scholarly journals Data- and Model-Based Discharge Hindcasting over a Subtropical River Basin

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2560
Author(s):  
Khondoker Billah ◽  
Tuan B. Le ◽  
Hatim O. Sharif
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Gene Expression Programming ◽  
Calibration Coefficient ◽  
Coefficient Of Determination ◽  
Functional Relationships ◽  
Auto Regressive ◽  
R Value ◽  
Input Variables ◽  
Gauging Station

This study aims to evaluate the performance of the Soil and Water Assessment Tool (SWAT), a simple Auto-Regressive with eXogenous input (ARX) model, and a gene expression programming (GEP)-based model in one-day-ahead discharge prediction for the upper Kentucky River Basin. Calibration of the models were carried out for the period of 2002–2005 using daily flow at a stream gauging station unaffected by the flow regulation. Validation of the calibrated models were executed for the period of 2008–2010 at the same gauging station along with another station 88 km downstream. GEP provided the best calibration (coefficient of determination (R) value 0.94 and Nash-Sutcliffe Efficiency (NSE) value of 0.88) and validation (R values of 0.93 and 0.93, NSE values of 0.87 and 0.87, respectively) results at the two gauging stations. While SWAT performed reasonably well in calibration (R value 0.85 and NSE value 0.72), its performance somewhat degraded in validation (R values of 0.85 and 0.82, NSE values of 0.65 and 0.65, for the two stations). ARX performed very well in calibration (R value 0.92, NSE value 0.82) and reasonably well in validation (R values of 0.88 and 0.92, NSE values of 0.76 and 0.85) at the two stations. Research results suggest that sophisticated hydrological models could be outperformed by simple data-driven models and GEP has the advantage to generate functional relationships that allows investigation of the complex nonlinear interrelationships among the input variables.

scholarly journals Simulating Reservoir Induced Lhasa Streamflow Variability Using ArcSWAT

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1370
Author(s):  
Muhammad Yasir ◽  
Tiesong Hu ◽  
Samreen Abdul Hakeem
Keyword(s):  
River Basin ◽  
Reservoir Operation ◽  
River Discharge ◽  
Water Distribution ◽  
Assessment Tool ◽  
Data Availability ◽  
Lhasa River Basin ◽  
Lhasa River ◽  
Downstream Flow ◽  
Gauging Station

Lhasa River Basin being the socio-economic hotspot of Qinghai-Tibetan Plateau is experiencing an increased hydropower capacity in the form of damming and reservoir construction. The Pangduo hydropower station, commenced in 2013, is one of these developments. Lhasa River discharge is analyzed for spatial variability under the reservoir operation at Pondo and Lhasa gauging station. The Mann–Kendall Trend analysis reveals an increased precipitation and a decreased Lhasa River discharge trend upstream and downstream the reservoir. However, the discharge received at Lhasa gauging station is experiencing a greater decline revealed by Sen’s slope estimator. Soil and Water Assessment Tool (SWAT) modelling of the Lhasa River discharge for both the hydrometric stations from 2008–2016 reveals better simulation results for Pondo hydrometric station in terms of R2, NSE and PBIAS values. The modelling results for Pondo station correspond comparatively well to the reservoir operation procedures including water level and inflow despite of data availability constraint. However, the importance of non-simulated processes (e.g., groundwater abstractions) to the accurate prediction of the Lhasa flow regime particularly at the downstream flow gauge is recommended. The study can prove beneficial for local water distribution measures in Lhasa River Basin.

scholarly journals Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Oluwatobi O. Akin ◽  
Amana Ocholi ◽  
Olugbenga S. Abejide ◽  
Johnson A. Obari
Keyword(s):  
Gene Expression ◽  
Compressive Strength ◽  
Stepwise Regression ◽  
Gene Expression Programming ◽  
Good Alternative ◽  
Coefficient Of Determination ◽  
Concrete Compressive Strength ◽  
Compressive Strength Of Concrete ◽  
Input Variables ◽  
The Relationship

