Developing climate resilience in aridlands using rock detention structures as green infrastructure

Laura M. Norman; Benjamin L. Ruddell; Deborah Tosline; Michael Fell; Blair P. Greimann; Jay Cederberg

doi:10.3390/su132011268

Home/Archive/USGS

USGS · 70227294

Developing climate resilience in aridlands using rock detention structures as green infrastructure

Laura M. Norman·Benjamin L. Ruddell·Deborah Tosline·Michael Fell·Blair P. Greimann·Jay Cederberg

View original source ↗Export metadata ↓

Abstract

The potential of ecological restoration and green infrastructure has been long suggested in the literature as adaptation strategies for a changing climate, with an emphasis on revegetation and, more recently, carbon sequestration and stormwater management. Tree planting and “natural” stormwater detention structures such as bioswales, stormwater detention basins, and sediment traps are popular approaches. However, the experimental verification of performance for these investments is scarce and does not address rock detention structures specifically. This 3-year study investigates the infiltration, peak flow mitigation, and microclimate performance of a natural wash stormwater retention installation using one-rock dams in an urban park in Phoenix, Arizona, USA. Field data collected during the study do not depict change in the hydrogeomorphology. However, hydrologic modeling, using data collected from the field, portrays decreases in peak flows and increases in infiltration at the treated sites. Additionally, we observe a lengthening of microclimate cooling effects following rainfall events, as compared with the untreated sites. In this urban arid land setting, the prospect that rock detention structures themselves could reduce warming or heat effects is promising.

Explore related subjects

Sustainability Article

Source-reported bounding extent: 32.46342595776104° to 34.492975402501536° latitude; -113.26904296874999° to -110.8245849609375° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Laura M. Norman, Benjamin L. Ruddell, Deborah Tosline, Michael Fell, Blair P. Greimann, Jay Cederberg. 2021-10-13. Developing climate resilience in aridlands using rock detention structures as green infrastructure. https://doi.org/10.3390/su132011268

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2025

Contribution of traffic emissions to PM2.5 concentrations at bus stops in Denver, Colorado

Individuals are routinely exposed to traffic-related air pollution on their commutes, which has significant health impacts. Mitigating exposure to traffic-related pollution is a key urban sustainability concern. In Denver, Colorado, low-income Americans are more likely to rely on buses and spend time waiting at bus stops. Evaluating the contribution of traffic emissions at bus stops can provide important information on risks experienced by these populations. We measured PM 2.5 constituents at eight bus stops and one background reference site in Denver, in the summer of 2023. Source profiles, including gasoline emissions from traffic, were estimated using Positive Matrix Factorization (PMF) analysis of PM 2.5 constituents collected at a Chemical Speciation Network site in our study region. The contributions of the different sources at each bus stop were estimated by regressing the vector of species concentrations at each site (dependent variable) on the source-profile matrix from the PMF analysis (independent variables). Traffic-related emissions (~2.5–6.6 μg/m 3 ) and secondary organics (~3–5 μg/m 3 ) contributed to PM 2.5 at the bus stops in our dataset. The highest traffic-related emissions-derived PM 2.5 concentrations were observed at bus stops near local sources: a gas station and a car wash. The contribution of traffic-related emissions was lower at the background site (~1 μg/m 3 ).

Colorado↗

USGS2025

Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan

The Ili River Basin is characterized by complex topography and diverse climatic zones with limited in situ observations. This study evaluates the performance of six widely used precipitation datasets, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), ERA5_Land (European Centre for Medium-Range Weather Forecasts—ECMWF Reanalysis 5_Land), GPCC (Global Precipitation Climatology Centre), IMERG (Integrated Multi-satellite Retrievals for GPM), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and TerraClimate, against ground-based data from 2001 to 2023. The evaluation is conducted across multiple spatial scales and temporal resolutions. At the basin scale, most datasets exhibit strong correlations with in situ observations across all temporal scales (r > 0.7), except for PERSIANN, which demonstrates a relatively weaker performance during summer and winter (r < 0.6). All datasets except ERA5_ Land show low annual and monthly bias (<5%), although larger errors are observed during summer, particularly for IMERG and PERSIANN. Dataset performance generally declines with increasing elevation. Basin-wide gridded evaluations reveal distinct spatial variations across all elevation zones, with CHIRPS showing the strongest ability to capture orographic precipitation gradients throughout the basin. All datasets correctly identified 2008 as a drought year and 2016 as a wet year, even though the magnitude and spatial resolution of the anomalies varied among them. These findings highlight the importance of selecting precipitation datasets that are suited to the complex topographic and climatic characteristics of transboundary basins. Our study provides valuable insights for improving hydrological modeling and can be used for water sustainability and flood–drought mitigation support activities in the Ili River Basin.

Ili River Basin↗

USGS2024

Rowing in the same direction using MIX— A tool to initiate the melding of individual disciplinary experts into an integrated interdisciplinary team

A common problem for interdisciplinary sustainability research is that scientists trained in different disciplines are often not rowing their boat effectively in the same direction. Sustainability tools can aid the implementation of this team-melding process. Here, our purpose is to illustrate our M ulti-step I ntegrated graphical and structured discussion e X ercise ( MIX ) tool that transforms diverse disciplinary experts into an interdisciplinary team. We use a visual puzzle-solving approach based on the blind men and the elephant metaphor (BMEM) because this story illustrates the shortcomings of siloed viewpoints and the need to integrate multiple perspectives. Our six-step MIX tool provides step-specific objectives, group activities, discussion questions, and learning outcomes. Activities promote experiential learning for team problem solving. The step-specific structured discussions are designed to get each individual to change their focus from their own discipline (i.e., an elephant trunk, tail, leg, or other isolated pieces of the whole animal) to the team’s interdisciplinary goal (i.e., the whole elephant or the entire multi-faceted problem). In our example proof of concept, we show that a narrow focus on only economic yield (trunk), ecological conservation (legs), or human values (tail) misrepresents the biologically involved sustainability problem (elephant) and blocks innovative solutions.

Sustainability↗