Assessing SWAT models based on single and multi-site calibration for the simulation of flow and nutrient loads in the semi-arid Onkaparinga catchment in South Australia

Shrestha, Manoj; Recknagel, Friedrich; Frizenschaf, Jacqueline; Meyer, Wayne S.

doi:10.1016/j.agwat.2016.02.009

Cited by 111 publications

(64 citation statements)

References 28 publications

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“…Successful applications were also reported for the regions of arid climate across the U.S. [18] and Africa [25]. In the case of the driest inhabited continent of Australia [2], studies of hydrological modelling by SWAT are concentrated more in the southeastern part of the country [24] with Shrestha et al [6] being the only known case study for South Australia.…”

Section: Introductionmentioning

confidence: 97%

“…Auto-calibration was performed using the SWAT Calibration and Uncertainty Procedure (SWAT-CUP4) [4,6,24,41]. It incorporates five methods of which the Sequential Uncertainty Fitting program (SUFI2) was selected in this study.…”

Section: Model Evaluationmentioning

confidence: 99%

“…SUFI2 provides two methods for sensitivity analysis, namely one-at-a-time sensitivity analysis (OAT) and global sensitivity analysis. OAT was tested first in order to select a set of sensitive parameters from available literature [2,4,6,41,42] for the model calibration. Global sensitivity analysis is incorporated with calibration in SUFI2 and results were used to evaluate the sensitivity of selected parameters.…”

Section: Model Evaluationmentioning

confidence: 99%

“…In addition to this, high flows can sporadically occur during the rainy seasons as well as from thunderstorms during the dry seasons [31]. Models for catchments dominated by low streamflows have been shown to often overestimate the low and underestimate the high flow events [2,4,6]. For long-term modelling of catchments with dominant low flows, it therefore seems to be advantageous to focus on methods that equally consider the contribution of both low and high flows as a whole rather than performing the discontinuous seasonal calibration.…”

Section: Introductionmentioning

confidence: 99%

“…Streamflows in South Australia experienced severe drought conditions in the period from 1998 to 2008 [5,6]. The consequent very low flows can seriously affect agricultural yield and the biodiversity of the system [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Analysing the Effects of Forest Cover and Irrigation Farm Dams on Streamflows of Water-Scarce Catchments in South Australia through the SWAT Model

Nguyen

Recknagel

Meyer

et al. 2017

Water

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Abstract:To assist water resource managers with future land use planning efforts, the eco-hydrological model Soil and Water Assessment Tool (SWAT) was applied to three catchments in South Australia that experience extreme low flow conditions. Particular land uses and management issues of interest included forest covers, known to affect water yields, and farm dams, known to intercept and change the hydrological dynamics in a catchment. The study achieved a satisfactory daily calibration when irrigation farm dams were incorporated in the model. For the catchment dominated by extreme low flows, a better daily simulation across a range of qualitative and quantitative metrics was gained using the base-flow static threshold optimization technique. Scenario analysis on effects of forest cover indicated an increase of surface flow and a reduction of base-flow when native eucalyptus lands were replaced by pastures and vice versa. A decreasing trend was observed for the overall water yield of catchments with more forest plantation due to the higher evapotranspiration (ET) rate and the decline in surface flow. With regards to effects of irrigation farm dams, assessment on a daily time step suggested that a significant volume of water is stored in these systems with the water loss rate highest in June and July. On an annual basis, the model indicated that approximately 13.1% to 22.0% of water has been captured by farm dams for irrigation. However, the scenario analysis revealed that the purposes of use of farm dams rather than their volumetric capacities in the catchment determined the magnitude of effects on streamflows. Water extracted from farm dams for irrigation of orchards and vineyards are more likely to diminish streamflows than other land uses. Outputs from this study suggest that the water use restrictions from farm dams during recent drought periods were an effective tool to minimize impacts on streamflows.

