Your search found 7 records
1 Liu, D.; Wang, X.; Aminjafari, S.; Yang, W.; Cui, B.; Yan, S.; Zhang, Y.; Zhu, J.; Jaramillo, F. 2020. Using InSAR [Interferometric Synthetic Aperture Radar] to identify hydrological connectivity and barriers in a highly fragmented wetland. Hydrological Processes, 14p. (Online first) [doi: https://doi.org/10.1002/hyp.13899]
Wetlands ; Hydrological factors ; SAR (radar) ; Radar imagery ; Water levels ; Satellites ; Remote sensing ; Interferometry ; Barriers ; Ecosystems ; Grasslands ; Vegetation / China / Baiyangdian Wetland
(Location: IWMI HQ Call no: e-copy only Record No: H049975)
https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.13899
https://vlibrary.iwmi.org/pdf/H049975.pdf
https://vlibrary.iwmi.org/pdf/H049975.pdf
(3.71 MB) (3.71 MB)
Hydrological connectivity is a critical determinant of wetland functions and health, especially in wetlands that have been heavily fragmented and regulated by human activities. However, investigating hydrological connectivity in these wetlands is challenging due to the costs of high-resolution and large-scale monitoring required in order to identify hydrological barriers within the wetlands. To overcome this challenge, we here propose an interferometric synthetic aperture radar (InSAR)-based methodology to map hydrologic connectivity and identify hydrological barriers in fragmented wetlands. This methodology was applied along 70 transects across the Baiyangdian, the largest freshwater wetland in northern China, using Sentinel 1A and 1B data, covering the period 2016–2019. We generated 58 interferograms providing information on relative water level changes across the transects that showed the high coherence needed for the assessment of hydrological connectivity. We mapped the permanent and conditional (temporary) barriers affecting connectivity. In total, 11% of all transects are permanently disconnected by hydrological barriers across all interferograms and 58% of the transects are conditionally disconnected. Areas covered by reed grasslands show the most undisturbed hydrological connectivity while some of these barriers are the result of ditches and channels within the wetland and low water levels during different periods of the year. This study highlights the potential of the application of Wetland InSAR to determine hydrological connectivity and location of hydrological barriers in highly fragmented wetlands, and facilitates the study of hydrological processes from large spatial scales and long-time scales using remote sensing technique.
2 Shi, W.; Huang, S.; Liu, D.; Huang, Q.; Han, Z.; Leng, G.; Wang, H.; Liang, H.; Li, P.; Wei, X. 2021. Drought-flood abrupt alternation dynamics and their potential driving forces in a changing environment. Journal of Hydrology, 597:126179. [doi: https://doi.org/10.1016/j.jhydrol.2021.126179]
Drought ; Flooding ; Climate change ; Precipitation ; Meteorological factors ; Water vapour ; River basins ; Spatial distribution ; Time series analysis / China / Wei River Basin / Jing River Basin / Beiluo River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H050405)
(8.36 MB)
Compared with a single drought or flood, drought-flood abrupt alternation (DFAA) may have more adverse impact on water resources management, crop production, and food security. However, existing studies have paid seldom attention on the evolution characteristics of DFAA in northern China, and their driving factors have not yet been fully revealed. To this end, DFAA events such as drought to flood (DTF) and flood to drought (FTD) are examined from 1960 to 2010 in the Wei River basin (WRB) located in northern China, which is the largest tributary of the Yellow River Basin. Firstly, the long-cycle drought-flood abrupt transition index (LDFAI) is defined to identify DFAA events during the flood season of WRB. Secondly, the spatiotemporal evolution characteristics and future trend variability of DFAA events are explored based on LDFAI. Finally, the driving factors of DFAA events are comprehensively evaluated using qualitative and quantitative combination framework. Results indicate that (1) the frequency of DTF events in the WRB presents a “less-more-less” variation pattern from southwest to northeast and shows a significant spatial difference. However, the FDT events are vice versa; (2) the flood season is dominated by FTD events in the WRB, and the upstream of the WRB and Jing River basin (JRB) are dominated by the DTF events before mutation point; (3) the four sub-regions of the WRB show oscillation changes of “DTF-FDT” with 35-year period, and are prone to DTF events after 2010 years; and (4) average water vapor pressure is the dominant factor of DFAA events in the WRB compared with other meteorological factors, whereas Arctic Oscillation among multiple teleconnection factors exerts strong impacts on DFAA dynamics. The findings may be significant to the early warning and prevention of flood and drought disasters in the WRB under the challenge of future climate change.
