for runoff and sediment yield modelling. It was recommended that the SWAT model might be applied for runoff and sediment yield simulation in the future.

Evaluation of land use/land cover effect on streamflow: a case of Robigumero watershed, Abay Basin, Ethiopia

Land use land cover change has an impact on hydrology of the watershed on the Robigumero watershed. The study mainly focused on estimating land use change and stream flow under different land use land cover changes of the Robigumero watershed. Land use land cove maps of 1996, 2006 and 2016 were collected from Ethiopian water irrigation and energy office. The soil and water assessment tool model (SWAT) was used to simulate LULC effects on the streamflow of Robigumero Watershed. The SWAT model performance was evaluated through sensitivity analysis, calibration, and validation. During the study period the land use land cover has changed due to growth in population of the study area. The Agricultural land increased by 22.4% and while grass land & forestland decreased by 17.5 and 5.3% Respectively in the year between 1996 to 2016. The findings of the stream flow simulation were used to assess the seasonal variability in stream flow caused by changes in land use and land cover. Both the calibration and validation result shows very good agreement between observed and simulated stream flow with NSE values of 0.81 and R2 values of 0.83 for calibration and NSE Values of 0.86 and R2 values of 0.87 for validation. The result of this study indicated that mean monthly stream flow were increased by 44.1m3/s for wet season and decreased by 2.3m3/s in dry season over 21 years’ period. In general redaction of agricultural land and increment of forest land on the degraded land reduce stream flow which shows the reduction of soil erosion. Therefore, this study results can be used to encourage different users and policymakers for planning and management of water resources in the Robigumero watershed as well as in other regions of Ethiopia.Graphical abstract

Comparison of SWAT and HEC-HMS model performance in simulating catchment runoff

Globally, surface water sources are important sources of drinking water and knowledge on their availability and sustainability is important for their protection. Such studies in data-poor regions are very limited. This paper compares the performance of SWAT and HEC-HMS in the event and continuous modeling of rainfall–runoff in two tropical catchments, a low laying and a mountainous one. Model calibration and validation were done using observed streamflow data at Busiu station for Manafwa and at Sezibwa falls for Sezibwa for the period 2000–2013. The results were compared based on objective functions and also the t-test was used to test the statistical significance of the difference in performance. The results show that HEC-HMS performed better than SWAT in Manafwa catchment (p = .003 and p = .000 during calibration and validation, respectively) while in Sezibwa the difference in model performance was not statistically significant (p = .63) although, during calibration, HEC-HMS performed better (p = .01).

The Effect of Spatial Input Data Quality on the Performance of the SWAT Model

Soil and land use information are important inputs for physically-based hydrological modeling such as SWAT. Although fine resolution local or regional data are often preferred for modeling, it is not always reliable that these data can lead to better model performance. In this study, we investigate the effect of input data on the sensitivity and uncertainty of the SWAT model in the Porijõgi catchment in Estonia. We created four model setups using global/regional level data (HWSD soil and CORINE) and local high-resolution spatial data, including the Estonian high-resolution EstSoil-EH soil dataset and the Estonian Topographic Database (ETAK). We employed statistical criteria to assess SWAT model performance for monthly simulated stream flows from 2007 to 2019. The results illustrated that models with high-resolution local soil data performed lower than models with global soil data, but in contrast, in the case of land use datasets, the local high-resolution ETAK dataset improved performance over the CORINE data.

Hydrological modeling, impact of land-use and land-cover change on hydrological process and sediment yield; case study in Jedeb and Chemoga watersheds

