Methods and Accounts for Water Withdrawal at the City Level and Evaluation of Sectoral Water Saving in China

In the context of the freshwater crisis, two-thirds of the cities in China suffer from freshwater scarcity, and there are restrictions on the use of water by industries. Although ‘Redline Regulation’ policies as core regulations were set to save water through improving water-withdrawal efficiency, China still has transnationally low efficiency owing to poor sectoral water-saving initiatives. Control on efficiency still lacks targeting and prioritization to specific sectors and cities. To save water at the city level has become a priority strategy of regulation and requirement for water management in China, yet how to conduct and realize it among various cities or sectors has not been answered. Although high water-consumption activities are determined in a few cities, comparison across the whole cities and economic-sectors could not be realized. Accounting for sectoral water withdrawal at the city level could help planners regulate water use in different sectors to improve water use efficiency. Thus, high-resolution water accounting methods and datasets in terms of spatiality and economic-sector are critical for China’s water saving. What is more, it is meaningful to investigate sectoral water-saving potential and implication for alleviating scarcity, to promote sustainable water use and economic development. Yet due to lack of measured efficiency data, there remains a dearth of water withdrawal accounting methods and datasets, as well as water availability and scarcity data, no matter for total or sectoral amounts for prefectural cities. These data limitations from water statistics and accounting in China are significant, long-lasting for two decades (typically data from 1995 are still being utilized in research, and urgently need to be updated). Compared to developed countries, such as Australia etc., water accounting in China has already fallen behind. Disaggregated sectoral water withdrawal accounting is not readily available for China. Not all cities in China are able to account for water as ‘routine’ management activities. Approximately two fifths of 343 cities do not collect or develop water data statistics. For data of the other three fifths of cities, there are only total numbers of six types provided, with differences in terms of statistical caliber etc.. New accounting methodology is needed to develop, which should be suitable for new cases according to specific statistical conditions of different cities and sectors, as well as China’s own actual state. This is quite different from developed countries. Water withdrawal statistics in China are patchy, and water data across all sectors at the city level appear to be relatively insufficient. Hence, in administrative and territorial scopes, I develop a general framework to, for the first time, account for water withdrawal of 65 economic-social-environmental sectors in cities of China. This novel methodology is based on water withdrawal efficiency, as benchmark performance, from point-sourced surveys in China (led and carried out by the Ministry of Ecology and Environment) in 2015. It features in selection of 22 driving forces, and I connect each size indicator with its unique water-withdrawal efficiency. The general framework is applied because only inconsistent water statistics collected from different data sources at the city level are available. Applying this general framework, I account for water withdrawal of all 65 economic-socio-environmental sectors for all 343 prefectural cities in China, using a 2015 data benchmark. Then I compare different scopes and methods of official accounts and statistics from various water withdrawal datasets. I