Desiccation of a saline lake as a lock-in phenomenon: A socio-hydrological perspective.

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.

Emergent dispersal networks in dynamic wetlandscapes.

The connectivity among distributed wetlands is critical for aquatic habitat integrity and to maintain metapopulation biodiversity. Here, we investigated the spatiotemporal fluctuations of wetlandscape connectivity driven by stochastic hydroclimatic forcing, conceptualizing wetlands as dynamic habitat nodes in dispersal networks. We hypothesized that spatiotemporal hydrologic variability influences the heterogeneity in wetland attributes (e.g., size and shape distributions) and wetland spatial organization (e.g., gap distances), in turn altering the variance of the dispersal network topology and the patterns of ecological connectivity. We tested our hypotheses by employing a DEM-based, depth-censoring approach to assess the eco-hydrological dynamics in a synthetically generated landscape and three representative wetlandscapes in the United States. Network topology was examined for two end-member connectivity measures: centroid-to-centroid (C2C), and perimeter-to-perimeter (P2P), representing the full range of within-patch habitat preferences. Exponentially tempered Pareto node-degree distributions well described the observed structural connectivity of both types of networks. High wetland clustering and attribute heterogeneity exacerbated the differences between C2C and P2P networks, with Pareto node-degree distributions emerging only for a limited range of P2P configuration. Wetlandscape network topology and dispersal strategies condition species survival and biodiversity.

Stochastic dynamics of wetlandscapes: Ecohydrological implications of shifts in hydro-climatic forcing and landscape configuration.

Wetlands are embedded in landscapes in fractal spatial patterns, and are characterized by highly dynamic, interlinked hydrological, biogeochemical, and ecological functions. We propose here a stochastic approach to evaluate and predict the spatiotemporal hydrologic variability of wetlands at landscape scale (100 km2). Stochastic hydro-climatic forcing (daily rainfall and evapotranspiration) and the landscape topographic setting (spatial structure of wetlands within the landscape) are key drivers of wetland eco-hydrologic functionality. The novelty of our approach lies in the quantification of the hydrological dynamics for all wetlands distributed in a given landscape, and in linking stochasticity of hydroclimatic forcing and ecologically meaningful wetland network metrics. We applied the modeling framework to investigate daily hydrologic dynamics in six landscapes across the U.S. that span gradients of hydroclimate and abundance of wetlands. We assess landscape-scale patterns using four key wetland hydrological attributes that have significance in terms of aquatic habitat suitability and dispersal: (1) Abundance (2) Diversity (3) Persistence, and (4) Accessibility. We observe that the hydrologic responses of each of the six landscapes are driven by the interactions between regional stochastic hydro-climatic forcing and landscape topographic setting. Despite differences in these features, similar scaling relations define diversity (area distributions) and accessibility (separation-distance distributions). Persistence of hydrologic regimes, defined by duration of inundation above thresholds, was least in more-arid settings, and higher in humid settings, consistent with intuitive understanding. These results can support assessments of the spatiotemporal variability of ecohydrological attributes in diverse wetlandscapes, including aquatic species dispersal and habitat suitability for unique flora and fauna.

Optimum positioning of wastewater treatment plants in a river network: A model-based approach to minimize microbial pollution.

Microbial pollution in river networks is widespread, threatening human health and activities. Wastewater treatment plants are a major source of microbial pollution that affects downstream communities. We propose a simple modeling approach to identify possible hot-spots of microbial pollution in river networks receiving treated wastewater. We consider every reach in a river network as a potential site for the disposal of treated wastewater and we identify the corresponding section of the downstream river where the concentration of indicator bacteria exceeds a prescribed threshold value. In this paper, we introduce the methodology and demonstrate its application to a small river basin (Lockwitzbach, Germany). We computed the lengths of the polluted river sections for different scenarios in order to separately identify the impacts of hydrological boundary conditions and bacterial retention processes. Effective parameters describing bacterial retention were inferred from field samples. The proposed modeling approach can be used to generate dynamic maps of safe and vulnerable zones in a river network. Our approach helps disentangle the effects of network structure, hydrological variability and in-stream processes on the location and length of unsafe river sections. Our model can be used to identify optimal sites for the discharge of treated wastewater. For example, in the Lockwitzbach basin, we show that relocating the existing effluent discharge could reduce the stream length affected by severe microbial pollution by almost 30%.

