University of Twente Student Theses
Stream flow and water quality modelling using the SWAT2005: A case study of the Roxo reservoir, Portugal
Negassi, Demoz Kidane (2010) Stream flow and water quality modelling using the SWAT2005: A case study of the Roxo reservoir, Portugal.
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| Abstract: | The European Water Framework Directive requires that all surface waters and groundwater must reach at least ‘good’ status by 2015. Thus, the directive requires the development of management strategies to restore rivers and lakes to “good” status within a specified timeframe. Thus this study was proposed to be an aid for the future decision making process concerning the improvement of water quality of Roxo reservoir; in order to achieve the goals set by the European water framework directive. The overall objective of this study was to develop a reliable and well calibrated water flow and water quality for the Roxo Catchment Reservoir using soil and water assessment tool (SWAT) model. To achieve this purpose the following specific objectives were identified; in-situ measurements was carried out and added to available data to provide the modelling environment with calibration and validation data sets. Calibration, validation, error and sensitivity analysis of stream flow and water quality parameters was carried out. Regarding the stream flow, performance of the model was statistical Nash-sucliffe prediction efficiency (ENS) value of 0.784 and 0.86, and the regression analysis (R2) result 0.802 and 0.872 for calibration and validation period respectively. This confirms that the model was successfully simulating the inflow dynamics of the different streams into Roxo reservoir. Chlorophyll a of Roxo reservoir over the 9 years (Sep. 2001-Oct.2009) simulated data was compared with observed data. The simulated chlorophyll a tends to show the trend of seasonal variation of the measured data. The regression line of simulated result was 0.17, (ENS) value of -1.4, RMSE result (101) and PBIAS (-9.22%) indicate the model tends to over estimating the simulated data. The result was not satisfactory in the calibration period as a result it was not validated. The most possible reason was the available water quality observation data; particularly chlorophyll a was incomplete (missing observed data) and inconsistence of the observed data. Monthly predicted and observed average total nitrogen (TN) of Roxo reservoir from Sep. 2001to Oct.2009 was compared. The performance of the model was statistical Nash-sucliffe prediction efficiency (ENS) value of -0.087 and -0.18, and the regression analysis (R2) result 0.47 and 0.54 for calibration and validation period respectively, however the model show over estimating the simulated data; generally the result was satisfactory in the validation even better than calibration period. In similar way, the monthly predicted and observed average sediment of Roxo reservoir from Sep. 2001to Oct.2009 was compared. The performance of the model; the statistical Nash-sucliffe prediction efficiency (ENS) value of 0.45 and 0.04, regression analysis result (R2) was 0.606 and 0.34 for calibration and validation period respectively. The validation period was not convincing as the calibration period, but it was satisfactory. The most possible reason was the available water quality observation data; was incomplete (missing observed data) and inconsistence of the observed data. Generally the SWAT model was successfully calibrated and validated for Roxo reservoir to estimate predicted monthly stream flow into the reservoir, sediment, chlorophyll a, and total nitrogen out of the reservoir from Sep.2001 to Oct 2009. This study found that the SWAT model is a powerful tool used to make hydrological analysis of Roxo reservoir; particularly it works well with to quantify water flow dynamics. The model needs further improvement to simulate the water quality parameters in lakes and reservoirs to support for the decision making process |
| Item Type: | Essay (Master) |
| Faculty: | ITC: Faculty of Geo-information Science and Earth Observation |
| Programme: | Geoinformation Science and Earth Observation MSc (75014) |
| Link to this item: | https://purl.utwente.nl/essays/91581 |
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