Long-Term Climate Variability and Drought Characteristics in Tropical Region of India

This work reports climate change signals and long-term trend analysis of climate variables, meteorological drought, and extreme climate indexes over the tropical state of Kerala in India. The trend analysis reveals statistically significant decrease of annual and southwest monsoon rainfall (as much as 63 mm and 55 mm per decade, respectively). A decrease in number of annual rainy days (up to 2.8 days=decade) is also reported. Temperature trend analysis indicates an increasing trend with as high as 1.3°C=decade. The spatiotemporal variation of extreme climate indexes across Kerala shows a decreasing trend of extreme precipitation indexes and an increasing trend of extreme temperature indexes. R95 and R95p decreased in northern and southern Kerala whereas R5 index increased in central and southern regions. Warm days have significantly increased whereas cold days exhibit a decreasing trend across the state. The increase in warmer nights is statistically significant whereas colder nights are decreasing in central and southern regions. Meteorological drought using Standardized Precipitation Index (SPI) reveals increasing occurrence of droughts in Kerala with higher frequencies over southern and central Kerala

Bias correction methods for hydrologic impact studies over India’s Western Ghat basins

The regional climate models (RCMs) used in the analysis of the impact of climate variables on the hydrology of river basins needs appropriate preprocessing (bias correction) to represent and reproduce future climate with a fair degree of accuracy. The performance of bias corrections methods was assessed in this investigation on the basis of their ability to minimize error on climate variables and streamflow. This work compares the performance of five bias correction methods applied for precipitation and four methods for temperature in modeling the hydrology of the river catchments of the Western Ghats of India. The Western Ghats are a mountainous forest range along the entire west coast of India that plays a major role in the distribution of Indian monsoon rains. Simulations were used to evaluate the performance of the bias correction methods. Using raw RCM, bias corrected precipitation and temperature time series, streamflows were estimated by the soil and water assessment tool (SWAT) hydrological model. The results indicated that the raw RCM-simulated precipitation was biased by 42% and the temperature was biased by 12% across the catchments investigated. Subsequently, a bias of 65% was found in the streamflow. The performance of the delta change correction method was consistently better for precipitation (with Nash-Sutcliffe efficiency, NSE>0.75NSE>0.75 for 5 catchments) and temperature (NSE=1NSE=1) compared with other methods. Good performance was observed between the observed and bias corrected streamflow (daily time scale) for the catchments Purna (NSE=0.97NSE=0.97), Ulhas (NSE=0.64NSE=0.64), Aghanashini (NSE=0.82NSE=0.82), Netravathi (NSE=0.89NSE=0.89), and Chaliyar (NSE=0.90NSE=0.90); low performance with an NSE of 0.3 was observed for the catchments Kajvi and Vamanapuram. The methods failed for Malaprabha and Tunga catchments. The results indicate that the delta change correction method performed best in analyzing the hydrological impact of climate variables on the windward side of Western Ghats of India

Estimating anisotropic heterogeneous hydraulic conductivity and dispersivity in a layered coastal aquifer of Dakshina Kannada District, Karnataka

•Constraining the 3D variable density numerical model with field measurements.•Estimation of anisotropic heterogeneous hydraulic conductivity.•A novel method to validate solute concentration results with ERT profile.•Verification of assigned aquifer topography and estimated geological formation. The solution for the inverse problem of seawater intrusion at an aquifer scale has not been studied as extensively as forward modeling, because of the conceptual and computational difficulties involved. A three-dimensional variable-density conceptual phreatic model is developed by constraining with real-field data such as layering, aquifer bottom topography and appropriate initial conditions. The initial aquifer parameters are layered heterogeneous and spatially homogeneous that are based on discrete field measurements. The developed conceptual model shows poor correlation with observed state variables (hydraulic head and solute concentration), signifying the importance of spatial heterogeneity in hydraulic conductivity and dispersivity of all the layers. The conceptual model is inverted to estimate the anisotropic spatially varying hydraulic conductivity and the longitudinal dispersivity at the pilot points by minimizing the least square error of state variables across the observation wells. The inverse calibrated model is validated for the hydraulic head at validation wells and the solute concentration is validated with equivalent solute concentration derived from the electrical resistivity, which shows good results against the field measurements. The verification of estimated anisotropic hydraulic conductivity with the electrical resistivity tomography image shows good agreement. This investigation gives an insight about constraining the highly parameterized inverse model with real-field data to estimate spatially varying aquifer parameters for an effective simulation of the seawater intrusion in a layered coastal aquifer

Effects of land use and climate change on water scarcity in rivers of the Western Ghats of India

This paper assesses the long-term combined effects of land use (LU) and climate change on river hydrology and water scarcity of two rivers of the Western Ghats of India. The historical LU changes were studied for four decades (1988–2016) using the maximum likelihood algorithm and the long-term LU (2016–2075) was estimated using the Dyna-CLUE prediction model. Five General Circulation Models (GCMs) were utilized to assess the effects of climate change (CC) and the Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the two river catchments. To characterize granular effects of LU and CC on regional hydrology, a scenario approach was adopted and three scenarios depicting near-future (2006–2040), mid-future (2041–2070), and far-future (2071–2100) based on climate were established. The present rate of LU change indicated a reduction in forest cover by 20% and an increase in urbanized areas by 9.5% between 1988 and 2016. It was estimated that forest cover in the catchments may be expected to halve compared to the present-day LU (55% in 2016 to 23% in 2075), along with large-scale conversion to agricultural lands (13.5% in 2016 to 49.5% in 2075). As a result of changes to LU and forecasted climate, it was found that rivers in the Western Ghats of India might face scarcity of fresh water in the next two decades until the year 2040. However, because of large-scale LU conversion toward the year 2050, streamflow in rivers might increase as high as 70.94% at certain times of the year. Although an increase in streamflow is perceived favorable, the streamflow changes during summer and winter may be expected to affect the cropping calendar and crop yield. The changes to streamflow were also linked to a 4.2% increase in ecologically sensitive wetlands of the Aghanashini river catchment

Evaluation of Satellite Precipitation Products in Simulating Streamflow in a Humid Tropical Catchment of India Using a Semi-Distributed Hydrological Model

Precipitation obtained from rain gauges is an essential input for hydrological modelling. It is often sparse in highly topographically varying terrain, exhibiting a certain amount of uncertainty in hydrological modelling. Hence, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. In this study, an attempt was made to evaluate the Tropical Rainfall Measuring Mission (TRMM) and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), employing a semi-distributed hydrological model, i.e., Soil and Water Assessment Tool (SWAT), for simulating streamflow and validating them against the flows generated by the India Meteorological Department (IMD) rainfall dataset in the Gurupura river catchment of India. Distinct testing scenarios for simulating streamflow were made to check the suitability of these satellite precipitation data. The TRMM was able to better estimate rainfall than CHIRPS after performing categorical and continuous statistical results with respect to IMD rainfall data. While comparing the performance of model simulations, the IMD rainfall-driven streamflow emerged as the best followed by the TRMM, CHIRPS-0.05, and CHIRPS-0.25. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) were in the range 0.63 to 0.86, 0.62 to 0.86, and −14.98 to 0.87, respectively. Further, an attempt was made to examine the spatial distribution of key hydrological signature, i.e., flow duration curve (FDC) in the 30–95 percentile range of non-exceedance probability. It was observed that TRMM underestimated the flow for agricultural water availability corresponding to 30 percent, even though it showed a good performance compared to the other satellite rainfall-driven model outputs.Validerad;2020;Nivå 2;2020-08-31 (alebob)</p