Field-Scale Monitoring of Urban Green Area Rainfall-Runoff Processes

Rainfall-runoff from urban green areas can potentially contribute with significant runoff loads to urban drainage networks. Nevertheless, Redfern et al. (2016) acknowledge that studies and research on this topic are limited; hence, accurately assessing the hydrological impact from urban green areas is a difficult task. Boyd et al. (2009, 1994) studied rainfall-runoff from urban green areas on urban catchment scales. However, more research is needed for deeper understanding as urban green surface runoff could increase uncertainty in urban drainage modeling (Thorndahl et al. 2006, 2008). Generally, runoff from urban green areas is dependent on a variety of parameters, and without empirical knowledge, it is difficult to qualitatively estimate the runoff load from these areas. In the design of urban drainage systems, this can result in wrong assumptions, leading to either under- or overestimation of the runoff load from urban green areas. The consequence of this is either too high construction costs in the case of overestimation or too high flood damage costs in the case of underestimation. Therefore, empirical knowledge is crucial to improve future assumptions regarding infiltration and runoff models for urban green areas.

Infiltration excess models such as Horton’s infiltration equation (Horton 1939) and the Green–Ampt model (Green and Ampt 1911) are widely used to estimate rainfall-runoff from permeable surfaces. These models assume that if the rainfall intensity exceeds the infiltration capacity, the excess will cause surface runoff. This runoff is known as infiltration excess overland flow and has always been considered the primary hydrological process for generating rainfall-runoff from permeable surfaces. However, studies have shown that permeable runoff is more diverse (Dunne and Black 1970a, b; Kirkby and Chorley 1967). Generally, permeable runoff can be grouped into three processes: (1) infiltration excess runoff, (2) saturation excess runoff, and (3) subsurface throughflow. All three types are observed in a field study by Pilgrim et al. (1978). However, other field studies have not been able to detect infiltration excess overland flow as a contributor of rainfall-runoff from permeable surfaces (Dunne and Black 1970a, b; Kirkby and Chorley 1967). More empirical knowledge about these hydrological processes will improve both the design and modeling of urban drainage networks. Such observations can be implemented in both model calibration and in data-driven models such as in data assimilation (Brocca et al. 2009) and artificial neural networks for hydrological applications (ASCE Task Committee on Application of Artificial Neural Networks in Hydrology 2000; Govindaraju 2000).

In empirical case studies from forest, agricultural areas, and laboratory studies, rainfall simulators are a widely used method to estimate runoff, erosion, nutrient transport, and other runoff-related mechanisms (Benavides Solorio and MacDonald 2001; Cerdà et al. 1997; Clarke and Walsh 2007; Humphry 2002; Ribolzi et al. 2011; Sharpley 2003; Shuster et al. 2008). However, with artificially generated rainfall, rain and soil interactions may not always be realistic. Therefore, large-scale studies are important to understand how small-scale rainfall simulator studies can be interpreted and scaled in relation to urban catchments.

Various factors have the potential to affect rainfall-runoff in urban environments. Pan and Shangguan (2006) found that grass cover reduces surface-runoff generation compared to bare soils. However, Quinton et al. (1997) found no significant relationship between the type of plant cover and runoff generation, except that plant cover generally reduces runoff. Quinton et al. (1997) further found that generated runoff decreases by increased canopy cover. Soil water content also affects permeable runoff and has been used to improve runoff prediction models (Jacobs et al. 2003). Grayson (1997) indicated that horizontal or vertical water transport processes in the soil could be detected depending on the spatial uniformity of soil water content. Furthermore, properties of soil types can significantly affect the infiltration capacity (Groenendyk et al. 2015). Some areas in urban environments suffer from degraded infiltration capacity due to heavy soil compaction caused by urban activity, for example, road and building constructions (Gregory 2006). Finally, morphological properties such as the slope and length of a catchment also affect the amount of runoff from permeable surfaces (Sharma 1986).

In the present study, a large-scale experimental field station is designed to measure rainfall-runoff from an urban green catchment. Simultaneously, soil water properties and rainfall are measured on site. Furthermore, a comprehensive study of the basic soil water properties and soil characteristics are investigated. The scope is to evaluate whether rainfall-runoff is present from a relatively common type of urban surface (grass covered park in a residential area). Studying the runoff processes on a large scale makes it possible to evaluate how urban green area rainfall-runoff responds as a result of hydrological mobilization of an entire catchment. This is contrary, for example, to rainfall simulation studies that only study runoff processes in areas of approximately $1{\mathrm{m}}^2$, which could lead to boundary effects affecting measured runoff. Furthermore, this study will be a reference study to urban green surface runoff studies because similar such experiments in urban environments are scarce, whereas only a few such experiments have been carried out in rural areas. Finally, it is the goal of this study to obtain qualitative hydrographs to examine the relationship between rainfall and permeable runoff. Thus, the correlation between soil water properties and rainfall-runoff is studied to assess whether such measurements have a potential use in urban drainage design.

