Urban Water Security: Definition and Assessment Framework

Achieving urban water security is a major challenge for many countries. While several studies have assessed water security at a regional level, many studies have also emphasized the lack of assessment of water security and application of measures to achieve it at the urban level. Recent studies that have focused on measuring urban water security are not holistic, and there is still no agreed-upon understanding of how to operationalize and identify an assessment framework to measure the current state and dynamics of water security. At present, there is also no clearly defined and widely endorsed definition of urban water security. To address this challenge, this study provides a systematic approach to better understand urban water security, with a working definition and an assessment framework to be applied in peri-urban and urban areas. The proposed working definition of urban water security is based on the United Nations (UN) sustainable development goal on water and sanitation and the human rights on water and sanitation. It captures issues of urban-level technical, environmental, and socio-economic indicators that emphasize credibility, legitimacy, and salience. The assessment framework depends on four main dimensions to achieve urban water security: Drinking water and human beings, ecosystem, climate change and water-related hazards, and socio-economic factors (DECS). The framework further enables the analysis of relationships and trade-off between urbanization and water security, as well as between DECS indicators. Applying this framework will help governments, policy-makers, and water stakeholders to target scant resources more eff ectively and sustainably. The study reveals that achieving urban water security requires a holistic and integrated approach with collaborative stakeholders to provide a meaningful way to improve understanding and managing urban water security

Assessing Water Security in Water-Scarce Cities: Applying the Integrated Urban Water Security Index (IUWSI) in Madaba, Jordan

Water security is a major concern for water-scarce cities that face dynamic water challenges due to limited water supply, climate change and increasing water demand. Framing urban water security is challenging due to the complexity and uncertainties of the definitions and assessment frameworks concerning urban water security. Several studies have assessed water security by granting priority indicators equal weight without considering or adapting to the local conditions. This study develops a new urban water security assessment framework with application to the water-scarce city of Madaba, Jordan. The study applies the new assessment framework on the study area and measures urban water security using the integrated urban water security index (IUWSI) and the analytic hierarchy process (AHP) as a decision management tool to prioritise and distinguish indicators that affect the four dimensions of urban water security: drinking water, ecosystems, climate change and water-related hazards, and socioeconomic aspects (DECS). The integrated urban water security index (IUWSI) highlights the state of water security and intervention strategies in Madaba. The study reveals that urban water security in Madaba is satisfactory to meet basic needs, with shortcomings in some aspects of the DECS. However, Madaba faces poor security in terms of managing climate- and water-related risks. The IUWSI framework assists with a rational and evidence-based decision-making process, which is important for enhancing water resources management in water-scarce cities

Harmonization of Landsat and Sentinel 2 for Crop Monitoring in Drought Prone Areas: Case Studies of Ninh Thuan (Vietnam) and Bekaa (Lebanon)

Proper satellite-based crop monitoring applications at the farm-level often require near-daily imagery at medium to high spatial resolution. The combination of data from different ongoing satellite missions Sentinel 2 (ESA) and Landsat 7/8 (NASA) provides this unprecedented opportunity at a global scale; however, this is rarely implemented because these procedures are data demanding and computationally intensive. This study developed a robust stream processing for the harmonization of Landsat 7, Landsat 8 and Sentinel 2 in the Google Earth Engine cloud platform, connecting the benefit of coherent data structure, built-in functions and computational power in the Google Cloud. The harmonized surface reflectance images were generated for two agricultural schemes in Bekaa (Lebanon) and Ninh Thuan (Vietnam) during 2018–2019. We evaluated the performance of several pre-processing steps needed for the harmonization including the image co-registration, Bidirectional Reflectance Distribution Functions correction, topographic correction, and band adjustment. We found that the misregistration between Landsat 8 and Sentinel 2 images varied from 10 m in Ninh Thuan (Vietnam) to 32 m in Bekaa (Lebanon), and posed a great impact on the quality of the final harmonized data set if not treated. Analysis of a pair of overlapped L8-S2 images over the Bekaa region showed that, after the harmonization, all band-to-band spatial correlations were greatly improved. Finally, we demonstrated an application of the dense harmonized data set for crop mapping and monitoring. An harmonic (Fourier) analysis was applied to fit the detected unimodal, bimodal and trimodal shapes in the temporal NDVI patterns during one crop year in Ninh Thuan province. The derived phase and amplitude values of the crop cycles were combined with max-NDVI as an R-G-B false composite image. The final image was able to highlight croplands in bright colors (high phase and amplitude), while the non-crop areas were shown with grey/dark (low phase and amplitude). The harmonized data sets (with 30 m spatial resolution) along with the Google Earth Engine scripts used are provided for public use

