The rapid shrinkage of Lake Urmia, one of the world's largest saline lakes located in northwestern Iran, is a tragic wake-up call to revisit the principles of water resources management based on the socio-economic and environmental dimensions of sustainable development. The overarching goal of this paper is to set a framework for deriving dynamic, climate-informed environmental inflows for drying lakes considering both meteorological/climatic and anthropogenic conditions. We report on the compounding effects of meteorological drought and unsustainable water resource management that contributed to Lake Urmia's contemporary environmental catastrophe. Using rich datasets of hydrologic attributes, water demands and withdrawals, as well as water management infrastructure (i.e. reservoir capacity and operating policies), we provide a quantitative assessment of the basin's water resources, demonstrating that Lake Urmia reached a tipping point in the early 2000s. The lake level failed to rebound to its designated ecological threshold (1274 m above sea level) during a relatively normal hydro-period immediately after the drought of record (1998–2002). The collapse was caused by a marked overshoot of the basin's hydrologic capacity due to growing anthropogenic drought in the face of extreme climatological stressors. We offer a dynamic environmental inflow plan for different climate conditions (dry, wet and near normal), combined with three representative water withdrawal scenarios. Assuming effective implementation of the proposed 40% reduction in the current water withdrawals, the required environmental inflows range from 2900 million cubic meters per year (mcm yr−1) during dry conditions to 5400 mcm yr−1 during wet periods with the average being 4100 mcm yr−1. Finally, for different environmental inflow scenarios, we estimate the expected recovery time for re-establishing the ecological level of Lake Urmia.
Adaptation to climate change requires careful evaluation of infrastructure performance under future climatic extremes. This study demonstrates how a multidisciplinary approach integrating geotechnical engineering, hydrology, and climate science can be employed to quantify site-specific impacts of climate change on geotechnical infrastructure. Specifically, this paper quantifies the effects of changes in future streamflow on the performance of an earthen levee in Sacramento, California, considering multiple modes of failure. The streamflows for historical (1950–2000) and projected (2049–2099) scenarios with different recurrence intervals were derived from routed hydrological simulations driven by bias-corrected global climate models. The historical and future flood levels were then applied in a set of transient coupled finite-element seepage and limit equilibrium slope stability analyses to simulate the levee subjected to extreme streamflow. Variability in hydraulic and mechanical properties of soils was addressed using a Monte Carlo sampling method to evaluate and compare the probability of failure of the levee under different historical and future climate scenarios. Three individual modes (underseepage, uplift, and slope stability) along with lower and upper bounds for the combined mode of failure were examined. The results showed that incorporating future floods into levee failure analysis led to considerable reductions in the mean factor of safety and increases in the levee's probability of failure, suggesting that risk assessment based on historical records can significantly underestimate the levee's failure probability in a warming climate. Despite inherent uncertainties in future projections and substantial variability across climate models, evaluating infrastructure against projected extremes offers insights into their likely performance for the future.
Right after a devastating multi-year drought, a number of flood events with unprecedented spatial extent hit different parts of Iran over the 2-week period of March 17th to April 1st, 2019, causing a human disaster and substantial loss of assets and infrastructure across urban and rural areas. Here, we investigate natural (e.g., rainfall, snow accumulation/melt, soil moisture) and anthropogenic drivers (e.g., deforestation, urbanization, and management practices) of these events using a range of ground-based data and satellite observations. These drivers can range from exceptionally extreme rainfall intensities, to cascades of several extreme and moderate events, and various anthropogenic interventions that exacerbated flooding. Our results reveal strong compounding impacts of natural drivers and anthropogenic triggers in escalating flood risks to unprecedented levels. We argue that a new form of floods, i.e. anthropogenic floods, is becoming more common and should be recognized during the "Anthropocene". This specific form of floods refers to high to extreme streamflow/runoff events that are primarily caused, or largely exacerbated, by anthropogenic drivers. We demonstrate how the growing risk of anthropogenic floods can be assessed using a wide range of climatic and non-climatic satellite and in-situ data.
Roads and developed land can alter hydrologic pathways, cause erosion, and increase pollution to nearby waters. Best management practices (BMPs) are commonly used to reduce adverse effects of post-construction runoff. This study is focused on providing performance and cost information for optimally selecting the BMPs for retaining post-construction stormwater on site. The performance of BMPs was simulated numerically using an idealized catchment in an urban setting environment. The cost of construction and maintenance of these BMPs were based on unit price. The considered BMPs were bioswale, infiltration trench, and vegetated filter strip. The effects of vegetated covers such as turf or prairie grass on stormwater runoff reduction of linear projects with and without BMPs were also evaluated. Finally, based on construction cost, maintenance costs, and performance of BMPs, recommendations are made to help decision makers in implementing the optimal BMP to control stormwater runoff for highways in urban areas.
Abstract Globally, land subsidence (LS) often adversely impacts infrastructure, humans, and the environment. As climate change intensifies the terrestrial hydrologic cycle and severity of climate extremes, the interplay among extremes (e.g., floods, droughts, wildfires, etc.), LS, and their effects must be better understood since LS can alter the impacts of extreme events, and extreme events can drive LS. Furthermore, several processes causing subsidence (e.g., ice‐rich permafrost degradation, oxidation of organic matter) have been shown to also release greenhouse gases, accelerating climate change. Our review aims to synthesize these complex relationships, including human activities contributing to LS, and to identify the causes and rates of subsidence across diverse landscapes. We primarily focus on the era of synthetic aperture radar (SAR), which has significantly contributed to advancements in our understanding of ground deformations around the world. Ultimately, we identify gaps and opportunities to aid LS monitoring, mitigation, and adaptation strategies and guide interdisciplinary efforts to further our process‐based understanding of subsidence and associated climate feedbacks. We highlight the need to incorporate the interplay of extreme events, LS, and human activities into models, risk and vulnerability assessments, and management practices to develop improved mitigation and adaptation strategies as the global climate warms. Without consideration of such interplay and/or feedback loops, we may underestimate the enhancement of climate change and acceleration of LS across many regions, leaving communities unprepared for their ramifications. Proactive and interdisciplinary efforts should be leveraged to develop strategies and policies that mitigate or reverse anthropogenic LS and climate change impacts.
Earthen levees protecting coastal regions can be exposed to compound flooding induced by multiple drivers such as coastal water level, river discharge, and precipitation. However, the majority of flood hazard analyses consider only one flood driver at a time. This study numerically investigates the performance of an earthen levee in Sherman Island, Sacramento, CA, under compound flooding induced by fluvial and pluvial flooding. A finite element model is built for fully coupled 3D stress-flow simulations of the levee. The finite element model is then used to simulate the hydro-mechanical response of the levee under different flood scenarios. Fluvial flood hydrographs for different scenarios are obtained using a bivariate extreme analysis of peak river discharge and peak ocean level while accounting for the significance of correlation between these two variables. Pluvial flooding is characterized using intensity-duration-frequency (IDF) curves of extreme precipitations for the study area. The fluvial and pluvial flood patterns for different recurrence intervals are used in the finite element model to simulate the hydro-mechanical response of the levee. Results show that considering compound flooding leads to 8.7% and 18.6% reduction in the factor of safety for 2 and 50-year recurrence intervals, respectively.