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 Ali, S.; Liu, D.; Fu, Q.; Cheema, M. J. M.; Pham, Q. B.; Rahaman, Md. M.; Dang, T. D.; Anh, D. T. 2021. Improving the resolution of GRACE data for spatio-temporal groundwater storage assessment. Remote Sensing, 13(17):3513. (Special Issue: Remote Sensing and Modelling of Water Storage Dynamics from Bedrock to Atmosphere) [doi: https://doi.org/10.3390/rs13173513]
Groundwater assessment ; Water storage ; Irrigation systems ; Aquifers ; Groundwater table ; Soil moisture ; Evapotranspiration ; Runoff ; Models ; Satellites ; Neural networks / Pakistan / Sindh / Punjab / Indus Basin Irrigation System
(Location: IWMI HQ Call no: e-copy only Record No: H050649)
(9.12 MB) (9.12 MB)
Groundwater has a significant contribution to water storage and is considered to be one of the sources for agricultural irrigation; industrial; and domestic water use. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a unique opportunity to evaluate terrestrial water storage (TWS) and groundwater storage (GWS) at a large spatial scale. However; the coarse resolution of GRACE limits its ability to investigate the water storage change at a small scale. It is; therefore; needed to improve the resolution of GRACE data at a spatial scale applicable for regional-level studies. In this study; a machine-learning-based downscaling random forest model (RFM) and artificial neural network (ANN) model were developed to downscale GRACE data (TWS and GWS) from 1° to a higher resolution (0.25°). The spatial maps of downscaled TWS and GWS were generated over the Indus basin irrigation system (IBIS). Variations in TWS of GRACE in combination with geospatial variables; including digital elevation model (DEM), slope; aspect; and hydrological variables; including soil moisture; evapotranspiration; rainfall; surface runoff; canopy water; and temperature; were used. The geospatial and hydrological variables could potentially contribute to; or correlate with; GRACE TWS. The RFM outperformed the ANN model and results show Pearson correlation coefficient (R) (0.97), root mean square error (RMSE) (11.83 mm), mean absolute error (MAE) (7.71 mm), and Nash–Sutcliffe efficiency (NSE) (0.94) while comparing with the training dataset from 2003 to 2016. These results indicate the suitability of RFM to downscale GRACE data at a regional scale. The downscaled GWS data were analyzed; and we observed that the region has lost GWS of about -9.54 ± 1.27 km3 at the rate of -0.68 ± 0.09 km3/year from 2003 to 2016. The validation results showed that R between downscaled GWS and observational wells GWS are 0.67 and 0.77 at seasonal and annual scales with a confidence level of 95%, respectively. It can; therefore; be concluded that the RFM has the potential to downscale GRACE data at a spatial scale suitable to predict GWS at regional scales.
5 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.
6 Zeng, Y.; Liu, D.; Guo, S.; Xiong, L.; Liu, P.; Chen, J.; Yin, J.; Wu, Z.; Zhou, W. 2023. Assessing the effects of water resources allocation on the uncertainty propagation in the water-energy-food-society (WEFS) nexus. Agricultural Water Management, 282:108279. (Online first) [doi: https://doi.org/10.1016/j.agwat.2023.108279]
Water resources ; Water availability ; Nexus approaches ; Uncertainty ; Sustainable development ; Models ; Climate change ; Water shortage ; Water flow ; Upstream ; Downstream ; Water supply ; Food shortages ; Socioeconomic aspects ; Water demand ; Food production / Chaina / Hanjiang River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H051846)
https://www.sciencedirect.com/science/article/pii/S0378377423001440/pdfft?md5=34477725d5a384fd6fa305b41758a107&pid=1-s2.0-S0378377423001440-main.pdf
https://vlibrary.iwmi.org/pdf/H051846.pdf
https://vlibrary.iwmi.org/pdf/H051846.pdf
(8.09 MB) (8.09 MB)
The water–energy–food–society (WEFS) nexus is profiled for sustainable development. The WEFS nexus exhibits strong uncertainty owing to the stochasticity of model structure, and water availability uncertainty under climate change and human activities. The WEFS nexus remains highly risky, as the uncertainty propagation in the WEFS nexus under the regulation of water resources allocation has rarely been investigated. In this study, white Gaussian noises were integrated into a system dynamic model for the WEFS nexus simulation, transforming the nexus from deterministic to stochastic. Based on a Monte Carlo simulation of the stochastic WEFS nexus with water availability uncertainty, the copula function was applied to evaluate the joint distributions between water availability and water shortage rates in the upstream and downstream zones to investigate the uncertainty propagation in the WEFS nexus. The effects of water resources allocation on the uncertainty propagation were analyzed by setting different water resources allocation schemes. The proposed approach was applied to the mid–lower reaches of Hanjiang River basin in China as a case study. The results indicate that an effective