Global-scale vs. regional-scale scenario assumptions: implications for estimating future water withdrawals in the Elbe River basin

In this paper, we explore how scenarios of future water withdrawals in a river basin are influenced by scale-dependent quantifications of the driving forces for two global-scale storylines. Either global-scale information or region-specific information is used to do the quantifications. In addition, we analyze the impact of including or not some restricted regional-scale information in the employed water use model. To develop scenarios of water withdrawals in the German part of the Elbe River basin, we applied the modules for domestic, thermoelectric power and manufacturing water use of the global water model WaterGAP, using scale-dependent driving forces scenarios and other scale-dependent model input. In the global-scale quantitative interpretations of the storylines of the IPCC SRES scenarios A1 and B2, all major driving forces of water withdrawals in the basin—population, thermoelectric power production and industrial gross domestic product—show vigorous increases between 2000 and 2025, while from the regional perspective, smaller increases but mostly decreases appear to be plausible. These discrepancies are partly due to the fact that for the global-scale interpretations only the historic developments until 1990 were taken into account, and not until 2000 as in the regional case. The resulting scenarios of sectoral water withdrawals in 2025 differ strongly between the two scale-dependent interpretations of the storylines, with the global one leading to much higher absolute water withdrawals and much lower withdrawal decreases between 2000 and 2025. Therefore, for regional assessments of water withdrawals, we recommend to embed the scenario analysis in global-scale storylines by performing regional-scale quantifications of the global qualitative driving forces scenarios, based on a limited amount of region-specific information.     

Downscaling nonclimatic drivers for surface water vulnerabilities in the Elbe river basin

Aggregated consideration of both climate and socio-economic change in a coarse spatial resolution is a central feature for scenario development in global change research. Downscaling of the supposed aggregated changes is a necessary prerequisite for the assessments of global change at the regional scale. The present paper describes the method and results of an approach to develop and to apply scenarios of socio-economic change at a sub-national level, which are consistent with global change scenarios. National and regional models of economic and demographic development are used to regionalise drivers of socio-economic change. Scenario results are subsequently applied in order to analyse the impacts of socio-economic and climatic changes on water management issues in the Elbe river basin. Starting from global IPCC-Emissions Scenarios and taking up their key points, we formulate two scenarios for the German and Czech parts of the Elbe catchment areas. We present a system of demographic and economic models, designed to consistently project socio-economic developments at a national and sub-national level and, thus, to quantitatively illustrate our scenarios. The results show that in a scenario that assumes continued globalisation and emphasis on economic growth, export orientation will result in a comparatively high share of manufacturing. Growth spreads from centres to peripheral regions. Still, at the national level, the increase in population and employment will be modest and create little additional pressure, but water stress will be considerably stronger on a regional basis, namely in metropolitan areas such as Prague, Berlin and Hamburg. In a scenario where economic goals are balanced with ecologic and social ones, growth is weaker and the weight of the service sector increases more rapidly, thus easing the driving forces for overall water demand and pollution. However, as in this scenario regional metropolitan centres develop at the cost of peripheral regions, regional development is more selective and the driving forces for potential water stress will diverge spatially.     

武汉城市圈土地利用变化系统仿真模拟与驱动力分析

土地利用变化是全球环境变化与可持续研究的重要内容,驱动力研究是土地利用变化研究中的核心问题。现有土地利用变化驱动力研究多针对单一的城市区域展开,无法解释城市群地区,城市一体化战略指导下城市交互作用对土地利用变化的影响。运用系统动力学(SD)方法,综合考虑经济、人口、城市化、政策等主要人文因素,并将城市交互作用因素引入SD,以武汉城市圈为例,构建土地利用变化系统SD模型,运用1997~2006年的历史数据进行检验,并对武汉城市圈2010~2020年不同情景下的土地利用变化进行模拟。结果表明,建立的SD模型是有效的,两种情景下土地利用变化表现出差异性,说明城市交互作用是除经济、人口城市化等社会经济因素外,土地利用变化的又一重要影响因素。     

