scholarly journals Hydrological process simulation in Manas River Basin using CMADS

2020 ◽  
Vol 12 (1) ◽  
pp. 946-957
Author(s):  
Xinchen Gu ◽  
Guang Yang ◽  
Xinlin He ◽  
Li Zhao ◽  
Xiaolong Li ◽  
...  

AbstractThe inability to conduct hydrological simulations in areas that lack historical meteorological data is an important factor limiting the development of watershed models, understanding of watershed water resources, and ultimate development of effective sustainability policies. This study focuses on the Manas River Basin (MRB), which is a high-altitude area with no meteorological stations and is located on the northern slope of the Tianshan Mountains, northern China. The hydrological processes were simulated using the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) using the Soil and Water Assessment Tool (SWAT) model. Simulated runoff was corrected using calibration/uncertainty and sensitivity program for the SWAT. Through parameter sensitivity analysis, parameter calibration, and verification, the Nash–Sutcliffe efficiency (NSE), adjusted R-square ({R}_{\text{adj}}^{2}), and percentage bias (\text{PBIAS}) were selected for evaluation. The results were compared with statistics obtained from Kenswat Hydrological Station, where the monthly runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.64, {R}_{\text{adj}}^{2}\hspace{.25em}=0.69, and \text{PBIAS}\hspace{.25em}=\mbox{--}0.9, and the daily runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.75, {R}_{\text{adj}}^{2} = 0.75, \text{PBIAS} = −1.5. These results indicate that by employing CMADS data, hydrological processes within the MRB can be adequately simulated. This finding is significant, as CMADS provide continuous temporal, detailed, and high-spatial-resolution meteorological data that can be used to build a hydrological model with adequate accuracy in areas that lack historical meteorological data.

Author(s):  
Son Ngo ◽  
Huong Hoang ◽  
Phuong Tran ◽  
Loc Nguyen

Land use/land cover (LULC) and climate changes are two main factors directly affecting hydrologic conditions. However, very few studies in Vietnam have investigated changes in hydrological process under the impact of climate and land use changes on a basin scale. The objective of this study is to assess the individual and combined impacts of land use and climate changes on hydrological processes for the Nam Rom river basin, Northwestern Viet Nam using Remote Sensing (RS) and Soil and Water Assessment Tools (SWAT) model. SWAT model was used for hydrological process simulation. Results indicated that SWAT proved to be a powerful tool in simulating the impacts of land use and climate change on catchment hydrology. The change in historical land use between 1992 and 2015 strongly contributed to increasing hydrological processes (ET, percolation, ground water, and water yield), whereas, climate change led to significant decrease of all hydrological components. The combination of land use and climate changes significantly reduced surface runoff (-16.9%), ground water (-5.7%), water yield (-9.2%), and sediment load (-4.9%). Overall climatic changes had more significant effect on hydrological components than land use changes in the Nam Rom river basin during the 1992–2015. Under impacts of projected land use and climate change scenarios in 2030 on hydrological process of the upper Nam Rom river basin indicate that ET and surface flow are more sensitive to the changes in land use and climate in the future. In conclusion, the findings of this study will basic knowledge of the effects of climate and land-use changes on the hydrology for future development of integrated land use and water management practices in Nam Rom river basin.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 636 ◽  
Author(s):  
Yan Liu ◽  
Geng Cui ◽  
Hongyan Li

Snowmelt is the main source of runoff in the alpine regions of northern China. When using the soil and water assessment tool (SWAT) to simulate snowmelt runoff, the snowmelt date and snowmelt factor parameters are set according to the North American values. To improve the accuracy of the runoff simulation in northern China, we innovatively used a baseflow segmentation method to determine the snowmelt time, taking temperature as a reference. The snowmelt period was extracted from statistical data, and the corresponding parameters in the source code of SWAT were optimized for the study area. After the calibration was completed, the modified simulation value was compared with the original code simulation value. The simulation accuracy of the daily runoff was improved, and we found that the greater the difference between the source code simulation value and the observed value was, the better the simulation accuracy. Therefore, modifying the source code in SWAT is an effective way to improve the accuracy of simulations of Alpine regions in Northern China. The results show that adjustments to the snowmelt modules of SWAT to reflect local conditions can be an effective way to improve the predictions.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 996 ◽  
Author(s):  
Limin Zhang ◽  
Xianyong Meng ◽  
Hao Wang ◽  
Mingxiang Yang ◽  
Siyu Cai

Reanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR), against gauge observations (OBS) by using interpolation software and statistical indicators in Northeast China (NEC), as well as their annual average spatial and monthly average distributions. The reliability and applicability of the two reanalysis datasets were assessed as inputs in a hydrological model (SWAT) for runoff simulation in the Hunhe River Basin. Statistical results reveal that CMADS performed better than CFSR for precipitation and temperature in NEC with the indicators closer to optimal values (the ratio of standard deviations of precipitation and maximum/minimum temperature from CMADS were 0.92, 1.01, and 0.995, respectively, while that from CFSR were 0.79, 1.07, and 0.897, respectively). Hydrological modelling results showed that CMADS + SWAT and OBS + SWAT performed far better than CFSR + SWAT on runoff simulations. The Nash‒Sutcliffe efficiency (NSE) of CMADS + SWAT and OBS + SWAT ranged from 0.54 to 0.95, while that of CFSR + SWAT ranged from −0.07 to 0.85, exhibiting poor performance. The CMADS reanalysis dataset is more accurate than CFSR in NEC and is a suitable input for hydrological simulations.


