A multi-pollutant pilot study to evaluate the grey water footprint of irrigated paddy rice
Abstract
Grey water footprint (GWF) is one component of water footprint (WF). It considers multiple pollutants and water quality regulations when determining the amount of freshwater required to assimilate the pollution load discharged by agricultural production into the receiving water body. This indicator is typically estimated for accounting the WF of agricultural productions including paddy rice. This study evaluates the GWF of irrigated paddy rice (IPR) through sampling multiple pollutants in both the inflow and drainage of a pilot area, simultaneously. It aims to find a realistic range for the GWF of IPR and emphasize the impacts of pollutants, regulations (Cmax), and inflow (Qin) variations. For this purpose, an isolated subsurface drained farm in northern Iran was chosen as a pilot area where 32 samples from inflow and outflow were taken during the cultivation period (94 days). Here, the concentrations of electro-conductivity (EC), dissolved oxygen (DO), chemical oxidation demand (COD), nitrate (NO3), total kjeldahl nitrogen (TKN), total phosphorous (TP), total nitrogen (TN), and butachlor herbicide, as well as irrigation and drainage volume were investigated. Cmax was examined through three regulation scenarios: strict (S1), normal (S2), and lenient (S3). In addition, Qin was measured by the methods of water balance and SCD-USDA. Results show that TP was most critical in paddy rice GWF (S1-S2), while DO can be an alternative critical parameter in S3. Based on calculations, GWF was ultimately varied between 1109 and 8079 m3/ton in all scenarios. It incorporated a significant share in WF as its ratio varied between 46% and 86%. Cmax showed relatively higher impacts on GWF comparing with the precise calculation of Qin. Moreover, calculating the net pollution loads of multiple pollutants discharged from paddy field was recommended for higher accuracy. As a result, a range for GWF is introduced instead of an absolute value that can be updated by further case studies. © 2023 The Authors