scholarly journals Assessment of the streamflow changes in the La Nga river basin

2020 ◽  
Vol 4 (1) ◽  
pp. first
Author(s):  
Nguyen Thi Thuy Trang ◽  
Ngo Ngoc Hoang Giang ◽  
Nguyen Thi Thuy Hang
Keyword(s):  
River Basin ◽  
Model Performance ◽  
Flow Simulation ◽  
Dry Season ◽  
Short Term ◽  
Seasonal Flow ◽  
Lst Model ◽  
The Impact ◽  
Deviation Ratio ◽  
Statistical Metrics

The paper aims to assess the changes of the streamflow under the impact of irrigation constructions in La Nga river basin using the Long and Short term runoff (LST) model. The LST model was calibrated and validated for the period of 1987–1995 and 1996–1999, respectively, to simulate the natural streamflow for the post–construction phase. Statistical metrics, including R2 coefficients, efficiency coefficients (NSE), percent error (PBIAS) and standard monitoring deviation ratio (RSR) were used to evaluate the model performance. The results showed that, LST model performed well in the flow simulation by the high values of R2 and NSE index greater than 0.80, RSR smaller than 0.50 and PBIAS lower than 7.22%. The comparison between the simulated (natural) and observed flows illustrated that there were changes of the flow regime in the post–construction phase. The average seasonal flow decreases 24.59% and increased 12.06% in the wet and dry season, respectively at Phu Dien station. Meanwhile, at Ta Pao station, the streamflow decreased 8.35% and increased 21.11% in the wet and dry season, respectively. The results of this study could be used in planning, managing and regulating the irrigation works'operation, and water resources management in the La Nga river basin.

Integrating 1D-2D Hydrodynamic Model For Sabarmati Upper River Basin With Special Reference to Ahmedabad City Area

2021 ◽  
Author(s):  
sejal chandel ◽  
suvarna shah
Keyword(s):  
River Basin ◽  
Hydrodynamic Model ◽  
Management Strategies ◽  
Flow Simulation ◽  
Urban Setting ◽  
Flood Inundation ◽  
Flash Flooding ◽  
Arc Gis ◽  
Sabarmati River ◽  
The Impact

<p>In recent study, Gujarat has become one of the India’s most urbanized state, causing severe flash flooding. The Sabarmati river is one of the major west-flowing rivers in India and biggest river of north Gujarat.Urbanization should meet the population’s need by enlargement of paved areas, which has unusually changed the catchment’s hydrological and hydraulic characteristic. Therefor, the frequency of flash flooding in Sabarmati river has been increased. The Sabarmati river basin experienced eight times devastating flooding coendition between 1972 to 2020.Among which July 2017 flooding event breakdown a 112 years old record of 1905. The Dharoi dam and Wasna barrage on Sabarmati river and surrounding district Kheda, Mehsana, Gandhinagar, Ahmedabad received a huge rainfall caused anomalous inflow to tributary which forced the dam authorities to release huge discharge in short duration which leads to flooding. The Sabarmati riverfront of Ahmedabad had been going under water for five days due incessant rainfall in the city that leads to swelling of the Sabarmati river in 2017. In order to determine extent of Inundation, Hydrodynamic Model HEC-RAS(5.0.6) with Arc GIS was used. Various scenarios were run with HEC-RAS to study the impact of flow simulation on flood inundation(with & without riverfront project). The simulated flood depths have been compared with actual depths obtained at gauging station, which were collected from Government authorities. Ultimately, the analysis was used to create maps for different return periods with RAS Mapper and ArcMap that visually show the reach of the floodplains, illustrating the affected areas. Results demonstrate the usefulness of  modelling system to predict the extent of flood inundation and thus support analyses of management strategies to deal with risk associated with infrastructure in an urban setting.</p>

scholarly journals Using the Soil and Water Assessment Tool to Simulate the Pesticide Dynamics in the Data Scarce Guayas River Basin, Ecuador

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 696 ◽  
Author(s):  
Naomi Cambien ◽  
Sacha Gobeyn ◽  
Indira Nolivos ◽  
Marie Anne Eurie Forio ◽  
Mijail Arias-Hidalgo ◽  
...  
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Model Development ◽  
Model Performance ◽  
Water Quality Monitoring ◽  
Freshwater Ecosystem ◽  
Set Up ◽  
The Impact ◽  
Water Assessment ◽  
Soil And Water