干旱灾害对江西省农业生产的影响及其对策

江西是农业大省,是国家重要的粮食主产区。近10 a来江西省干旱发生频繁,导致农业生产损失严重,威胁到农业的可持续发展。基于历史文献与资料,结合江西省农业厅的农业灾情调查数据和干旱指数最高的星子县、都昌县调研数据,着力分析近10 a来江西省的干旱状况及其对农作物生产的影响,探讨农业干旱灾害的成因。研究结果表明:江西干旱灾害以秋旱为主,近10 a年对江西的粮食和棉花生产造成重大损失,尤其是鄱阳湖区地区;江西农业干旱灾害的主要成因包括降水分布不均匀、红壤持水能力低、水利设施年久失修、植被结构破坏和易改变水文过程的大型水利设施建设。最后针对农业干旱灾害的主要成因,提出了减轻干旱灾害对农业生产不利影响的对策     

基于CLUE-S模型的重庆市渝北区土地利用变化动态模拟

以重庆市渝北区为研究区域,运用CLUE-S模型,结合Logistic回归分析,分别以2007年和2009年为基期,对渝北区2013年土地利用情况进行模拟研究,在此基础上构建了渝北区2013~2020年3种不同情景的土地利用变化模式,模拟了3种情景模式下渝北区在2020年的土地利用空间分布格局。结果表明:(1)两期模拟的正确率分别达到了92.26%和94%,Kappa系数值分别为90.32%和92.5%,均取得了较好的模拟效果,说明CLUE-S模型适用于渝北区的土地利用空间格局变化的模拟研究,具有较好的模拟区域土地利用时空变化的能力;(2)地形、国道、省道、高速公路等主要道路、河流、城镇和村庄是影响渝北区土地利用空间格局变化的重要驱动因素;(3)在3种情景模式中,主要的用地格局变化均发生在两江新区,区内建设用地总体呈现向东北部扩张的趋势,表明区域经济社会发展政策对用地类型的变化具有较大的影响;(4)从促进城乡统筹和谐发展、土地节约集约利用、生态环境显著改善和保护耕地的区域发展目标而言,情景模式2为较为合理的发展模式。研究结果可为决策部门在土地可持续利用和土地管理方面提供参考依据。     

基于地块尺度的耕地非农化驱动力空间异质性研究——以武汉市为例

土地用途管制和基本农田保护制度下,耕地非农化概率值和其驱动力的空间作用强度分布在土地资源配置和耕地保护方面有积极的指示性。基于武汉市2000~2011年耕地非农化地块的微观数据,通过比较分析Logistic回归模型和地理加权Logistic回归模型参数估计结果,验证了耕地非农化驱动力的空间异质性,并对异质性的空间分布规律和政策涵义做出总结分析。研究表明:1耕地间的空间依赖效应和建设用地对耕地的空间溢出效应在耕地非农化过程中具有显著影响力,且耕地非农化驱动力存在显著的空间异质性;2地理加权Logistic回归模型由于考虑到数据的空间非平稳状态所以比Logistic回归模型有更好的拟合效果;3耕地非农化驱动力的异质性在空间上呈现出一定规律,这些受到产业布局、经济和城市发展特点等的影响,根据不同驱动力空间异质性产生的原因进行差异化土地管理可以解决耕地保护和建设用地供给间的矛盾。研究结果能从地块尺度上反映出耕地非农化驱动因素的空间异质性,实现了驱动因素作用强度空间分布的可视化,并能为国土资源差异化管理提供理论和实践参考。     

Projections of industrial water withdrawal under shared socioeconomic pathways and climate mitigation scenarios

