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Although the UN concluded, already in 1997, that water would be the most contentious issue of the 21st century, water governance is still confused, nearly everywhere. Even the severe impacts of escalating water bankruptcy and global warming have so far failed to incur a marked improvement in governance systems. The global community has adopted sustainable development as a common vision and guide for the future. Yet, the adoption of the underlying principles of sustainable development has been slow in the water sector and elsewhere. Despite the realization that water governance is a political issue, the near-universal neoliberal agenda tends to only employ technologic and economic solutions to address water problems. This paper presents a historical overview, from the end of the Second World War (WWII) and onwards, of events that could, or should, have had an impact on water management frameworks. It evidences some important consequences of the institutional rigidity exposed during that period. The paper also turns to the fields of science, policy, and management, to pinpoint failures in the translation of political rhetoric as well as new scientific findings into change at the operational level. It explores how an updated knowledge base could serve a quest for sustainable water governance strategies. It is argued that a persistent failure to learn is an important reason behind the dire state that we are now in. As a result, water management is still based on century-old, technocratic, and instrumental methodologies that fail to take advantage of important scientific advancements since WWII and remain unable to properly deal with real-world complexities and uncertainties. The paper concludes that when it is linked to a transformation of the institutional superstructure, adaptive water management (AWM), a framework rooted in systems thinking, emerges as a prominent way to embark on a needed, radical transformation of the water governance systems.

The application of agricultural ponds and small engineered impoundments (often < 0.1 km2 area) is growing globally to support livestock, irrigation, and local municipal and industrial demands during dry spells. However, evaporation diminishes the storage efficiency of these popular but often un-inventoried resources. This study provides a reliable framework for estimating global abundance of small reservoirs and associated evaporative hotspots under different climate change scenarios serving as a basis for future water management and planning. To show the applicability of the proposed method and the utility of the insights it provides, we use satellite data to identify spatio-temporal distribution of small reservoirs (~0.001 to 0.1 km2 area) in southern Europe (Italy, Spain, and Portugal) where irrigation heavily depends on water storage in agricultural ponds. While current estimates of evaporative water losses from small reservoirs often rely on pan measurements or Penman-type approaches with locally calibrated heat and mass transfer coefficients, we employ a physically-based model [Aminzadeh et al., 2018] that accounts for inherent reservoir characteristics (e.g., depth and light attenuation), and radiative energy storage within the water body to quantify energy balance and evaporation dynamics from small water reservoirs. Our preliminary results indicate that cumulative area of small reservoirs in the study area has increased from 518 km2 in 2000 to 614 km2 in 2020 (18.5% increase) with cumulative evaporative losses that may exceed 400 Mm3 during warm months (April to September). Although the estimated evaporative water loss looks negligible relative to the annual agricultural water use (< 2%), its significance could be gauged by societal impacts in these regions with chronic water stress problems or the cost of alternate water sources (e.g., desalinated water).ReferenceAminzadeh, M., Lehmann, P., Or, D. (2018). Evaporation suppression and energy balance of water reservoirs covered with self-assembling floating elements. Hydrol. Earth Syst. Sci., 22, 4015–4032.

Climate, climate variability, and climate change could influence groundwater. Shifts in precipitation patterns, recharge, or snowmelt are among the several climate-related variables with important impacts on groundwater. However, the climate-groundwater relationship is not one-way. Groundwater can also impact the climate itself via its influence on different processes and variables such as evaporation, soil moisture, and vegetation. Understanding the interactions and the feedback relationship between groundwater and climate is crucial for sustainable water resource management and resilient adaptation to climate change. Current understanding of how climate influences groundwater and the resulting feedback from groundwater and its impacts on climate is limited. This is of particular importance in the face of projected climatic changes. Here, we aim to develop a simple analytical framework to extend the projection capabilities required to characterize the climate-groundwater interactions depending on the soil characteristics serving as an intermediate domain between the groundwater and climate systems. Our proposed analytical framework can be used to identify potential regions with significant two-way (bidirectional) interactions between climate and groundwater using soil characteristics and soil water retention curves following the theoretical lines discussed in Shokri and Salvucci (2011) and Or and Lehmann (2019). Using this framework, we identify regions of expected hydraulic connections between groundwater and soil surface, depending on the competition between capillary forces and the limiting gravity and viscous forces, and the groundwater depth (GWD) in the city of Hamburg. We argue that in regions with bidirectional interactions, groundwater is potentially more vulnerable to climate change and variability. Moreover, our initial results suggest that regions with finer textured soils are more sensitive to changes in evaporation and air temperature in terms of hydraulic connections between groundwater and the soil surface, which can influence the groundwater-climate interactions. Our analysis provides the basis for further investigation of the feedback impacts of groundwater on several variables, such as soil moisture, ground cooling capacity, and vegetation patterns under different climate change scenarios. ReferencesOr, D., & Lehmann, P. (2019). Surface evaporative capacitance: How soil typeand rainfall characteristics affect global‐scale surface evaporation. Water Resources Research, 55, 519–539.https://doi.org/10.1029/2018WR024050.Shokri, N., Salvucci, G. (2011). Evaporation from porous media in the presence of a water table. Vadose Zone J., 10, 1309-1318.

Reliable projection of evaporative fluxes from lakes is at the core of a wide range of hydrological, climatological, and environmental modeling processes. Evaporation results in losses of blue water from lakes in regions with limited freshwater resources and affects aquatic and terrestrial biodiversity. While current estimates of evaporative losses from lakes remain largely empirical depending on locally calibrated heat and mass transfer coefficients or remotely sensed surface temperature data, we propose a physically-based framework that builds on inherent lake characteristics (e.g., bathymetry, light attenuation characteristics) and atmospheric forcing variables to quantify energy dynamics of the water body and surface evaporative fluxes from the largest lakes across different climatic zones on a global scale. To evaluate the performance of the model, the modelling results determining the seasonal variation of vertical temperature profiles and latent heat loss were compared with in situ measurements of water temperature and surface heat fluxes measured in Lake Mead, in the Southwestern USA. We found good agreements between the physically-based estimations and the measured data. We then quantified evaporative losses from 30 lakes in 30 different climate zone sub-types with an average depth ranging from 1.1 m to 577 m and a surface area of 45 km² to 82,000 km². Our preliminary findings for 2020 indicate that variation of first-order atmospheric parameters (i.e., wind, radiation, air temperature, and humidity) across climatic zones and the change in lake bathymetry altering local vertical temperature profiles within the water body significantly affect evaporative losses. The energy-constrained model enables quantifying the extent of evaporative water losses from lakes and provides a theoretical basis for delineating potential impacts on water management and ecological and climatological processes under different climate change scenarios.

The Zayandeh-Rud River Basin in the central plateau of Iran continues to grapple with water shortages due to a water-intensive development path made possible by a primarily supply-oriented water management approach to battle the water limits to growth. Despite inter-basin water transfers and increasing groundwater supply, recurring water shortages and associated tensions among stakeholders underscore key weaknesses in the current water management paradigm. There was an alarming trend of groundwater depletion in the basin’s four main aquifers in the 1993–2016 period as indicated by the results of the Mann-Kendall3 (MK3) test and Innovative Trend Analysis (ITA) of groundwater volume. The basin’s water resources declined by more than 6 BCM in 2016 compared to 2005 based on the equivalent water height (EWH) derived from monthly data (2002–2016) from the GRACE. The extensive groundwater depletion is an unequivocal evidence of reduced water availability in the face of growing basin-wide demand, necessitating water saving in all water use sectors. Implementing an integrated water resources management plan that accounts for evolving water supply priorities, growing demand and scarcity, and institutional changes is an urgent step to alleviate the growing tensions and preempt future water insecurity problems that are bound to occur if demand management approaches are delayed.

Composting is one of the environmentally friendly ways of reducing organic waste. It is economically viable since it cuts costs associated with the hauling of wastes and enables farmers to reduce the use of fertilizers. Composting operations are relatively non-existent in the solid municipal waste sector, as the market has molded itself and grown into a standard “bury-or-burn” model. As humans are trying to address global warming, composting proves to be a promising climate change mitigation option, benefiting societies in terms of the environment, the economy, and overall health. This study projects that—with the current trends—by the end of 2030, the U.S. can increase the compost to waste ratio by 18% from 10%, reducing carbon emissions by 30 million tons a year while saving around 16 billion USD in municipal waste management costs. Analyzing the existing records in the OECD countries suggests that economic motives are not powerful enough to incentivize the industry/household toward composting. Stricter environmental policies can boost the composting volume by 214-574 thousand tons per year. Imposing waste taxes and penalties can give birth to a vast industry that has not yet flourished while the economic subsidies financed by the collected taxes and penalties can incentivize the private sector to further invest in composting.

Significance Iran is facing a state of water bankruptcy that threatens its socioeconomic development and natural environments. Using an exceptionally rich measured groundwater dataset, we illustrate the extent and severity of Iran’s groundwater depletion and salinization problems during the 2002 to 2015 period, when the number of groundwater extraction points nearly doubled. Iran’s nonrenewable groundwater withdrawal was about 66 million m3 in 1965, which cumulatively grew to approximately 133 × 103 million m3 in 2019. This increase is about 3.4 times the capacity of the famous Three Gorges Dam in China. Groundwater decline due to extensive overexploitation of nonrenewable groundwater and rising salinity levels are documented in almost all subbasins, pointing to dire, worsening water security risks across the country., Global groundwater assessments rank Iran among countries with the highest groundwater depletion rate using coarse spatial scales that hinder detection of regional imbalances between renewable groundwater supply and human withdrawals. Herein, we use in situ data from 12,230 piezometers, 14,856 observation wells, and groundwater extraction points to provide ground-based evidence about Iran’s widespread groundwater depletion and salinity problems. While the number of groundwater extraction points increased by 84.9% from 546,000 in 2002 to over a million in 2015, the annual groundwater withdrawal decreased by 18% (from 74.6 to 61.3 km3/y) primarily due to physical limits to fresh groundwater resources (i.e., depletion and/or salinization). On average, withdrawing 5.4 km3/y of nonrenewable water caused groundwater tables to decline 10 to 100 cm/y in different regions, averaging 49 cm/y across the country. This caused elevated annual average electrical conductivity (EC) of groundwater in vast arid/semiarid areas of central and eastern Iran (16 out of 30 subbasins), indicating “very high salinity hazard” for irrigation water. The annual average EC values were generally lower in the wetter northern and western regions, where groundwater EC improvements were detected in rare cases. Our results based on high-resolution groundwater measurements reveal alarming water security threats associated with declining fresh groundwater quantity and quality due to many years of unsustainable use. Our analysis offers insights into the environmental implications and limitations of water-intensive development plans that other water-scarce countries might adopt.

The cryptocurrency sector is increasingly integrated into the global financial system. The world’s transition to a digital economy, facilitated by major technological breakthroughs, has several ben...

Problems have a high rank in decision making when they are both urgent and important. Accordingly, water has not earned the attention it deserves in public policy agenda because under normal circumstances it is not viewed as an urgent matter in the eyes of the public and politicians. By creating a sense of urgency, extreme events such as droughts, floods, conflicts, and migrations can create opportunities for implementing some essential policy reforms that would be politically costly otherwise. So, despite their high short-term costs, extreme natural and societal events have the potential to increase the resilience of water systems in the long run. It is argued here that the societal and political sense of urgency about water must be promoted through public outreach and information dissemination. Otherwise, for useful reforms and long-term improvements, we will rely on costly and risky extreme events that sometimes have the potential to fully collapse the human-natural system-of-systems.

Decarbonizing electricity risks unintended consequences for other environmental resources. The European Union’s (EU) Member States (MSs) embarked on a decarbonization and renewables deployment program aware of this risk. However, uncertainty remains around which technologies are best suited to the nexus of resources affected. In this study, we illustrate the benefits of using the Relative Aggregate Footprint (RAF) concept to evaluate energy technology alternatives. The RAF is an indicator based on a System of Systems approach that assesses technologies along multiple performance criteria, takes account of performance uncertainty, adjusts criteria importance according to local resource availabilities, and makes the evaluation robust to differing notions of optimality to determine the desirability of technologies. We evaluated 11 electricity generation technologies by cost, carbon, water and land footprint. Assuming equal weightings of the four criteria, we found nuclear, geothermal, and onshore wind to generally have the lowest RAF. We then calculated the MS-specific RAF’s by weighing each criterion based on the local availability of the respective resource: 1) gross domestic product per capita, 2) carbon emissions per capita, 3) freshwater withdrawals as a share of renewable freshwater, and 4) land availability per capita. By analyzing variances between MSs’ RAFs we highlighted how differences in resource availability generate trade-offs for EU electricity decarbonization policies.

Lake Urmia—a shallow endemic hypersaline lake in northwest Iran—has undergone a dramatic decline in its water level (WL), by about 8 m, since 1995. The primary cause of the WL decline in Lake Urmia has been debated in the scientific literature, regarding whether it has been predominantly driven by atmospheric climate change or by human activities in the watershed landscape. Using available climate, hydrological, and vegetation data for the period 1981–2015, this study analyzes and aims to explain the lake desiccation based on other observed hydro-climatic and vegetation changes in the Lake Urmia watershed and classical exploratory statistical methods. The analysis accounts for the relationships between atmospheric climate change (precipitation P, temperature T), and hydrological (soil moisture SM, and WL) and vegetation cover (VC; including agricultural crops and other vegetation) changes in the landscape. Results show that P, T, and SM changes cannot explain the sharp decline in lake WL since 2000. Instead, the agricultural increase of VC in the watershed correlates well with the lake WL change, indicating this human-driven VC and associated irrigation expansion as the dominant human driver of the Lake Urmia desiccation. Specifically, the greater transpiration from the expanded and increasingly irrigated agricultural crops implies increased total evapotranspiration and associated consumptive use of water (inherently related to the irrigation and water diversion and storage developments in the watershed). Thereby the runoff from the watershed into the lake has decreased, and the remaining smaller inflow to the lake has been insufficient for keeping up the previous lake WL, causing the observed WL drop to current conditions.

Hydropolitical conflicts between the Eastern Nile countries over the Grand Ethiopian Renaissance Dam (GERD) are systematically analyzed at three points in time: just before the announcement of construction by Ethiopia on April 11, 2011, before the negotiations in early January 2014, and late August 2014. Hypergame theory, as developed within the framework of the Graph Model for Conflict Resolution for handling misperceptions, is used to gain strategic insights into these conflicts and to ascertain the possible resolutions of the disputes. In all of three conflicts, the key decision makers are Egypt and Sudan, the downstream countries, and Ethiopia, the upstream nation. The findings from the analyses demonstrate the significant utilization of strategic surprise, a decisive act in which a decision maker intentionally exercises a course of action in the dispute that is hidden to its opponents in order to attempt to reach a more desirable outcome for itself. In particular, both Egypt and Sudan were caught by surprise when Ethiopia publicly announced on April 11, 2011 that it was going to build GERD, since no prior notification was given. Because Ethiopia was aware of Egypt and Sudan’s misperception this dispute is modeled as a second level hypergame. The conflict investigations also show that the geopolitical and economic changes in Egypt, Sudan, and Ethiopia allowed Ethiopia to construct the dam without any harsh confrontation with Egypt and Sudan.

We may translate anthropogenic climate change as a reaction of our planet to our unsustainable economic activities. This research explores whether environmental policies have been impacted by extreme climatic events like droughts, floods, storms, tornados, and wildfires. We use yearly panel data from 1990 to 2017 for the OECD (Organization for Economic Cooperation and Development) countries to examine such a relationship. To have an impartial analysis, we control major variables influencing environmental policies such as energy consumption, gross domestic product (GDP), population, technology, head of the state’s political affiliation, carbon emission, and waste generation. The analysis results suggest that policymakers make more stringent environmental decisions as the death rate increases and environmental threats become more imminent putting human life is at risk; this correlation is stronger in the case of European Countries.

Oman is a country characterised by high solar availability, yet very little electricity is produced using solar energy. As the residential sector is the largest consumer of electricity in Oman, we develop a novel approach, using houses in Muscat as a case study, to assess the potential of implementing roof-top solar PV/battery technologies, that operate without recourse to the electricity grid. Such systems target the complete decarbonisation of electricity demand per household and are defined in this study as grid-independent systems. The approach adopted starts with a technical assessment of grid-independent systems that evaluates the characteristics of the solar panel and the battery facility required to provide grid-independence. This is then compared to a similar grid-connected system and any techno-economic targets necessary to enhance the feasibility of residential roof-top PV systems in Muscat are identified. Such an analysis was achieved through developing a detailed techno-economic mathematical model describing four sub-systems; the solar panel DC source, the grid-independent sub-system, the grid-connected sub-system and the economic sub-system. The model was implemented in gPROMS and uses real hourly weather and climate conditions matched with real demand data, over a simulated period of 20 years. The results indicate that, in the context of the system studied, grid-independent PV systems are not feasible. However, combined with a sufficiently high electricity price, grid-independent systems can become economically feasible only with significant reductions in battery costs (>90% reductions).

The Zayandeh-Rud River Basin in the central plateau of Iran continues to grapple with water shortages due to a water-intensive development path made possible by a primarily supply-oriented water management approach to battle the water limits to growth. Despite inter-basin water transfers and increasing groundwater supply, recurring water shortages and associated tensions among stakeholders underscore key weaknesses in the current water management paradigm. There was an alarming trend of groundwater depletion in the basin's four main aquifers in the 1993-2016 period as indicated by the results of the Mann-Kendall3 (MK3) test and Innovative Trend Analysis (ITA) of groundwater volume. The basin's water resources declined by more than 6 BCM in 2016 compared to 2005 based on the equivalent water height (EWH) derived from monthly data (2002-2016) from the GRACE. The extensive groundwater depletion is an unequivocal evidence of reduced water availability in the face of growing basin-wide demand, necessitating water saving in all water use sectors. Implementing an integrated water resources management plan that accounts for evolving water supply priorities, growing demand and scarcity, and institutional changes is an urgent step to alleviate the growing tensions and preempt future water insecurity problems that are bound to occur if demand management approaches are delayed.

Iran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. In this paper, we developed a compartmental transmission model to estimate the time-dependent effective reproduction number since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method accounts for the underreporting due to low case ascertainment. Our estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60 – 1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions. The series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public.

Understanding the complexity and feedbacks among food, energy, and water (FEW) systems is key to making informed decisions about sustainable development. This paper presents qualitative representation and quantitative system dynamics simulation of the water resources system in the Qazvin Plain, Iran, taking into account the energy intensity of water supply and interconnected water use sectors (e.g., urban, industrial, and agricultural). Qazvin Plain faces water resources challenges that are common to arid/semi-arid areas, including frequent droughts, declining surface water and groundwater, and increased urban and agricultural water demand. A system dynamics model is developed using historical data (2006–2016) to investigate the effects of anticipated dynamics of integrated water and energy sectors in the next two decades. The results of policy scenarios (2020–2039) demonstrate that the continuation of the existing management policies will cause severe damage to the water and energy sectors, pushing the system towards water resources limits to growth. An annual groundwater table decline of nearly 1 m is anticipated, indicating significant overshoot of the plain's natural recharge capacity, which may lead to the depletion of recoverable groundwater in the plain within the next three decades. The groundwater table decline will cause energy consumption of water supply to increase by about 32% (i.e., 380 GWh) to maintain irrigated agriculture. It is critical to implement a combination of water demand and supply management policies (e.g., net agricultural water savings and recycling treated wastewater) to delay the problem of water limits to growth in the region.

SUMMARYBackgroundIran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East with 74,877 confirmed cases and 4,683 deaths as of 15 April 2020. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. We use a mathematical epidemic model utilizing official confirmed data and estimates of underreporting to understand how transmission in Iran has been changing between February and April 2020.MethodsWe developed a compartmental transmission model to estimate the effective reproduction number and its fluctuations since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method also accounts for the underreporting due to low case ascertainment by estimating the percentage of symptomatic cases using delay-adjusted case fatality ratio based on the distribution of the delay from hospitalization-to-death.FindingsOur estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60 – 1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions including school closures, a ban on public gatherings including sports and religious events, and full or partial closure of non-essential businesses. Based on these estimates and given that a near complete containment is no longer feasible, it is likely that the outbreak may continue until the end of the 2020 if the current level of physical distancing and interventions continue and no effective vaccination or therapeutic are developed and made widely available.InterpretationThe series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19 within the studied time period. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public especially in the earlier stages of the outbreak.FundingNil.

East Africa is embarking on an ambitious journey to improve access to energy and support its rapid economic and population growth. Hydropower dominates the region’s electricity sector and the current plans continue to favor this technology for future development. This chapter analyzes the desirability of energy alternatives across East Africa using a System of Systems approach that assesses the performance of technologies across four vital systems namely economy, climate, land, and water. The Relative Aggregate Footprint (RAF) of different energy options in East Africa is measured with respect to the resource availability conditions of the countries in the region. The study results show geothermal and solar to be among the most desirable energy technologies for East Africa, while biomass and oil are the least desirable alternatives. Hydropower is outperformed by fossil fuels such as coal and oil. Its desirability ranges from average to highly undesirable once its impacts on other resources beyond carbon emissions are considered. Comparison of the desirability of alternatives against the planned investments of the region shows serious disparities. This calls for fundamental changes in the development policies in the energy sector of the region if a more sustainable electricity mix is to be achieved.

To satisfy the energy demand and secure energy independence, Indonesia plans to maintain a large share from its carbon-intensive coal-fired power plants and natural gas, while incorporating some renewable energies in its future emery supply mix. While the promoted targets might be cost-effective, the potential impacts of future energy developments on other sectors such as environment and agriculture (food) must not be overlooked to avoid unintended consequences. This chapter computes the desirability of energy generation alternatives for Indonesia using a stochastic multi-criteria decision making (MCDM) framework. The applied evaluation model considers the trade-offs among independently managed yet inter-linked energy systems and other interacting systems, namely, water, land, climate, and economy. The aggregate desirability of energy alternatives is determined for Indonesia as a whole and individually for its seven main islands. The study indicates nuclear and geothermal to be among the desirable technologies for Indonesia, assuming that they are feasible and can be developed and operated without causing major security risks. Although biomass and hydropower are renewable, they are among the least desirable technologies for Indonesia, given their secondary impacts on other resources. The analysis results portray the need for Indonesia to make fundamental changes in its future energy mix to avoid eventual collapse of its valuable natural system.

The lack of holistic decision-making assessments has been the main reason behind Lebanon’s persistent energy challenges for a long time. Increasing the capacity of renewable electricity generation as well as conventional power plants running on imported fuels has been proposed to ensure energy security in Lebanon. However, this approach does not necessarily consider Lebanon’s most persistent energy challenges and the potential impacts of selected technologies on Lebanon’s scarce land and water resources. Relying on a System of Systems (SoS) perspective and considering the Climate, Land, Energy, and Water (CLEW) nexus, this study is an effort to help overcome Lebanon’s energy sustainability challenges while reducing impacts on the country’s valuable natural, economic, and social resources. Two parallel but complementary frameworks are used. First, through Resource Efficiency Assessment (REA), the potential impacts of the electricity technologies on the nation’s environmental and economic resources are evaluated. Next, the Sustainability Performance Assessment (SPA) considers a number of criteria relative to the region’s economic, social, environmental, and technical energy challenges. Using the Aggregate Performance Index (API), the relative performance of each energy is calculated based on the results of REA and SPA. Results suggest that offshore wind, solar photovoltaics, natural gas, geothermal, nuclear, and hydropower technologies are the most desirable electricity generation options in Lebanon based on the assumptions and values used in this study.

By combining long-term ground-based data on water withdrawal with climate model projections, this study quantifies the compounding effects of human activities and climate change on surface water availability in Iran over the twenty-first century. Our findings show that increasing water withdrawal in Iran, due to population growth and increased agricultural activities, has been the main source of historical water stress. Increased levels of water stress across Iran are expected to continue or even worsen over the next decades due to projected variability and change in precipitation combined with heightened water withdrawals due to increasing population and socio-economic activities. The greatest rate of decreased water storage is expected in the Urmia Basin, northwest of Iran, (varying from ~ − 8.3 mm/year in 2010–2039 to ~ − 61.6 mm/year in 2070–2099 compared with an observed rate of 4 mm/year in 1976–2005). Human activities, however, strongly dominate the effects of precipitation variability and change. Major shifts toward sustainable land and water management are needed to reduce the impacts of water scarcity in the future, particularly in Iran’s heavily stressed basins like Urmia Basin, which feeds the shrinking Lake Urmia.

Sustainable green chemistry depends on technically feasible, cost-effective and socially acceptable decisions by regulators, industry and the wider community. The discipline needs to embrace a new suite of tools and train proponents in their use. We propose a set of tools that will bridge the gap between technical feasibility and efficiency on one hand, and social preferences and values on the other. We argue that they are indispensable in the next generation of regulators and chemistry industry proponents.

Reforms currently under way in China's electricity markets bear important implications for its decarbonization objectives. The southwestern province of Yunnan is among the provinces piloting the current iteration of power market reforms. As such, lessons from Yunnan will inform future market reform and renewable energy policies in China and potentially elsewhere. The dominance of hydropower in Yunnan's energy portfolio and the particular transmission constraints it faces, offer an interesting case study of the challenges of decarbonization. We report on market architecture reforms and aggregate market data collected from the Yunnan Power Exchange. We review four elements in the reformed market architecture. Market pricing rules, transitional quantity controls, the generation rights market, and inter-provincial trade. The specifics of market reform reflect a compromise between decarbonization, inter-provincial competition, grid security and development objectives and contribute to understanding of how the dual transitions of hydropower decarbonization and market liberalization interact. We conclude on six insights regarding the role of the grid operator, security checks on trade, integration of cascade hydropower, the inclusion of renewables in the generation rights market, price controls, and market participant price uncertainty.

The uncertainty of a changing climate raises challenges for water infrastructure planning and design. Not accounting for nonstationarity may result in under-designed structures that fail too frequently, or over-designed structures that are economically inefficient. This concern is magnified by uncertainty in the long-term frequency and magnitude of future extreme events. Planning strategies that allow adaptations over a structure's life could improve both reliability and economic efficiency. This study develops a method to inform adaptive water infrastructure planning with uncertain hydrologic and other forms of nonstationarity, applied to levee system planning. A stochastic dynamic programming model including a Markov process is developed for infrastructure planning with uncertain nonstationarity in flood frequency. Bayes' theorem is used to update peak flow probabilities conditioned on observed past peak flows and to update expected residual flood damages over time. A levee system planning problem with a numerical example from California illustrates the approach to derive optimal levee heights over time, and economic values of adapting to uncertain nonstationary flood risk. The projected range of probabilistic hydrology scenarios affects the optimal results, particularly in later planning stages as hydrology scenarios diverge with time. Adaptive planning strategies allowing more levee upgrades over time slightly lowers the overall cost and provides better flood protection than one-time construction under nonstationary hydrology for any climate in the example. Compared to a known future nonstationary hydrology, incorporating uncertain nonstationary climate results in higher levees being planned for observed severe hydrology scenarios in later stages. The overall present value cost with uncertain nonstationary climate depends on rates of change in peak flow distribution parameters in future hydrology scenarios.

Human livelihood requires reliable water supply and protection from water-related hazards. Significant growth in population and anthropogenic activities along with unfolding effects of global environmental change have enormously increased the vulnerability of human systems to changes in water quantity and/or quality. Addressing such vulnerabilities has high management priority in urban regions due to the concertation of population and socio-economic activities. This has resulted into emerging various discussions around the concept of “urban water security”. Here we provide a brief overview on the water-related threats to human society and the context of water security, with a greater goal of recognizing operational and social challenges along with science needs in urban environments.

Urbanisation and climate change are augmenting the uncertainty surrounding the future state of the world’s water resource and are resulting in cities experiencing growing levels of risk of pluvial flooding. Drainage infrastructure is generally built using the paradigm of ‘predict and optimise’; however, this approach fails to account for erroneous predictions. This can result in drainage systems delivering insufficient levels of flood protection. Irrespective of these uncertainties new drainage systems must be built, and existing ones adapted in such a way that they remain reliable. This work presents a critical analysis of the drivers of change of urban pluvial flooding and the uncertainties surrounding urban flood planning; thereby highlighting the shortcomings of current planning methodologies. Different Decision Making Under Deep Uncertainty (DMDU) frameworks are then explored and it is shown that they offer an improved ability to design reliable urban flood systems regardless of highly uncertain future conditions.

Lake Urmia in northwest Iran, once one of the largest hypersaline lakes in the world, has shrunk by almost 90% in area and 80% in volume during the last four decades. To improve the understanding of regional differences in water availability throughout the region and to refine the existing information on precipitation variability, this study investigated the spatial pattern of precipitation for the Lake Urmia basin. Daily rainfall time series from 122 precipitation stations with different record lengths were used to extract 15 statistical descriptors comprising 25th percentile, 75th percentile, and coefficient of variation for annual and seasonal total precipitation. Principal component analysis in association with cluster analysis identified three main homogeneous precipitation groups in the lake basin. The first sub-region (group 1) includes stations located in the center and southeast; the second sub-region (group 2) covers mostly northern and northeastern part of the basin, and the third sub-region (group 3) covers the western and southern edges of the basin. Results of principal component (PC) and clustering analyses showed that seasonal precipitation variation is the most important feature controlling the spatial pattern of precipitation in the lake basin. The 25th and 75th percentiles of winter and autumn are the most important variables controlling the spatial pattern of the first rotated principal component explaining about 32% of the total variance. Summer and spring precipitation variations are the most important variables in the second and third rotated principal components, respectively. Seasonal variation in precipitation amount and seasonality are explained by topography and influenced by the lake and westerly winds that are related to the strength of the North Atlantic Oscillation. Despite using incomplete time series with different lengths, the identified sub-regions are physically meaningful.

The Zayandeh-Rud River basin, Iran, is projected to face spatiotemporally heterogeneous temperature increase and precipitation reduction that will decrease water supply by mid-century. With projected increase (0.70–1.03 °C) in spring temperature and reduction (6– 55%) in winter precipitation, the upper Zayandeh-Rud sub-basin, the main source of renewable water supply, will likely become warmer and drier. In the lower sub-basin, 1.1–1.5 °C increase in temperature and 11–31% decrease in annual precipitation are likely. A system dynamics model was used to analyze adaptation strategies taking into account feedbacks between water resources development and biophysical and socioeconomic sub-systems. Results suggest that infrastructural improvements, rigorous water demand management (e.g., replacing high water demand crops such as rice, corn, and alfalfa), and ecosystem-based regulatory prioritization, complemented by supply augmentation can temporarily alleviate water stress in a basin that is essentially governed by the Limits to Growth archetype

In practice, selecting an energy project for development requires balancing criteria and competing stakeholder priorities to identify the best alternative. Energy source selection can be modeled as multi-criteria decision-maker problems to provide quantitative support to reconcile technical, economic, environmental, social, and political factors with respect to the stakeholders' interests. Decision making among these complex interactions should also account for the uncertainty present in the input data. In response, this work develops a stochastic decision analysis framework to evaluate alternatives by involving stakeholders to identify both quantitative and qualitative selection criteria and performance metrics which carry uncertainties. The developed framework is illustrated using a case study from Fairbanks, Alaska, where decision makers and residents must decide on a new source of energy for heating and electricity. We approach this problem in a five step methodology: (1) engaging experts (role players) to develop criteria of project performance; (2) collecting a range of quantitative and qualitative input information to determine the performance of each proposed solution according to the selected criteria; (3) performing a Monte-Carlo analysis to capture uncertainties given in the inputs; (4) applying multi-criteria decision-making, social choice (voting), and fallback bargaining methods to account for three different levels of cooperation among the stakeholders; and (5) computing an aggregate performance index (API) score for each alternative based on its performance across criteria and cooperation levels. API scores communicate relative performance between alternatives. In this way, our methodology maps uncertainty from the input data to reflect risk in the decision and incorporates varying degrees of cooperation into the analysis to identify an optimal and practical alternative.

Engineers face the ongoing challenge to effectively communicate for diverse purposes and audiences across multiple settings. The authors interviewed 10 practicing water resources systems en...

The present paper tries to identify the optimal size of a wind farm using North European data. An empirical analysis of 61 sites constructed between 2004 and 2014 suggests that economies-of-scale are highly heterogeneous across on-shore and off-shore projects. A Varying Coefficient Model captures such diversity by making the impact of the farm site on the amount of its potential capacity a non-linear function of the number of installed turbines. The resulting scale elasticities suggest that small on-shore farms have a bigger per-turbines output than off-shore ones, while the opposite is true for big projects.

often recognized too late, typically when changing the adopted technologies and behavioral norms is difficult. A similar story may unfold if society continues to blindly transition to an unregulated and environmentally unaudited digital world, a transition path that has been facilitated by the fourth industrial revolution and is now accelerated by the global COVID-19 crisis. The newly developed digital lifestyle has major environmental benefits, including the reduction of travel-related CO2 emissions. Yet, increased Internet use has some hidden environmental impacts that must be uncovered (Fig. 1a) to make the transition to a lowcarbon and green economy successful. The data centers’ electricity consumption accounts for 1% of the global energy demand (Masanet et al., 2020), more than the national energy consumption of many countries. Depending on the energy supply mix and use efficiency, Internet traffic contributes differently to negative environmental impacts and climate change. As the number of Internet users increases, the number of online services and applications they use grow. This trend exacerbates the environmental footprint of the Internet, despite the many successful and significant efforts to improve the efficiency of data centers (Masanet et al., 2020) and reduce their reliance on fossil energy. In order to build a sustainable digital world, it is imperative to carefully assess the environmental footprints of the Internet and identify the individual and collective actions that most affect its growth.

The competition over extracting the energy resources of the Caspian Sea together with the major anthropogenic changes in the coastal zones have resulted in increased pollution and environmental degradation of the sea. We provide the first evaluation of the spatiotemporal variation of chlorophyll-a (Chl-a) across the Caspian Sea. Using remotely sensed data from 2003 to 2017, we found that the Caspian Sea has suffered from a growing increase in Chl-a, especially in warmer months. The shallow parts of the sea, near Russia and Kazakhstan, especially where the Volga and Terek rivers discharge large nutrient loads (nitrogen- and phosphorus-rich compounds) into the sea, have experienced the highest variations in Chl-a. The Carlson’s trophic state index showed that during the study period, on average, about 12%, 26%, and 62% of the Caspian Sea’s area was eutrophic, mesotrophic, and oligotrophic, respectively. The identified trends reflect an increasing rate of environmental degradation in the Caspian Sea, which has been the subject of conflict among its littoral states that since the collapse of the Soviet Union have remained unable to agree on a legal regime for governing the sea and its resources.

Optimal risk-based levee designs are usually developed for economic efficiency. However, in river systems with multiple levees, the planning and maintenance of different levees are controlled by different agencies or groups. For example, along many rivers, levees on opposite riverbanks constitute a simple leveed river system with each levee designed and controlled separately. Collaborative planning of the two levees can be economically optimal for the whole system. Independent and self-interested landholders on opposite riversides often are willing to separately determine their individual optimal levee plans, resulting in a less efficient leveed river system from an overall society-wide perspective (the tragedy of commons). We apply game theory to simple leveed river system planning where landholders on each riverside independently determine their optimal risk-based levee plans. Outcomes from noncooperative games are analyzed and compared with the overall economically optimal outcome, which minimizes net flood cost system-wide. The system-wide economically optimal solution generally transfers residual flood risk to the lower-valued side of the river, but is often impractical without compensating for flood risk transfer to improve outcomes for all individuals involved. Such compensation can be determined and implemented with landholders' agreements on collaboration to develop an economically optimal plan. By examining iterative multiple-shot noncooperative games with reversible and irreversible decisions, the costs of myopia for the future in making levee planning decisions show the significance of considering the externalities and evolution path of dynamic water resource problems to improve decision-making.

On 18 May, the Edenville and Sanford dams, built in the 1920s to serve the people of Michigan, failed after a series of extreme rainfall events. More than 10,000 residents were evacuated, and flood waters inundated a major chemical complex, raising concerns of a widespread environmental catastrophe ([ 1 ][1]). These incidents, the latest in the long line of increasingly frequent ([ 2 ][2]) dam failures, highlight once again the importance of proactively addressing aging and problematic dams. To move forward, we need a scientific and legal framework in place to evaluate if and when dam removal is required and to ensure that adequate funds are devoted to implementing responsible decisions. The United States has removed about 1700 dams ([ 3 ][3]), many of them since 2000, but our understanding of how these decisions are made and the effects on local ecosystems remains incomplete. Less than 10% of dam removal cases have been scientifically evaluated ([ 4 ][4]). Most post-dam removal studies are less than a decade old and do not adequately represent the diversity of dam types, watershed conditions, dam-removal methods, and the decision-making processes in the United States. To prepare for future decisions, scientists should document, share, and analyze the collected data and lessons from both past and ongoing dam removal missions. We also lack information about the effects of dam removal on the environment. Records show that the local river and ecosystem do not fully revert to their pre-dam condition ([ 5 ][5]). Environmental impact assessments should inform all dam rehabilitation and removal decisions by considering a wide range of ecosystem evolution trajectories. Restoring the environment will require careful planning, close monitoring of the state of the ecosystem, sediment removal, and land use regulations. Finally, we must identify and address socio-economic, technological, and regulatory barriers to judicious and timely dam maintenance, rehabilitation, and removal. Both of the Michigan dams were more than 90 years old and previously classified as “high hazard,” as are a third of Michigan's 1059 dams and more than 15,600 dams across the United States ([ 6 ][6]). Because rehabilitating the nation's non-federal dams would cost more than $65 billion ([ 7 ][7]), unsafe dams continue to operate. To prevent future catastrophic events like the one in Michigan, we must clarify the importance of making funds available for rehabilitation and removal by raising awareness about the risks of problematic dams to human safety and environmental health. 1. [↵][8]1. D. K. Li , “Chemical plant and hazardous waste sites in path of Michigan flooding,” NBC News (2020). 2. [↵][9]National Performance of Dams Program, “Dam failures in the U.S., NPDP-01 V1” (Department of Civil & Environmental Engineering, Stanford University, 2018); [https://npdp.stanford.edu/sites/default/files/reports/npdp\_dam\_failure\_summary\_compilation\_v1\_2018.pdf][10]. 3. [↵][11]American Rivers, American Rivers Dam Removal Database, Version 7 (2020); . 4. [↵][12]1. R. Bellmore et al ., WIREs Wat. 4, e1164 (2017). [OpenUrl][13] 5. [↵][14]1. M. M. Foley et al ., Wat. Resour. Res. 53, 5229 (2017). [OpenUrl][15] 6. [↵][16]1. A. Singhvi, 2. T. Griggs , “Two dams that failed were rated ‘high hazard.’ A Third of Michigan's dams hold a similar risk,” The New York Times (2020). 7. [↵][17]Association of State Dam Safety Officials, State Performance and Current Issues (2020); [www.damsafety.org/state-performance][18]. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #xref-ref-1-1 "View reference 1 in text" [9]: #xref-ref-2-1 "View reference 2 in text" [10]: https://npdp.stanford.edu/sites/default/files/reports/npdp_dam_failure_summary_compilation_v1_2018.pdf [11]: #xref-ref-3-1 "View reference 3 in text" [12]: #xref-ref-4-1 "View reference 4 in text" [13]: {openurl}?query=rft.jtitle%253DWIREs%2BWat.%26rft.volume%253D4%26rft.spage%253De1164%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [14]: #xref-ref-5-1 "View reference 5 in text" [15]: {openurl}?query=rft.jtitle%253DWat.%2BResour.%2BRes.%26rft.volume%253D53%26rft.spage%253D5229%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [16]: #xref-ref-6-1 "View reference 6 in text" [17]: #xref-ref-7-1 "View reference 7 in text" [18]: http://www.damsafety.org/state-performance

Global warming urges governments to decarbonise their energy portfolios. Many governments have indistinctly transited away from fossil fuels towards renewable energies. However, a sustainable turnaround calls for limiting the overall impact of this transition on environmental resources and the economy. This study identifies the most desirable energy alternatives for the Middle Eastern and North African (MENA) countries based on their environmental and economic footprints using the Relative Aggregate Footprint (RAF) indicator. The RAFs of eleven widespread electricity generation technologies are computed for each country by considering the availability of four resources - energy, water, land, and the economy - which were weighted according to the national resource availability conditions. The results indicate that the MENA region must adapt their electricity mix to mitigate the impacts of climate change with respect to resource availability conditions, especially their scarce water resources. Due to the specificities of this region, deploying biomass and large-scale hydropower may lower greenhouse gases but significantly alter the impact on other valuable natural resources. Therefore, wind, geothermal, and nuclear power plants seem more desirable for a transition away from carbon-intensive technologies while their secondary effects on other resources (e.g. nuclear energy's possible water and environmental impacts) must be carefully considered.

We propose an unsupervised consensus approach for the control chart pattern recognition problem.We provide computational evidence of consensus clustering robustness.We provide motivation for further research on unsupervised learning for the CCPR problem. Early identification and detection of abnormal patterns is vital for a number of applications. In manufacturing for example, slide shifts and alterations of patterns might be indicative of some production process anomaly, such as machinery malfunction. Usually due to the continuous flow of data, monitoring of manufacturing processes and other types of applications requires automated control chart pattern recognition (CCPR) algorithms. Most of the CCPR literature consists of supervised classification algorithms. Fewer studies consider unsupervised versions of the problem. Despite the profound advantage of unsupervised methodology for less manual data labeling their use is limited due to the fact that their performance is not robust enough and might vary significantly from one algorithm to another. In this paper, we propose the use of a consensus clustering framework that takes care of this shortcoming and produces results that are robust with respect to the chosen pool of algorithms. Computational results show that the proposed method achieves not less than 79.10% G-mean with most of test instances achieving higher than 90%. This happens even when in the algorithmic pool are included algorithms with performance less than 15%. To our knowledge, this is the first paper proposing an unsupervised consensus learning approach in CCPR. The proposed approach is promising and provides a new research direction in unsupervised CCPR literature.