Your search found 7 records
1 Shi, Q.; Zeng, X.; Li, M.; Tan, X.; Xu, F. 2002. Effects of different water management practices on rice growth. In Bouman, B. A. M.; Hengsdijk, H.; Hardy, B.; Bindraban, P. S.; Tuong, T. P.; Ladha, J. K. (Eds.), Water-wise rice production. Los Baños, Philippines: International Rice Research Institute (IRRI). pp.3-13.
Rice ; Irrigation practices ; Flood irrigation ; Intermittent irrigation ; Water table ; Crop yield ; Experiments / China / Jiangxi
(Location: IWMI-HQ Call no: 631.7.2 G000 BOU Record No: H032415)
(3 MB)
2 Shi, Q.; Zeng, X.; Zhu, A.; Li, M.; Fu, S.; Liu, F.; Hengsdijk, H.; Henstra, P.; Bindraban, P. S. 2005. Effects of intermittent irrigation on growth, yield and water use efficiency of rice in a field lysimeter experiment. In Thiyagarajan, T. M.; Hengsdijk, H.; Bindraban, P. S. (Eds.), Transitions in agriculture for enhancing water productivity. Proceedings of an international symposium held in Killikulam, Tamil Nadu, India, 23-25 September 2003. Tamil Nadu, India; Wageningen, Netherlands: Tamil Nadu Agricultural University. Agricultural College & Research Institute; Wageningen University and Research Centre. Plant Research International. pp.97-110.
Intermittent irrigation ; Rice ; Lysimetry ; Experiments ; Water balance ; Water use efficiency ; Nitrogen / China
(Location: IWMI-HQ Call no: 631.7.2 G570 THI Record No: H037030)
3 Li, M.; Li, H.; Fu, Q.; Liu, D.; Yu, L.; Li, T. 2021. Approach for optimizing the water-land-food-energy nexus in agroforestry systems under climate change. Agricultural Systems, 192:103201. [doi: https://doi.org/10.1016/j.agsy.2021.103201]
Water resources ; Land resources ; Food security ; Energy ; Nexus ; Agroforestry systems ; Climate change ; Water allocation ; Water supply ; Water use efficiency ; Irrigation water ; Greenhouse gas emissions ; Carbon footprint ; Sustainable Development Goals ; Models / China / Heilongjiang
(Location: IWMI HQ Call no: e-copy only Record No: H050518)
(6.00 MB)
CONTEXT: Agroforestry systems are widely promoted for their economic and environmental benefits. Food, energy, water and land resources in agroforestry systems are inextricably intertwined and expected to be severely impacted by climate change. Socioeconomic development and increasing populations have posed unique challenges for meeting the demand for food, energy, water and land, and the challenge will become more pressing under projected resource shortages and eco-environmental deterioration. Thus, a method of optimizing and sustainably managing the water-land-food-energy nexus in agroforestry systems under climate change must be developed.
OBJECTIVE: This paper develops an optimization model framework for the sustainable management of limited water-land-food-energy resources in agroforestry systems under climate change. The aims are to (1) quantify the interactions and feedbacks within water, land, food and energy subsystems; (2) provide trade-offs among water and energy utilization efficiency, economic benefits and environmental protection in agroforestry systems; and (3) generate optimal policy options among water and land resources for different crops and woodlands in different regions under different climate change patterns.
METHODS: The model framework is based on multiobjective fractional programming, and compromise programming is used to solve it. Climate change patterns are obtained from atmospheric circulation models and representative concentration pathways. The above aims are investigated through an actual nexus management problem in northeast China. Spatiotemporal meteorological and report-based databases, life cycle assessments, Pearson correlation analyses, data envelopment analyses and analytic hierarchy processes are integrated to realize practical application.
