Emergy evaluation of the contribution of irrigation water, and its utilization, in three agricultural systems in China

Abstract

Emergy theory and method are used to evaluate the contribution of irrigation water, and the process of its utilization, in three agricultural systems. The agricultural systems evaluated in this study were rice, wheat, and oilseed rape productions in an irrigation pumping district of China. A corresponding framework for emergy evaluation and sensitivity analysis methods was proposed. Two new indices, the fraction of irrigation water (FIW), and the irrigation intensity of agriculture (IIA), were developed to depict the contribution of irrigation water. The calculated FIW indicated that irrigation water used for the rice production system (34.7%) contributed more than irrigation water used for wheat (5.3%) and oilseed rape (11.2%) production systems in a typical dry year. The wheat production with an IIA of 19.0 had the highest net benefit from irrigation compared to the rice (2.9) and oilseed rape (8.9) productions. The transformities of the systems’ products represented different energy efficiencies for rice (2.50E+05 sej·J^-1), wheat (1.66E+05 sej·J^-1) and oilseed rape (2.14E+05 sej·J^-1) production systems. According to several emergy indices, of the three systems evaluated, the rice system had the greatest level of sustainability. However, all of them were less sustainable than the ecological agricultural systems. A sensitivity analysis showed that the emergy inputs of irrigation water and nitrogenous fertilizer were the highest sensitivity factors influencing the emergy ratios. Best Management Practices, and other agroecological strategies, could be implemented to make further improvements in the sustainability of the three systems.

Keywords

emergy / evaluation / irrigation / agriculture / sustainability

Introduction

Continued climate variability, population growth, and rising food prices, are issues that present ongoing challenges to the achievement of food and water security in many countries (Gohar et al., 2013). China is among those that are racing to develop potential adaptation strategies to achieve these two goals (Larson, 2013). Irrigation improvement has been identified as an important adaptation strategy (Connor et al., 2012). The strong relationship between crop revenue and irrigation provides evidence of the importance of irrigation in past and future poverty alleviation in China (Huang et al., 2006). Yet, irrigated agriculture, as the major user of water and land resources in China and other countries, is facing the risks of water scarcity and environmental issues (Chen et al., 2011; Özerol et al., 2012). Modernization of irrigation systems has become a worldwide trend, intended to increase water productivity through gains in crop yield, and reductions in the use of irrigation water (Playán and Mateos, 2006; Chen et al., 2011). The Chinese government issued its first national outline for agricultural water-saving development (2012–2020) in December, 2012. According to this plan, the size of the irrigated area will increase from 9.25E+08 Mu (1Mu=667 m²) in 2012 to 1.00E+09 Mu in 2020, and the efficiency of irrigation water use will rise from 0.50 in 2012 to 0.55 in 2020. The investment in agricultural water-saving and irrigation improvement projects is estimated increase greatly in the near future. Therefore, the scientific analysis of these project proposals is of vital importance in order to ensure high efficiency in the use of investments. Quantifying the contribution of irrigation water and the sustainability of irrigated agriculture plays a major role in the cost–benefit analysis of these projects, and decisions regarding policy in irrigation development.

Several methods have been used in previous studies to estimate the contribution, benefit, or value of irrigation water. These can be classified, mainly, into the following categories: conventional market-based approaches, alternative or replacement cost approaches, observed, indirect or implicit, or revealed preference approaches, and stated preference approaches (Jiang, 1998; Blamey et al., 1999;Faux and Perry, 1999; Shen et al., 1999; Kim and Schaible, 2000; Reca et al., 2001; Barton, 2002; Seyam et al., 2002; Tsadilas and Vakalis, 2003; Jabeen et al., 2006; Hussain et al., 2007; Chen et al., 2009b; Hussain et al., 2009). However, these methods mainly focus on the economic, social, cultural, or environmental value of irrigation water using a monetary unit. The monetary valuation of natural capital may be useful in demonstrating its economic value; but it is insufficient to measure the intrinsic worth of the life-support function of the ecosystem (Costanza et al., 1998). Natural resource overexploitation and ecosystem degradation are often justified using monetary valuation of natural capital as the only parameter driving human action (Pulselli et al., 2011). Thus, the development of a set of indicators that can be used to determine the value of irrigation water is needed, that provide results that are robust and meaningful in guiding decision making, but simple enough to be computed with resource and data constraints (Hussain et al., 2007). A unifying approach with an objective, uniform unit of measure, can help to solve this and other problems, such as that of determining solar energy units (emergy) and land equivalents (ecological footprints) (Patterson, 2002; Chen et al., 2009b; Chen et al., 2011).

Emergy is the available energy, of a specific type, that is used in transformations, directly and indirectly, to make a product or service (Odum, 1996; Yan and Odum, 2001; Lan et al., 2002). Emergy evaluation is used to account for different forms of energy and resources, including both free environmental, and purchased inputs (Yan and Odum, 2001; Chen and Chen, 2011). Emergy evaluation has suffered a lot of resistance and criticism. The issues have included theoretical arguments, problems with transformity calculations, accounting procedures, co-products or splits treatment, uncertainty and sensitivity. Even so, it has become a frequently used holistic approach that provides a uniform unit of measure for valuating ecosystem goods and services (Hau and Bakshi, 2004; Sciubba and Ulgiati, 2005; Mayer, 2008; Ingwersen, 2010; Li et al., 2011a; Rugani and Benetto, 2012). Emergy evaluations of contributions of water at different levels of the global and regional hydrological cycle, and the energy conversion process, could also be evaluated using the approach proposed in this study (Chen et al., 2009b).

