Modelling long-term water yield effects of forest management in a Norway spruce forest

Abstract

Intensive forest management is one of the main land cover changes over the last century in Central Europe, resulting in forest monoculture. It has been proposed that these monoculture stands impact hydrological processes, water yield, water quality and ecosystem services. At the Lysina Critical Zone Observatory, a forest catchment in the western Czech Republic, a distributed physics-based hydrologic model, Penn State Integrated Hydrologic Model (PIHM), was used to simulate long-term hydrological change under different forest management practices, and to evaluate the comparative scenarios of the hydrological consequences of changing land cover. Stand-age-adjusted LAI (leaf area index) curves were generated from an empirical relationship to represent changes in seasonal tree growth. By consideration of age-adjusted LAI, the spatially-distributed model was able to successfully simulate the integrated hydrological response from snowmelt, recharge, evapotranspiration, groundwater levels, soil moisture and streamflow, as well as spatial patterns of each state and flux. Simulation scenarios of forest management (historical management, unmanaged, clear cutting to cropland) were compared. One of the critical findings of the study indicates that selective (patch) forest cutting results in a modest increase in runoff (water yield) as compared to the simulated unmanaged (no cutting) scenario over a 29-year period at Lysina, suggesting the model is sensitive to selective cutting practices. A simulation scenario of cropland or complete forest cutting leads to extreme increases in annual water yield and peak flow. The model sensitivity to forest management practices examined here suggests the utility of models and scenario development to future management strategies for assessing sustainable water resources and ecosystem services.

Editor D. Koutsoyiannis     

Effects of land‐cover changes on the hydrological response of interior Columbia River basin forested catchments

The topographically explicit distributed hydrology–soil–vegetation model (DHSVM) is used to simulate hydrological effects of changes in land cover for four catchments, ranging from 27 to 1033 km², within the Columbia River basin. Surface fluxes (stream flow and evapotranspiration) and state variables (soil moisture and snow water equivalent) corresponding to historical (1900) and current (1990) vegetation are compared. In addition a sensitivity analysis, where the catchments are covered entirely by conifers at different maturity stages, was conducted. In general, lower leaf‐area index (LAI) resulted in higher snow water equivalent, more stream flow and less evapotranspiration. Comparisons with the macroscale variable infiltration capacity (VIC) model, which parameterizes, rather than explicitly represents, topographic effects, show that runoff predicted by DHSVM is more sensitive to land‐cover changes than is runoff predicted by VIC. This is explained by model differences in soil parameters and evapotranspiration calculations, and by the more explicit representation of saturation excess in DHSVM and its higher sensitivity to LAI changes in the calculation of evapotranspiration. Copyright © 2002 John Wiley & Sons, Ltd.     

Effects of land-use/cover change on hydrological processes using a GIS/RS-based integrated hydrological model: case study of the East River,China

Abstract

An integrated model, combining a surface energy balance system, an LAI-based interception model and a distributed monthly water balance model, was developed to predict hydrological impacts of land-use/land-cover change (LUCC) in the East River basin, China, with the aid of GIS/RS. The integrated model is a distributed model that not only accounts for spatial variations in basin terrain, rainfall and soil moisture, but also considers spatial and temporal variation of vegetation cover and evapotranspiration (ET), in particular, thus providing a powerful tool for investigating the hydrological impact of LUCC. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time series of precipitation from 170 stations in the basin. The model was calibrated and validated based on river discharge data from three stations in the basin for 21 years. The calibration and validation results suggested that the model is suitable for application in the basin. The results show that ET has a positive relationship with LAI (leaf area index), while runoff has a negative relationship with LAI in the same climatic zone that can be described by the surface energy balance and water balance equation. It was found that deforestation would cause an increase in annual runoff and a decrease in annual ET in southern China. Monthly runoff for different land-cover types was found to be inversely related to ET. Also, for most of the scenarios, and particularly for grassland and cropland, the most significant changes occurred in the rainy season, indicating that deforestation would cause a significant increase in monthly runoff in that season in the East River basin. These results are important for water resources management and environmental change monitoring.