Land use and land cover changes in the Jedeb and Chemoga watersheds have been detected in the past 29 years. The study used ERDAS IMAGINE 2015 tools to classify landsat 5 TM, landsat satellite images for the preparation of the year 1990, 2000, 2009 and 2018 land use class maps through likelihood supervised classification techniques. The SWAT model has been used to determine the seasonal variability of streamflow and sediment yield due to land use and land cover changes in the watersheds. To calibrate and validate streamflow and sediment yields as well as to test SWAT model performance SWAT-CUP SUFI 2 algorithm was used. The outcome showed that 29 years generalized shift of 62.3% increase in farm land, 57.8% decrease in forest cover, 52.4% decrease in grass land, 64.2% decrease in shrub land, 145.2% increase in bare land and 46.5 percent increase in Jedeb watershed settlement. Similarly, the analysis showed that 47.3% increase in farm land, 81.8% decrease in forest cover, 148.9% increase in grass land, 89% decrease in shrub land, 10.7% increase in bare land and 96.9% decrease in Chemoga watershed water body. The average monthly flow of Jedeb watershed flows increased by 39.31 m3 / s from 1990 to 2009 and decreased by 17.19 m3 / s from 2009 to 2018. In Chemoga watershed average monthly streamflow increase between 1990 and 2009 in 36.73 m3 / s but decrease between 2009 and 2018 in 37.77 m3 / s. The average monthly Jedeb watershed sediment yield decreased by 204.59 ton / month from 1990 to 2000, increased by 15,962.76 ton / month from 2000 to 2009 and ultimately decreased by 9,012.83 ton / month from 2009 to 2018. Average monthly sediment rises in Chemoga watershed from 1990 to 2000 at 13,618.72 ton / month, decreased by 11,316.6 ton / month from 2000 to 2009 but increased by 11,192.93 ton / month from 2009 to 2018. The result indicates a strong agreement between observed ad simulated streamflow and sediment yield during calibration and validation, with a minimum result of R2=0.68 and NSE=0.54 and a maximum of R2=0.88 and NSE=0.84. The model performs well in estimating streamflow and sediment yield Jedeb and Chemoga watersheds. Therefore, special attention should be needed for Jedeb watershed for sustainable water resource management.

Performance of SWAT Model in Quantitative and Qualitative Simulation of Runoff and Watershed Protective Measures in Zarrinehrood Basin

Performance of SWAT Model in Quantitative and Qualitative Simulation of Runoff and Watershed Protective Measures in Zarrinehrood Basin

Evaluation of the Performance of SWAT Model to Simulate Stream Flow of Mojo River Watershed: In the Upper Awash River Basin, in Ethiopia

The assessment of the accessibility of water in the basin and significance setting of its use is essential before planning for the expansion and development of additional sectors which poses pressure on water availability. The main purpose of this study was to evaluate the performance of SWAT model to simulate stream flow of Mojo River. The performance evaluation of the model was to obtain the water balances was conducted. In this study both secondary and primary data were used. The SWAT model was used for data analysis. In this study for stream flow yield simulation the parameters involving surface runoff (CN2.mgt) and ground water (ALPHA_BNK.rte was found to be the most sensitive parameters. A good agreement between observed and simulated discharge were observed, which was verified using both graphical technique and quantitative statistics. The value of R2=0.80, NSE=0.75, RSR=0.5 and PBIAS=-10.6 obtained during calibration and R2 value 0.76, NSE value 0.69, RSR value 0.56 and PBIAS -14.4 obtained during validation as well as the uniformly scatter points along the 1:1 line during calibration and validation justify that the model is very good in simulating observed steam flow. From the results the total annual surface water available yields is estimated around 0.401Billion Cubic Meters (BCM).

Evaluation of multisite performance of SWAT model in the Gomti River Basin, India

The basin was calibrated through monthly discharge for the period (2002–2008) including 2 years as warm-up (2000–2001), after that model was validated on 5 years of hydrometeorological datasets (2009–2013) at two gauge sites located at Neemsar (upstream gauge) and Lucknow (downstream gauge). It is found that the most sensitive parameter for moisture condition II (CN2) was initial curve number. The p-factor and r-factor were obtained in calibration period at Neemsar 0.73 and 0.58 while at Lucknow values are 0.79 and 0.51, whereas in validation period values are 0.61, 0.45 and 1.22, 0.75, respectively. Three statistical parameters have been used to evaluate the SWAT model performance such as Coefficient of Determination (R2), Nash–Sutcliff efficiency (NSE), percent bias (PBIAS). The NSE and R2 values were observed as 0.85, 0.84 and 0.87, 0.86, respectively, in the time of calibration period and values is 0.76, 0.76 and 0.79, 0.83, respectively, in the time of validation period at two above said gauging stations. The PBIAS values during calibration and validation period are − 13.3, − 14.7 and − 4.0, − 15.7, respectively, at the same gauge site which indicates good model performance result.