The emergy concept has been used in numerous studies to evaluate different aspects of water (Brown and McClanahan, 1996; Odum, 1996; Buenfil, 2001; Kang and Park, 2002; Chen et al., 2008; Chen et al., 2009a, b; Chen and Chen, 2009; Lv and Wu, 2009; Brown et al., 2010; Chen et al., 2011; Chen et al., 2012; Shao et al., 2013), and has also been applied to the analysis of different agricultural systems on many scales (Bastianoni et al., 2001; Lefroy and Rydberg, 2003; Cavalett et al., 2006; Chen et al., 2006; Chen and Chen, 2006; Martin et al., 2006; Rydberg and Haden, 2006; Jiang et al., 2007; Zhang et al., 2007; La Rosa et al., 2008; de Barros et al., 2009; Lu et al., 2010; Chen and Chen, 2012; Lima et al., 2012; Zhang et al., 2012). However, this technique has rarely been used to evaluate irrigation and its linkage to irrigated agriculture development (Chen et al., 2011; Chen et al., 2013). Chen et al. (2013) reported an emergy evaluation of irrigation water from the perspective of the irrigation water production process (Chen et al., 2013). This report focuses on emergy analysis applied to the utilization process of irrigation water for different agricultural productions. The current study will help to understand the contribution of water to the whole process of irrigation water production and utilization.

The main objectives of this study were: (i) to compare the emergy contributions of irrigation water in the production of three different irrigated crops, and (ii) to evaluate the corresponding agricultural systems with regard to their resource use, productivity, environmental impact and overall sustainability. The three systems studied were rice, wheat, and oilseed rape productions, in an irrigation pumping district in China. The typical features associated with the irrigated plain areas in southern China, small irrigation pumping districts, and major irrigated crops, were represented by these three systems. The remainder of this paper is organized into the following sections. Section 2 presents a brief overview of the study area, the data source, and the emergy evaluation and sensitivity analysis methods, including several emergy indices. Results are then presented and discussed in Section 3. Section 4 concludes by summarizing the main results and pointing to some implications based on the emergy evaluations.

Methods

Study area and data

The study area is located in Hongqiao Town, in Taixing City of the Jiangsu Province, China (31°55'N, 119°38'E). It is in the northern subtropical maritime monsoon climate zone, where irrigation is essential for agricultural production, especially in dry years. The main irrigated crops are rice, wheat and oilseed rape. Irrigation is accomplished by pumping water from the local river, and then distributing it via concrete-lined canals into the farmlands. The local river was mainly extracting water from the lower Yangtze River in dry seasons. The main data for the production of these three crops, under the condition of a satisfied demand for water, were averaged using the annual data from field surveys conducted from 2008 to 2011(Table 1). Since water availabilities mainly depend on the sum of rainfall and irrigation use, the data for rainfall and irrigation requirements (No. 2 and No. 3 in Table 1) in a typical dry year were used to evaluate the contribution of irrigation water. A typical hydrological year was selected based on the monthly average rainfall from 1954 to 2010 (TWCB, 2011<FootNote>

TWCB (2011). The planning report on agricultural water conservancy projects in Taixing City. Taixing Water Conservancy Bureau (TWCB)

</FootNote>). These data were used to evaluate the irrigated agricultural systems. Irrigation water production was addressed using the evaluated results, from a nearby irrigation pumping district, adopted from a previous report (Chen et al., 2013).

Emergy evaluation and sensitivity analysis methods

Quantifications of the contribution of irrigation water were analyzed to produce an emergy evaluation of irrigated agricultural systems. Emergy assessments for agriculture can follow the same procedure as was presented originally. The general methodology of emergy analysis can be found in detail in the original work (Odum, 1996), and in a series of emergy folios (Odum, 2000; Odum et al., 2000; Brown and Bardi, 2001; Brandt-Williams, 2002). The first step for an emergy evaluation is to draw energy systems diagrams, using specific symbolic modeling language (Odum, 1996). This is necessary to identify various sources of flows and major processes in the system, and to depict the environmental base and its connection to the economy. An aggregated system diagram of a typical irrigated system in China that produces rice, wheat, or oilseed rape, is presented in Fig. 1. In addition to irrigation water, the inputs to an irrigated agriculture production system are generally aggregated into the following categories: 1) renewable resources (sunlight, wind and rain) (R), 2) nonrenewable resources (soil erosion) (N), 3) purchased materials (fertilizers, pesticide and seeds) (M), and 4) services (machinery service and labor) (S). The metabolism of energy and materials in this system is thereby characterized by the combination of R, N, M and S. The total emergy yield (Y) is theoretically equal to the total emergy used (Y=R+N+M+S). System outputs are the products of rice, wheat and oilseed rape respectively.