Transdisciplinary research in support of land and water management in China and Southeast Asia : evaluation of four research projects

Unidad de excelencia María de Maeztu MdM-2015-0552Transdisciplinary research (TDR) aims at identifying implementable solutions to difficult sustainability problems and at fostering social learning. It requires a wellmanaged collaboration among multidisciplinary scientists and multisectoral stakeholders. Performing TDR is challenging, particularly for foreign researchers working in countries with different institutional and socio-cultural conditions. There is a need to synthesize and share experience among researchers as well as practitioners regarding how TDR can be conducted under specific contexts. In this paper, we aim to evaluate and synthesize our unique experience in conducting TDR projects in Asia. We applied guiding principles of TDR to conduct a formative evaluation of four consortium projects on sustainable land and water management in China, the Philippines, and Vietnam. In all projects, local political conditions restricted the set of stakeholders that could be involved in the research processes. The set of involved stakeholders was also affected by the fact that stakeholders in most cases only participate if they belong to the personal network of the project leaders. Language barriers hampered effective communication between foreign researchers and stakeholders in all projects and thus knowledge integration. The TDR approach and its specific methods were adapted to respond to the specific cultural, social, and political conditions in the research areas, also with the aim to promote trust and interest of the stakeholders throughout the project. Additionally, various measures were implemented to promote collaboration among disciplinary scientists. Based on lessons learned, we provide specific recommendations for the design and implementation of TDR projects in particular in Asia

Violent aggression predicted by multiple pre-adult environmental hits

Early exposure to negative environmental impact shapes individual behavior and potentially contributes to any mental disease. We reported previously that accumulated environmental risk markedly decreases age at schizophrenia onset. Follow-up of matched extreme group individuals (≤1 vs. ≥3 risks) unexpectedly revealed that high-risk subjects had >5 times greater probability of forensic hospitalization. In line with longstanding sociological theories, we hypothesized that risk accumulation before adulthood induces violent aggression and criminal conduct, independent of mental illness. We determined in 6 independent cohorts (4 schizophrenia and 2 general population samples) pre-adult risk exposure, comprising urbanicity, migration, physical and sexual abuse as primary, and cannabis or alcohol as secondary hits. All single hits by themselves were marginally associated with higher violent aggression. Most strikingly, however, their accumulation strongly predicted violent aggression (odds ratio 10.5). An epigenome-wide association scan to detect differential methylation of blood-derived DNA of selected extreme group individuals yielded overall negative results. Conversely, determination in peripheral blood mononuclear cells of histone-deacetylase1 mRNA as 'umbrella mediator' of epigenetic processes revealed an increase in the high-risk group, suggesting lasting epigenetic alterations. Together, we provide sound evidence of a disease-independent unfortunate relationship between well-defined pre-adult environmental hits and violent aggression, calling for more efficient prevention

Design of Watershed Bades Water Quality Monitoring: The Case of Nitrate Pollution in the Aconcagua River, Chile