We estimated global future industrial water withdrawal (IWW) by considering socioeconomic driving forces, climate mitigation, and technological improvements, and by using the output of the Asia–Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. We carried out this estimation in three steps. First, we developed a sector- and region-specific regression model for IWW. The model utilized and analyzed cross-country panel data using historical statistics of IWW for 10 sectors and 42 countries. Second, we estimated historical IWW by applying a regression model. Third, we projected future IWW from the output of AIM/CGE. For future projections, we considered and included multiple socioeconomic assumptions, namely different shared socioeconomic pathways (SSPs) with and without climate mitigation policy. In all of the baseline scenarios, IWW was projected to increase throughout the twenty-first century, but growth through the latter half of the century is likely to be modest mainly due to the effects of decreased water use intensity. The projections for global total IWW ranged from 461 to 1,560 km³/year in 2050 and from 196 to 1,463 km³/year in 2100. The effects of climate mitigation on IWW were both negative and positive, depending on the SSPs. We attributed differences among scenarios to the balance between the choices of carbon capture and storage (CCS) and renewable energy. A smaller share of CCS was accompanied by a larger share of non-thermal renewable energy, which requires a smaller amount of water withdrawal per unit of energy production. Renewable energy is, therefore, less water intensive than thermal power with CCS with regard to decarbonizing the power system.     

深圳市土地利用变化驱动力系统分析

以深圳市土地利用变化的驱动力系统为例，用灰色关联方法确定影响土地利用变化的驱动因子并判别其最大驱动力，结果表明：深圳城市建设用地面积变化与外资利用额的关联系数最大，达到0.8491，其次为基础建设投资颧、第三产业产值、工业总产值及总人口数量；耕地、林地、荒地、水域面积变化则与城市化率的关联系数最大。以1991-1999年间的建设用地面积作为灰色系统特征数据序列，选取与其关联系数最大的五个驱动因子序列数据作为相关因素数据系列，建立CM（1，6）模型，结果表明：该模型的计算值和实际值的相对误差最大为11.11％，最小为-0.25％，平均相对误差也只有3.41％；检验结果表明，2000-2004年的模拟值与检验值的平均相对误差仅为3.74％，模拟精度较高，因而可以利用该模型预测深圳市建设用地的增长规模。     

Study on the Balance of Agricultural Water and Land Resources on Ningxia Plain

The article puts forward the process and means of regional water and land balance research, and then from two scenarios which are the balances under natural regulation and human intervention, calculated and analysed the balance between water and land on Ningxia Plain. For the balance under natural regulation named farmland water balance, using farmland water resource balance equation, the research estimated the monthly farmland＂ water balance of 8 major crops for all of the 12 counties on Ningxia Plain in the period of 1960-2001; for the balance under human intervention, the research estimated land-use water balance equation of the counties in 2000, and calculated the balance between land use and water resources including irrigating water of all the 12 counties on Ningxia Plain. Results showed that ①precipitation can not meet the water demand of the crops for growth and development on Ningxia Plain, and water shortage is the primary character of farmland water balance under natural regulation. ②the diversity of water and land balance of different counties is distinctly influenced by the crop structure, water quantity for irrigation and irrigation level. ③Irrigation water could meet the crop water demand on Ningxia Plain in 2000, but there was not much space to expand irrigating cultivated land.     

农业节水和南水北调对华北平原可持续水管理的影响

针对华北平原可持续水管理中存在的问题,采用MIKE SHE模型和SD模型耦合的方式,设定现状保持、农业节水和南水北调等3种情景,模拟2014~2028年农业节水和南水北调对华北平原可持续水管理的影响。结果表明：（1）农业节水的实施对华北平原可持续水管理有一定影响,模拟期末的缺水指数下降15.8%,非充分灌溉和减少灌溉量分别使得地下水储量恢复约0.06和0.12 m;（2）南水北调显著降低缺水指数（下降50.7%）,地下水水位和含水层储量出现较大的恢复（含水层储量恢复1.12 m）;（3）华北平原短期内无法解决缺水问题,但通过多种途径结合,倡导节约用水,提高用水效率,引入区域外的水,可以有效地缓解华北平原的缺水问题,保证水资源的可持续利用和发展。     

