Plant growth, water quality, carbon, and nutrient flows in rural-urban cropping systems at different spatial scales

不同空间尺度城乡耕作系统中的植物生长、水质、碳和养分流

• 批准号: 289780390
• 负责人: Professor Dr. Andreas Bürkert
• 金额: --
• 依托单位: University of Agricultural Sciences (UASB)
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/289780390?language=en
• 关键词: Plant; growth; water; quality; carbon

Scarcity of land, water, and labour are the main constraints to agricultural production along the rural-urban interface of Bangalore. This has led to the widespread replacement of diverse dryland farming systems by intensive irrigated vegetable production on open lands at the city fringe and in scattered city areas. The consequences of such changes in traditional Indian farming systems on the nutrient dynamics and soil fertility are largely unknown. This project therefore addresses transformation-related changes in the intensity of agricultural production systems at the micro(plot)- and meso-scale (field and household) by analysing horizontal and vertical flows of nutrients and carbon in field and laboratory experiments, turnover of soil organic carbon and soil nitrogen in different pools, and their effects on nutrient and water use efficiency under rainfed and irrigated conditions on-station and on 72 selected farmer fields. It combines expertise in agronomy, plant nutrition and non-destructive measurements of soil physical properties and plant growth (Bürkert) with modelling of water dynamics, crop growth, and carbon (C) and nutrient fluxes (Ludwig). The project will contribute to the overall goals of FOR2432 by providing spatially explicit data on the effects of intensification-related land use changes on nutrient and water use efficiencies for major food crops in the study region. It also aims at assessing the impact of these changes on key chemical soil parameters (pools of C and nitrogen N, phosphorus P, potassium K, and sulphur S) that govern crop output and ecosystem services. It thereby provides data for the calibration and validation of models to predict medium- and long-term changes of key soil parameters determining crop productivity and ESS. To this end we will investigate the plant uptake and turnover of C and N, P, K, and S including gaseous (N2O, NH3, CO2) and leaching losses (NO3-, dissolved organic carbon, organic P, and SO4[2-]), by photo-acoustic spectroscopy, gas chromatography, and resin cartridges /micro-lysimeters, respectively, and relate them to the soil hydrological data of A02 and the multi-spectral cropping / land use signatures of C01 and C02. Using 15N in the central experiment will allow to determine the fate of added fertilizer N. The data will also be used to parameterize the DNDC model. High resolution aerial photography and multispectral canopy scanning from hexacopters will be used to non-destructively monitor, in cooperation with C01, plant growth in the on-station experiments and the spatial variability of final biomass on-farm and to collect high resolution, low altitude multispectral crop signature data. Thereby this project will contribute to the estimation of the current productive value of agricultural lands which partly explain a decisions of farmers to intensify crop production or give up land for urban development.

土地、水和劳动力的稀缺是沿着班加罗尔城乡交界处农业生产的主要制约因素。这导致在城市边缘和分散的城市地区的开阔地上进行密集的灌溉蔬菜生产，广泛取代了各种旱地耕作制度。印度传统耕作制度的这种变化对养分动态和土壤肥力的影响在很大程度上是未知的。因此，本项目在微观（地块）和中观尺度上探讨农业生产系统强度的转型相关变化（田间和家庭）通过分析田间和实验室试验中养分和碳的水平和垂直流动，不同库中土壤有机碳和土壤氮的周转，以及它们对站上和72个选定的农民农田的灌溉和灌溉条件下养分和水分利用效率的影响。它结合了农学、植物营养和土壤物理性质和植物生长的非破坏性测量（Bürkert）的专业知识，以及水动力学、作物生长、碳（C）和养分通量（Ludwig）的建模。该项目将有助于FOR 2432的总体目标，通过提供空间上明确的数据，集约化相关的土地利用变化的影响，养分和水的利用效率的主要粮食作物在研究区域。它还旨在评估这些变化对控制作物产量和生态系统服务的关键化学土壤参数（C和氮N，磷P，钾K和硫S）的影响。因此，它为模型的校准和验证提供了数据，以预测决定作物生产力和ESS的关键土壤参数的中长期变化。为此，我们将研究植物对C和N，P，K和S的吸收和周转，包括气体（N2 O，NH3，CO2）和淋失（NO3-、溶解有机碳、有机磷和SO 4 [2-]），分别通过光声光谱、气相色谱和树脂筒/微蒸渗仪测定，并将它们与A02的土壤水文数据和C 01和C 02的多光谱作物/土地利用特征相关联。在中心实验中使用15 N将允许确定添加的肥料N的去向。这些数据还将用于DNDC模型的参数化。将与C 01合作，利用六旋翼飞行器的高分辨率航空摄影和多光谱冠层扫描，对实地试验中的植物生长和农场最终生物量的空间变异性进行非破坏性监测，并收集高分辨率、低空多光谱作物特征数据。因此，本项目将有助于估计农业用地的当前生产价值，这部分解释了农民决定加强作物生产或放弃土地用于城市发展的原因。