Editor Z.W. Kundzewicz     

Evaluating the functionality and streamflow impacts of explicitly modelling forest–snow interactions and canopy gaps in a distributed hydrologic model

Many plot‐scale studies have shown that snow‐cover dynamics in forest gaps are distinctly different from those in open and continuously forested areas, and forest gaps have the potential to alter the magnitude and timing of snowmelt. However, the watershed‐level impacts of canopy gap treatment on streamflows are largely unknown. Here, we present the first research that explicitly assesses the impact of canopy gaps on seasonal streamflows and particularly late‐season low flows at the watershed scale. To explicitly model forest–snow interactions in canopy gaps, we made major enhancements to a widely used distributed hydrologic model, distributed hydrology soil vegetation model, with a canopy gap component that represents physical processes of snowpack evolution in the forest gap separately from the surrounding forest on the subgrid scale (within a grid typically 10–150 m). The model predicted snow water equivalent using the enhanced distributed hydrology soil vegetation model showed good agreement (R² > 0.9) with subhourly snow water equivalent measurements collected from open, forested, and canopy gap sites in Idaho, USA. Compared with the original model that does not account for interactions between gaps and surrounding forest, the enhanced model predicted notably later melt in small‐ to medium‐size canopy gaps (the ratio of gap radius (r) to canopy height (h) ≤ 1.2), and snow melt rates exhibited great sensitivity to changing gap size in medium‐size gaps (0.5 ≤ r/h ≤ 1.2). We demonstrated the watershed‐scale implications of canopy gaps on streamflow in the snow‐dominated Chiwawa watershed, WA, USA. With 24% of the watershed drainage area (about 446 km²) converted to gaps of 60 m diameter, the mean annual 7‐day low flow was increased by 19.4% (i.e., 0.37 m³/s), and the mean monthly 7‐day low flows were increased by 13.5% (i.e., 0.26 m³/s) to 40% (i.e., 1.76 m³/s) from late summer through fall. Lastly, in practical implementation of canopy gaps with the same total gap areas, a greater number of distributed small gaps can have greater potential for longer snow retention than a smaller number of large gaps.     

On the significance of crop‐type information for the simulation of catchment hydrology

Spatially distributed hydrological models require information on the land cover pattern, as it directly influences the generation of run‐off. However, it is not clear which detail of land cover information is suitable for simulating the catchment hydrology. A better understanding of the relationship between the land cover detail and the hydrological processes is therefore required as it would enhance a successful application of the hydrological model. This study investigates the relevance of accurate information about the crop types in the catchment for the simulation of run‐off, baseflow and evapotranspiration. Results reveal that adding knowledge about the crop type in the model simulation is redundant when area‐averaged water flux predictions are intended. On the contrary, when a spatial distribution of water flux predictions is desired, it is meaningful to increase the land cover detail because an increased heterogeneity in the land cover map induces an increased heterogeneity in the hydrological response and locally reduces the uncertainty in the model prediction up to 50%. To assess the land cover uncertainty and to locate the regions for which the reduction in prediction uncertainty is the highest, the thematic uncertainty map (constructed through fuzzy logic) is shown to be a useful tool. Copyright © 2014 John Wiley & Sons, Ltd.     

Modelling plant canopy effects on annual variability of evapotranspiration and heat fluxes for a semi‐arid grassland on the southern periphery of the Eurasian cryosphere in Mongolia

The ability to predict vegetation cover effects on thermal/water regimes can enhance our understanding of canopy controls on evapotranspiration. The Simultaneous Heat and Water (SHAW) model is a detailed process model of heat and water movement in a snow–residue–soil system. This paper describes provisions added to the SHAW model for vegetation cover and simulation of heat and water transfer through the soil–plant–air continuum. The model was applied to four full years (May 2003–April 2007) of data collected on sparse grassland at Nalaikh in north‐eastern Mongolia. Simulated soil temperature and radiation components agreed reasonably well with measured values. The absolute differences between simulated and measured soil temperatures were larger at both the surface layer and deeper layer, but relatively smaller in the layer from 0·8 to 2·4 m. Radiation components were mimicked by the SHAW model with model efficiency (ME) reaching 0·93–0·72. Latent and sensible heat fluxes were simulated well with MEs of 0·93 and 0·87, respectively. The vegetation control on evapotranspiration was investigated by sensitivity experiments of model performance with changing leaf area index (LAI) values but constant of other variables. The results suggest that annual evapotranspiration ranged from 16 to ? 22% in response to extremes of doubled and zero LAI. Copyright © 2010 John Wiley & Sons, Ltd.     

Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

The spatial distribution of sub-pixel components has an impact on retrieval accuracy, and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index (LAI). To investigate this effect, we constructed three realistic scenarios with the same LAI values and other properties, except that the simulated plants had different distributions. We implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor (BRF) datasets based upon these simulated scenes. The inversion was conducted using these data, which showed that spatial distribution affects retrieval accuracy. The inversion was also conducted for LAI based on charge-coupled device (CCD) data from the Environment and Disaster Monitor Satellite (HJ-1), which depicted both forest and drought-resistant crop land cover. This showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI inversion. The spatial distribution of global fractal dimension index, which can be used to describe the area of sub-pixel components and their spatial distribution modes, shows good consistency with the coarse resolution LAI inversion error.     

Modelling the interaction of climate,forest ecosystem,and hydrology to estimate catchment dissolved organic carbon export

The potential for increased loads of dissolved organic carbon (DOC) in streams and rivers is a concern for regulating the water quality in water supply watersheds. With increasing hydroclimatic variability related to global warming and shifts in forest ecosystem community and structure, understanding and predicting the magnitude and variability of watershed supply and transport of DOC over multiple time scales have become important research and management goals. In this study, we use a distributed process‐based ecohydrological model (Regional Hydro‐Ecological Simulation System [RHESSys]) to explore controls and predict streamflow DOC loads in Biscuit Brook. Biscuit Brook is a forested headwater catchment of the Neversink Reservoir, part of the New York City water supply system in the Catskill Mountains. Three different model structures of RHESSys were proposed to explore and evaluate hypotheses addressing how vegetation phenology and hydrologic connectivity between deep groundwater and riparian zones influence streamflow and DOC loads. Model results showed that incorporating dynamic phenology improved model agreement with measured streamflow in spring, summer, and fall and fall DOC concentration, compared with a static phenology. Additionally, the connectivity of deep groundwater flux through riparian zones with dynamic phenology improved streamflow and DOC flux in low flow conditions. Therefore, this study suggests the importance of inter‐annual vegetation phenology and the connectivity of deep groundwater drainage through riparian zones in the hydrology and stream DOC loading in this forested watershed and the ability of process‐based ecohydrological models to simulate these dynamics. The advantage of a process‐based modelling approach is specifically seen in the sensitivity to forest ecosystem dynamics and the interactions of hydroclimate variability with ecosystem processes controlling the supply and distribution of DOC. These models will be useful to evaluate different forest management approaches toward mitigating water quality concerns.     

Simulated watershed responses to land cover changes using the Regional Hydro‐Ecological Simulation System

In this work, we used the Regional Hydro‐Ecological Simulation System (RHESSys) model to examine runoff sensitivity to land cover changes in a mountain environment. Two independent experiments were evaluated where we conducted simulations with multiple vegetation cover changes that include conversion to grass, no vegetation cover and deciduous/coniferous cover scenarios. The model experiments were performed at two hillslopes within the Weber River near Oakley, Utah watershed (USGS gauge # 10128500). Daily precipitation, air temperature and wind speed data as well as spatial data that include a digital elevation model with 30 m grid resolution, soil texture map and vegetation and land use maps were processed to drive RHESSys simulations. Observed runoff data at the watershed outlet were used for calibration and verification. Our runoff sensitivity results suggest that during winter, reduced leaf area index (LAI) decreases canopy interception resulting in increased snow accumulations and hence snow available for runoff during the early spring melt season. Increased LAI during the spring melt season tends to delay the snow melting process. This delay in snow melting process is due to reduced radiation beneath high LAI surfaces relative to low LAI surfaces. The model results suggest that annual runoff yield after removing deciduous vegetation is on average about 7% higher than with deciduous vegetation cover, while annual runoff yield after removing coniferous vegetation is on average as about 2% higher than that produced with coniferous vegetation cover. These simulations thus help quantify the sensitivity of water yield to vegetation change. Copyright © 2013 John Wiley & Sons, Ltd.     

