China's water–energy nexus: greenhouse-gas emissions from groundwater use for agriculture

We use extensive survey data collected in rural China by the Centre for Chinese Agricultural Policy (CCAP), of the Chinese Academy of Sciences. CCAP conducted several large field surveys during the period between 2004 and 2006, covering more than 500 randomly selected villages in 11 provinces, representing the main groundwater using provinces. Sample screening for villages with no tubewells and quality control checking for survey errors of groundwater levels and pump lifts reduced the number of villages to 366 for our analysis. Figure 2 shows the location of the 366 villages and the 11 provinces. The surveys covered population, cultivated area, groundwater and surface water irrigated area, the number of deep and shallow tubewells and their corresponding pump lift, groundwater level, power sources of pumps (electricity or diesel) and socio-economic characteristics of the villages. Full details of the surveys and sampling techniques can be found in Wang et al (2006, 2007, 2009).

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2.1.1. Energy use rate.

The main components of energy use associated with irrigated agriculture are primarily related to processes required to apply water to crops in the field by lifting, conveying, and in some cases, pressurizing it (Rothausen and Conway 2011). Lift relates to the vertical distance over which water is raised prior to application and is the most crucial factor but energy use varies both with the source of water (groundwater or surface water) and the application method (i.e. whether it is gravity fed or pressurized irrigation system). The efficiencies of the power generation and supply, the pump and pipeline system also influence energy use. Here we focus on energy for abstraction of water and for this purpose we apply a basic theoretical physical relationship, which prescribes the energy required to lift 1 m³ of water (with a density 1000 kg m⁻³) up 1 m at 100% efficiency is 0.0027 kWh (see equation (1), Rothausen and Conway 2011)

$$\begin{eqnarray} &&\text{Energy~ (kWh)}=\frac{9.8~\mathrm{m}~{\mathrm{s}}^{-2}\times \text{Lift~ (m)}\times \text{Mass~ (kg)}}{3.6\times 1{0}^{6}\times \text{Efficiency}~(\% )}. \end{eqnarray} \tag{ 1 }$$

Given a lack of detailed knowledge of the efficiency of the individual pumps, we select efficiencies according to available information on pumping efficiency, Chinese conditions and studies of energy use for irrigation pumping in India where the pumping efficiencies are around 30% (Nelson et al 2009, Shah 2009). Overall efficiencies in diesel powered pumping systems result from the compounded efficiencies of the diesel engine (typically 15–40%), transmission (60–100%), pump (40–80%) and pipes (30–95%), giving an overall efficiency of 0.5–27% (Fraenkel 1986), for which we have selected the approximate mid-point of 15%. With higher efficiencies of electrical motors of 75–85% (Fraenkel 1986, Kay 2008) and the direct coupling of motor and pump within down-hole submersible pumps, higher overall efficiencies of 30–60% are achieved within electrical pumping systems, for which we have used 40%. The overall efficiency of using electricity to power pumps is reduced further by inefficiencies in the transmission and distribution (T&D) of electricity. There is some disagreement about the T&D losses in China but according to three studies of the rural electricity network it is between 10 and 19% (Li et al 2007, Sun 2006, Xia 2003). We adopt a mid-range value of 15% T&D loss. Applying equation (1) and the selected efficiencies, we can estimate by village the average energy use required to pump/lift a cubic metre of groundwater (kWh m⁻³). The field survey showed that all tubewells categorized as deep relied on electric pumps. Other studies also indicate that most pump sets run on electricity in China (e.g. Zhu et al 2007) and our study confirms this with more than three-quarters of the surveyed pumps being electric (also see table 1).

Table 1.  Basic characteristics of the 366 surveyed villages in 11 provinces in China.

Province	No. of surveyed villages	Average village irrigated area	Proportion of groundwater-fed irrigated areas	Average no. of tubewells in villages	Proportion of deep tubewells	Proportion of diesel pumps	Average deep pump lift	Average shallow pump lift
		(ha)	(%)		(%)	(%)	(m)	(m)
Hebei	93	96	90	18	43	10	83	34
Henan	56	114	81	67	10	67	42	24
Shaanxi	25	125	67	28	29	0	98	50
Shanxi	46	96	77	8	59	1	82	59
Inner Mongolia	56	232	67	56	38	8	44	29
Liaoning	45	139	60	113	11	17	35	17
Ningxia	10	264	9	50	11	0	40	24
Gansu	27	294	64	19	49	0	80	29
Hubei	4	238	16	46	9	2	59	23
Hunan	1	26	15	2	100	0	50	NA
Shandong	3	18	93	7	0	0	NA	58
Total	366	149	69	38	23	24	61	35