One of the problems of optimization of concrete is to formulate a mathematical equation that shows the relationship between the various constituents of concrete and its properties. In this work, modelling of the compressive strength of concrete admixed with metakaolin was carried out using the Gene Expression Programming (GEP) algorithm. The dataset from laboratory experimentation was used for the analysis. The mixture proportions were made of three different water/binder ratios (0.4, 0.5, and 0.6), and the grades of concrete produced were grade M15 and M20. The compressive strength of the concrete was determined after 28 days of curing. The parameters used in the GEP algorithm are the input variables which include cement content, water, metakaolin content, and fine and coarse aggregate, while the response was designated as the compressive strength. The model was trained and tested using the parameters. The R-square value from the GEP algorithm was compared with the use of conventional stepwise regression analysis. With a coefficient of determination (R-square value) of 0.95, the GEP algorithm has shown to be a good alternative for modelling concrete compressive strength.

scholarly journals Theoretical Hydrokinetic Power Potential Assessment of the U-Tapao River Basin Using GIS

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1749
Author(s):  
Fida Ali ◽  
Chatchawin Srisuwan ◽  
Kuaanan Techato ◽  
Adul Bennui ◽  
Tanita Suepa ◽  
...  
Keyword(s):  
River Basin ◽  
New Technologies ◽  
Assessment Tool ◽  
Model Performance ◽  
Coefficient Of Determination ◽  
Lake Basin ◽  
Discharge Data ◽  
Flow Estimation ◽  
Southern Thailand ◽  
Water Assessment

Conventional hydropower technologies such as dams have been criticized due to their negative environmental effects which have necessitated the development of new technologies for sustainable development of hydropower energy. Hydrokinetic (HK) energy is one such emerging renewable energy technology and, in this study, a theoretical potential assessment was done using a Geographic Information System (GIS) and Soil and Water Assessment Tool (SWAT) hydrological model, for the U-Tapao river basin (URB), a major tributary of the Songkhla lake basin (SLB) in southern Thailand. The SWAT was calibrated and validated with SWAT calibration and uncertainty (SWAT-CUP)-SUFI 2 programs using the observed discharge data from the gauging stations within the watershed. The model performance was evaluated based on the Nash–Sutcliffe efficiency (NSE) and the coefficient of determination (R2) values, achieving 0.62 and 0.60, respectively, for calibration, and 0.65 and 0.68 for validation which is considered acceptable and can be used to represent flow estimation. The theoretical HK potential was estimated to be 71.9 MW along the 77.18 km U-Tapao river, which could be developed as a renewable and reliable energy source for the communities living around the river. The method developed could also be applied to river systems around the world for resource and time efficient HK potential assessments.

scholarly journals Evaluation of Water Quality Interaction by Dam and Weir Operation Using SWAT in the Nakdong River Basin of South Korea

2020 ◽  
Vol 12 (17) ◽  
pp. 6845 ◽  
Author(s):  
Jiwan Lee ◽  
Yonggwan Lee ◽  
Soyoung Woo ◽  
Wonjin Kim ◽  
Seongjoon Kim
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Assessment Tool ◽  
Water Quality Monitoring ◽  
Coefficient Of Determination ◽  
Nakdong River ◽  
Nakdong River Basin ◽  
Gate Control ◽  
The Nakdong River ◽  
Dam Inflow