Impacts of Dem Source, Resolution and Area Threshold Values on SWAT Generated Stream Network and Streamflow in Two Distinct Nepalese Catchments

This study explores the relationship of Digital Elevation Model (DEM) resolution and flow accumulation threshold value to watershed characteristics and streamflow in two Nepalese catchments, Kaligandaki and Bagmati basin. DEMs from three different sources: ASTER Global DEM v2, SRTM v4.1, and Contour of Nepal, with resolutions of 30 m, 90 m, and 250 m were used. Automatic watershed delineation in SWAT was used to derive the stream network, and basin and flow characteristics at different DEM scenarios. It is found that DEM source and resolution influence basin characteristics and stream network morphology. The assumption that SWAT model performance improves with an increase in DEM resolution did not hold true. All the models were equally efficient in predicting the runoff. The model performance for both basins was similar regardless of the origin of the DEM. NSE and R2 varied in the range 0.726–0.781 and 0.772–0.81, respectively, for Kaligandaki basin. Similarly, for Bagmati basin, NSE and R2 varied in the range 0.772–0.837 and 0.779–0.839, respectively. The drainage density and simulated flow got better when the threshold area was decreased. However, the model ceased to improve any further after the optimum value of the threshold area. Our results indicate that DEM of higher resolution (30 m or finer) needs to be used to model the catchment in SWAT accurately and appropriate threshold area needs to be used for best model performance based on the temporal sensitivity of the runoff.

Evaluation and application of a SWAT model to assess the climate change impact on the hydrology of the Himalayan River Basin

The water resources of Tamor River Basin in the eastern Himalayas of Nepal is heavily tapped for agricultural water use and hydropower production. Several studies show that the hydrology of the Himalayan River Basins is vulnerable to climate change. Topographical variations, data scarcity and its complex climate have always been barriers to achieving realistic simulation of the hydrological regime in the Himalayan River Basins, and the Tamor River Basin is no different. In hydrological response unit (HRU) based models, fixing the number of HRUs and sub-basins has a tendency towards confusion. This is especially true in regions with altitudinal and climatic variations. Therefore, this study aims to evaluate the SWAT model performance uncertainty associated with the number of sub-basins, HRUs, and elevation bands and quantify the impact of climate change on streamflows in the Tamor River Basin. Future climate scenarios were developed for three different time frames, the 2030s, 2060s, and 2080s, based on an ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) and four Regional Climate Models (RCMs) under the Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios. The linear scaling method (LSM) of bias correction was used to bias-correct the climate data and then fed into the SWAT model to simulate the future streamflows of the basin. An increase in the annual average maximum temperature (+4 °C) and minimum temperature (+5.5 °C), and a decrease in precipitation (−4.5%) is projected by the end of the twenty-first century under RCP8.5 scenarios. The study found that the future climate could decrease the streamflow by over 8.5% during the twenty-first century under RCP8.5 scenarios. The results show elevation bands (EBs) to be more significant compared to HRUs and sub-basins (SBs) in getting a robust hydrological model in the Himalayan region. The estimates prepared in this study would be beneficial for hydropower developers, planners and policymakers, and water resource managers in developing adaptation strategies to offset the negative impact of climate change in the Tamor River Basin.

Comparison of the performance of SWAT, IHACRES and artificial neural networks models in rainfall-runoff simulation (case study: Kan watershed, Iran)

The catchment area is essentially a heterogeneous dynamic, time and space hydrological system, and so the process of rainfall-runoff transmission in the catchment area is a very complex phenomenon. The temporal and spatial changes in the catchment characteristics, uncertainties in rainfall patterns, and a large number of parameters that alter the rainfall in to runoff, are the main sources of complexity in such relationships. Hydrological models are vital and exigent tools for water resources and environmental planning and management. In present study three models of SWAT, IHACRES and ANN were used on a daily, monthly and annual basis in the Kan watershed, which located in the west part of Tehran, Iran. The results showed that the performance of the three considered models are generally suitable for rainfall-runoff process simulation, however, ANN model showed a better performance for daily, monthly, and annual flow simulations compared with other two models (NSE = 0.86, R2 = 0.87, RMSE = 2.2, MBE = 0.08), and particularly for the simulation of maximum and minimum flow values. In addition, the performance of SWAT model (NSE = 0.65, R2 = 0.68, RMSE = 3.3, MBE = −0.168) was better than the IHACRES model (NSE = 0.57, R2 = 0.58, RMSE = 3.7, MBE = 0.049). However, the results of the IHACRES model were still acceptable.

