Development of multiple linear regression models for predicting the stormwater quality of urban sub-watersheds.

Stormwater management at urban sub-watershed level has been envisioned to include stormwater collection, treatment, and disposal of treated stormwater through groundwater recharging. Sizing, operation and control of the stormwater management systems require information on the quantities and characteristics of the stormwater generated. Stormwater characteristics depend upon dry spell between two successive rainfall events, intensity of rainfall and watershed characteristics. However, sampling and analysis of stormwater, spanning only few rainfall events, provides insufficient information on the characteristics. An attempt has been made in the present study to assess the stormwater characteristics through regression modeling. Stormwater of five sub-watersheds of Patiala city were sampled and analyzed. The results obtained were related with the antecedent dry periods and with the intensity of the rainfall event through regression modeling. Obtained regression models were used to assess the stormwater quality for various antecedent dry periods and rainfall event intensities.

Electrocoagulation removal of Cr(VI) from simulated wastewater using response surface methodology.

The present study envisages the performance of a laboratory scale electrocoagulation system for the removal of Cr(VI) from 100 mg l(-1) solution using Al-Al electrodes with an effective surface area of 100 cm(2), and placed 15 mm apart. The interaction between voltage x time, and amperage x time best explained the Cr(VI) reduction efficiency with the coefficient of determination (R(2)) being 0.8873 and 0.9270 respectively. Similarly, the square root of energy consumption in Cr(VI) reduction had a linear correlation with voltage x time (R(2)=0.8949), whereas, amperage x time better explained energy consumption (R(2)=0.9400). Response surface methodology was used for the optimization of process variables (pH, voltage and treatment time), response modeling and predictions. Maximum Cr(VI) reduction efficiency of 90.4% was achieved at pH 5, 24 V and 24 min treatment time, and the treatment consumed 137.2 KWh m(-3) of electrical energy. Multiple response optimization for maximizing Cr(VI) reduction efficiency and minimizing energy consumption showed 49.6% Cr(VI) removal at pH 5, 12.8 V and 24 min treatment time. The response models developed explained 95.2% variability for Cr(VI) reduction efficiency and 99.4% variability for energy consumption. Results of the prediction models were validated through laboratory scale batch experiments.