Your search found 7 records
1 Wang, M.; Zheng, C. 1998. Ground water management optimization using genetic algorithms and simulated annealing: Formulation and comparison. Journal of the American Water Resources Association, 34(3):519-530.
(Location: IWMI-HQ Call no: PER Record No: H023013)
2 Wang, M.; Hjelmfelt, A. T.; Garbrecht, J. 2000. DEM aggregation for watershed modeling. Journal of the American Water Resources Association, 36(3):579-584.
(Location: IWMI-HQ Call no: PER Record No: H026360)
3 Ren, L.; Wang, M.; Li, C.; Zhang, W. 2002. Impacts of human activity on river runoff in the northern area of China. Journal of Hydrology, 261:204-217.
Rivers ; Runoff ; Precipitation ; Catchment areas / China / Yellow River / Haihe River / Luanhe River ; Songhuajiang River
(Location: IWMI-HQ Call no: P 7363 Record No: H037128)
4 Wang, M.; Tang, T.; Burek, P.; Havlik, P.; Krisztin, T.; Kroeze, C.; Leclere, D.; Strokal, M.; Wada, Y.; Wang, Y.; Langan, Simon. 2019. Increasing nitrogen export to sea: a scenario analysis for the Indus River. Science of the Total Environment, 694:133629. [doi: https://doi.org/10.1016/j.scitotenv.2019.133629]
Water pollution ; Sea pollution ; Chemical contamination ; Nitrogen ; River basins ; International waters ; Agricultural wastes ; Human wastes ; Climate change ; Nutrient management ; Socioeconomic development ; Models ; Estimation / Pakistan / India / China / Afghanistan / Indus River
(Location: IWMI HQ Call no: e-copy only Record No: H049540)
(2.41 MB)
The Indus River Basin faces severe water quality degradation because of nutrient enrichment from human activities. Excessive nutrients in tributaries are transported to the river mouth, causing coastal eutrophication. This situation may worsen in the future because of population growth, economic development, and climate change. This study aims at a better understanding of the magnitude and sources of current (2010) and future (2050) river export of total dissolved nitrogen (TDN) by the Indus River at the sub-basin scale. To do this, we implemented the MARINA 1.0 model (Model to Assess River Inputs of Nutrients to seAs). The model inputs for human activities (e.g., agriculture, land use) were mainly from the GLOBIOM (Global Biosphere Management Model) and EPIC (Environmental Policy Integrated Model) models. Model inputs for hydrology were from the Community WATer Model (CWATM). For 2050, three scenarios combining Shared Socio-economic Pathways (SSPs 1, 2 and 3) and Representative Concentration Pathways (RCPs 2.6 and 6.0) were selected. A novelty of this study is the sub-basin analysis of future N export by the Indus River for SSPs and RCPs. Result shows that river export of TDN by the Indus River will increase by a factor of 1.6–2 between 2010 and 2050 under the three scenarios. N90% of the dissolved N exported by the Indus River is from midstream sub-basins. Human waste is expected to be the major source, and contributes by 66–70% to river export of TDN in 2050 depending on the scenarios. Another important source is agriculture, which contributes by 21–29% to dissolved inorganic N export in 2050. Thus a combined reduction in both diffuse and point sources in the midstream sub-basins can be effective to reduce coastal water pollution by nutrients at the river mouth of Indus.
