Assessment of Climate Change Impacts on River Basins Originating in the Western Ghats of India

Abstract

The Western Ghats of India are an environmental and climate-sensitive region of India. The Western Ghats are the mountainous forest range of tropical region which plays a major role in the distribution of Indian monsoon rains. The present study was focused on the assessment of climate change impacts on the hydrology of river basins originating in the Western Ghats of India. Nine river catchments across the Western Ghats were selected to represent the complete range of spatial, topographical and climate variability. The study was carried out with four objectives which include (i) Analysis of historical trends in rainfall, temperature, evapo-transpiration, and streamflow, (ii) Performance evaluation of bias correction methods for precipitation and temperature with regard to hydrological modeling, (iii) Simulation of catchment response under forecasted climate conditions by using the Soil and Water Assessment Tool (SWAT) hydrological model, and, (iv) Examination of dependence of streamflow on elevation and suitability of regional network of weather stations and river gauges for predicting hydrological impacts of climate change. The data used in the study were procured from India Meteorological Department (historical meteorological data), Rossby Centre Regional Climate Model - RCA4 (RCP 4.5 forecasted meteorological data), and India Water Resource Information System (river gauging data). The frequency analysis was also carried out on the river flow to obtain flow quantiles at 10% duration intervals in the range 10% - 90%. The High flow index (HFI) (Q10/Q50) and the Low flow index (LFI) (Q90/Q50) were derived from the flow quantiles. The HFI was used to characterize the relative magnitudes of peak flow (Q10) with reference to the median flow (Q50), while the LFI was used to characterize relative magnitudes of low flow (Q90) to the median flow. The trend analysis was performed using the modified Mann-Kendall trend test and the magnitude of the trend was estimated using the Sen’s Slope Estimator. The analysis was carried out for scenarios: Scenario 1 (1951-2005; historical data) and Scenario 2 (2006-2060; forecasted data). The trend analysis of historical data revealed that the effect of climate change in the river basins of Western Ghats of India is quite heterogeneous and the central and southern portions of the Western Ghats are more vulnerable to the climate change. The annual rainfall was found to increase over central rivers (Malaprabha and Aghanashini) by 4% and 3.5% per decade, respectively. The annual rainfall over southern rivers, Netravathi and Vamanapuram decreased by 3% and 4.3% per decade. The southern rivers indicated a weakening of the Indian South-west monsoon as monsoon rainfall decreased at the rate of 3.2%, 2.3%, and 6.2% per decade over Netravathi, Chaliyar, and Vamanapuram river catchments, respectively. However, the post-monsoon and summer rainfall was found to be increasing. No improvement was noticed in the forecasted scenario. The historical temperature was found to be increasing with average annual temperature rising to the extent from 0.02 °C to 0.12 °C per decade. The southern river catchments witnessed the highest increase in average annual temperature (0.12 °C per decade in Vamanapuram catchment) and it was found that the southern river catchments are warming more rapidly as compared to the northern river catchments. Upon analysis of the seasonal temperature, the increase during monsoon season was the highest followed by the summer season. The forecasted scenario indicates a higher rate of increase in annual and seasonal temperature. The monsoon and summer season could witness an increase at the rate of 0.14 °C per decade. The potential evapo- transpiration indicates an increasing trend over several catchments, as a consequence of rising temperature. The streamflow in the rivers was found to be decreasing by as much as 17.50% annually in the southern rivers followed by 12% and 4% decrease in central and northern rivers, respectively. The river Aghanashini in the central portion of the Western Ghats of India demonstrated better resilience to climate change. The bias correction methods adopted and compared in this study were the Linear Scaling (LS), Delta Change Correction (DC), Local Intensity (LI) scaling, Power Transform (PT), Variance Scaling (VS), and the Distribution Mapping (DM) method. These six methods may be classified into five bias correction methods applied for precipitation (LS, DC, LI, PT, and DM) and four methods for temperature (LS, DC, VS, and DM). The results indicated that the raw-RCM simulated precipitation is biased by 42% and the temperature is biased by 12% across the catchments investigated. Subsequently, a bias of 65% was found in the streamflow. This was attributed to underestimation of heavy precipitation and overestimation of light precipitation events and precipitation frequencies, by the RCM. The DC method significantly improved the rainfall and temperature time series for the catchments. The hydrologic modeling using the bias-corrected data forced on SWAT hydrological model showed the superiority of DC method. The performance of the delta change correction method was consistently better for precipitation (with NSE >0.75 for 5 catchments) and temperature (NSE = 1) compared to other methods. Good performance was observed between the observed and bias corrected streamflow (daily time scale) for the catchments Purna (NSE = 0.97), Ulhas (NSE = 0.64), Aghanashini (NSE = 0.82), Netravathi (NSE = 0.89), and Chaliyar (NSE = 0.90), low performance with NSE of 0.3 was observed for catchments Kajvi and Vamanapuram. The methods failed for Malaprabha and Tunga catchments. This work concludes that, the delta correction method is the most appropriate method of bias correction for the impact analysis of climate variables for the catchments of the Western Ghats. The examination of dependence of rainfall and streamflow on elevation stratification revealed that the lag time between the rainfall event and resulting runoff was proportional to elevation stratification (10, 20, and 30 days in Zone 1, 2, and 3, respectively for river Aghanashini). Also, the maximum intensity of rainfall over the west-flowing rivers of the Western Ghats of India is at some distance from the crest on the windward side. In the east-flowing rivers, the maximum rainfall is at the crest and decreases on the leeward side from the Western Ghats. The impacts of climate change on the local response to streamflow pattern was found to be varying and the availability of water in the month of May was higher compared to previous decades. The number of rainy days (rainfall>2.5mm/day) was lesser in the northern catchments and higher in the central and southern catchments indicating that, the central and southern portions of the Western Ghats receive more events of rainfall, but the intensity of rainfall is decreasing over time. The major contributing months for monsoon rainfall are June-July and the second half of monsoon (August and September) are witnessing a decrease in rainfall. Compared to conventional peak streamflow availability during July and August, the peak streamflow availability is higher during July as a response to such changing rainfall pattern. The variation in annual streamflow availability is less in the northern rivers and decreasing in the southern rivers. The frequency analysis suggests more Q10 flows in central rivers (Malaprabha, Aghanashini, and Tunga) and lesser Q10 and Q90 flow in the southern rivers (Netravathi, Chaliyar, and Vamanapuram). The High Flow Index (HFI) slightly increased in the northern rivers and magnitude of increase was higher in central rivers. The HFI decreased in the southern rivers and accordingly, the Low Flow Index (LFI) increased. The present work is an attempt to comprehensively study the climate change and its impact on rivers of the Western Ghats of India. The work is an effective tool in understanding the hydrological impacts of climate change and adopting strategies to counter the impacts of climate change.