The field station is established in the city of Lystrup, Denmark, to collect rainfall-runoff from a $\mathrm{4,300}{\mathrm{m}}^2$ permeable catchment (Fig. 1) with an average slope of 8.8%. Before urban development, the land was used as agricultural farmland until the 1960s. The monitored area in Lystrup is a recreational park surrounded by residential houses. The field station is equipped with a slope-intercept line drain (Fig. 1) that collects surface runoff and measures the discharge from the catchment with a flow meter. Furthermore, three clusters of soil sensors are established for measuring soil volumetric water content (VWC) and matric potential (MP). The soil sensor clusters will be further denoted as the bottom, middle, and top sensor clusters. Finally, a tipping bucket rain gauge monitors the rainfall. All sensors are connected to battery-driven YDOC ML-315ADS-Li data loggers (YDOC 2016, Bennekom, The Netherlands), and data are transferred through a mobile broadband connection to a file transfer protocol (FTP) server in real time. The field station has been collecting data since September 2016 and is still active. Data included in this study extend from September 2016 to July 2018.

The field station measures some of the central parameters used in traditional surface runoff modeling. Eq. (1) presents a simple continuity equation that shows the primary processes that affects the accumulation of water on a permeable surface:where $A$ (${\mathrm{m}}^2$) = catchment surface area; $y$ (m) = ponding water level on soil surface; $t$ (s) = time; $P$ (${\mathrm{ms}}^{-1}$) = precipitation; $Q$ (${\mathrm{m}}^3{\mathrm{s}}^{-1}$) = surface runoff rate; and $f$ (${\mathrm{ms}}^{-1}$) = infiltration rate. Precipitation is the input source of water to the runoff model, while the surface runoff rate and infiltration rate discharges water from the model. Precipitation and the runoff rate can be measured directly, while the infiltration rate is more difficult to measure. However, infiltration depends on the soil water content and matric potential. Therefore, these parameters can be used as indirect indicators of infiltration. In urban drainage modeling, various simplified approaches are typically used to model the vertical infiltration capacity of a permeable surface. The Green–Ampt model is one of the most commonly used models and describes the infiltration rate as a function of time (Green and Ampt 1911; Kale and Sahoo 2011):where $K$ (${\mathrm{ms}}^{-1}$) = saturated hydraulic conductivity; $h_0$ (m) = depth of ponding water level on soil surface; $h_s$ (m) = capillary suction head or matric potential at wetting front; and $L$ (m) = distance to wetting front. The matric potential depends on the soil water content. As seen, runoff, precipitation, soil water content, and soil matric potential can therefore be used to describe the primary processes that could affect rainfall-runoff from the $\mathrm{4,300}{\mathrm{m}}^2$ permeable catchment in Lystrup.

Dunne and Black (1970a) and Kirkby and Chorley (1967) concluded that rainfall-runoff from permeable hill slopes is produced by wet spot (saturation excess) runoff and subsurface throughflow. Rainfall-runoff observed in this study show the same dynamics. Saturated areas near the line drain seem to produce short-term peaks during rainfall, while subsurface throughflow generates runoff in an extended time afterward. Subsurface throughflow seems to be the primary contributor to runoff and occurs when the soil water content is high. High soil water content is necessary to produce subsurface throughflow as this increases horizontal water transport in the soil. Measured soil water content at the bottom of a hill is highly correlated with produced runoff. This indicates that water is first transported across this point within the soil before reaching the soil surface and, thereby, the line drain. The soil characteristics of the area could further induce horizontal water transport in the soil since a siltier soil is present at a depth of 46 cm. Furthermore, the soil will supposedly be prone to higher compaction at a depth of 46 cm, which will reduce the effective porosity. Due to a higher silt content and soil compaction, the soil layer at a depth of 46 cm will have a lower infiltration capacity than the topsoil layer and, therefore, in some periods become a barrier to vertical water transport in the soil. This forces water to move horizontally.

During most of the year, there is a potential for surface runoff from the urban green area in Lystrup. According to Fig. 5, the soil water content is $0.34{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil or above from September until July. This is a high soil water content that is relatively close to the average total porosity of 0.43, which locally is as low as 0.37. The high soil volumetric water content is probably maintained in this period due to low evapotranspiration during fall and winter. Comparatively, during late spring and summer, the soil water content is significantly reduced and reaches values as low as $0.13–0.20{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil in the upper soil layer. In this way, a significant storage volume is available during spring and summer that will be exhausted only if the soil volumetric water content reaches $0.34{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil again.

Several rainfall events are seen to produce runoff at the field station in Lystrup. None of these rainfall events exceeded the measured infiltration capacity of the topsoil, which in this case is the saturated hydraulic conductivity of $1.1{\mathrm{mm}\min }^{-1}$. This indicates that runoff is produced primarily because rainfall exceeds the water storage capacity of the topsoil as the infiltration capacity of the lower soil layer is exceeded. The water storage capacity, $\mathrm{\Delta }S$ (mm), of the soil is dependent on the soil water content and can be written in the form of a simple mass balance in Eq. (6):where ${\theta }_{sc}$ (${\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil) = soil volumetric water content at maximum storage capacity before mobilization of horizontal water transport in soil; $\theta$ (${\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil) = initial soil volumetric water content; and $d_s$ (mm) = depth of soil body capable of storing water. If $\theta <{\theta }_{sc}$, there is an excess water storage capacity and horizontal water transport will not be significant. For example, under dry conditions, as seen in the summer where the soil volumetric water content reaches $\theta =0.15{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil, there is an excess storage volume up to ${\theta }_{sc}=0.34{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil, whereas the storage capacity according to the measurements is exhausted. The difference in soil water content is multiplied by the depth of the topsoil layer in Lystrup, which is ${\mathrm{d}}_{\mathrm{s}}=460\mathrm{mm}$. This results in a temporary storage capacity at this point in time of 97 mm. The theory presented in Eq. (6) is confirmed by measurements where runoff is not produced below an average soil volumetric water content of $0.34{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil.