The second step is to establish emergy tables (Tables 2–4). All of the material and energy flows, presented in the energy systems diagram, are converted into solar emjoules (sej) using transformities (Odum, 1996). These transformities are derived mainly from previous studies that used emergy evaluations (Odum, 1996; Brandt-Williams, 2002). The global emergy baseline of reference in this study is 15.83E+24 sej·yr^-1. The new transformities for rice, wheat and oilseed rape, as the systems’ products, could be calculated by dividing the total emergy yield (Y) in the specific system by the energy or mass of each product. The third step is to calculate emergy indices in order to evaluate the sustainability of a system (Table 5). Several emergy indices have been introduced to assess agriculture: (a) the emergy yield ratio (EYR), EYR=Y/(M+S), the total emergy used per unit of emergy invested; (b) the emergy investment ratio (EIR), EIR= (M+S)/(R+N), the emergy investment needed to exploit one unit of local renewable and nonrenewable resource; (c) the environment loading ratio (ELR), ELR=€(M+N+S)/R, the total nonrenewable and imported emergy used per unit of local renewable resource; and (d) the environmental sustainability index (ESI), ESI=EYR/ELR, the emergy yield per unit of environmental loading (Odum, 1996; Brown and Ulgiati, 1997; Ulgiati and Brown, 1998; Chen et al., 2006; Jiang et al., 2007; Chen et al., 2011). Besides these indices, two new indices were developed to assess the emergy contribution of rationed irrigation water in a typical dry year. These were calculated as follows:

The first new index scales irrigation water input to an emergy basis for the irrigated agricultural system. The fraction of irrigation water (FIW) is computed as % of total emergy used (U) arising from irrigation water (R_I):

(1)FIW=R_I/U.

The second new index, irrigation intensity, provides a cost-benefit ratio for irrigated agriculture. The irrigation intensity of agriculture (IIA) compares the emergy yield from agriculture (irrigated crops) (Y) to the emergy in irrigation water (R_I):

(2)IIA=Y/R_I.

The above two indices depict the emergy contribution of irrigation water from two perspectives: (i) FIW is a measure of the emergy input of irrigation water to agricultural production, and (ii) IIA is the emergy cost-benefit ratio of irrigation water. Since irrigation water is considered to be a component of both inputs and outputs of the irrigated agricultural system, it appears in both the numerator and denominator of the calculation formulae for FIW and IIA. Values of FIW and IIA that approach one indicate the most deleterious situation found in agricultural production. The higher the value of FIW, the greater the contribution of irrigation water to the irrigated agriculture system being considered. A large IIA value indicates a high contribution to productivity from irrigation water use; but it cannot indicate the pressure that irrigation water use places on the environment.

In order to depict environmental pressure resulting from irrigation activities, the indices of ELR and ESI are helpful for the sustainability analysis. At small scales, there is an inverse relationship between these two indices because the emergy yield (Y) from a specific irrigated crop production system is assumed to be its total emergy use (U). Yet at large scales, the two indices are relatively independent, due to the difference between Y and U. Thus, these two indices can be used for comparative purposes (e.g., the evaluation of a system of integrated irrigation works across different irrigated crops), when evaluating the irrigation performance of different irrigation districts. This study focused on the emergy contribution of irrigation water to different crop production systems within one irrigation district.

Emergy evaluation relies on extensive calculations with large amounts of data. This possibly introduces uncertainty (Voora and Thrift, 2010). Yet, averaged transformities have been used frequently in specific case studies, with no knowledge of the degree of the resulting output (Hau and Bakshi, 2004; Voora and Thrift, 2010). The lack of uncertainty analyses has hindered the wider application and acceptance of this methodology (Li et al., 2011a). Thus, uncertainty analyses should be incorporated into emergy evaluations, via identifying sensitive variables and estimating the extent of their impact, in order to guide appropriate measures, and to avoid uncertainty. Several scholars have described the sources of uncertainty in emergy analysis, and used analytical and stochastic methods for estimating this uncertainty (Ingwersen, 2010; Li et al., 2011a). In order to assess the effects of variations in both transformities and emergy inputs on the results, a sensitivity analysis was performed in this study. This was accomplished by doubling, or halving, the annual emergy of each input upon the emergy indices (Odum and Odum, 2000; Martin et al., 2006; Li et al.,2011b).

Results and discussion

Emergy accounting and indices

The results of the emergy assessment of the irrigated production systems of rice, wheat, and oilseed rape are presented in Table 2, Table 3, and Table 4, respectively. Figure 2 shows the main emergy inputs for the three production systems, reflecting the emergy structure of each system in a detailed way. Table 5 presents the emergy indicators for these three systems. In Tables 2–4 the different inputs required for these production processes were converted to unified solar emergy, based on the specific transformities. By totaling all of the inputs of the rice system, the emergy assigned to the system’s yield was 1.92E+15 sej·yr^-1, about two times larger than those for wheat and oilseed rape systems (1.08E+15 sej·yr^-1 and 1.01E+15 sej·yr^-1). Emergy analysis of the irrigated rice production system shows that the largest emergy flows were associated with irrigation water (34.7%) and nitrogenous fertilizer (27.4%). These two sources accounted for 62.0% of the total emergy budget. Emergy in service and labor accounted for 28.1% of the total emergy budget. In the irrigated wheat production system, emergy in nitrogenous fertilizer (45.0%) was the single largest driving force, followed by labor (15.2%), and machinery service (13.2%). In the irrigated oilseed rape production system, nitrogenous fertilizer (38.0%) was again the largest emergy source, followed by labor (35.6%) and irrigation water (11.2%). In emergy terms, rain, soil, phosphate fertilizer, potash fertilizer, compound fertilizer, pesticide, and seeds, were almost one order of magnitude lower than the largest emergy sources in these systems. The results in Fig. 3 indicate that water and nutrients with a great percentage of energy input are the principal limiting factors for crop yields in irrigated agricultural production systems (Pimentel and Pimentel, 2007). An emergy evaluation of a corn system in the USA showed similar results, reporting that irrigation and fertilizers accounted for 95% of purchased resources (Martin et al., 2006). Therefore, to some extent, research results indicate that large gains in crop yields are highly dependent on irrigating and fertilizing.