Agricultural intensification has stimulated the economy in the Guayas River basin in Ecuador, but also affected several ecosystems. The increased use of pesticides poses a serious threat to the freshwater ecosystem, which urgently calls for an improved knowledge about the impact of pesticide practices in this study area. Several studies have shown that models can be appropriate tools to simulate pesticide dynamics in order to obtain this knowledge. This study tested the suitability of the Soil and Water Assessment Tool (SWAT) to simulate the dynamics of two different pesticides in the data scarce Guayas River basin. First, we set up, calibrated and validated the model using the streamflow data. Subsequently, we set up the model for the simulation of the selected pesticides (i.e., pendimethalin and fenpropimorph). While the hydrology was represented soundly by the model considering the data scare conditions, the simulation of the pesticides should be taken with care due to uncertainties behind essential drivers, e.g., application rates. Among the insights obtained from the pesticide simulations are the identification of critical zones for prioritisation, the dominant areas of pesticide sources and the impact of the different land uses. SWAT has been evaluated to be a suitable tool to investigate the impact of pesticide use under data scarcity in the Guayas River basin. The strengths of SWAT are its semi-distributed structure, availability of extensive online documentation, internal pesticide databases and user support while the limitations are high data requirements, time-intensive model development and challenging streamflow calibration. The results can also be helpful to design future water quality monitoring strategies. However, for future studies, we highly recommend extended monitoring of pesticide concentrations and sediment loads. Moreover, to substantially improve the model performance, the availability of better input data is needed such as higher resolution soil maps, more accurate pesticide application rate and actual land management programs. Provided that key suggestions for further improvement are considered, the model is valuable for applications in river ecosystem management of the Guayas River basin.

Predicted Changes in Short-Term Rainfall Intensities and Runoff at the Ipoltica River Basin

2020 ◽  
Vol 15 (3) ◽  
pp. 172-183
Author(s):  
Gabriel Földes ◽  
Silvia Kohnová ◽  
Marija Mihaela Labat ◽  
Kamila Hlavčová
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Model ◽  
Regional Climate ◽  
Curve Number ◽  
Short Term ◽  
Community Land Model ◽  
Design Values ◽  
Service Curve ◽  
The Impact

The paper focuses on the impact of climate change on runoff in the Ipoltica River basin in northern Slovakia. The analysis is divided into two parts: the first part contains an analysis of predicted changes in short-term rainfall intensities at the Liptovská Teplička climatological station; the second part is focused on the impact of runoff on a small mountainous river basin. The predicted short-term rainfall intensities were analyzed using the Community Land Model, which is a Regional Climate Model. The analysis was performed in durations of 60 to 1440 minutes for a warm period. The focus was aimed at comparing changes in rainfall characteristics, especially changes in seasonality, the scaling exponents, and design values. The second part focuses on the impact of changes in short-term rainfall on changes in runoff. The estimation of predicted runoff changes was provided for the period 2070 - 2100. These results were compared with the results from actual observations. The design floods were calculated using the Soil Conservation Service - Curve Number method. The results show that the runoff will be affected by climate change. Hence, it is important to reevaluate the land use management and practices at the Ipoltica River basin.

scholarly journals Short-Term Daily Prediction of Sea Ice Concentration Based on Deep Learning of Gradient Loss Function

2021 ◽  
Vol 8 ◽  
Author(s):  
Quanhong Liu ◽  
Ren Zhang ◽  
Yangjun Wang ◽  
Hengqian Yan ◽  
Mei Hong
Keyword(s):  
Deep Learning ◽  
Sea Ice ◽  
Loss Function ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Short Term ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
The Impact

The navigability potential of the Northeast Passage has gradually emerged with the melting of Arctic sea ice. For the purpose of navigation safety in the Arctic area, a reliable daily sea ice concentration (SIC) prediction result is required. As the mature application of deep learning technique in short-term prediction of other fields (atmosphere, ocean, and hurricane, etc.), a new model was proposed for daily SIC prediction by selecting multiple factors, adopting gradient loss function (Grad-loss) and incorporating an improved predictive recurrent neural network (PredRNN++). Three control experiments are designed to test the impact of these three improvements for model performance with multiple indicators. Results show that the proposed model has best prediction skill in our experiments by taking physical process and local SIC variation into consideration, which can continuously predict daily SIC for up to 9 days.

scholarly journals Twentieth and Twenty-First Century Water Storage Changes in the Nile River Basin from GRACE/GRACE-FO and Modeling

2021 ◽  
Vol 13 (5) ◽  
pp. 953
Author(s):  
Emad Hasan ◽  
Aondover Tarhule ◽  
Pierre-Emmanuel Kirstetter
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Water Storage ◽  
Model Performance ◽  
Dry Season ◽  
Nile River ◽  
Surface Model ◽  
Wet Season ◽  
Distribution Fitting ◽  
Nile River Basin

