Climate change impact on water resources in Indian river basins: A review

Manivannan, S.; Thilagam, V. Kasthuri; Yaligar, Ravindra

doi:10.5958/2455-7145.2022.00009.1

Cited by 2 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…River basin water resources have been used for irrigation, industry, navigation, drinking water, hydropower, and variety of local livelihoods (Mirza et al 2003). Manivannan et al (2022) states that blue print of irrigation and water conservation structures needs to deliberated, as due to climate change and melting of glaciers there could be increase in river flows due to melting of glaciers and the trend will reverse in the long term, high intensity rainfall events and temperature will have its own consequences. The peak discharge rate will be high resulting in frequent floods, hence necessary designs need to be adopted for protecting structures in addition to afforestation for conservation of soil and water.…”

Section: Biomass Carbonization Cum Liquefaction Unitmentioning

confidence: 99%

Tree-based diversified land-use system: Augmenting livelihood security and industrial growth

2023

IJE

View full text Add to dashboard Cite

Forests are very important natural resource helping in ecological balance. Sustainable use of forest resources is critical for better livelihood options and contribute substantially to the economic development of any nation by providing goods and services to the human society, wild and domestic animal and industry. Tree based diversified land use system is very much essential to reduce the vulnerability of people to climate change by providing food and other ecosystem services during critical periods of climate change driven food shortages. In the present scenario, it is required to provide security for food, environment, livelihood and raw material for present and future generation. To address these all, tree based diversified land-use systems are much advocated. Many academicians, researcher, industrialists, policy makers throughout the world have started orbiting around these pertinent issues. With this background, it is planned to take up the scientific event entitled "Tree Based Diversified Land-use System: Augmenting Livelihood Security

show abstract

Section: Biomass Carbonization Cum Liquefaction Unitmentioning

confidence: 99%

Tree-based diversified land-use system: Augmenting livelihood security and industrial growth

2023

IJE

View full text Add to dashboard Cite

show abstract

Understanding the Effect of Hydro-Climatological Parameters on Dam Seepage Using Shapley Additive Explanation (SHAP): A Case Study of Earth-Fill Tarbela Dam, Pakistan

Ishfaque

Salman

Jadoon

et al. 2022

Water

View full text Add to dashboard Cite

For better stability, safety and water resource management in a dam, it is important to evaluate the amount of seepage from the dam body. This research is focused on machine learning approach to predict the amount of seepage from Pakistan’s Earth and rock fill Tarbela Dam during 2003 to 2015. The data of temperature, rainfall, water inflow, sediment inflow, reservoir level collected during 2003 to 2015 served as input while the seepage from dam during this period was the output. Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), and CatBoost (CB), have been used to model the input-output relationship. The algorithms used to predict the dam seepage reported a high R2 scores between actual and predicted values of average seepage, suggesting their reliability in predicting the seepage in the Tarbela Dam. Moreover, the CatBoost algorithm outperformed, by achieving an R2 score of 0.978 in training, 0.805 in validation, and 0.773 in testing phase. Similarly, RMSE was 0.025 in training, 0.076 in validation, and 0.111 in testing phase. Furthermore, to understand the sensitivity of each parameter on the output (average seepage), Shapley Additive ExPlanations (SHAP), a model explanation algorithm, was used to understand the affect of each parameter on the output. A comparison of SHAP used for all the machine learning models is also presented. According to SHAP summary plots, reservoir level was reported as the most significant parameter, affecting the average seepage in Tarbela Dam. Moreover, a direct relationship was observed between reservoir level and average seepage. It was concluded that the machine learning models are reliable in predicting and understanding the dam seepage in the Tarbela Dam. These Machine Learning models address the limitations of humans in data collecting and analysis which is highly prone to errors, hence arriving at misleading information that can lead to dam failure.

show abstract

Climate change impact on water resources in Indian river basins: A review

Cited by 2 publications

References 0 publications

Tree-based diversified land-use system: Augmenting livelihood security and industrial growth

Tree-based diversified land-use system: Augmenting livelihood security and industrial growth

Understanding the Effect of Hydro-Climatological Parameters on Dam Seepage Using Shapley Additive Explanation (SHAP): A Case Study of Earth-Fill Tarbela Dam, Pakistan

Contact Info

Product

Resources

About