5 Wang, M.; Chen, X.; Sidike, A.; Cao, L.; DeMaeyer, P.; Kurban, A. 2021. Optimal allocation of surface water resources at the provincial level in the Uzbekistan Region of the Amudarya River Basin. Water, 13(11):1446. [doi: https://doi.org/10.3390/w13111446]
Surface water ; Water resources ; Water allocation ; River basins ; Water demand ; Water supply ; Water distribution ; Water use ; Livestock ; Irrigation ; Ecology ; Canals ; Economic aspects ; Models ; Optimization / Central Asia / Uzbekistan / Amudarya River Basin / Aral Sea / Kashkadarya River / Zarafshan River / Bukhara / Samarkand / Navoiy / Khorezm / Karakalpakstan / Karshi Canal
(Location: IWMI HQ Call no: e-copy only Record No: H050536)
(2.31 MB) (2.31 MB)
Water users in the Amudarya River Basin in Uzbekistan are suffering severe water use competition and uneven water allocation, which seriously threatens ecosystems, as shown, for example, in the well-known Aral Sea catastrophe. This study explores the optimized water allocation schemes in the study area at the provincial level under different incoming flow levels, based on the current water distribution quotas among riparian nations, which are usually ignored in related research. The optimization model of the inexact two-stage stochastic programming method is used, which is characterized by probability distributions and interval values. Results show that (1) water allocation is redistributed among five different sectors. Livestock, industrial, and municipality have the highest water allocation priority, and water competition mainly exists in the other two sectors of irrigation and ecology; (2) water allocation is redistributed among six different provinces, and allocated water only in Bukhara and Khorezm can satisfy the upper bound of water demand; (3) the ecological sector can receive a guaranteed water allocation of 8.237–12.354 km3; (4) under high incoming flow level, compared with the actual water distribution, the total allocated water of four sectors (except for ecology) is reduced by 3.706 km3 and total economic benefits are increased by USD 3.885B.
6 Wei, J.; Wang, M.; Mikelsons, K.; Jiang, L.; Kratzer, S.; Lee, Z.; Moore, T.; Sosik, H. M.; Van der Zande, D. 2022. Global satellite water classification data products over oceanic, coastal, and inland waters. Remote Sensing of Environment, 282:113233. [doi: https://doi.org/10.1016/j.rse.2022.113233]
Water resources ; Classification ; Satellite observation ; Coastal areas ; Inland waters ; Remote sensing ; Hyperspectral imagery ; Spectral analysis ; Biogeochemical cycle ; Uncertainty ; Case studies
(Location: IWMI HQ Call no: e-copy only Record No: H051470)
https://www.sciencedirect.com/science/article/pii/S003442572200339X/pdfft?md5=599b4e8903d886292de7a4fdbdd7064a&pid=1-s2.0-S003442572200339X-main.pdf
https://vlibrary.iwmi.org/pdf/H051470.pdf
https://vlibrary.iwmi.org/pdf/H051470.pdf
(8.68 MB) (8.68 MB)
Satellites have generated extensive data of remote sensing reflectance spectra (Rrs( )) covering diverse water classes or types across global waters. Spectral classification of satellite Rrs( ) data allows for the distinguishing and grouping of waters with characteristic bio-optical/biogeochemical features that may influence the productivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite (VIIRS). We developed and implemented a hyperspectral scheme that accounts for the Rrs( ) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation result suggests that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data appear to be a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, despite the need for continuous improvement toward perfection.
7 Li, Y.; Wang, M.; Wang, H. 2023. Towards consistency of value and order: cooperation strategies of international water projects. Surveys in Geophysics, 48(3):393-422. (Special Issue: Intelligent River Basins in China: A SMART Water Revolution) [doi: https://doi.org/10.1080/02508060.2023.2204690]
International waters ; Transboundary waters ; Water scarcity ; Strategies ; Water resources ; Risk ; Conflicts ; Political aspects ; Community involvement ; Participation ; Climate change ; International organizations ; International cooperation ; Water supply ; Investment ; Infrastructure ; Empowerment ; Developing countries ; Economic development
(Location: IWMI HQ Call no: e-copy only Record No: H051994)
(1.60 MB)
This article discusses the policy principles and strategy models for water resources projects around developing regions of the World Bank, the Asian Development Bank, African Development Bank, European Union, United States and Japan. To address conflicts and risks, they adapted different frameworks following a similar logic. A two-track sustainable model – value of isomorphism and order of symbiosis – is then identified, combining strategies of consistency, methodology diffusion, community participation and resource incentives.
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