Impacts of climate change on hydrology,water quality and crop productivity in the Ohio-Tennessee River Basin

Nonpoint source pollution from agriculture is the main source of nitrogen and phosphorus in the stream systems of the Corn Belt region in the Midwestern US.The eastern part of this region is comprised of the Ohio-Tennessee River Basin(OTRB),which is considered a key contributing area for water pollution and the Northern Gulf of Mexico hypoxic zone.A point of crucial importance in this basin is therefore how intensive corn-based cropping systems for food and fuel production can be sustainable and coexist with a healthy water environment,not only under existing climate but also under climate change conditions in the future.To address this issue,a OTRB integrated modeling system has been built with a greatly refined 12-digit subbasin structure based on the Soil and Water Assessment Tool(SWAT)water quality model,which is capable of estimating landscape and in-stream water and pollutant yields in response to a wide array of alternative cropping and/or management strategies and climatic conditions.The effects of three agricultural management scenarios on crop production and pollutant loads exported from the crop land of the OTRB to streams and rivers were evaluated:(1)expansion of continuous corn across the entire basin,(2)adoption of no-till on all corn and soybean fields in the region,(3)implementation of a winter cover crop within the baseline rotations.The effects of each management scenario were evaluated both for current climate and projected mid-century(2046-2065)climates from seven global circulation models(GCMs).In both present and future climates each management scenario resulted in reduced erosion and nutrient loadings to surface water bodies compared to the baseline agricultural management,with cover crops causing the highest water pollution reduction.Corn and soybean yields in the region were negligibly influenced from the agricultural management scenarios.On the other hand,both water quality and crop yield numbers under climate change deviated considerably for all seven GCMs compared to the baseline climate.Future climates from all GCMs led to decreased corn and soybean yields by up to 20%on a mean annual basis,while water quality alterations were either positive or negative depending on the GCM.The study highlights the loss of productivity in the eastern Corn Belt under climate change,the need to consider a range of GCMs when assessing impacts of climate change,and the value of SWAT as a tool to analyze the effects of climate change on parameters of interest at the basin scale.

Code modernization and modularization of APEX and SWAT watershed simulation models

SWAT(Soil and Water Assessment Tool)and APEX(Agricultural Policy/Environmental eXtender)are respectively large and small watershed simulation models derived from EPIC(Environmental Policy Integrated Climate),a field-scale agroecology simulation model.All three models are coded in Fortran and have evolved over several decades.They are widely used to analyze anthropogenic influences on soil and water quality and quantity.Much of the original Fortran code has been retained even though Fortran has been through several cycles of development.Fortran now provides functionality originally restricted to languages like C,designed to communicate directly with the operating system and hardware.One can now use an object-oriented style of programming in Fortran,including inheritance,run-time polymorphism and overloading.In order to enhance their utility in research and policy-making,the models are undergoing a major revision to use some of the new Fortran features.With these new programming paradigms the developers of SWAT,APEX,and EPIC are working to make communication between the two models seamless.This paper describes the ongoing revision of these models that will make them easier to use,maintain,modify and document.It is intended that they will converge as they continue to evolution,while maintaining their distinctive features,capabilities and identities.

Simulation of rice paddy systems in SWAT:A review of previous applications and proposed SWAT+rice paddy module

The Soil and Water Assessment Tool(SWAT)is an ecohydrological watershed-scale model which was initially developed in the early 1990s to simulate the impacts of land use,management systems,and climate on hydrology and/or water quality.First adopted in the U.S.,the use of the model then spread to Europe and then later to Asia and other regions.The range of applications that SWAT has been applied to have also expanded dramatically,which influenced ongoing model development which has been virtually continuous over the past two decades.A key component of many SWAT applications in Asia is accounting for rice paddy production that is common in some subregions within the continent.However,most of these studies do not provide explicit details of how rice production was simulated in SWAT.Other research has revealed that significant problems occur when trying to represent rice paddy systems in standard versions of SWAT,due to limitations in algorithms based on the runoff curve number approach or the pothole option.In response,key modifications have been made to SWAT in recent studies that have resulted in more accurate representation of rice paddy systems.These developments point to the need for the incorporation of an enhanced rice paddy module within SWAT to better capture rice paddy hydrological and pollutant dynamics,which would support improved use of the model in Asia and other rice production regions.Subtopics related to simulating rice production in SWAT are discussed as follows:1)an overview of global rice production;2)history of SWAT development;3)typical approaches for simulating rice production;4)problems associated with the typical approaches;5)recent code modifications to address deficiencies in replicating rice paddy systems;6)recommendations for developing a standard rice paddy module for future SWAT codes.

Evaluation of alternative surface runoff accounting procedures using SWAT model

For surface runoff estimation in the Soil and Water Assessment Tool(SWAT)model,the curve number(CN)procedure is commonly adopted to calculate surface runoff by dynamically updating CN values based on antecedent soil moisture condition(SCSI)in field.From SWAT2005 and onward,an alternative approach has become available to apply the CN method by relating the runoff potential to daily evapotranspiration(SCSII).While improved runoff prediction with SCSII has been reported in several case studies,few investigations have been made on its influence to water quality output or on the model uncertainty associated with the SCSII method.The objectives of the research were:(1)to quantify the improvements in hydrologic and water quality predictions obtained through different surface runoff estimation techniques;and(2)to examine how model uncertainty is affected by combining different surface runoff estimation techniques within SWAT using Bayesian model averaging(BMA).Applications of BMA provide an alternative approach to investigate the nature of structural uncertainty associated with both CN methods.Results showed that SCSII and BMA associated approaches exhibit improved performance in both discharge and total NO3 predictions compared to SCSI.In addition,the application of BMA has a positive effect on finding well performed solutions in the multi-dimensional parameter space,but the predictive uncertainty is not evidently reduced or enhanced.Therefore,we recommend additional future SWAT calibration/validation research with an emphasis on the impact of SCSII on the prediction of other pollutants.