water resources allocation scheme can ensure water supply, and diminish the impacts of water availability uncertainty on water supply through reservoir operation. The annual average water supply rate increased from 84.74% to 93.45%, and the standard deviation decreased from 3.37% to 1.78%. The high-level environmental awareness evoked by water or food shortages decreased significantly with smaller uncertainty. The co-evolution of the WEFS was ensured through its nexus. Water storage capacity was the vital factor to regulate the uncertainty propagation in the WEFS nexus. The impacts of upstream water availability uncertainty were efficiently regulated via reservoir operation for the zones with sufficient water storage capacity. Water supply was ensured and there was no significant response of the WEFS through its nexus to different water resources allocation schemes. If there was few water storage capacity in a zone, the water supply was remarkably influenced by the water availability uncertainty in the upstream zone. The water supply was difficult to ensure, and was sensitive to different water resources allocation schemes. The environmental awareness evoked by water or food shortages increased. The environmental awareness feedback under the impacts of the noises increased water demand uncertainty by altering the socioeconomic expansion, further increased WEFS uncertainty through its nexus, particularly when water availability was much smaller than water demand. The proposed approach can help quantify the effects of water resources allocation on the uncertainty propagation in the WEFS nexus and contribute to the sustainable development of the WEFS nexus.
7 Zeng, Y.; Liu, D.; Guo, S.; Xiong, L.; Liu, P.; Chen, J.; Chen, H.; Yin, J.; Wu, Z.; Zhou, W. 2024. Assessment of the impacts of water resources allocation on the reliability, resilience and vulnerability of the water–energy–food–society (WEFS) nexus system. Agricultural Water Management, 295:108780. [doi: https://doi.org/10.1016/j.agwat.2024.108780]
(Location: IWMI HQ Call no: e-copy only Record No: PendingH052815)
https://www.sciencedirect.com/science/article/pii/S037837742400115X/pdfft?md5=8496ca5a699c81f26bfb31572ae0b85d&pid=1-s2.0-S037837742400115X-main.pdf
https://vlibrary.iwmi.org/pdf/H052815.pdf
https://vlibrary.iwmi.org/pdf/H052815.pdf
(7.47 MB) (7.47 MB)
To ensure water, energy and food supply security in the future, examining resources shortage risks within the integrated management strategy of the water-energy-food-society (WEFS) nexus system under uncertainties is necessary. Reliability, resilience, and vulnerability (RRV) are the most popular criteria for quantifying risks. However, their current applications focus on individual systems and adopt constant resource shortage rate thresholds across different spatial scales. To consider the interconnections in the WEFS nexus system and reflect the spatial heterogeneities of resource shortage risks when estimating the RRV, this study proposed a framework for estimating the RRV of the WEFS nexus system under uncertainties through a WEFS nexus model integrating water resources allocation model. Water availability uncertainty was simulated using Monte Carlo simulation and inputted into the stochastic WEFS nexus model. The water, energy, and food shortage rates outputted from the WEFS nexus model were used to determine the RRV of the WEFS nexus system. The impacts of water resources allocation on the RRV of the WEFS nexus system were studied by investigating its response to different water resources allocation scenarios at the basin and operational zone scales. The results indicated that water resources allocation can effectively ensure water supply through reservoir operation and further decrease the shortage risk of water and food systems through its nexus. The vulnerability of the water system decreased from 15.87% to 6.71% and the RRV of the food system improved from 27.33%, 8.20%, and 13.15–69.84%, 26.17%, and 7.03%, respectively. The energy shortage risk increased with increasing energy demand, with a trade-off between water and energy systems, the RRV of which decreased from extremely low levels to 69.84%, 26.17%, and 7.03%. The water shortage risk exhibited spatial heterogeneities owing to the uneven distribution of the water regulating capacity. The water shortage risk significantly decreased in areas with sufficient water regulating capacity but remained high in areas with few water regulating capacity and further propagated from upstream to downstream through hydrologic connections. Even an insignificant water shortage can be found across the basin, risking water system and further the WEFS nexus system through its nexus. Our proposed framework for assessing the impacts of water resources allocation on the RRV of the WEFS nexus system can not only help understand the risk of the WEFS nexus system under uncertainties, but also contribute to the integrated planning and management of water, energy, and food.
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