ASSESSMENT OF WATER BALANCE COMPONENTS IN THE KRISHNA RIVER BASIN: A PERSPECTIVE OF CLIMATE AND LAND USE LAND COVER CHANGE

Abstract

Natural resources like water have a direct or indirect impact on the ecological and socioeconomic development of a region. In a given location, variations in the land cover, weather, geology, morphological factors such as basin slope and topography, climate change and human activity all contribute to changes in the water budget both spatially and temporally. A worldwide phenomenon, climate change affects different regions to differing degrees. The assessment of climate change effects across a river basin has become essential for effective water resource management due to the accelerating rate of climate change. With this climate change, the changes in Land Use Land Cover (LULC) over a long period in a regional scale is also plays a key role for the availability of water resources. Several Global Climate Models (GCMs) have been generated to forecast the earth's climate in a variety of conceivable futures. GCMs are numerical simulations of distinct physical processes that reflect the seas, land surface, atmosphere, cryosphere and among other components of the global climate system. Policymakers can create recommendations and mitigation plans by using the future climate projections to comprehend the possible effects of climate change. However, the direct use GCMs for the climate change projections in a regional scale may lead to large uncertainty in the results due to their larger spatial resolution. And performance of GCMs are region specific due their coarser resolution, structure, parameterization, boundary conditions and so on. The GCMs are need to be bias corrected and selection of suitable GCMs are necessary before using in the regional scale climate change studies. The need for water is growing worldwide due to population growth and the expansion of cities, industries and agriculture, all of which are causing a decline in the amount of freshwater resources available. Consequently, it is necessary to look into the hydrological changes linked to climate change in order to secure water availability and promote sustainable development, particularly in an agricultural nation like India. In this study, the GCMs of Coupled Modelled Intercomparison Project 6 (CMIP6) phase repositories are considered for climate change projections in a river basin. This study used Tier 1 Shared-Socioeconomic Pathways (SSPs) scenarios that include SSP1-2.6, SSP2-4.5, SSP3 7.0 and SSP5-8.5 to provide a full range of forcing targets similar in both magnitude and distribution to the RCPs used in CMIP5. In the present work the comprehensive analysis of climate change and their extremes in a river basin is analysed using Multi Model Ensemble (MME) of CMIP6-GCMs. xv Initial phase of research work is devoted to investigate the subjectivity involved in the ranking of CMIP6-GCMs using maximum and minimum temperature (Tmax and Tmin) across India. Different ranking procedures are employed, encompassing a variety of components in the process, such as model evaluation criteria, criteria weight allocation methods, Multi-Criteria Decision Making (MCDM) techniques and reference gridded datasets. The effect of each individual component on the ranking pattern is systematically analysed and the spatial distribution of grids with same ranking patterns across all the combinations are considered as grids with same ranking. The performance of best performing GCMs are attributed to homogenous climatic zones of India and its corresponding topological features. An ensemble of frequently performing top five GCMs among 16 different ranking procedures are extracted for each climate zone as the most suitable set of GCMs. The second part of the study work, focused on climate change impact on a river basin in India. The Krishna River Basin (KRB), which is heavily exploited and extremely vulnerable to climate change, was studied to assess the effects of climate change under several forcing scenarios. The concept of Symmetric Uncertainty (SU) is employed on monthly scale to select the top five GCMs. Reliability Ensemble Averaging (REA) approach is used to allocate the weights of selected GCMs to analyse the spatio-temporal analysis of precipitation variation across the KRB. The MME mean of the chosen GCMs showed significant changes in precipitation projection that occurs for a far future period (2071–2100) over the KRB. The projection changes of precipitation range from -36.72 to 83.05% and -37.68 to 95.75% for the annual and monsoon periods, respectively, for various SSPs. Monsoon climate projections show higher changes compared with the annual climate projections, which reveals that precipitation concentration is more during the monsoon period over the KRB. This study draws attention to the better comprehension of spatio-temporal analysis of climate changes based on precipitation extremes and projection of future streamflow for efficient management