Embedded fuzzy controller for water level control

This article presents the design of a fuzzy controller embedded in a microcontroller aimed at implementing a low-cost, modular process control system. The fuzzy system's construction is based on a classical proportional and derivative controller, where inputs of error and its derivate depend on the difference between the desired setpoint and the actual level; the goal is to control the water level of coupled tanks. The process is oriented to control based on the knowledge that facilitates the adjustment of the output variable without complex mathematical modeling. In different response tests of the fuzzy controller, a maximum over-impulse greater than 8% or a steady-state error greater than 2.1% was not evidenced when varying the setpoint.

Effects of Cone Penetrometer Testing on Shallow Hydrogeology at a Contaminated Site

Penetration testing is a popular and instantaneous technique for subsurface mapping, contaminant tracking, and the determination of soil characteristics. While the small footprint and reproducibility of cone penetrometer testing makes it an ideal method for in-situ subsurface investigations at contaminated sites, the effects to local shallow groundwater wells and measurable influence on monitoring networks common at contaminated sites is unknown. Physical and geochemical parameters associated with cone penetrometer testing were measured from a transect of shallow groundwater monitoring wells adjacent to penetrometer testing. For wells screened above the depth of cone refusal, the physical advancement and retraction of the cone had a significant effect (p < 0.01) on water level for several pushes within 10 meters of a monitoring well, and a measured increase in specific conductivity. No effect on geochemistry or water level was observed in continuous monitoring data from wells screened below the depth of cone refusal, but variability in specific conductivity from these wells during penetration testing was only a fraction of the natural variation measured during precipitation events. Continuous measurements of specific conductivity and water level demonstrated that the effects of penetration testing have limited spatial and temporal distributions with a null effect post-testing.

Comparative Analysis of GEDI’s Elevation Accuracy from the First and Second Data Product Releases over Inland Waterbodies

Spaceborne LiDAR altimetry has been demonstrated to be an essential source of data for the estimation and monitoring of inland water level variations. In this study, water level estimates from the Global Ecosystem Dynamics Investigation (GEDI) were validated against in situ gauge station records over Lake Geneva for the period between April 2019 and September 2020. The performances of the first and second releases (V1 and V2, respectively) of the GEDI data products were compared, and the effects on the accuracy of the instrumental and environmental factors were analyzed in order to discern the most accurate GEDI acquisitions. The respective influences of five parameters were analyzed in this study: (1) the signal-over-noise ratio (SNR); (2) the width of the water surface peak within the waveform (gwidth); (3) the amplitude of the water surface peak within the waveform (A); (4) the viewing angle of GEDI (VA); and (5) the acquiring beam. Results indicated that all these factors, except the acquiring beam, had an effect on the accuracy of GEDI elevations. Nonetheless, using VA as a filtering criterion was demonstrated to be the best compromise between retained shot count and water level estimation accuracy. Indeed, by choosing the shots with a VA ≤ 3.5°, 74.6% of the shots (after an initial filter) were retained with accuracies similar to choosing A > 400 (46.2% retained shots), SNR > 15 dB (63.3% retained shots), or gwidth < 10 bins (46.5% of retained shots). Finally, the comparison between V1 and V2 elevations showed that V2, overall, provided elevations with a more constant, but higher, bias and fewer deviations to the in situ data than V1. Indeed, by choosing GEDI shots with VA ≤ 3.5°, the unbiased RMSE (ubRMSE) of GEDI elevations was 27.1 cm with V2 (r = 0.66) and 42.8 cm with V1 (r = 0.34). Results also show that the accuracy of GEDI (ubRMSE) does not seem to depend on the beam number and GEDI acquisition dates for the most accurate GEDI acquisitions (VA ≤ 3.5°). Regarding the bias, a higher value was observed with V2, but with lower variability (54 cm) in comparison to V1 (35 cm). Finally, the bias showed a slight dependence on beam GEDI number and strong dependence on GEDI dates.

WATER LEVEL FLUCTUATION USING SURVEILLANCE CAMERA

Floods are the most frequent type of natural disaster that cause loss of life and damages to personal property and eventually affect the economic state of the country. Researchers around the world have been made significant efforts in dealing with the flood issue. Computer vision is one of the common approaches being employed which include the use of image segmentation techniques for image understanding and image analysis. The technique has been used in various fields including in flood disaster applications. This paper explores the use of a hybrid segmentation technique in detecting water regions from surveillance images and introduces a flood index calculation to study water level fluctuations. The flood index was evaluated by comparing the result with water level measured by sensor on-site. The experimental results demonstrated that the flood index reflects the trend of water levels of the river. Thus, the proposed technique can be used in detecting water regions and monitoring the water level fluctuation of the river.

