scholarly journals Measurement of the water balance components of a large green roof in Greater Paris Area

2019 ◽  
Author(s):  
Pierre-Antoine Versini ◽  
Filip Stanic ◽  
Auguste Gires ◽  
Daniel Scherzer ◽  
Ioulia Tchiguirinskaia
Keyword(s):  
Water Balance ◽  
Spatial Variability ◽  
Stormwater Management ◽  
Green Roof ◽  
Rainfall Event ◽  
Monitoring Site ◽  
Water Balance Components ◽  
Data Set ◽  
Paris Area ◽  
Substrate Heterogeneity

Abstract. The Blue Green Wave of Champs-sur-Marne (France) represents the largest green roof (1 ha) of the Greater Paris Area. The Hydrology, Meteorology and Complexity lab of Ecole des Ponts ParisTech has chosen to convert this architectural building as a full-scale monitoring site devoted to study the performances of green infrastructures in stormwater management. For this purpose, the relevant components of the water balance during a rainfall event have been monitored: rainfall, water content in the substrate and the discharge flowing out of the infrastructure. Data provided by adapted measurement sensors were collected during 78 days between February and May 2018. The related raw data and a python program transforming them into hydrological quantities and providing some first elements of analysis have been made available. These measurements are useful to better understand the processes (infiltration and retention) conducted their hydrological performances, and their spatial variability due to substrate heterogeneity. Link to the data set (Versini et al., 2019): https://doi.org/10.5281/zenodo.3467300 (doi:10.5281/zenodo.3467300).

scholarly journals Measurements of the water balance components of a large green roof in the greater Paris area

2020 ◽  
Vol 12 (2) ◽  
pp. 1025-1035 ◽  
Author(s):  
Pierre-Antoine Versini ◽  
Filip Stanic ◽  
Auguste Gires ◽  
Daniel Schertzer ◽  
Ioulia Tchiguirinskaia
Keyword(s):  
Water Management ◽  
Water Balance ◽  
Green Roof ◽  
Rainfall Event ◽  
Storm Water ◽  
Monitoring Site ◽  
Water Balance Components ◽  
Data Set ◽  
Paris Area ◽  
Substrate Heterogeneity

Abstract. The Blue Green Wave of Champs-sur-Marne (France) represents the largest green roof (1 ha) of the greater Paris area. The Hydrology, Meteorology and Complexity lab of École des Ponts ParisTech has chosen to convert this architectural building into a full-scale monitoring site devoted to studying the performance of green infrastructures in storm-water management. For this purpose, the relevant components of the water balance during a rainfall event have been monitored: rainfall, water content in the substrate, and the discharge flowing out of the infrastructure. Data provided by adapted measurement sensors were collected during 78 d between February and May 2018. The related raw data and a Python program transforming them into hydrological quantities and providing some preliminary elements of analysis have been made available. These measurements are useful to better understand the hydrological processes (infiltration and retention) conducting green roof performance and their spatial variability due to substrate heterogeneity. The data set is available here: https://doi.org/10.5281/zenodo.3687775 (Versini et al., 2019b).

scholarly journals Characterizing uncertainty in the hydraulic parameters of oil sands mine reclamation covers and its influence on water balance predictions

2020 ◽  
Vol 24 (2) ◽  
pp. 735-759 ◽  
Author(s):  
M. Shahabul Alam ◽  
S. Lee Barbour ◽  
Mingbin Huang
Keyword(s):  
Water Balance ◽  
Oil Sands ◽  
Monitoring Site ◽  
Hydraulic Parameters ◽  
Oil Sand ◽  
Water Balance Components ◽  
Area Index ◽  
Parameter Values ◽  
The Impact

Abstract. One technique to evaluate the performance of oil sands reclamation covers is through the simulation of long-term water balance using calibrated soil–vegetation–atmosphere transfer models. Conventional practice has been to derive a single set of optimized hydraulic parameters through inverse modelling (IM) based on short-term (<5–10 years) monitoring datasets. This approach is unable to characterize the impact of variability in the cover properties. This study utilizes IM to optimize the hydraulic properties for 12 soil cover designs, replicated in triplicate, at Syncrude's Aurora North mine site. The hydraulic parameters for three soil types (peat cover soil, coarse-textured subsoil, and lean oil sand substrate) were optimized at each monitoring site from 2013 to 2016. The resulting 155 optimized parameter values were used to define distributions for each parameter/soil type, while the progressive Latin hypercube sampling (PLHS) method was used to sample parameter values randomly from the optimized parameter distributions. Water balance models with the sampled parameter sets were used to evaluate variations in the maximum sustainable leaf area index (LAI) for five illustrative covers and quantify uncertainty associated with long-term water balance components and LAI values. Overall, the PLHS method was able to better capture broader variability in the water balance components than a discrete interval sampling method. The results also highlight that climate variability dominates the simulated variability in actual evapotranspiration and that climate and parameter uncertainty have a similar influence on the variability in net percolation.

