Building a climate resilient farm: A risk based approach for understanding water, energy and emissions in irrigated agriculture

The links between water application, energy consumption and emissions are complex in irrigated agriculture. There is a need to ensure that water and energy use is closely considered in future industry planning and development to provide practical options for adaptation and to build resilience at the farm level. There is currently limited data available regarding the uncertainty and sensitivity associated with water application and energy consumption in irrigated crop production in Australia. This paper examines water application and energy consumption relationships for different irrigation systems, and the ways in which the uncertainty of different parameters impacts on these relationships and associated emissions for actual farms. This analysis was undertaken by examining the current water and energy patterns of crop production at actual farms in two irrigated areas of Australia (one using surface water and the other groundwater), and then modelling the risk/uncertainty and sensitivity associated with the link between water and energy consumption at the farm scale. Results showed that conversions from gravity to pressurised irrigation methods reduced water application, but there was a simultaneous increase in energy consumption in surface irrigation areas. In groundwater irrigated areas, the opposite is true; the use of pressurised irrigation methods can reduce water application and energy consumption by enhancing water use efficiency. Risk and uncertainty analysis quantified the range of water and energy use that might be expected for a given irrigation method for each farm. Sensitivity analysis revealed the contribution of climatic (evapotranspiration and rainfall) and technical factors (irrigation system efficiency, pump efficiency, suction and discharge head) impacting the uncertainty and the model output and water-energy system performance in general. Flood irrigation systems were generally associated with greater uncertainty than pressurised systems. To enhance resilience at the farm level, the optimum situation envisaged an irrigation system that minimises water and energy consumption and greenhouse gas emissions. Where surface water is used, well designed and managed flood irrigation systems will minimise the operating energy and carbon equivalent emissions. Where groundwater is the dominant use, the optimum system is a well designed and managed pressurised system operating at the lowest discharge pressure possible that will still allow for efficient irrigation. The findings might be useful for farm level risk mitigation strategies in surface and groundwater systems, and for aiding adaptation to climate change.     

The impacts of climate change on livestock and livestock systems in developing countries: A review of what we know and what we need to know

Despite the importance of livestock to poor people and the magnitude of the changes that are likely to befall livestock systems, the intersection of climate change and livestock in developing countries is a relatively neglected research area. Little is known about the interactions of climate and increasing climate variability with other drivers of change in livestock systems and in broader development trends. In many places in the tropics and subtropics, livestock systems are changing rapidly, and the spatial heterogeneity of household response to change may be very large. While opportunities may exist for some households to take advantage of more conducive rangeland and cropping conditions, for example, the changes projected will pose serious problems for many other households. We briefly review the literature on climate change impacts on livestock and livestock systems in developing countries, and identify some key knowledge and data gaps. We also list some of the broad researchable issues associated with how smallholders and pastoralists might respond to climate change. The agendas of research and development organisations may need adjustment if the needs of vulnerable livestock keepers in the coming decades are to be met effectively.     

基于RS和GIS的土地利用/覆被变化及其功能转型特征分析——以新疆叶城县为例#br#

以土地利用遥感影像数据解译的基础及相关遥感技术支持,将土地利用类型分为6大类型的LUCC数据源,通过选取土地利用动态度与土地利用程度指数,结合采用土地利用程度和转移矩阵模型,对新疆喀什地区叶城县近15年的土地利用/覆被变化及其功能演变进行综合分析。研究结果表明：2005—2020年期间叶城县的草地、耕地、水域面积及建设用地整体呈现增长的趋势,分别增加421.21 km2、181.25 km2、120.49 km2、7.37 km2,沙地、冰川及永久积雪、林地及其他未利用地面积在不断减少,分别减少 320.58 km2、303.92 km2、61.16 km2、43.21 km2;土地利用程度方面,在近15年研究区的土地利用程度呈现上涨,表明土地利用正处于发展期,尤其是2010—2015年期间土地利用程度指数与其他时期相比较高;由土地利用转移矩阵可知：研究区主要转入土地类型为耕地、草地、建设用地、水域等,土地面积都呈现一定幅度的增加,而林地、沙地、冰川及永久积雪和其他未利用地的面积都有所减少;在研究期间,土地利用功能类型中生态生产用地增加幅度最大,增加480.92 km2,其次是生产生态用地排列第二,为181.02 km2,而生态容纳用地呈现减少趋势,减少667.82 km2,说明叶城县土地利用功能类型的变化受到人为影响较大。研究结果可为新疆叶城县土地资源的可持续利用,科学管理和生态规划提供依据。     

Water and salt balance at irrigation scheme scale: A comprehensive approach for salinity assessment in a Saharan oasis

