Your search found 8 records
1 Babovic, V.. 1991. Applied hydroinformatics: A control and advisory system for real-time applications. Delft, The Netherlands: IHEE. 134p.
(Location: IWMI-HQ Call no: 551.48 G000 BAB Record No: H011926)
A dissertation submitted in partial fulfillment of the Master of Science Degree of the International Institute for Hydraulic and Environmental Engineering (IHE) Delft, on the basis of work carried out at the Danish Hydraulic Institute (DHI).
2 Liong, S. Y.; Gautam, T. R.; Khu, S. T.; Babovic, V.; Keijzer, M.; Muttil, N. 2002. Genetic programming: A new paradigm in rainfall runoff modeling. Journal of the American Water Resources Association, 38(3):705-718.
(Location: IWMI-HQ Call no: PER Record No: H030958)
3 Vojinovic, Z.; Kecman, V.; Babovic, V.. 2003. Hybrid approach for modeling wet weather response in wastewater systems. Journal of Water Resources Planning and Management, 129(6):511-521.
(Location: IWMI-HQ Call no: PER Record No: H033265)
4 Sannasiraj, S. A.; Zhang, H.; Babovic, V.; Chan, E. S. 2004. Enhancing tidal prediction accuracy in a deterministic model using chaos theory. Advances in Water Resources, 27(7):761-772.
(Location: IWMI-HQ Call no: PER Record No: H035403)
5 Meshgi, A.; Schmitter, P.; Babovic, V.; Chui, T. F. M. 2014. An empirical method for approximating stream baseflow time series using groundwater table fluctuations. Journal of Hydrology, 519:1031-1041. [doi: https://doi.org/10.1016/j.jhydrol.2014.08.033]
Stream flow ; Time series analysis ; Hydrology ; Models ; Simulation ; Water resources ; Groundwater table ; Catchment areas ; River basins ; Rain ; Soil hydraulic properties ; Case studies / Singapore / USA / Kent Ridge Catchment / Beaver River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046591)
(1.73 MB)
Developing reliable methods to estimate stream baseflow has been a subject of interest due to its importance in catchment response and sustainable watershed management. However, to date, in the absence of complex numerical models, baseflow is most commonly estimated using statistically derived empirical approaches that do not directly incorporate physically-meaningful information. On the other hand, Artificial Intelligence (AI) tools such as Genetic Programming (GP) offer unique capabilities to reduce the complexities of hydrological systems without losing relevant physical information. This study presents a simple-to-use empirical equation to estimate baseflow time series using GP so that minimal data is required and physical information is preserved. A groundwater numerical model was first adopted to simulate baseflow for a small semi-urban catchment (0.043 km2) located in Singapore. GP was then used to derive an empirical equation relating baseflow time series to time series of groundwater table fluctuations, which are relatively easily measured and are physically related to baseflow generation. The equation was then generalized for approximating baseflow in other catchments and validated for a larger vegetation-dominated basin located in the US (24 km2). Overall, this study used GP to propose a simple-to-use equation to predict baseflow time series based on only three parameters: minimum daily baseflow of the entire period, area of the catchment and groundwater table fluctuations. It serves as an alternative approach for baseflow estimation in un-gauged systems when only groundwater table and soil information is available, and is thus complementary to other methods that require discharge measurements.
6 Meshgi, A.; Schmitter, Petra; Chui, T. F. M.; Babovic, V.. 2015. Development of a modular streamflow model to quantify runoff contributions from different land uses in tropical urban environments using Genetic Programming. Journal of Hydrology, 525:711-723. [doi: https://doi.org/10.1016/j.jhydrol.2015.04.032]
Urbanization ; Hydrology ; Stream flow ; Models ; Rainfall runoff relationships ; Land use ; Infiltration ; Catchment areas ; Vegetation / Singapore / Kent Ridge Catchment
(Location: IWMI HQ Call no: e-copy only Record No: H046995)
(2.55 MB)
The decrease of pervious areas during urbanization has severely altered the hydrological cycle, diminishing infiltration and therefore sub-surface flows during rainfall events, and further increasing peak discharges in urban drainage infrastructure. Designing appropriate waster sensitive infrastructure that reduces peak discharges requires a better understanding of land use specific contributions towards surface and sub-surface processes. However, to date, such understanding in tropical urban environments is still limited. On the other hand, the rainfall–runoff process in tropical urban systems experiences a high degree of non-linearity and heterogeneity. Therefore, this study used Genetic Programming to establish a physically interpretable modular model consisting of two sub-models: (i) a baseflow module and (ii) a quick flow module to simulate the two hydrograph flow components. The relationship between the input variables in the model (i.e. meteorological data and catchment initial conditions) and its overall structure can be explained in terms of catchment hydrological processes. Therefore, the model is a partial greying of what is often a black-box approach in catchment modelling. The model was further generalized to the sub-catchments of the main catchment, extending the potential for more widespread applications. Subsequently, this study used the modular model to predict both flow components of events as well as time series, and applied optimization techniques to estimate the contributions of various land uses (i.e. impervious, steep grassland, grassland on mild slope, mixed grasses and trees and relatively natural vegetation) towards baseflow and quickflow in tropical urban systems. The sub-catchment containing the highest portion of impervious surfaces (40% of the area) contributed the least towards the baseflow (6.3%) while the sub-catchment covered with 87% of relatively natural vegetation contributed the most (34.9%). The results from the quickflow module revealed average runoff coefficients between 0.12 and 0.80 for the various land uses and decreased from impervious (0.80), grass on steep slopes (0.56), grass on mild slopes (0.48), mixed grasses and trees (0.42) to relatively natural vegetation (0.12). The established modular model, reflecting the driving hydrological processes, enables the quantification of land use specific contributions towards the baseflow and quickflow components. This quantification facilitates the integration of water sensitive urban infrastructure for the sustainable development of water in tropical megacities.