further account for total water availability, and water scarcity status in each of 343 prefectures. These high-resolution water accounts in terms of spatiality and economic-sector are unprecedented in China. From the water withdrawal datasets, I first find 1) different from conventional perceptions that agriculture is usually the largest water user, industrial and household water withdrawal may also account for the largest percentages in the water-use structure of some cities, for example Luoyang (central) for industrial water withdrawal; and Guangzhou (south) and Qingdao (east) for household water withdrawal. 2) The difference among annual household water use per resident in the urban areas of different cities is relatively small (as is the case for rural areas), but that between urban and rural areas is large. Thus, increased attention should be paid to controlling industrial and urban household water use in particular cities, such as Xi’an (west), Shaoxing (east), Taizhou (east), Luoyang (central), and Chongqing (southwest). These high-resolution water scarcity accounts throw light upon low water-efficiency sectors in cities suffering from water scarcity: I find 3) agricultural and industrial sectors with high water-withdrawal intensity exist in representatively small developing cities. 4) The top 10% of low-efficiency industrial sectors represent 46% industrial water withdrawal. Examples of 3) and 4) are listed below: papermaking and product manufacturing in Chenzhou (central), Lincang (southwest) and Qiqihar (northeast); liquor, beverage and tea manufacturing in Jingdezhen (mid-east), Anqing (mid-south) and Wuzhou (southwest); electricity and hot water supply in Changde (mid-south); and agricultural-related sectors in Zhoukou (central), Linyi (east) and Fuyang (mid-south). Thus, attention should also be paid to both coordinating production scales in water-scarce cities, and reducing water withdrawal intensities for stringent management. What is more, to investigate sectoral water-saving potential and implication for alleviating stress, I build water-saving scenarios in 41 industrial and 5 agricultural sectors across 180 water-scarce cities, by assuming a convergence of below-average efficiencies to the national sector-average for technical improvement. I find overall industrial water-withdrawal efficiency could improve by 20%, satisfying the redline regulation. 18.9 km3 (±3.2%) water saving in industry and 50.3 km3 (±2.3%) in agriculture would be achieved, equivalent to the annual water demand of Russia. Top sectors and cities with above-average water saving potential were detected. There is possibility that a minority of sectors could contribute to most water savings whilst minimizing economic disturbances. In contrast, implementing water efficiency measures in the majority of sectors would result in substantial economic change to achieve identical savings. As a result, water efficiency improvements should be targeted towards this minority of sectors: cloth(ing) and chemical manufacturing in industry, and rice, vegetables and fruits cultivation in agriculture. Cities with above-average water saving potential are Suzhou (south), Nanjing (southeast), Xiangtan (mid-south), Guangzhou (south) and so on for industry; Bayannur (north), Kashi (northwest), Akesu (northwest), and Daqing (northeast) etc. for agriculture. There would be 18 cities with population of 40 million alleviated below the scarcity threshold (40%) and shake off water scarcity at identical water availability levels, for example Xining, Zhangye, Hotan, Haidong (northwest), Jincheng, Yulin (west), Jilin city (northeast), Wuxi and Xiangtan (mid-south). At the national level, mean scarcity level of water-scarce cities would fall by 20 percentage points from 96% to 76%, being alleviated to sub extreme-scarcity level. Through unique account, I propose that sectoral water saving should be well positioned to alleviate water stress, through improving sectoral water use efficiency, especially by reducing sectoral water withdrawal intensities with little disturbance to the production or economy. I think sectors of low efficiency in water scarce cities should be well-targeted. Requiring all sectors to evenly or in-general improve water efficiency does not represent an optimal policy choice. In sum, this complete analysis through unique account would bring a conceptual advance. Our results help to enable targeted saving strategies and identify priorities, to facilitate more effective water regulation through optimizing efforts for improving efficiency. At last, these data of high resolution could be used directly in input-output models, consumption-based accounting and structural decomposition analyses. The data accounted would facilitate proceeding to in-depth exploration. Data could also help gain in-depth insights, concerning sectoral water withdrawal, and alleviating water stress from local activities.

在淡水资源短缺的背景下，尽管中国设立全国范围的“最严格水资源管理的红线政策”，旨在通过提高用水效率来节约水资源，但是与国际平均水平相比，中国的用水效率仍然很低1–4。这主要归咎于缺乏细分产业的节水方案5，即对于用水效率的监管仍未瞄准特定的、重点行业或目标城市，未找到相应的优先次序6。在城市层面核算细分产业的用水量有助于监管不同产业用水、降低节水成本，从而切实提高用水效率、节约水资源。因此，对于中国落实十九大“节水优先、空间均衡”的战略要求而言，开发空间分辨率较高、经济部分划分精细的水核算方法论和数据集是重要而紧迫的。综合评估细分产业的节水潜力及其对减轻水短缺状况的作用、缓解“经济-水资源”掣肘困局，从而促进用水和经济的可持续发展，具备战略和现实意义。 然而在城市层面（地级行政单元，包括地级市、盟、地区、自治州等），由于没有实测的用水效率的数据，关于取水量核算的方法学及数据集仍然缺乏；也没有关于可利用水资源量、水短缺程度的详实数据，无论是总量还是分产业的量。其实纵观中国水资源统计和核算，这种数据缺陷十分严重，并且存在长达二十年之久。当下由于缺乏最新的数据，通常的文献（甚至主流文献）仍然不得不使用过去1995年的数据7，因此更新这方面的数据的需求是非常迫切的。与美国、法国和澳大利亚等发达国家相比，当前中国的水资源核算已经相对落后。中国的取水量的统计可谓是捉襟见肘，城市级别、涵盖多产业的取水量数据仍然也显得相对不足。 因此为了解决中国水资源核算相对落后的问题，在地级行政单位范围内，本研究在沿袭现有的、各部门取水量统计与核算的一般规律的基础上，开发了中国地级市用水数据集编纂模型。首次提出在发展中国家的城市中、核算取水量的综合框架(Figure 1)。包含经济、社会和环境等三个维度，涵盖农业、工业、建筑、服务、生活和生态等六大类65个细分产业。该创新性的方法基于省级和城市级水资源公报、中国高分辨率排放数据库和各省市统计年鉴等。受IPCC碳排放核算框架的启发，该方法的特色在于针对每个大类部门取水量，我们发现了相应的、独有的驱动力指标（共计22个），将每个规模变量及其独一无二的用水效率变量联结起来。该创新性的方法是我国具备自主知识产权的科学体系。 首先，应用该创新性的方法体系，2017年9月至今申请人及团队核算了中国2015年343地级市、细分65产业的取水量数据，覆盖完整的、全部的城市和行业。随后本人比较了现有关于中国的、大部分主流官方数据集及其方法来源、范围口径。本人进一步核算了中国343地级市各自的可利用水资源量和水短缺程度。在中国，这些具备较高空间分辨率、精细部分划分的水核算方法论和取水量清单数据集是前所未有、独一无二的。 本研究的数据集具有里程碑式的数据贡献。特别是经过前期多轮核算与校验，核算的研究对象包括农业及其细分行业（作物）的结果。考虑到美国等目前已经细分农业，而中国没有细分，这些数据更为稀缺。本研究利用现有文献和数据8（进行数据清理、迅速对现有不同数据集进行“摸底”、确保没有人为错误，使数据“靠得住”），最终拓展了农业细分的数据集、克服以往数据集在这方面的局限，从而形成创新点、也具备实际价值。水短缺程度的数据也有助于阐明遭受水短缺的城市及其低效用水的行业。所有数据免费、透明、可验证，公开分享、公众使用，从而推动中国水科学的快速发展。 更重要的是，为了综合评估细分产业节水潜力及其对减轻水压力的作用，我们针对180个水短缺城市，构建了节水的情景分析，覆盖41个工业部门和5个农业部门。主要的假设是：在每个产业内部，低于全国平均用水效率的城市将会采取技术进步、提高用水效率，从而达到各自产业的（全国）平均水平。研究发现，整体上工业用水效率将会提高20%，满足“红线监管”的要求。实现工业节水量约189亿立方米(±3.2%)，农业节水约503亿立方米(±2.3%)，总和相当于俄罗斯全国全年的需水量。很凑巧的是，发现只有少数行业不仅带来最大的节水贡献，而且改变最少的城市、附带最小的经济干扰（节水成本）。即这些少数行业可通过“四两拨千斤”的方式实现“经济-水资源”的双赢。相反，在大多数产业实施节水政策，要想获取同等的节水收益，将会对经济造成重大干扰，是一件“费力不讨好”的事情。因此提高用水效率应该瞄准这部分特定的、少数的重点行业：纺织服务服饰业和纺织制造业的全产业链、化学原料和制品制造业、水稻种植业、蔬菜和水果种植业。本研究最后给出了这些“目标”城市的名单。从而最终揭示“红线管理”制度下应有的节水重点行业和城市。 透过独一无二的数据集，本研究倡议在行政管理尺度下面，从（细分产业）的产业角度考虑节水问题：我们认为应该瞄准水短缺城市的低效行业实现“精准节水”，在对经济扰动较小的同时提高少数重点产业的用水效率。相反，“强制要求全部的行业笼统地、平均地提升用水效率”，并非最佳的政策选择。从而带来更多观念的冲击或更新。本研究计划对“怎样节水、效果怎样”作详细分析，聚焦多数读者关切的、有共同兴趣的话题。总体来看，统筹农业工业的角度、综合评估节水潜力，主线鲜明、逻辑连贯而完整、具备重要而广泛的意义。 总之，本研究通过独有的数据集、开展完整的分析，将会推动水资源管理科学领域内的观念进步。成果将有助于为“精准节水”战略赋能，找到节水的优先次序、避免蛮力，从而有利于实现更加有效的水资源监管。最后，这些高分辨率的地学数据将会引发更为深入的探讨、推动交叉学科前进。 申请人及团队预期本研究将会在中国工农产业激发关于节水潜力的广泛讨论，推动政策制定和技术进步。我们也认为该研究将会在世界范围的学术界和产业圈引起更为广泛的兴趣和实践。总之，这项基础研究只是探索中国水资源管理科学“知识极限”的第一步，但是又是一项相当需要的突破。相关论文将会吸引地学界的、覆盖46个工农产业经济活动的、基层的研究人员。最终缩短当前中国与美国、澳大利亚等发达国家在该领域的差距。 综上所述，该研究符合中国水资源（核算与管理）科学领域内自身发展的需要。虽然本研究具备较强创新性、本人潜心付出，但由于工作量较大，目前研究刚走出“初期探索”的阶段，数据刚完成核算和校验。目前的最新成果、相关论文也在Nature Geoscience/Scientific Data等Nature-index高水平期刊的同行评议之中。