Search

Urban green space has increased significantly in many cities in China as a result of rapid urbanization. Despite various environmental and societal benefits of urban green space, its irrigation water use has become an important yet under-researched issue in urban water management. Using a newly developed green space evapotranspiration and soil water budgeting model coded in Python, this research estimated the irrigation water requirement of urban green space for 286 cities at the prefecture level and above in China, with daily meteorological data in 1986–2011, the distribution and areas of urban green space from the 30 m resolution “Essential Urban Land-Use Categories in China” database, and green space types from the 10 m resolution “10 m resolution global land cover” database. The estimated annual average irrigation water requirement of urban green space for these 286 cities was 8.7 billion m3, accounting for over 20% of residential water consumption in the cities where data on residential water use were available. We also investigated the spatiotemporal variation of urban green space irrigation water requirement and the factors that influence such variations. To the best of our knowledge, this study develops the first set of results of urban green space irrigation for all major cities in China, thus providing useful insights for green space irrigation and urban water man-agement in the context of rapid urbanization and sustainable water management.

The Mekong River is the largest transboundary river in Southeast Asia and the main source of water supply for agricultural irrigation in the Lower Mekong River Basin (LMRB), supporting socioeconomic development and the livelihoods of millions of people. Irrigation accounts for more than 70% of water use in the LMRB, and issues of water use and allocation in the basin attract much attention, especially in dry years. However, there is a lack of systematic and up-to-date estimation of irrigation water requirements (IWR) in the LMRB, for historical and climate change conditions, which are essential for water resources planning and management in the basin. We use gridded meteorological and crop land use data to estimate monthly IWR at 5-arc minute resolution in the five LMRB countries, namely Myanmar, Laos, Thailand, Cambodia and Vietnam, using meteorological observations of 1991-2020 and climate projections for 2031-2060 and 2061-2090 by five global climate models under two climate scenarios, SSP126 and SSP585. Crop water productivity and water footprint are also estimated along with IWR. Under historical climate, the total IWR in the LMRB is estimated to be 20.44 billion m3, with Vietnam having the largest share of 9.18 billion m3, followed by Thailand with 7.54 billion m3. IWR concentrates in the dry season of November-April, accounting for 78.4% of annual IWR. Rice is the main water-consuming crop, accounting for 86.7% of total IWR. Relative to historical climate condition, SSP126 generally leads to slightly decreased IWR, whereas SSP585 leads to a large increase in IWR. Crop water productivity of rice is unevenly distributed in the basin, being higher in Vietnam and Laos and lower in Cambodia and Thailand. Green water footprint of rice is about 3.7 times higher than that of blue water footprint, indicating most of rice water consumption is from precipitation. Under SSP126, there is little change in water footprint, however under SSP585 blue water footprint increases significantly, in 2061-2090. This study provides update-to-date and high-resolution IWR estimates which can support water use and allocation dialogue, policy-making and management in the basin.

Urban residential water uses entail energy consumption and associated carbon emissions. Reducing residential water uses thus can simultaneously save water and energy and help reduce carbon emissions. However, residential water uses are strongly affected by the choices of household appliances and fixtures, and water use behaviors. In this study, we first conducted a household water use survey in Shanghai, the largest city in China, to understand residential water use behaviors in different seasons. A two-stage stochastic optimization model is developed to optimize water and energy conservation decisions so as to minimize the expected total cost of water and water-related energy uses and maximize carbon emission reduction. Data collected through questionnaire surveys are used to parameterize the optimization model. Water and energy conservation choices are categorized into long- and short-term decisions. The results show that in Shanghai residential water uses has a strong impact on urban carbon emission reduction. Typical temperature range in different seasons strongly affects the effectiveness of short-term conservation actions. The results support a subsidy policy for water-saving appliances that can incentivize citizens in water-saving. Model results are useful for exploring the water-energy-carbon nexus of urban households considering seasonal factors