RESULTS AND CONCLUSIONS: The results show that climate variation will change the water and land allocation patterns and these changes will be more pronounced for major grain-producing areas. The optimized water allocation decreased (especially for rice, e.g., the optimal average value of the irrigation quota of rice was 4226 m3/ha, while the corresponding actual irrigation requirement of rice was [4200–7200] m3/ha) to improve the water use efficiency, and surface water allocation accounted for two-thirds. Maize had the largest planting area, although planting soybean generated the most greenhouse gases (greenhouse gas emissions from field activities for rice, maize, and soybean were 43.46%, 84.06% and 91.16%, respectively); However, these gases can be absorbed by forests. The model improved the harmonious degree of the resource-economy-environment system from 0.24 to 0.56 after optimization.
SIGNIFICANCES: Integrated models contribute to the sustainable management of water, food, energy and land resources and can consider the complex dynamics under climate change. It can be used as a general model and extended to other agroforestry systems that show inefficient agricultural production.
OBJECTIVE: This paper develops an optimization model framework for the sustainable management of limited water-land-food-energy resources in agroforestry systems under climate change. The aims are to (1) quantify the interactions and feedbacks within water, land, food and energy subsystems; (2) provide trade-offs among water and energy utilization efficiency, economic benefits and environmental protection in agroforestry systems; and (3) generate optimal policy options among water and land resources for different crops and woodlands in different regions under different climate change patterns.
METHODS: The model framework is based on multiobjective fractional programming, and compromise programming is used to solve it. Climate change patterns are obtained from atmospheric circulation models and representative concentration pathways. The above aims are investigated through an actual nexus management problem in northeast China. Spatiotemporal meteorological and report-based databases, life cycle assessments, Pearson correlation analyses, data envelopment analyses and analytic hierarchy processes are integrated to realize practical application.
RESULTS AND CONCLUSIONS: The results show that climate variation will change the water and land allocation patterns and these changes will be more pronounced for major grain-producing areas. The optimized water allocation decreased (especially for rice, e.g., the optimal average value of the irrigation quota of rice was 4226 m3/ha, while the corresponding actual irrigation requirement of rice was [4200–7200] m3/ha) to improve the water use efficiency, and surface water allocation accounted for two-thirds. Maize had the largest planting area, although planting soybean generated the most greenhouse gases (greenhouse gas emissions from field activities for rice, maize, and soybean were 43.46%, 84.06% and 91.16%, respectively); However, these gases can be absorbed by forests. The model improved the harmonious degree of the resource-economy-environment system from 0.24 to 0.56 after optimization.
SIGNIFICANCES: Integrated models contribute to the sustainable management of water, food, energy and land resources and can consider the complex dynamics under climate change. It can be used as a general model and extended to other agroforestry systems that show inefficient agricultural production.
4 Li, M.; Cao, X.; Liu, D.; Fu, Q.; Li, T.; Shang, R. 2021. Sustainable management of agricultural water and land resources under changing climate and socio-economic conditions: a multi-dimensional optimization approach. Agricultural Water Management, 259:107235. (Online first) [doi: https://doi.org/10.1016/j.agwat.2021.107235]
Agricultural water use ; Water management ; Land resources ; Climate change ; Socioeconomic aspects ; Sustainable development ; Water security ; Water supply ; Water demand ; Water allocation ; Surface water ; Irrigation water ; Water footprint ; Decision making ; Economic development ; Models / China / Songhua River Basin / Heilongjiang / Harbin / Hegang / Shuangyashan / Yichun / Jiamusi / Qitaihe / Mudanjiang / Suihua
(Location: IWMI HQ Call no: e-copy only Record No: H050756)
(5.27 MB)
Conflict between limited water supply and the ever-increasing water demand poses the challenge of synergetic management of agricultural water and land resources (AWLR). Sustainable development strategy and changing environment increase the multi-dimensional characteristic and complexity of the management of AWLR. This paper establishes a model framework for the multi-dimensional optimization of AWLR in a changing environment. The model framework is advantageous of: (1) Comprehensively allocating water and land resources on the basis of clarifying their interactions; (2) Balancing incompatible goals from multiple dimensions including resources, society, economy, ecology, and environment; (3) proposing alternative allocation schemes of AWLR that can response to the changing environment of both natural and socio-economic changes. Allocation schemes of AWLR based on the model framework are generated, analyzed and evaluated. The comprehensiveness, equilibrium, and security of multi-dimensional targets help obtain the optimum adaptation allocation plans of AWLR to cope with changing environment. The real-world case study in Songhua River Basin in Northeast China verifies the feasibility and practicality of the model framework. The study found that the model framework can manage AWLR in a sustainable way and meanwhile provide decision makers alternatives plans of AWLR for different natural and social changing environments, which will further contribute to the alleviation of agricultural water scarcity and the promotion of agricultural sustainable development.
