scholarly journals Simulation of Rainfall-Induced Floods in Small Catchments (the Polomet’ River, North-West Russia) Using Rain Gauge and Radar Data

Hydrology ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 92 ◽  
Author(s):  
Elena Grek ◽  
Sergey Zhuravlev

In recent years, rain floods caused by abnormal rainfall precipitation have caused several damages in various part of Russia. Precise forecasting of rainfall runoff is essential for both operational practice to optimize the operation of the infrastructure in urbanized territories and for better practices on flood prevention, protection, and mitigation. The network of rain gauges in some Russian regions are very scarce. Thus, an adequate assessment and modeling of precipitation patterns and its spatial distribution is always impossible. In this case, radar data could be efficiently used for modeling of rain floods, which were shown by previous research. This study is aimed to simulate the rain floods in the small catchment in north-west Russia using radar- and ground-based measurements. The investigation area is located the Polomet’ river basin, which is the key object for runoff and water discharge monitoring in Valdai Hills, Russia. Two datasets (rain gauge and weather radar) for precipitation were used in this work. The modeling was performed in open-source Soil and Water Assessment Tool (SWAT) hydrological model with three types of input data: rain gauge, radar, and gauge-adjusted radar data. The simulation efficiency is assessed using the coefficient of determination R2, Nash–Sutcliffe model efficiency coefficient (NSE), by comparing the mean values to standard deviations for the calculated and measured values of water discharge. The SWAT model captures well the different phases of the water regime and demonstrates a good quality of reproduction of the hydrographs of the river runoff of the Polomet’ river. In general, the best model performance was observed for rain gauge data (NSE is up to 0.70 in the Polomet’river-Lychkovo station); however, good results have been also obtained when using adjusted data. The discrepancies between observed and simulated water flows in the model might be explained by the scarce network of meteorological stations in the area of studied basin, which does not allow for a more accurate correction of the radar data.

2020 ◽  
Author(s):  
Elena Grek ◽  
Sergey Zhuravlev

<p>The previous research had shown that change of rainfall structure is taking place over Russia which increases the probability of occurrence of hazardous hydrological phenomena such as flash rainfall floods. Thus, the relevance and significance of the study is determined by the necessity of taking into account the structural changes of precipitation for reliable estimates of rainfall runoff characteristics in terms of climate change. The data of this study are comprehensive and consist of various sources of hydrometeorological information, including ground-based observations of precipitation and runoff, radar data. The assessment of the changes occurred in the maximum rainfall runoff and daily rainfall depth within the Russian part of the Baltic Sea basin was carried out in this study. The majority of the basins in our study showed positive trends in maximum discharge. The results of the work describe the experience of using different types of meteorological information of precipitation for rainfall floods modeling. The open-source SWAT (Soil and Water Assessment Tool) hydrological model was utilized. Small catchment (631 km<sup>2</sup>) situated in the Polomet’ River basin were chosen as the object of test modeling. The simulation efficiency is assessed using the coefficient of determination R<sup>2</sup>, Nash–Sutcliffe model efficiency coefficient (NSE), by comparing the mean values to standard deviations for the calculated and measured values of water discharge. This study was supported by RFBR, grant 19-35-90123 “Rain floods in the North-West Russia: assessment of variability and development of new forecasting methods”.</p>


2020 ◽  
pp. 22-31 ◽  
Author(s):  
Nguyen Kim Loi ◽  
Vo Ngoc Quynh Tram ◽  
Nguyen Thi Tinh Au

Climate is the main factor affecting hydrology in a watershed. For purely agricultural watershed, hydrological assessment and management play a very important role in the region's agricultural development. In this study, the hydrological was simulated by the Soil and Water Assessment Tool (SWAT) model. This paper aimed to calibrate and validate the SWAT model in Dak B’la watershed in Central Highland Vietnam and assess the climate change on water discharge. The coefficient of determination (R²) and Nash-Sutcliffe index (NSI), and Percent BIAS (PBIAS) during the calibration process was 0.75, 0.72, and -1.15 respectively and validation process was 0.82, 0.83, 3.67 respectively. It proved the high reliability of the SWAT model after calibration. The two climate scenarios were selected in this investigation: scenario A is the existing climate using the data from 2001 to 2018 and scenario B is the A1B emission scenario for the future period from 2020 to 2069. Compared to the average water discharge from 2001-2018 and average water discharge from 2020 to 2069, the results indicated that climate change increases the average water discharge (0.55%), especially in 2050, the water discharge in the flood season (in November) is 584 m3/s, which higher than the largest flood in 2009 of 450 m3/s.