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Section: Introductionmentioning

confidence: 97%

Section: Model Evaluationmentioning

confidence: 99%

Section: Model Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysing the Effects of Forest Cover and Irrigation Farm Dams on Streamflows of Water-Scarce Catchments in South Australia through the SWAT Model

Nguyen

Recknagel

Meyer

et al. 2017

Water

Self Cite

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Modeling stage‐discharge and sediment‐discharge relationships in data‐scarce Himalayan River Basin Dhauliganga, Central Himalaya, using neural networks

Rautela,

Gupta,

Devi

et al. 2024

CLEAN Soil Air Water

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This study focuses on the hydro‐sedimentological characterization and modeling of the Dhauliganga River in Uttarakhand, India. Field data collected from 2018–2020, including stage, velocity, and suspended sediment concentration (SSC), showed notable variations influenced by melting snow, glaciers, and precipitation. Challenges in accurately modeling rivers with a topography and sparse gauging stations were addressed using artificial neural networks (ANN). The calibrated models precisely predicted stage‐discharge and sediment‐discharge relationships, demonstrating the effectiveness of machine learning, particularly ANN‐based modeling, in such challenging terrains. The model's performance was assessed using coefficient of determination (R2), root mean square error (RMSE), and mean square error (MSE). During the calibration phase, the model exhibited notable performance with R2 values of 0.96 for discharge and 0.63 for SSC, accompanied by low RMSE values of 5.29 cu m s–1 for discharge and 0.61 g for SSC. Subsequently, in the prediction phase, the model maintained its robustness, achieving R2 values of 0.97 for discharge and 0.63 for SSC, along with RMSE values of 5.67 cu m s–1 for discharge and 0.68 g for SSC. The study also found a strong agreement between water flow estimates derived from traditional methods, ANN, and actual measurements. The suspended sediment load, influenced by both water flow and SSC, varied annually, potentially modifying aquatic habitats through sediment deposition, and altering aquatic communities. These findings offer crucial insights into the hydro‐sedimentological dynamics of the studied river, providing valuable applications for sustainable water‐resource management in challenging terrains and addressing environmental concerns related to sedimentation, water quality, and aquatic ecosystem.

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Effects of single‐ and multi‐site calibration strategies on hydrological model performance and parameter sensitivity of large‐scale semi‐arid and semi‐humid watersheds

Liu

Yang

et al. 2022

Hydrological Processes

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In large‐scale watersheds, only the calibration of parameters for the outlet may ignore spatial heterogeneity and fail to meet the simulation accuracy of local areas. Based on the runoff observation data of three hydrological stations (Qingyang, Yangjiaping and Zhangjiashan) in the Jinghe River Watershed, single‐ and multi‐site calibration strategies were designed to investigate the performance and applicability of the Soil and Water Assessment Tool (SWAT) in predicting the monthly runoff of nested catchments and evaluate the differences in parameter sensitivity between the upstream and downstream. (i) The two calibration strategies showed little difference in the simulation accuracy of the watershed outlet; the Nash–Sutcliffe efficiency (NSE) and determination coefficient (R2) were approximately 0.8 and 0.6, respectively, and the percentage of bias (PBIAS) was mostly <15%. The single‐site one‐by‐one calibration was significantly better than the multi‐site joint calibration at the interior points of the watershed. Among them, Qingyang decreased most obviously in the joint calibration with Zhangjiashan, with both NSE and R2 < 0.5, whereas Yangjiaping was >0.5 in combination with the other two sites. (ii) The sensitive parameters obtained by the two calibration strategies were different, and different parameters were effective for different‐sized catchments because hydrological processes exhibit astounding variability at all scales. The single‐site one‐by‐one calibration was mainly affected by the hydrological processes of the local catchment, whereas the multi‐site joint calibration was largely constrained by the sensitive parameters of the single‐site calibration. (iii) Parameters at different scales and locations were related to the problem of scaling and regionalization. The multi‐site joint calibration did not significantly improve the model performance of the watershed outlet but increased the capacity for synchronous identification of local sensitive parameters when compared to single‐site calibration. These findings are expected to provide experience for parameter calibration in other similar large‐scale watersheds and to lay a good foundation for the accurate identification of other related hydrological behaviours at watershed scales.

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Assessing SWAT models based on single and multi-site calibration for the simulation of flow and nutrient loads in the semi-arid Onkaparinga catchment in South Australia

Cited by 111 publications

References 28 publications

Analysing the Effects of Forest Cover and Irrigation Farm Dams on Streamflows of Water-Scarce Catchments in South Australia through the SWAT Model

Analysing the Effects of Forest Cover and Irrigation Farm Dams on Streamflows of Water-Scarce Catchments in South Australia through the SWAT Model

Modeling stage‐discharge and sediment‐discharge relationships in data‐scarce Himalayan River Basin Dhauliganga, Central Himalaya, using neural networks

Effects of single‐ and multi‐site calibration strategies on hydrological model performance and parameter sensitivity of large‐scale semi‐arid and semi‐humid watersheds

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