Salt balance methods are generally applied in the root-zone and at local scales but do not provide relevant information for salinity management at irrigation scheme scales, where there are methodological impediments. A simple salt balance model was developed at irrigation scheme and yearly time scales and applied in Fatnassa oasis (Nefzaoua, Tunisia). It accounts for input by irrigation, export by drainage and groundwater flow, and provides novel computation of the influence of biogeochemical processes and variations in the resident amount of salt for each chemical component in the soil and shallow groundwater. Impediments were overcome by limiting the depth of the system so that the resident amount of salt that remained was of the same order of magnitude as salt inputs and allowed indirect and reliable estimation of groundwater flow. Sensitivity analyses as partial derivatives of groundwater salinity were carried out according to non-reactive salt balance under steady-state assumption. These analyses enabled the magnitude of the salinization process to be foreseen as a function of hydrological changes linked to irrigation, drainage, groundwater flow and extension of the irrigated area. From a salt input of 39 Mg ha⁻¹ year⁻¹ by irrigation, 21 Mg ha⁻¹ year⁻¹ (54%) and 10 Mg ha⁻¹ year⁻¹ (26%) were exported by groundwater flow and drainage, respectively. 7 Mg ha⁻¹ year⁻¹ (18%) were removed from groundwater by geochemical processes, while a non-significant 2 Mg ha⁻¹ year⁻¹ were estimated to have been stored in the soil and shallow groundwater where the residence time was only 2.7 years. The leaching efficiency of drainage was estimated at 0.77. With a water supply of 1360 mm by irrigation and 90 mm by rainfall, drainage, groundwater flow and actual evapotranspiration were 130, 230, and 1090 mm, respectively. The current extension of date palm plantations and salinization of groundwater resources are expected to significantly increase the salinity hazard while the degradation of the drainage system is expected to be of lesser impact. The approach was successfully implemented in Fatnassa oasis and proved to be particularly relevant in small or medium irrigation schemes where groundwater fluxes are significant.     

Assessment of irrigation and environmental quality at the hydrological basin level: II. Salt and nitrate loads in irrigation return flows

Irrigation return flows may induce salt and nitrate pollution of receiving water bodies. The objectives of this study were to perform a salt and nitrogen mass balance at the hydrological basin level and to quantify the salt and nitrate loads exported in the drainage waters of three basins located in a 15,500 ha irrigation district of the Ebro River Basin (Spain). The main salt and nitrogen inputs and outputs were measured or estimated in these basins along the 2001 hydrological year. Groundwater inflows in the three basins and groundwater outflow in one basin were significant components of the measured mass balances. Thus, the off-site impact ascribed solely to irrigation in these basins was estimated in the soil drainage water. Salt concentrations in soil drainage were low (TDS of around 400–700 mg/l, depending on basins) due to the low TDS of irrigation water and the low presence of salts in the geologic materials, and were inversely related to the drainage fractions (DF = 37–57%). However, due to these high DF, salt loads in soil drainage were relatively high (between 3.4 and 4.7 Mg/ha), although moderate compared to other areas with more saline geological materials. Nitrate concentrations and nitrogen loads in soil drainage were highest (77 mg NO₃⁻/l and 195 kg N/ha) in basin III, heavily fertilized (357 kg N/ha), with the highest percentage of corn and with shallow, low water retention flood-irrigated soils. In contrast, the lowest nitrate concentrations and nitrogen loads (21 mg NO₃⁻/l and 23 kg N/ha) were found in basin II, fertilized with 203 kg N/ha and preponderant in deep, alluvial valley soils, crops with low N requirements (alfalfa and pasture), the highest non-cropped area (26% of total) and with fertigation practices in the sprinkler-irrigated fields (36% of the irrigated area). Thus, 56% of the N applied by fertilization was lost in soil drainage in basin III, as compared to only 16% in basin II. In summary, a low irrigation efficiency coupled to an inadequate management of nitrogen fertilization are responsible for the low-salt, high-nitrate concentrations in soil and surface drainage outflows from the studied basins. In consequence, higher irrigation efficiencies, optimized nitrogen fertilization and the reuse for irrigation of the low-salt, high-nitrate drainage waters are key management strategies for a better control of the off-site pollution from the studied irrigation district.     