2.1.2. GHG emission rate.

The UK Department of Environment, Food and Rural Affairs/Department of Energy and Climate Change GHG conversion factors for diesel (0.320 21 kgCO₂e kWh⁻¹) and electricity produced in China (0.947 73 kgCO₂e kWh⁻¹) are used to derive the average GHG emission rate (kgCO₂e m⁻³) based on the combination of power sources for pumps in each village. Equation (2) illustrates this calculation, with each energy use rate expressed as a proportion of the total number of pumps under the assumption that all pumps in the village are used equally. To obtain a provincial average GHG emission rate we weight the village emissions by its area under groundwater irrigation. This proportional weighting captures the greater importance of the villages with large areas of groundwater irrigation and discounts villages where groundwater pumps were not used for irrigation purposes.

$$\begin{eqnarray} \displaystyle \fl \text{GHG~ emission~ rate}\left(\frac{{\mathrm{kgCO}}_{2}\mathrm{e}}{{\mathrm{m}}^{3}}\right)&&\displaystyle \\ \displaystyle ={\text{Energy~ use~ rate}}_{{\mathrm{Deep}}_{\mathrm{Electric}}}\left(\frac{\mathrm{kWh}}{{\mathrm{m}}^{3}}\right)&&\displaystyle \\ \displaystyle \times ~0.94773\frac{{\mathrm{kgCO}}_{2}\mathrm{e}}{\mathrm{kWh}}&&\displaystyle \\ \displaystyle +~{\text{Energy~ use~ rate}}_{{\mathrm{Shallow}}_{\mathrm{Electric}}}\left(\frac{\mathrm{kWh}}{{\mathrm{m}}^{3}}\right)&&\displaystyle \\ \displaystyle \times ~0.94773\frac{{\mathrm{kgCO}}_{2}\mathrm{e}}{\mathrm{kWh}}&&\displaystyle \\ \displaystyle +~{\text{Energy~ use~ rate}}_{{\mathrm{Shallow}}_{\mathrm{Diesel}}}\left(\frac{\mathrm{kWh}}{{\mathrm{m}}^{3}}\right)&&\displaystyle \\ \displaystyle \times ~0.32021\frac{{\mathrm{kgCO}}_{2}\mathrm{e}}{\mathrm{kWh}}.&&\displaystyle \end{eqnarray} \tag{ 2 }$$

2.1.3. Agricultural water use.

2.2.1. Estimated pump lift.

To determine GHG emissions in the 20 non-surveyed provinces we extrapolate pump lift (the most essential factor for energy use, see equation (1)) from observations of groundwater levels for different aquifer types for year 2005, from unpublished data and published data in the China Groundwater Level Yearbook from GEO-Environmental Monitoring Institute (China GEO-Environmental Monitoring Institute 2006). Pump lift is greater than groundwater level because pumping causes a localized lowering of the aquifer groundwater level. To define a relationship between groundwater levels and pump lifts, a linear regression of these variables is used based on the data from the 366 surveyed villages. The correlation between groundwater level (x) and average pump lift (y) is shown in equation (3)

$$\begin{eqnarray} &&y=0.906 x+21.75\tqs {R}^{2}=0.62 \end{eqnarray} \tag{ 3 }$$

with the pump lift being an average of 20 m deeper than groundwater level (supplementary figure S1 available at stacks.iop.org/ERL/7/014035/mmedia). This relationship was used with the groundwater level observed in the 20 non-surveyed provinces to generate an estimate of pump lift.

2.2.2. Estimated energy use rate and emission rate.

2.2.3. Agricultural water use.

This step involves simply adding together the emissions from the surveyed and non-surveyed provinces to obtain a national estimate of total GHG emissions from groundwater use for irrigation.