Agriculture is essential for economic growth in the Lower Mekong River basin (LMB), which plays a key role in ensuing water and food security of the riparian regions and provides livelihoods for tens of millions of people. Agricultural irrigation, hydropower development, increasing water demand from other sectors, and ecosystem protection necessitate taking a holistic approach when analyzing irrigation in the LMB. This paper examines the existing problems and opportunities of irrigation in the LMB from the angle of water-food-energy (WFE) nexus. We selected journal articles from the Web of Science database and imported them into CiteSpace, a bibliometric analysis software for visual exploration of scientific literature. The visualized results summarize the significance of authors and their affiliations in the selected body of literature, and the country-wise distribution. Four key research themes of LMB irrigation were identified based on the bibliometric analysis, for conducting an in-depth review. First, we investigated the factors that influence agricultural water management which directly affects irrigation water demand and supply as well as crop productivity. This part of the literature focused on water and land management and applications of various models to assess impacts on crop yields of irrigation management. Second, from the literature we analyzed the identified impacts of human flow alternations on downstream water uses, ecosystem health, and land subsidence due to groundwater overdraft. Nevertheless, upstream water management can mitigate downstream flood damages and augment dry-season water supply. Third, the spatiotemporal mismatch between water demand and supply pose a serious challenge for transboundary river basin management. Moreover, inappropriate water utilization, mismanagement and poor governance appear to be the more fundamental causes of the LMB water problems, thus calling for sound agricultural water policies within a riparian country and effective water management cooperation strategies across the riparian countries. Fourth, despite of the relatively few publications on the Mekong’s WFE nexus so far, this particular topic is gaining growing attention in the Mekong basin research community. Moreover, it offers a valuable holistic perspective for analyzing irrigation in the LMB, by considering its connections with the food and energy sectors in one way or another, compared against many existing studies that view irrigation as solely an agricultural water management problem.

Water shortage and soil salinization are main limiting factors in agricultural production in arid and semi-arid regions worldwide. Located in western Inner Mongolia of China, the Hetao Irrigation District (HID) is the largest gravity-fed irrigation district in Asia and one of the top three largest irrigation districts in China. Irrigation water overuse and high level of soil salinity are the main challenges that curb agricultural productivity, adversely affect farmers’ revenues, and threaten long-term sustainability of irrigated farming in the HID. Nevertheless, irrigation water allocation, salt leaching and accumulation, crop productivity and farming decisions are intrinsically connected and thus necessitate taking a holistic approach to investigate into the interactions among all those factors and devising appropriate technological, management and policy interventions. Towards this goal, an integrated hydro-agro--economic optimization model was developed to optimize water allocation among sub-irrigation districts, across stable and cash crops, and in the four irrigation events of a year that are unique for the HID. The model optimizes net revenue of the HID considering water and salt balance, the response of crops to salinity and water stress, land availability, and existing irrigation management practices that have been proved effective. The Positive Mathematical Programming (PMP) approach is used to calibrate the model such that it can reproduce base year observations of crop acreage, water uses and production costs and benefits, making the model suitable for evaluating alternative management and policy scenarios. Sensitivity analysis were conducted for initial groundwater table, initial soil salinity level and leaching coefficient, and the results were moderately sensitive to initial soil salinity and marginally sensitive to groundwater table and leaching coefficient values. Scenario analyses were conducted to analyze the effects of irrigation water supply, winter irrigation (non-growing period) water application, irrigation efficiency and crop commodity market prices. We found that water supply reduction increases land fallow and reduces net revenue. Winter irrigation can store soil moisture to increase summer crop planting areas and increase salt-leaching to lower crop salinity stress. However, irrigation water use efficiency improvement can cause unintended negative consequences, such as exacerbated soil salinization. Higher crop commodity market price increases planting areas and water allocation of the crop but reduce areas and water uses of other crops, leading to a “crowding-out” effects. These results and modeling exercises provide a holistic perspective and useful insights for future water, land and salinity management, irrigation infrastructure investment, and market risk management in the HID.