The transformities for each product in this study (rice, wheat, and oilseed rape) were calculated by dividing the total emergy flow in each irrigated production system by the available energy of the outputs in joules. Transformity indicates the energy efficiency of production (Brown and Ulgiati, 1997). It also provides a measure of value, given the assumption that systems operating under the constraints of the maximum emergy principle generate products that stimulate the production process at least as much as they cost (Odum, 1996; Cavalett et al., 2006). The calculated transformities for rice, wheat and oilseed rape were 2.50E+05 sej·J^-1, 1.66E+05 sej·J^-1, and 2.14E+05 sej·J^-1 respectively (Table 5). These values indicate that grain production, in the wheat system, required nearly 33.6% less emergy than in the rice system, and 22.4% less emergy than in the oilseed rape system. However, the relative efficiencies of these production systems, as indicated by their higher transformities, are lower than those of the rice-vegetable rotation, organic rice-duck mutualism, rice-wheat rotation, and biogas-linked agrosystems (Xi and Qin, 2009; Lu et al., 2010; Chen and Chen, 2012).

Of particular interest are FIW and IIA values (Table 5), which quantify irrigation water as a component of the overall resource basis. The FIW value for the rice system indicates that irrigation water represented nearly 34.7% of total emergy use. This is far higher than the FIW values that were calculated for the wheat system (5.3%) and the oilseed rape system (11.2%). This indicates that irrigation water was a more significant contributor to rice than it was for the other two crops. Correspondingly, irrigation water, the highest emergy flow in the rice system, had an annual flow of 6.67E+14 sej·yr^-1. This is nearly twelve times larger than in the wheat system, and six times larger than in the oilseed rape system (Tables 2–4). The IIA index (2.9) suggested that for each unit of irrigation water, 2.9 units of rice production were possible. This value was much lower than those for the wheat and oilseed rape systems. The wheat production system had the highest net benefit (19.0) from irrigation water. In contrast, the IIA (8.9) for the oilseed rape system was moderate.

Other summary indices for these three systems include the synthesis indices EYR, EIR, ELR and ESI (Table 5). EYR, the emergy yield ratio, reflects the ability of a process to exploit local resources by investing outside resources in order to make further contributions to the economy. This index was found to be 1.59 for the rice system, 1.08 for the wheat system, and 1.17 for the oilseed rape system. These values were higher than the 1.0 for the balance between the system’s output and input from the economy (Odum, 1996). These results indicate that intensive conventional agricultural systems have EYR values lower than two (Odum, 1996; Ortega et al., 2005; Agostinho et al., 2008).

The values of the emergy investment ratio (EIR) were 1.70, 11.96 and 6.03 for the rice, wheat, and oil seed rape production systems, respectively. In contrast, the values of EIR for integrated production systems of grains, pigs, and fish, in southern Brazil ranged from 2.68 to 4.61, (Cavalett et al., 2006) and that for the Chinese agricultural system was 1.15 in 2004 (Jiang et al., 2007). The higher the EIR value, the more resources have to be used from the local economy. The results indicate that both rice and oilseed rape production used more environmental inputs than did wheat production. However, the EIR values also demonstrate that wheat systems, which utilize more purchased resources, might not be able to compete with the other two systems.

The environmental load ratio (ELR) is a measure of the environmental impact of a system. The reported ELR for the Chinese agricultural system in 2004 was 2.96 (Jiang et al., 2007). The rice system, with ELR of 1.71, (less than 3.0) is relatively low in environmental impact. The values of 12.57 for the wheat system, and 6.25 for the oilseed rape system, indicate more environmental impact on the part of these two systems (Brown and Ulgiati, 1997).

The environmental sustainability index (ESI) is another important ratio to consider. It indicates the environmental sustainability of a system. The reported ESI for the Chinese agricultural system was 2.96 in 2004 (Jiang et al., 2007). The ESI of 0.93 for the rice system, close to 1.0, showed that this system was energetic. In contrast, the calculated values of ESI for the other two systems, much less than 1.0, indicated that they were consumptive economic systems (Brown and Ulgiati, 1997; Ulgiati and Brown, 1998). The above indices also showed that the three agricultural systems studied were less sustainable than other reported ecological agricultural systems (Xi and Qin, 2009; Lu et al., 2010; Chen and Chen, 2012).

Sensitivity analysis

By doubling or halving the specific emergy input values, changes greater than 10% in EYR, ELR and ESI were documented (Fig. 3). The emergy value for irrigation water, when doubled or halved, resulted in a greater than 10% difference in emergy indices for many of the systems. Doubling/halving the emergy of the irrigation water increased/reduced the EYR by more than 10%, but only for the rice and oilseed rape systems. Doubling the emergy value for irrigation water, decreased the ELRs by more than 40%, and increased the ESIs by more than 80% across the three systems. Yet the ELRs increased by more than 55%, and the ESIs decreased by more than 35%, when the emergy value for irrigation water was halved.

For the rice system, the other inputs that affected these indices by more than 10% were nitrogenous fertilizer, machinery service, and labor. For the wheat system, besides irrigation water, four inputs (rain, nitrogenous fertilizer, machinery service, and labor) altered at least two of the three indices by more than 10% when their emergy values were doubled and halved. For the oilseed rape system, in addition to irrigation water, three inputs (rain, nitrogenous fertilizer and labor) altered at least two of the three indices by more than 10% when their emergy values were doubled and halved..