2015 ◽  
Vol 73 (6) ◽  
pp. 1341-1348 ◽  
Author(s):  
Yong Wu ◽  
Changyou Li ◽  
Chengfu Zhang ◽  
Xiaohong Shi ◽  
Charles P.-A. Bourque ◽  
...  

Hetao Oasis is located in a typical piedmont alluvial plain bounded by the Langshan Mountain Range in the north, desert in the west, and the Yellow River in the south. Agricultural activities within the oasis significantly impact the hydrological cycle and water quality in downstream locations. The research uses the Soil and Water Assessment Tool (SWAT) for a piedmont plain by defining the watershed boundary as coinciding with the natural mountain ridge, the border between the oasis and the desert, and the Yellow River. The model simulates water discharge with coefficient of determination and a Nash–Sutcliffe model efficiency of 0.78 and 0.62 during model calibration, and 0.75 and 0.69 during model validation, suggesting that delineation of the watershed as carried out in this research is suitable for piedmont plain topography. From the results, the mountains contribute 28.4% to the water discharge at the outlet of the watershed, and water-use efficiency of irrigated water is about 40%, which is consistent with field-based measurements. Methodologies used in delineating watershed boundaries and parameterizing SWAT provide a solid foundation for water balance studies in other regions of the world with similar topography.


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.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1511
Author(s):  
Jung-Ryel Choi ◽  
Il-Moon Chung ◽  
Se-Jin Jeung ◽  
Kyung-Su Choo ◽  
Cheong-Hyeon Oh ◽  
...  

Climate change significantly affects water supply availability due to changes in the magnitude and seasonality of runoff and severe drought events. In the case of Korea, despite high water supply ratio, more populations have continued to suffer from restricted regional water supplies. Though Korea enacted the Long-Term Comprehensive Water Resources Plan, a field survey revealed that the regional government organizations limitedly utilized their drought-related data. These limitations present a need for a system that provides a more intuitive drought review, enabling a more prompt response. Thus, this study presents a rating curve for the available number of water intake days per flow, and reviews and calibrates the Soil and Water Assessment Tool (SWAT) model mediators, and found that the coefficient of determination, Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) from 2007 to 2011 were at 0.92, 0.84, and 7.2%, respectively, which were “very good” levels. The flow recession curve was proposed after calculating the daily long-term flow and extracted the flow recession trends during days without precipitation. In addition, the SWAT model’s flow data enables the quantitative evaluations of the number of available water intake days without precipitation because of the high hit rate when comparing the available number of water intake days with the limited water supply period near the study watershed. Thus, this study can improve drought response and water resource management plans.


2009 ◽  
Vol 21 ◽  
pp. 49-55 ◽  
Author(s):  
Q. D. Lam ◽  
B. Schmalz ◽  
N. Fohrer

Abstract. The aims of this study are to identify the capacities of applying an ecohydrological model for simulating flow and to assess the impact of point and non-point source pollution on nitrate loads in a complex lowland catchment, which has special hydrological characteristics in comparison with those of other catchments. The study area Kielstau catchment has a size of approximately 50 km2 and is located in the North German lowlands. The water quality is not only influenced by the predominating agricultural land use in the catchment as cropland and pasture, but also by six municipal wastewater treatment plants. Ecohydrological models like the SWAT model (Soil and Water Assessment Tool) are useful tools for simulating nutrient loads in river catchments. Diffuse entries from the agriculture resulting from fertilizers as well as punctual entries from the wastewater treatment plants are implemented in the model set-up. The results of this study show good agreement between simulated and measured daily discharges with a Nash-Sutcliffe efficiency and a correlation coefficient of 0.76 and 0.88 for the calibration period (November 1998 to October 2004); 0.75 and 0.92 for the validation period (November 2004 to December 2007). The model efficiency for daily nitrate loads is 0.64 and 0.5 for the calibration period (June 2005 to May 2007) and the validation period (June 2007 to December 2007), respectively. The study revealed that SWAT performed satisfactorily in simulating daily flow and nitrate loads at the lowland catchment in Northern Germany.


