List of Notation
2.4 Impact assessment of urban settlement on hydrology
The two important components of hydrology, surface and groundwater, both may be affected by the expansion of urban settlement. Till date, numerous studies have been carried out to study the impact of imperviousness on hydrology. Some of those are presented below:
Brun and Band (2000) investigated the impact of impervious surface on runoff ratio and base flow in a watershed Baltimore, USA by coupling “Hydrologic Simulation Program Fortran” (HSPF) with “GIS”. The relationships between rainfall-runoff ratio and base flow versus percent impervious cover and percent soil saturation were analysed. It was found that the runoff ratio does not change dramatically till the imperviousness crosses a threshold value (18%). Again, base flow declines as percent impervious cover increases for any percent soil saturation. At 100% soil saturation, base flow ranges from 13 mm per week at 0% impervious cover to 3.5 mm per week near 100% impervious cover.
Megic et al. (2004) evaluated the impact of urbanization (impervious cover) on water availability for groundwater based water supply in Florida. The net groundwater recharge was calculated by using water balance equation with consideration of the constant precipitation but the changing values of the evapotranspiration, groundwater inflow/outflow, surface runoff and artificial recharge under the impact of imperviousness. In the study area, it was found that there is an increase in net recharge as more amount of stormwater runoff generated as result of the increase in urban cover, can be directly recharged to the Floridan aquifer.
Burns et al. (2005) studied the effect of urban cover on hydrologic processes in high density, medium density and undeveloped area individually. It was done by direct measurement of the rainfall, stream discharge and groundwater levels at wells in every
catchment. The mean residence time of stream water was calculated from measurements in precipitation and base flow for every type of catchments. It was found that the peak runoff increases and the mean residence time decrease with the suburban development.
Kauffman et al. (2009) examined how the base flow is affected by impervious covers by plotting stream base flow data against impervious covers of 19 watersheds ranging from heavily forested to highly urbanized in White Clay Creek watershed, part of the Christina River Basin in northern Delaware. The impervious surface was quantified by GIS mapping and base flows were estimated by using stream velocity and cross- sectional areas of streams. A good correlation was found between the base flow and imperviousness indicating that base flow decreases with the increase in impervious cover in watersheds. This decrease in base flow may result in drinking water scarcity especially during drought for the study areas.
Menzel et al. (2009) showed how the stream base-flow is affected by land use and land cover change in Jordan river region. The LandSHIFT.R model was used to simulate and to generate the land use and land cover change distribution maps for the two scenarios- the “Poverty & Peace” and the “Modest Hopes”. These maps were input to the hydrological model “Train” in order to simulate the water availability for the considered scenarios. It was found that for both scenarios though there is an average increase in surface water availability in the urban areas due to the high volume of simulated surface runoff, there will be a shortage of drinking water, especially in dry periods. Again, the 'Modest Hopes' shows the increase of irrigation water demand.
Flinker (2010) reported the hydrological, physical, biological and chemical impacts of impervious surface on a watershed. The “Impervious Cover Model” was used to determine the impact of impervious cover on the present as well as the future stream health. It was mentioned that under natural condition, in general, 10% of rainfall becomes runoff, 50% is absorbed by the ground and the rest 40% is taken by trees and evapo-transpirated to the atmosphere. Again, for a highly impervious surface (75%- 100% imperviousness), the absorption of water by ground may reduce to 15% and the runoff may increase up to 55%.
Fig. 2.1: Changes in site hydrology with increasing impervious cover (US EPA) (Flincker, 2010)
Caldwell et al. (2012) performed a study to quantify the impacts LULC change, water withdrawals, and climate change on river flows in the conterminous US by using integrated Water Supply Stress Index (WaSSI) monthly water balance and flow routing model. It was found that in comparison to 1981–2000 flows without impervious cover, 2010 levels of impervious cover (1.3 % of the total land area) increases the mean annual river flow by 9.9%. Again, compared to no water withdrawals, 2005 withdrawals decreased the mean annual river flows by 1.4 %. In 2060, for the Low and High growth emission scenarios, the combined effect of impervious, population, and climate change, showed a mean decrease in river flow by 11.8% and 11.0%, respectively.
Wagner et al. (2013) analyzed the impact of land cover and land use change on runoff and evaporation for Mula and Mutha rivers catchment upstream of Pune. Three multi- temporal land use scenarios were prepared from multispectral satellite data of three different sensors. SWAT model has been used to assess the impact of land use change on water resources. It was found that due to the increased impervious surface, there is an increase in water yield (+ 7.6%), which can be balanced by the decrease in water yield due to the increase in cropland in some areas of Pune.
Barron et al. (2013) used a coupled surface water–groundwater model (MODHMS) to examine the impacts of urbanization on catchment water balance. This result indicates that depending upon the amount of groundwater abstracted, a 10% increase in imperviousness leads to an increase in discharge by 13% to 33%. Again, infiltration reduced from 70% to less than 20% after urbanization. This shows that increase in imperviousness increases the water availability which can be used for water supply.
Zhou et al. (2014) used distributed object-oriented rainfall and runoff simulation (DORS) model to simulate the discharge, runoff, base flow etc. in Rhode Island, US.
From the simulated data, discharge per unit area and the ratio of runoff to base flow (response variables) are correlated to a set of watershed characteristics including the percentage of IS, distance from IS to stream, and stream density in 20 study watersheds by using ordinary least square, spatial lag and spatial error regression models. The results show that the study watershed with 11 % impervious surface, the magnitude of the peak discharge is almost doubled compared to the simulated discharge without impervious surface. Similarly, the magnitude of peak ratio of runoff to base flow is twice of that from the simulation without IS.
Gwenzi and Nyamadzawo (2014) performed a review on the impact of urbanization and urban roof water harvesting on hydrologic processes in water-limited catchments. It was mentioned that impervious surface causes urban heat island effect due to which there is an alteration in atmospheric water demand, frequency and magnitude of high- intensity rainfall (summer time). Evaporation and ground-water recharge also decline for low soil moisture availability, especially in water limited area. It was suggested that by adopting roof water harvesting, some percentage of water shortage and surface runoff generation can be reduced.
Li et al. (2015) presented how water utilization ratio can be related to land use changes in the upper and middle reaches of the Heihe River Basin, China. The generation time and also the magnitude of peak runoff decreases with the increase of forest or vegetated area. As a result, water yield will decrease and hence there is an increase in water utilization ratio. To simulate spatial land use patterns, the Dynamic Landuse System (DLS) was used for three different land used scenarios based on low, medium and high utilization ratio. After that, SWAT model was used to simulate surface runoff and water yield changes in response to the impacts of land use changes.