Study on the Balance of Agricultural Water and Land Resources on Ningxia Plain

Abstract

The article puts forward the process and means of regional water and land balance research, and then from two scenarios which are the balances under natural regulation and human intervention, calculated and analysed the balance between water and land on Ningxia Plain. For the balance under natural regulation named farmland water balance, using farmland water resource balance equation, the research estimated the monthly farmland water balance of 8 major crops for all of the 12 counties on Ningxia Plain in the period of 1960–2001; for the balance under human intervention, the research estimated land-use water balance equation of the counties in 2000, and calculated the balance between land use and water resources including irrigating water of all the 12 counties on Ningxia Plain. Results showed that ①precipitation can not meet the water demand of the crops for growth and development on Ningxia Plain, and water shortage is the primary character of farmland water balance under natural regulation, ②the diversity of water and land balance of different counties is distinctly influenced by the crop structure, water quantity for irrigation and irrigation level. ③Irrigation water could meet the crop water demand on Ningxia Plain in 2000, but there was not much space to expand irrigating cultivated land.     

基于SD模型的三峡库区快速城镇化地区耕地利用模拟研究

对引起耕地变化的驱动因素进行研究,有利于解决当下人口、经济和社会发展与耕地资源的矛盾。基于对耕地变化相关因素的线性分析,提出改进基于时间序列对耕地变化驱动力静态研究的模式,利用系统动力学模型从动态的耕地变化仿真模拟过程中对长寿区耕地变化趋势进行预测研究,为快速城镇化地区耕地资源的合理利用与保护提供借鉴。结果表明：（1）长寿区耕地面积25 a间共减少 9 535 hm2,在数量上总体呈现波动下降趋势;（2）长寿区耕地变化的主要驱动力与社会经济发展、人口与城市发展、农业结构调整与科技进步密切相关;（3）利用SD模型在不同情景设定下的模拟发现,区内城镇化率对耕地面积的影响＞GDP对耕地面积的影响＞人口增长对耕地面积的影响;（4）耕地利用变化在不同社会经济发展模式下的差异较大,而GDP和城镇化率的缓速增长发展模式最为理想,对区内耕地资源保护有一定的促进作用。由此可以得出,为减轻未来长寿区耕地保护工作压力,必须转变以牺牲耕地作为代价的经济发展模式,通过集约节约用地、积极开展农村建设用地复垦等工作来协调城镇化的快速发展与耕地保护之间的矛盾。 关键词： 耕地变化;驱动力;耕地非农化;系统动力学;城镇化;三峡库区     

基于CLUE-S模型的重庆市主城区土地利用情景模拟

以重庆市主城区为研究区,采用120m×120m栅格大小的数据为模拟基准,借助CLUE-S模型、情景分析法、SPSS软件及ArcGIS10.1软件建立了数量变化和空间分布变化相结合的不同情景下土地利用/覆盖变化的动态模拟模型,并对研究区不同情景下的土地利用/覆盖动态变化进行了模拟,模型综合考虑各种宏观驱动因子与土地利用变化之间的关系,较全面地考虑了多种土地利用/覆盖变化驱动因子,并利用SPSS软件进行相关性分析,确定了各因子的回归模型,提高了模拟结果的精度,通过对已有数据的模拟及精度分析,整体模拟精度达86%以上,在一定程度上反映了该模型在研究高分辨率土地利用/覆盖变化方面有很好的适应性,对土地利用/覆盖变化的复杂性研究和相关部门对土地布局、规划方面具有一定的参考价值。模拟结果表明:到2030年湿地、人工用地、林地将增加,耕地和其它用地减少,草地在不同的情景下均有稍微的增加,耕地和人工用地是变化最大的两种类型,随着时间的推移耕地和林地面积不断接近甚至持平,研究区西部及西南部变化比较明显。     

Consumptive water footprint and virtual water trade scenarios for China — With a focus on crop production,consumption and trade