The measurements from the field station indicate that subsurface throughflow is present, and therefore both horizontal water transport in terms of throughflow and vertical water transport in terms of infiltration to deeper aquifers are essential to describe rainfall-runoff in Lystrup. Therefore, a two-dimensional model could be the best solution to model the measured runoff processes. In this case, Horton’s infiltration equation or other one-dimensional infiltration models are not sufficient. Furthermore, a measured cloudburst of a 10-year return period produced no runoff. The reason that no runoff was produced is that the rainfall intensity was not high enough to exceed the infiltration capacity, and as the initial soil water content prior to the rainfall event was $0.30{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil, and so below the critical soil volumetric water content of $0.34{\mathrm{m}}^3{\mathrm{H}}_2\mathrm{O}{\mathrm{m}}^{-3}$ soil, there were also storage capacity left in the soil to store rainfall in the soil matrix. In general, this rainfall event is an indication that rainfall intensities must be relatively large to cause infiltration excess overland flow in Lystrup. Future experiments will investigate which rainfall characteristics are needed to generate infiltration excess overland flow in Lystrup.

To assess the runoff dynamics due to infiltration excess overland flow, it is necessary to use other means such as rainfall simulators if the natural rainfall intensity does not exceed the infiltration capacity. Rainfall simulators are generally designed to study high-intensity rainfall and how this affects infiltration excess runoff and processes related to this type of runoff. However, rainfall simulators would not be able to study subsurface throughflow because this requires the entire catchment to be hydrologically mobilized. This would simply require an unrealistic amount of water if such hydrological conditions should be reached with a rainfall simulator. Therefore, this study supplements rainfall simulator studies well because it can be used to study throughflow effects, while the rainfall simulators can be used to study infiltration excess overland flow. The disadvantage of this large-scale study is the missing ability to produce desired rainfall characteristics, which means that infiltration excess runoff will rarely be observed in this case.

The field station gives insights on where to locate soil sensor equipment in other research locations. Within the field station in Lystrup, the bottom hill sensor cluster showed the best correlation to the dynamics of generated runoff. Therefore, the most useful data are collected closest to the outlet of the catchment. This is expected because the bottom hill sensor cluster measures the result of all hydrological processes occurring within the hill slope. Although the uphill sensor clusters showed weaker correlations with the runoff, they are still important to indicate the average soil water content of the hill to estimate the total water storage capacity of the soil body.

The field station developed in this project collects and monitors all runoff reaching the line drain at the soil surface. The result of this can be that several types of runoff are mixed, for example, that subsurface throughflow is mixed with infiltration excess overland flow. In this way, it could be difficult to separate one runoff type from another and qualitatively quantify them. Future studies could put more emphasis on separating runoff types in the field by separating the surface from the subsurface. However, measuring the subsurface throughflow within the subsurface could lead to measuring throughflow that would have stayed in the subsurface and at a later point infiltrate to deeper aquifers.

It has been found that an urban green area in Lystrup, Denmark, frequently contributes to runoff. The following characteristics of runoff were found:

The results of this study agree with other large-scale studies carried out in rural areas. Generally, infiltration excess overland flow was not present, which is often assumed in the terms of Horton’s infiltration theory. This indicates that engineers and scientists should be careful when deciding which runoff mechanism is the most dominant in urban green areas. Furthermore, as infiltration excess overland flow is often assumed to be dominant, it will be necessary in future studies to revisit current models used in design practice and determine whether the current assumptions and models for urban green area rainfall-runoff are reliable.

Future studies are necessary to develop both engineers’ and scientists’ knowledge of this field as urban green area rainfall-runoff can be crucial for optimal urban drainage design. Therefore, future research projects in urban environments are highly recommended. They can be conducted as large-scale experiments but also with small-scale rainfall simulator studies, which are often used to study runoff processes in rural and agricultural areas.

The authors would like to give special thanks to Søren Højmark Rasmussen (EnviDan A/S), who attended discussions of both theoretical and experimental aspects in this study. Thanks also go to Lene Bassø Duus (Aarhus Vand A/S) for her opinions and ideas on the implementation of findings in the Danish water utility sector. Furthermore, thank you to Anette Næslund Pedersen for her guidance and help in the laboratories. This research was partially funded by the Foundation for Development of Technology in the Danish Water Sector, Innovation Fund Denmark, Aarhus Vand, EnviDan A/S, and Aalborg University.