scholarly journals Physics-Informed Data-Driven Models to Predict Surface Runoff Water Quantity and Quality in Agricultural Fields

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 200 ◽  
Author(s):  
Jing Liang ◽  
Wenzhe Li ◽  
Scott Bradford ◽  
Jiří Šimůnek
Keyword(s):  
Surface Water ◽  
Surface Runoff ◽  
Overland Flow ◽  
Data Driven ◽  
Water Quantity ◽  
Soil Conditions ◽  
Runoff Water ◽  
Physically Based ◽  
Physically Based Models ◽  
Water Quantity And Quality

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models (PBMs), which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with PBMs, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. Here we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport. A large number of numerical simulations was then carried out to develop a database containing information about the impact of various relevant factors on surface runoff quantity and quality, such as different weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices. Finally, the resulting database was used to train data-driven models. Several Machine Learning techniques were explored to find input-output functional relations. The results indicate that the Neural Network model with two hidden layers performed the best among selected data-driven models, accurately predicting runoff water quantity and quality over a wide range of parameters.

Response of Winter Manure Application on Surface Runoff Water Quantity and Quality from Small Watersheds in South Dakota

2017 ◽  
Vol 228 (10) ◽  
Author(s):  
Shikha Singh ◽  
Nathan Brandenburg ◽  
Laurent Ahiablame ◽  
Arturo Gonzalez ◽  
Jeppe Kjaersgaard ◽  
...  
Keyword(s):  
South Dakota ◽  
Surface Runoff ◽  
Water Quantity ◽  
Runoff Water ◽  
Manure Application ◽  
Small Watersheds ◽  
Water Quantity And Quality

Modelling of Solute Transfer to Surface Runoff

1992 ◽  
Vol 26 (7-8) ◽  
pp. 1851-1856 ◽  
Author(s):  
J. L. Lai ◽  
K. S. L. Lo
Keyword(s):  
Potassium Chloride ◽  
Surface Runoff ◽  
Laboratory Experiments ◽  
Overland Flow ◽  
Chloride Concentration ◽  
Runoff Water ◽  
Mixing Depth ◽  
Change Rate ◽  
Solute Transfer ◽  
The Media

A mixing-based model for describing solute transfer to overland flow was developed. This model included a time-dependent mixing depth of the top layer and a complete-mixed surface runoff zone. In a series of laboratory experiments, runoff was passed at various velocities and depths over a medium bed. The media were saturated with uniform concentration of potassium chloride solution. Runoff water was sampled at the beginning and end of the flume and the potassium chloride concentration analyzed. Using this model, dimensionless ultimate mixing depth and dimensionless change rate of mixing depth from experimental data were investigated and implemented. The results showed that the Reynolds number and relative roughness are two important factors.

Rainfall and surface water resources of Rajasthan State, India

Water Policy ◽  
2015 ◽  
Vol 18 (2) ◽  
pp. 276-287 ◽  
Author(s):  
Naveen Kumar Gupta ◽  
A. S. Jethoo ◽  
S. K. Gupta
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Surface Runoff ◽  
Overland Flow ◽  
Anthropogenic Activities ◽  
The State ◽  
Subsequent Increase ◽  
Surface Water Resources ◽  
Fast Pace ◽  
Percentage Area

The water resources in Rajasthan State are facing a crucial stage even after average/good rainfall. Temporal distributions as well as the spatial variability of rainfall within the state were investigated by applying an analysis of variance (ANOVA) test. The effect of change in catchment characteristics and anthropogenic activities on overland flow are also investigated in this paper by applying a regression technique. Inflow to the surface water resources of the state is regularly decreasing. Time series analysis and sequential cluster analysis reveals that 1994 was the critical year, which divides the two consecutive non-overlapping epochs viz. pre-disturbance and post-disturbance. Due to increasing population and the subsequent increase in agriculture (specifically using groundwater sources) having increased catchment interceptions, there is a regular decreasing trend of surface runoff and surface water availability. The study highlights that, in spite of an increasing trend of rainfall witnessed during the last 100 years, inflow to the surface water resources of the state is decreasing at a fast pace owing to a decrease in the percentage area contributing to surface runoff.

scholarly journals Runoff water quantity and quality data from native tallgrass prairie and crop–livestock systems in Oklahoma between 1977 and 1999

2020 ◽  
Vol 49 (4) ◽  
pp. 1062-1072
Author(s):  
Amanda M. Nelson ◽  
Daniel N. Moriasi ◽  
Ann‐Marie Fortuna ◽  
Jean L. Steiner ◽  
Patrick J. Starks ◽  
...  
Keyword(s):  
Tallgrass Prairie ◽  
Quality Data ◽  
Water Quantity ◽  
Runoff Water ◽  
Livestock Systems ◽  
Water Quantity And Quality

scholarly journals Integrating Satellite Soil Moisture and Rainfall Data on a Data-Driven Model for the Assessment of Shallow Landslides Hazard

Proceedings ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 42
Author(s):  
Meisina ◽  
Bordoni ◽  
Lucchelli ◽  
Brocca ◽  
Ciabatta ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Methodological Approach ◽  
Regional Scale ◽  
Shallow Landslides ◽  
Predisposing Factors ◽  
Data Driven ◽  
Triggering Factors ◽  
Physically Based ◽  
Physically Based Models ◽  
Triggering Events

Shallow landslides are very dangerous phenomena, widespread all over the world, which could provoke significant damages to buildings, roads, facilities, cultivations and, sometimes, loss of human lives. It is then necessary assessing the most prone zones in a territory which is particularly susceptible to these phenomena and the frequency of the events, according to the return time of the triggering events, which generally correspond to intense and concentrated rainfalls. Susceptibility and hazard of a territory are usually assessed by means of physically-based models, that quantify the hydrological and the mechanical responses of the slopes according to particular rainfall amounts. Whereas, these methodologies could be applied in a reliable way in little catchments, where geotechnical and hydrological features of the materials affected by shallow failures are homogeneous. Moreover, physically-based models require, sometimes, significant computation power, which limit their implementations at regional scale. Data-driven models could overcome both of these limitations, even if they are generally built up taking into only the predisposing factors of shallow instabilities. Thus, they allow usually to estimate the susceptibility of a territory, without considering the frequency of the triggering events. It is then required to consider also triggering factors of shallow landslides to allow these methods to estimate also the hazard. This work presents the preliminary results of the development and the implementation of data-driven model able to estimate the hazard of a territory towards shallow landslides. The model is based on a Genetic Algorithm Model (GAM), which links geomorphological, hydrological, geological and land use predisposing factors to triggering factors of shallow failures. These triggering factors correspond to the soil moisture content and to the rainfall amounts, which are available for entire a study area thanks to satellite measures. The methodological approach is testing in different catchments of 30–40 km2 located in Oltrepò Pavese area (northern Italy), where detailed inventories of shallow landslides occurred during past triggering events and corresponding satellite soil moisture and rainfall maps are available. This work was made in the frame of the ANDROMEDA project, funded by Fondazione Cariplo.

Amending greenroof soil with biochar to affect runoff water quantity and quality

2011 ◽  
Vol 159 (8-9) ◽  
pp. 2111-2118 ◽  
Author(s):  
Deborah A. Beck ◽  
Gwynn R. Johnson ◽  
Graig A. Spolek
Keyword(s):  
Water Quantity ◽  
Runoff Water ◽  
Water Quantity And Quality
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