Abstract: HERMES is a widely used agricultural system model; however, it has never been tested for simulating N loss to subsurface drainage. Here, we integrated a simple drain flbw component into HERMES. We then compared the predictions to four years of data (2002-2005) from central Iowa fields in corn-oybean with winter rye as a cover crop (CC) and without winter rye (NCC). We also compared the HERMES predictions to the more complex Root Zone Water Quality Model (RZWQM) predictions for the same dataset. The average annual observed and simulated N loss to drain flow were 43.8 and 44.4 kg N/ha (NCC) and 17.6 and 18.9 kg N/ha (CC). The slightly over predicted N loss for CC was because of over predicted nitrate concentration, which may be partly caused by slightly under predicted average annual rye shoot N (observed and simulated values were 47.8 and 46.0 kg N/ha). Also, recent research from the site suggests that the soil field capacity may be greater in CC while we used the same soil parameters for both treatments. A local sensitivity analysis suggests that increased field capacity affects HERMES simulations, which includes reduced drain flow nitrate concentrations, increased denitrification, and reduced drain flow volume. HERMES-simulated cumulative monthly drain flow and annual drain flow were reasonable compared to field data and HERMES performance was comparable to other published drainage model tests. Unlike the RZWQM simulations, however, the modified HERMES did riot accurately simulate the year to year variability in nitrate concentration difference between NCC and CC, possibly due in part to the lack of partial mixing and displacement of the soil solution. The results suggest that 1) the relatively simple model HERMES is a promising tool to estimate annual N loss to drain flow under corn-soybean rotations with winter rye as a cover crop and 2) soil field capacity is a critical parameter to investigate to more thoroughly understand and appropriately model denitrification and N losses to subsurface drainage. Published by Elsevier B.V.

Abstract: Exploitation of alternative water sources is expected to grow in the decades to come in water-stressed countries with fast population growth, especially in regions where a further decline of natural freshwater availability is expected due to climate change. Increasing utilization of non-freshwater usually leads to salinity build-up in fields and water sources as well as accumulation of various pollutants — both having a considerable impact on the suitability of non-freshwater for irrigation due to constraints associated with crop salinity tolerance and food safety regulations. We developed a linked Computable General Equilibrium (CGE) — farm-level model of a water economy with representation for multiple water types characterized by different qualities. We employ the model to assess the impact of water shortage on the Israeli economy, where steadily growing water scarcity leads to an increasing utilization of alternative water sources. We simulate water shortage scenarios based on the Long Term National Master Plan for The Water Economy developed by the Israeli Water Authority (IWA). The linked CGE — farm-level model provides a mechanism for estimating the Constant Elasticity of Substitution (CES) rates between different irrigation water types used in agriculture. This mechanism accounts for the effects of salinity on yields and takes into consideration food safety regulations for irrigating crops with treated wastewater. We demonstrate that, in contrast to previous studies, CES rates between different water types are not identical. The CES rates obtained in our study have relatively low values, which can be attributed to the constraints associated with crop salinity tolerance and food safety regulations. Our results reveal that water shortage can lead to a significant decline of Israel’s GDP, where a considerable part of the decline is attributed to the decrease in agricultural outputs. The magnitude of the impact depends on the underlying assumptions regarding future desalination capacity. To further study the effect of desalination, we run simulations under various desalination levels and examine its impact on the GDP. We also examine the extent to which the impact of water shortage is sensitive to CES rates between different irrigation water types.

Abstract: Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.