Investigating Spatial and Temporal Variation of Hydrological Processes in Western China Driven by CMADS

The performance of hydrological models in western China has been restricted due to the scarcity of meteorological observation stations in the region. In addition to improving the quality of atmospheric input data, the use hydrological models to analyze Hydrological Processes on a large scale in western China could prove to be of key importance. The Jing and Bortala River Basin (JBR) was selected as the study area in this research. The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) is used to drive SWAT model, in order to greatly improve the accuracy of SWAT model input data. The SUFI-2 algorithm is also used to optimize 26 sensitive parameters within the SWAT-CUP. After the verification of two runoff observation and control stations (located at Jing and Hot Spring) in the study area, the temporal and spatial distribution of soil moisture, snowmelt, evaporation and precipitation were analyzed in detail. The results show that the CMADS can greatly improve the performance of SWAT model in western China, and minimize the uncertainty of the model. The NSE efficiency coefficients of calibration and validation are controlled between 0.659–0.942 on a monthly scale and between 0.526–0.815 on a daily scale. Soil moisture will reach its first peak level in March and April of each year in the JBR due to the snow melting process in spring in the basin. With the end of the snowmelt process, precipitation and air temperature increased sharply in the later period, which causes the soil moisture content to fluctuate up and down. In October, there was a large amount of precipitation in the basin due to the transit of cold air (mainly snowfall), causing soil moisture to remain constant and increase again until snowmelt in early spring the following year. This study effectively verifies the applicability of CMADS in western China and provides important scientific and technological support for the spatio-temporal variation of soil moisture and its driving factor analysis in western China.

Analisis Respon Hidrologi dan Kualitas Air DAS Cisangkuy

DAS Cisangkuy memiliki peran penting sebagai penyangga lingkungan dan pemasok air untuk Kota Bandung dan Kabupaten Bandung. Kuantitas dan kualitas air sungai perlu dipertahankan untuk memenuhi kebutuhan air. Penelitian ini bertujuan untuk menganalisis kinerja model SWAT untuk memprediksi respon hidrologi dan kualitas air DAS Cisangkuy dan untuk menganalisis respon hidrologi dan kualitas air dari skenario pengelolaan penggunaan lahan yang tersirat. Metode yang digunakan adalah permodelan dengan model hidrologi SWAT. Hasil penelitian menunjukkan bahwa model tersebut dapat digunakan untuk memprediksi respon hidrologi DAS Cisangkuy dengan nilai kalibrasi NSE sebesar 0.38 (memuaskan) dan nilai validasi NSE sebesar 0.43 (memuaskan). Pembentukan kawasan hutan lindung, Desain Teknis Rehabilitasi Lahan dan Hutan (RTk-RHL) dan skenario agroforestri berbasis kopi menunjukkan penurunan aliran permukaan, peningkatan aliran lateral dan aliran dasar. Respons hidrologi skenario RTRW menunjukkan peningkatan aliran permukaan dan penurunan aliran lateral dan aliran basa. Penurunan tertinggi konten N-organik, NO3, NH4, dan NO2 ditunjukkan oleh implikasi skenario RTRW.

Evaluation of static and dynamic land use data for watershed hydrologic process simulation: A case study in Gummara watershed, Ethiopia

Land Use Land Cover (LULC) change significantly affects hydrological processes. Several studies attempted to understand the effect of LULC change on biophysical processes; however, limited studies accounted dynamic nature of land use change. In this study, Soil and Water Assessment Tool (SWAT 2012) hydrological model and statistical analysis were applied to assess the impacts of land use change on hydrological responses such as surface runoff, evapotranspiration, and peak flow in Gummara watershed, Ethiopia. Moreover, the effects of static and dynamic land use data application on the SWAT model performance were evaluated. Two model setups, Static Land Use (SLU) and Dynamic Land Use (DLU), were studied to investigate the effects of accounting dynamic land use on hydrological responses. Both SLU and DLU model setups used the same meteorological, soil, and DEM data, but different land use. The SLU setup used the 1985 land use layer, whereas the DLU setup used 1985, 1995, 2005, and 2015 land use data. The calibration (validation) results showed that the model satisfactorily predicts temporal variation and peak streamflow with Nash Sutcliffe Efficiency (NSE) of 0.75 (0.71) and 0.73 (0.71) in the DLU and SLU setups, respectively. However, the DLU model setup simulated the detailed biophysical processes better during the calibration period. Both model setups equally predicted daily streamflow during the validation period. Better performance was obtained while applying the DLU model setup because of improved representation of the dynamic watershed characteristics such as curve number (CN2), overland Manning's (OV_N), and canopy storage (CANMX). Expansion of agricultural land use by 11.1% and the reduction of forest cover by 2.3% during the period from 1985 to 2015 increased the average annual surface runoff and peak flow by 11.6 mm and 2.4 m3/s, respectively and decreased the evapotranspiration by 5.3 mm. On the other hand, expansion of shrubland by 1% decreased the surface runoff by 1.2 mm and increased the evapotranspiration by 1.1 mm. The results showed that accounting DLU into the SWAT model simulation leads to a more realistic representation of temporal land use changes, thereby improving the accuracy of temporal and spatial hydrological processes estimation.

