Temporal estimation of hydrodynamic parameter variability in stormwater constructed wetlands – The hysteresis effect during multi-rainfall events

Abstract

Constructed wetland (CW) systems are increasingly implemented as rustic water treatment facilities, the efficiency of which varies with time due to possible malfunctions such as clogging related to excessive loads of suspended solids or inadequate CW sizing. A numerical flow modeling can be used to evaluate filtering performance and to improve the design of CWs. Such a modeling usually involves the so-called van Genuchten-Mualem (vGM) soil hydrodynamic parameters which are notoriously difficult to measure. The meticulous attention brought to the sensitivity of the model to the vGM parameters reveals a predominant influence of the shape parameters and the saturated conductivity of the filter on the piezometric heads, during feeding and drainage. We then discuss a simple, robust and low-cost inverse modeling approach, deterministic and stochastic, for the identification of the soil hydrodynamic properties from piezometric heads measured during successive storm events. The temporal variability of hydrodynamic parameters is assessed and analyzed with regards to modeling efficiency. Principal component analysis shows that the estimated hydrodynamic parameters from the feeding and drainage sub-periods are significantly different.

Urban stormwater characterization, control, and treatment

“…Based on these findings, Hale et al (2019) suggest management approaches to minimize adverse effects on resident biota by, for example, deliberately designing vegetation and other habitat features to attract biota to suitable habitat away from wetland inlets or other areas with higher pollutant concentrations. Moezzibadi, Charpentier, Wanko, and Mosé (2019) examined changes in physical filtration functions of a vertical flow constructed stormwater wetland over a 5-year period using both piezometric head data and deterministic and stochastic modeling approaches. The filter layer's hydraulic response to wetting and drying cycles exhibited hysteresis effects, but also changed through time, likely in association with changes in vegetation biomass and root structure, deposition, and other characteristics of the filtration layer.…”

“…Moezzibadi, Charpentier, Wanko, and Mosé (2019) examined changes in physical filtration functions of a vertical flow constructed stormwater wetland over a 5‐year period using both piezometric head data and deterministic and stochastic modeling approaches. The filter layer's hydraulic response to wetting and drying cycles exhibited hysteresis effects, but also changed through time, likely in association with changes in vegetation biomass and root structure, deposition, and other characteristics of the filtration layer.…”

“…Nearly every study reviewed indicated these ecological components play an important role in pollutant transformations and/or removal in CSW systems. Many also provided insights into how ecologically mediated pollutant removal processes may change in response to environmental variables such as temperature (e.g., Rahman et al, 2019) and wetting and drying cycles (Moezzibadi et al, 2019; Rahman, Grace, Grace, Roberts, Kessler, & Cook, 2019) pointing to the need to consider how water treatment and other services provided by CSWs may respond to changes in climate, rainfall and drought patterns, and associated shifts in modes of pollutant delivery.…”

Wetlands for environmental protection

“…Temporal estimation of hydrodynamic parameter variability in stormwater CWs was studied using numerical flow modeling technique and reported that the hydrodynamic characterization was influenced by the rain characteristics (Moezzibadi, Charpentier, Wanko, & Mosé, 2019). Efficacy of Carex paniculata planted CW for the treatment of mixed stormwater, sewage, and livestock wastewater effluent was investigated, and 2‐years of operational results demonstrated that Carex paniculata CWs showed greater potential for wastewater treatment, with high removal efficiency for BOD 5 , COD, and TSS (96%, 91%, 83%, respectively) (Cicero Fernandez, Expósito Camargo, Peña Fernandez, & Antizar‐Ladislao, 2019).…”