The purpose of this study was to evaluate the streamflow and water quality (SS, T-N, and T-P) interaction of the Nakdong river basin (23,609.3 km2) by simulating dam and weir operation scenarios using the Soil and Water Assessment Tool (SWAT). The operation scenarios tested were dam control (Scenario 1), dam control and weir gate control (Scenario 2), dam control and sequential release of the weirs with a one-month interval between each weir (Scenario 3), dam control and weir gate full open (Scenario 4), dam control and weir gate sequential full open (Scenario 5), weir gate control (Scenario 6), weir gate full open (Scenario 7), and weir gate sequential full open (Scenario 8). Before evaluation, the SWAT was calibrated and validated using 13 years (2005–2017) of daily multi-purpose dam inflow data from five locations ((Andong Dam (ADD), Imha Dam (IHD), Hapcheon Dam (HCD), Namkang Dam (NKD), and Milyang Dam (MYD))multi-function weir inflow data from seven locations (Sangju Weir (SJW), Gumi Weir (GMW), Chilgok Weir (CGW), Gangjeong-Goryeong Weir (GJW), Dalseong Weir (DSW), Hapcheon-Changnyeong Weir (HCW), and Changnyeong-Haman Weir (HAW)), and monthly water quality monitoring data from six locations (Andong-4 (AD-4), Sangju (SJ-2), Waegwan (WG), Hapcheon (HC), Namkang-4 (NK-4), and Mulgeum (MG). For the dam inflows and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.59~0.78, and the coefficient of determination (R2) was 0.71~0.90. For water quality, the R2 values of SS, T-N, and T-P were 0.58~0.83, 0.53~0.68, and 0.56~0.79, respectively. For the eight dam and weir release scenarios suggested by the Ministry of Environment, Scenarios 4 and 8 exhibited water quality improvement effects compared to the observed data.

scholarly journals Assessment of the SWAT model in simulating watersheds in arid regions: Case study of the Yarmouk River Basin (Jordan)

2021 ◽  
Vol 13 (1) ◽  
pp. 377-389
Author(s):  
Majed Abu-Zreig ◽  
Lubna Bani Hani
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Positive Impact ◽  
Swat Model ◽  
Development Project ◽  
Coefficient Of Determination ◽  
Statistical Measures ◽  
Yarmouk River ◽  
Monthly Runoff ◽  
The Impact

Abstract The Soil and Water Assessment Tool (SWAT) was used to simulate monthly runoff in the Yarmouk River Basin (YRB). The objectives were to assess the performance of this model in simulating the hydrological responses in arid watersheds then utilized to study the impact of YRB agricultural development project on transport of sediments in the YRB. Nine and three years of input data, namely from 2005 to 2013, were used to calibrate the model, whereas data from 2014 to 2015 were used for model validation. Time series plots as well as statistical measures, including the coefficient of determination (R 2) and the Nash–Sutcliffe coefficient of efficiency (NSE) that range between 0 to 1 and −∞ to 1, respectively, between observed and simulated monthly runoff values were used to verify the SWAT simulation capability for the YRB. The SWAT model satisfactorily predicted mean monthly runoff values in the calibration and validation periods, as indicated by R 2 = 0.95 and NSE = 0.96 and R 2 = 0.91 and NSE = 0.63, respectively. The study confirmed the positive impact of soil conservation measures implemented in the YRB development project and confirmed that contouring can reduce soil loss from 15 to 44% during the study period. This study showed that the SWAT model was capable of simulating hydrologic components in the drylands of Jordan.

scholarly journals Impact of climate change on the hydrology of a semi-arid river basin of India under hypothetical and projected climate change scenarios

2020 ◽  
Author(s):  
Sujeet Desai ◽  
D. K. Singh ◽  
Adlul Islam ◽  
A. Sarangi
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Assessment Tool ◽  
Circulation Model ◽  
Central India ◽  
Coefficient Of Determination ◽  
Climate Change Scenarios ◽  
Global Circulation Model ◽  
Calibration And Validation ◽  
Semi Arid