Simulating surface flow and baseflow in Poko catchment, Kon Tum province, Vietnam

Abstract Estimating the volume of water resources has important significance in assessing water availability in a basin, particularly in mountainous areas. The Poko catchment, a sub-basin of Se San river basin, is located in the Central Highland of Vietnam with an area of about 3,210 km2. This study focused on evaluating the performance of SWAT model and baseflow filtering algorithm in simulating surface flow and baseflow in Poko catchment. The model was calibrated and validated for the period 1996–2004 and 2005–2013, respectively, using the observed water discharge data at Dak Mot stream gauge. Statistical measures including R2 (coefficient of determination), NSI (Nash–Sutcliffe index), and PBIAS (percent bias) indicated good performance of the model in simulating water discharge on monthly time step during the calibration and validation period. Using baseflow filtering algorithm with filter parameter (0.925), surface flow and baseflow were separated from water discharge. The results demonstrated good performance in capturing the patterns of surface flow and baseflow, which confirmed the appropriateness of the model for future scenario simulation. These findings provide useful information for water resources planning in Poko catchment, in particular, and other basins, which have a hydro-meteorological response similar to this catchment, in general.

Integrated water resources management under climate change scenarios in the sub-basin of Abaya-Chamo, Ethiopia

In this study, the impact of climate change on surface water availability and its allocation system was carried out within Bilate watershed in the Abaya-Chamo sub-basin of Rift Valley Lakes Basin in Ethiopia. Predicted rainfall and temperature time series data were obtained from regional climate outputs of Coordinated Regional Climate Downscaling Experiment (CORDEX)-Africa for the three representative concentration pathways (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) for the four time periods (2015–2020, 2021–2025, 2026–2030 and 2031–2035). The result revealed that the future maximum and minimum temperature can be increased during all three scenarios. However, precipitation showed an increase or decreasing trend in future scenarios at different time scales. Further, SWAT model was calibrated and validated to simulate the future streamflow under RCP2.6 and RCP8.5 scenarios. WEAP model was employed for integrated water resources allocations under selected climate change scenarios. The SWAT model performance was found satisfactory during calibration [correlation coefficient (R2) = 0.77, Nash–Sutcliffe efficiency (NSE) = 0.755, percent deviation (D) = 2.558] and validation period (R2 = 0.798, NSE = 0.778, D= − 3.93). The model output shows that there may be an annual decrease in flow upto − 12.1 and − 16.21% for RCP2.6 and RCP8.5 scenarios. The annual surface water availability was found to be 570 million cubic meter (MCM) in the Bilate watershed for the current accounted year 2015. However, the current utilization of these resources is very limited about 51.49 MCM (9.03%) in the basin including domestic, livestock and minor agricultural activities. Furthermore, four scenarios were developed based on different set of assumptions in the basin up to 2035. It was estimated that total annual consumption will be around 14.53, 20.43, 37.47 and 44.46% for the reference, scenario one, two and three, respectively. This study also determines the environmental flow requirements (25% of the mean annual flow volume) to maintain the basic ecological functioning in the basin and regulate flow for downstream uses. This study was found that integrated water resources management strategy in the basin could utilize water resources potential effectively in the future. Therefore, this study is useful for the different stakeholders in the study region for the optimal allocation of water resources under climate change scenarios.

Improving streamflow simulations and forecasting performance of SWAT model by assimilating remotely sensed soil moisture observations

This article presents a study carried out using EnKF based assimilation of coarser-scale SMOS soil moisture retrievals to improve the streamflow simulations and forecasting performance of SWAT model in a large catchment. This study has been carried out in Munneru river catchment, India, which is about 10,156 km2. In this study, an EnkF based new approach is proposed for improving the inherent vertical coupling of soil layers of SWAT hydrological model during soil moisture data assimilation. Evaluation of the vertical error correlation obtained between surface and subsurface layers indicates that the vertical coupling can be improved significantly using ensemble of soil storages compared to the traditional static soil storages based EnKF approach. However, the improvements in the simulated streamflow are moderate, which is due to the limitations in SWAT model in reflecting the profile soil moisture updates in surface runoff computations. Further, it is observed that the durability of streamflow improvements is longer when the assimilation system effectively updates the subsurface flow component. Overall, the results of the present study indicate that the passive microwave-based coarser-scale soil moisture products like SMOS hold significant potential to improve the streamflow estimates when assimilating into large-scale distributed hydrological models operating at a daily time step.

