Performance Evaluation of Ecological Compensation at the County Level: A Case Study of Anyuan County in Dongjiangyuan Watershed, China

doi:10.5814/j.issn.1674-764x.2023.02.004

Abstract

Abstract:

Watershed ecological compensation is an important means to protect the ecological environment and an important part of China’s ecological civilization construction. It can promote the sustainable and coordinated development of a region, enhance the advantages of the ecological environment in the upstream area, and lay the foundation for the high-quality development of ecological tourism in the upstream area. The accurate evaluation of the effect and efficiency of ecological compensation is a prerequisite for optimizing and perfecting the ecological compensation system. In order to evaluate the effect and efficiency of watershed ecological compensation, this paper used the case study area of Anyuan County, an important ecological area of the Dongjiangyuan watershed in the pilot area of China’s interprovincial watershed ecological compensation. This paper established an evaluation index system, used the entropy method and the data envelopment analysis (DEA) method to construct a watershed ecological compensation effect and efficiency evaluation model, and selected the ecological compensation index data from 2015 to 2020 to evaluate the effect and efficiency. This paper also constructed an econometric model to analyze their driving factors. The results showed that the effect of watershed ecological compensation was generally on the rise. Low pure technical efficiency (PTE) was the main reason for low comprehensive efficiency (CE), and the management efficiency of ecological compensation projects needs to be improved. The overall performance of scale efficiency (SE) was good, but there was still a problem of capital redundancy. Ecological compensation expenditure had a significant negative impact on the efficiency of ecological compensation, and ecotourism had a significant positive impact on the effect and efficiency of the ecological compensation. The results of this study can provide a scientific basis and theoretical reference for improving the effect and efficiency of watershed ecological compensation schemes.

Key words: watershed ecological compensation, performance evaluation, entropy method, DEA, Anyuan County

TANG Wenyue, WANG Qianguang, CHENG Hao, ZHU Zhenhong. Performance Evaluation of Ecological Compensation at the County Level: A Case Study of Anyuan County in Dongjiangyuan Watershed, China[J]. Journal of Resources and Ecology, 2023, 14(2): 252-264.

