Characterization of Sediment Yield Behaviour from a Micro Catchment Area of a Farm Pond for Storm Wise Runoff Events in North-Eastern Dry Zone of Karnataka, India

Aims: The study aims to measure the runoff event wise sediment yield for a micro catchment area of the farm pond and characterise its behaviourPlace and Duration of Study: The study was conducted in a micro catchment (field sized area) of a dugout farm pond, having an area of 6 ha located in the new area of UAS campus Raichur, which comes under Zone II in Region-I of Karnataka state. Geographically it is located at 16° 12′ N latitude and 77° 20′ E longitude and at an elevation of 389 m above the mean sea level (MSL). The study was conducted for a period of one year during 2019.Methodology: The existing farm pond was used to conduct sediment yield studies in a micro catchment area. The rainfall intensity for each storm has been measured using self-recording rain gauge. The runoff has been measured at the out let of the field sized micro catchment area of farm pond using hydraulic structures coupled with automatic runoff recorder. The runoff sampling has been done for sediment/ soil loss assessment. The event wise rainfall, rainfall intensity and runoff followed by sediment yield have been have been measured and analysed to see the relationship between rainfall intensity and runoff with prevailing soil and topographical characteristics of the study area.Results: The event wise runoff samples of the micro catchment area during the runoff events were collected from the stilling well coupled with hydraulic structure constructed at the outlet of the micro catchment area. As rainfall intensity increases it causes the water loss and surface soil erosion and increases sediment yield at the surface.Conclusion: In the present study the red gram crop was grown and it had affected the sediment yield especially during September and October months. Rainfall is most dynamic factor which affects the sediment yield.

Daily Sediment Yield Prediction Using Hybrid Machine Learning Approach

In this study, four different soft computing AI techniques were tested for the prediction of sediment yield based on hydro-meteorological variables at Jondhara station, Seonath stream in Rajnandgaon district, India. In order to fulfill this purpose, the models namely, multilayer perceptron (MLP), support vector machine (SVM), multilayer perceptron coupled with genetic algorithm (MLP-GA), and support vector machine coupled with genetic algorithm (SVM-GA) models were employed. To select the optimal input variables, a statistical method such as the Gamma test was considered among several methods. Based on the results of the analysis, all models were evaluated by using the following statistical indices: Coefficient of Correlation (CC), room mean square error (RMSE) and percent bias (PBAIS). Overall, the performance of the studied models indicates that all of them are capable of simulation sediments yield at Jondhara station, Seonath river basin in a satisfactory manner. Comparison of results showed that the MLP-GA with CC = 0.988, RMSE = 0.006 and PBIAS = 0.000 in training period and CC= 0.990, RMSE = 0.007 and PBIAS = 0.000 in testing period for S-6 model and CC = 0.986, RMSE = 0.025 and PBIAS = -0.001 in training period and CC = 0.988, RMSE = 0.029 and PBIAS = -0.001 in testing period for S-13 model were able to yield better results than the other models considered. Furthermore, an SVM model is also observed to have some advantages over MLP models and SVM-GA models since it can represent the output data in a continuous manner by fitting a linear regression function to the output data, which has the advantage of making the model more precise than MLP and SVM-GA models.

Monitoramento de bacias hidrográficas para identificar fontes de sedimentos em suspensão / Catchment monitoring to trac suspended sediment sources

Programas de conservação do solo e da água que utilizam a bacia hidrográfica como unidade de planejamento têm sido amplamente empregados. Um componente importante desses programas se refere à implantação de projetos de monitoramento hidrossedimentométrico e de qualidade de água para avaliar o impacto nos recursos hídricos das práticas introduzidas. Entretanto, em alguns casos, os resultados obtidos pelos projetos de monitoramento têm sido pouco conclusivos, devido a limitações dos procedimentos experimentais adotados. Esta revisão explora metodologias de avaliação que combinam técnicas tradicionais de monitoramento com técnicas de identificação de fontes de sedimentos que contribuem para elucidar os efeitos das práticas conservacionistas na produção de sedimentos em bacias hidrográficas e também a inter-relação dinâmica entre as fontes de sedimentos.

Soil and water conservation programs frequently use catchments as planning units. An important follow-up component of these programs is the installment of hydrosedimentometric and water quality monitoring projects to evaluate the impact of the practices introduced. However, in some cases, these monitoring projects have yielded inconclusive results, mostly due to procedural limitations. This review explores methods that combine traditional monitoring techniques with sediment source identification to further elucidate the impact of conservation practices on sediment yield in the catchment and dynamic interactions between different sediment sources.

Hydrosedimentological dynamic on Água Fria Watershed

This study aimed surveying the amount of sediment yielded from the Água Fria watershed (Palmas, Tocantins, Brazil), from February-1998 to January-1999, and investigating the relations between the sediment yield and some environmental and/or antropic factors. The Colby's method was the technique employed for this investigation. The specific sediment yield and sediment delivery ratio were also determined for this period. It was estimated that 138,619 tons of sediment were yielded and the specific sediment yield for the study area was 827 t km-2 y-1, while the sediment delivery ratio was 6.2 percent. The suspended load was the most dominating fraction in almost all the studied period.

Este estudo objetivou estimar a quantidade de sedimento que foi carreada da microbacia do Ribeirão Água Fria (Palmas, TO) entre fevereiro de 1998 e janeiro de 1999. Almejou-se ainda investigar as relações entre a produção de sedimento e alguns fatores antrópicos e ambientais. O método de Colby foi a técnica empregada no estudo. A produção específica de sedimento e o coeficiente de remoção de sedimentos foram parâmetros também investigados neste trabalho. Foi estimada uma quantidade de 138.619 toneladas de sedimento produzido e a produção específica de sedimentos foi estimada como sendo 827 t km-2 ano-1, enquanto que o coeficiente de remoção de sedimentos foi 6,2 por cento. A fração suspensa foi a predominante durante quase todo o período de estudo.