We explore the sensitivity of our results to varying assumptions about efficiency and pump lift. Figure 4 shows the average GHG emission rate for the 366 surveyed villages with a range of values. Our estimate uses 85% T&D efficiency, 40% electric pump efficiency and 15% diesel pump efficiency, and average deep and shallow pump lift for each village. By changing these factors in intervals of 5% or 5 m (absolute changes), we can evaluate their individual effects on the GHG emission rate. Whilst there is some debate about the rate and extent of declining groundwater levels in China (Wang et al 2007, 2009), it is likely that in many areas pump lifts will increase. An average 5 m deeper pump lift would increase total GHG emissions by almost 10%. Yet figure 4 shows that changes in the efficiency of electric pumps have the largest effect on GHG emission rates. The GHG emissions would more than double with a 20% decrease in electric pump efficiency, whereas a 20% increase in electric pump efficiency will reduce the emission rate by a third. Changes in diesel pump efficiency have the least effect. Accurate data on pump efficiency and its influencing factors will be important for estimating GHG emissions and appropriate pump selection and regular maintenance crucial for limiting emissions.

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National estimates of energy use and GHG emissions from water delivery for irrigation are, to our knowledge, only available for India and the US. India is the world's largest irrigator and has experienced even greater development of groundwater abstraction than China, with the area of groundwater irrigation quadrupling since 1950 (Shah et al 2004). Emissions from groundwater pumping for irrigated rice were estimated to be 58.7 MtCO₂e in 2000 (Nelson et al 2009). Another estimate, including all water pumped or lifted for irrigation, was 95.0 MtCO₂e yr⁻¹ (Shah 2009), roughly 6% of India's total GHG emissions. Both studies show much higher GHG emissions than our results for China, mainly because of India's greater use of groundwater for agriculture but partly due to differences in methodology (see supplementary table S1 for more detail available at stacks.iop.org/ERL/7/014035/mmedia). Nelson et al (2009) applies a similar methodology to ours, with minor differences in pump lifts and assumptions about pump efficiencies and power source distribution. Their overall emission rate (MtCO₂e km⁻³) is also similar to ours, however, the modelled agricultural groundwater use in India is 195 km³ (Nelson et al 2009) compared with approximately 93 km³ in China. Shah (2009) bases calculations purely on information about the number of well structures, standardized pump energy requirements and operating hours, without considering actual agricultural water use. This approach includes energy used for pumping surface water and the results for groundwater pumping are much higher (∼93 MtCO₂e yr⁻¹). The village survey data used for this study show a very weak relationship between the area under groundwater irrigation and the number of tubewells (see supplementary figure S2 available at stacks.iop.org/ERL/7/014035/mmedia) which suggests that individual wells/pumps support widely varying areas of irrigation and supply water for purposes other than irrigation. Hence, calculating energy use based on the number of well structures may not be as accurate. In the US, the world's third largest irrigator, where irrigation accounts for 34% of the water use, an estimate of energy use and GHG emissions from pumping water for irrigation was 15.8 MtCO₂e in 2005 (Griffiths-Sattenspiel and Wilson 2009).

Irrigation in China relies heavily on surface water from rivers and reservoirs which sometimes also require energy use for pumping and conveyance. However, information on this is sparse and to our knowledge no quantification of aggregate energy use exists. Currently, power equipment for pumping surface water resources in China has a capacity of 22 million kW (Irrigation and Drainage Center 2007), and the related energy use is likely to be considerable. Imbalances in local and inter-province water resources distribution and demand have exacerbated problems of water scarcity and enhanced the energy intensity of water supply. For example, China has many large-scale inter-basin water transfers. Out of the seven established, two of them include a total of 24 pumping stations to irrigate 2.89 × 10⁶ ha (Shao et al 2003). A further seven projects are planned, including the south to north water transfer scheme. Four of the proposed projects are to include a total of 37 pumping stations to irrigate 5.80 × 10⁶ ha (Shao et al 2003). The construction and operation of this water supply infrastructure will require energy as will water quality treatment where this is necessary.

While the abstraction/supply of water is proportional to the lift and distance over which it is pumped/transported, the energy required to apply water to fields is dependent on the irrigation method/technology. Across the largest proportion of irrigated land in China water is applied as flood/gravity irrigation, yet water conservation policies are promoting the introduction of pressurized irrigation systems (e.g. sprinkler, drip) which require energy to operate. These technologies generally provide a larger degree of control and depending upon other factors can improve water use efficiency considerably, so that any additional energy use may be offset by water savings. However, only 3.5% of the irrigated areas in our surveyed villages were equipped with pressurized irrigation systems and there is little evidence for widespread or effective adoption of water-saving technologies in China (Lohmar et al 2003). Many argue that a lack of economic incentives to save water is a barrier to the uptake of water-saving practices (e.g. Blanke et al 2007), while others emphasize that problems with water rights (e.g. institutional and policy dimensions of ensuring stability of supply and sufficient access) are also critical (Webber et al 2008). Nevertheless, potential exists to realize co-benefits in water and energy savings through improved irrigation technology and this opportunity may be under-recognised in the design and cost benefit analysis of water-saving practices and policy in China and elsewhere (Rothausen and Conway 2011).