The differences among the three indices within each system revealed additional characteristics of these systems. The large changes in the three indices that occurred with changing inputs indicate that the uncertainty in transformities and annual input values potentially impacted the results of this study. The observed impact, on key indices, of changing the emergy value associated with irrigation water demonstrates a high degree of sensitivity to transformity and annual use of irrigation water, on the part of the three systems. Levels of nitrogenous fertilizer in these systems were another important input to which the emergy ratios were sensitive. Similar sensitivity analysis results were obtained by other emergy studies (Martin et al., 2006; Li et al., 2011b), which provide a possible direction for improving the systems evaluated.

Doubling and halving the inputs did not result in any changes greater than 100% in the emergy ratios for the wheat system, potentially revealing a characteristic specific to that system. This was that inputs to the wheat system had a more equal weight, compared to the rice and oilseed rape systems. Changes greater than 100% in the rice and oilseed rape systems demonstrate their heavy dependence on irrigation water. The lack of rain effects on the rice system indicate the greater amount of emergy associated with irrigation water needed for rice cultivation in a dry year. The lack of machinery service effects observed in the oilseed rape system reflected more emergy associated with machinery service needed for the rice and wheat systems, than for the oilseed rape system. The fact that doubling and halving each input to the wheat system did not have more than a 10% effect on the EYRs, was another indicator of the greater importance, to this system, of efficiencies in the use of all resources, when compared to the rice and oilseed rape systems.

Discussion and policy implications

Emergy evaluation as a biophysical method can compare the contribution of natural resources and ecosystem services to a production process. It can identify “leakage” in material and energy flows into or out of the system (Mayer, 2008). The emergy accounting procedure used in this study indicated that irrigation water and nitrogenous fertilizer were the main emergy inputs into three irrigated agricultural systems. A sensitivity analysis showed that the same two emergy inputs were the most sensitive factors. These results pointed toward optimization directions for the three systems, (i.e., improving efficiency in the use of irrigation water and nitrogenous fertilizer). Yet reducing the emergy input of irrigation water, with a lower FIW and higher IIA than before, could increase the ELR and decrease the EYR and the ESI. The key point is that the optimal irrigation quota, that balances irrigation water supply and crop yield, may vary for different crops.

Considering the uncertainty of irrigation requirements in different hydrological years, the feasible method was to select a typical dry year to estimate the emergy contribution of irrigation water to crop production. In the irrigation district studied, the efficiency in the production process for irrigation water was relatively high, with the values of 98% for pumping and 90% for distribution. Yet there was the potential for water conservation in the fields. The current composite irrigation quota in a typical dry year in this district was 283.8 m³·Mu^-1; while the corresponding average water-saving irrigation quota in Jiangsu Province by 2030 is estimated to be 207.9 m³·Mu^-1(WRDJSP, 2013<FootNote>

WRDJSP (2013). The planning report on agricultural water-saving irrigation in Jiangsu Province. Nanjing: Water Resources Department of Jiangsu Province. http://www.jswater.gov.cn/bmzwxx/nfzx/csxw/ztxx/zxgh/20081205/153759718.html.

</FootNote>). Some water-saving technologies in the fields could be applied to achieve this goal. Some of these are, improving water-saving irrigation programs, dry nursery seeding and controlled irrigation for rice production, and the water-fertilizer coupling technique. Applying emergy evaluation to conventional irrigation efficiency indicators, and irrigation experiment analysis, can help us to understand the process of irrigation water production and utilization in biophysical terms.

The calculated indicators showed that the rice system had the greatest level of sustainability of the three systems. This measure assumes that the objective function of sustainability is that of obtaining the highest yield ratio, while minimizing environmental loading (Ulgiati and Brown, 1998; Martin et al., 2006). For the oilseed rape and wheat systems, high environmental loading ratios resulted in low sustainability indicators. The possible reason is that these two systems have more nonrenewable and imported emergy inputs than inputs from local renewable resources. However, the studied production systems were still models of single and conventional agriculture, which show less sustainability than circular or ecological agriculture.

Agenda 21 recommendations, or Best Management Practices (BMPs), can be used to promote the adjustment of conventional chemical-agriculture farms in order to reduce associated negative social and environmental impacts (Agostinho et al., 2008). The main objectives of BMPs are to promote the conservation of environmental services by improving the efficiencies of resources and material engery inputs, and to reduce dependency on nonrenewable and imported emergy inputs (Cavalett et al., 2006). Thus, some agroecological practices could be implemented that reduce the purchase of chemical inputs and contribute to added renewability. Some possibilities are product diversification, organic fertilizer and nutrient recycling, conservation of topsoil and water, and biological control of plant diseases and insect pests (Cavalett et al., 2006; Agostinho et al., 2008; Wezel et al., 2009; Amekawa et al., 2010). Furthermore, to cope with the increasing stress from energy crises and global warming, biogas-linked agriculture can serve, both, as part of the country’s developmental strategy of clean energy, and as an important reaction to calls for sustainable agricultural practices. (Chen and Chen, 2012).

In addition, this study focused on emergy accounting, rather than economic analysis, which is currently the dominant value measurement system. The application of emergy evaluation in real production and management systems is still limited without the results of economic analysis (Lu et al., 2009). Economic analysis and emergy accounting are complementary valuation methods (Lu et al., 2009; Zhang et al., 2011). Integrating the two methodologies into a combined analysis can provide better insight into the environmental and economic effects of irrigated agricultural production systems.