The study assesses green and blue water footprints (WFs) and virtual water (VW) trade in China under alternative scenarios for 2030 and 2050, with a focus on crop production, consumption and trade. We consider five driving factors of change: climate, harvested crop area, technology, diet, and population. Four scenarios (S1–S4) are constructed by making use of three of IPCC's shared socio-economic pathways (SSP1–SSP3) and two of IPCC's representative concentration pathways (RCP 2.6 and RCP 8.5) and taking 2005 as the baseline year. Results show that, across the four scenarios and for most crops, the green and blue WFs per tonne will decrease compared to the baseline year, due to the projected crop yield increase, which is driven by the higher precipitation and CO₂ concentration under the two RCPs and the foreseen uptake of better technology. The WF per capita related to food consumption decreases in all scenarios. Changing to the less-meat diet can generate a reduction in the WF of food consumption of 44% by 2050. In all scenarios, as a result of the projected increase in crop yields and thus overall growth in crop production, China will reverse its role from net VW importer to net VW exporter. However, China will remain a big net VW importer related to soybean, which accounts for 5% of the WF of Chinese food consumption (in S1) by 2050. All scenarios show that China could attain a high degree of food self-sufficiency while simultaneously reducing water consumption in agriculture. However, the premise of realizing the presented scenarios is smart water and cropland management, effective and coherent policies on water, agriculture and infrastructure, and, as in scenario S1, a shift to a diet containing less meat.     

Assessment of irrigation system sustainability using the Theil–Sen estimator of slope of time series

Agriculture, especially the irrigated sector, is the mainstay of Sudan’s economy as it accounts for 40 % of gross domestic product (GDP) and employs 70 % of the workforce. The economic viability of irrigated schemes is dependent on three factors: crop yield, water management and cropped area. The research question of this study was whether or not the current status of these factors can be sustained in order to maintain the economic viability of irrigation systems? To answer this question, a new (to the best of the author’s knowledge) approach was developed based on time series analysis, and on the Theil–Sen estimator of slope. The study defined sustainability conceptually as “the ability of an irrigation system to sustain crop yields using the optimum cropped area and water consumption to realize the economic viability of the irrigation system without a decline in soil quality and environment”. Time series datasets of crop yields, cropped area and irrigation water consumption are collected routinely by statistical departments. Any abrupt years in the development of trends were detected and related to their driving forces/causes, of which climatic conditions and marketing policies were found to be the most important. The simple approach developed proved its suitability for quantifying the progress of irrigated schemes’ towards sustainability development as tested under the conditions of Gezira irrigated scheme in Sudan—the largest singly managed irrigation scheme in the world. The scheme was found to be sustainable under the condition that the crop yield is considered as the top priority; otherwise, the sustainability of the scheme is jeopardized.     

Improvement in irrigation water use efficiency: a strategy for climate change adaptation and sustainable development of Vietnamese tea production

Irrigation is indispensable to overcome insufficient rainfall and to achieve a stabilized yield for tea production. As the severe scarcity of water resources because of climate change, water conservation through efficient irrigation has turned into a vital strategy for tea sector in solving this rising challenge. This paper analyzes irrigation water use efficiency of small-scale tea farms in Vietnam and identifies its determinants applying stochastic frontier analysis. Results showed that under decreasing returns to scale, the mean irrigation water use efficiency was 42.19 %, indicating the existence of substantial water waste. If farmers become more efficient in using water, saving 57.81 % of irrigation water is possible unaccompanied by reducing the observed output. The factors affecting tea farms’ irrigation water use efficiency were investigated by Tobit model. Gender, water shortage awareness, soil and water conservation practice, off-farm income share, extension services access and well water utilization showed significant influence on the efficiency of irrigation water. The study’ results provide insights to policymakers in implementing better water resource management amid climate change.     

Multi-scales Analysis of Driving Forces on Land Use/Cover Change in China： Taking Farmland Returning to Forest or Grassland as a Case

Increasing populations are causing an increase in food demands, and the area of cultivated land expands every year. Inappropriate land transition from ecology to production results in the constant decline of the ecological security level and influences the regional sustainable development. Adjusting unreasonable land use mode and reconstructing natural land cover are important ways to maintain and improve the ecological environment. Also reclaiming farmland as areas for forests and grasslands （FRFG） is another way. Successful implementation of FRFG in China is the result of comprehensive effect of the multi-scales driving forces. This paper analyses the driving forces of FRFG in China on a national （country） -regional （province） - local （county） - household （farmer） level scale, and the results are： driving forces at the national scale include ecological and food security and the western development of China; at the regional scale, ecological and economic benefits become the main factors to influence the dimension of FRFG under the same policy. The driving forces can be divided into 6 types： industrial structure adjustment, water source protection, flood prevention, the Three-Gorge Project protection, reduction of the amount of sediment flowing into the Yellow River and wind erosion desertification prevention. The driving forces at the local scale can be divided into 12 types with developing leading industries, increasing farmers＇ income and improving agricultural production conditions as the main types; at the household scale, the national policy meeting farmers＇ demands and the optimization of individual interests are all driving forces.     

