168 research outputs found
Planning Green Space for Climate Change Adaptation and Mitigation: A Review of Green Space in the Central City of Beijing
No full textThe ongoing rapid urbanization and its socio-economic impacts on Chinese cities have engendered numerous environmental issues, food insecurity and significant stress on water resources besides accelerating some ecological degradation. Among these issues, urban-heat-island (UHI) and climate change in large cities had drawn much attention so that many researches on climate change adaptation and mitigation emerged in recent years. How to make the cities cool down and more liveable is more important than before for urban planning. Urban planners have been placing more stress on green space planning and the green environment of cities where dwellers crowd together. This paper is a review of green space in the Central City of Beijing under current situation and puts forward some advice on green space planning in responding to the climate change in the new era of China. Planning green space with the principal objective of “green-sponge-city” and the key concept of “low-carbon-city” is the primary adaptation and mitigation approach to climate change for urban planners and policymakers. No doubt, more attention and support from the government regarding strengthening green space systems in response to climate change will improve the liveability, resilience, and sustainability of cities in China
Agricultural Adaptation to Reconcile Food Security and Water Sustainability Under Climate Change: The Case of Cereals in Iran
No full textIn this study, we simulate the crop yield and water footprint (WF) of major food crops of Iran on irrigated and rainfed croplands for the historical and the future climate. We assesse the effects of three agricultural adaptation strategies to climate change in terms of potential blue water savings. We then evaluate to what extent these savings can reduce unsustainable blue WF. We find that cereal production increases under climate change in both irrigated and rainfed croplands (by 2.6-3.1 and 1.4-2.3 million t y-1, respectively) due to increased yields (6.6%-78.7%). Simultaneously, the unit WF (m3 t-1) tends to decrease in most scenarios. However, the annual consumptive water use increases in both irrigated and rainfed croplands (by 0.3-1.8 and 0.5-1.7 billion m3 y-1, respectively). This is most noticeable in the arid regions, where consumptive water use increases by roughly 70% under climate change. Off-season cultivation is the most effective adaptation strategy to alleviate additional pressure on blue water resources, with blue water savings of 14-15 billion m3 y-1. The second most effective is WF benchmarking, which results in blue water savings of 1.1-3.5 billion m3 y-1. The early planting strategy is less effective, but still leads to blue water savings of 1.7-1.9 billion m3 y-1. In the same order of effectiveness, these three strategies can reduce blue water scarcity and unsustainable blue water use in Iran under current conditions. However, we find that these strategies do not mitigate water scarcity in all provinces per se, nor all months of the year
From global goals to local gains—a framework for crop water productivity
No full textCrop water productivity (CWP) has become a recognised indicator in assessing the state of Sustainable Development Goals (SDG) 6.4—to substantially increase water use efficiency. This indicator, while useful at a global scale, is not comprehensive at a local scale. To fill this gap, this research proposes a CWP framework, that takes advantage of the spatio-temporal availability of remote sensing, that identifies CWP goals and sub-indicators specific to the needs of the targeted domain. Three sub-indicators are considered; (i) a global water productivity score (GWPS), (ii) a local water productivity score (LWPS) and (iii) a land and water use productivity score (YWPS). The GWPS places local CWP in the global context and focuses on maximised CWP. The LWPS differentiates yield zones, normalising for potential product, and focuses on minimising water consumption. The YWPS focuses simultaneously on improving land and water productivity equally. The CWP framework was applied to potato in the West Bank, Palestine. Three management practices were compared under each sub-indicator. The case study showed that fields with high and low performance were different under each sub-indicator. The performance associated with different management practices was also different under each sub-indicator. For example, a winter rotation had a higher performance under the YWPS, the fall rotation had a higher performance under the LWPS and under the GWPS there was little difference. The results showed, that depending on the basin goal, not only do the sub-indicators required change, but also the management practices or approach required to reach those basin goals. This highlights the importance of providing a CWP framework with multiple sub-indicators, suitable to basin needs, to ensure that meeting the SDG 6.4 goal does not jeopardise local objectives.Water Resource
Evaluating the Greenness of Sanandaj City Using Sentinel Imagery in Google Earth Engine