Conclusions

Emergy theory has been proven to be an effective tool for evaluating agricultural production processes. Emergy evaluation has also provided useful emergy indices that can be used to quantify the sustainability of different agricultural systems. Different forms of energy and resources, including free environmental and purchased inputs into agricultural production, can be assessed using the unified basis of emergy theory and emergy evaluation methodology. For example, a basic input, irrigation water consumed in different irrigated agricultural processes, can be evaluated and compared with other inputs in terms of emergy. Two new indices, named the fraction of irrigation water (FIW), and the irrigation intensity of agriculture (IIA), were developed to depict the emergy contribution of irrigation water.

In this paper, results are presented from a case study on an irrigation district in China, which illustrated emergy evalualtion methodology through the assessment of three irrigated agricultural systems (rice, wheat and oilseed rape). The calculated values of FIW indicated that irrigation water contributed more to the rice system (34.7%), than to those for wheat (5.3%) and oilseed rape (11.2%) systems. The wheat production system, with the IIA of 19.0, had the highest net benefit from irrigation water input, when compared to the rice (2.9) and oilseed rape (8.9) productions. The wheat system also had higher energy efficiency in production than the rice and oilseed rape systems. The calculated transformities were 2.50E+05 sej·J^-1, 1.66E+05 sej·J^-1, and 2.14E+05 sej·J^-1 respectively. Other emergy indices showed that the rice system had the greatest level of sustainability of the three systems; but all of them were less sustainable than ecological agricultural systems. The sensitivity analysis indicated that the emergy associated with irrigation water and nitrogenous fertilizer, were the two principal limiting factors for crop production, and were the highest sensitivity factors influencing the emergy ratios for these three systems. Therefore, implementation of Best Management Practices, and other agroecological strategies, was suggested, in order to improve the sustainability of the three systems considered in this case study. Furthermore, additional emergy evaluations and economic analyses of irrigation water production and utilization systems should be integrated, in order to provide adequate guidelines for policy decisions about the sustainable development of irrigated agriculture.

References

[1] Agostinho F, Diniz G, Siche R, Ortega E (2008). The use of emergy assessment and the Geographical Information System in the diagnosis of small family farms in Brazil. Ecol Modell, 210(1–2): 37–57

[2] Amekawa Y, Sseguya H, Onzere S, Carranza I (2010). Delineating the multifunctional role of agroecological practices: toward sustainable livelihoods for smallholder farmers in developing countries. J Sustain Agric, 34(2): 202–228

[3] Barton D N (2002). The transferability of benefit transfer: contingent valuation of water quality improvements in Costa Rica. Ecol Econ, 42(1–2): 147–164

[4] Bastianoni S, Marchettini N, Panzieri M, Tiezzi E (2001). Sustainability assessment of a farm in the Chianti area (Italy). J Clean Prod, 9(4): 365–373

[5] Blamey R, Gordon J, Chapman R (1999). Choice modelling: assessing the environmental values of water supply options. Aust J Agric Resour Econ, 43(3): 337–357

[6] Brandt-Williams S L (2002). Handbook of Emergy Evaluation. Folio# 4. Emergy of Florida Agriculture (2nd printing). Center for Environmental Policy, Environmental Engineering Sciences, University of Florida, Gainesville, FL

[7] Brown M, Bardi E (2001). Handbook of Emergy Evaluation. Folio# 3: Emergy of Ecosystems. Center for Environmental Policy, University of Florida, Gainesville

[8] Brown M T, Martínez A, Uche J (2010). Emergy analysis applied to the estimation of the recovery of costs for water services under the European Water Framework Directive. Ecol Modell, 221(17): 2123–2132

[9] Brown M T, McClanahan T (1996). Emergy analysis perspectives of Thailand and Mekong River dam proposals. Ecol Modell, 91(1–3): 105–130

[10] Brown M T, Ulgiati S (1997). Emergy-based indices and ratios to evaluate sustainability: monitoring economies and technology toward environmentally sound innovation. Ecol Eng, 9(1–2): 51–69

[11] Buenfil A A (2001). Emergy evaluation of water. Dissertation for Ph.D Degree. Gainesville: University of Florida

[12] Cavalett O, Queiroz J F, Ortega E (2006). Emergy assessment of integrated production systems of grains, pig and fish in small farms in the South Brazil. Ecol Modell, 193(3–4): 205–224

[13] Chen B, Chen G (2006). Ecological footprint accounting based on emergy—A case study of the Chinese society. Ecol Modell, 198(1–2): 101–114

[14] Chen B, Chen G Q (2009). Emergy-based energy and material metabolism of the Yellow River basin. Commun Nonlinear Sci Numer Simul, 14(3): 923–934

[15] Chen B, Chen Z, Zhou Y, Zhou J, Chen G (2009a). Emergy as embodied energy based assessment for local sustainability of a constructed wetland in Beijing. Commun Nonlinear Sci Numer Simul, 14(2): 622–635

[16] Chen D, Chen J, Luo Z H (2012). Communications on emergy indices of regional water ecological-economic system. Ecol Eng, 46: 116–117

[17] Chen D, Chen J, Luo Z H, Lv Z W (2009b). Emergy evaluation of the natural value of water resources in Chinese rivers. Environ Manage, 44(2): 288–297

