Modeling of Inland Surface Waters and Drainage System of Urbanized City in Climate Change Scenario Munjid Maryam1 and Rohitashw Kumar2 1 Research Scholar and 2 Associate Dean, College of Agricultural Engineering and Technology, SKUAST-K

OBJECTIVES RESULTS Figure 2: Water Spread Area Maps Figure 4: Climate Change Run

Climate Change Run 1. Quantifying the impact of urban sprawl on inland surface waters using geospatial approach. INTRODUCTION 2071-2100

2041-2070 2. Climate Change analysis by delta change approach 2020-2040 using Mike Climate change tool. 2006-2017

Water is an overwhelming inexhaustible asset. 3. Simulation of hydrological and hydraulic response and

(m3/s) Discharge performance of inland surface waters and drainage  Evaluation and the operation of water assets system using MIKE 11 and MIKE URBAN Time Period with respect to quality and amount is basic for appropriate use of these assets. By 2050 it is Climate Change Run predicted that 67% of the world population is 8 7 expected to be living in urban areas. 2017 METHODS AND MATERIALS 6 2020-2040 5 2041-2070 4  Urbanization is often directly linked to the 2071-2100 degradation of environmental quality, including 3 2 quality of water. Concurrently, the climate is 1. Monitoring the spatial extent of the inland surface (m) Level Water 1 also changing. waters 0

2. Data collection and preparation Figure 3: Mann-Kendall Statistics of Climatic Variables

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1-Mar 1-Nov As per IPCC (2007) the awareness of the 3. Derivation of parameters 1-May Precipitation Time Period extent to which change of climate can affect the 4. Input data into the model Mann-Kendall Temperature environment, society, and economy is increasing 5. Calibrate and validate the model Climate Change Run 3 Evaporation 2.5 6. Climate change analysis using delta change approach 2018  Together, the negative impacts of climate 7. Simulation of hydrological response of inland surface 2 2

2020- change and urbanization result in urban heat waters 1 1.5 2040 island effect whereby urban areas have higher 8. Simulation of hydraulic performance of drainage 1 temperatures. system 0

0.5

Statistic Discharge (m3/s) Discharge - -1  And thus cause heavy precipitation events Z 0 -2 Zone Zone Zone Zone leading to increase in flood frequency of rivers. 1 2 3 4 -3 Zones Also, there is an impact on urban drainage RESULTS Month system because the volume and flow rate may Table 2: Statistical Analysis CONCLUSIONS exceed the capacity of existing drainage system Table 1: Water Spread Area leading to frequent surcharging, surface flooding and water logging. Model Accuracy Criteria Inland Surface Percentage Change Percentage •The inland surface waters are declining rapidly due to the urban sprawl. Waters (2000-2010) Change Nash- Coefficient of Root Mean (2010-2020) Accuracy • The statistical results reveal that there will be an Sutcliffe Determination Square -16.57 17.85 impact on precipitation and evapotranspiration as Criteria→ Efficiency R2 Error temperature is expected to increase by 2.8 ºC . -0.84 -0.85 NSE • The statistical results of MIKE 11 and MIKE URBAN Amir Khan Nallah -10.28 -30.21 Hydrodynamic reveal that the models are efficient for simulations. Gilsar and Khushalsar -7.83 -18.49 Modeling↓ • The climate change run indicates an that the Lake discharge, gauge water level and link discharge Average Value 0.898 0.912 0.281 and thus flood threats and wtaerlogging risk will Figure 1. Ecologically degraded -43.92 -34.46 increase. Gilsar Lake -12.18 -6.93 River Jhelum -8.06 15.94