Monitoring the water balance of seepage lakes to track regional responses to an evolving climate

2021 ◽  
Author(s):  
Carl J Watras ◽  
James R Michler ◽  
Jeff Rubsam
Keyword(s):  
Water Balance ◽  
Spatial Variability ◽  
Low Cost ◽  
Water Levels ◽  
Model Systems ◽  
Water Balance Components ◽  
Single Node ◽  
Water Budgets ◽  
Seepage Lake ◽  
Lake Stage

Understanding the causes of large fluctuations in lake water levels is important for adaptive resource management. The relatively simple water budgets of small seepage lakes make them potentially useful model systems, provided that key water balance components can be well constrained. Here, spatial variability in measured rates of evaporation (E) and precipitation (P) at the whole lake scale was investigated, and the effect on daily and seasonal water balance estimates was quantified. To estimate spatial variability, triplicate sensor platforms were deployed on and near an 18 ha seepage lake. Lake stage (S) was monitored at a single node in the lake. The water balance was closed by estimating net groundwater seepage (Gnet) analytically as Gnet = ∆S – (P – E). Instrumentation on a second seepage lake was maintained by citizen scientists to assess the potential for more widespread sensor deployments. Data were collected every 30-minutes for six months. The results indicate that low-cost sensor networks with single nodes to measure E, P and ∆S provide well-constrained water budgets at daily and seasonal time scales.

scholarly journals Green-roof as a solution to solve stormwater management issues? Assessment on a long time period at the parcel scale

2014 ◽  
Vol 364 ◽  
pp. 538-544
Author(s):  
P.-A. Versini ◽  
G. Petrucci ◽  
B. de Gouvello
Keyword(s):  
Flow Rate ◽  
Stormwater Management ◽  
Positive Impact ◽  
Retention Volume ◽  
Green Roof ◽  
Absolute Threshold ◽  
Green Roofs ◽  
Rainfall Event ◽  
Time Period ◽  
Management Issues

Abstract. Experimental green-roof rainfall–runoff observations have shown a positive impact on stormwater management at the building scale; with a decrease in the peak discharge and a decrease in runoff volume. This efficiency of green-roofs varies from one rainfall event to another depending on precipitation characteristics and substrate antecedent conditions. Due to this variability, currently, green-roofs are rarely officially used as a regulation tool to manage stormwater. Indeed, regulation rules governing the connection to the stormwater network are usually based on absolute threshold values that always have to be respected: maximum areal flow-rate or minimum retention volume for example. In this context, the aim of this study is to illustrate how a green-roof could represent an alternative to solve stormwater management issues, if the regulation rules were further based on statistics. For this purpose, a modelling scheme has been established at the parcel scale to simulate the hydrological response of several roof configurations: impervious, strictly regulated (in terms of areal flow-rate or retention volume), and covered by different types of green-roof matter. Simulations were carried out on a long precipitation time period (23 years) that included a large and heterogeneous set of hydrometeorological conditions. Results obtained for the different roof configurations were compared. Based on the return period of the rainfall event, the probability to respect some regulation rules (defined from real situations) was assessed. They illustrate that green-roofs reduce stormwater runoff compared to an impervious roof surface and can guarantee the respect of the regulation rules in most of the cases. Moreover, their implementation can appear more realistic than that of other infrastructures strictly complying with regulations and demanding significant storage capacity.

scholarly journals Addressing the Water–Energy–Food Nexus through Enhanced Green Roof Performance

2021 ◽  
Vol 13 (4) ◽  
pp. 1972
Author(s):  
Jeremy Wright ◽  
Jeremy Lytle ◽  
Devon Santillo ◽  
Luzalen Marcos ◽  
Kristiina Valter Mai
Keyword(s):  
Climate Change ◽  
Performance Optimization ◽  
Urban Areas ◽  
Stormwater Management ◽  
Green Roof ◽  
Green Roofs ◽  
Management Tool ◽  
Contributing Factors ◽  
Rainwater Runoff ◽  
Rain Events

