Urban drought challenge to 2030 sustainable development goals

Advancing deep learning-based acoustic leak detection methods towards application for water distribution systems from a data-centric perspective

Against the backdrop of severe leakage issue in water distribution systems (WDSs), numerous researchers have focused on the development of deep learning-based acoustic leak detection technologies. However, these studies often prioritize model development while neglecting the importance of data. This research explores the impact of data augmentation techniques on enhancing deep learning-based acoustic leak detection methods. Five random transformation-based methods-jittering, scaling, warping, iterated amplitude adjusted Fourier transform (IAAFT), and masking-are proposed. Jittering, scaling, warping, and IAAFT directly process original signals, while masking operating on time-frequency spectrograms. Acoustic signals from a real-world WDS are augmented, and the efficacy is validated using convolutional neural network classifiers to identify the spectrograms of acoustic signals. Results indicate the importance of implementing data augmentation before data splitting to prevent data leakage and overly optimistic outcomes. Among the techniques, IAAFT stands out, significantly increasing data volume and diversity, improving recognition accuracy by over 7%. Masking enhances performance mainly by compelling the classifier to learn global features of the spectrograms. Sequential application of IAAFT and masking further strengthens leak detection performance. Furthermore, when applying a complex model to acoustic leakage detection through transfer learning, data augmentation can also enhance the effectiveness of transfer learning. These findings advance artificial intelligence-driven acoustic leak detection technology from a data-centric perspective towards more mature applications.

Characterizing the water resource-environment-ecology system harmony in Chinese cities using integrated datasets: A Beautiful China perspective assessment

Integrated management and synergistic improvement of the water system is a topic of widespread concern. This study innovatively integrates three functions of quality assessment, synergy evaluation, and driving influence determination to establish a systematic framework assessing water system harmony. A case study of 336 Chinese cities is further performed by combining multi-scale and multi-source datasets. The results show China's water system quality has improved from 2015 to 2022. Development in the water resource, environment, and ecology subsystems have been differentiated, with 0.05 %, 4.33 %, and -1.64 % changes, respectively. The degradation of water ecology and the weak synergy with the other two subsystems have limited China's water system harmony. Water environment improvement played a contributive role in improving the water system quality. The contribution structure of water resources, environment, and ecology has shifted towards equilibrium in recent years. We found and highlighted the north-south differentiation of water system harmony in Chinese cities. The Beijing-Tianjin-Hebei and its surroundings, the Yangtze River Delta, and the middle reaches of the Yangtze River are identified as priority regions for water system harmony improvement. The primary contribution of this study is to propose an assessing concept of water resource-environment-ecology system harmony, establish well-structured assessment methods, and integrate the multiple data sources. The novel methods and findings, including the indicator system, application of data mining and decomposing methods, and the city-level water system harmony map, deconstruct and quantify the complex and diverse water system, supporting clearer and more efficient water management policymaking.

Recent Progress on Synthesis and Properties of Black Phosphorus and Phosphorene As New-Age Nanomaterials for Water Decontamination

Concerted efforts have been made in recent years to find solutions to water and wastewater treatment challenges and eliminate the difficulties associated with treatment methods. Various techniques are used to ensure the recycling and reuse of water resources. Owing to their excellent chemical, physical, and biological properties, nanomaterials play an important role when integrated into water/wastewater treatment technologies. Black phosphorus (BP) is a potential nanomaterial candidate for water and wastewater treatment, especially its monolayer 2D derivative called phosphorene. Phosphorene offers relative adjustability in its direct bandgap, high charge carrier mobility, and improved in-plane anisotropy compared to the most extensively studied 2D nanomaterials. In this study, we examined the physical and chemical characteristics and synthetic processes of BP and phosphorene. We provide an overview of the latest advancements in the main applications of BP and phosphorene in water/wastewater treatment, which are categorized as photocatalytic, adsorption, and membrane filtration processes. Additionally, we explore the existing difficulties in the integration of BP and phosphorene into water/wastewater treatment technologies and prospects for future research in this field. In summary, this review highlights the ongoing necessity for significant research efforts on the integration of BP and phosphorene in water and wastewater applications.

Between flood and drought: How cities are facing water surplus and scarcity

Droughts and floods are weather-related hazards affecting cities in all climate zones and causing human deaths and material losses on all inhabited continents. The aim of this article is to review, analyse and discuss in detail the problems faced by urban ecosystems due to water surplus and scarcity, as well as the need of adaptation to climate change taking into account the legislation, current challenges and knowledge gaps. The literature review indicated that urban floods are much more recognised than urban droughts. Amongst floods, flash floods are currently the most challenging, which by their nature are difficult to monitor. Research and adaptation measures related to water-released hazards use cutting-edge technologies for risk assessment, decision support systems, or early warning systems, among others, but in all areas knowledge gaps for urban droughts are evident. Increasing urban retention and introducing Low Impact Development and Nature-based Solutions is a remedy for both droughts and floods in cities. There is the need to integrate flood and drought disaster risk reduction strategies and creating a holistic approach.

Assessment of groundwater and surface water quality in a typical mining community: application of water quality indices and hierarchical cluster analyses

The rate at which freshwater sources are being contaminated by mining operations in the South-Western part of Ghana is alarming. However, no study has quantified the degree of contamination of the freshwater in such areas, leaving a gap in the literature that requires immediate attention. This study assessed the quality of the surface and groundwater in the Tarkwa Nsuaem Municipality. Even though the physical parameters such as pH and electrical conductivity were indicative of safe freshwater, other parameters such as turbidity, total suspended solids (TSS), dissolved oxygen (DO), and heavy metals in the water sources were high; thus, confirming possible leaching, runoff, and dissolution of the hazardous substances employed in the manganese mining operations. The water quality of 82% of the water sources along the Kawere Stream was low (Classes III and IV). Therefore, the local people are at risk of contracting water-related diseases, and health problems associated with the ingestion of Fe, As, and Mn. The findings in this study are important in establishing the rate at which mining operations are reducing the quality of freshwater in developing countries, and potentially affecting human health.

Delay in timing and spatial reorganization of rainfall due to urbanization- analysis over India’s smart city Bhubaneswar

Bhubaneswar is the first designed ‘smart city’ in India and has experienced rapid urbanization since 2000. The question undertaken in this study is to assess if there is a change in the rainfall over this rapidly urbanizing region, and if so, what are the characteristics of the change? The broader intent is to understand if the change in urbanization and rainfall are interlinked? The India Meteorological Department (hourly station and daily gridded) and Tropical Rainfall Measurement Mission (3-hourly) datasets are analyzed for the 1980–2018 period (39 years) for different seasons separately. Wavelet and trend analysis reveal that precipitation intensity has increased over the study period. The assessments of the hourly rainfall data show an interesting feature. There is a decrease in the midnight to early-morning rain, with a corresponding increase in the late-afternoon to midnight rainfall. The increase in the rainfall is preferentially downwind and on the east side of the city. A supervised classified land use land cover map of the Bhubaneswar region is developed for 1980, 1990, 2000, 2010, and 2019 using Landsat imagery to compute the urban sprawl. The urban area and population density over Bhubaneswar is increasing with time. Analysis of the LULC and rainfall data indicates that the rainfall over urban regions and the shift in the timing of rains to evenings is highly correlated with the urban sprawl.