A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin,East China

Parameter calibration and sensitivity analysis (SA) are usually not straightforward tasks for distributed hydrological models, owing to the complexity of models and the large number of parameters. A two-step SA approach is proposed for analysing hydrological signatures based on the distributed hydrology–soil–vegetation model (DHSVM) in the Jinhua River Basin, East China. A preliminary SA is conducted to obtain influential parameters via analysis of variance. These parameters are further analysed through a variance-based global sensitivity analysis method to achieve robust rankings and parameter contributions. Parallel computing is designed to reduce the computational burden. The results reveal that only a few parameters are significantly sensitive and that interactions between parameters cannot be ignored. When analysing hydrological signatures, it is found that water yield is simulated very well for most samples. Small and medium floods are simulated very well, while slight underestimations happen for large floods.     

Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

The spatial distribution of sub-pixel components has an impact on retrieval accuracy, and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index (LAI). To investigate this effect, we constructed three realistic scenarios with the same LAI values and other properties, except that the simulated plants had different distributions. We implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor (BRF) datasets based upon these simulated scenes. The inversion was conducted using these data, which showed that spatial distribution affects retrieval accuracy. The inversion was also conducted for LAI based on charge-coupled device (CCD) data from the Environment and Disaster Monitor Satellite (HJ-1), which depicted both forest and drought-resistant crop land cover. This showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI inversion. The spatial distribution of global fractal dimension index, which can be used to describe the area of sub-pixel components and their spatial distribution modes, shows good consistency with the coarse resolution LAI inversion error.

     

Estimation of winter leaf area index and sky view fraction for snow modelling in boreal coniferous forests: consequences on snow mass and energy balance

Leaf area index (LAI) and canopy coverage are important parameters when modelling snow process in coniferous forests, controlling interception and transmitting radiation. Estimates of LAI and sky view factor show large variability depending on the estimation method used, and it is not clear how this is reflected in the calculated snow processes beneath the canopy. In this study, the winter LAI and sky view fraction were estimated using different optical and biomass‐based approximations in several boreal coniferous forest stands in Fennoscandia with different stand density, age and site latitude. The biomass‐based estimate of LAI derived from forest inventory data was close to the values derived from the optical measurements at most sites, suggesting that forest inventory data can be used as input to snow hydrological modelling. Heterogeneity of tree species and site fertility, as well as edge effects between different forest compartments, caused differences in the LAI estimates at some sites. A snow energy and mass balance model (SNOWPACK) was applied to detect how the differences in the estimated values of the winter LAI and sky view fraction were reflected in simulated snow processes. In the simulations, an increase in LAI and a decrease in sky view fraction changed the snow surface energy balance by decreasing shortwave radiation input and increasing longwave radiation input. Changes in LAI and sky view fraction affected directly snow accumulation through altered throughfall fraction and indirectly snowmelt through the changed surface energy balance. Changes in LAI and sky view fraction had a greater impact on mean incoming radiation beneath the canopy than on other energy fluxes. Snowmelt was affected more than snow accumulation. The effect of canopy parameters on evaporation loss from intercepted snow was comparable with the effect of variation in governing meteorological variables such as precipitation intensity and air temperature. Copyright © 2012 John Wiley & Sons, Ltd.     

Soil water dynamics under different forest vegetation cover: Implications for hillslope stability