Abstract Climate change impact on the hydrology of the Betwa river basin, located in the semi-arid region of Central India, was assessed using the Soil and Water Assessment Tool (SWAT), driven by hypothetical scenarios and Model of Interdisciplinary Research on Climate version 5 (MIROC5) Global Circulation Model projections. SWAT-Calibration and Uncertainty Programs (SWAT-CUP) was used for calibration and validation of SWAT using multi-site streamflow data. The coefficient of determination, Nash–Sutcliffe efficiency, RMSE-observations standard deviation ratio and percent bias during calibration and validation period varied from 0.83–0.92, 0.6–0.91, 0.3–0.63 and −19.8–19.3, respectively. MIROC5 projections revealed an increase in annual mean temperature in the range of 0.7–0.9 °C, 1.2–2.0 °C and 1.1–3.1 °C during the 2020s, 2050s, and 2080s, respectively. Rainfall is likely to increase in the range of 0.4–9.1% and 5.7–15.3% during the 2050s and 2080s, respectively. Simulation results indicated 3.8–29% and 12–48% increase in mean annual surface runoff during the 2050s and 2080s, respectively. Similarly, an increase of 0.2–3.0%, 2.6–4.2% and 3.5–6.2% in mean annual evapotranspiration is likely during the 2020s, 2050s and 2080s, respectively. These results could be used for developing suitable climate change adaptation plans for the river basin.

scholarly journals Application of Machine Learning Techniques in Rainfall–Runoff Modelling of the Soan River Basin, Pakistan

Water ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 3528
Author(s):  
Muhammad Tariq Khan ◽  
Muhammad Shoaib ◽  
Muhammad Hammad ◽  
Hamza Salahudin ◽  
Fiaz Ahmad ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Tree ◽  
River Basin ◽  
Gene Expression Programming ◽  
Research Work ◽  
Model Performance ◽  
Coefficient Of Determination ◽  
Discrete Wavelet ◽  
Rainfall Runoff ◽  
The Impact

Rainfall–runoff modelling has been at the essence of research in hydrology for a long time. Every modern technique found its way to uncover the dynamics of rainfall–runoff relation for different basins of the world. Different techniques of machine learning have been extensively applied to understand this hydrological phenomenon. However, the literature is still scarce in cases of extensive research work on the comparison of streamline machine learning (ML) techniques and impact of wavelet pre-processing on their performance. Therefore, this study compares the performance of single decision tree (SDT), tree boost (TB), decision tree forest (DTF), multilayer perceptron (MLP), and gene expression programming (GEP) in rainfall–runoff modelling of the Soan River basin, Pakistan. Additionally, the impact of wavelet pre-processing through maximal overlap discrete wavelet transformation (MODWT) on the model performance has been assessed. Through a comprehensive comparative analysis of 110 model settings, we concluded that the MODWT-based DTF model has yielded higher Nash–Sutcliffe efficiency (NSE) of 0.90 at lag order (Lo4). The coefficient of determination for the model was also highest among all the models while least root mean square error (RMSE) value of 23.79 m3/s was also produced by MODWT-DTF at Lo4. The study also draws inter-technique comparison of the model performance as well as intra-technique differentiation of modelling accuracy.

scholarly journals Analysis of Non-Point Source Pollution Features of Chao River Basin Based on the CMADS-Driven SWAT Model

2021 ◽  
Vol 252 ◽  
pp. 03066
Author(s):  
Zhang Min ◽  
Yang Long ◽  
An Tongyan ◽  
Fan Qing
Keyword(s):  
Point Source ◽  
River Basin ◽  
Pollution Control ◽  
Assessment Tool ◽  
Swat Model ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Major Type ◽  
Nitrogen And Phosphorus ◽  
Nps Pollution

By the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS 1.0), this paper simulated the non-point source (NPS) pollution of Chao River Basin in the upper reach of Miyun Reservoir, and analyzed the spatial-temporal distribution pattern of nitrogen and phosphorus pollutants and the contribution rates of pollution sources. The major findings of the research are as follows. The CMADS V1.0-driven SWAT model shows good applicability to the study area. The simulation of the runoff, nitrogen and phosphorous pollution in the calibration period and the validation period has yielded a Nash-Sutcliffe efficiency (Ens) coefficient at 0.51~0.78, and a coefficient of determination at 0.73~0.88, which meets the model evaluation standards. The total nitrogen (TN) and total phosphorus (TP) pollution load in the flood season is considerably large, and the average inflow of TN and TP into the reservoir accounts for 60.62% and 75.15% the total annual inflow, respectively. The #26 sub-basin marks the biggest TN and TP loads, and it is thus worth more attention from pollution control administrations. Overall, the TN and TP load in the lower reach of the basin are larger than the upper reach. NPS pollution is the major type of pollution caused by human production and life. The livestock and poultry farming as well as fertilizers, which are the main contributors to NPS pollution, are considered the focus of NPS pollution control.

