scholarly journals Advancing model calibration and uncertainty analysis of SWAT models using cloud computing infrastructure: LCC-SWAT

Author(s):  
Masood Zamani ◽  
Narayan Kumar Shrestha ◽  
Taimoor Akhtar ◽  
Trevor Boston ◽  
Prasad Daggupati

Abstract Calibration and uncertainty analysis of a complex, over-parameterized environmental model such as the Soil and Water Assessment Tool (SWAT) requires thousands of simulation runs and multiple calibration iterations. A parallel calibration system is thus desired that can be deployed on cloud-based architectures for reducing calibration runtime. This paper presents a cloud-based calibration and uncertainty analysis system called LCC-SWAT that is designed for SWAT models. Two optimization techniques, sequential uncertainty fitting (SUFI-2) and dynamically dimensioned search (DDS), have been implemented in LCC-SWAT. Moreover, the cloud-based system has been deployed on the Southern Ontario Smart Computing Innovation Platform's (SOSCIP) Cloud Analytics platform for diagnostic assessment of parallel calibration runtime on both single-node and multi-node CPU architectures. Unlike other calibrations/uncertainty analysis systems developed on the cloud, this system is capable of generating a comprehensive set of statistical information automatically, which facilitates broader analyses of the performance of the SWAT models. Experimental results on SWAT models of different complexities showed that LCC-SWAT can reduce runtime significantly. The runtime reduction is more pronounced for more complex and computationally intensive models. However, the reported runtime efficiency is significantly higher for single node systems. Comparative experiments with DDS and SUFI-2 show that parallel DDS outperforms parallel SUFI-2 in terms of both parameter identifiability and reducing uncertainty in model simulations. LCC-SWAT is a flexible calibration system and other optimization algorithms and asynchronous parallelization strategies can be added to it in future.

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3190
Author(s):  
Zhu Liu ◽  
Jina Yin ◽  
Helen E. Dahlke

Precipitation occurs in two basic forms defined as liquid state and solid state. Different from rain-fed watershed, modeling snow processes is of vital importance in snow-dominated watersheds. The seasonal snowpack is a natural water reservoir, which stores snow water in winter and releases it in spring and summer. The warmer climate in recent decades has led to earlier snowmelt, a decline in snowpack, and change in the seasonality of river flows. The Soil and Water Assessment Tool (SWAT) could be applied in the snow-influenced watershed because of its ability to simultaneously predict the streamflow generated from rainfall and from the melting of snow. The choice of parameters, reference data, and calibration strategy could significantly affect the SWAT model calibration outcome and further affect the prediction accuracy. In this study, SWAT models are implemented in four upland watersheds in the Tulare Lake Basin (TLB) located across the Southern Sierra Nevada Mountains. Three calibration scenarios considering different calibration parameters and reference datasets are applied to investigate the impact of the Parallel Energy Balance Model (ParBal) snow reconstruction data and snow parameters on the streamflow and snow water-equivalent (SWE) prediction accuracy. In addition, the watershed parameters and lapse rate parameters-led equifinality is also evaluated. The results indicate that calibration of the SWAT model with respect to both streamflow and SWE reference data could improve the model SWE prediction reliability in general. Comparatively, the streamflow predictions are not significantly affected by differently lumped calibration schemes. The default snow parameter values capture the extreme high flows better than the other two calibration scenarios, whereas there is no remarkable difference among the three calibration schemes for capturing the extreme low flows. The watershed and lapse rate parameters-induced equifinality affects the flow prediction more (Nash-Sutcliffe Efficiency (NSE) varies between 0.2–0.3) than the SWE prediction (NSE varies less than 0.1). This study points out the remote-sensing-based SWE reconstruction product as a promising alternative choice for model calibration in ungauged snow-influenced watersheds. The streamflow-reconstructed SWE bi-objective calibrated model could improve the prediction reliability of surface water supply change for the downstream agricultural region under the changing climate.


2020 ◽  
Vol 13 (2) ◽  
pp. 576
Author(s):  
Letícia Lopes Martins ◽  
Wander Araújo Martins ◽  
Jener Fernando Leite De Moraes ◽  
Mário José Pedro Júnior ◽  
Isabella Clerici De Maria