5 Li, M.; Yang, X.; Wu, F.; Babuna, P. 2022. Spatial equilibrium-based multi-objective optimal allocation of regional water resources. Journal of Hydrology: Regional Studies, 44:101219. [doi: https://doi.org/10.1016/j.ejrh.2022.101219]
Water resources ; Water allocation ; Spatial equilibrium analysis ; Water conservation ; Water supply ; Water demand ; Towns ; Water use ; Decision making ; Socioeconomic development ; Environmental impact ; Economic benefits ; Indicators ; Case studies ; Models ; Uncertainty / China / Guangdong
(Location: IWMI HQ Call no: e-copy only Record No: H051484)
https://www.sciencedirect.com/science/article/pii/S2214581822002324/pdfft?md5=b291269772a0b77d86b7fb377373fd73&pid=1-s2.0-S2214581822002324-main.pdf
https://vlibrary.iwmi.org/pdf/H051484.pdf
https://vlibrary.iwmi.org/pdf/H051484.pdf
(9.30 MB) (9.30 MB)
Study region: Guangdong Province in China.
Study focus: Water shortages due to the spatially uneven distribution of water resources have become the main obstacle to the sustainable development of regional society and the economy. To alleviate this problem, this study developed a framework including prediction, optimization, and decision-making models to allocate available water resources among the different sectors of the cities in the region. The framework was advantageous in efficiently predicting future water demand and supply for multiple cities, quantitatively reflecting the level of the spatial equilibrium of water allocation (SEWA) through coupling coordination degree (CCD), and achieving a higher level of SEWA rather than just the equitable water distribution.
New hydrological insights for the region: The results indicated that: (i) by 2030, the deficit of water supply and demand of Guangdong Province would be further aggravated, with a water shortage rate of 4.18%; (ii) by optimal water allocation, the water shortage rate of Guangdong Province decreased to 1.56% and the level of SEWA improved significantly from moderate equilibrium to good equilibrium; and (iii) from 2018 to 2030, key water-saving sectors in different cities were identified, while the industrial sector had a higher water-saving intensity than other water use sectors. This study could provide references for integrated water allocation strategies to realize the coordinated development of socioeconomic and environmental systems in other regions of the world.
Study focus: Water shortages due to the spatially uneven distribution of water resources have become the main obstacle to the sustainable development of regional society and the economy. To alleviate this problem, this study developed a framework including prediction, optimization, and decision-making models to allocate available water resources among the different sectors of the cities in the region. The framework was advantageous in efficiently predicting future water demand and supply for multiple cities, quantitatively reflecting the level of the spatial equilibrium of water allocation (SEWA) through coupling coordination degree (CCD), and achieving a higher level of SEWA rather than just the equitable water distribution.
New hydrological insights for the region: The results indicated that: (i) by 2030, the deficit of water supply and demand of Guangdong Province would be further aggravated, with a water shortage rate of 4.18%; (ii) by optimal water allocation, the water shortage rate of Guangdong Province decreased to 1.56% and the level of SEWA improved significantly from moderate equilibrium to good equilibrium; and (iii) from 2018 to 2030, key water-saving sectors in different cities were identified, while the industrial sector had a higher water-saving intensity than other water use sectors. This study could provide references for integrated water allocation strategies to realize the coordinated development of socioeconomic and environmental systems in other regions of the world.