scholarly journals Comparative Water Environment Simulation Study of Two Typical Models with BMPs in a Karst Basin

Agriculture ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 69
Author(s):  
Jing Zhang ◽  
Peiqi Zhang ◽  
Yongyu Song
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Best Management Practices ◽  
Management Practices ◽  
Assessment Tool ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Pollution Load ◽  
Hspf Model ◽  
Lijiang River

Carbonate rocks are widely distributed in southwest China, forming a unique karst landscape. The Lijiang River Basin provides a typical example of an area with concentrated karst. Research on the laws of hydrology and water quality migration in the Lijiang River Basin is important for the management of the water resources of Guilin City and similar areas. In this study, we combined three meteorological data with the soil and water assessment tool (SWAT) model and the hydrological simulation program-Fortran (HSPF) model to simulate the hydrological and water quality processes in the Lijiang River Basin separately. We chose the Nash–Sutcliffe efficiency (NSE) coefficient, coefficient of determination (R2), root mean square error-observations standard deviation ratio (RSR), and mean absolute error (MAE) as the metrics used to evaluate the models. The results, combined with the time-series process lines, indicated that the SWAT model provides a more accurate performance than the HSPF model in streamflow, ammonia nitrogen (NH3-N), and dissolved oxygen (DO) simulations. In addition, we divided the karst and non-karst areas, and we analyzed the differences between them in water balance, sediment transport, and pollution load. We further identified the key source areas of pollution load in the Lijiang River Basin, evaluated the pollution reduction effect of best management practices (BMPs) on surface source pollution, and proposed some pollution control countermeasures. Each scenario, especially returning farmland to forest and creating vegetation buffer zones, reduces the NH3-N and DO pollution load.

scholarly journals Calibration and Uncertainty Analysis for Modelling Runoff in the Tambo River Basin, Peru, Using Sequential Uncertainty Fitting Ver-2 (SUFI-2) Algorithm

2021 ◽  
Vol 14 ◽  
pp. 117862212098870
Author(s):  
Juan Adriel Carlos Mendoza ◽  
Tamar Anaharat Chavez Alcazar ◽  
Sebastián Adolfo Zuñiga Medina
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Hydrological Cycle ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Economic Activities ◽  
Warm Up ◽  
Simulation Efficiency ◽  
Basin Scale ◽  
Water Assessment

Basin-scale simulation is fundamental to understand the hydrological cycle, and in identifying information essential for water management. Accordingly, the Soil and Water Assessment Tool (SWAT) model is applied to simulate runoff in the semi-arid Tambo River Basin in southern Peru, where economic activities are driven by the availability of water. The SWAT model was calibrated using the Sequential Uncertainty Fitting Ver-2 (SUFI-2) algorithm and two objective functions namely the Nash-Sutcliffe simulation efficiency (NSE), and coefficient of determination ( R2) for the period 1994 to 2001 which includes an initial warm-up period of 3 years; it was then validated for 2002 to 2016 using daily river discharge values. The best results were obtained using the objective function R2; a comparison of results of the daily and monthly performance evaluation between the calibration period and validation period showed close correspondence in the values for NSE and R2, and those for percent bias (PBIAS) and ratio of standard deviation of the observation to the root mean square error (RSR). The results thus show that the SWAT model can effectively predict runoff within the Tambo River basin. The model can also serve as a guideline for hydrology modellers, acting as a reliable tool.

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