A dificuldade na gestão de recursos hídricos aliada à dinâmica do uso e ocupação do solo em bacias hidrográficas agrícolas são fatores relevantes para a conservação da água e solo. A gestão de bacias hidrográficas, bem como o monitoramento de cenários de expansão agrícola e mudança no uso do solo, podem se beneficiar de ferramentas de modelagem hidrossedimentológica, como o SWAT (Soil and Water Assessment Tool). Entretanto, para que os resultados obtidos sejam confiáveis, os modelos precisam ser calibrados. Objetivou-se, neste trabalho, calibrar e validar o modelo SWAT, para a variável vazão, tendo como base a bacia hidrográfica do Ribeirão do Pinhal, Limeira -São Paulo, que se caracteriza pela expansão da cana-de-açúcar sobre áreas citrícolas. Dados de vazão de um posto fluviométrico localizado no exutório da bacia foram utilizados para a calibração e validação, a partir de séries temporais diferentes.  Utilizou-se o software QSWAT para a simulação hidrológica e o SWAT-CUP para a calibração e validação do modelo. O modelo foi calibrado e validado resultando nos seguintes índices estatísticos NSE=0,64; PBIAS=15,2 e RSR=0,60 para calibração e NSE=0,68 PBIAS=-2,8 e RSR=0,56 para a validação. O ajuste de parâmetros do SWAT (USLE_P, USLE_C, CN2) e do calendário de operações da cana-de-açúcar em acordo com a situação real da bacia foi necessário para a calibração do modelo. Os resultados indicam que o modelo SWAT subestima as vazões extremas, no entanto, dentro de faixa aceitável. O SWAT, após a calibração, pode ser utilizado na gestão de recursos hídricos na bacia do Ribeirão do Pinhal.Hydrological calibration of the SWAT model in a watershed characterized by the expansion of sugarcane cultivationA B S T R A C TThe difficulty in water resources management combined with the dynamics of land use and occupation in agricultural watersheds are relevant factors for water and soil conservation. River basin management, as well as monitoring scenarios of agricultural expansion and land-use change, can benefit from hydrossedimentological modeling tools such as the SWAT (Soil and Water Assessment Tool). However, for the results to be reliable, the models must be calibrated. The objective of this study was to calibrate and validate the SWAT model for the flow variable, based on the Ribeirão do Pinhal watershed, Limeira-São Paulo, which is characterized by the expansion of sugarcane over citrus areas. Flow data from a fluviometric station located in the basin's outfall were used for calibration and validation from different time series. QSWAT software was used for hydrological simulation and SWAT-CUP for model calibration and validation. The model was calibrated and validated resulting in the following statistical indices NSE = 0.64; PBIAS = 15.2 and RSR = 0.60 for calibration and NSE = 0.68 PBIAS = -2.8 and RSR = 0.56 for validation. Adjustment of SWAT parameters (USLE_P, USLE_C, and CN2) and the sugarcane operation schedule according to the actual basin situation was necessary for model calibration. The results indicate that the SWAT model underestimates the extreme flow rates, however, within an acceptable range. After calibration, the SWAT can be used to manage water resources in the Ribeirão do Pinhal basin.Keywords: Hydrologic simulation; land use; flow rate.


2020 ◽  
Vol 14 (2) ◽  
pp. 154-161
Author(s):  
Diah Ainunisa ◽  
◽  
Gusfan Halik ◽  
Wiwik Yunarni Widiarti ◽  
◽  
...  

Population growth is one of the causes of land-use change that can increase runoff. Tanggul watershed is one of the watersheds which often overflows during the rainy season. This study purpose to analyze the effect of land-use changes on runoff in Tanggul watershed using SWAT (Soil and Water Assessment Tool) model. To make sure the performance of SWAT model calibration and classified by the value of NSE and R2. The result of calibration included in a good category and validation included in a very good category. This study was modeling forest land-use change in 2004-2017 to determine the effect of land-use change on runoff. The result in this model of forest land-use change can increase runoff.


Hydrology ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 8
Author(s):  
Anwar A. Adem ◽  
Yihun T. Dile ◽  
Abeyou W. Worqlul ◽  
Essayas K. Ayana ◽  
Seifu A. Tilahun ◽  
...  

Comprehensive spatially referenced soil data are a crucial input in predicting biophysical and hydrological landscape processes. In most developing countries, these detailed soil data are not yet available. The objective of this study was, therefore, to evaluate the detail needed in soil resource inventories to predict the hydrologic response of watersheds. Using three distinctively different digital soil inventories, the widely used and tested soil and water assessment tool (SWAT) was selected to predict the discharge in two watersheds in the headwaters of the Blue Nile: the 1316 km2 Rib watershed and the nested 3.59 km2 Gomit watershed. The soil digital soil inventories employed were in increasing specificity: the global Food and Agricultural Organization (FAO), the Africa Soil Information Service (AfSIS) and the Amhara Design and Supervision Works Enterprise (ADSWE). Hydrologic simulations before model calibration were poor for all three soil inventories used as input. After model calibration, the streamflow predictions improved with monthly Nash–Sutcliffe efficiencies greater than 0.68. Predictions were statistically similar for the three soil databases justifying the use of the global FAO soil map in data-scarce regions for watershed discharge predictions.