Figures/Tables 6

References 42

[1]	Alix-Garcia J, De Janvry A, Sadoulet E. 2008. The role of deforestation risk and calibrated compensation in designing payments for environmental services. Environment and Development Economics, 13(3): 375-394.
[2]	Chang L, Xu D W, Hou T S, et al. 2013. On the intergovernmental river basin ecological compensation mechanism of across administration area. Science-Technology and Management, 15(2): 92-97. (in Chinese)
[3]	Chen T G, Liu F, Yang Y. 2021. Performance evaluation and influence factors of ecological compensation policy in the Yangtze River Basin: The case study of Hubei and Guizhou provinces. Journal of Natural Resources, 36(12): 3144-3155. (in Chinese)
[4]	Chen W, Yu X H, Xiong X. 2018. Study on the measurement of ecological compensation efficiency of government led river basins: A case study of major coastal cities in the Yangtze River Economic Belt. Jiang-huai Tribune, (3): 43-50. (in Chinese)
[5]	Costanza R, d’Arge R, de Groot R, et al. 1997. The value of the world’s ecosystem services and natural capital. Nature, 387(6630): 253-260.
[6]	Freeman R E. 1994. The politics of stakeholder theory: Some future directons. Business Ethics Quarterly, 4(4): 409-421.
[7]	General Office of the State Council. 2016. Opinions of the General Office of the State Council on improving the ecological protection compensation mechanism. Contemporary Rural Finance and Economics, (6): 44-46. (in Chinese)
[8]	Geng X Y, Ge Y X, Wang A M. 2017. Study on comprehensive benefit evaluation of ecological compensation in water source areas: A case study of Lake Yunmeng in Shandong Province. Issues in Agricultural Economy, 38(4): 93-101, 112. (in Chinese)
[9]	Govindan K, Kaliyan M, Kannan D, et al. 2014. Barriers analysis for green supply chain management implementation in Indian industries using analytic hierarchy process. International Journal of Production Economics, 147: 555-568.
[10]	Guo Q H. 2020. Comparative analysis of the efficiency of regional financial technology investment based on DEA-Tobit analysis method. Diss., Tianjin, China: Tianjin University of Finance and Economics. (in Chinese)
[11]	Jing S W, Zhang J. 2018. Can Xin’anjiang River Basin horizontal ecological compensation reduce the intensity of water pollution? China Population, Resources and Environment, 28(10): 152-159. (in Chinese)
[12]	Kaplowitz M D. 2001. Assessing mangrove products and services at the local level: The use of focus groups and individual interviews. Landscape and Urban Planning, 56(1-2): 53-60.
[13]	Kosoy N, Martinez-Tuna M, Muradian R, et al. 2007. Payments for environmental services in watersheds: Insights from a comparative study of three cases in central America. Ecological Economics, 61(2-3): 446-455.
[14]	Li C H, Ge Y X. 2019. Study on comprehensive benefit evaluation of two-way ecological compensation in river basins: A case study of Xiaoqing River Basin in Shandong Province. Shandong Social Sciences, (12): 85-90. (in Chinese)
[15]	Li Q P, Li C J. 2015. Study on the measurement of ecological compensation efficiency of watershed water resources: A case study of Yichang City in Central China. Seeker, (10): 34-38. (in Chinese)
[16]	Ma Q H, Du P F. 2015. Evaluation on the effect of ecological compensation in Xin’an River Basin. Chinese Journal of Environmental Management, 7(3): 63-70. (in Chinese)
[17]	Martin-Ortega J, Dekker T, Ojea E, et al. 2019. Dissecting price setting efficiency in payments for ecosystem services: A meta-analysis of payments for watershed services in Latin America. Ecosystem Services, 38: 100961. DOI: 10.1016/j.ecoser.2019.100961.
[18]	Meng Y, Zhang K, Gao F H, et al. 2019. Comprehensive evaluation of ecological compensation effect in Xiaohong River Basin based on combination weight model. Water Saving Irrigation, (10): 64-67. (in Chinese)
[19]	Ministry of Finance, Ministry of Environmental Protection, Development and Reform Commission, et al. 2017. Guiding opinions on accelerating the establishment of a horizontal ecological protection and compensation mechanism for the upper and lower reaches of the watershed. Gazette of the Ministry of Finance of the People ’ s Republic of China, (4): 54-56. (in Chinese)
[20]	Ministry of Water Resources. 2019. Nine departments including the National Development and Reform Commission, the Ministry of Finance, and the Ministry of Water Resources jointly issued the “Action Plan for Establishing a Market-oriented and Diversified Ecological Protection and Compensation Mechanism”. Journal of Economics of Water Resources, 37(1): 64. (in Chinese)
[21]	Miranda M, Porras I T, Moreno M L. 2003. The social impacts of payments for environmental services in Costa Rica: A quantitative field survey and analysis of the Virilla Watershed. London, UK: International Institute for Environment and Development.
[22]	National Development and Reform Commission. 2019. Ecological comprehensive compensation pilot program. Energy Saving of Nonferrous Metallurgy, 35(6): 1-2. (in Chinese)
[23]	Pagiola S, Arcenas A, Platais G. 2005. Can payments for environmental services help reduce poverty? An exploration of the issues and the evidence to date from Latin America. World Development, 33(2): 237-253.
[24]	Pagiola S, Ramirez E, Gobbi J, et al. 2007. Paying for the environmental services of silvopastor practices in Nicaragua. Ecological Economics, 64(2): 374-385.
[25]	Peng Y T. 2020. Comprehensive benefit evaluation of ecological compensation for water source areas in Xin’an River Basin. Jiang-huai Tribune, (5): 75-82. (in Chinese)
[26]	Pfaff A, Robalino J, Sanchez-Azofeifa G A. 2008. Payments for environmental services: Empirical analysis for Costa Rica. Durham, USA: Duke University.
[27]	Robalino J, Pfaff A, Sanchez-Azofeifa G A, et al. 2008. Deforestation impacts of environmental services payments: Costa Rica’s PSA Program 2000-2005. Washington, USA: Environments for Development.
[28]	Shao Y F. 2019. “Six Steps Ahead” plays the strongest voice in poverty alleviation: The practice and results of poverty alleviation in Anyuan County. Old District Construction, (9): 31-35. (in Chinese)
[29]	Song X Y, Liu Y Q, Zhong F L, et al. 2020. Payment criteria and mode for watershed ecosystem services: A case study of the Heihe River Basin, Northwest China. Sustainability, 12(15): 6177. DOI: 10.3390/su12156177.
[30]	State Council. 2012. Opinions of the State Council on implementing the strictest water resources management system. Western Resources, (1): 28-30. (in Chinese)
[31]	Sun F H, Zhang X J, Gao X, et al. 2021. Cooperative mechanism of trans-stream ecological compensation evolution based on reputation effect. Resources & Industries, 23(1): 87-96. (in Chinese)
[32]	Tang P P, Zhang X L, Hu Y Y. 2018. The construction and application of ecological compensation performance evaluation system in water source area: Based on empirical analysis of Hanjiang water source area in middle route of the South-North Water Transfer Project. Ecological Economy, 34(2): 170-174. (in Chinese)
[33]	Von Thaden J, Manson R H, Congalton G, et al. 2021. Evaluating the environmental effectiveness of payments for hydrological services in Veracruz, Mexico: A landscape approach. Land Use Policy, 100: 105055. DOI: 10.1016/j.landusepol.2020.105055.
[34]	Wang H J, Bi F F, Dong Z F. 2020. Evaluation of ecological compensation policy for Xin’an River Basin based on AHP-Fuzzy comprehensive method. Acta Ecologica Sinica, 40(20): 7493-7506. (in Chinese)
[35]	Wu Q, Xie R P, Song C. 2021. Research on the coordinated development of tourism, economy and environment in Guangdong Province. Ecological Economy, 37(4): 140-146, 155. (in Chinese)
[36]	Wunscher T, Engel S. 2012. International payments for biodiversity services: Review and evaluation of conservation targeting approaches. Biological Conservation, 152: 222-230.
[37]	Yang J. 2015. The research of supervision and accountability mechanism of county governments under the system of province directly governing county. Diss., Changsha, China: Hunan Normal University. (in Chinese)
[38]	Yu L J, Ge L Y, Liang Y X. 2011. Evaluation of the water environment ecological compensation mechanism and implementation effect in Henan Province. Environmental Pollution & Control, 33(4): 87-90. (in Chinese)
[39]	Zhang J, Ni C H, Zhu M M. 2020. Study on the financial expenditure efficiency of ecological compensation in Xin’an River Basin. Chinese Journal of Environmental Management, 12(4): 112-119. (in Chinese)
[40]	Zhang L Z, Dang W Q, Zheng H, et al. 2010. Implimention effect evaluation and mechanism of soil and water conservation eco-compensation in Yellow River Basin. Bulletin of Soil and Water Conservation, 30(3): 176-181. (in Chinese)
[41]	Zhao Y. 2013. Research on willingness to payment and payment behavior of ecological compensation of trans-regional river basin: Taking Liaohe River as an example. Diss., Dalian, China: Dalian University of Technology. (in Chinese)
[42]	Zheng H X, Zhang L B. 2006. Chinese practices for ecological compensation and payments for ecological and environmental services and its policies in river basins:Washington DC, USA: The World Bank.

