Flow variation in urban and forested environments at Atlantic Forest Biome

Código

I-EBHE0168

Autores

Emanuel Giovani Cafofo Silva, Thiago Auer Camilo de Jesus, Luiz Fernando Teodoro Tabosa Flegler, Leandro Meneguelli Biondo, Laércio Ferracioli

Tema

WG 3.3: Co-Creating Water Knowledge

Resumo

A collaborative study was conducted, comparing flow variation coefficients from hydrological monitoring and citizen science data collection in a threatened biodiversity hotspot with sustainability opportunities in Santa Teresa, Espírito Santo State, Brazil. The hydrological monitoring has been ongoing since 2022, gathering data from five forest reserve streams (24KUD3667002359, 24KUC3876099035, 24KUC3791096313, 24KUC3094796521, and 24KUC3971190538) in a rainy mountainous region within the Atlantic Forest Biome, a crucial area for environmental conservation. Here We select data within the range between March 29 to April 7, 2022, aligning with the "citizen science" flow data collection period (March 22-31, 2022) for a single impacted river (24KUC3249394706). All these rivers belong to mild or cold climate areas. The flow measurements were obtained by timing the flow of a floating lemon over a 6-meter stream section with known depths. flow=(((1ºud+2ºud+3ºud+4ºud)*uw)+((1ºdd+2ºdd+3ºdd+4ºdd)*dw))/2*slt/t*c, where ud=upstream depth, dd=downstream depth, uw=upstream width, dw=downstream width, sl=section length, t=time, c=correction coefficient. The formula for calculating flow includes a correction coefficient of 0.81 for stony-bottom rivers. In collaboration with our team, six school classes obtained five flow estimates (x ?=10,937.232l/min, s=898.496), each based on averages of eleven lemon floating travel intervals timed by students. Regarding the monitoring data, each of the five flow estimates was an intermediate result of two flow estimates obtained within 24 hours by one collector using the average of three consecutive lemon travel times. These five flow estimates (x ?=643.18776l/min, s=280.918) underwent Mantel tests to assess changes in stream altitude and upstream length. Also, Mantel correlograms were conducted to identify spatial correlation. Neither spatial correlation, altitude and length effects were identified. The monitored streams are classified as 2º order, while the Citizen Science stream is above the 4º order, a difference that, when coupled with distinct data protocols, could influence dataset patterns. We address this with: variation coefficient=s/x ? *100, determined as 43.67584% for monitoring and 8.215017% for citizen science data collection. This value indicates that the expected low variability for measurements of the same river is achieved even with timers operated by different observers, highlighting the significant potential of citizen science in generating quality data. On the other hand, the high monitoring variation coefficient indicates flow differences among streams within almost the same geographic context. Those differences were observed even with single collector measurements, perhaps due to the absence of geographic distance-decay patterns over altitude and channel length, suggesting that streams in similar preserved areas still have unique characteristics. These findings reveal the significance of monitoring and societal support in the Atlantic Forest Biome hydrology and conservation.