A systematic review and quantitative meta-analysis of the relationships between driving forces and cyanobacterial blooms at global scale

The global expansion of cyanobacterial blooms poses a major risk to the safety of freshwater resources. As a result, many explorations have been performed at a regional scale to determine the underlying impact mechanism of cyanobacterial blooms for one or several waterbodies. However, two questions still need to be answered quantitatively at a global scale to assist the water management. One is to specify which factors were often selected as the driving forces of cyanobacterial blooms, and the other is to estimate their quantitative relationships. For that, this paper applied a systematic literature review for 41 peer-reviewed studies published before May 2021 and a statistical meta-analysis based on the Pearson's or Spearman's correlation coefficients from 27 studies. These results showed that the water quality, hydraulic conditions, meteorological conditions and nutrient levels were often considered the driving forces of cyanobacterial blooms in global freshwater systems. Among these, meteorological conditions and nutrient level had the highest probability of being chosen as the driving force. In addition, knowledge of the quantitative relationships between these driving forces and cyanobacterial blooms was newly synthesized based on the correlation coefficients. The results indicated that, at a global scale, meteorological conditions were negatively related to cyanobacterial blooms, and other driving forces, such as water quality, hydraulic conditions and nutrient levels, were positively related to cyanobacterial blooms. In addition, the measurement indicators of these driving forces had diverse forms. For example, the nutrient level can be measured by the concentration of different forms of nitrogen or phosphorus, which may lead to different results in correlation analysis. Thus, a subgroup meta-analysis was necessary for the subdivided driving forces and cyanobacterial blooms, which had a better accuracy. Overall, the synthesized knowledge can help guide advanced cyanobacteria-centered water management, especially when the necessary cyanobacterial data of targeting waterbodies are inaccessible.

Multivariable integrated risk assessment for cyanobacterial blooms in eutrophic lakes and its spatiotemporal characteristics

Climate change has catalyzed the global expansion of cyanobacterial blooms in eutrophic , lakes and threatens water security. In most studies, the cyanobacterial bloom risk levels in lakes were evaluated using field-collected data from multiple indicators or spatially continuous data from one cyanobacteria-related indicator. Nevertheless, the occurrence of cyanobacterial blooms in lakes has clear spatial heterogeneity and is affected by numerous factors. Therefore, we developed a multivariable integrated risk assessment framework for cyanobacterial blooms in lakes using five spatially continuous datasets to estimate the risk level of cyanobacterial blooms at the pixel scale (250 m). The spatial and temporal variations in cyanobacterial bloom risk levels from May 1, 2002, to October 31, 2020, were investigated for three typical eutrophic lakes in China: Lakes Taihu, Chaohu, and Dianchi. Seasons and regions of high cyanobacterial bloom risk were identified for each lake. Environmental characteristics were discussed. A long-term investigation revealed that owing to its warm climate, the cyanobacterial risk levels in summer and autumn were much higher than those in the other two seasons. At the synoptic scale, Lake Taihu had a lower cyanobacterial bloom risk than Lakes Chaohu and Dianchi. A further comparison found that precipitation, wind speed, and temperature were responsible for the differences in cyanobacterial bloom risk levels among the three lakes. At the pixel scale, the risk map indicated that the cyanobacterial bloom risk levels of Lake Taihu were unevenly distributed, and the cyanobacterial bloom risk of the lakeshore was higher than that of the other subregions. Nutrient levels played the most critical role in the regional differences in cyanobacterial bloom risk levels in a lake. While the differences of cyanobacterial bloom risk levels in three lakes were resulted by the climates. Bloom events were defined and classified as "long-term bloom" or "flash bloom" according to their duration (over or below a year). Overall, this study can assist in advanced water management with a pixel-scale evaluation of cyanobacterial bloom risk levels.

Comparative Economic and Life Cycle Analysis of Future Water Supply Mix Scenarios for Hong Kong - A Water Scarce City

Increasing urbanization and changes in climate have placed increasing stress on urban water supply systems. Policy makers have increasingly adopted alternative water supply sources, such as desalination and water reclamation to meet this challenge, however these technologies may increase the negative environmental impacts of the water supply system. These alternative sources are energy intensive, and more expensive to produce, which raises questions about their sustainability. In this study, a Life Cycle Assessment (LCA) and a economic portfolio choice model were used to determine the impacts of Hong Kong's long term water policy. The results of our study show that the current water policy will increase the carbon emissions of producing 1 m³ of freshwater by 11% to 1.65 kg CO2-Eq due to the addition of desalination. However, a fit-for-purpose water policy approach only increases emission by 4%, to 1.54 kg CO2-Eq, by instead relying on water reclamation to offset freshwater consumption. Impacts from increased energy consumption were mitigated by improved wastewater treatment, which reduced CH₄ emissions. Although, ozone layer impacts increased due to higher NOx and N₂O emissions, highlighting the need to consider emissions from wastewater treatment processes when evaluating water reclamation processes. Impacts to water prices were also minimized when reclaimed water was chosen over desalination, due to its lower unit production cost. By considering both cost and environmental impacts of such system level changes, decision makers can more accurately evaluate different water supply approaches for data-driven policymaking.

Developing computable sustainable urbanization science: interdisciplinary perspective

In this era of drastic global change, the Anthropocene, carbon neutrality and sustainable development have become common twenty-first century human challenges and goals. Large-scale urbanization is indicative of human activities and provides an important impetus for environmental changes; therefore, cities have become an important stage in which to promote a more sustainable future development of human society. However, current researchers study urbanization issues based on the perspectives and tools of their respective disciplines; therefore, a holistic and comprehensive understanding of urbanization is lacking due to the insufficient integration of multidisciplinary study perspectives. We explored the construction of interdisciplinary computable sustainable urbanization and introduces a conceptual framework for interdisciplinary urbanization, as scientific computing supports and integrates the natural sciences and humanities to simulate urban evolution and further observe, explain, and optimize human and environment interactions in urban areas. We advocated for the establishment of major international research programs and organizations in the field of sustainable urbanization, and the cultivation of talented young professionals with broad-ranging interdisciplinary interests. Expectantly, we hope a livable planet in the Anthropocene era could be created by developing sustainable urbanization and achieving carbon neutrality.

Technological drought: a new category of water scarcity

In this paper, we argue that current definitions of drought, especially in the context of small-scale agricultural production, are incomplete. We introduce the concept of 'technological drought' to account for crop failures, reduced yields or water scarcity, which are the consequence of an inability to supplement water when there is a lack of irrigation technology and/or existing poor water management. We illustrate the diversity of causes of technological drought, which can include shortages of fuel or electricity to operate pumps, problematically high costs to access irrigation infrastructure, or constrained access to pumps that have to be shared among multiple farmers. We argue that vulnerability to technological drought can be strongly conditioned by socio-economic conditions and that its impact can be magnified when population growth and the demand for food mean that any decline in yield can have serious consequences for food security. We show that technological drought is a complex phenomenon, and can be differentiated from the more widely-recognised classes of drought (meteorological, agricultural, hydrological, and socio-economic) in multiple ways. In particular, technological drought exhibits an important dependence on the socio-economic context of agricultural production. It is perhaps most evident in developing economies, especially where agricultural output depends strongly on the capacity of individual farmers to manage crop water supply on small holdings. Technological drought can follow from even brief interruptions to monsoon rainfall during critical stages of crop growth, such that technological droughts can be distinguished from other forms of drought by their brevity.

Does Public Awareness Matter to Achieve the UN’s Sustainable Development Goal 6: Clean Water for Everyone?

United Nations set a Sustainable Development Goal to provide clean water for everyone (SDG 6). The successful implementation of SDG 6 is still miles to go. Public awareness’s role as a key factor in achieving Sustainable Development Goal 6 is vital but received less attention from researchers in the past. To understand the role of public awareness and other relevant factors in achieving SDG 6, we have collected a cross-sectional dataset from a developing country and applied a partial least square structural equation modelling approach. The results revealed that willingness to pay for clean water, social influence, and facilities provided by the government, public awareness, and knowledge about contaminated water positively influence the households’ intentions to use clean water. We also found that public awareness partially mediates relationships. Study results have useful policy implications for governments, NGOs, and other stakeholder organizations working on achieving SDG 6 in developing countries.

Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin

Analyzing historical droughts is essential to improve the assessment of future hydrological risks and to understand the effects of climate variability on streamflow. However, prolonged and consistent hydrological time series are scarce in the Brazilian savanna region. This study aimed to analyze the performance of climate reanalysis products in precipitation estimation, hydrological modeling, and historical drought analysis in a Brazilian savanna basin. For this purpose, precipitation data from the twentieth-century atmospheric model ensemble (ERA-20CM) and the land component of the fifth generation of European ReAnalysis (ERA5-Land) with bias correction were used. The weather variables were obtained from the Climatic Research Unit (CRU) and the hydrological modeling was performed using the Soil and Water Assessment Tool (SWAT). The Standardized Streamflow Index (SSI) was used to calculate hydrological drought in the basin. Overall, ERA5-Land performed satisfactorily in precipitation estimation, mainly on the monthly time scale, hydrological modeling, and drought prediction. Since ERA-20CM showed unsatisfactory values for the performance statistics in all analyses, the hydrologic drought (1950 to 2018) was performed with ERA5-Land. The results showed both an increase in the number of dry months and a decrease in wet months in recent decades.

Lack of phenotypic plasticity in leaf hydraulics for 10 woody species common to urban forests of North China

The survival and performance of urban forests are increasingly challenged by urban drought, consequently compromising the sustainability and functionality of urban vegetation. Plant-water relations largely determine species drought tolerance, yet little is known about the hydraulics of urban forest species. Here, we report the leaf hydraulic and carbon traits that govern plant growth and drought resistance, including vulnerability to embolism, hydraulic conductivity and leaf gas exchange characteristics, as well as morphological traits that are potentially linked with these physiological attributes, with the aim of guiding species selection and management in urban forests. Plant materials were collected from mature shrubs and trees on our university campus in Beijing, representing 10 woody species common to urban forests in north China. We found that the leaf embolism resistance, represented by the water potential inducing 50% loss of hydraulic conductivity (P50), as well as the hydraulic safety margin (HSM) defined by P50 and the water potential threshold at the inception of embolism (P12), varied remarkably across species, but was unrelated to growth form. Likewise, stem and leaf-specific hydraulic conductivity (Kstem and kl) was also highly species-specific. Leaf P50 was positively correlated with hydraulic conductivity. However, neither P50 nor hydraulic conductivity was correlated with leaf gas exchange traits, including maximum photosynthetic rate (Amax) and stomatal conductance (gs). Plant morphological and physiological traits were not related, except for specific leaf area, which showed a negative relationship with HSM. Traits influencing plant-water transport were primarily correlated with the mean annual precipitation of species climatic niche. Overall, current common woody species in urban forest environments differed widely in their drought resistance and did not have the capacity to modify these characteristics in response to a changing climate. Species morphology provides limited information regarding physiological drought resistance. Thus, screening urban forest species based on plant physiology is essential to sustain the ecological services of urban forests.

Can ecological landscape pattern influence dry-wet dynamics? A national scale assessment in China from 1980 to 2018

Land cover has been demonstrated to have substantial impacts on climate and dry-wet environment, but potential influence of landscape pattern dynamics accompanying land cover change on drought remains unclear. In this study, response of dry-wet dynamics to landscape pattern in China was examined. Results suggest that landscape pattern in China's nine agricultural districts had transformed to varying extents and showed spatiotemporal heterogeneity from 1980 to 2018. For forest landscape, the highest annual average Percentage of Landscape (PLAND) was recorded in SC, reaching 62.26%; and the highest Largest Patch Index (LPI) was presented in YGP, followed by SC, with annual values of 53.79% and 46.26% respectively. The QTP has the most prominent forest connectivity in spite of its lower abundance. For grass landscape, the highest abundance and dominance were recorded in QTP, with annual PLAND fluctuation range of 49.66%-63.52% and annual LPI variation range of 34.10%-58.46%, which is associated with its climate and altitude. The most prominent crop landscape abundance and dominance were recorded in HHHP, with annual PLAND fluctuating interval of 56.53%-60.64%, indicating the highest agricultural development level in this district. At landscape level, dry-wet circumstance could be improved with enhancements in the largest patch percentage, patch density and spatial connectivity, while worsen with increases of landscape fragmentation and separated degree. At class level, increases in abundance and dominance of forest and crop landscapes would reduce drought risk, while it was opposite for grass landscape. Improved forest connectedness would optimize dry-wet environment and reduce drought risk. The PLAND of forest and crop landscapes contributed the most prominent effect to alleviate drought intensity. Compared with forestland and grassland, determining suitable crop landscape configuration to reduce drought risk is more complex because the balance between agricultural economic benefits and ecological landscape effects should be taken into account.

Investigating into the Coupling and Coordination Relationship between Urban Resilience and Urbanization: A Case Study of Hunan Province, China

In the context of accelerated urbanization, constructing resilient cities is an effective approach to tackling risks, such as extreme weather, and various urban challenges. The coupling and coordinated development of urbanization and urban resilience is a prominent embodiment of urban sustainable development and high-quality development capacity. In this study, Hunan Province, China, which is frequently affected by various disasters, is selected as a representative for examining the coupling and coordination relationship between urban resilience and urbanization level. The panel data are adopted to construct a dual-system evaluation framework integrating urban resilience and urbanization level based on the entropy weight-coefficient of variation (CV)-CRITIC method. The coupling coordination degree of this dual-system evaluation framework is calculated with the coupling model in physics and GM (1, 1) grey prediction model. Additionally, the spatial–temporal evolution characteristics of the coupling coordination degree are investigated and analyzed by ArcGIS and Geoda software. The following are indicated from the results: (1) The resilience of all cities is related to their geographical location and is characterized by a decrease from east to west; in addition, the resilience level of most cities presents a downward trend with time. (2) The urbanization level of most cities develops stably with time, but there is a growing gap in the urbanization level between regions. (3) There is a strong correlation between urban resilience and urbanization level in all cities; the unbalanced coupling and coordinated development emerge, specifically manifested by the polarization phenomenon. Eventually, a circle-difference spatial distribution pattern that starts from the central urban agglomeration and gradually decreases to the periphery is formed. (4) The prediction results of the coupling coordination degree suggest that there is an increasingly distinct polarization trend for the coupling and coordinated development between cities, and it is necessary to pay attention to those cities with a declined predicted value. (5) There is a significant positive spatial autocorrelation and agglomeration effects in the distribution of the coupling coordination degree of all cities, and the correlation is getting stronger with each passing year; the correlation mode is mainly characterized by homogeneity and supplemented by heterogeneity. Finally, several suggestions are proposed in this paper, in an attempt to lead the coordinated development of regions by novel urbanization and thus promote the sustainable development of cities. The methods and insights adopted in this study contribute to investigating the relationship between urban resilience and urbanization in China and other regions worldwide.

An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends

As satellite observation technology develops and the number of Earth observation (EO) satellites increases, satellite observations have become essential to developments in the understanding of the Earth and its environment. However, the current impacts to the remote sensing community of different EO satellite data and possible future trends of EO satellite data applications have not been systematically examined. In this paper, we review the impacts of and future trends in the use of EO satellite data based on an analysis of data from 15 EO satellites whose data are widely used. Articles that reference EO satellite missions included in the Web of Science core collection for 2020 were analyzed using scientometric analysis and meta-analysis. We found the following: (1) the number of publications and citations referencing EO satellites is increasing exponentially; however, the number of articles referencing AVHRR, SPOT, and TerraSAR is tending to decrease; (2) papers related to EO satellites are concentrated in a small number of journals: 43.79% of the articles that were reviewed were published in only 13 journals; and (3) remote sensing impact factor (RSIF), a new impact index, was constructed to measure the impacts of EO satellites and to predict future trends in applications of their data. Landsat, Sentinel, MODIS, Gaofen, and WorldView were found to be the most significant current EO satellite missions and MODIS data to have the widest range of applications. Over the next five years (2021–2025), it is expected that Sentinel will become the satellite mission with the greatest influence.

Impact of the Sustainable Development Goals on the academic research agenda. A scientometric analysis

Today, global challenges such as poverty, inequality, and sustainability are at the core of the academic debate. This centrality has only increased since the transition from the Millennium Development Goals (MDGs) to the Sustainable Development Goals (SDGs), whose scope is to shift the world on to a path of resilience focused on promoting sustainable development. The main purpose of this paper is to develop a critical yet comprehensive scientometric analysis of the global academic production on the SDGs, from its approval in 2015 to 2020, conducted using Web of Science (WoS) database. Despite it being a relatively short period of time, scholars have published more than five thousand research papers in the matter, mainly in the fields of green and sustainable sciences. The attained results show how prolific authors and schools of knowledge are emerging, as key topics such as climate change, health and the burden diseases, or the global governance of these issues. However, deeper analyses also show how research gaps exist, persist and, in some cases, are widening. Greater understanding of this body of research is needed, to further strengthen evidence-based policies able to support the implementation of the 2030 Agenda and the achievement of the SDGs.

Peanut and cotton intercropping increases productivity and economic returns through regulating plant nutrient accumulation and soil microbial communities

BACKGROUND

Intercropping (IC) has been widely adopted by farmers for enhancing crop productivity and economic returns; however, the underpinning mechanisms from the perspective of below-ground interspecific interactions are only partly understood especially when intercropping practices under saline soil conditions. By using permeable (100 μm) and impermeable (solid) root barriers in a multi-site field experiment, we aimed to study the impact of root-root interactions on nutrient accumulation, soil microbial communities, crop yield, and economic returns in a peanut/cotton IC system under non-saline, secondary-saline, and coastal saline soil conditions of China.

RESULTS

The results indicate that IC decreased the peanut pods yield by 14.00, 10.01, and 16.52% while increased the seed cotton yield by 61.99, 66.00, and 58.51%, respectively in three experimental positions, and consequently enhanced the economic returns by compared with monoculture of peanut (MP) and cotton (MC). The higher accumulations of nutrients such as nitrogen (N), phosphorus (P), and potassium (K) were also observed in IC not only in the soil but also in vegetative tissues and reproductive organs of peanut. Bacterial community structure analysis under normal growth conditions reveals that IC dramatically altered the soil bacterial abundance composition in both peanut and cotton strips of the top soil whereas the bacterial diversity was barely affected compared with MP and MC. At blossom-needling stage, the metabolic functional features of the bacterial communities such as fatty acid biosynthesis, lipoic acid metabolism, peptidoglycan biosynthesis, and biosynthesis of ansamycins were significantly enriched in MP compared with other treatments. Conversely, these metabolic functional features were dramatically depleted in MP while significantly enriched in IC at podding stage. Permeable root barrier treatments (NC-P and NC-C) counteracted the benefits of IC and the side effects were more pronounced in impermeable treatments (SC-P and SC-C).

CONCLUSION

Peanut/cotton intercropping increases crop yield as well as economic returns under non-saline, secondary-saline, and coastal saline soil conditions probably by modulating the soil bacterial abundance composition and accelerating plant nutrients accumulation.

Suicide Mortality Rate as a Sustainable Development Goal (SDG): A Bibliometric Analysis

Suicidal behaviors are a serious but potentially preventable cause of premature death. Increased awareness of the importance of mental health for global health has led to new initiatives, supported by the World Health Organization (WHO) and the United Nations (UN). The suicide mortality rate is one of the indicators covered in the UN's Sustainable Development Goal (SDG) 3. The aim of this study is to identify the scientific production and its temporal evolution related to the suicide mortality rate indicator in the context of mental disorders and as one of the SDG. A bibliometric analysis was performed in Scopus to assess the related research on suicide mortality rate, including on the context of the third SDG, from inception to September 2, 2020. The set of articles were analyzed for bibliometric measures. A total of 3126 documents about mental health and suicide mortality rate on the context of SDG were collected. Articles were the predominant type of literature on this area (78.3%), with significant expression on the last years, more evident around 2015, the year of adoption of SDGs. Despite a large volume of evidence, the debate about suicide mortality rate as an indicator of SDG is still very sparse suggesting a need for better consensus on its evaluation methods. This study presents useful characteristics for the formulation of new studies and provides specific targets for the construction or improvement of public policies on the context of the SDGs for further discussion on this strategy proposed by the UN.

The Contribution of Data-Driven Technologies in Achieving the Sustainable Development Goals

The United Nations’ Sustainable Development Goals (SDGs) set out to improve the quality of life of people in developed, emerging, and developing countries by covering social and economic aspects, with a focus on environmental sustainability. At the same time, data-driven technologies influence our lives in all areas and have caused fundamental economical and societal changes. This study presents a comprehensive literature review on how data-driven approaches have enabled or inhibited the successful achievement of the 17 SDGs to date. Our findings show that data-driven analytics and tools contribute to achieving the 17 SDGs, e.g., by making information more reliable, supporting better-informed decision-making, implementing data-based policies, prioritizing actions, and optimizing the allocation of resources. Based on a qualitative content analysis, results were aggregated into a conceptual framework, including the following categories: (1) uses of data-driven methods (e.g., monitoring, measurement, mapping or modeling, forecasting, risk assessment, and planning purposes), (2) resulting positive effects, (3) arising challenges, and (4) recommendations for action to overcome these challenges. Despite positive effects and versatile applications, problems such as data gaps, data biases, high energy consumption of computational resources, ethical concerns, privacy, ownership, and security issues stand in the way of achieving the 17 SDGs.

Leveraging Multi-Source Data and Digital Technology to Support the Monitoring of Localized Water Changes in the Mekong Region

The limited availability of high-resolution monitoring systems for the drought phenomena and water dynamics affected by weather anomalies hinders policy decisions in a multitude of ways. This paper introduces the availability of the high-resolution Water Monitoring System (WMS) developed from a mix of sophisticated multi-spectral satellite imageries, analytic and data sciences, and cloud computing, for monitoring the changes in water levels and vegetation water stress at the local scale. The WMS was tested in the Lower Mekong Region (LMR) case basin, Thailand’s Chi River Basin, in the period from January 2021 to April 2021, the dry season. The overall quality of the VHI, VCI, TCI, and NDVI drought simulation results showed a statistically positive Pearson correlation with the reservoir and dam water volume data (ranged between 0.399 and 0.575) but demonstrated a strong negative correlation with the groundwater level data (between −0.355 and −0.504). Further investigation and more detailed analysis of the influence of different physical environmental conditions related to change in groundwater level should be considered to increase scientific knowledge and understanding about the changing nature of the local system from local perspectives with the alternative use of drought indices in data-poor areas. Our result suggests that the WMS can provide quantitative spatiotemporal variations of localized and contextualized surface water changes as a preliminary analysis. The WMS results can offer guidance for finding a better smaller unit management that suits the local conditions, such as water resource management, disaster risk reduction measures (i.e., drought and flood), irrigation practice, land use planning, and crop management. The existing WMS is geared toward the early warning of water and agricultural development, progress on the SDGs, utilization of digital innovation, and improved abilities of decision-makers to monitor and foresee extreme weather events earlier and with high spatial accuracy.

Machine-learning algorithms for forecast-informed reservoir operation (FIRO) to reduce flood damages

Water is stored in reservoirs for various purposes, including regular distribution, flood control, hydropower generation, and meeting the environmental demands of downstream habitats and ecosystems. However, these objectives are often in conflict with each other and make the operation of reservoirs a complex task, particularly during flood periods. An accurate forecast of reservoir inflows is required to evaluate water releases from a reservoir seeking to provide safe space for capturing high flows without having to resort to hazardous and damaging releases. This study aims to improve the informed decisions for reservoirs management and water prerelease before a flood occurs by means of a method for forecasting reservoirs inflow. The forecasting method applies 1- and 2-month time-lag patterns with several Machine Learning (ML) algorithms, namely Support Vector Machine (SVM), Artificial Neural Network (ANN), Regression Tree (RT), and Genetic Programming (GP). The proposed method is applied to evaluate the performance of the algorithms in forecasting inflows into the Dez, Karkheh, and Gotvand reservoirs located in Iran during the flood of 2019. Results show that RT, with an average error of 0.43% in forecasting the largest reservoirs inflows in 2019, is superior to the other algorithms, with the Dez and Karkheh reservoir inflows forecasts obtained with the 2-month time-lag pattern, and the Gotvand reservoir inflow forecasts obtained with the 1-month time-lag pattern featuring the best forecasting accuracy. The proposed method exhibits accurate inflow forecasting using SVM and RT. The development of accurate flood-forecasting capability is valuable to reservoir operators and decision-makers who must deal with streamflow forecasts in their quest to reduce flood damages.

Towards the evaluation of regional ecosystem integrity using NDVI, brightness temperature and surface heterogeneity

Maintaining ecological integrity is globally acknowledged as a strategic goal, yet there is no consensus on a practical and widely usable methodology to assess it. This study proposes a comprehensive approach to quantify regional ecosystem integrity based on FAIR data, obtained using satellite remote sensing and image analysis. Three variables are central to this approach: normalized difference vegetation index (NDVI), at-satellite brightness temperature (BT) and vegetation surface heterogeneity (HG), corresponding to ecosystem integrity indicators exergy capture, biotic water flows and abiotic heterogeneity. The indicators are assessed across the vegetation period and a representative Regional Index of Ecological Integrity (RIEI) is proposed to express the integrity of two case study areas and representative land use types. The proposed approach proved powerful in representing the anthropogenic and autopoietic gradient within study regions in high detail. Arable lands and urban areas ranked lowest, while dense forests and wetlands highest, agriculture being the most significant factor reducing regional integrity. Areas with conservation significance ranked either having the highest integrity, when dense vegetation was present, and mediocre or even low in case of e.g., sand dunes, marches and rock formations. Limitations of the method comprise: insufficient representation of biodiversity, sensitivity to cloud cover and demanding in-situ validation. The approach can be scaled from global to local level, adapted to various remote sensing techniques and complemented by a diversity of data (e.g., ecosystem services, geomorphological, climatic) to provide deeper understanding of landscape ecosystem integrity.

Significance of Urban Vegetation on Lawns Regarding the Risk of Fire

Urban green infrastructure significantly influences the functioning of a city and the comfort of its residents. Lawns are an essential element of public greenery. They represent a live component, and if they are lacking, of low quality, or neglected, this will cause major problems in the urban environment. The vegetation structure of urban grassy areas changes under the influence of different management methods used for their maintenance. The main goal of this study was to evaluate the species diversity of urban lawns and to determine the influence of this vegetation on factors based on the representation of the species found. Three sites with urban lawns were chosen in a built-up city area where different types of vegetation management were applied: Typical management, in which grassy areas are mowed twice a year; intensive management, in which lawns are mowed several times a year and the biomass is removed; and extensive management, in which lawns are mowed irregularly, once a year at most, and the biomass is left unevenly on the site. Extensive management and unkempt urban grassy areas represent a high risk of fire due to the presence of plant species that produce great amounts of biomass. Combined with dry and warm weather, the dead biomass can lead to outbreaks of fire. Extensive management of urban grassy areas brings some benefits, such as lower maintenance costs and increased biodiversity and bioretention. On the other hand, intensive management reduces the risk of fire and the biodiversity of the plant community. Attention should be paid to the composition of vegetative species and their functions that could threaten the safety of residents, with the risk of fire being one of them. However, the vegetation biomass of grassy areas affected by management practices is only a precondition for the risk of fire because weather and drought occurrence play important roles as well.

Scientometric Analysis-Based Review for Drought Modelling, Indices, Types, and Forecasting Especially in Asia

An extended drought period with low precipitation can result in low water availability and issues for humans, animals, and plants. Drought forecasting is critical for water resource development and management as it helps to reduce negative consequences. In this study, scientometric analysis and manual comprehensive analysis on drought modelling and forecasting are used. A scientometric analysis is used to determine the current research trend using bibliometric data and to identify relevant publication field sources with the most publications, the most frequently used keywords, the most cited articles and authors, and the countries that have made the greatest contributions to the field of water resources. This paper also tries to provide an overview of water issues, such as drought classification, drought indices, historical droughts, and their impact on Asian countries such as China, Pakistan, India, and Iran. There have been many models established for this purpose and choosing the appropriate model for study is a long procedure for researchers. An appropriate, comprehensive, pedagogical study of model ideas and historical implementations would benefit researchers by helping them to avoid overlooking viable model options, thus reducing their time spent on the topic. As a result, the goal of this paper is to review drought-forecasting approaches and recommend the best models for the Asian region. The models are divided into four categories based on their mechanisms: Regression analysis, stochastic modelling, machine learning, and dynamic modelling. The basic concepts of each approach in terms of the model’s historical use, benefits, and limitations are explained. Finally, prospects for future drought research in Asia are discussed as well as potential modelling techniques.

The Ukrainian Economy Transformation into the Circular Based on Fuzzy-Logic Cluster Analysis

In the era of limited resources and progressive environmental degradation, the circular economy is a practical application of sustainable development. It is an alternative, but also competitive way to achieve economic growth in accordance with the principles of sustainable development. This issue was considered in this paper in the context of the Ukrainian economy. The Ukrainian economy’s transformation into a circular one needs to find ways to choose practical tools for such a transition, considering the destructive impact of economic activities on the environment, population, and economy. The goal was to develop a method of choosing tools for the circular transformations of economic activities for each cluster and to reduce man-made damage to the environment. Cluster analysis, fuzzy C-means method, and grouping of economic activities were used. Two analyzed sectors turned out to be the most interesting: mining and quarrying, and electricity, gas, steam, and air conditioning supply, which were finally assigned to the cluster with a high level of destructive impact, defined as ‘environmentally unfriendly’. The proposed method allows the choice of circular transformation tools for economic activities depending on the destructive impact of these economic activities within each cluster.

What factors affect the water saving behaviors of farmers in the Loess Hilly Region of China?

Water shortage has become one of the most serious challenges faced by humans. Thus, improving water use behaviors and saving water are critical. In this paper, based on the extended Value-Belief-Norm (VBN) theory, we used the structural equation model and the survey data of 558 households in the Loess Hilly Region to analyze the key factors affecting water saving behaviors of farmers. The domestic water consumption of farmers in Loess Hilly Region is mainly for diet and personal hygiene. The water-saving behaviors of farmers are significantly affected by their willingness, knowledge and age. Personal habits, policy incentives, egocentric values and biospheric values indirectly affect the willingness to save water by acting on personal water-saving norms. Gender and annual household income also have a significant impact on water-saving willingness of farmers. The estimation results of multi-group structural equation model and full-sample structural equation model are generally consistent, and there are significant differences in the influence of gender and water source adjustment variables on water-saving behaviors among different hypothetical paths. Among them, female, cellar water and well water groups have the greater impact on water-saving behaviors. These results provide references for policy makers to formulate effective rural water-saving strategies. Policymakers should strengthen the propagandize of water-saving knowledge and skills, popularize knowledge about water resources and ecological environment changes, encourage farmers to develop good water use habits, and actively promote the subsidy system for water-saving appliances. Then they should establish a supervision and management mechanism of water resources to stimulate farmers to save water, which realize the sustainable use of local water resources.

Water Utilities Challenges: A Bibliometric Analysis

The water utilities are under big pressure to guarantee water access to their customers with the right level of service and quality due to challenges such as climate change, aging infrastructure, water scarcity, and growing populations, which put pressure on their operations. The scientific community has worked intensively over the last years to propose solutions and alternatives for the utilities to improve their operation and management in order to overcome these challenges. This paper aims to review scientific contributions to this field. The result shows increasing awareness from the scientific community in this topic which translates into a growing number of publications since the beginning of the current century. This paper analyzes the evolution of the publications, identifies the main countries and institutions working in this field and their scientific relationships over time. It also identifies the main keywords in the literature, which are grouped into three main topics: water quality, water management, and water optimization. The development of smart technologies is accelerating the scientific production towards the topic of water optimization, which is acquiring more importance over the last years. Future trends of research are related to identifying specific challenges per country and the specific solutions proposed by the scientific community to address them and its feasibility to be applied in other places.

Spatial identification and determinants of trade-offs among multiple land use functions in Jiangsu Province, China

Understanding the relationships among multiple land use functions (LUFs) is crucial for land-based spatial planning that can guide targeted land use policy-making in complex socio-ecological systems. However, few studies concerned the interactions among various LUFs integrating the issues of economy, environment, and society at a fine scale. In this study, we quantified 12 LUFs using a geospatial model and statistical analysis at the grid scale in Jiangsu Province. Then, we identified the relationships among three primary LUFs-agricultural production function (APF), urban-rural living function (ULF), and ecological maintenance function (EMF)-and further explored the determinants of LUF trade-offs aimed to provide a reference for policy-makers to make decisions in future land use planning and management. The results revealed that the high trade-off areas for APF and ULF are mainly distributed in central and northern Jiangsu, and the trade-offs for both APF-EMF and ULF-EMF were higher in the area covered with water and forest. The determinants of LUF trade-offs mainly refers to land use/land cover, potential evapotranspiration, and vegetation coverage ratio. Moreover, landscape configuration metrics and distance to the nearest county and nearest road also have remarkable impacts on the trade-offs of APF-EMF and ULF-EMF. Finally, we proposed that the concepts of LUF trade-offs should be incorporated into the processes of delineating boundaries for urban growth, farmland, and natural areas. We also propose that land consolidation projects should be implemented in an orderly manner to alleviate LUF trade-offs.

Three pillars of sustainability in the wake of COVID-19: A systematic review and future research agenda for sustainable development

The COVID-19 pandemic has immensely impacted the economic, social, and environmental pillars of sustainability in human lives. Due to the scholars' increasing interest in responding to the urgent call for action against the pandemic, the literature of sustainability research considering COVID-19 consequences is very fragmented. Therefore, a comprehensive review of the COVID-19 implications for sustainability practices is still lacking. This research aims to analyze the effects of COVID-19 on the triple bottom line (TBL) of sustainability to support the future sustainable development agenda. To achieve that, the following research questions are addressed by conducting a systematic literature review: (i) what is the current status of research on the TBL of sustainability considering COVID-19 implications? (ii) how does COVID-19 affect the TBL of sustainability? and (iii) what are the potential research gaps and future research avenues for sustainable development post COVID-19? The results manifest the major implications of the COVID-19 outbreak for the triple sustainability pillars and the sustainable development agenda from the economic, social, and environmental points of view. The key findings provide inclusive insights for governments, authorities, practitioners, and policy-makers to alleviate the pandemic's negative impacts on sustainable development and to realize the sustainability transition opportunities post COVID-19. Finally, five research directions for sustainable development corresponding to the United Nations' sustainable development goals (SDGs) post COVID-19 are provided, as follows: (1) sustainability action plan considering COVID-19 implications: refining sustainability goals and targets and developing measurement framework; (2) making the most of sustainability transition opportunities in the wake of COVID-19: focus on SDG 12 and SDG 9; (3) innovative solutions for economic resilience towards sustainability post COVID-19: focus on SDG 1, SDG 8, and SDG 17; (4) in-depth analysis of the COVID-19 long-term effects on social sustainability: focus on SDG 4, SDG 5, and SDG 10; and (5) expanding quantitative research to harmonize the COVID-19-related sustainability research.

An Evaluation of Coupling Coordination between Rural Development and Water Environment in Northwestern China

Balancing the relationship between rural development and the protection of water resources is a challenging undertaking. This study develops a coupling coordination degree (CCD) model to examine the non-linear interaction between rural development and water environment in the 11 prefectures of Gansu, northwestern China. There are three key findings. First, economic development is the key driver of rural development, whereas social development has relatively little impact. For the water environment subsystem, improved water efficiency has been the key contributor, whereas environmental carrying capacity is secondary. Second, the CCD increased steadily in the studied period, which suggests that the relationship between rural development and water environment has gradually changed from antagonistic to mutually beneficial. However, this change is not occurring rapidly and in fact shows signs of slowing. Third, the complex spatial differences of the CCD are related to the level of economic and social development, the process of urban–rural integration, and regional natural conditions. The findings of this study have great significance for further quantitative analysis of the interaction and mutual feedback mechanism between the rural economy and the water environment in China and support evidence-based policymaking.

Research on the Efficiency and Improvement of Rural Development in China: Based on Two-Stage Network SBM Model

China has always been a major agricultural country, and the issues of agriculture, rural areas and farmers have always been fundamental issues of China’s reform and development. First of all, most previous studies did not combine agricultural development with rural economic development to consider the rural development status. Through the network-slack-based measure (SBM) model, agricultural development and rural economic development are taken as the first stage and the second stage, respectively, to determine the overall efficiency of rural development. Secondly, most previous studies directly selected a number of agricultural materials as inputs to evaluate agricultural production efficiency, and did not consider the impact of a variety of agricultural materials comprehensively. We use the entropy method to calculate a comprehensive index including a variety of agricultural materials. Third, most previous studies did not take into account the harmful effects of agricultural production on the environment. We take carbon emissions and agricultural non-point source pollution (ANPSP) as undesirable outputs into the model, and consider the impact of agricultural production on the ecological environment comprehensively. On the basis of the above innovation, we adopt the two-stage SBM-undesirable model to comprehensively and systematically study the efficiency of rural development in China. Furthermore, the gap of rural development efficiency is determined by sigma convergence and a convergence test. All the data are from the National Bureau of Statistics of China. The results show that the development level of China’s rural agricultural eco-efficiency is significantly higher than that of rural economic development, and the low efficiency of the whole rural development is mainly affected by the low efficiency of rural economic development. The distribution of efficiency value shows that the eastern region is the best, and the development level of the remaining three regions is very low. The regional development gap is large, and this gap still exists for a long period of time. Nevertheless, the efficiency of rural development has improved year by year. Based on empirical analysis, we put forward some feasible suggestions to provide reference for policymakers in formulating rural development policies, narrowing the regional gap and rural sustainable development.

Does the Household Save Water? Evidence from Behavioral Analysis

Management of water supply in urban areas is a challenge that must be faced by water supply companies to ensure the continuity of domestic water supply to the residents in the area. Hence, this study aims to identify local people’s behavior and daily activities that led to domestic water wastage. Furthermore, the relationship between the demographic factors of the population trends in reducing water use through water savings in their daily activities or installing a home-saving water system is also undertaken. The data were analyzed and interpreted using IBM SPSS software such as descriptive analysis, covering frequencies, mean and standard deviation, correlation with bivariate correlation, cross-tabulation, and multivariate analysis (MANOVA). Availability and demand in water management will only be managed if water resources and water supply engineers address all the balance sides. It will ensure a more comprehensive and interconnected water sector, ensuring the security and sustainability of water.

Effects of small ridge and furrow mulching degradable film on dry direct seeded rice

Global climate change and socio-economic development have led to a shortage of water and labour resources, which has had a significant impact on rice cultivation. In this study, the application of micro-ridge-furrow planting technology and degradable film mulching in dry direct-seeded rice was investigated to address the factors restricting the development of the rice industry and reduce the impact of rice production on the environment. The effects of a micro-ridge-furrow planting pattern and degradable film mulching on soil temperature, seedling growth, and yield of dry direct-seeded rice in a semiarid region of China were studied through three field experiments: micro-ridge-furrow mulching with traditional plastic film (T1); micro-ridge-furrow mulching with degradable film (T2); and traditional flat-cropping mulching with traditional plastic film (CK). The experimental results demonstrated that the micro-ridge-furrow mulching film planting pattern promoted the germination of rice seeds and improved the soil temperature, plant height, leaf area, dry mass, and grain yield. T2 had the highest average soil temperature (14.68–17.83 ℃ during the day; 14.4–15.74 ℃ at night), leaf area (41.85 cm² plant⁻¹), root dry mass (45.32 mg plant⁻¹), shoot dry mass (58.46 mg plant⁻¹), root–shoot ratio (0.821), and yield (8.112 t ha⁻¹). In summary, the micro-ridge-furrow mulching with degradable film (T2) is recommended as an efficient planting and mulching pattern for sustainably solving environmental problems and improving grain yield in semiarid regions of China.

Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review

Climate variability and recurrent droughts have caused remarkable strain on water resources in most regions across the globe, with the arid and semi-arid areas being the hardest hit. The impacts have been notable on surface water resources, which are already under threat from massive abstractions due to increased demand, as well as poor conservation and unsustainable land management practices. Drought and climate variability, as well as their associated impacts on water resources, have gained increased attention in recent decades as nations seek to enhance mitigation and adaptation mechanisms. Although the use of satellite technologies has, of late, gained prominence in generating timely and spatially explicit information on drought and climate variability impacts across different regions, they are somewhat hampered by difficulties in detecting drought evolution due to its complex nature, varying scales, the magnitude of its occurrence, and inherent data gaps. Currently, a number of studies have been conducted to monitor and assess the impacts of climate variability and droughts on water resources in sub-Saharan Africa using different remotely sensed and in-situ datasets. This study therefore provides a detailed overview of the progress made in tracking droughts using remote sensing, including its relevance in monitoring climate variability and hydrological drought impacts on surface water resources in sub-Saharan Africa. The paper further discusses traditional and remote sensing methods of monitoring climate variability, hydrological drought, and water resources, tracking their application and key challenges, with a particular emphasis on sub-Saharan Africa. Additionally, characteristics and limitations of various remote sensors, as well as drought and surface water indices, namely, the Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Normalized Difference Vegetation (NDVI), Vegetation Condition Index (VCI), and Water Requirement Satisfaction Index (WRSI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Land Surface Water Index (LSWI+5), Modified Normalized Difference Water Index (MNDWI+5), Automated Water Extraction Index (shadow) (AWEIsh), and Automated Water Extraction Index (non-shadow) (AWEInsh), and their relevance in climate variability and drought monitoring are discussed. Additionally, key scientific research strides and knowledge gaps for further investigations are highlighted. While progress has been made in advancing the application of remote sensing in water resources, this review indicates the need for further studies on assessing drought and climate variability impacts on water resources, especially in the context of climate change and increased water demand. The results from this study suggests that Landsat-8 and Sentinel-2 satellite data are likely to be best suited to monitor climate variability, hydrological drought, and surface water bodies, due to their availability at relatively low cost, impressive spectral, spatial, and temporal characteristics. The most effective drought and water indices are SPI, PDSI, NDVI, VCI, NDWI, MNDWI, MNDWI+5, AWEIsh, and AWEInsh. Overall, the findings of this study emphasize the increasing role and potential of remote sensing in generating spatially explicit information on drought and climate variability impacts on surface water resources. However, there is a need for future studies to consider spatial data integration techniques, radar data, precipitation, cloud computing, and machine learning or artificial intelligence (AI) techniques to improve on understanding climate and drought impacts on water resources across various scales.

Health consequences of drought in the WHO Eastern Mediterranean Region: hotspot areas and needed actions

BACKGROUND

Over the past four decades, drought episodes in the Eastern Mediterranean Region (EMR) of the of the World Health Organization (WHO) have gradually become more widespread, prolonged and frequent. We aimed to map hotspot countries and identified key strategic actions for health consequences.

METHODS

We reviewed scientific literature and WHO EMR documentation on trends and patterns of the drought health consequences from 1990 through 2019. Extensive communication was also carried out with EMR WHO country offices to retrieve information on ongoing initiatives to face health consequences due to drought. An index score was developed to categorize countries according vulnerability factors towards drought.

RESULTS

A series of complex health consequences are due to drought in EMR, including malnutrition, vector-borne diseases, and water-borne diseases. The index score indicated how Afghanistan, Yemen and Somalia are "hotspots" due to poor population health status and access to basic sanitation as well as other elements such as food insecurity, displacement and conflicts/political instability. WHO country offices effort is towards enhancing access to water and sanitation and essential healthcare services including immunization and psychological support, strengthening disease surveillance and response, and risk communication.

CONCLUSIONS

Drought-related health effects in the WHO EMR represent a public health emergency. Strengthening mitigation activities and additional tailored efforts are urgently needed to overcome context-specific gaps and weaknesses, with specific focus on financing, accountability and enhanced data availability.

The Energy Trade-Offs of Transitioning to a Locally Sourced Water Supply Portfolio in the City of Los Angeles

Predicting the energy needs of future water systems is important for coordinating long-term energy and water management plans, as both systems are interrelated. We use the case study of the Los Angeles City’s Department of Water and Power (LADWP), located in a densely populated, environmentally progressive, and water-poor region, to highlight the trade-offs and tensions that can occur in balancing priorities related to reliable water supply, energy demand for water and greenhouse gas emissions. The city is on its path to achieving higher fractions of local water supplies through the expansion of conservation, water recycling and stormwater capture to replace supply from imported water. We analyze scenarios to simulate a set of future local water supply adoption pathways under average and dry weather conditions, across business as usual and decarbonized grid scenarios. Our results demonstrate that an aggressive local water supply expansion could impact the geospatial distribution of electricity demand for water services, which could place a greater burden on LADWP’s electricity system over the next two decades, although the total energy consumed for the utility’s water supply might not be significantly changed. A decomposition analysis of the major factors driving electricity demand suggests that in most scenarios, a structural change in LADWP’s portfolio of water supply sources affects the electricity demanded for water more than increases in population or water conservation.

Addressing Urban–Rural Water Conflicts in Nagpur through Benefit Sharing

Urban and rural areas often meet their water demands from a shared stock of finite water resources. Against the changing climate, the rising water demands in fast-growing urban areas are leading to increasing water-use conflicts with the co-dependent rural areas. Although poor water governance is frequently cited as the key reason for such urban–rural conflicts, it is also recognized as a potential pathway to resolve them. In the case of Nagpur Region in Central India, water stress has today become a subject of serious concern. The water demands in Nagpur City are primarily met through the multipurpose Pench Dam on priority, but the recently declining water availability has raised undue concerns for irrigation in the Pench command areas. To substantiate the limited understanding of ongoing water conflicts in the wider Nagpur Metropolitan Area, this study analyzes a specific set of secondary data related to the history of the Pench Project and its water utilization trends. By uncovering the periodic decline in irrigated area and the increasing groundwater use for irrigation, the cross-sectoral and transboundary implications of increasing water transfer to Nagpur City are revealed. To address these concerns, this study then suggests feasible governance strategies based on benefit sharing and multi-stakeholder engagement.

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.

Climate and landscape mediate patterns of low lentil productivity in Nepal

Lentil (Lens culinaris Medik.) is a cool-season pulse grown in winter cropping cycle in South Asia and provides a major source of nutrition for many low-income households. Lentil productivity is perceived to be sensitive to high rainfall, but few studies document spatial and temporal patterns of yield variation across climate, soil, and agronomic gradients. Using farm survey data from Nepal, this study characterizes patterns of lentil productivity and efficiency for two cropping seasons. Additional insights were derived from on-farm trials conducted over a 5-year period that assess agronomic, drainage, and cultivar interventions. To contextualize the inferences derived from farm surveys and trials, the Stempedia model was used to simulate the severity of Stemphylium blight (Stemphylium botryosum) risk-the principal fungal disease in lentil-with 30 years of historical climate data. Although development efforts in Nepal have prioritized pulse intensification, results confirm that lentil remains a risky enterprise highlighting the prevalence of crop failures (16%), modest yields (353 kg ha-1), and low levels of profitability (US$ 33 ha-1) in wet winters. Nevertheless, site factors such as drainage class influence responses with upland sites performing well in wet winters and lowland sites performing well in dry winters. In wet winters, a phenomena perceived to be increasing, 76% of surveyed farmers reported significant disease pressure and simulations with Stempedia predict that conditions favoring Stemphylium occur in >60% of all years. Nevertheless, simulation results also suggest that these risks can be addressed through earlier planting. Based on the combined results, gains in yield, yield stability, and technical efficiency can be enhanced in western Nepal by: 1) ensuring timely lentil planting to mitigate climate-mediated disease risk, 2) evaluating new lentil lines that may provide enhanced resistance to diseases and waterlogging, and 3) encouraging the emergence of mechanization solutions to overcome labor bottlenecks.

Evaluation of Meteorological Drought and Flood Scenarios over Kenya, East Africa

This work examines drought and flood events over Kenya from 1981 to 2016 using the Standardized Precipitation–Evapotranspiration Index (SPEI). The spatiotemporal analysis of dry and wet events was conducted for 3 and 12 months. Extreme drought incidences were observed in the years 1987, 2000, 2006, and 2009 for SPEI-3, whilst the SPEI-12 demonstrated the manifestation of drought during the years 2000 and 2006. The SPEI showed that the wettest periods, 1997 and 1998, coincided with the El Nino event for both time steps. SPEI-3 showed a reduction in moderate drought events, while severe and extreme cases were on the increase tendencies towards the end of the twentieth century. Conversely, SPEI-12 depicted an overall increase in severe drought occurrence over the study location with ab observed intensity of −1.54 and a cumulative frequency of 64 months during the study period. Wet events showed an upward trend in the western and central highlands, while the rest of the regions showed an increase in dry events during the study period. Moreover, moderate dry/wet events predominated, whilst extreme events occurred least frequently across all grid cells. It is apparent that the study area experienced mild extreme dry events in both categories, although moderately severe dry events dominated most parts of the study area. A high intensity and frequency of drought was noted in SPEI-3, while the least occurrences of extreme events were recorded in SPEI-12. Though drought event prevailed across the study area, there was evidence of extreme flood conditions over the recent decades. These findings form a good basis for next step of research that will look at the projection of droughts over the study area based on regional climate models.