ANNOUNCEMENTS
The changing land-use land cover (LULC) or accelerated urbanization is one of the primary reasons for increased urban runoff. With increasing urbanization and development, various cities in India and across the world are witnessing urban floods. Delhi, the capital of India and a part of Yamuna river basin has witnessed severe problem of urban runoff in the form of floods in past years. The scarcity of studies focussing on quantitative (scenario based) runoff estimation in Delhi and estimation of effective impervious area in larger ungauged basins is the motivation for this research work. This doctoral research work aims at assessing the impacts of changing LULC on the runoff of Delhi for time period 2005-2031. To achieve the desired aim, the entire research work is divided into three research objectives. In the first objective, the LULC of Delhi for year 2031 is predicted using multilayer perceptron markov chain algorithm through land change modeling. The spatiotemporal land-use dynamics during 2005-2031 reveals outward growing urban areas especially on the western part of the city, encroaching into the agricultural areas. The spatial approaches of urban expansion, intensity, rate and direction of urbanization are examined to understand the phenomenon of urbanization in the city over the period of time. In the second objective, the efficacy of GIS-CN method in calculating effective impervious area (EIA) is demonstrated for an ungauged large urban basin having an area of 1483km2. The calculated EIA values are validated with directly connected impervious area (DCIA) values measured using geospatial data. In the third research objective, hydrological impacts of historical and future LULC for the year 2005, 2010, 2016 and 2031 are examined. Soil and Water Assessment Tool (SWAT) hydrological model has been employed at daily interval for simulating hydrological responses. The model has been validated using sequential uncertainty fitting 2 (SUFI-2) algorithm in SWAT calibration and uncertainty program (SWAT-CUP). The model is observed to perform well with R2 and NSE >0.8 and PBIAS <5. Among EIA and TIA, model determines EIA as a preferable parameter in runoff calculation. The findings of hydrological response reveal that surface runoff is majorly influenced by built-up whereas evapotranspiration, percolation and groundwater recharge are affected in vegetation dominated LULC classes. The predicted scenario of year 2031 reveals more runoff from urbanizing sub-basins in comparison to that of previous years. The research indicates that groundwater state in the study region is continuously declining and would become more adverse in future with predicted urbanization. This research would pave the way for use of EIA in runoff estimation studies in larger urban basins and comprehensive understanding of quantification of hydrological changes in different land-use scenarios.