6 Xu, X.; Chen, Y.; Zhou, Y.; Liu, W.; Zhang, X.; Li, M.. 2023. Sustainable management of agricultural water rights trading under uncertainty: an optimization-evaluation framework. Agricultural Water Management, 280:108212. (Online first) [doi: https://doi.org/10.1016/j.agwat.2023.108212]
Water rights ; Uncertainty ; Optimization methods ; Evaluation ; Water resources ; Irrigation water ; Hydrological cycle ; Models ; Evapotranspiration ; Economic benefits ; Water supply ; Water demand ; Water use ; Indicators ; Water footprint ; Carbon footprint ; Water allocation ; Sustainable development ; Rice / China / Heilongjiang
(Location: IWMI HQ Call no: e-copy only Record No: H051718)
https://www.sciencedirect.com/science/article/pii/S037837742300077X/pdfft?md5=3053b49293b0c5e8a5380876d7685ede&pid=1-s2.0-S037837742300077X-main.pdf
https://vlibrary.iwmi.org/pdf/H051718.pdf
https://vlibrary.iwmi.org/pdf/H051718.pdf
(5.41 MB) (5.41 MB)
The optimal allocation of agricultural water rights is of great importance in promoting the efficient management of water resources in irrigation areas. In the process of agricultural water rights allocation, problems develop when the dynamics and uncertainties caused by changes in water cycle elements are ignored. To balance socioeconomic development and environmental protection, this study develops a model framework for evaluating and optimizing the synergistic management of agricultural water rights allocation trading under multiple uncertainties (AWRAS-TCME). The model is capable of reflecting the dynamic changes in meteorological and hydrological factors such as rainfall, evapotranspiration and runoff and quantitatively measures the synergistic effect of multidimensional objectives of the economy-society-resources-environment on water rights allocations and transactions. The AWRAS-TCME model integrates a two-level multiobjective nonlinear programming model and a projection tracking model into a framework to measure the fairness and economic benefits of water rights allocation based on an analysis of the sustainability of water rights prices in multiple dimensions, fully considering the influence of uncertainties in hydrological and social systems. The model was applied to an actual irrigation area, and the results showed that (1) total optimized water rights allocation was reduced by 4.7–20.9% at different levels of water supply and demand; (2) the total volume of water rights transfer among regions was increased by 4.8%-12.9%, and the trading volume of the water rights market was increased to account for 5%-16.2% of the total revenue; and (3) the optimal net income of water rights allocation was increased by 1.2%-3.3%, and the equity of water rights allocation was increased by 0.06–0.09. The developed model promotes the sustainable utilization of agricultural water resources in irrigated areas.
7 Lin, J.; Bryan, B. A.; Zhou, X.; Lin, P.; Do, H. X.; Gao, L.; Gu, X.; Liu, Z.; Wan, L.; Tong, S.; Huang, J.; Wang, Q.; Zhang, Y.; Gao, H.; Yin, J.; Chen, Z.; Duan, W.; Xie, Z.; Cui, T.; Liu, J.; Li, M.; Li, X.; Xu, Z.; Guo, F.; Shu, L.; Li, B.; Zhang, J.; Zhang, P.; Fan, B.; Wang, Y.; Zhang, Y.; Huang, J.; Li, X.; Cai, Y.; Yang, Z. 2023. Making China’s water data accessible, usable and shareable. Nature Water, 1:328-335. [doi: https://doi.org/10.1038/s44221-023-00039-y]
Water resources ; Data collection ; Databases ; Monitoring ; Modelling ; Water quality ; Wastewater treatment ; Stream flow ; Transboundary waters ; Water demand ; Infrastructure ; Policies / China
(Location: IWMI HQ Call no: e-copy only Record No: H052133)
(1.42 MB)
Water data are essential for monitoring, managing, modelling and projecting water resources. Yet despite such data—including water quantity, quality, demand and ecology—being extensively collected in China, it remains difficult to access, use and share them. These challenges have led to poor data quality, duplication of effort and wasting of resources, limiting their utility for supporting decision-making in water resources policy and management. In this Perspective we discuss the current state of China’s water data collection, governance and sharing, the barriers to open-access water data and its impacts, and outline a path to establishing a national water data infrastructure to reform water resource management in China and support global water-data sharing initiatives.
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