Improving SWAT model performance in the upper Blue Nile Basin using meteorological data integration and subcatchment discretization

Abstract. The Blue Nile Basin is confronted by land degradation problems, insufficient agricultural production, and a limited number of developed energy sources. Hydrological models provide useful tools to better understand such complex systems and improve water resources and land management practices. In this study, SWAT was used to model the hydrological processes in the upper Blue Nile Basin. Comparisons between a Climate Forecast System Reanalysis (CFSR) and a conventional ground weather dataset were done under two sub-basin discretization levels (30 and 87 sub-basins) to create an integrated dataset to improve the spatial and temporal limitations of both datasets. A SWAT error index (SEI) was also proposed to compare the reliability of the models under different discretization levels and weather datasets. This index offers an assessment of the model quality based on precipitation and evapotranspiration. SEI demonstrates to be a reliable additional and useful method to measure the level of error of SWAT. The results showed the discrepancies of using different weather datasets with different sub-basin discretization levels. Datasets under 30 sub-basins achieved Nash–Sutcliffe coefficient (NS) values of −0.51, 0.74, and 0.84; p factors of 0.53, 0.66, and 0.70; and r factors of 1.11, 0.83, and 0.67 for the CFSR, ground, and integrated datasets, respectively. Meanwhile, models under 87 sub-basins achieved NS values of −1.54, 0.43, and 0.80; p factors of 0.36, 0.67, and 0.77; r factors of 0.93, 0.68, and 0.54 for the CFSR, ground, and integrated datasets, respectively. Based on the obtained statistical results, the integrated dataset provides a better model of the upper Blue Nile Basin.

Simulation of the catchments hydrological processes in arid, semi-arid and semi-humid areas

Hydrological processes and their spatial distribution directly are relevant to climate, topography, geology, and land use in the watershed. Therefore, use of a model whit integrity and high performance for simulating the process in deferent watersheds is very important. In this study was assessment performance of semi-distributed SWAT model in simulating hydrology processes in three watersheds with different climate: Jazmurian basin with 1258 (km2) in an arid climate, Khorramabad watershed white 2467 (km2) in a semi-arid climate and Talar watershed white 2057 climate in semi-humid climate. To this purpose, maps land use, soil, digital elevation model, and meteorological data in daily step collected from many stations for each region. After running the SWAT model, the calibration and validation model did whit SUFI2 algorithm. Performance models were assessed with statistical coefficients NS, R2 and bR2. The results showed that the values of these coefficients in Jazmurian basin is 0.56, 0.54 and 0.20, in Khorramabad watershed is 0.68, 0.72 and 0.32 respectively and in Talar watershed is 0.64 0.66 and 0.31 respectively. Overall, the results showed that the SWAT model performance in Talar watershed is higher than the other watersheds.

Multi-variable SWAT model calibration with remotely sensed evapotranspiration and observed flow

ABSTRACT Although intrinsic, uncertainty for hydrological model estimation is not always reported. The aim of this study is to evaluate the use of satellite-based evapotranspiration on SWAT model calibration, regarding uncertainty and model performance in streamflow simulation. The SWAT model was calibrated in a monthly step and validated in monthly (streamflow and evapotranspiration) and daily steps (streamflow only). The validation and calibration period covers the years from 2006 to 2009 and the study area is the upper Negro river basin, situated in Santa Catarina and Paraná. SWAT-CUP was used to calibrate and validate the model, using SUFI-2 with KGE (Kling-Gupta Efficiency) as objective function. Different calibration strategies were evaluated, considering single-variable and multi-variable calibration, using streamflow and evapotranspiration. Compared to conventional single-variable calibration (streamflow only), multi-variable calibration (streamflow and evapotranspiration, simultaneously) produce better streamflow performance, especially for low flow periods and daily step validation. Despite that, no evidence of reduction of streamflow prediction uncertainty was observed. SWAT model calibration using solely evapotranspiration still requires further studies.