Hydrological status of the Dagu River Basin and management suggestions based on soil and water assessment tool multi-station calibration
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Abstract Soil and water assessment tool (SWAT) model was used to calculate the runoff, nitrogen and phosphorus emissions in the Dagu River Basin from 2002 to 2012 and provided preliminary suggestions on environmental protection measures. Calibration on hydrological watershed parameters was obtained from data obtained from multiple representative stations. Cluster analysis was used to group all stations, and the parameters of different representative stations were applied to the entire geographical area to reflect the hydrological conditions of the basin. Additionally, the spatiotemporal changes and pollution source characteristics of nitrogen and phosphorus were analyzed. Anthropogenic sources—chemical fertilizer loss and livestock breeding—accounted for 49.9–29.6% of total nitrogen (TN) and 41.4% and 40.3% of total phosphorus (TP), respectively. Non-point sources accounted for 85.8% of the TN and 89.4% of the TP. Six landscape management practices were set up to evaluate the reduction effect on non-point source pollution loads, and comprehensive measures were proposed to reduce TN (TP) by ~ 70%. According to water quality model, the response relationship between river control and nutrient distribution in Jiaozhou Bay is calculated. Based on the findings, we propose an optimal control scheme for non-point source pollution in the Dagu River Basin and other similar basins.Keywords:
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The current study analyses the runoff response using Soil and Water Assessment Tool (SWAT) during rainfall incidents over the sub-basin of Deo River, Panch Mahal, Gujarat, India. The SWAT model is developed for the Deo river sub-basin having catchment area of 194.36 km2, with 7 sub-basins comprising of 94 Hydrological Response Units (HRUs). Two rain gauge stations present in the study area (viz., Deo dam and Shivrajpur) werechosen to evaluate the efficiency of the SWAT model. To conduct SWAT model Calibration and Validation, the Soil and Water Assessment Tool-Calibration Uncertainty Program (SWAT-CUP) with Sequential Uncertainty Fitting (SUFI-2) algorithm has been used. The model was run for the period from 2000 to 2017 considering 2 years (2000-2001) warm up period with a calibration period of 2002 to 2012 and a validation period of 2013 to 2017. The sensitivity of the basin parameters was evaluated and found Curve Number as the most sensitive parameter, hence, it can be considered to improve the model's runoff simulation efficiency. The study found that the model performed good with a Coefficient of Determination (R2) and Nash–Sutcliffe Efficiency (NSE) as 0.89 and 0.87 during calibration and 0.88 and 0.81 during validation respectively giving data at daily scale. The findings of this study revealed that SWAT model is helpful for runoff prediction and flood forecasting for extreme rainfall occurrences in Deo river basin.
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The source area of the Liao River is an important grain growing area in China which experiences serious problems with agricultural nonpoint source pollution (NPS) which is impacting the regional economy and society. In order to address the water quality issues it is necessary to understand the spatial distribution of NPS in the Liao River source area. This issue has been investigated by coupling a wavelet artificial neural network (WA-ANN) precipitation model with a soil and water assessment tool (SWAT) model to assess the export of nonpoint source pollutants from the Liao River source area. The calibration and validation of these models are outlined. The WA-ANN models and the SWAT model were run to generate the spatial distribution of nonpoint source nutrient (nitrogen and phosphorus) exports in the source area of the Liao River. It was found that the SWAT model identified the sub-catchments which not only receive high rainfall but are also densely populated with high agricultural production from dry fields and paddy fields, which are large users of pesticides and chemical fertilizer, as the primary source areas for nutrient exports. It is also concluded that the coupled WA-ANN models and the SWAT model provide a tool which will inform the identification of NPS issues and will facilitate the identification of management practices to improve the water environments in the source area of the Liao River.
