Understanding the Effects of Climate Change on Urban Stormwater Infrastructures in the Las Vegas Valley

Ranjeet Thakali, Ajay Kalra, Sajjad Ahmad
2016 Hydrology  
The intensification of the hydrological cycle due to climate change entails more frequent and intense rainfall. As a result, urban water systems will be disproportionately affected by the climate change, especially in such urban areas as Las Vegas, which concentrates its population, infrastructure, and economic activity. Proper design and management of stormwater facilities are needed to attenuate the severe effects of extreme rainfall events. The North American Regional Climate Change
more » ... ate Change Assessment Program is developing multiple high-resolution projected-climate data from different combinations of regional climate models and global climate models. The objective of this study was to evaluate existing stormwater facilities of a watershed within the Las Vegas Valley in southern Nevada by using a robust design method for the projected climate. The projected climate change was incorporated into the model at the 100 year return period with 6 h duration depths, using a statistical regionalization analysis method. Projection from different sets of climate model combinations varied substantially. Gridded reanalysis data were used to assess the performance of the climate models. An existing Hydrologic Engineering Center's Hydrological Modeling System (HEC-HMS) model was implemented using the projected change in standard design storm. Hydrological simulation using HEC-HMS showed exceedances of existing stormwater facilities that were designed under the assumption of stationarity design depth. Recognizing climate change and taking an immediate approach in assessing the city's vulnerability by using proper strategic planning would benefit the urban sector and improve the quality of life. United States has grown as a progressively urban society since last century [11] . Urbanization augments the impervious areas, resulting in less infiltration of rainwater and, consequently, magnified hydrologic effects [12] . The change in land cover associated with urbanization has resulted in an increase in discharge, volume, and frequency of floods [11] . Future changes in high-intensity rainfalls that are derived from climate change will have amplified effects on urban stormwater systems. Stormwater infrastructures are used to convey water from storm runoff to outlets, and serve as artificial flood-mitigation facilities. The proper design and management of stormwater drainage systems can attenuate the more severe effects of extreme rainfall events. The current prevailing standards for the design of stormwater drainage systems are based on the assumption that the probability distribution of rainfall extremes remains statistically stationary [13, 14] . The climate change has resulted in uncertainty regarding the future performance of facilities designed and built under this standard [15] . A nonstationary nature of the recent extreme events has directed researchers for the need of better flood protection practice [14] . The increased frequency and magnitude of storm events could surpass the capacity of stormwater facilities and increase the amount of total sediment transport [16] . The effects of excess rainfall range from the localized street to large-scale flooding. Increasing uncertainty resulting from the fast-changing nature of climate is becoming a major challenge in the field of water management [17] [18] [19] . The current practice for hydrologic design of stormwater facilities uses precipitation depths calculated from the analysis of historical data for a standard return period [16] . Design from the analysis of historical data does not account for the effects of climate change on future meteorological conditions. Thus, the assumption may be subjected to errors [20] . The conventional method of stationarity-based design of water management systems has long been compromising the fluctuating nature of climate [21] . Predicted changes in climate over the next century necessitates a change in the current traditional practices for stormwater facilities design [22] . More flexible and robust design methods are needed to incorporate climate-induced changes [16, 20] . These methods should be simple and straightforward enough in their application for design engineers and water managers. In the current urban drainage design practice, the use of the hydrological models such as design, planning, and management have become common practice. New design practices need to include the use of existing hydrological models for different places with some necessary adjustments [23] . Surface hydrology models are used to study and design stormwater facilities, especially to assess the effects of climate change [24] . These models take rainfall input as event-based data or continuous time-series data. Various types of climate models are used to assess the effects of climate change. Projected climate data from global climate models (GCMs) and regional climate models (RCMs) are found in gridded datasets. RCMs are used to downscale coarsely gridded data from GCMs to the regional level [2, 25] . These climate models assess climate change scenarios with different assumptions, and the output varies substantially in each. Assessment of climate-change effects on future hydrologic conditions should take into consideration various climate models in order to account for the inherent uncertainty of projected outputs [25] . The North American Regional Climate Change Assessment Program (NARCCAP) provides various sets of climate data using the nesting technique between the synoptic-scale GCMs and the associated mesoscale spatial and temporal resolution fields simulated by RCMs [26]. Both GCMs and RCMs project the effects of climate change on hydrology; however, the level of detail for both models is not suitable for hydrological application [7] . Projected data from these climate models are contingent on systematic bias, particularly with regard to precipitation [27] . Generally, two types of downscaling methods, statistical downscaling and dynamical downscaling, are used to link the projected climate outputs to the desired catchment-level hydrological application of climate-change effects [25, 28] . These downscaling methods are not straightforward to apply. The delta change method (DCM), which serves as an alternative to more complicated downscaling methods, transposes the gridded future climate data to point-precipitation data [29, 30] . DCMs include pertinent information for assessing hydrological effects induced by climate change; its implementation is simple and straightforward [29] . In DCM, calculated deviations between the gridded projected future and
doi:10.3390/hydrology3040034 fatcat:7lhwqhpejvcipotfm4txxa2sse