Climate change impacts on irrigation water requirements in the Guadalquivir river basin in Spain

Irrigated production in the Guadalquivir river basin in Spain has grown significantly over the last decade. As a consequence, water resources are under severe pressure, with an increasing deficit between available supplies and water demand. To conserve supplies, the water authority has reduced the volume of water assigned to each irrigation district. Major infrastructural investments have also been made to improve irrigation efficiency, including the adoption of high technology micro-irrigation systems. Within a context of increasing water scarcity, climate change threatens to exacerbate the current supply-demand imbalance. In this study, the impacts of climate change on irrigation water demand have been modelled and mapped. Using a combination of crop and geographic information systems, maps showing the predicted spatial impacts of changes in agroclimate (climate variables that determine the irrigation requirements) and irrigation need have been produced. The maps highlight a significant predicted increase in aridity and irrigation need. Modelling of irrigation water requirements shows a typical increase of between 15 and 20% in seasonal irrigation need by the 2050s, depending on location and cropping pattern, coupled with changes in seasonal timing of demand.     

长江流域土地利用/覆被变化的大尺度水文效应

土地利用/覆被变化(LUCC)对流域水文过程具有重要的长期影响作用。针对土地利用覆被变化对大型流域水文过程的影响程度,利用构建的长江流域分布式水文模型分析了土地利用变化情景下的水文效应特征。结果显示:分布式水文模型综合考虑了下垫面土壤、坡度、植被等特征,可以较好的反映降水发生后水分在不同土壤、植被和地形条组合件下,蒸散、地表和地下径流等组分的运移过程。根据不同土地覆被类型的径流成分差异,以及长江流域实际可供调节的土地利用方式,流域现有土地利用格局中农林地依然具有较大的转换空间。根据典型流域中预设的农林地转换情景下的径流效应看,各种情景虽然对流域径流总量变化影响较小,但对蒸散、地表径流和基流可以产生显著影响。其中,林地增加使基流最高提升超过15%,同时可使地表径流下降近5%,两者对蒸散的改变在1%左右,对径流总量变化幅度则只有0.7%左右。不同情景下的水文响应模式反映了未来土地利用调整的水文效应,因此可以基于不同的径流效应,开展有利于综合发挥流域持水能力的空间规划,提升林地所占比重。     

Multi-scales Analysis of Driving Forces on Land Use/Cover Change in China: Taking Farmland Returning to Forest or Grassland as a Case

Abstract

Increasing populations are causing an increase in food demands, and the area of cultivated land expands every year. Inappropriate land transition from ecology to production results in the constant decline of the ecological security level and influences the regional sustainable development. Adjusting unreasonable land use mode and reconstructing natural land cover are important ways to maintain and improve the ecological environment. Also reclaiming farmland as areas for forests and grasslands (FRFG) is another way. Successful implementation of FRFG in China is the result of comprehensive effect of the multi-scales driving forces. This paper analyses the driving forces of FRFG in China on a national (country)—regional (province)—local (county)—household (farmer) level scale, and the results are: driving forces at the national scale include ecological and food security and the western development of China; at the regional scale, ecological and economic benefits become the main factors to influence the dimension of FRFG under the same policy. The driving forces can be divided into 6 types: industrial structure adjustment, water source protection, flood prevention, the Three-Gorge Project protection, reduction of the amount of sediment flowing into the Yellow River and wind erosion desertification prevention. The driving forces at the local scale can be divided into 12 types with developing leading industries, increasing farmers' income and improving agricultural production conditions as the main types; at the household scale, the national policy meeting farmers' demands and the optimization of individual interests are all driving forces.