Target layer	Criterion layer	Index layer	Description	Units
Water environmental protection	Water ecological protection and restoration	Aquatic product output	Negative index	t
		Plantation area	Positive index	mu
		Soil erosion control area	Negative index	km²
Water pollution prevention	Urban and rural pollution prevention and control	Sewage treatment rate	Positive index	%
	Urban and rural pollution prevention and control	Harmless treatment rate of garbage	Positive index	%
	Industrial pollution prevention	Industrial wastewater discharge	Negative index	t
		COD emissions in industrial wastewater	Negative index	t
		Ammonia nitrogen emissions from industrial wastewater	Negative index	t
	Agricultural pollution prevention	Amount of agricultural fertilizer	Negative index	t
	Agricultural pollution prevention	Pesticide usage	Negative index	t

Target layer	Criterion layer	Index layer	Description	Units
Water environmental protection	Water ecological protection and restoration	Aquatic product output	Negative index	t
		Plantation area	Positive index	mu
		Soil erosion control area	Negative index	km²
Water pollution prevention	Urban and rural pollution prevention and control	Sewage treatment rate	Positive index	%
	Urban and rural pollution prevention and control	Harmless treatment rate of garbage	Positive index	%
	Industrial pollution prevention	Industrial wastewater discharge	Negative index	t
		COD emissions in industrial wastewater	Negative index	t
		Ammonia nitrogen emissions from industrial wastewater	Negative index	t
	Agricultural pollution prevention	Amount of agricultural fertilizer	Negative index	t
	Agricultural pollution prevention	Pesticide usage	Negative index	t

