Conference Agenda

This study presents a methodologically rigorous cost-benefit analysis of Precision Agriculture (PA) and Enhanced Efficiency Fertilizers (EEF) in the Želivka catchment, Czech Republic, serving 1.3 million people. We develop a dynamic probabilistic framework combining high-resolution LPIS field data (52,845 hectares across 729 farms), SWAT+ hydrological modeling outputs for nitrogen transport pathways, and recently derived health cost valuations (EUR 7.25 per mg/L per capita) with biophysical effectiveness parameters from meta-analysis of 403 field experiments. The heterogeneous agent adoption model accounts for farm size distribution, risk aversion, and learning costs, calibrated using Czech agricultural structure. Monte Carlo simulation (10,000 iterations) propagates uncertainty across all key parameters over a 10-year horizon at 3.38% social discount rate. The analysis reveals that indirect public health benefits dramatically outweigh direct private costs and benefits: while farmers gain EUR 23.7 million from yield improvements, society captures EUR 99.6 million in avoided health costs from reduced nitrate exposure. Technology adoption reaches 44.7% (PA) and 7.3% (EEF) by Year 10, reducing nitrogen loads by 65,843 kg annually and decreasing reservoir nitrate concentration by 2.96 mg/L. Sensitivity analysis confirms that SWAT-calibrated nitrogen transport parameters and health cost valuation drive results more than technology costs, highlighting the critical importance of proper externality valuation in agricultural environmental policy design.