of water resources in KRB. Grid-wise trend analysis reveals that there are more number of decreasing trends in extreme precipitation indices than increasing trends for the observed period 1973-2003. It is observed that the percentage contributions of maximum one day (RX1day) and five-day (RX5day) precipitation indices to the annual total precipitation indices are more important. It is found that in future periods, the precipitation extremes based on Expert Team of Climate Change Detection Indices (ETCCDI) are expected to increase. The projection of future streamflow in the KRB is done using a Support Vector Machine (SVM) xvi and is expected to increase under different SSPs. These precipitation extremes may increase the chance of hydrological calamities in the future across the basin. This study assesses the impacts of climate change on the water balance of KRB in India. A frequency-based metric, known as SU, is used to select the top 50% of GCMs from a pool of eighteen CMIP6-GCMs for hydrological modelling. The impact of climate change is projected for three future time frames: Near Future (NF: 2026-2050), Mid Future (MF: 2051-2075) and Far Future (FF: 2076-2100) using four scenarios from SSPs: SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. Soil and Water Assessment Tool (SWAT) model is used to simulate climate change impact on historical and future periods in the basin. The SWAT model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI-2) technique of the SWAT calibration and uncertainty programme (SWAT-CUP). The results show a significant increase in the annual average precipitation, surface runoff, water yield and streamflow in the future under all SSP scenarios. The increase in the projected annual average precipitation is ranged from 12% to 54% for four SSP scenarios compared to the historical ensemble average. The ensemble average of Indian Summer Monsoon Rainfall (ISMR) precipitation is projected to increase in the range of 13.7% to 55% for the future period compared to historical GCMs ensemble average of baseline period. The highest precipitation, water yield, surface runoff and streamflow are projected to increase 54%, 125%, 124% and 114.5% respectively in FF under SSP5-8.5 scenario compared to ensemble average of baseline period. Precipitation change has a significant influence on future streamflow, with projections showing a potential increase of 31 to 114.5%. Future periods show a shift in the monthly peak flows as compared to the baseline period. More availability of water in the future in the KRB can be effectively used for various water management works. In this research work the combined impact of climate and LULC change over Tungabhadra River Basin (TRB) was analysed. TRB is one of the major tributary of KRB, which is very essential water resource for the Karnataka state in India. The developed future land use dataset based on SSP-RCP framework for the years 2015 to 2100 is used in this investigation. The LULC for the base year 2015 and future periods under two SSP scenarios, SSP1-2,6 and SSP5 8.5 are forced for the hydrological SWAT model. In the calibration period, both coefficient of determination (R2) and Nash Sutcliff Coefficient (NSE) is obtained as 0.75 and for the validation period these values are obtained as 0.72 and 0.7 respectively. The simulated major land use classes are identified in Tungabhadra basin as water (1.41%), built-up (0.23%), cropland (76.23%), barren land (9.3%), forests (12.8%) and grassland (0.04%) as per the LULC xvii of the year 2015. The grass land and barren land is totally converted to cropland in the future under SSP585 scenario where as in case of SSP1-2.6 scenario only barren land totally converted to cropland. The grassland is projected to decrease from 8.37% to 1.61%, a reduction of 6.76% in the FF under SSP1-2.6 scenario. The urbanization and cropland are projected to extend up to 0.59% and 87.88% respectively under SSP5-8.5 scenario till 2100. There is no significant change in the forest cover under SSP1-2.6 scenario but under SSP5-8.5 it has shown small decline by 2.92% in the future. By the end of the twenty-first century, the ensemble mean temperature is predicted to increase by 1.56 oC and 4.65 oC, respectively, under the SSP1-2.6 and SSP5-8.5 scenarios. The results show that the WBC such as Surface runoff (SurQ), Groundwater (GWq), and Water Yield (WY) are also following the significant increasing trend with the precipitation. Peak streamflow for all the GCMs are varying between months of August and September under both SSP scenarios. The findings of this study on the Krishna River's climate change impact can be utilised to create appropriate adaptation plans for the management of these basins' water resources. The research work's methodology can be applied to various river basins in India and around the globe. Keywords: GCM, Performance metrics, MCDM techniques, River basin, Symmetric Uncertainty, Climate Change Impacts, LULC, WBC and Stremflow