[18] Chen D, Chen J, Lv Z W, Chen X (2008). A quantitative analysis method in water sciences research: emergy theory and method. Journal of China Three Gorges University(Natural Sciences), 30(2): 1–5

[19] Chen D, Luo Z H, Webber M, Chen J, Wang W G (2013). Emergy evaluation of a pumping irrigation water production system in China. Frontiers of Earth Science, doi: 10.1007/s11707-013-0367-x

[20] Chen D, Webber M, Chen J, Luo Z H (2011). Emergy evaluation perspectives of an irrigation improvement project proposal in China. Ecol Econ, 70(11): 2154–2162

[21] Chen G Q, Jiang M M, Chen B, Yang Z F, Lin C (2006). Emergy analysis of Chinese agriculture. Agric Ecosyst Environ, 115(1–4): 161–173

[22] Chen S Q, Chen B (2011). Assessing inter-city ecological and economic relations: an emergy-based conceptual model. Frontiers of Earth Science, 5(1): 97–102

[23] Chen S Q, Chen B (2012). Sustainability and future alternatives of biogas-linked agrosystem (BLAS) in China: an emergy synthesis. Renew Sustain Energy Rev, 16(6): 3948–3959

[24] Connor J D, Schwabe K, King D, Knapp K (2012). Irrigated agriculture and climate change: the influence of water supply variability and salinity on adaptation. Ecol Econ, 77: 149–157

[25] Costanza R, d’Arge R, de Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O’Neill R V, Paruelo J, Raskin R G, Sutton P, van den Belt M (1998). The value of the world’s ecosystem services and natural capital. Ecol Econ, 25(1): 3–15

[26] de Barros I, Blazy J M, Rodrigues G S, Tournebize R, Cinna J P (2009). Emergy evaluation and economic performance of banana cropping systems in Guadeloupe (French West Indies). Agric Ecosyst Environ, 129(4): 437–449

[27] Faux J, Perry G M (1999). Estimating irrigation water value using hedonic price analysis: a case study in Malheur County, Oregon. Land Econ, 75(3): 440–452

[28] Gohar A A, Ward F A, Amer S A (2013). Economic performance of water storage capacity expansion for food security. J Hydrol (Amst), 484: 16–25

[29] Hau J L, Bakshi B R (2004). Promise and problems of emergy analysis. Ecol Modell, 178(1–2): 215–225

[30] Huang Q, Rozelle S, Lohmar B, Huang J, Wang J (2006). Irrigation, agricultural performance and poverty reduction in China. Food Policy, 31(1): 30–52

[31] Hussain I, Sial M H, Hussain Z, Akram W (2009). Economic value of irrigation water: evidence from a Punjab Canal. Lahore Journal of Economics, 14(1): 69–84

[32] Hussain I, Turral H, Molden D, Ahmad M D (2007). Measuring and enhancing the value of agricultural water in irrigated river basins. Irrig Sci, 25(3): 263–282

[33] Ingwersen W W (2010). Uncertainty characterization for emergy values. Ecol Modell, 221(3): 445–452

[34] Jabeen S, Ashfaq M, Baig A (2006). Linear program modeling for determining the value of irrigation water. J Agric Soc Sci, 2(2): 101–105

[35] Jiang M M, Chen B, Zhou J B, Tao F R, Li Z, Yang Z F, Chen G Q (2007). Emergy account for biomass resource exploitation by agriculture in China. Energy Policy, 35(9): 4704–4719

[36] Jiang W L (1998). The research of value-model assessment about value of water resource. Journal of natural resources, 1: 35–43

[37] Kang D, Park S S (2002). Emergy evaluation perspectives of a multipurpose dam proposal in Korea. J Environ Manage, 66(3): 293–306

[38] Kim C, Schaible G D (2000). Economic benefits resulting from irrigation water use: theory and an application to groundwater use. Environ Resour Econ, 17(1): 73–87

[39] La Rosa A, Siracusa G, Cavallaro R (2008). Emergy evaluation of Sicilian red orange production. A comparison between organic and conventional farming. J Clean Prod, 16(17): 1907–1914

[40] Lan S F, Qin P, Lu H F (2002). Emergy Analysis of Eco-economic System. Beijing: Chemical Industry Press

[41] Larson C (2013). Climate change. Losing arable land, China faces stark choice: adapt or go hungry. Science, 339(6120): 644–645

[42] Lefroy E, Rydberg T (2003). Emergy evaluation of three cropping systems in southwestern Australia. Ecol Modell, 161(3): 195–211

[43] Li L, Lu H, Campbell D E, Ren H (2011a). Methods for estimating the uncertainty in emergy table-form models. Ecol Modell, 222(15): 2615–2622

[44] Li L, Lu H, Ren H, Kang W, Chen F (2011b). Emergy evaluations of three aquaculture systems on wetlands surrounding the Pearl River Estuary, China. Ecol Indic, 11(2): 526–534

[45] Lima J S G, Rivera E C, Focken U (2012). Emergy evaluation of organic and conventional marine shrimp farms in Guaraira Lagoon, Brazil. J Clean Prod, 35: 194–202

[46] Lu H F, Bai Y, Ren H, Campbell D E (2010). Integrated emergy, energy and economic evaluation of rice and vegetable production systems in alluvial paddy fields: implications for agricultural policy in China. J Environ Manage, 91(12): 2727–2735