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섬강 시험유역의 지형학적 특성 매개변수와 SWAT-CUP의 SUFI-2 알고리즘을 이용한 SWAT 모형 매개변수와의 상관관계와 이들의 관계식을 개발하였다. 개발한 상관 관계식을 이용하여 속사천 유역의 SWAT 모형의 매개변수를 추정하였다. 아울러, 속사천 유역의 2000 - 2007년의 강우-유출 자료를 대상으로 SWAT-CUP의 SUFI-2 알고리즘을 이용하여 SWAT 모형의 매개변수를 추정하였다. 개발한 식에 의해 산정한 각 매개변수의 적용성을 검토하기 위해 2000 - 2007년의 속사천 시험유역 자료를 이용하여 SWAT 모형의 유출모의를 실시하였다. 실측자료와 지형학적 특성 매개변수의 상관관계 분석으로 산정된 매개변수를 이용하여 속사천에 적용한 유출 모의결과와의 RMSE (root mean square error)는 $1.09m^3/s$ 이고, SWAT-CUP의 SUFI-2 최적 매개변수를 적용한 유출 모의결과와의 RMSE는 $0.93m^3/s$ 으로 나타났다. 따라서 지형학적 특성 매개변수를 이용한 SWAT 모형의 매개변수 추정이 적용성이 있다고 판단된다. The correlation relationships and their corresponding equations between the geomorphological parameters and the Soil Water Assessment Tool (SWAT) model parameters by Sequential Uncertainty Fitting - version 2 (SUFI-2) algorithm of SWAT Calibration and Uncertainty Programs (SWAT-CUP) were developed at the Seom-river experimental watershed. The parameters of the SWAT model at the Soksa-river experimental watershed were estimated by the developed equations. The SWAT model parameters were estimated by SUFI-2 algorithm of SWAT-CUP with rainfall-runoff data from the Soksa-river experimental watershed from 2000 to 2007. Rainfall-runoff simulation of the SWAT model was carried out at the Soksa-river experimental watershed from 2000 to 2007 for the applicability of the estimated parameters by the developed equations. The root mean square errors (RMSE) between the observed and the simulated rainfall-runoffs using the estimated parameters by developed equations of correlation analysis and the optimum parameters by SUFI-2 of SWAT-CUP were $1.09m^3/s$ and $0.93m^3/s$ respectively at the Soksa-river experimental watershed from 2000 to 2007. Therefore, it is considered that the parameter estimation of the SWAT model by the geomorphological characteristics parameters has applicability.
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Agricultural non-point source pollution is one of the major reasons,which causes watershed pollution in China.However,mathematic model is an important tool in the research of watershed pollution,water quality analysis and forecast.After synthetically analyzing the advantages and disadvantages of non-point source pollution at present,the more advanced and perfect distributed hydrological model—SWAT model was selected,using GIS and RS technology,the study on agricultural non-point source pollution simulation in Erhai Lake Watershed was carried out,and non-point source pollution condition was understood to provide a reasonable reference and basis for the comprehensive management and plan of Erhai Lake Watershed.
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Soil and Water Assessment Tools (SWAT) which is developed in America was used to analyze the effect of land management on discharge, sedimentation, and water quality in a river basin area. The hydrological conditions in the Americas are different from Indonesia, so a modified SWAT is done. This research aimed to implement a modified SWAT program to predict the results of a better discharge analysis based on hydrological analysis in the sub-Watershed area. About 13.90% of the area was paddy fields. The evaluation of the module had been done by looking at the coefficient of determination (R²) and Nash-Sutcliffe Efficiency (NSE) based on the comparison of simulated discharge results with an observation discharge. Research began with delineation DEM, HRU formation, simulation, calibration, and validation. The R² value for daily data on modified SWAT was 0,725. It was better than the original SWAT and SWAT with Pothole, which were 0,706 and 0,708 respectively. Likewise, the NSE value for daily data on modified SWAT was 0,721, on original SWAT and on SWAT with Pothole was 0,668 and 0,685 respectively. The analysis result showed that the modified SWAT provide good discharge prediction results, indicated by relatively high R2 and NSE values.Keywords: hydrological analysis,modified SWAT, paddy field, pothole, SWAT
