Abstract
A nonparametric machine learning model was used to study the behaviour of the variables of a concrete arch dam: Roode Elsberg dam. The variables used were ambient temperature, water temperatures, and water level. Water temperature was measured using twelve thermometers; six thermometers were on each flank of the dam. The thermometers were placed in pairs on different levels: avg6 (avg6-R and avg6-L) and avg5 (avg5-R and avg5-L) were on level 47.43 m, avg4 (avg4-R and avg4-L) and avg3 (avg3-R and avg3-L) were on level 43.62 m, and avg2 (avg2-R and avg2-L) and avg1 (avg1-R and avg1-L) were on level 26.23 m. Four neural networks and four random forests were cross-validated to determine their best-performing hyperparameters with the water temperature data. Quantile random forest was the best performer at mtry 7 (Number of variables randomly sampled as candidates at each split) and RMSE (Root mean square error) of 0.0015, therefore it was used for making predictions. The predictions were made using two cases of water level: recorded water level and full dam steady-state at Representative Concentration Pathway (RCP) 4.5 (hot and cold model) and RCP 8.5 (hot and cold model). Ambient temperature increased on average by 1.6 °C for the period 2012–2053 when using recorded water level; this led to increases in water temperature of 0.9 °C, 0.8 °C, and 0.4 °C for avg6-R, avg3-R, and avg1-R, respectively, for the period 2012–2053. The same average temperature increase led to average increases of 0.7 °C for avg6-R, 0.6 °C for avg3-R, and 0.3 °C for avg1-R for a full dam steady-state for the period 2012–2053.
Highlights
Dams are an important infrastructure, and their failure has high economic and social consequences
Does this mean that the dam wall gets exposed to more temperatures during seasons when the water level is low? It is definitely an area to explore, but the evidence from the data shows that it takes on average 53 days for the dam to feel the effects of temperature increase in the season when the dam lost most of its water and it takes 79 days on average for the day to feel the effects of an increase in temperature during a full dam’s steady-state
An average temperature increase of 1.6 ◦ C for ambient temperature led to average water temperature increases of 0.9 ◦ C for avg6-R, which is at level 47.3 m; of 0.8 ◦ C for avg3-R at level 43.62 m; and of 0.4 ◦ C for avg1-R, which is at level 26.23 m
Summary
Dams are an important infrastructure, and their failure has high economic and social consequences. This is because they have an associated risk that must be managed in a continuous and updated process [1]. In the context of dam safety, risk is estimated by combining the impact of a scenario, the probability of occurrence of that scenario, and the associated consequence of that scenario [2]. The associated risk posed on dams by a scenario is carried out assuming stationary climatic and non-climatic conditions. The projected alterations due to climate change are likely to affect different factors driving dam risk [4], like variations in extreme temperatures or frequency of heavy precipitation events
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