Visual Harmony of Engineering Structures in a Mountain Stream

This study uses the cognitive factor of “visual harmony” to assess the visual quality of stream engineering in a mountainous region. Images of engineering structures such as revetments and submerged dams in the mountain streams of Taiwan were collected. Three image groups with different structures invaded by vegetation were used for a questionnaire survey, which yielded 154 valid samples. We used statistical analysis to develop a model of visual harmony H with respect to the percentage of visible greenery GR, that is, the perceived curve of vegetation change. A comparison of our data with the literature determined the upper and lower bound curves of the relationship between H and GR. We found that the physical elements of “softscape” and “hardscape”—namely, percentage of visible water WR, visible structure IR, and visible natural material on the structure NR—affected this relationship. Results show that H is equivalent to visual preference P, and both can be improved by better green visibility (increasing GR and GR < 50%), avoiding low water visibility (WR < 10%), or increasing the amount of visible natural material (NR > 0.9). High visibility of the structures (IR > 0.3) may decrease H and P. We ultimately propose a visual harmony or preference model concerning a combined physical indicator that comprises GR, WR, IR and NR. Results of this study could be helpful to improve or access the aesthetics of stream engineering design

Visual Harmony of the Proportion of Water and Greenery in Urban Streams: Baxi Stream, Yongan City, China

This study investigated the visual harmony of an urban stream considering changes to the ratio of water to greenery on the riverbed. The Baxi stream, a third-order stream in Yongan City, Fujian Province, China was selected as the study site. The stream reach is disturbed by several hydraulic structures, such as restricted water flow by a vertical revetment and water level regulation by submerged dams. Images of the river were captured, and image processing was performed to change the proportion of water and greenery, and the proportions of various landscape elements in the image were calculated. Based on the statistical analysis of survey results, cognitive indicators (vividness and naturalness) associated with harmony and preference, and the relationship between harmony or preference and landscape elements, were established. Landscape elements included ratios of visible water (WR), visible greenery (GR), visible buildings, and visible infrastructure. The results demonstrated that visual preference, P, is positively correlated with harmony, H, vividness, V, and naturalness, N. In particular, H is almost consistent to P. The proportion of visible water and greenery had a significant impact on the H and P of the stream landscape. When the ratio of WR to GR was approximately 0.8, H was optimal, and the public’s P was high. These results can be used to improve and enhance the visual landscape quality of this stream reach. The methodology proposed in this study could provide other study areas with a reference for how to obtain the best visual harmony or achieve public acceptance by changing the amount of visible water and/or greenery

Evaluation of Rainfall-Triggered Debris Flows under the Impact of Extreme Events: A Chenyulan Watershed Case Study, Taiwan

This study examined the conditions that lead to debris flows, and their association with the rainfall return period (T) and the probability of debris flow occurrence (P) in the Chenyulan watershed, central Taiwan. Several extreme events have occurred in the Chenyulan watershed in the past, including the Chi-Chi earthquake and extreme rainfall events. The T for three rainfall indexes (i.e., the maximum hourly rainfall depth (Im), the maximum 24-h rainfall amount (Rd), and RI (RI = Im× Rd)) were analyzed, and the T associated with the triggering of debris flows is presented. The P–T relationship can be determined using three indexes, Im, Rd, and RI; how it is affected and unaffected by extreme events was developed. Models for evaluating P using the three rainfall indexes were proposed and used to evaluate P between 2009 and 2020 (i.e., after the extreme rainfall event of Typhoon Morakot in 2009). The results of this study showed that the P‒T relationship, using the RI or Rd index, was reasonable for predicting the probability of debris flow occurrence

THE VISUAL PREFERENCE FOR RIVERBED VEGETATION: A CASE STUDY IN CENTRAL TAIWAN

The visual preference influenced by riverbed vegetation was studied in this paper. The study area is located in the Liou River and Ma-Yuan-Tou River in Taichung city, central Taiwan. Five artificialized sections in both rivers were selected as the observation sites to examine the changes in the riverbed. The green looking ratio (GR) was used to evaluate the images of green areas in spaces due to vegetation on the riverbed. Six cognitive factors: naturalness N, vividness V, harmony H, closure CL, continuity CO, and mystery M, were used to discuss the factors associated with visual preference. First, various river landscape images with changes in riverbed vegetation were collected and simulated by image processing. Second, the visual preference and cognitive factors were rated by the questionnaire survey method. A total of 246 valid questionnaires were used. Finally, the visual preference associated with GR and the cognitive factors were analyzed. The results showed that the visual preference P increased with increasing GR, especially when GR > 40%. A higher N, V, and CO, or a lower CL can help promote visual preference

Assessment of the Visual Quality of Sediment Control Structures in Mountain Streams

Sediment control structures such as check dams, groundsills, and revetments are commonly used to balance sediment transport. In this study, we investigated the visual quality of sediment control structures that have been installed to manage mountain streams by analyzing images from the Soil and Water Conservation Bureau (SWCB) of Taiwan. We used visual preference (P) as an indicator in the evaluation of visual quality and considered two softscape elements and four cognitive factors associated with P. The two softscape elements were the visible body of water and vegetation, which were represented by the percentage of visible water (WR) and the percentage of visible greenery (GR). We considered four cognitive factors: naturalness, harmony, vividness, and closeness. Using a questionnaire-based survey, we asked 212 experts and laypeople to indicate their visual preferences (P) for the images. We examined the associations of the P ratings with cognitive factors and softscape elements and then established an empirical relationship between P and the cognitive factors using multiple regression analysis. The results showed that the subjects’ visual preferences were strongly affected by the harmony factor; the subjects preferred the proportion of softscape elements to be 30% WR and 40% GR for optimal harmony, naturalness, and visual quality of the sediment control structures. We discuss the visual indicators, visual aesthetic experiences, and applications of the empirical relationship, and offer insights into the study’s implications

Assessment of the Visual Quality of Sediment Control Structures in Mountain Streams

Sediment control structures such as check dams, groundsills, and revetments are commonly used to balance sediment transport. In this study, we investigated the visual quality of sediment control structures that have been installed to manage mountain streams by analyzing images from the Soil andWater Conservation Bureau (SWCB) of Taiwan. We used visual preference (P) as an indicator in the evaluation of visual quality and considered two softscape elements and four cognitive factors associated with P. The two softscape elements were the visible body of water and vegetation, which were represented by the percentage of visible water (WR) and the percentage of visible greenery (GR). We considered four cognitive factors: naturalness, harmony, vividness, and closeness. Using a questionnaire-based survey, we asked 212 experts and laypeople to indicate their visual preferences (P) for the images. We examined the associations of the P ratings with cognitive factors and softscape elements and then established an empirical relationship between P and the cognitive factors using multiple regression analysis. The results showed that the subjects’ visual preferences were strongly a ected by the harmony factor; the subjects preferred the proportion of softscape elements to be 30% WR and 40% GR for optimal harmony, naturalness, and visual quality of the sediment control structures. We discuss the visual indicators, visual aesthetic experiences, and applications of the empirical relationship, and o er insights into the study’s implications