Target layer	Criterion layer	Index layer	Weight	2015	2016	2017	2018	2019	2020
Water environmental protection	Water ecological protection and restoration	Aquatic product output	0.1130	0.1130	0.0925	0.0527	0.0416	0.0231	0.0000
		Plantation area	0.1044	0.0827	0.0285	0.0338	0.0589	0.0000	0.1044
		Soil erosion control area	0.1027	0.0000	0.0992	0.1027	0.0818	0.0175	0.0893
		Subtotal	0.3201	0.1957	0.2202	0.1892	0.1823	0.0406	0.1937
Water pollution prevention	Urban and rural pollution prevention and control	Sewage treatment rate	0.0817	0.0000	0.0331	0.0418	0.0495	0.0535	0.0817
		Harmless treatment rate of garbage	0.0649	0.0000	0.0649	0.0649	0.0649	0.0649	0.0649
		Subtotal	0.1466	0.0000	0.0980	0.1067	0.1144	0.1184	0.1466
	Industrial pollution prevention	Industrial wastewater discharge	0.0672	0.0000	0.0568	0.0633	0.0672	0.0476	0.0594
		COD emissions in industrial wastewater	0.0653	0.0000	0.0565	0.0629	0.0624	0.0653	0.0598
		Ammonia nitrogen emissions from industrial wastewater	0.0658	0.0000	0.0638	0.0658	0.0658	0.0652	0.0540
		Subtotal	0.1983	0.0000	0.1771	0.1920	0.1954	0.1781	0.1732
	Agricultural pollution prevention	Amount of agricultural fertilizer	0.1755	0.0000	0.0009	0.0426	0.1533	0.1625	0.1755
		Pesticide usage	0.1595	0.0000	0.0087	0.0318	0.1209	0.1264	0.1597
		Subtotal	0.3350	0.0000	0.0096	0.0744	0.2742	0.2889	0.3352
	Subtotal		0.6799	0.0000	0.2847	0.3731	0.5840	0.5854	0.6550
Overall			1.0000	0.1957	0.5049	0.5623	0.7663	0.6260	0.8487

Target layer	Criterion layer	Index layer	Weight	2015	2016	2017	2018	2019	2020
Water environmental protection	Water ecological protection and restoration	Aquatic product output	0.1130	0.1130	0.0925	0.0527	0.0416	0.0231	0.0000
		Plantation area	0.1044	0.0827	0.0285	0.0338	0.0589	0.0000	0.1044
		Soil erosion control area	0.1027	0.0000	0.0992	0.1027	0.0818	0.0175	0.0893
		Subtotal	0.3201	0.1957	0.2202	0.1892	0.1823	0.0406	0.1937
Water pollution prevention	Urban and rural pollution prevention and control	Sewage treatment rate	0.0817	0.0000	0.0331	0.0418	0.0495	0.0535	0.0817
		Harmless treatment rate of garbage	0.0649	0.0000	0.0649	0.0649	0.0649	0.0649	0.0649
		Subtotal	0.1466	0.0000	0.0980	0.1067	0.1144	0.1184	0.1466
	Industrial pollution prevention	Industrial wastewater discharge	0.0672	0.0000	0.0568	0.0633	0.0672	0.0476	0.0594
		COD emissions in industrial wastewater	0.0653	0.0000	0.0565	0.0629	0.0624	0.0653	0.0598
		Ammonia nitrogen emissions from industrial wastewater	0.0658	0.0000	0.0638	0.0658	0.0658	0.0652	0.0540
		Subtotal	0.1983	0.0000	0.1771	0.1920	0.1954	0.1781	0.1732
	Agricultural pollution prevention	Amount of agricultural fertilizer	0.1755	0.0000	0.0009	0.0426	0.1533	0.1625	0.1755
		Pesticide usage	0.1595	0.0000	0.0087	0.0318	0.1209	0.1264	0.1597
		Subtotal	0.3350	0.0000	0.0096	0.0744	0.2742	0.2889	0.3352
	Subtotal		0.6799	0.0000	0.2847	0.3731	0.5840	0.5854	0.6550
Overall			1.0000	0.1957	0.5049	0.5623	0.7663	0.6260	0.8487

Year	CE	PTE	SE	Return to scale
2015	0.292	0.293	0.995	Decrease
2016	0.981	1.000	0.981	Decrease
2017	1.000	1.000	1.000	Constant
2018	0.579	0.661	0.876	Decrease
2019	0.770	0.880	0.875	Decrease
2020	0.855	1.000	0.855	Decrease
Average	0.746	0.806	0.930