Agriculture in China is by far the largest water user with irrigated agriculture generating around 70% of total grain production, yet the national crop deficit was 11% in 2000 (Amarasinghe et al 2005). With a growing population and rising living standards, the demand for food, particularly animal products, is increasing. Shifts in food consumption patterns and population growth may lead to additional unconstrained requirements of 407–515  km³ water for food production by 2030, compared with 2003 (Liu and Savenije 2008). Such large increases would likely induce further water resource deterioration and higher energy intensive supply. Intensification and expansion of irrigated agriculture is often seen as necessary to meet future demand and to achieve growth in the agricultural sector and such measures will require more water and more energy for abstraction, transportation and application to crops.

Given China's continued rapid economic transition, the demand for water in the urban and industrial sectors is also likely to increase (Kahrl and Roland-Holst 2008, Xiong et al 2009). Re-allocation of already scarce water resources from agriculture to other sectors with higher output/water use ratios may become increasingly necessary (Kahrl and Roland-Holst 2008). During the past 60 years, with expansion of industrialization and urbanization, the share of water allocated to agriculture has declined from 97% in 1949 to 62% in 2009 (Ministry of Water Resources 2009). During this process, increasing (and sometimes unsustainable) exploitation of groundwater resources has played an important role in sustaining irrigated agriculture. Between 1978 and 2003, the number of groundwater tubewells across China more than doubled (Wang et al 2007) and with increasing privatization of tubewells it is likely that development will continue to exacerbate declining trends in groundwater levels. Groundwater utilization in northern China is over 70% of known resources in the region. In contrast, 70% of all China's groundwater resources are located in southern China, where less than 30% of the resources are currently in use (Wang et al 2007). Drought in parts of southern China (e.g. Qui 2010) may promote groundwater use to secure yields, and multi-climate model averages project drier conditions in southern China out to the 2050s (Li et al 2011). These pressures point towards further groundwater development across China with implications for energy use.

Strategic reform of water resources allocation has been initiated by the Chinese Government with attempts to regulate agricultural water use through a water use rights system (Huang et al 2009). The system is designed to gradually reduce surface water quotas for farmers to transfer agricultural water to other sectors. However, studies show that farmers compensate the 'loss' of surface water by using more groundwater to maintain production practices and yields (Zhang 2007, Pittock 2011). Regulation of groundwater use is well known to be difficult (e.g. Shah et al 2003). These conditions have promoted a shift in policy from supply-side measures towards more water 'efficient' agriculture and irrigation technology innovations. China is to an increasing degree investing in water-saving technologies for farming. Programmes under China's Agenda 21: White Paper on Population, Environment and Development and 'Dryland Farming' are major initiatives that provide support for selected research facilities which target increasing water utilization efficiency by 20–30% (PRC 1994). Various approaches to improve regulation and compliance are also being tested as part of water-saving programmes (World Bank 2009). Since 1991, the water use intensity of Chinese agriculture has decreased, as agricultural investments in channel lining, field levelling, pressurized irrigation systems etc have reduced inefficiencies and water losses (Wu et al 2010).

Yet, many of these technologies require energy and, pressurized irrigation systems especially, are often coupled with groundwater use. It will be a challenge to harmonize water conservation with the 12th Five Year Plan targets of reducing energy and carbon intensity by 16% and 17%, respectively (Hannon et al 2011). Water-saving technologies need to be assessed in relation to energy trade-offs and potential co-benefits. Our sensitivity analysis highlights the importance of optimization of the efficiency of electric pumps as a promising way of decreasing energy use (section 3.1). Research from India also shows widespread low efficiencies of agricultural pumps, with significant potential for economic (and hence energy) savings through improved standards (Sant and Dixit 1996). The use of renewable energy sources for pumping and application of water should also be explored, although projections of renewable energy dissemination in India show that water pumping technologies may not reach their maximum potential even after 25 years (Purohit and Kandpal 2005).