No full textUrban greenery and cooling initiatives have become top priorities for municipalities worldwide as they contribute to improved environmental quality and urban resilience. This study leverages advancements in remote sensing (RS) and cloud-based processing to assess and monitor changes in public urban green spaces (PUGS) in Sanandaj, Iran. Using high-resolution Sentinel-2 imagery (10 m) processed in Google Earth Engine (GEE), we calculated and mapped the normalized difference vegetation index (NDVI) across 20 major PUGSs over a five-year period, from 2019 to 2023. A total of 507 Sentinel-2 images were analyzed, offering a comprehensive view of seasonal and annual greenness trends. Our findings reveal that May is the peak month for greenery, while February consistently shows the lowest NDVI values, indicating seasonal greenness variability. Specifically, the mean NDVI of PUGSs decreased significantly between 2019 and 2022, with values recorded at 0.735, 0.737, 0.622, 0.417, and 0.570 in the greenest month of each respective year, highlighting a noticeable decline in vegetation health and extent. This reduction can be attributed to water scarcity and suboptimal management practices, as evidenced by dried or underperforming green spaces in recent years. Our results underscore the potential of integrating NDVI-based assessments within urban development frameworks to more accurately define and sustain PUGSs in Sanandaj. This methodology provides a replicable approach for cities aiming to optimize urban greenery management through RS technology
Summer Nights in Berlin, Germany: Modeling Air Temperature Spatially With Remote Sensing, Crowdsourced Weather Data, and Machine Learning
No full textUrban areas tend to be warmer than their rural surroundings, well-known as the “urban heat island” effect. Higher nocturnal air temperature (Tair) is associated with adverse effects on human health, higher mortality rates, and higher energy consumption. Prediction of the spatial distribution of Tair is a step toward the “Smart City” concept, providing an early warning system for vulnerable populations. The study of the spatial distribution of urban Tair was thus far limited by the low spatial resolution of traditional data sources. Volunteered geographic information provides alternative data with higher spatial density, with citizen weather stations monitoring Tair continuously in hundreds or thousands of locations within a single city. In this article, the aim was to predict the spatial distribution of nocturnal Tair in Berlin, Germany, one day in advance at a 30-m resolution using open-source remote sensing and geodata from Landsat and Urban Atlas, crowdsourced Tair data, and machine learning (ML) methods. Results were tested with a “leave-one-date-out” training scheme (testingcrowd) and reference Tair data (testingref). Three ML algorithms were compared-Random Forest (RF), Stochastic Gradient Boosting, and Model Averaged Neural Network. The optimal model based on accuracy and computational speed is RF, with an average root mean square error (RMSE) for testingcrowd of 1.16 °C (R 2 = 0.512) and RMSE for testingref of 1.97 °C (R 2 = 0.581). Overall, the most important geographic information system (GIS) predictors were morphometric parameters and albedo. The proposed method relies on open-source datasets and can, therefore, be adapted to many cities worldwide
The blue water footprint of urban green spaces: An example for Adelaide, Australia
No full textThe development of ‘greening’ cities introduces an uneasy tension between more green spaces and the increased use of scarce blue water resources to maintain this greenness, particularly in dry regions. This paper presents the first estimate of the blue water footprint (WF) of urban greenery. We estimated total water consumption of a 10-hectare parkland in Adelaide, South Australia. Evapotranspiration of the urban vegetation was estimated by monitoring soil water inflows, outflows, and storage changes at an experimental site representing different species, microclimates, and plant densities, the most critical parameters affecting water use. The total WF was estimated at 11,140 m3/ha per year, 59% from blue water (irrigation), and 41% from green water (rainwater), with the highest water consumption in summer. The dependency on blue water resources for maintaining the greenery varied from 49% in October to 67% in March. Even in the wet period of the year, there was a significant blue WF. Given the lack of blue water resources to allocate for further greening the city in an arid environment, we suggest an integrated adaptive management strategy to maintain available greenery and expand green spaces with a minimum of extra pressure on blue water resources
Agro-economic and socio-environmental assessments of food and virtual water trades of Iran
No full textAbstract Ending hunger and ensuring food security are among targets of 2030’s SDGs. While food trade and the embedded (virtual) water (VW) may improve food availability and accessibility for more people all year round, the sustainability and efficiency of food and VW trade needs to be revisited. In this research, we assess the sustainability and efficiency of food and VW trades under two food security scenarios for Iran, a country suffering from an escalating water crisis. These scenarios are (1) Individual Crop Food Security (ICFS), which restricts calorie fulfillment from individual crops and (2) Crop Category Food Security (CCFS), which promotes “eating local” by suggesting food substitution within the crop category. To this end, we simulate the water footprint and VW trades of 27 major crops, within 8 crop categories, in 30 provinces of Iran (2005–2015). We investigate the impacts