The sustainable management of water resources is of high relevance with regard to overall socioeconomic development and environmental protection. Water quality monitoring plays a key role in this context as it provides the necessary information on the status of water resources and on the impact of human alterations of the hydrological cycle and hence forms an important basis for decision making. Current legislative approaches to water management like the European Water Framework Directive place a high importance to water quality monitoring. Monitoring systems have to provide relevant data in an efficient manner and are at the same time under budget constraints. This makes a case for optimization strategies for water quality monitoring networks, where the location of sampling stations and monitoring frequencies play a central role. Scientific methods to optimize water quality monitoring systems have been extensively described in literature. However, they are hardly ever applied since most of them depend on a-priory knowledge of the spatial and temporal variability of water quality parameters – information which is seldom available. The objective of this dissertation is to develop a method which allows estimating long term variability of water quality parameters. The parameter nitrate is chosen as an example parameter and the Aconcagua watershed in Chile is selected as a case study. The variability of nitrate concentrations over space and time is modelled on the basis of available hydrological, land use and point source data for the time period 1986 – 2006. For estimating nitrate exports to surface water the export coefficient method was used. The results are validated with measured nitrate concentrations of the same period. Results show that the model represents nitrate concentrations well for the upper and lower part of the watershed while low agreement between modelled and observed values was found for the lower part of the watershed, probably due to an insufficient representation of the hydrology of that zone but it could also be related to shortcomings of the current sampling methods at that particular monitoring station. Criteria for the location of monitoring stations and for the selection of monitoring frequencies were developed and applied together with the modelling results to develop recommendations for an optimized monitoring system. The main conclusions were on one hand that the current monitoring frequency of four samples per year is much too low recommending biweekly sampling instead; on the other hand one station could be omitted from the network as correlation between two stations was detected. The described method can serve as a general approach to support optimizing monitoring design if a minimum of data is available in order to estimate variance of a water quality parameter. This refers to daily information on discharges and to reliable estimates of point and diffuse pollution loadings to surface water. Thus, the method can be transferred to other watersheds and to other parameters

Modeling River Discharge Using Automated River Width Measurements Derived from Sentinel-1 Time Series

Against the background of a worldwide decrease in the number of gauging stations, the estimation of river discharge using spaceborne data is crucial for hydrological research, river monitoring, and water resource management. Based on the at-many-stations hydraulic geometry (AMHG) concept, a novel approach is introduced for estimating river discharge using Sentinel-1 time series within an automated workflow. By using a novel decile thresholding method, no a priori knowledge of the AMHG function or proxy is used, as proposed in previous literature. With a relative root mean square error (RRMSE) of 19.5% for the whole period and a RRMSE of 15.8% considering only dry seasons, our method is a significant improvement relative to the optimized AMHG method, achieving 38.5% and 34.5%, respectively. As the novel approach is embedded into an automated workflow, it enables a global application for river discharge estimation using solely remote sensing data. Starting with the mapping of river reaches, which have large differences in river width over the year, continuous river width time series are created using high-resolution and weather-independent SAR imaging. It is applied on a 28 km long section of the Mekong River near Vientiane, Laos, for the period from 2015 to 2018

Analysis of water footprints of rainfed and irrigated crops in Sudan

Water rather than land is the limiting factor for crop production in Sudan. This study attempts to use the water footprint (WFP) and virtual water concepts to account for crops water consumption under the Sudanese rainfed and irrigated conditions. The general average of the green WFP of sorghum and millet were found to be about 7700 and 10700 m3 ton-1, respectively. According to experimental results at three different climates, in-situ rainwater harvesting techniques could reduce the WFP of rainfed sorghum by 56% on the average. The blue component (surface water) shows the highest contribution to the total WFP of irrigated crops: 88% for cotton, 70% for sorghum, 68% for groundnut and 100% for wheat. However, the role of the green water (rainwater) is not marginal since it largely influences the operation and maintenance (silt clearance) of the gravity-fed irrigation system. Under normal conditions, the annual total virtual water demand of sorghum (the dominant food crop in Sudan) is found to be 15 km3, of which 91% is green water. During a dry year, however, Sudan could experience a deficit of 2.3 km3 of water, necessitating the adoption of a wise food stocking-exporting policy