Evaluation of the water use efficiency of alternative farm practices at a range of spatial and temporal scales: A conceptual framework and a modelling approach

Water is the principal limiting resource in Australian broadacre farming, and the efficiency with which farmers use water to produce various products is a major determinant both of farm profit and of a range of natural resource management (NRM) outcomes. We propose a conceptual framework based on multiple water use efficiencies (WUEs) that can be used to gain insight into high-level comparisons of the productivity and sustainability of alternative farming practices across temporal and spatial scales. The framework is intended as a data aggregation and presentation device. It treats flows of water, biomass and money in a mixed farming system; economic inefficiencies in these flows are tracked as they are associated with a range of NRM indicators.We illustrate the use of the framework, and its place in a larger research programme, by employing it to synthesise the results from a set of modelling analyses of the effect of land use choices on long-term productivity and a range of NRM indicators (frequency of low ground cover, deep drainage, N leaching rates and rate of change in surface soil organic carbon). The analyses span scales from single paddocks and years to whole farms and have been carried out with the APSIM and GRAZPLAN biophysical simulation models and the MIDAS whole-farm economic model.In single wheat crops in one study, different land uses in preceding years affect grain yield primarily by affecting the harvest index. When the scale changes to cropping rotations, the critical factor affecting overall water use efficiency is found to be the proportion of stored soil water that is transpired by crops. When ordinated in terms of their water use efficiencies, a set of 45 modelled rotation sequences at another location are differentiated mainly by the proportion of pasture in the rotation; when rotations are ordinated using key NRM indicators, the proportion of lucerne pasture is the main distinguishing factor. Finally, we show that for whole crop-livestock farms at three different locations across southern Australia, the pattern of water use efficiencies in the most profitable farming systems changes in similar ways as cropping proportion is altered. At this scale, land use choices affect multiple water use efficiency indices simultaneously and commodity prices determine the balance of the resulting economic tradeoffs.Limitations to the use of the WUE framework arising from its relative simplicity are discussed, as are other areas of farming systems research and development to which it can be applied.     

InfoCrop: A dynamic simulation model for the assessment of crop yields,losses due to pests,and environmental impact of agro-ecosystems in tropical environments. II. Performance of the model

InfoCrop, a generic crop model, simulates the effects of weather, soils, agronomic management (planting, nitrogen, residues and irrigation) and major pests on crop growth, yield, soil carbon, nitrogen and water, and greenhouse gas emissions. This paper presents results of its evaluation in terms of its validation for rice and wheat crops in contrasting agro-environments of tropics, sensitivity to the key inputs, and also illustrates two typical applications of the model. Eleven diverse field experiments, having treatments of location, seasons, varieties, nitrogen management, organic matter, irrigation, and multiple pest incidences were used for validation. Grain yields in these experiments varied from 2.8 to 7.2 ton ha⁻¹ in rice and from 3.6 to 5.5 ton ha⁻¹ in wheat. The results indicated that the model was generally able to explain the differences in biomass, grain yield, emissions of carbon dioxide, methane and nitrous oxides, and long-term trends in soil organic carbon, in diverse agro-environments. The losses in dry matter and grain yield due to different pests and their populations were also explained satisfactorily. There were some discrepancies in the simulated emission of these gases during first few days after sowing/transplanting possibly because of the absence of tillage effects in the model. The sensitivity of the model to change in ambient temperature, crop duration and pest incidence was similar to the available field knowledge. The application of the model to quantify multiple pests damage through iso-loss curves is demonstrated. Another application illustrated is the use of InfoCrop for analyzing the trade-offs between increasing crop production, agronomic management strategies, and their global warming potential.     

InfoCrop: A dynamic simulation model for the assessment of crop yields,losses due to pests,and environmental impact of agro-ecosystems in tropical environments. I. Model description

The problems of agriculture in many tropical countries are gradually becoming more intense due to increasing food demand led by population growth, stagnation in farm productivity, mounting yield losses due to multiple pests, increasing vulnerability to global environmental changes and the need to reduce emission of greenhouse gases. Tools and techniques are needed to assist in developing strategies that can lead to higher food production, prevent crop production losses, and ensure minimal greenhouse gas emissions while maintaining soil fertility. Several dynamic models have been developed in recent past but most of these are generally strong either in soils and crops, or in greenhouse gases (GHG) emissions. Pest induced yield losses, a critical issue in the tropics, is not addressed in most models. InfoCrop, a generic dynamic crop model, has been developed to meet these specific requirements. It provides integrated assessment of the effect of weather, variety, pests, soil and management practices on crop growth and yield, as well as on soil nitrogen and organic carbon dynamics in aerobic as well as anaerobic conditions, and greenhouse gas emissions. The model considers the key processes related to crop growth, effects of water deficit, flooding, nitrogen management, temperature and frost stresses, crop–pest interactions, soil water and nitrogen balance and (soil) organic carbon dynamics. Its general structure relating to basic crop growth and yield is largely based on several earlier models, especially SUCROS series, and is written in Fortran Simulation Environment (FSE) programming language. The model has been validated for dry matter and grain yields of several annual crops, losses due to multiple diseases and pests, and emissions of carbon dioxide, methane and nitrous oxide in a variety of agro-environments. To increase the applications of model in research and development, an extremely simple menu driven version of InfoCrop has also been developed. The users of this version do not need any background in programming.