Evaluation of impact of climate changes in the lower Seyhan irrigation project area, Turkey

Evaluation of impact of climate changes in the lower Seyhan irrigation project area, Turkey
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土耳其塞伊汉下游灌溉项目区气候变化影响评估

DOI:
10.1007/978-3-030-01036-2_6
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发表时间:
2018
期刊:
Climate Change Impacts on Basin Agro-ecosystems
影响因子:
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通讯作者:
T. Kume and T. Watanabe
T. Kume and T. Watanabe
中科院分区:
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文献类型:
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作者:
K. Hoshikawa;T. Nagano;T. Kume and T. Watanabe

文献摘要

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本研究通过将预测的未来气候数据纳入作物生长和水文结构的计算模拟中,定量评估了 2070 年代气候变化对土耳其下塞伊汉灌溉项目 (LSIP) 地区灌溉农业的影响。根据耦合模型比对项目第五阶段(CMIP5)注册模型在代表性浓度(RCP)8.5情景下的模拟结果,2081-2100年地中海地区年气温和降水量分别比1986-2005年高4-5℃和少10-20%。为了同时评估对这些因素的影响,使用了基于网格的分布式水文模型 - IMPAM(灌溉管理绩效评估模型)。 IMPAM 包括准三维土壤水动力学、蒸发蒸腾、作物生长、灌溉和渗流以及排水模块,由作者开发,用于模拟灌溉农业区的水文。模拟采用了三种适应气候变化的情景:(a) 无需大量水资源管理投资的适应;(b) 增加灌溉面积;(c) 增加农作物净用水量,减少河流引水量,并为 21,900 公顷果园引入地下水灌溉。本研究中使用的 2070 年代的气候数据是通过使用“伪变暖”方法对 NCEP 再分析数据和两个 GCM(MRI-CGCM2 和 CCSR/NIES-CGCM)的结果进行 RCM(区域气候模型)降尺度而得出的。结果表明,全球变暖对LSIP水文的直接影响可能不足以影响农业生产。海平面上升的影响可能仅限于距海岸线几公里、大田作物面积稀缺的范围。气候变化对大型工业园区农作物种植的影响并不明显大于水资源管理变化的原因是现有的水资源管理,用水量很大,包括损失。即使在塞伊汉河引水量大幅减少的情况下,通过改善过度湿度也给水文条件和作物生长带来了积极影响。实际蒸腾与潜在蒸腾的平均比率(Ta/Tp比)随作物水分胁迫的增加而减小,随着适应情景和预测气候的组合而变化,从0.81到0.89不等,而基于当前管理的所有模拟都得到几乎相同的Ta/Tp比,即0.86。这些事实表明,水资源管理变化对大型工业园区水平衡和农业生产的影响远大于气候变化的直接影响。
This study quantitatively assesses the impacts of climate change on the irrigated agriculture of the Lower Seyhan Irrigation Project (LSIP) area in Turkey in the 2070s by factoring the projected future climate data into computational simulations of crop growth and the hydrological structure. According to simulation results by models registered to Coupled Model Intercomparison Project Phase 5 (CMIP5) with the representative concentration (RCP) 8.5 scenario, annual temperatures and precipitation around the Mediterranean region in 2081–2100 are, respectively, 4–5 °C higher and 10–20% smaller than those in 1986–2005. To assess the effects on these factors at the same time, a grid-based distributed hydrological model – IMPAM (Irrigation Management Performance Assessment Model) – was used. IMPAM, which includes modules for quasi three-dimensional soil-water dynamics, evapo-transpiration, crop-growth, irrigation and seepage, and drainage was developed by the authors for the simulation of the hydrology in irrigated agricultural areas. Three scenarios of adaptation to climate change were employed for the simulations: (a) adaptation without a large amount of investment for water management, (b) increasing the irrigation area, and (c) increasing the net amount of water applied to crops with decreasing water diversion from the river and the introduction of groundwater irrigation for 21,900 ha of orchards. Climate data for the 2070s that was used in this study was derived through RCM (Regional Climate Model) downscaling of the NCEP-reanalysis data and results of two GCMs (MRI-CGCM2 and CCSR/NIES-CGCM) with the “pseudo warming” method. The results revealed that the direct effect of global warming on the hydrology of the LSIP may not be large enough to affect agricultural production. The effect of the sea-level rise might be limited to the range of a few kilometres from the coastline with scarce field crop areas. The reason why the effect of climate change on crop cultivation in the LSIP is not significantly larger than changes in water management is the existing water management, with plentiful water application, including losses. Even the scenarios with large decreases in water diversion from the Seyhan River brought positive effects to hydrological conditions and crop growth through the improvement of over-humidity. The average ratio of actual transpiration to potential transpiration (Ta/Tp ratio), which decreases as water stress on crops increases, varies from 0.81 to 0.89 with combinations of adaptation scenarios and projected climate, while all simulations based on the current management resulted in almost the same Ta/Tp ratio, 0.86. These facts indicate that the effects of changes in water management are much greater than the direct effects of climate change with regard to water balance and agricultural production in the LSIP.