Though it is well known that vegetation affects the water balance of soils through canopy interception and evapotranspiration, its hydrological contribution to soil hydrology and stability is yet to be fully quantified. To improve understanding of this hydrological process, soil water dynamics have been monitored at three adjacent hillslopes with different vegetation covers (deciduous tree cover, coniferous tree cover, and grass cover), for nine months from December 2014 to September 2015. The monitored soil moisture values were translated into soil matric suction (SMS) values to facilitate the analysis of hillslope stability. Our observations showed significant seasonal variations in SMS for each vegetation cover condition. However, a significant difference between different vegetation covers was only evident during the winter season where the mean SMS under coniferous tree cover (83.6 kPa) was significantly greater than that under grass cover (41 kPa). The hydrological reinforcing contribution due to matric suction was highest for the hillslope with coniferous tree cover, while the hillslope with deciduous tree cover was second and the hillslope with grass cover was third. The greatest contributions for all cover types were during the summer season. During the winter season, the wettest period of the monitoring study, the additional hydrological reinforcing contributions provided by the deciduous tree cover (1.5 to 6.5 kPa) or the grass cover (0.9 to 5.4 kPa) were insufficient to avoid potential slope failure conditions. However, the additional hydrological reinforcing contribution from the coniferous tree cover (5.8 to 10.4 kPa) was sufficient to provide potentially stable hillslope conditions during the winter season. Our study clearly suggests that during the winter season the hydrological effects from both deciduous tree and grass covers are insufficient to promote slope stability, while the hydrological reinforcing effects from the coniferous tree cover are sufficient even during the winter season. Copyright © 2018 John Wiley & Sons, Ltd.     

Decoupling the effects of deforestation and climate variability in the Tapajós river basin in the Brazilian Amazon

Tropical river basins are experiencing major hydrological alterations as a result of climate variability and deforestation. These drivers of flow changes are often difficult to isolate in large basins based on either observations or experiments; however, combining these methods with numerical models can help identify the contribution of climate and deforestation to hydrological alterations. This paper presents a study carried out in the Tapaj?s River (Brazil), a 477,000 km² basin in South‐eastern Amazonia, in which we analysed the role of annual land cover change on daily river flows. Analysis of observed spatial and temporal trends in rainfall, forest cover, and river flow metrics for 1976 to 2008 indicates a significant shortening of the wet season and reduction in river flows through most of the basin despite no significant trend in annual precipitation. Coincident with seasonal trends over the past 4 decades, over 35% of the original forest (140,000 out of 400,000 km²) was cleared. In order to determine the effects of land clearing and rainfall variability to trends in river flows, we conducted hindcast simulations with ED2 + R, a terrestrial biosphere model incorporating fine scale ecosystem heterogeneity arising from annual land‐use change and linked to a flow routing scheme. The simulations indicated basin‐wide increases in dry season flows caused by land cover transitions beginning in the early 1990s when forest cover dropped to 80% of its original extent. Simulations of historical potential vegetation in the absence of land cover transitions indicate that reduction in rainfall during the dry season (mean of ?9 mm per month) would have had an opposite and larger magnitude effect than deforestation (maximum of +4 mm/month), leading to the overall net negative trend in river flows. In light of the expected increase in future climate variability and water infrastructure development in the Amazon and other tropical basins, this study presents an approach for analysing how multiple drivers of change are altering regional hydrology and water resources management.     

Global sensitivity analysis of DRAINMOD‐FOREST,an integrated forest ecosystem model

Global sensitivity analysis is a useful tool to understand process‐based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD‐FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The analysis was carried out for multiple long‐term model predictions of hydrology, biogeochemistry, and plant growth. Results showed that long‐term mean hydrological predictions were highly sensitive to several key plant physiological parameters. Long‐term mean annual soil organic C content and mineralization rate were mainly controlled by temperature‐related parameters for soil organic matter decomposition. Mean annual forest productivity and N uptake were found to be mainly dependent upon plant production‐related parameters, including canopy quantum use efficiency and carbon use efficiency. Mean annual nitrate loss was highly sensitive to parameters controlling both hydrology and plant production, while mean annual dissolved organic nitrogen loss was controlled by parameters associated with its production and physical sorption. Parameters controlling forest production, C allocation, and specific leaf area highly affected long‐term mean annual leaf area. Results of this study could help minimize the efforts needed for calibrating DRAINMOD‐FOREST. Meanwhile, this study demonstrates the critical role of plants in regulating water, C, and N cycles in forest ecosystems and highlights the necessity of incorporating a dynamic plant growth model for comprehensively simulating hydrological and biogeochemical processes. Copyright © 2013 John Wiley & Sons, Ltd.     

