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Understanding of how anthropogenic droughts occur in socio-hydrological systems is critical in studying resilience of these systems. This is especially relevant when a "lock-in" toward watershed desiccation occurs as an emergent outcome of coupling among social dynamics and surface and underground water processes. How the various processes collectively fit together to reinforce such a lock-in and what may be a critical or ignored feedback worsening the state of the socio-hydrological systems remains poorly understood. Here we tackle this gap by focusing on the case of Lake Urmia in Iran, a saline lake that faces the same fate as that of Aral Sea due to over-extraction of water sources that feed the lake. We develop an integrative, system-level understanding of how various anthropogenic, surface and underground environmental processes collectively generate the water scarcity and soil salinization issues in the study case. To this end, we investigate a paradoxical phenomenon wherein the increase of soil salinity has not noticeably affected the level of vegetation cover in Lake Urmia Basin. The outcome of our analysis may provide useful insights for informing policymakers how to cope with drought and water scarcity issues in many fragile saline lakes around the world that are currently under threat by overexploitation.

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The Sustainable Development Goals (SDGs) of the United Nations Agenda 2030 represent an ambitious blueprint to reduce inequalities globally and achieve a sustainable future for all mankind. Meeting the SDGs for water requires an integrated approach to managing and allocating water resources, by involving all actors and stakeholders, and considering how water resources link different sectors of society. To date, water management practice is dominated by technocratic, scenario-based approaches that may work well in the short term but can result in unintended consequences in the long term due to limited accounting of dynamic feedbacks between the natural, technical, and social dimensions of human-water systems. The discipline of sociohydrology has an important role to play in informing policy by developing a generalizable understanding of phenomena that arise from interactions between water and human systems. To explain these phenomena, sociohydrology must address several scientific challenges to strengthen the field and broaden its scope. These include engagement with social scientists to accommodate social heterogeneity, power relations, trust, cultural beliefs, and cognitive biases, which strongly influence the way in which people alter, and adapt to, changing hydrological regimes. It also requires development of new methods to formulate and test alternative hypotheses for the explanation of emergent phenomena generated by feedbacks between water and society. Advancing sociohydrology in these ways therefore represents a major contribution toward meeting the targets set by the SDGs, the societal grand challenge of our time.

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Food flows underpin the complex food supply chains that are prevalent in our increasingly globalized world. Recently, much effort has been devoted to evaluating the resources (e.g. water, carbon, nutrients) embodied in food trade. Now, research is needed to understand the scientific principles of the food commodity flows that underpin these virtual resource transfers. How do food flows vary with spatial scale? To address this question, we present an empirical analysis of food commodity flow networks across the full spectrum of spatial scales: global, national, and village. We discover properties of both scale invariance and scale dependence in food flow networks. The statistical distribution of node connectivity and mass flux are consistent across scales. Node connectivity follows a generalized exponential distribution, while node mass flux follows a Gamma distribution across scales. Similarly, the relationship between node connectivity and mass flux follows a power law across scales. However, the parameters of the distributions change with spatial scale. Mean node connectivity and mass flux increase with increasing scale. A core group of nodes exists at all scales, but node centrality increases as the spatial scale decreases, indicating that some households are more critical to village food exchanges than countries are to global trade. Remarkably, the structural network properties of food flows are consistent across spatial scales, indicating that a universal mechanism may underpin food exchange systems. In future research, this understanding can be used to develop theoretical models of food flow networks and to model food flows at resolutions for which empirical information is not available.

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Implementing public policies often involves navigating an array of choices that have economic and environmental consequences that are difficult to quantify due to the complexity of multiple system interactions. Implementing the mandate for cellulosic biofuel production in the Renewable Fuel Standard (RFS) and reducing hypoxia in the northern Gulf of Mexico by reducing riverine nitrate-N loads represent two such cases that overlap in the Mississippi River Basin. To quantify the consequences of these interactions, a system of systems (SoS) model was developed that incorporates interdependencies among the various subsystems, including biofuel refineries, transportation, agriculture, water resources and crop/ethanol markets. The model allows examination of the impact of imposing riverine nitrate-N load limits on the biofuel production system as a whole, including land use change and infrastructure needs. The synergies of crop choice (first versus second generation biofuel crops), infrastructure development, and environmental impacts (streamflow and nitrate-N load) were analyzed to determine the complementarities and trade-offs between environmental protection and biofuel development objectives. For example, the results show that meeting the cellulosic biofuel target in the RFS using Miscanthus x giganteus reduces system profits by 8% and reduces nitrate-N loads by 12% compared to the scenario without a mandate. However, greater water consumption by Miscanthus is likely to reduce streamflow with potentially adverse environmental consequences that need to be considered in future decision making.