7 Schmitter, Petra; Goedbloed, A.; Galelli, S.; Babovic, V.. 2016. Effect of catchment-scale green roof deployment on stormwater generation and reuse in a tropical city. Journal of Water Resources Planning and Management, 142(7):1-13. [doi: https://doi.org/10.1061/(ASCE)WR.1943-5452.0000643]
Catchment areas ; Drainage ; Precipitation ; Water reuse ; Water management ; Vegetation ; Hydrological cycle ; Hydraulic conductivity ; Models ; Reservoir operation ; Urbanization ; Discharges ; Rainfall-runoff relationships ; Weather / Singapore / Marina Reservoir
(Location: IWMI HQ Call no: e-copy only Record No: H047458)
(12.37 MB)
Low-impact development (LID) comprises a broad spectrum of stormwater management technologies for mitigating the impacts of urbanization on hydrological processes. Among these technologies, green roofs are one of the most adopted solutions, especially in densely populated metropolitan areas, where roofs take up a significant portion of the impervious surfaces and land areas are scarce. While the in situ hydrological performance of green roofs—i.e., reduction of runoff volume and peak discharge—is well addressed in literature, less is known about their impact on stormwater management and reuse activities at a catchment or city scale. This study developed an integrated urban water cycle model (IUWCM) to quantitatively assess the effect of uniform green roof deployment (i.e., 25, 50, and 100% conversion of traditional roofs) over the period 2009–2011 in the Marina Reservoir catchment, a 100-km2, highly urbanized area located in the heart of Singapore. The IUWCM consists of two components: (1) a physically based model for extensive green roofs integrated within a one-dimensional numerical hydrological-hydraulic catchment model linked with (2) an optimization-based model describing the operation of the downstream, stormwater-fed reservoir. The event-based hydrological performance of green roofs varied significantly throughout the simulation period with a median of about 5% and 12% for the catchment scale reduction of runoff volume and peak discharge (100% conversion of traditional roofs). The high variability and lower performance (with respect to temperate climates) are strongly related to the tropical weather and climatic conditions—e.g., antecedent dry weather period and maximum rainfall intensity. Average annual volume reductions were 0.6, 1.2, and 2.4% for the 25, 50, and 100% green roof scenarios, respectively. The reduction of the stormwater generated at the catchment level through green roof implementation had a positive impact on flood protection along Marina Reservoir shores and the energy costs encountered when operating the reservoir. Vice versa, the drinking water supply, which depends on the amount of available stormwater, decreased due to the evapotranspiration losses from green roofs. Better performance in terms of stormwater reuse could only be obtained by increasing the time of concentration of the catchment. This may be achieved through the combination of green roofs with other LID structures.
8 Babovic, F.; Babovic, V.; Mijic, A. 2018. Antifragility and the development of urban water infrastructure. International Journal of Water Resources Development, 34(4):499-509. (Special issue: Urban Resilience to Droughts and Floods: Policies and Governance). [doi: https://doi.org/10.1080/07900627.2017.1369866]
Water supply ; Infrastructure ; Urban areas ; Climate change adaptation ; Towns ; Governance ; Uncertainty ; Decision making ; Models ; Flooding ; Risk management
(Location: IWMI HQ Call no: e-copy only Record No: H048813)
(0.95 MB)
Antifragility is a system property that results in systems becoming increasingly resistant to external shocks by being exposed to them. These systems have the counter-intuitive property of benefiting from uncertain conditions. This paper presents one of the first known applications of antifragility to water infrastructure systems and outlines the development of antifragility at the city scale through the use of local governance, data collection and a bimodal strategy for infrastructure development. The systems architecture presented results in a management paradigm that can deliver reliable water systems in the face of highly uncertain future conditions.
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