Conference Agenda

Rice production in the Guadalquivir River rice-growing area (Spain) relies on flood irrigation and is exposed to high salinity levels in the pumped water. This study aimed to link water-quality monitoring with rice yield response and to enable district-scale assessment of salinity-driven losses by converting available chloride concentration data (Cl−) to electrical conductivity (EC), calibrating local yield–salinity parameters, and applying the locally calibrated yield function to the district with a circulation water and solute mass-balance model previously developed.

Paired Cl− and EC measurements from a monitoring network were used to fit a proportional relationship (Cl− = a·EC). Farm-scale yield records were related to salinity expressed as EC using the Maas and Hoffman threshold model: 100·Y/Ymax = 100 − Bs·(EC − ECu), where Y and Ymax are the yield and maximum yield, ECu is the salinity threshold, and Bs is the slope of yield loss beyond the threshold.

Monitoring confirmed a stable proportionality of Cl− with EC. Yields declined linearly above the threshold and parameters ECu and Bs were fitted. Finally, a yield-loss module was coupled to the existent mass-balance model to quantify production losses driven by salinity and to benchmark differences in yield loss among scenarios.

This study focuses on the microbiological monitoring of water quality in the rice agroecosystem of the Lower Mondego Valley,, aiming to assess the impact of rice cultivation activities on the quality of water drained into the environment. Water samples were collected from irrigation and drainage networks of paddies. Microbiological quality indicators assessed included total coliforms (TC), fecal coliforms (FC), fecal enterococci (FE), and ampicillin-resistant Enterobacteriaceae (E-Ampr), using standardized analytical methods. Antibiograms were performed directly on the isolates in mixed culture, using direct antimicrobial susceptibility tests, to determine the phenotypes resistant to 13 antibiotics, representing the main classes used in human medicine and livestock production. Results revealed that irrigation water across the monitored plots exhibited a high microbial load. Notably, the rice agroecosystem exerted a beneficial effect on the microbial quality of drainage water, with observed reductions of approximately two orders of magnitude in TC, FC, and FE counts from the inlet to the outlet of the rice fields. However, E-Ampr counts increased in the paddy soil, likely due to the specific characteristics of the wetland ecosystem and the influence of local wildlife activity. This study highlights the positive role of rice agroecosystems in reducing microbial loads in drainage water.