This research assesses the changes in total water storage (TWS) during the twentieth century and future projections in the Nile River Basin (NRB) via TWSA (TWS anomalies) records from GRACE (Gravity Recovery and Climate Experiment), GRACE-FO (Follow-On), data-driven-reanalysis TWSA and a land surface model (LSM), in association with precipitation, temperature records, and standard drought indicators. The analytical approach incorporates the development of 100+ yearlong TWSA records using a probabilistic conditional distribution fitting approach by the GAMLSS (generalized additive model for location, scale, and shape) model. The model performance was tested using standard indicators including coevolution plots, the Nash–Sutcliffe coefficient, cumulative density function, standardized residuals, and uncertainty bounds. All model evaluation results are satisfactory to excellent. The drought and flooding severity/magnitude, duration, and recurrence frequencies were assessed during the studied period. The results showed, (1) The NRB between 2002 to 2020 has witnessed a substantial transition to wetter conditions. Specifically, during the wet season, the NRB received between ~50 Gt./yr. to ~300 Gt./yr. compared to ~30 Gt./yr. to ~70 Gt./yr. of water loss during the dry season. (2) The TWSA reanalysis records between 1901 to 2002 revealed that the NRB had experienced a positive increase in TWS of ~17% during the wet season. Moreover, the TWS storage had witnessed a recovery of ~28% during the dry season. (3) The projected TWSA between 2021 to 2050 unveiled a positive increase in the TWS during the rainy season. While during the dry season, the water storage showed insubstantial TWS changes. Despite these projections, the future storage suggested a reduction between 10 to 30% in TWS. The analysis of drought and flooding frequencies between 1901 to 2050 revealed that the NRB has ~64 dry-years compared to ~86 wet-years. The exceedance probabilities for the normal conditions are between 44 to 52%, relative to a 4% chance of extreme events. The recurrence interval of the normal to moderate wet or dry conditions is ~6 years. These TWSA trajectories call for further water resources planning in the region, especially during flood seasons. This research contributes to the ongoing efforts to improve the TWSA assessment and its associated dynamics for transboundary river basins.

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.

A Newspaper’s Effect on the Strength of Automatic Associations in Memory

2012 ◽  
Vol 24 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Florian Arendt
Keyword(s):  
Treatment Group ◽  
Term Effect ◽  
Control Group ◽  
Implicit Measure ◽  
Short Term ◽  
Short Term Treatment ◽  
Short Term Effect ◽  
Automatic Associations ◽  
Foreign Nationality ◽  
The Impact

A test was done to see if reading a newspaper which consistently overrepresents foreigners as criminals strengthens the automatic association between foreign country and criminal in memory (i.e., implicit cultivation). Further, an investigation was done to find out if reading articles from the same newspaper produces a short-term effect on the same measure and if (1) emotionalization of the newspaper texts, (2) emotional reactions of the reader (indicated by arousal), and (3) attributed text credibility moderate the short-term treatment effect. Eighty-five participants were assigned to one of three experimental conditions. Participants in the control group received short factual crime texts, where the nationality of the offender was not mentioned. Participants in the factual treatment group received the same texts, but the foreign nationality was mentioned. Participants in the emotionalized treatment group received emotionalized articles (i.e., texts which are high in vividness and frequency) covering the same crimes, with the foreign nationality mentioned. Supporting empirical evidence for implicit cultivation and a short-term effect was found. However, only emotionalized articles produced a short-term effect on the strength of the automatic association, indicating that newspaper texts must have a minimum of stimulus intensity to overcome an effect threshold. There were no moderating effects of arousal or credibility pertaining to the impact on the implicit measure. However, credibility moderated the short-term effect on a first-order judgment (i.e., estimated frequency of foreigners of all criminals). This indicates that a newspaper’s effect on the strength of automatic associations is relatively independent from processes of propositional reasoning.

Diatoms in the Amur Bay sediments (Sea of Japan) and the impact of typhoons on their accumulation over the last 2000 years

2019 ◽  
pp. 252-256
Author(s):  
Irina A. Prushkovskaya ◽  
Ira B. Tsoy
Keyword(s):  
Sea Of Japan ◽  
Short Term ◽  
Catastrophic Events ◽  
Bromine Content ◽  
Amur Bay ◽  
The Impact

The study of diatoms in the sediments of the Amur Bay (Sea of Japan), formed over the last 2000 years, showed that the sharp short-term drops in the concentration of diatoms coincide with the minima of bromine content, which can be explained by the influence of typhoons or other catastrophic events leading to floods and used later in paleoreconstructions.

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