Effects of vertical hydrodynamic mixing on photomineralization of dissolved organic carbon in arctic surface waters.

Photomineralization, the transformation of dissolved organic carbon (DOC) to CO2 by sunlight, is an important source of CO2 in arctic surface waters. However, quantifying the role of photomineralization in inland waters is limited by the understanding of hydrologic controls on this process. To bridge this gap, this study evaluates mixing limitations, i.e., whether and by how much vertical mixing limits the depth-integrated photomineralization rate, in freshwater systems. We developed a conceptual model to qualitatively assess mixing limitations across the range of light attenuation and hydrologic conditions observed in freshwaters. For the common case of exponential light attenuation over depth, we developed a mathematical model to quantify mixing limitation, and used this model to assess a range of arctic freshwater systems. The results demonstrate that mixing limitations are important when there is significant light attenuation by suspended sediment (SS), which is the case in some arctic, boreal and temperate waters. Mixing limitation is pronounced when light attenuation over depth is strong and when the photomineralization rate at the water surface exceeds the vertical mixing rate. Arctic streams and rivers have strong vertical mixing relative to surface photomineralization, such that model results demonstrate no mixing limitation regardless of how much SS is present. Our analysis indicates that well-mixed assumptions used in prior work are valid in many, but not all, arctic surface waters. The effects of mixing limitations in reducing the photomineralization rate must be considered in arctic lakes with high SS concentrations.

A Process-Based Model for Bioturbation-Induced Mixing.

Bioturbation refers to the transport processes carried out by living organisms and their physical effects on soils and sediments. It is widely recognized as an important mixing mechanism, particularly at the sediment-water interface in many natural systems. In order to quantify its impact on mixing, we propose a process-based model based on simple assumptions about organism burrowing behavior. Specifically, we consider burrowing events to be stochastic but memoryless, leading to exponential inter-burrow waiting times and depths. We then explore the impact of two different transport mechanisms on the vertical concentration distributions predicted by the model for a conservative (inert) tracer. We compare the results of our model to experimental data from a recent laboratory study of bioturbation by the freshwater oligochaete worm Lumbriculus variegatus, and find good quantitative agreement.

Noise-Driven Return Statistics: Scaling and Truncation in Stochastic Storage Processes.

In countless systems, subjected to variable forcing, a key question arises: how much time will a state variable spend away from a given threshold? When forcing is treated as a stochastic process, this can be addressed with first return time distributions. While many studies suggest exponential, double exponential or power laws as empirical forms, we contend that truncated power laws are natural candidates. To this end, we consider a minimal stochastic mass balance model and identify a parsimonious mechanism for the emergence of truncated power law return times. We derive boundary-independent scaling and truncation properties, which are consistent with numerical simulations, and discuss the implications and applicability of our findings.

An Integrated Experimental and Modeling Approach to Predict Sediment Mixing from Benthic Burrowing Behavior.

Bioturbation is the dominant mode of sediment transport in many aquatic environments and strongly influences both sediment biogeochemistry and contaminant fate. Available bioturbation models rely on highly simplified biodiffusion formulations that inadequately capture the behavior of many benthic organisms. We present a novel experimental and modeling approach that uses time-lapse imagery to directly relate burrow formation to resulting sediment mixing. We paired white-light imaging of burrow formation with fluorescence imaging of tracer particle redistribution by the oligochaete Lumbriculus variegatus. We used the observed burrow formation statistics and organism density to parametrize a parsimonious model for sediment mixing based on fundamental random walk theory. Worms burrowed over a range of times and depths, resulting in homogenization of sediments near the sediment-water interface, rapid nonlocal transport of tracer particles to deep sediments, and large areas of unperturbed sediments. Our fundamental, parsimonious random walk model captures the central features of this highly heterogeneous sediment bioturbation, including evolution of the sediment-water interface coupled with rapid near-surface mixing and anomalous late-time mixing resulting from infrequent, deep burrowing events. This approach provides a general, transferable framework for explicitly linking sediment transport to governing biophysical processes.