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Hydrological models have long been used to study the interactions between land, surface and groundwater systems, and to predict and manage water quantity and quality. The soil and water assessment tool (SWAT), a widely used hydrological model, can simulate various ecohydrological processes on land and subsequently route the water quality constituents through surface and subsurface waters. So far, in-stream solute transport algorithms of the SWAT model have only been minimally revised, even though it has been acknowledged that an improvement of in-stream process representation can contribute to better model performance with respect to water quality. In this study, we aim to incorporate a new and improved solute transport model into the SWAT model framework. The new process-based model was developed using in-stream process equations from two well established models—the One-dimensional Transport with Inflow and Storage model and the Enhanced Stream Water Quality Model. The modified SWAT model (Mir-SWAT) was tested for water quality predictions in a study watershed in Germany. Compared to the standard SWAT model, Mir-SWAT improved dissolved oxygen (DO) predictions by removing extreme low values of DO (<6 mg/L) simulated by SWAT. Phosphate concentration peaks were reduced during high flows and a better match of daily predicted and measured values was attained using the Mir-SWAT model (R2 = 0.17, NSE = −0.65, RSR = 1.29 with SWAT; R2 = 0.28, NSE = −0.04, RSR = 1.02 with Mir-SWAT). In addition, Mir-SWAT performed better than the SWAT model in terms of Chlorophyll-a content particularly during winter months, improving the NSE and RSR for monthly average Chl-a by 74 and 42%, respectively. With the new model improvements, we aim to increase confidence in the stream solute transport component of the model, improve the understanding of nutrient dynamics in the stream, and to extend the applicability of SWAT for reach-scale analysis and management.
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SWAT model was used to calculate the agricultural non-point source pollution in Daninghe watershed.The runoff and the sediment data series from 2000 to 2004 were used to calibrate the parameters and validate the model.Results indicated that SWAT model was appropriate for Daninghe watershed.Then the calibrated model was used to calculate the spatial distribution of non-point source pollution.The calculated result indicated that the west part of the watershed was the serious soil erosion area,which is the same as the spatial distribution of organic nitrogen.In one word,the production of non-point source pollution in the west is more than that in the east,while in the south,more than that in the north.The measures for the prevention of non-point source pollution were presented according to the simulated results.
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Non-point source(NPS)pollution is considered to be a major contributor to local water degradation in the Three Gorges Reservoir Area of China. Xiangxi River, which is a large watershed near the Three Gorges Reservoir, was selected to investigate the effectiveness of vegetated waterway in alleviating agricultural NPS pollution using SWAT(Soil and Water Assessment Tool)model. DEM, soil data, land use data in 2011 and the meteorological data from 1970 to 2011 were input to the SWAT model to simulate total N(TN)and total P(TP)pollution loads before and after applying vegetated waterway management in 2011. The pollution loads were divided into five classes with Jenk optimal methods. The SWAT model generated satisfying results. Total N and TP pollution loads were 1388 t and 239 t, respectively, which were both concentrated in Nanyang River and the downstream of Gufu and Gaolan River. Applying vegetated waterway reduced TN and TP pollution loads to 1120 t and 157 t, respectively. The reduction rates of TN and TP were 16.7% and 34%, respectively. These results could help local managers design effective management practices to improve water quality in similar watersheds.
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Non-point source pollutants in down stream of Nakdong river were simulated by SWAT. GIS was utilized to make input data of SWAT such as landuse pattern and soil. Meteorological data of 2007 and 2009 were applied for the calibration and validation of runoff in SWAT. It was difficult to calibrate and validate the runoff and nutrient results since a study area was influenced by the tidal effects. Jindong site was selected to escape from the bias of runoff simulation in the coastal area. $R^2$ values of calibration and validation were 0.8 and 0.79. However, $R^2$ values of water qualities were very low level in comparison to runoff. These resulted from the concentration scale of water qualities such as BOD, T-N and T-P. Additionally, tidal influence could effected on the measurements of nutrients. The simulated annual averages and patterns of BOD, T-N and T-P in SWAT were similar to the measurement data. 80 ~ 96 % of nonpoint source pollutants at Nakbon M site were released from April to August of 2009. The ratio of T-N and T-P from nonpoint source were above 50 % during the rainy season.
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