Author(s):  
Yuechao Chen ◽  
Yue Zhang ◽  
Qing Zhang ◽  
Xue Song ◽  
Jiajia Gao ◽  
...  

Accurate runoff simulation is of great importance to understand watershed hydrologic cycle process, effective utilize water resources and respond flood disaster. Hydrologic model is one of the main tools for runoff simulation research and the continuous improvement in Machine Learning offers powerful tools for modeling of hydrologic process. This research took the runoff process of the Atsuma River basin in Hokkaido from 2015 to 2019 as object, proposed a special machine learning framework: Long-and Short-term Time-series Network (LSTNet) for runoff simulation, discussed the accuracy for runoff simulation of LSTNet model with (multivariate LSTNet Model) or without (univariate LSTNet Model) meteorological factors and Soil and Water Assessment Tool (SWAT) model respectively, analyzed the model selection for runoff simulation under different data conditions in the basin. The Nash-Sutcliffe efficiency coefficients (NSE) of the runoff simulation results in the validation (test) period were 0.633 (SWAT model), 0.643 (multivariate LSTNet model), and 0.716 (univariate LSTNet model) respectively. The results show that the accuracies of the two models for runoff simulation in the Atsuma River basin are all very high. SWAT model has prominent advantages in runoff simulation and shortcomings. LSTNet model shows great advantages and potential in runoff simulation. In summary, when target basin’ s data is accurate and complete, the accuracy of SWAT model in runoff simulation is high and stable. When the target basin lacks data or the quality of data is poor, LSTNet model can realize high-precision runoff simulation only based on the measured runoff data, which has a strong application.


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.


2021 ◽  
Vol 14 ◽  
pp. 117862212098870
Author(s):  
Juan Adriel Carlos Mendoza ◽  
Tamar Anaharat Chavez Alcazar ◽  
Sebastián Adolfo Zuñiga Medina

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.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.


Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1803
Author(s):  
Xiaoli Chen ◽  
Guoru Huang

The assessment of various precipitation products’ performances in extreme climatic conditions has become a topic of interest. However, little attention has been paid to the hydrological substitutability of these products. The objective of this study is to explore the performance of the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) product in the Feilaixia catchment, China. To assess its applicability in extreme consecutive climates, several statistical indices are adopted to evaluate the TMPA performance both qualitatively and quantitatively. The Cox–Stuart test is used to investigate extreme climate trends. The Soil and Water Assessment Tool (SWAT) model is used to test the TMPA hydrological substitutability via three scenarios of runoff simulation. The results demonstrate that the overall TMPA performance is acceptable, except at high-latitudes and locations where the terrain changes greatly. Moreover, the accuracy of the SWAT model is high both in the semi-substitution and full-substitution scenarios. Based on the results, the TMPA product is a useful substitute for the gauged precipitation in obtaining acceptable hydrologic process information in areas where gauged sites are sparse or non-existent. The TMPA product is satisfactory in predicting the runoff process. Overall, it must be used with caution, especially at high latitudes and altitudes.


2020 ◽  
Vol 12 (23) ◽  
pp. 10050 ◽  
Author(s):  
Junfang Liu ◽  
Baolin Xue ◽  
Yuhui Yan

Land use and climate change are the two major driving factors of watershed runoff change, and it is of great significance to study the influence of watershed hydrological processes on water resource planning and management. This study takes the Changyang River basin as the study area, builds a SWAT model and explores the applicability of the SWAT model in the basin. Moreover, we combine data on land use and climate change in different periods to construct a variety of scenario models to quantitatively analyze the impacts of different scenarios on runoff. The results show that the R2 and Ensof the model are 0.71 and 0.68 in the calibration period, respectively, and those in the verification period are 0.68 and 0.65, respectively, indicating that the SWAT model has good applicability in simulating the runoff of the Changyang River basin. Under the comprehensive scenario of land use and climate change on runoff, we found that land use and climate change have a certain contribution to the change in runoff. Therefore, the runoff of the basin increased by 0.22 m3/s, in which land-use change caused the runoff in the basin to increase by 0.07 m3/s attributed to the decreased area of arable land and the increased area of urban land in the basin. Moreover, climate change has caused the runoff in the basin to increase by 0.13 m3/s, mainly influenced by the increased precipitation. The results show that climate change has a more significant effect on runoff in the basin.


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