Effects of climate change on corn: numerical simulation of soil water dynamics in a corn crop in Illinois (USA)

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Ferreira, Nicole Costa Resende
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.teses.usp.br/teses/disponiveis/11/11152/tde-16032018-123509/
Resumo: Given the importance of climate conditions in the agricultural environment, more specifically in the transport of water in the soil, there is a need to understand the effects of climate change on the water dynamics in the soil. This influence of climate conditions in the agricultural environment seems to be important in evapotranspiration, water availability for plants and roots, and for other processes. Many theoretical models have been developed to characterize the physical processes involved in water and transport. Climate prediction models such as the suite of models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) make it possible generate climate data that can be used to characterize physical and biological processes. This research focuses on two main aspects: 1) the effects of climate change on the occurrence of extreme events that may affect agricultural processes in the region of Urbana-Champaign, in Illinois (USA) and 2) the effects of climate change on the dynamic of soil water in a corn crop (two fields, ANW and ASW) in the studied area. To explore the impacts of climate change on the occurrence of extreme events, the errors of some climate models from CMIP5 were evaluated and the models were subsequently used to develop indices to represent the occurrence of extreme events. These indices were calculated from observed data, and historical and future simulations, considering pessimistic and optimistic scenarios of climate change. The model that best represents the climate in the region was used to provide input data for Hydrus simulation of the soil water dynamics in two fields with different drainage system layout. These simulations with the Hydrus model were made for current conditions and for near term, midcentury, and end of century time periods (2011-2040, 2041-2070, 2071-2100, respectively). The results indicate that the variation of precipitation in the future may result in increased in one (RX1DAY) and five days (RX5DAY) maximum precipitation, and in the number of consecutive dry days (CDD) and consecutive wet days (CWD). Changes in temperature will be reflected as an increase of the indices of maximum and minimum values of temperatures and summer days (TNn, TNx, TXn, TXx and SU); and decreasing of the index of icing and frost days (ID, FD). This increasing of temperatures will represent a risk for agriculture, due to increased evapotranspiration, which will increase crop water demand and can create a hydric stress. Results of Hydrus simulations of surface flux, cumulative surface flux, runoff, cumulative runoff, soil water storage and cumulative infiltration, with input data from the IPSL model, are presented. These variables are critical in a corn crop, and are dependent on climate variables, soil conditions, parameters of the study region, drainage system, crop characteristics, inter alia. The ANW field had lower values of surface flux and cumulative surface flux comparing to the ASW field. This results is indicative that the risk associated with the ASW drainage system layout is higher than that of the ANW drainage system layout, related to the wider spacing between drains and the difficulty in removing water at the required rate. In general, the maximum and average values of surface flux and cumulative surface flux, will increase over time. In addition, it is noticeable that all Hydrus simulation indicates increasing maximum surface runoff and cumulative surface runoff over time. Percentile changes in average runoff and cumulative runoff are dependent on the period simulated. Increases range from 5.61 to 24.4% in the short term (2011-2040), 16.45 to 39.32% in the medium term (2041-2070) and 3.32 to 19.98% in the long term (2071-2100) compared to historical simulation. The maximum values of infiltration tend to be higher in all simulations when compared to the reference period in both fields. Changes in cumulative infiltration are indicative that infiltration will increase in the future. With respect to the correlation between runoff and extreme events, all simulations showed that the correlation between runoff and extreme precipitation events (RX1DAY ranges between 0.76 and 0.78, and RX5DAY ranges between 0.5 and 0.66), are higher than the correlation between runoff and precipitation (ranges between 0.31 and 0.43). This approach can improve the understanding of climate changes impacts on sustainable groundwater management based on adaptive management. Information gained in this work can be used to design monitoring systems to manage a sustainable groundwater in future climate regimes and create mitigation measures to prevent any risk for food security. An implication of the study is that the impact of climate change on water resources is a function of the projection scenario. The study was limited by the use of daily time step, necessitated by the large data sets.