Urban densification and climate change are creating a multitude of issues for cities around the globe. Contributing factors include increased impervious surfaces that result in poor stormwater management, rising urban temperatures, poor air quality, and a lack of available green space. In the context of volatile weather, there are growing concerns regarding the effects of increased intense rainfalls and how they affect highly populated areas. Green roofs are becoming a stormwater management tool, occupying a growing area of urban roof space in many developed cities. In addition to the water-centric approach to the implementation of green roofs, these systems offer a multitude of benefits across the urban water–energy–food nexus. This paper provides insight to green roof systems available that can be utilized as tools to mitigate the effects of climate change in urbanized areas. A new array of green roof testing modules is presented along with research methods employed to address current issues related to food, energy and water performance optimization. Rainwater runoff after three rain events was observed to be reduced commensurate with the presence of a blue roof retention membrane in the testbed, the growing media depth and type, as well as the productive nature of the plants in the testbed. Preliminary observations indicate that more productive green roof systems may have increasingly positive benefits across the water–energy–food nexus in dense urban areas that are vulnerable to climate disruption.

scholarly journals Afforestation of Degraded Croplands as a Water-Saving Option in Irrigated Region of the Aral Sea Basin

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1433
Author(s):  
Navneet Kumar ◽  
Asia Khamzina ◽  
Patrick Knöfel ◽  
John P. A. Lamers ◽  
Bernhard Tischbein
Keyword(s):  
Land Use ◽  
Water Balance ◽  
Water Supply ◽  
Water Availability ◽  
Irrigation Water ◽  
Water Saving ◽  
Aral Sea ◽  
Water Balance Components ◽  
Study Region ◽  
Trade Offs

Climate change is likely to decrease surface water availability in Central Asia, thereby necessitating land use adaptations in irrigated regions. The introduction of trees to marginally productive croplands with shallow groundwater was suggested for irrigation water-saving and improving the land’s productivity. Considering the possible trade-offs with water availability in large-scale afforestation, our study predicted the impacts on water balance components in the lower reaches of the Amudarya River to facilitate afforestation planning using the Soil and Water Assessment Tool (SWAT). The land-use scenarios used for modeling analysis considered the afforestation of 62% and 100% of marginally productive croplands under average and low irrigation water supply identified from historical land-use maps. The results indicate a dramatic decrease in the examined water balance components in all afforestation scenarios based largely on the reduced irrigation demand of trees compared to the main crops. Specifically, replacing current crops (mostly cotton) with trees on all marginal land (approximately 663 km2) in the study region with an average water availability would save 1037 mln m3 of gross irrigation input within the study region and lower the annual drainage discharge by 504 mln m3. These effects have a considerable potential to support irrigation water management and enhance drainage functions in adapting to future water supply limitations.

scholarly journals Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

2019 ◽  
Vol 13 (11) ◽  
pp. 3045-3059 ◽  
Author(s):  
Nick Rutter ◽  
Melody J. Sandells ◽  
Chris Derksen ◽  
Joshua King ◽  
Peter Toose ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Layer Thickness ◽  
Snow Water Equivalent ◽  
Estimation Accuracy ◽  
Snow Layer ◽  
Data Set ◽  
Snow Water ◽  
Retrieval Errors ◽  
Snow Microstructure ◽  
The Impact

Abstract. Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across nine trenches) collected over two winters at Trail Valley Creek, NWT, Canada, was applied in synthetic radiative transfer experiments. This allowed for robust assessment of the impact of estimation accuracy of unknown snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer thickness varied over the shortest horizontal distances, controlled by subnivean vegetation and topography, while variability in total snowpack thickness approximated that of wind slab layers. Mean horizontal correlation lengths of layer thickness were less than a metre for all layers. Depth hoar was consistently ∼30 % of total depth, and with increasing total depth the proportion of wind slab increased at the expense of the decreasing surface snow layer. Distinct differences were evident between distributions of layer properties; a single median value represented density and specific surface area (SSA) of each layer well. Spatial variability in microstructure of depth hoar layers dominated SWE retrieval errors. A depth hoar SSA estimate of around 7 % under the median value was needed to accurately retrieve SWE. In shallow snowpacks <0.6 m, depth hoar SSA estimates of ±5 %–10 % around the optimal retrieval SSA allowed SWE retrievals within a tolerance of ±30 mm. Where snowpacks were deeper than ∼30 cm, accurate values of representative SSA for depth hoar became critical as retrieval errors were exceeded if the median depth hoar SSA was applied.

Effect of watershed subdivision on simulation of water balance components

2006 ◽  
Vol 20 (5) ◽  
pp. 1137-1156 ◽  
Author(s):  
M. P. Tripathi ◽  
N. S. Raghuwanshi ◽  
G. P. Rao
Keyword(s):  
Water Balance ◽  
Water Balance Components
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