A model to consider the spatial variability of rainfall partitioning within deciduous canopy. I. Model description

In this first paper of two, a numerical simulation model capable of simulating the spatial variability of rainfall partitioning within a canopy is presented. The second paper details how the model is parameterized, and some testing of its capabilities. The first stage of the model is to derive the mature canopy structure. This is achieved through simplified individual tree structures and a random placement routine based on a modified Poisson distribution. Following this the spatial discretization for throughfall is attained as a series of layers of triangles with a tree trunk at every apex. The number of layers is derived from the leaf area index through a modified Poisson distribution. Seasonal variation in the deciduous canopy is simulated through a time vector routine. The rainfall partitioning section of the model is based upon the Rutter model which has been modified to each individual triangle layer. The main feature of this model is that it offers a method of simulating rainfall partitioning at a scale that is a function of the size of the elementary physical components (tree and leaf scale). This can be used to investigate soil moisture variations under a canopy, or to study the variations within the forest hydrological processes themselves. © 1997 John Wiley & Sons, Ltd.     

Studies on changes in extreme flood peaks resulting from land-use changes need to consider roughness variations

ABSTRACT

The impacts of changes in forest coverage on extreme floods have drawn much attention globally. This study quantifies the sensitivity of flood peaks to forest coverage and roughness changes. With this objective, a framework is first introduced that includes a variance-based sensitivity analysis approach and a water and energy budget-based distributed hydrological model with a vegetation module. The influence of forest coverage changes is simulated by altering land-use types that are based on physical parameters. A variance decomposition approach is used to quantify the contribution of influential factors, i.e. event size, forest coverage and roughness changes, to extreme flood peak variations. The results in a medium-sized river basin show forest coverage changes have little influence: variations in canopy interception, ground surface water retention, soil moisture and groundwater table resulting from changing forest coverage did not alter flood peaks considerably. In contrast, it is found that flood peaks are more sensitive to roughness variations.     

Discriminating residual and colluvial soils using topographic analysis in a small,forested catchment in Japan

Soil moisture plays an important role in hydrology. Understanding factors (such as topography, vegetation, and meteorological conditions) that influence spatio‐temporal variability in soil moisture, and how this influence is manifested, is important for understanding hydrological processes. A number of distributed (quasi‐)physical hydrological models have been developed to investigate this subject. Previous studies have shown that the spatial differences in the distribution of soil types (residual and colluvial soils) dominantly reflect spatio‐temporal fluctuations in soil moisture and runoff. We present a methodology for assessing the spatial distribution of residual and colluvial soils, which differ with respect to their physical characteristics, in a 0·88 km² forested catchment with complex topography and a complex land‐use history. Our method is based on penetration resistance profile data; in this data set, each data point represents soil physical characteristics within an area of about 25 m². If the spatial distribution of soils under similar meteorological, geological, historical land use, and other conditions could be characterized on the basis of similarity in topographic features, then the spatial distribution of soil could be predicted based on relationships between various topographic indices (e.g. topographic index and local slope). We tested whether our model correctly assessed the reference data. The model's results were 90·5% correct for residual soils and 87·3% correct for colluvial soils. Further studies will quantify the relationships between topographic features of land covered by residual and colluvial soils and changes in spatio‐temporal variations in the catchment (e.g. vegetation and land use) as a function of geology or meteorology. Copyright © 2007 John Wiley & Sons, Ltd.     

Influence of leaf and canopy characteristics on rainfall interception and urban hydrology

Considering the rapid expansion of urban populations and the corresponding urbanization of landscapes, a dearth of knowledge exists regarding the role of urban vegetation in modulating urban ecosystem functioning. In response to the need for the development of new approaches to quantify ecohydrological processes along urban-to-rural gradients at alternate scales, this study explores the relationship between individual plant selection choices in landscaping and changes in urban hydrological functioning. This research examines differences in the variation of rainfall interception, leaf hydrophobicity, canopy structure, and water storage, between 13 species in an urban, semi-arid location. The species studied were selected based on resident preferences, and hence this research considers the role that urban residents play, through individual choices, in modifying the ecohydrology of an urban watershed. Rainfall interception, canopy surface storage, leaf hydrophobicity, and water droplet retention were significantly different between species. Results indicate that individual choice in plant selection for landscaping may influence urban hydrology.