Application of QUAL2Kw to the Oglio River (Northern Italy) to assess diffuse N pollution via river-groundwater interaction

Abstract

Water quality modeling is increasingly recognized as a useful tool for obtaining valuable information for optimal water quality management. In this study, the free software QUAL2Kw was used to evaluate the impacts of agricultural nitrogen (N) excess on river nitrate (NO3-N) concentrations. We explored the possibility to use QUAL2Kw in order to back calculate the exchange of water and N from the groundwater to the Oglio River, northern Italy, which drains a heavily irrigated and fertilized agricultural land. Along the river course water monitoring activities carried out in the dry, summer period revealed steep increases of NO3-N in different sectors, by up to 2 orders of magnitude, not explained by any significant point inputs. Such increases suggest the occurrence of large water exchange with nitrate-polluted groundwater and diffuse inputs. In turn, groundwater pollution is due to high N excess in the watershed (~200 kg N ha-1 yr-1), flood-based irrigation techniques and soil permeability. The QUAL2Kw model was calibrated using the average of 2 years' data collected in winter 2010 and 2011 and validated using the data of winter 2012. To minimize the error between simulation results and measured data, the constants of inorganic suspended solid (ISS), ammonium (NH4-N), nitrate and organic N were calibrated. The calibration and validation results showed a good correspondence between the calculated and measured values for most of water-quality variables. QUAL2Kw was then run separately with three years' summer data (2009, 2010 and 2011), and large gaps were found between the measured and predicted values of discharge, electrical conductivity, NO3-N and total N. Such gaps are discussed in terms of river-groundwater interactions, limited to the summer period and following irrigation by flooding, rise of the groundwater table and vertical transport of N. The gaps allowed to back calculate the volumes of water and the amount of N exchanged. The total load of NO3-N entering into the river from groundwater was estimated in 25.17, 25.63 and 29.89 ton per day for NO3-N in 2009, 2010 and 2011, respectively. Similar results were obtained in another study based on mass balance of N isotopes. The combination of experimental and QUAL2Kw modelled data proved to be a simple, low cost but effective tool in the estimation of NO3-N exchange between the surface and groundwater.

Total Maximum Daily Load of the Curug Sub-district Segment of The Cirarab River, Indonesia

“…A valid model means that the concentration values of BOD and COD generated by the model do not differ greatly from the measured BOD and COD concentration values, and they are still in the acceptable range. These values were in accordance with previous research in different study areas of which R 2 and RMSE values were close to the number 1 and 10%; the results were still acceptable, and the models were stated to be valid and precise [35,36]. The results from running scenario one are presented in Figure 1.…”

Is Flood Irrigation a Potential Driver of River-Groundwater Interactions and Diffuse Nitrate Pollution in Agricultural Watersheds?

“…Our results for the Oglio River basin confirm the findings of recent studies that estimated N loads from the aquifer to surface-spring to be about 1200 t year −1 (3280 kg day −1 ), and from the aquifer to river to be about 1500 t year −1 (4100 kg day −1 ) in the spring belt zone [14,72,83]. Taherisoudejani et al [85] calculated a NO 3 − load in the range between 3800 and 6000 kg day −1 during the summers of 2009, 2010, and 2011, which would be similar to the N loads calculated in this study (L ds value). Delconte et al [27] investigated the SW-GW interaction in the Oglio basin with a general mass balance approach and with end member mixing analysis, using also water and NO 3 − isotopes to estimate a total groundwater input of between 4 and 5 m 3 s −1 (equivalent to 0.39 and 0.50 m 3 s −1 km −1 ).…”

“…These data provide evidence that irrigation and SW-GW interactions may explain the observed NO 3 − trends. The diffuse input of NO 3 − to the Oglio River reach was demonstrated with a simulation of the Oglio River water quality by means of the QUAL2Kw model [85]. The modelling of ammonification and nitrification rates was, in fact, not able to explain the increase of NO 3 − concentration along the river reach crossing the spring belt during the irrigation period.…”

Agricultural practices regulate the seasonality of groundwater-river nitrogen exchanges

“…Such percentage is a large overestimation of the real value as it was obtained neglecting all other oxygen-consuming processes, including macrophytes, sh, macroinvertebrates, and the whole heterotrophic microbial community respiration. A comparable nitrate production (~ 80 t N y -1 ) was obtained using the nitri cation rate set by Taherisoudejani et al (2018) in the QUAL2Kw model applied to the Oglio River, a nearby Po River tributary with similar hydrological characteristics. Pinardi et al (2014) found that the processes in the hyporheic zone or the microbial metabolism of carbonate dissolution could explain up to 15% of the DIC increase, including the role of macrophytes in modulating dissolved CO 2 saturation values and xation of C.…”

“…For example, human activities (e.g., crop production) and altered hydrology may in uence the seasonality of N river export (Basu et ) have highlighted the presence of hot-spots within watersheds that represent outliers in N budgets (e.g., with very large N excess or very low N use e ciency). They also emphasized the presence of hot-moments within watersheds, that are speci c periods during which N mass transfer peaks as a combination of decreased uptake, increased runoff or variation of the water table level, resulting in the reactivation of river-groundwater interaction (Rosenzweig et al 2008;Preisendanz et al 2020;Taherisoudejani et al 2018). The analysis of N hot-spots and hot-moments in watersheds require speci c studies, focusing on small spatial and temporal scales.…”