Water Level Has Higher Influence on Soil Organic Carbon and Microbial Community in Poyang Lake Wetland Than Vegetation Type

Although microorganisms play a key role in the carbon cycle of the Poyang Lake wetland, the relationship between soil microbial community structure and organic carbon characteristics is unknown. Herein, high-throughput sequencing technology was used to explore the effects of water level (low and high levels above the water table) and vegetation types (Persicaria hydropiper and Triarrhena lutarioriparia) on microbial community characteristics in the Poyang Lake wetland, and the relationships between soil microbial and organic carbon characteristics were revealed. The results showed that water level had a significant effect on organic carbon characteristics, and that soil total nitrogen, organic carbon, recombinant organic carbon, particle organic carbon, and microbial biomass carbon were higher at low levels above the water table. A positive correlation was noted between soil water content and organic carbon characteristics. Water level and vegetation type significantly affected soil bacterial and fungal diversity, with water level exerting a higher effect than vegetation type. The impacts of water level and vegetation type were higher on fungi than on bacteria. The bacterial diversity and evenness were significantly higher at high levels above the water table, whereas an opposite trend was noted among fungi. The bacterial and fungal richness in T. lutarioriparia community soil was higher than that in P. hydropiper community soil. Although both water level and vegetation type had significant effects on bacterial and fungal community structures, the water level had a higher impact than vegetation type. The bacterial and fungal community changes were the opposite at different water levels but remained the same in different vegetation soils. The organic carbon characteristics of wetland soil were negatively correlated with bacterial diversity but positively correlated with fungal diversity. Soil water content, soluble organic carbon, C/N, and microbial biomass carbon were the key soil factors affecting the wetland microbial community. Acidobacteria, Alphaproteobacteria, Verrucomicrobia, Gammaproteobacteria, and Eurotiomycetes were the key microbiota affecting the soil carbon cycle in the Poyang Lake wetland. Thus, water and carbon sources were the limiting factors for bacteria and fungi in wetlands with low soil water content (30%). Hence, the results provided a theoretical basis for understanding the microbial-driven mechanism of the wetland carbon cycle.

Determining Extreme Still Water Levels for Design and Planning Purposes Incorporating Sea Level Rise: Sydney, Australia

This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can drive ocean water levels higher at the coast. The analysis is based on the Peaks-Over-Threshold (POT) method using a fitted Generalised Pareto Distribution (GPD) function to estimate extreme hourly heights above mean sea level. The analysis highlights the impact of the 1974 East Coast Low event and rarity of the associated measured water level above mean sea level at Sydney, with an estimated return period exceeding 1000 years. Extreme hourly predictions are integrated with future projections of sea level rise to provide estimates of relevant still water levels at 2050, 2070 and 2100 for a range of return periods (1 to 1000 years) for use in coastal zone management, design, and sea level rise adaptation planning along the NSW coastline. The analytical procedures described provide a step-by-step guide for practitioners on how to develop similar baseline information from any long tide gauge record and the associated limitations and key sensitivities that must be understood and appreciated in applying EVA.

Stabilitas Tanah Timbunan Sisi BH-1 Proyek Jalan Akses Pembangunan Jembatan Pulau Balang II

Problem on the road access landfill at Balang Island II Bridge is the landslide at STA 23+025 on left side slope (BH-1) caused by a swamp pond on the roadside. The landfill that cutted into the swampy area made the water get stuck on one side (water could not flow to the original condition). The research method is the form of direct observation in the field which focuses on the results of information and laboratory testing which is then processed and analyzed. The analysis obtained that the soil type on the spot is clay with N-SPT 6 – 29. There are 2 alternatives solutions for the problem. First, if there is a ROW problem, the treatments are watercourse, adding counterweight, wooden pile under the landfill and one layer Geotextile PP 50 (initial ground water level on exsisting condition with 90,4 kPa loads). Second, if there is no ROW problem, the treatments are watercourse, adding counterweight, wooden pile under the landfill and one layer Geotextile PET 100 (initial ground water level on top of landfill with 90,4 kPa loads). Based on technical analysis, the second solution was chosen because it has bigger safety factor, smallest settlement value, and shorter time implementation. However it is still need more detail technical justification to strengthen the desicion.