2006 ◽  
Vol 9 ◽  
pp. 137-143 ◽  
Author(s):  
J. Schuol ◽  
K. C. Abbaspour

Abstract. Distributed hydrological models like SWAT (Soil and Water Assessment Tool) are often highly over-parameterized, making parameter specification and parameter estimation inevitable steps in model calibration. Manual calibration is almost infeasible due to the complexity of large-scale models with many objectives. Therefore we used a multi-site semi-automated inverse modelling routine (SUFI-2) for calibration and uncertainty analysis. Nevertheless, the question of when a model is sufficiently calibrated remains open, and requires a project dependent definition. Due to the non-uniqueness of effective parameter sets, parameter calibration and prediction uncertainty of a model are intimately related. We address some calibration and uncertainty issues using SWAT to model a four million km2 area in West Africa, including mainly the basins of the river Niger, Volta and Senegal. This model is a case study in a larger project with the goal of quantifying the amount of global country-based available freshwater. Annual and monthly simulations with the "calibrated" model for West Africa show promising results in respect of the freshwater quantification but also point out the importance of evaluating the conceptual model uncertainty as well as the parameter uncertainty.


2020 ◽  
Vol 12 (22) ◽  
pp. 3768
Author(s):  
T. A. Jeewanthi G. Sirisena ◽  
Shreedhar Maskey ◽  
Roshanka Ranasinghe

Conventional calibration methods adopted in hydrological modelling are based on streamflow data measured at certain river sections. However, streamflow measurements are usually sparse and, in such instances, remote-sensing-based products may be used as an additional dataset(s) in hydrological model calibration. This study compares two main calibration approaches: (a) single variable calibration with streamflow and evapotranspiration separately, and (b) multi-variable calibration with both variables together. Here, we used remote sensing-based evapotranspiration data from Global Land Evaporation: the Amsterdam Model (GLEAM ET), and measured streamflow at four stations to calibrate a Soil and Water Assessment Tool (SWAT) and evaluate the performances for Chindwin Basin, Myanmar. Our results showed that when one variable (either streamflow or evapotranspiration) is used for calibration, it led to good performance with respect to the calibration variable but resulted in reduced performance in the other variable. In the multi-variable calibration using both streamflow and evapotranspiration, reasonable results were obtained for both variables. For example, at the basin outlet, the best NSEs (Nash-Sutcliffe Efficiencies) of streamflow and evapotranspiration on monthly time series are, respectively, 0.98 and 0.59 in the calibration with streamflow alone, and 0.69 and 0.73 in the calibration with evapotranspiration alone. Whereas, in the multi-variable calibration, the NSEs at the basin outlet are 0.97 and 0.64 for streamflow and evapotranspiration, respectively. The results suggest that the GLEAM ET data, together with streamflow data, can be used for model calibration in the study region as the simulation results show reasonable performance for streamflow with an NSE > 0.85. Results also show that many different sets of parameter values (‘good parameter sets’) can produce results comparable to the best parameter set.


2014 ◽  
Vol 43 (1) ◽  
pp. 132-144 ◽  
Author(s):  
Mieczyslaw S. Ostojski ◽  
Jerzy Niedbala ◽  
Paulina Orlinska-Wozniak ◽  
Pawel Wilk ◽  
Joanna Gębala

2017 ◽  
Vol 10 ◽  
pp. 117862211773179 ◽  
Author(s):  
Milad Jajarmizadeh ◽  
Lariyah Mohd Sidek ◽  
Sobri Harun ◽  
Mohsen Salarpour

One of the major issues for semidistributed models is calibration of sensitive parameters. This study compared 3 scenarios for Soil and Water Assessment Tool (SWAT) model for calibration and uncertainty. Roodan watershed has been selected for simulation of daily flow in southern part of Iran with an area of 10 570 km2. After preparation of required data and implementation of the SWAT model, sensitivity analysis has been performed by Latin Hypercube One-factor-At-a-Time method on those parameters which are effective for flow simulation. Then, SWAT Calibration and Uncertainty Program (SWAT-CUP) has been used for calibration and uncertainty analysis. Three schemes for calibration were followed for the Roodan watershed modeling in calibration analysis as evolution. These include the following: the global method (scheme 1), this is a method that takes in all globally adjusted sensitive parameters for the whole watershed; the discretization method (scheme 2), this method considered the dominant features in calibration such as land use and soil type; the optimum parameters method (scheme 3), this method only adjusted those sensitive parameters by considering the effectiveness of their features. The results show that scheme 3 has better performance criteria for calibration and uncertainty analysis. Nash-Sutcliffe (NS) coefficient has been obtained 0.75 for scheme 3. However, schemes 1 and 2 resulted in NS 0.71 and 0.74, respectively, between predicted and observed daily flows. Moreover, percentage bias (P-bias) obtained was 6.7, 5.2, and 1.5 for schemes 1, 2, and 3, respectively. The result also shows that condition of parameters (parameter set) during calibration in SWAT-CUP program model has an important role to increase the performance of the model.


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