2018 ◽  
Vol 49 (3) ◽  
pp. 908-923 ◽  
Author(s):  
Richarde Marques da Silva ◽  
José Carlos Dantas ◽  
Joyce de Araújo Beltrão ◽  
Celso A. G. Santos

Abstract A Soil and Water Assessment Tool (SWAT) model was used to model streamflow in a tropical humid basin in the Cerrado biome, southeastern Brazil. This study was undertaken in the Upper São Francisco River basin, because this basin requires effective management of water resources in drought and high-flow periods. The SWAT model was calibrated for the period of 1978–1998 and validated for 1999–2007. To assess the model calibration and uncertainty, four indices were used: (a) coefficient of determination (R2); (b) Nash–Sutcliffe efficiency (NS); (c) p-factor, the percentage of data bracketed by the 95% prediction uncertainty (95PPU); and (d) r-factor, the ratio of average thickness of the 95PPU band to the standard deviation of the corresponding measured variable. In this paper, average monthly streamflow from three gauges (Porto das Andorinhas, Pari and Ponte da Taquara) were used. The results indicated that the R2 values were 0.73, 0.80 and 0.76 and that the NS values were 0.68, 0.79 and 0.73, respectively, during the calibration. The validation also indicated an acceptable performance with R2 = 0.80, 0.76, 0.60 and NS = 0.61, 0.64 and 0.58, respectively. This study demonstrates that the SWAT model provides a satisfactory tool to assess basin streamflow and management in Brazil.


2017 ◽  
Vol 21 (8) ◽  
pp. 3975-3989 ◽  
Author(s):  
Jeremy White ◽  
Victoria Stengel ◽  
Samuel Rendon ◽  
John Banta

Abstract. Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.


Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 594 ◽  
Author(s):  
Majid Fereidoon ◽  
Manfred Koch ◽  
Luca Brocca

Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.


Agronomy ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 576 ◽  
Author(s):  
Adrián López-Ballesteros ◽  
Javier Senent-Aparicio ◽  
Raghavan Srinivasan ◽  
Julio Pérez-Sánchez

Best management practices (BMPs) provide a feasible solution for non-point source pollution problems. High sediment and nutrient yields without retention control result in environmental deterioration of surrounding areas. In the present study, the soil and water assessment tool (SWAT) model was developed for El Beal watershed, an anthropogenic and ungauged basin located in the southeast of Spain that drains into a coastal lagoon of high environmental value. The effectiveness of five BMPs (contour planting, filter strips, reforestation, fertilizer application and check dam restoration) was quantified, both individually and in combination, to test their impact on sediment and nutrient reduction. For calibration and validation processes, actual evapotranspiration (AET) data obtained from a remote sensing dataset called Global Land Evaporation Amsterdam Model (GLEAM) were used. The SWAT model achieved good performance in the calibration period, with statistical values of 0.78 for Kling–Gupta efficiency (KGE), 0.81 for coefficient of determination (R2), 0.58 for Nash–Sutcliffe efficiency (NSE) and 3.9% for percent bias (PBIAS), as well as in the validation period (KGE = 0.67, R2 = 0.83, NS = 0.53 and PBIAS = −25.3%). The results show that check dam restoration is the most effective BMP with a reduction of 90% in sediment yield (S), 15% in total nitrogen (TN) and 22% in total phosphorus (TP) at the watershed scale, followed by reforestation (S = 27%, TN = 16% and TP = 20%). All effectiveness values improved when BMPs were assessed in combination. The outcome of this study could provide guidance for decision makers in developing possible solutions for environmental problems in a coastal lagoon.


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