of these two scenarios on (a) provincial food security (FSp) and exports; (b) sustainable and efficient blue water consumption, and (c) blue VW export. We then test the correlation between agro-economic and socio-environmental indicators and provincial food security. Our results show that most provinces were threatened by unsustainable and inefficient blue water consumption for crop production, particularly in the summertime. This water mismanagement results in 14.41 and 8.45 billion m3 y−1 unsustainable and inefficient blue VW exports under ICFS. “Eating local” improves the FSp value by up to 210% which lessens the unsustainable and inefficient blue VW export from hotspots. As illustrated in the graphical abstract, the FSp value strongly correlates with different agro-economic and socio-environmental indicators, but in different ways. Our findings promote “eating local” besides improving agro-economic and socio-environmental conditions to take transformative steps toward eradicating food insecurity not only in Iran but also in other countries facing water limitations
River basin-scale flood hazard assessment using a modified multi-criteria decision analysis approach: A case study
No full textFlood is a major natural hazard with extremely large impact on social-ecological systems. Therefore, developing reliable and efficient tools to identify areas vulnerable to potential flooding is vital for water managers, engineers and decision makers. Moreover, being able to accurately classify the level of hazard is a step forward towards more efficient flood hazard mapping. This study presents a multi-criteria index approach to classify potential flood hazards at the river basin scale. The presented methodology was implemented in the Mashhad Plain basin in North-east Iran, where flood has been a major issue in the last few decades. In the present study, seven factors, selected based on their greater influence towards flooding, were identified and extracted from the basic thematic layers to be used to generate a five-class Flood Hazard Index (FHI) map. The Soil and Water Assessment Tool (SWAT) was used to develop a runoff coefficient map, which was found to be the most influential factor. A sensitivity analysis was performed and the results incorporated to generate a modified Flood Hazard Index (mFHI) map. The accuracy of the proposed method was evaluated against the well-documented flood records in the last 42 years at the study area. The results showed that, for both FHI and mFHI maps, more than 97% of historical flood events have occurred in moderate to very high flood hazard areas. This demonstrates that incorporating hydrological model (such as SWAT) and multi-criteria analysis introduces a robust methodology to generate comprehensive potential flood hazard maps. Moreover, the proposed modified methodology can be used to identify high potential flood hazard zones and work towards more efficient flood management and mitigation strategies
Powers of Powerlessness: The Politics of Defeat in the Cinema of Nouri Bouzid
No full text This article examines the cultural politics of defeat in the cinema of Tunisian filmmaker Nouri Bouzid. Taking a lead from Bouzid’s directorial début Man of Ashes, the author focuses on Golden Horseshoes (1989) and Making of (2006), the two films that best dramatize the continuities between the crisis of filiation and the crisis of affiliation, and that deal head-on with left-wing (socialism) and right-wing (religious fundamentalism) ideologies. These two early films paint the broad strokes of Bouzid’s cinematic project, specifically its entwined dramatization of the crisis of filiation ( Man of Ashes) and the crisis of affiliation ( Golden Horseshoes), the profound loss of any discernible project of psychoaffective investiture, intellectual commitment and decolonial resistance, especially in the wake of the spectacular dissolution of international socialism and the ensuing triumphalism of global capitalism and financial imperialism. </jats:p
Water requirements of urban landscape plants in an arid environment: The example of a botanic garden and a forest park
No full textCreation and conservation of urban parks is challenging in arid environments where daily thermal extremes, water scarcity, air pollution and shortage of natural green spaces are more conspicuous. Water scarcity in the arid regions of Iran is major challenge for water managers. Accurate estimation of urban landscape evapotranspiration is therefore critically important for cities located in naturally dry environments, to appropriately manage irrigation practices. This study investigated two factor-based approaches, Water Use Classifications of Landscape Species (WUCOLS) and Landscape Irrigation Management Program (LIMP), to measure the water demand of two heterogeneous urban landscapes: a botanic garden and a sparse forest park. The irrigation water volume applied was compared with the gross water demand for the period from 2011 to 2013. In this research, WUCOLS estimated the annual water requirement of a botanic garden and a sparse forest park to be 5% and 44% lower, respectively, than LIMP. Comparison of estimated and applied irrigation showed that water savings can be made by the LIMP method. The outcomes of this research stressed the need to modify the irrigation requirements based on effective rainfall throughout the year, rather relying on long-term average data
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