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Vegetation has different adjustable properties for adaptation to its environment. Examples include stomatal conductance at short time scale (minutes), leaf area index and fine root distributions at longer time scales (days-months) and species composition and dominant growth forms at very long time scales (years-decades-centuries). As a result, the overall response of evapotranspiration to changes in environmental forcing may also change at different time scales. The vegetation optimality model simulates optimal adaptation to environmental conditions, based on the assumption that different vegetation properties are optimized to maximize the long-term net carbon profit, allowing for separation of different scales of adaptation, without the need for parametrization with observed responses. This paper discusses model simulations of vegetation responses to today's elevated atmospheric CO2 concentrations (eCO2) at different temporal scales and puts them in context with experimental evidence from free-air CO2 enrichment (FACE) experiments. Without any model tuning or calibration, the model reproduced general trends deduced from FACE experiments, but, contrary to the widespread expectation that eCO2 would generally decrease water use due to its leaf-scale effect on stomatal conductance, our results suggest that eCO2 may lead to unchanged or even increased vegetation water use in water-limited climates, accompanied by an increase in perennial vegetation cover.

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Assisted colonization-the deliberate translocation of species from unsuitable to suitable regions-is a controversial management tool that aims to prevent the extinction of populations that are unable to migrate in response to climate change or to survive in situ. The identification of suitable translocation sites is therefore a pressing issue. Correlative species distribution models, which are based on occurrence data, are of limited use for site selection for species with historically restricted distributions. In contrast, mechanistic species distribution models hold considerable promise in selecting translocation sites. Here we integrate ecoenergetic and hydrological models to assess the longer-term suitability of the current habitat of one of the world's rarest chelonians, the Critically Endangered Western Swamp Tortoise (Psuedemydura umbrina). Our coupled model allows us to understand the interaction between thermal and hydric constraints on the foraging window of tortoises, based on hydrological projections of its current habitat. The process can then be repeated across a range of future climates to identify regions that would fall within the tortoise's thermodynamic niche. The predictions indicate that climate change will result in reduced hydroperiods for the tortoises. However, under some climate change scenarios, habitat suitability may remain stable or even improve due to increases in the heat budget. We discuss how our predictions can be integrated with energy budget models that can capture the consequences of these biophysical constraints on growth, reproduction and body condition.

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The timing and magnitude of rainfall events are known to be dominant controls on pesticide migration into streams and groundwater, by triggering rapid flow processes, such as preferential flow and surface runoff. A better understanding of how regional differences in rainfall impact rapid leaching risk is required in order to match the scale at which water regulation occurs. We estimated the potential amount of rapid leaching, and the frequencies of these events in a case study of the southwest of Western Australia, for one soil type and a range of linearly sorbing, first order degrading chemicals. At the regional scale, those chemicals with moderate sorption and long half lives were the most susceptible to rapid transport within a year of application. Within the region, this susceptibility varied depending upon application time and seasonality in storm patterns. Those chemicals and areas with a high potential for rapid transport on average, also experience the greatest inter-annual variability in rapid leaching, as measured by the coefficient of variation. The timing and frequencies of rapid leaching events appeared to strongly relate to an area's relative susceptibility to rapid leaching. In the study region the results also suggested that frontal rainfall dominates rapid leaching along the western and southern coasts while convective thunderstorms play a greater role in the arid east.

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Common empirical models of stomatal conductivity often incorporate a sensitivity of stomata to the rate of leaf photosynthesis. Such a sensitivity has been predicted on theoretical terms by Cowan and Farquhar, who postulated that stomata should adjust dynamically to maximize photosynthesis for a given water loss. In this study, we implemented the Cowan and Farquhar hypothesis of optimal stomatal conductivity into a canopy gas exchange model, and predicted the diurnal and daily variability of transpiration for a savanna site in the wet-dry tropics of northern Australia. The predicted transpiration dynamics were then compared with observations at the site using the eddy covariance technique. The observations were also used to evaluate two alternative approaches: constant conductivity and a tuned empirical model. The model based on the optimal water-use hypothesis performed better than the one based on constant stomatal conductivity, and at least as well as the tuned empirical model. This suggests that the optimal water-use hypothesis is useful for modelling canopy gas exchange, and that it can reduce the need for model parameterization.

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Photosynthesis provides plants with their main building material, carbohydrates, and with the energy necessary to thrive and prosper in their environment. We expect, therefore, that natural vegetation would evolve optimally to maximize its net carbon profit (NCP), the difference between carbon acquired by photosynthesis and carbon spent on maintenance of the organs involved in its uptake. We modelled N(CP) for an optimal vegetation for a site in the wet-dry tropics of north Australia based on this hypothesis and on an ecophysiological gas exchange and photosynthesis model, and compared the modelled CO2 fluxes and canopy properties with observations from the site. The comparison gives insights into theoretical and real controls on gas exchange and canopy structure, and supports the optimality approach for the modelling of gas exchange of natural vegetation. The main advantage of the optimality approach we adopt is that no assumptions about the particular vegetation of a site are required, making it a very powerful tool for predicting vegetation response to long-term climate or land use change.

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