Improved calibration scheme of SWAT by separating wet and dry seasons

Zhang, Dejian; Chen, Xingwei; Yao, Huaxia; Lin, Bingqing

doi:10.1016/j.ecolmodel.2015.01.018

Cited by 115 publications

(58 citation statements)

References 29 publications

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“…Similar good results were reported when calibrating streamflow under wet and dry seasons separately in [29,30]. Since the NS efficiency metric applies to the whole simulation period, it was not recommended for application to low flow periods of streamflows [27,30].…”

Section: Introductionsupporting

confidence: 65%

“…Meanwhile, RCHRG_DP played a less important role in the model calibration and ranked from 8 to 14. The parameters defined as sensitive in this study were similar to those selected in other studies with a focus on semi-arid catchments and low flow conditions [2,4,28,30].…”

Section: Parameter Sensitivity Analysismentioning

confidence: 50%

“…The climate is Mediterranean with an average annual rainfall of 585 mm [30]. Whilst its average monthly rainfall in January and February is around 20 mm, rainless months are quite common [31].…”

Section: Study Areamentioning

confidence: 99%

“…Nash-Sutcliffe (NS) statistics have become increasingly used for SWAT model optimization compared to other metrics [20,22,26]. Some studies with a focus on dry time series using NS as objective functions showed both good and poor results [2,4,[27][28][29][30]. A study by Saha et al [2] achieved a satisfactory solution of NS statistical threshold at a monthly time step, but the highest value at a daily time step was 0.124 which is far below the satisfactory threshold.…”

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: Introductionsupporting

confidence: 65%

Section: Parameter Sensitivity Analysismentioning

confidence: 50%

Section: Study Areamentioning

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

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“…However, there was no advantage when only the winter (wet period) data were used for calibration compared with the conventional calibration method which used the entire data over the whole period. Paik et al (2005), Kim and Lee (2014), Zhang et al (2015) and Kim et al (2016) also used the seasonal calibration method.…”

Section: Introductionmentioning

confidence: 99%

Exploration of sub-annual calibration schemes of hydrological models

Kim¹,

Han²

2016

Hydrology Research

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms AbstractThis study has compared hydrological model performances under different sub-annual period calibration schemes using two conceptual models, IHACRES and HYMOD. In several publications regarding sub-annual period calibration, the authors showed that such an approach generally performed better than the conventional whole period method. Hence, there are advantages in dividing (or clustering) the data into sub-annual periods for calibration. However, little attention has been paid to the issue of how to calibrate the non-continuous subannual period. It is therefore important to explore reliable calibration schemes for such a situation. Unlike the conventional whole period calibration which assumes time-invariant parameters for the entire calibration period, the model parameters vary in sub-annual calibration. We have explored two sub-annual calibration schemes, serial calibration scheme (SCS) and parallel calibration scheme (PCS). We assume that the relationships between the rainfall and runoff could be different for each sub-annual period and consider intraannual variations of the system. The models are then evaluated for a different validation period to avoid overfitting (or, over parameterisation) and the optimal sub-annual calibration period is explored. Overall, we have found that PCS performed slightly better than SCS and the optimal calibration periods are seasonal and bimonthly for IHACRES and biannual for HYMOD at the study catchment. Since there are pros and cons in both SCS and PCS, we recommend choosing the method depending on the purpose of the model usage.Although the catchment is specific in the study, the methodology proposed is general and applicable to other catchments.

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Season‐based rainfall–runoff modelling using the probability‐distributed model (PDM) for large basins in southeastern Brazil

Zhang

Cuartas

Carvalho

et al. 2018

Hydrological Processes

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Southeastern Brazil is characterized by seasonal rainfall variability. This can have a great social, economic, and environmental impact due to both excessive and deficient water availability. During 2014 and 2015, the region experienced one of the most severe droughts since 1960. The resulting water crisis has seriously affected water supply to the metropolitan region of São Paulo and hydroelectric power generation throughout the entire country. This research considered the upstream basins of the southeastern Brazilian reservoirs Cantareira (2,279 km 2 ; water supply) and Emborcação (29,076 km 2 ), Três Marias (51,576 km 2 ), Furnas (52,197 km 2 ), and Mascarenhas (71,649 km 2 ; hydropower) for hydrological modelling. It made the first attempt at configuring a season-based probability-distributed model (PDM-CEMADEN) for simulating different hydrological processes during wet and dry seasons. The model successfully reproduced the intra-annual and interannual variability of the upstream inflows during 1985-2015. The performance of the model was very satisfactory not only during the wet, dry, and transitional seasons separately but also during the whole period. The best performance was obtained for the upstream basin of Furnas, as it had the highest quality daily precipitation and potential evapotranspiration data. The Nash-Sutcliffe efficiency and logarithmic Nash-Sutcliffe efficiency were 0.92 and 0.93 for the calibration period 1984-2001, 0.87 and 0.88 for the validation period 2001-2010, and 0.93 and 0.90 for the validation period 2010-2015, respectively. Results indicated that during the wet season, the upstream basins have a larger capacity and variation of soil water storage, a larger soil water conductivity, and quicker surface water flow than during the dry season. The added complexity of configuring a season-based PDM-CEMADEN relative to the traditional model is well justified by its capacity to better reproduce initial conditions for hydrological forecasting and prediction. The PDM-CEMADEN is a simple, efficient, and easy-touse model, and it will facilitate early decision making and implement adaptation measures relating to disaster prevention for reservoirs with large-sized upstream basins. KEYWORDS 2014/2015 water crisis, intra-annual and interannual rainfall variability, PDM-CEMADEN, seasonal calibration, southeastern Brazil

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Improved calibration scheme of SWAT by separating wet and dry seasons

Cited by 115 publications

References 29 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

Exploration of sub-annual calibration schemes of hydrological models

Season‐based rainfall–runoff modelling using the probability‐distributed model (PDM) for large basins in southeastern Brazil

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