[47] Lu H F, Kang W L, Campbell D E, Ren H, Tan Y W, Feng R X, Luo J T, Chen F P (2009). Emergy and economic evaluations of four fruit production systems on reclaimed wetlands surrounding the Pearl River Estuary, China. Ecol Eng, 35(12): 1743–1757

[48] Lv C M, Wu Z N (2009). Emergy analysis of regional water ecological–economic system. Ecol Eng, 35(5): 703–710

[49] Martin J F, Diemont S A W, Powell E, Stanton M, Levy-Tacher S (2006). Emergy evaluation of the performance and sustainability of three agricultural systems with different scales and management. Agric Ecosyst Environ, 115(1–4): 128–140

[50] Mayer A L (2008). Strengths and weaknesses of common sustainability indices for multidimensional systems. Environ Int, 34(2): 277–291

[51] Odum H T (1996). Environmental Accounting: Emergy and Environmental Decision Making. New York: John Wiley & Sons

[52] Odum H T (2000). Handbook of Emergy Evaluation. Folio# 2, Emergy of Global Processes. Handbook of Emergy Evaluation. Center for Environmental Policy, Environmental Engineering Sciences, University of Florida, Gainesville, 30

[53] Odum H T, Brown M T, Brandt-Williams S (2000). Handbook of Emergy Evaluation. Folio# 1: Introduction and Global Budget. Center for Environmental Policy, Environmental Engineering Sciences, University of Florida, Gainesville

[54] Odum H T, Odum E C (2000). Modeling for All Scales: An Introduction to System Simulation. Academic Press

[55] Ortega E, Cavalett O, Bonifácio R, Watanabe M (2005). Brazilian soybean production: emergy analysis with an expanded scope. Bull Sci Technol Soc, 25(4): 323–334

[56] Özerol G, Bressers H, Coenen F (2012). Irrigated agriculture and environmental sustainability: an alignment perspective. Environ Sci Policy, 23: 57–67

[57] Patterson M G (2002). Ecological production based pricing of biosphere processes. Ecol Econ, 41(3): 457–478

[58] Pimentel D, Pimentel M H (2007). Food, Energy, and Society (3rd Edition). CRC

[59] Playán E, Mateos L (2006). Modernization and optimization of irrigation systems to increase water productivity. Agric Water Manage, 80(1–3): 100–116

[60] Pulselli F M, Patrizi N, Focardi S (2011). Calculation of the unit emergy value of water in an Italian watershed. Ecol Modell, 222(16): 2929–2938

[61] Reca J, Roldán J, Alcaide M, Lopez R, Camacho E (2001). Optimisation model for water allocation in deficit irrigation systems: I. Description of the model. Agric Water Manage, 48(2): 103–116

[62] Rugani B, Benetto E (2012). Improvements to Emergy evaluations by using Life Cycle Assessment. Environ Sci Technol, 46(9): 4701–4712

[63] Rydberg T, Haden A C (2006). Emergy evaluations of Denmark and Danish agriculture: assessing the influence of changing resource availability on the organization of agriculture and society. Agric Ecosyst Environ, 117(2–3): 145–158

[64] Sciubba E, Ulgiati S (2005). Emergy and exergy analyses: complementary methods or irreducible ideological options? Energy, 30(10): 1953–1988

[65] Seyam I, Hoekstra A, Savenije H (2002). Calculation methods to assess the value of upstream water flows and storage as a function of downstream benefits. Physics and Chemistry of the Earth, Parts A/B/C, 27 (11–22): 977–982

[66] Shao L, Wu Z, Zeng L, Chen Z M, Zhou Y, Chen G Q (2013). Embodied energy assessment for ecological wastewater treatment by a constructed wetland. Ecol Modell, 252: 63–71

[67] Shen D J, Liang R J, Wang H (1999). Water Pricing in Theory and Practice. Beijing: Science Press

[68] Tsadilas C, Vakalis P (2003). Economic benefit from irrigation of cotton and corn with treated wastewater. Water supply, 3(4): 223–229

[69] Ulgiati S, Brown M T (1998). Monitoring patterns of sustainability in natural and man-made ecosystems. Ecol Modell, 108(1–3): 23–36

[70] Voora V, Thrift C (2010). Using Emergy to Value Ecosystem Goods and Services. Winnipeg: International Institute for Sustainable Development, Canada

[71] Wezel A, Bellon S, Doré T, Francis C, Vallod D, David C (2009). Agroecology as a science, a movement and a practice. A review. Agronomy For Sustainable Development, 29(4): 503–515

[72] Xi Y G, Qin P (2009). Emergy evaluation of organic rice-duck mutualism system. Ecol Eng, 35(11): 1677–1683

[73] Yan M C, Odum H T (2001). New Visual Angle to View Eco-economic System Emergy Evaluation Case Studies of Chinese Regional Eco-economic System. Beijing: China Zhigong Publishing House

[74] Zhang L X, Ulgiati S, Yang Z F, Chen B(2011). Emergy evaluation and economic analysis of three wetland fish farming systems in Nansi Lake area, China. J Environ Manage, 92(3): 683–694

[75] Zhang L X, Song B, Chen B (2012). Emergy-based analysis of four farming systems: insight into agricultural diversification in rural China. J Clean Prod, 28(0): 33–44

[76] Zhang L X, Yang Z F, Chen G Q (2007). Emergy analysis of cropping–grazing system in Inner Mongolia Autonomous Region, China. Energy Policy, 35 (7): 3843–3855

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg