Regional and Sectoral Impacts of Water Redline Policy in China: Results from an Integrated Regional CGE Water Model

Y. Zhang¹; K. Chen²; T. Zhu³

1: Institute of Agricultural Economics and Development of Chinese Academy of Agricultural Sciences, , China, 2: International Food Policy Research Institute, Beijing Office, China, 3: International Food Policy Research Institute, , United States of A Corresponding author email: [email protected] Abstract: China has started to implement the most stringent of “Three Red Lines” water policy since 2012, which sets targets for total water use, water use efficiency, and water quality for a number of benchmark years to 2030 by province and prefecture. This paper aims to develop an integrated regional CGE and water resource model at river basin-provincial level for China and to quantify regional and sectoral economic impacts of three red lines. Five policy scenarios are constructed to assess the impacts of water red lines, including the red line of total water use cap, irrigation efficiency, industrial water use intensity, surface water pollution and all redlines combined. The red line of total water use cap will increase water shortage drastically, leading to considerable negative impacts on the economic growth of East, South Central and Southwest. The sectors with the higher water use intensity such as machinery and equipment, metal and metal products, chemical products and non-metal products are affected most. Other two red lines need to go hand in hand to minimize water shortage and mitigate potentially negative economic impacts. Establishing regional water use right market and promoting economic restructuring are two policy options to cope with water scarcity challenge. Acknowledegment: We would like to acknowledge Winston Yu from the World Bank for the guidance and Shuzhong Gu from Development Research Center of the State Council (DRC) for his valuable comments in the early stage of the research. We are grateful to Xinshen Diao and James Thurlow from International Food Policy Research Institute for their guidance on developing regional CGE model. We acknowledge funding support by the World bank through the project “Mind the Gap: Balancing Growth and Water Security in China”, and the National Natural Science Foundation of China (NSFC) (Grant No.71761147004) ,the Agricultural Science and Technology Innovation Program (ASTIP-IAED-2017-04 ）

JEL Codes: C68, O25

#1290

Regional and Sectoral Impacts of Water Redline Policy in China: Results from an Integrated Regional CGE Water Model

Abstract

China has started to implement the most stringent of “Three Red Lines” water policy since 2012, which sets targets for total water use, water use efficiency, and water quality for a number of benchmark years to 2030 by province and prefecture. This paper aims to develop an integrated regional CGE and water resource model at river basin-provincial level for China and to quantify regional and sectoral economic impacts of three red lines. Five policy scenarios are constructed to assess the impacts of water red lines, including total water use cap, irrigation efficiency redline, industrial water use intensity redline, surface water pollution redline and all redlines combined. The red line of total water use cap will increase water shortage drastically, leading to considerable negative impacts on the economic growth of East, South Central and Southwest. The sectors with the higher water use intensity such as machinery and equipment, metal and metal products, chemical products and non-metal products are affected most. Other two red lines need to go hand in hand to minimize water shortage and mitigate potentially negative regional and sectoral economic impacts. Establishing regional water use right market and promoting economic restructuring are the two policy options to cope with water scarcity challenge in China.

Key words: water policy, water shortage, economy impacts, CGE model, water resource model, China

I. Introduction China faces increasing challenges of water shortage and the mismatch of regional water demand and supply. China is trying to feed 22% of the world’s population with 7% of the world’s arable land and 6% of global fresh water resources. Per capita water resources are only 2,039 m3 in 2015, which is equivalent to a quarter of the world’s average. Especially in North China, per capita water availability is only 1/4 of the national average level. There is a huge discrepancy between the spatial distribution of water resources and the spatial distribution of population and economic development. For example, in 2014 the North, Northeast and Northwest1 of China account for 57% of land area, 27.8% population, but only 15.6% fresh water resources. The East, Central areas2, with 45.65% of fresh water resources, have 57.38% of China's population and contribute to 66% of GDP (NBS, 2015). Water is as a primary input to all goods and services either directly or indirectly, available water quantity and quality can affect the production of goods and services and thus influences the level of economic activities especially in rapidly transforming societies. Many worries that limited water resources could become a bottleneck of China’s future economic development, especially in regions with severe water shortage. In the recent years, Chinese government has made significant efforts to address the issue of water scarcity through improving water resource management. The most significant policy is the “Opinions of the State Council on the Implementation of the Most Stringent Water Resources Management” in 2012 (the State Council, 2012). In particular, the Opinions established the three “red lines” to control water supply, uses and pollution: 1) controlling the total amount of water use, 2) increasing water use efficiency, and 3) controlling the total amount of pollutant discharge into rivers. Several specific targets have been set for 2030: the national total water use should not exceed 700 billion m3; water use intensity defined as water use per CNY10,000 of industrial value-added (at 2000 constant price) should be reduced to less than 40 m3, and effective irrigative water utilization coefficient should increase to 0.6; and total major pollutants into rivers and lakes will be controlled within the pollutant discharge capacity in the water function zones with water quality compliance rate in the water function zone at 95%. Undoubtedly, an implementation of the most stringent water policy will have substantial impacts on China’s water use in the next decades. Few studies assess the economy impacts of red lines policy quantitatively. Many questions remain unanswered. How much water shortage will it bring? Whether the new water shortage due to the most stringent water policy will have an impact on the economic development? What is the potential impacts of the water shortage on the regional economy? Which regions and which sectors will be affected most? An objective of this paper is to estimate the water shortage constraints under the red lines water policy and further evaluate its impacts on regional economies. To achieve the above objective, an integrated China multi-regional CGE and water resource management model based on river basin-provincial unit is developed to understand the relationship of water and regional economic growth. China water resource

1 North of China refers to provinces of Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia; Northeast refers to Liaoning, Jilin, Heilongjiang; Northwest refers to Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang; 2 East area refers to Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shandong; Central area refers to Henan, Hubei, Hunan, Guangdong, Guangxi, Hainan.

2 model is developed to estimate the water shortage under the constrained water supply and optimize water allocation among different sectors, while multi-regional CGE model is developed to access the regional economic impacts. The integrated regional model has the advantages of reflecting both the characteristics of regional water and the economic systems. The remaining of this paper is organized as follows. Section II describes a construction of an integrated multi-region CGE model with a river basin-provincial water model in China. Section III presents policy scenarios and the model results. Major conclusions and policy recommendations are drawn in the final section.

II. Methodology

The integrated China multi-regional CGE and water resource model is developed for the paper, which links regional CGE model with China water resource model at river basin- provincial level. This model is used to simulate watershed water dispatch and optimize the allocation of water consumption of each sector, and evaluate the impacts of water shortage on regional economy. The integrated model takes into account both the characteristics of the water system and the economic system, and draw on the strengths of the two models. The basin-provincial water resource model is better to capture the regional heterogeneity than the national model, which is also in line with the characteristics of uneven distribution of water resources and regional economic development. The CGE models build the interrelationship between production activities, factors of production, households and government, which can capture both the direct and indirect effects of policy change. This study develop a multi-regional dynamic CGE model for China to estimate the value of water to the economy, and tracks how water resources contribute to economic outputs through linking with China water resource model. This model is extended to regional level based on China dynamic CGE model (Zhang, 2009; Diao, et al., 2012). This model is modified based on the standard CGE model developed by international Food Policy Research Institute (IFPRI), as documented in Lofgren, Harris, and Robinson (2001), which is coded in the General Algebraic Modeling System (GAMS). The recursive dynamic version of the CGE model incorporates of a series of dynamic factors. China regional CGE model is a multi-sectoral general equilibrium model that captures economic activities on both supply and demand sides. The equations also include a set of “system constraints” that define macroeconomic equilibria and equilibrium in markets for factors and commodities. There are several characteristics of a multi-region DCGE model of China. First, the base year is updated to 2014, which can reflect the recent economy structure. Second, in the production side, production activities and production factors are divided into 6 regions: north, northeast, east, central China, southwest, and northwest. This can reflect the regional production characteristics. The products are linked to a unified national market at the same price, inter-regional trade is not explicitly counted in this model. Each region co-produce a class of products and products can be replaced with each other. Factors are assumed that can be mobile between sectors within regions and between regions. Third, this CGE model is regionally disaggregation with a number of agricultural sectors to capture the impacts of water stress on crops, which includes 11 crops of total 62 sectors.

Fourth, industrial water use is integrated in the CGE model as an intermediate good for the production. Industrial water use and household water use are separated into two types in each region to identify the different water constraints, water demand and water supply are balanced at regional level, no water trade among the regions are assumed. In that way, the water stress in one region only impacts the regional water price. The quantity of industrial water use by region and by sector are incorporated into the model. Water taxes by sector by region are introduced to derive uniform average water price according total water quantity and total water value as intermediate goods. The sectoral water use quantity is incorporated into the model to assess the impacts of water shortage. Fifth, recursive dynamics are applied in the model, the dynamics occur only between two periods, and neither consumption smoothing along the growth path, nor intertemporal investment and saving decisions are taken into account, instead, private investment is determined by a Solow type of saving decision, in which savings are proportional to income. The database used in CGE modeling analysis is a social accounting matrix (SAM). A SAM is a square matrix in which each account is represented by a row and a column. Each cell shows the payment from the account of its column to the account of its row (Lofgren et al., 2002). A SAM is flexible in its structure and the scale of a given SAM can be split or aggregated in accordance with the purpose of research and data availability. Both aggregate and disaggregate SAMs are constructed for the Chinese economy in 2014. The disaggregate SAM contains much more detail information, which reflects both the detail sectoral characters and regional characters. There are 62 production sectors in total, which include 21 agricultural subsectors, 25 industrial subsectors and 16 service subsectors in six regions to reflect the regional production characters. Especially, this SAM disaggregated agriculture in each region into 21 subsectors, including 11 crops and 5 livestock, and 4 other subsectors. A list of sectors included in the SAM is presented in Appendix Table A1. The disaggregate SAM has three types of productive factors—land, capital and labor. Labor is further disaggregated into unskilled labor, low skilled labor and high skilled labor according the education level. All types of labors and land are also distinguished by regions. Water capitals are separated from total capital, which are used to link the water production in the CGE model. The cross entropy estimation is used to get a balanced SAM.

The China water resource model (CWRM) is an extended river basin management (RBM) model which operates at more aggregate spatial level than traditional RBM models do (Cai et al., 2006; Harou et al., 2009), and its network structure and database cover the entire territory of China. The model adopts the approach of determining spatial modeling unit through intersecting river basin and administrative boundaries as used in the IFPRI’s IMPACT-Water model (Robinson et al., 2015). The IMPACT-Water model has been adapted to water resource management or agricultural production simulations for a single river basin (Zhu and Ringler, 2012) or a single country (Zhu et al., 2013). For a country as large as China, it is necessary for policy-oriented water resource modeling to disaggregate large river basins into smaller spatial units, in order to capture spatial heterogeneities in water and land resource endowment, socioeconomic development, the structure of water-using sectors, water infrastructure, water-using technologies, and water management institutions. We intersected the 10 first-order river basins delineated by the Ministry of Water Resources, China, with the 34 provincial-level administrative units and created 76 spatial units which are hereafter called basin-province units (BPUs) (see Figure 1). Besides capturing spatial variations of water availability, water demand and water uses in a spatial unit smaller than basin or province, the use of BAUs allows conveniently aggregating input data and output results from BAUs to river basins, provinces and regions. Figure 1．Map of basin-province units (BAUs) with BPU IDs in the ten first-order river basins in China. Grey lines represent provincial boundaries.

The CWRM includes three components: 1) water demand projections for domestic, industrial,

5 irrigation and other sectors, 2) water supply optimization, 3) water allocation across sectors, and 4) crop-wise water allocation and simulation of crop yield reductions under water stress, wherever it occurs. The model can simulate water use impacts of technological and socio-economic changes, as well as climate change. The basic structure of the CWRM is illustrated in Figure 2. The BPUs within a river basin are connected through main stem or main tributaries and they share water resource in the basin following hydrological principles, which reflect the allocation of surface water to provinces in the basin given the definition of BPU. BPUs in one river basin are hydrologically independent from BPUs in another river basin, except that there are inter-basin water transfer projects that import or export water from or to another river basin or basins. Within a BPU, an aggregated water demand area (WDA) diverts surface water from an aggregate reservoir storage and extracts groundwater from underlying aquifers. In some coastal BPUs, where there are desalinization facilities in operation, desalinated seawater is an additional source of water supply. Return flows, which includes irrigation drainage and treated or untreated effluent from municipal and industrial uses, re-join the water resource system at the immediately adjacent downstream BPU. The aggregated reservoir storage has inflows from upstream, local runoff and precipitation falling on reservoir surface area as incoming flows and water diversion to WDA, release to downstream, and reservoir open water evaporation as outgoing flows. The last BPU along the main stem of the river in a basin drains into the ocean, or terminal lakes for endorheic basins, or other countries for international rivers originating from China. Minimum environmental flow requirement is applied to constrain release from the last BPU in a basin. Minimum flow requirements are also applied to BPUs in the upstream to reflect water allocation regulations between provinces within the same river basin. Figure 2.Schematic illustrating basic structure of the CWRM based on the BPU concept

Note: Water-using sectors in the demand box include rural domestic (DMR), urban domestic (DMU), industrial (IND), irrigation (IRR), other agricultural water uses such as aquaculture (OAG) and water use for ecosystem protection (ECO). The letters “P” and “E” represent precipitation falling on surface reservoirs and evaporation from surface reservoirs, respectively. The “sink” refers to ocean, or terminal lakes for endorheic basins, or other countries for international rivers originating from China.

Water demand growth is driven by several factors. Domestic water demand is currently set up as a function of urban and rural population and daily water use quota per capita (DWUQ) in urban and rural areas, which gradually increase over time. Industrial water demand is estimated with industrial GDP growth simulated in the CGE model and industrial water use intensity (IWUI), which decreases over time. The DWUQ and IWUI data are river basin-specific and are taken from the report “National Comprehensive Planning of Water Resources (2010-2030)” (for short, “Comprehensive Planning”) published in 2010 by the General Institute of Water Resources and Hydropower Planning and Design (GIWP). Irrigation water demand is first simulated using weather record of the 1956-2000 period, irrigated area by crop, cropping pattern, and irrigation water use efficiency at the level of BPUs. Crop-specific irrigation land areas are obtained from the global gridded database, IFPRI’s Spatial Production Allocation Model (SPAM) (You et al., 2014). Reference evapotranspiration is calculated using the Priestley-Taylor method (Priestley and Taylor, 1972) at monthly intervals in 0.5-degree grid cells. The gridded irrigated areas and reference evapotranspiration are aggregated to BPUs. Crop-specific evapotranspiration demand is calculated using the FAO approach (Allen et al., 1998). Net irrigation water requirement is calculated using crop-specific evapotranspiration and effective rainfall in the growing season months. Gross irrigation water demand is calculated using net irrigation water requirement and irrigation water use efficiency (IREF) reported in the “Comprehensive Planning.” Inflow to BPUs and local runoff are based on simulated monthly runoff for the 1956-2000 period at the level of 0.5-degree grid cells using the IFPRI’s IMPACT Global Hydrological Model (IGHM) (Zhu et al., 2017), and have been bias-corrected where necessary using mean annual runoff data for the 1956-2000 period reported in the “Comprehensive Planning.” Groundwater use limits are also based on data in the “Comprehensive Planning.” The CWRM is coded in the General Algebraic Modeling System, GAMS (Rosenthal, 2012), as a quadratic programing problem. The objective of the current version of the model minimizes water shortages and deviations of relative water shortages across months in each sector to avoid water scarcity concentrating in a particular month or very few months. The Crop Water Allocation and Stress module in CWRM allocates irrigation water among crops in a BPU. Irrigation water supplies to each crop is assumed to be proportional to water demand of the crop when water shortage occurs, thus equalizing relative water shortage across crops. We use the FAO approach (Doorenbos and Kassam, 1979; Rao et al., 1988) to simulate the effects of water stress on crop yield using a monthly time step to include seasonality of water stress. The integrated CGE model and water resource model is constructed to account for water and value flows throughout the entire economy and the water resource systems, and to explore the relationships between water resources and economic development. The water model and CGE model are linked through two channels. The first channel is land productivity. The output of changes in crops yields by region under different water stress from water model is transferred to the changes in land productivity by crop by region, which are imported into the CGE model as

7 input variables. The second channel is the industrial water use. The CGE model generates the regional industrial GDP growth rates, which are imported into the water resource model. In the water resource model, the demand of industrial water use is determined by the growth rates of industrial GDP. The water model provides the shortage of industrial water by region through optimize the water allocation among different users. The shortage of industrial water will be feed back to the CGE model, the CGE model runs the new industrial GDP growth under the new industrial supply constraints. The Figure 3 demonstrates the linkage mechanism between the water resource model and CGE model. China CGE and water resource models use the same solver tool: GAMS software (Generic Algebra Model System), which allows for integrated solution of the suit of models. Moreover, both the models use the same data source of exogenous driving variables, such as regional population growth and urbanization rate.

Figure 3. Linkage between China Water Resource Model and Regional CGE Model

China Water Industrial GDP by China Multi-regional CGE Resource Model sector by region Model

Agricultural water use/ Land productivity crop yield

Industrial water use Industrial water use shortage shortage

III. The Regional and Sectoral Impacts of Water Redlines Scenario Design The baseline considers the exogenous drives, such as population growth, urbanization, and technology change. The total population will reach to the peak at 1.41 billion and the urbanization rate will be near to 68% by 2030. The total productivity growth rate is set with referencing to the historical GDP growth by sector. In the baseline, the irrigation efficiency and water use intensity are increased modestly at annual growth rates halved compared with that for meeting redlines and % of polluted water remain unchanged throughout 2030. Thus, the drivers of water demand are population and economic growth, besides moderate increases in water use efficiencies. To assess the impacts of water redlines on economy, we design six policy scenarios as noted in Table 1.

Table 1. A List of Scenarios Scenario name Scenario Specifications Business-As-Usual (BAU) BAU scenario assumes modest increase of water use efficiencies (annual growth rates at 50% of that for meeting redlines) and length of river reaches seriously polluted remain unchanged throughout 2030. Total Water Use Cap (REDTWUC) All other factors same as BAU, except the national and provincial “total

water use red line” of 700 billion m3is simulated. Industrial Water Use Intensity All other factors same as BAU, except the red line target of 40 m3 per Redline (REDIWUI) 10,000 RMB industrial GDP in 2030 is simulated. Increased Irrigation Efficiency All other factors same as BAU, except the “irrigation water use efficiency” Redline (REDIE) increase to 0.6 in 2030 is simulated. Surface Water Pollution Redline All other factors same as BAU, except 100% of water qualified for (REDSWP) domestic uses and other productive uses. All the above red lines (REDALL) All the “red lines” above are applied.

Impacts of Water Red lines on Regional Water Use Figure 44 shows average annual renewable surface water resources by BPU in China, simulated by the IGHM global hydrological model for the 1956-2000 period and bias-corrected on a mean annual basis and at the first-order river basin level according to mean annual runoff values reported for the same period in the “Comprehensive Planning.” The basic water resource situation of drier North and wetter South is clearly seen in the Figure 4.

Figure 4. Average annual renewable surface water resources by BPU, in 108 m3 a-1.

Note: Numbers on the map are BPU IDs. Renewable surface water resources are based on simulated gridded runoff for the 1956-2000 period using the IGHM hydrological model. Bias correction was conducted at the first-order river basin level, where necessary, to match average annual water resources reported for the same period in the “Comprehensive Planning.”

Total water demand in China is projected to continuously grow out to 2030 under moderate water use efficiency improvement3 in the domestic, industrial, and irrigation sectors, as shown in

3 Moderate WUE improvement represents halved WUE annual growth rates specified in the WUE redline for both irrigation and industrial sectors. Actual WUE values in the base year (i.e. 2014) vary across river basins per data published by the Ministry of

Figure 5. The growth is primarily driven by relatively strong growth of industrial GDP during this period. Water shortage in the “Business-As-Usual” (BAU) scenario is estimated to be 59.6 km3 in 2030 at the national level. Accelerated WUE improvement in irrigation (REDIE) or industrial sector (REDIWUI), representing decreased industrial water use intensity) as prescribed in the “three red lines” leads to demand reduction and declined water demand-supply gaps. The “REDTWUC” red line 4 , when being implemented without adopting red lines of water use efficiency and water pollution, results in pronounced decline in water supply and significant increase in water shortage. The “REDSWP” redline contributes to reducing water shortages, but at a significantly lower level, because only those river reaches with Class VI 5 water were considered unusable in the analysis. In the “REDALL” scenario, which include total water use control, increased water use efficiency, and pollution reduction, water shortage at the national level is estimated at 72.7 km3, which is greater than BAU by 13.1 km3.

Figure 5. Estimated national water demand and supply in 2030 under business-as-usual, single redline, and three-redline scenarios, in km3

Water Demand and Supply in 2030 (km3)

640 REDALL 712 679 REDTWUC 841 785 REDSWP 841 678 REDIWUI 724 773 REDIE 830 782 BAU 841

0 200 400 600 800

Supply Demand

Regionally, water shortage problem persists in North and Northwest, however in absolute term the East and Central China regions account for a large share of shortages due to high industrial water demand there (Figure 6). Northeast is projected to have little or no water shortage in most scenarios except the REDTWUC. The amount of water shortage is generally very low in Southwest, however the REDTWUC can cause major water shortages in the region.

Water Resources, China. 4 Total water use redline is implemented at the provincial level, using provincial level data in “The Evaluation Methods of Implementing the Most Stringent Water Resources Management” rectified by the State Council (Available at: http://www.gov.cn/zwgk/2013-01/06/content_2305762.htm). 5 Water quality in surface water bodies are categorized into five classes in China, i.e. classes I, II, III, IV, and V, according to the “Environmental Quality Standards for Surface Water (GB 3838-2002)” published in 2002 by the National General Bureau of Environment Protection (the predecessor of the Ministry of Environmental Protection, or MEP). There are also seriously polluted water bodies which are classified VI as “worse-than-Class V” and water of this category is not usable for any productive purposes.

Figure 6. Estimated regional water shortages in 2030 under business-as-usual, single redline, and three-redline scenarios, in km3

REDALL

REDSWP

REDIWUI

REDIE

REDTWUC

BAU

0 20 40 60 80 100 120 140 160 180 Northwest Northeast North East South Central Southwest

Water shortages in 2030 under each alternative scenario are compared with BAU, and the relative changes from BAU are shown in Table2. The REDTWUC scenario also leads to dramatic increases in water shortages, in the East, South Central, and Southwest, suggesting that there are considerable risks for these regions to overuse available water resources if water withdrawals are not regulated. The REDIE scenario leads to only marginal reduction in water shortages, and the REDIWUI leads to much higher water shortage reductions. Note in the red lines water use efficiency gains of irrigation is significantly lower than that of industrial water use, and the share of industrial water use keeps increasing and the share of agricultural water use keeps declining by 2030.

Table 2. Percent changes of water shortages from BAU, 2030. REDTWUC REDIE REDIWUI REDSWP REDALL Northeast 0.0 0.0 -0.2 -0.1 -0.2 Northwest 5.4 -0.4 -1.3 -0.1 0.0 North 2.9 -0.5 -2.1 -0.5 -1.8 East 36.2 -1.0 -6.0 -1.3 3.1

South 41.6 -0.9 -3.9 -1.2 8.0 Central Southwest 16.6 0.0 0.0 0.0 4.1

Sectoral water shortages in 2030 under BAU are shown in Table 3 along with percent changes of water shortages from BAU for each alternative scenario. Notably, industrial water shortages are high in the East, South Central and North, while agricultural water shortages are high in the East, South Central, North and Northwest. The Southwest has virtually no water shortage in both sectors under BAU; the Northeast has basically no water shortage for the industrial sector and only a relative small amount of water shortage for agriculture (0.2 km3). Domestic water shortage is not presented in Table because there is either no shortage or very low level of shortage in the domestic sector. Under alternative scenarios, the most pronounced industrial water shortages, in absolute term, occurs in the East and South Central, two regions with high level of industrialization in China. The North also experiences considerable level of shortages. Southwest and northeast are the two regions that experience little shortages, suggesting that demand management is indispensable even in water abundant regions. The REDTWUC scenario also results in considerable water shortages in all regions except Northeast. This implies that implementing water withdrawal regulations without simultaneously improving water use efficiency and reducing pollution may lead to significant industrial water shortages and associated economic damages. The REDIWUI scenario is able to reduce water shortages, but only marginally. Overall, the REDALL scenario reduces industrial water shortages in East, North, and South Central, but increases shortages in Northwest and Southwest. Agricultural water shortages show a similar pattern across regions and scenarios as industrial water shortages. The East, South Central, North, and Northwest show considerable levels of shortages across all scenarios; the Northeast only experiences low level of agricultural water shortages, and the Southwest only experiences shortages under the REDTWUC scenario and the REDALL scenario.

Table 3. Estimated regional industrial and agricultural water shortages in 2030 under BAU and alternative scenarios (in km3)

BAU REDTWUC REDIE REDIWUI REDSWP REDALL Northeast 0.0 0.0 0.0 0.0 0.0 0.0 Northwest 0.2 3.0 0.2 0.1 0.2 0.9 North 1.4 2.3 1.4 0.9 1.4 1.1 Industry East 8.2 21.7 8.2 4.0 7.6 5.5 South Central 2.8 10.4 2.8 1.2 2.7 1.9 Southwest 0.0 5.6 0.0 0.0 0.0 1.1 Northeast 0.2 0.2 0.2 0.0 0.1 0.0 Northwest 6.0 8.6 5.5 4.8 5.9 5.3 Agriculture North 8.8 10.8 8.3 7.2 8.4 7.4 East 20.9 43.6 20.0 19.2 20.2 26.7 South Central 11.1 45.1 10.1 8.7 10.0 19.9

Southwest 0.0 10.9 0.0 0.0 0.0 3.0

The Impacts on Crop Yield Agricultural water shortages directly affect irrigated crop yields. Table 14 shows the results of the impacts on crop yield by region under alternative scenarios in 2030, and average yield changes from the baseline. Among all scenarios, REDTWUC leads to the severest yield reduction. The impacts of REDIE, REDIWUI, and REDSWP are positive but modest. The overall impacts of all red lines on crop yields are mixed. Yield of some crops in some regions increase, while some other crops in other regions decrease. Comparatively, the impacts on crop yields in Northwest and East are larger, followed by Central and Southwest, while the impacts on the crop yields in North and Northeast are limited. The impacts on rice yield are most significant, followed by wheat and maize. There are also obvious impacts on soybean and cotton in certain regions. Specifically, under the scenario of REDTWUC, in the year of 2030, in the Northwest, the yields of wheat, rice and maize are estimated to decrease by about 6%. The yields of rice decrease by 6.5%, 5.8%, 9.1% and 12.4% in Southwest, Northwest, East and Central, respectively, under the scenarios of REDTWUC in 2030. The yields of wheat increase by 0.3%, 2.2% and 1.0% under the scenarios of REDIE, REDIWUI, and REDSWP in 2030, respectively. Under the scenario of REDALL, the impacts on Northwest are much smaller. The yields of wheat, rice and maize decrease by 1.8%, 3.2% and 1.5% in the Northwest in 2030, respectively. There are positive impacts in North under the scenario of REDALL, as the yields of wheat, rice and maize increase by 3.6%, 2.4% and 1.9%, respectively. The impacts on the East and Central China are complex. The rice yields decrease by 2.0% and 2.7%, while the wheat yields increase by 4% and 3.9% in 2030, respectively. Table 1. The change of yield by crop by region under alternative scenarios in 2030 (%)

Wheat Rice Maize Soybean Cotton Wheat Rice Maize Soybean Cotton REDTWUC REDSWP Southwest 0 -6.5 0 0 0 0 0 0 0 0 Northwest -5.9 -5.8 -5.7 -0.4 -0.9 0.1 0 0.1 0 0 North 0 0 -0.4 -0.2 0 0.4 0.3 0.4 0.1 0 Northeast 0 0 0 0 0 0 0.1 0 0 0 East -0.5 -9.1 -1 -0.8 -0.4 1.3 0.2 1.5 0.1 0.3

South Central -2 -12.4 -2.2 -1.7 -5.2 1.5 0.2 0.2 0.8 1.2

National -1.4 -8.9 -0.9 -0.4 -0.6 1 0.1 0.3 0.2 0.2 REDIWUI REDALL Southwest 0 0 0 0 0 0 -3.2 0 0 0 Northwest 0.1 0 0.2 0.1 0 -1.8 -3.2 -1.5 0 -0.3 North 2.9 1.9 1.4 0.5 0 3.6 2.4 1.9 0.6 0 Northeast 0 0.2 0 0 0 0 0.3 0.1 0 0 East 2.1 0.5 4.9 0.1 0.3 4.4 -2 6.4 0 0.6

South Central 3.3 0.7 0.5 1.1 1.6 3.9 -2.7 -0.5 1.1 1.5

National 2.2 0.5 1 0.2 0.2 3 -2.2 1.1 0.2 0.3 Note: The impacts of REDIE on crop yield is very limited, we did not report the results in the table to save page. Source: Results from China Water Resource Model

Impacts on Regional Economy These results from China water resource model are incorporated into China CGE model to access the impacts on economy. Table 5 shows the impacts on the national and regional GDP real growth rates. Facing an increasing water shortage, China’s national GDP is projected to continuously grow from 2017 to 2030 on an average rate of 5.92% annually under BAU. Similar national GDP growth rates are projected under the scenarios compared to the BAU, which indicating that, overall, redlines have little impacts on the national GDP growth rate. However, most impacts are localized. Table 6 presents the impacts on the national and regional GDP value. Similar to the regional impacts of the red line policy on water shortage, the impacts on the regional economy are much more significant than the impacts on the national economy. Overall, the red lines water policy has relative larger impacts on East China and South Central. Under the scenario of REDTWUC, there are negative impacts on East China, Central China, Southwest and Northwest, but positive on North and Northeast. The GDP growth will slow down by 0.12, 0.06, 0.06 and 0.03 percentage point, respectively, in East China, Central China and Southwest during the period from 2017-30, while the GDP growth will be up by 0.20, and 0.33, respectively, in North and Northeast under the scenario of REDTWUC. During the same period, the regional GDP in East, South Central, Southwest and Northwest will decrease by 470 billion (equivalent to 4.87% of regional GDP), 77 billion yuan (equivalent to 0.08% of regional GDP), 44 billion yuan (equivalent to 0.49% of regional GDP), and 8 billion yuan (equivalent to 0.09% of regional GDP loss), respectively. On the contrary, during the same period, the GDP in North and Northeast will increase by 270 billion (equivalent to the 1.06%), and 196 billion yuan (equivalent to 2.03% of regional GDP), respectively, during 2017-2030. The main reason is the shares of industrial water use in East and South Central China are much higher than these in Northeast and North with almost 34% and 25% of the total water use. As a result, East and South central will face more serious industrial water use shortage in the future along with the fast industrial development. The more severe industrial water shortage will result in the higher water prices and higher industrial production cost in East and South Central China than other regions, which will lead to the decrease of industrial outputs. In an integrated market, some of the capital and labor factors would flow out from the East and South central and into the North and Northeast. As a result, there are obvious negative economy impacts on East and South Central, while positive impacts on North and Northeast. Under the REDIE scenario, the impacts on East China are positive, the impacts on other regions are negative. Under the both scenarios of REDIWUE and REDSWP, the East China benefits much more from the improvement of industrial intensity and water pollution control, while for other regions, there are even small negative impacts. The reasons of the water constraints are improved much more in East China than other regions, which lead to the water price in East China decrease more, which further lower the cost in East China and further attract more labor and capital factors move in from other regions. The GDP value of East China will increase by 32 billion (equivalent of 0.33% of its GDP), 98 billion (equivalent of 1.01% of its GDP) and 21 billion (equivalent of 0.21% of its GDP) under the scenarios of REDIE, REDDIWUE and REDSWP, respectively. Under the scenario of REDALL, the impacts on East China and Central China are largest and positive, there are negative impacts on Southwest, Northwest and North, and the impacts on Northeast are relatively small. Under the scenario REDALL, the GDP growth will be up by 0.04, 0.02 percentage point in East and Central China, respectively, during the period from 2017-2030,

14 while the GDP growth will be down by 0.07 and 0.14, respectively, in Southwest and Northwest. During the same period, the cumulative GDP in Northeast, East and Central China will increase by 3 billion yuan (equivalent to the 0.03% of regional GDP), 58 billion yuan (equivalent to the 0.6% of regional GDP), and 15 billion yuan equivalent to the 0.15% of regional GDP), respectively. On the contrary, during the same period, the GDP of Southwest and Northwest will decrease by 31 billion yuan (equivalent to the 0.32% of regional GDP) and 40 billion yuan (equivalent to the 0.41% of regional GDP), respectively. The results indicate that the East region would be benefit due to the redline water policy, followed by the Central China region, while the Southwest and Northwest will be loss, there overall effects are little. Table 5. Annual Real Growth Rate of National and Regional GDP under BAU and alternative scenarios: 2017-2030 (%)

BAU REDTWUC REDIE REDIWUI REDSWP REDALL National 5.92 5.91 5.92 5.92 5.92 5.92 North China 5.85 6.05 5.84 5.82 5.85 5.85 Northeast 5.81 6.14 5.79 5.76 5.80 5.81 East China 5.95 5.83 5.97 6.01 5.97 5.99 Central China 5.94 5.88 5.94 5.94 5.95 5.96 Southwest 5.93 5.87 5.92 5.89 5.92 5.86 Northwest 5.91 5.88 5.89 5.86 5.89 5.77 Source: Integrated CGE water model results

Table 6. Cumulative Impacts on Regional GDP under Alternative Scenarios during 2017-2030 Central National North Northeast East China Southwest Northwest Change of GDP (Billion Yuan, 2014 constant price) REDTWUC -133 270 196 -470 -77 -44 -8 REDIE 9 -8 -6 32 -1 -4 -4 REDIWUE 34 -20 -14 98 -3 -17 -10 REDSWP 8 -2 -2 21 0 -5 -5 REDALL 3 -2 3 58 15 -31 -40 Equivalent ratio of GDP (%) REDTWUC -0.08 1.06 2.03 -4.87 -0.80 -0.46 -0.09 REDIE 0.01 -0.03 -0.06 0.33 -0.01 -0.04 -0.05 REDIWUE 0.02 -0.08 -0.14 1.01 -0.03 -0.17 -0.10 REDSWP 0.00 -0.01 -0.02 0.21 0.00 -0.05 -0.05 REDALL 0.00 -0.01 0.03 0.60 0.15 -0.32 -0.41 Source: Integrated CGE-water model results

Impacts on Regional Industrial Sectors Table 7 shows the cumulative impacts on the sectoral value added for selected industrial sectors during 2017-2030. The results show that the negative impacts on industrial value added are large under the scenario REDTWUC, while there are positive impacts under REDIE, REDIWUI, REDSWP and REDALL. Overall, the value added of all industrial sectors will drop by 2,784.9

15 billion yuan under the REDTWUC, which is equivalent to 3.9% of its value added. The negative impacts largely come from the sectors such as machinery and equipment, metal and metal products, chemical products, construction, electricity, gas and steam, and mining. Meanwhile, the industrial sectors will be benefited from the improvement of industrial water use efficiency. The industrial value added will be increased by 284.5 billion yuan (equivalent to 0.4% of its value added) during 2017-2030. The sectoral impacts are similar under the scenarios RDIE, REDSWP and REDALL, but with much small values. Table 7. The cumulative impacts on the value added of selected industrial sectors during 2017- 2030 (%) REDT REDIW REDSW REDAL REDIE Sector name WUC UI P L Change of Value Added (billion Yuan) All industrial sectors -2784.9 103.4 284.5 92.3 0.4 Mining -124.3 1.5 3.8 2.7 -12.5 Manufacture -2375.0 88.1 241.9 78.7 4.8 Textile -17.4 0.3 0.7 0.2 0.1 Paper making, Printing, Cultural and Educational Goods Manufacturing -41.4 1.5 4.3 1.2 1.5 Petroleum Processing, Coking Nuclear Fuel Processing -49.0 1.7 4.8 1.5 -0.3 Chemical products -309.9 12.3 34.3 10.8 1.0 Non-metal products -144.2 6.2 17.3 5.5 0.0 Metal and metal products -500.7 19.4 52.9 17.7 -3.1 Machinery and equipment -1098.5 41.8 114.1 36.3 14.7 Electricity, gas and steam -153.5 6.4 18.1 5.8 -2.5 Construction -254.6 8.8 24.3 7.7 -1.9 Equivalent ratio of Sectoral value added (%) All industrial sectors -3.92 0.15 0.40 0.13 0.00 Mining -1.85 0.02 0.06 0.04 -0.19 Manufacture -4.33 0.16 0.44 0.14 0.01 Textile -0.59 0.01 0.02 0.01 0.00 Paper making, Printing, Cultural and Educational Goods Manufacturing -1.60 0.06 0.17 0.05 0.06 Petroleum Processing, Coking Nuclear Fuel Processing -2.03 0.07 0.20 0.06 -0.01 Chemical products -4.31 0.17 0.48 0.15 0.01 Non-metal products -4.07 0.17 0.49 0.15 0.00 Metal and metal products -6.16 0.24 0.65 0.22 -0.04 Machinery and equipment -7.30 0.28 0.76 0.24 0.10 Electricity, gas and steam -3.65 0.15 0.43 0.14 -0.06 Construction -2.15 0.07 0.21 0.07 -0.02 Source: Integrated CGE water model results

IV. Conclusion and Implications The integrated regional dynamic CGE model and water resource model is developed to assess the regional and sectoral impacts of 2030 water red lines policies in China. Five policy scenarios are designed to capture the impacts of single red line and the combined effects of all red lines. The paper has the four main conclusions. First, water scarcity is a problem not only in the hydrologically dry North and Northwest, but also in the wetter East and South Central where rapidly growing water demand outstrips supply. The demand growth is primarily driven by

16 relatively strong growth of industrial GDP during this period. The competition for water between agriculture and industry becomes intensified in East and South Central. Not only agriculture, but also industrial sectors would be affected by water shortages. Second, the impacts of red lines water policy on East are significant and largest, followed by South Central and Northeast. Imposing the total water use cap leads to dramatic increases in water shortages and large economy losses in the East, South Central, and Southwest. The percent changes of water shortages from BAU in 2030 would be 36%, 42% and 17%, respectively, for East, South Central, and Southeast. The cumulative negative impacts on regional GDP reach 4.87% in East, 0.8% and 0.46% in South Central and Southwest, respectively. The main positive impacts of water use efficiency improvement and water pollution control are also from East. Third, the impacts of red line water policy on different sectors are varied. Industrial sectors with the higher water use intensity such as machinery and equipment, metal and metal products, chemical products and non-metal products are affected most. The value added of all industrial sectors would be lost about 3.9% under the scenario of total water use cap. However, machinery and equipment would be lost 7% of its value added, followed by metal and metal products with a loss of 6%, and chemical products and non-metal products with more than 4%. Similarly, these industrial sectors also benefit more from the improvement of industrial water use efficiency than other sectors. Fourth, the red line policy has significant impacts on irrigation water and crop yields in Northwest, followed by East, while the impacts on North and Northeast are limited. Rice yield is affected most significantly, followed by wheat and maize. The above findings have a number of key policy implications. First, the water regulation of total water use cap needs to go hand in hand with water use efficiency improvement and pollution reduction to minimize water shortage and associated economic cost. Technologies to improve water use efficiency can play an important role in mitigating water shortage. The water pollution control can augment water supply, though small. Second, water transfer and other measures will be also an effective mechanism to mitigate water shortage where provincial level withdrawal regulation significantly increases shortages. Administering the total water use control red line essentially establishes water rights at the provincial and lower administrative levels, thus facilitating market-based water re-allocation between willing buyers and willing sellers. Third, restructuring the regional economy should be considered as key to cope with water scarcity in China. Water scarce regions should develop less water intensive industries (e.g., services) as a priority, and monitor the development of polluted industries closely.

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Appendix Table A1. List of Sectors in 2014 China SAM Agriculture 32 Chemistry 1 Rice 33 Non-metallic mineral products 2 Wheat 34 Pressing of metals 3 Maize 35 Metal products 4 Other grain 36 Machinery 5 Bean 37 Transport equipment 6 Oil crop 38 Electrical machinery 7 Cotton 39 Communication equipment 8 Sugar 40 Measuring instruments and machinery 9 Vegetable 41 Other manufactures 10 Fruit 42 Recycling waste 11 Other crops 43 Electric and heat power 12 Pork 44 Gas supply 13 Beef 45 Production and Distribution of Water for industrial use Production and Distribution of Water for household 14 Mutton 46 Construction 15 Poultry Services 16 Other livestock 47 Transport 17 Forestry 48 Post 18 Logging and transport of wood 49 Information and computer services 19 Fishing 50 Trade 20 Agricultural services 51 Hotel and restaurant 21 Eggs Industry 52 Finance 22 Mining 53 Real estate 23 Petroleum and natural gas 54 Leasing 24 Metal mining 55 Research 25 Nonmetal mining 56 Technical services 26 Foods and Tobacco 57 Environment and public facilities 27 Textile 58 Other private services 28 Leather and products 59 Education 29 Wood manufacture 60 Health 30 Paper and printing 61 Entertainment 31 Petroleum 62 Other public services

Table A2. Regions in the SAM and CGE Model Region Provinces Northeast Liaoning, Jilin, Heilongjiang North Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia Northwest Shaanxi, Ningxia, Xinjiang, Gansu, Qinghai East Shanghai, Anhui, Shandong, Jiangsu, Jiangxi, Zhejiang, Fujian Central China Guangdong, Guangxi, Henan, Hainan, Hubei, Hunan Southwest Yunnan, Sichuan, Xizang, Guizhou, Chongqing