A contribution to rainfall simulator design – a concept of moving storm automation

• Published in: Hydrology and earth system sciences Vol. 26; no. 16; pp. 4379 - 4390
• Main Authors: Meena, Ravi Kumar, Sen, Sumit, Nanda, Aliva, Dass, Bhargabnanda, Mishra, Anurag
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 26.08.2022; Copernicus Publications
• Subjects: Analysis; Applications programs; Automatic control; Automation; Control systems; Dependent variables; Design; Experiments; Flood peak; Flumes; Hydrographs; Hydrology; Independent variables; Loam soils; Mobile computing; Movement; Multiple regression models; Nozzles; Power supply; Precipitation; Pressure regulators; Rain; Rain and rainfall; Raindrop velocity; Rainfall; Rainfall simulators; Regression analysis; Regression models; Runoff; Simulation; Simulators; Slope gradients; Soil erosion; Soils; Sprinkler systems; Statistical analysis; Storm rainfall; Storms; Technology application; Valves; Velocity; Water shortages
• ISSN: 1607-7938; 1027-5606; 1607-7938
• DOI: 10.5194/hess-26-4379-2022

We developed an advanced-design programmable rainfall simulator (RS) to simulate a moving storm rainfall condition. The RS consists of an automated nozzle control system coupled with a pressure regulator mechanism for an operating range of 50 to 180 kPa at a drop height of 2000 mm above the soil flume surface. Additionally, a programmable mobile application was developed to regulate all RS valves. Near natural rainfall conditions were simulated at varying spatial and temporal resolutions in a controlled environment. A soil flume of 2500 mm × 1400 mm × 500 mm was fabricated to conduct different hydrological experiments. The flume was designed to record overland, subsurface, and baseflows simultaneously. This study focused on a detailed analysis of moving storms and their impact on hydrograph characteristics. Experimental results showed a considerable difference in terms of time to peak (tp), peak discharge (Qp), and hydrograph recession for two different storm movement directions (upstream and downstream). Two multiple regression models indicate a statistically significant relationship between the dependent variable (tp or Qp) and the independent variables (i.e. storm movement direction, storm velocity, and bed slope gradient) at a 5 % level of significance. Further, the impact of these moving storm phenomena reduces with the increase in the storm movement velocity.