Detecting Streamflow in Dryland Rivers Using CubeSats.

Determining the flow regime of non-perennial rivers is critical in hydrology. In this study, we developed a new approach using CubeSat imagery to detect streamflow presence using differences in surface reflectance for areas within and outside of a river reach. We calibrated the approach with streamflow records in the Hassayampa River of Arizona over 3 years (2019-2021), finding good agreement in the annual fractions of flowing days at stream gages (R 2 = 0.82, p < 0.0001). Subsequently, annual fractions of flowing days were derived at 90 m intervals along the Hassayampa River, finding that 12% of reaches were classified as intermittent, with the remaining as ephemeral. Using a Hovmöller diagram, streamflow presence was visualized in unprecedented spatiotemporal detail, allowing estimates of daily fraction of flowing channel and annual fractions of flowing days. This new tool opens avenues for detecting streamflow and studying hydrological and biogeochemical processes dependent on water presence in drylands.

Modeling riverine pathogen fate and transport in Mexican rural communities and associated public health implications.

The discharge of untreated or poorly treated wastewater to river systems remains a major problem affecting public and environmental health, particularly in rural communities of less developed countries. One of the primary goals in setting policies for wastewater management is to reduce risks to human health associated with microbial contamination of receiving water. In this study, we apply a surface water quality model to develop an Escherichia coli based indicator that reflects the quality of surface water and the potential impact to recreational users in a large, rural river in northwest Mexico (upper Sonora River). The model assesses the relative importance of streamflow variations and the uncertainty in E. coli removal coefficient parameters for the predictions of E. coli concentrations in the river. Given the sparse information on streamflow, we use a physically-based, distributed hydrologic model to generate tributary contributions to the river. We determined the best estimate and uncertainty of E. coli removal rates to explore the impacts of parameter uncertainty on the transport of E. coli downstream from two wastewater discharge zones. Our results depict the regions in the river that are in noncompliance with fresh water pathogen norms. The impact of streamflow variability and uncertainty in the removal rates of pathogen indicators was used to derive a range of river distances in noncompliance. The comparison between two sites with different streamflow behaviors was used to illustrate the impacts of streamflow spatiotemporal variability on pathogen indicators. We derive a simple relationship that can be used to assess the relative importance of dilution (ratio of wastewater discharge to river discharge) and pathogen removal (ratio of residence time to reaction time).

Hydrological and topographic determinants of biomass and species richness in a Mediterranean-climate shrubland.

BACKGROUND: In arid and semiarid shrublands, water availability directly influences ecosystem properties. However, few empirical tests have determined the association between particular soil and hydrology traits with biodiversity and ecosystem biomass at the local scale. METHODS: We tested if plant species richness (S) and aboveground biomass (AGB) were associated with soil and topographic properties on 36 plots (ca. 12.5 m2) in 17 hectares of chaparral in the Mediterranean-climate of Valle de Guadalupe, Baja California, México. We used close-to-the-ground aerial photography to quantify sky-view cover per species, including all growth forms. We derived an elevation model (5 cm) from other aerial imagery. We estimated six soil properties (soil water potential, organic matter content, water content, pH, total dissolved solids concentration, and texture) and four landscape metrics (slope, aspect, elevation, and topographic index) for the 36 plots. We quantified the biomass of stems, leaves, and reproductive structures, per species. RESULTS: 86% of AGB was in stems, while non-woody species represented 0.7% of AGB but comprised 38% of S (29 species). Aboveground biomass and species richness were unrelated across the landscape. S was correlated with aspect and elevation (R = 0.53, aspect P = 0.035, elevation P = 0.05), while AGB (0.006-9.17 Kg m-2) increased with soil water potential and clay content (R = 0.51, P = 0.02, and P = 0.04). Only three species (11% of total S) occupied 65% of the total plant cover, and the remaining 26 represented only 35%. Cover was negatively correlated with S (R = -0.38, P = 0.02). 75% of AGB was concentrated in 30% of the 36 plots, and 96% of AGB corresponded to only 20% of 29 species. DISCUSSION: At the scale of small plots in our studied Mediterranean-climate shrubland in Baja California, AGB was most affected by soil water storage. AGB and cover were dominated by a few species, and only cover was negatively related to S. S was comprised mostly by uncommon species and tended to increase as plant cover decreased.

Urban land cover type determines the sensitivity of carbon dioxide fluxes to precipitation in Phoenix, Arizona.

Urbanization modifies land surface characteristics with consequent impacts on local energy, water, and carbon dioxide (CO2) fluxes. Despite the disproportionate impact of cities on CO2 emissions, few studies have directly quantified CO2 conditions for different urban land cover patches, in particular for arid and semiarid regions. Here, we present a comparison of eddy covariance measurements of CO2 fluxes (FC) and CO2 concentrations ([CO2]) in four distinct urban patches in Phoenix, Arizona: a xeric landscaping, a parking lot, a mesic landscaping, and a suburban neighborhood. Analyses of diurnal, daily, and seasonal variations of FC and [CO2] were related to vegetation activity, vehicular traffic counts, and precipitation events to quantify differences among sites in relation to their urban land cover characteristics. We found that the mesic landscaping with irrigated turf grass was primarily controlled by plant photosynthetic activity, while the parking lot in close proximity to roads mainly exhibited the signature of vehicular emissions. The other two sites that had mixtures of irrigated vegetation and urban surfaces displayed an intermediate behavior in terms of CO2 fluxes. Precipitation events only impacted FC in urban patches without outdoor water use, indicating that urban irrigation decouples CO2 fluxes from the effects of infrequent storms in an arid climate. These findings suggest that the proportion of irrigated vegetation and urban surfaces fractions within urban patches could be used to scale up CO2 fluxes to a broader city footprint.

Woody Plant Encroachment has a Larger Impact than Climate Change on Dryland Water Budgets.

Woody plant encroachment (WPE) into grasslands is a global phenomenon that is associated with land degradation via xerification, which replaces grasses with shrubs and bare soil patches. It remains uncertain how the global processes of WPE and climate change may combine to impact water availability for ecosystems. Using a process-based model constrained by watershed observations, our results suggest that both xerification and climate change augment groundwater recharge by increasing channel transmission losses at the expense of plant available water. Conversion from grasslands to shrublands without creating additional bare soil, however, reduces transmission losses. Model simulations considering both WPE and climate change are used to assess their relative roles in a late 21st century condition. Results indicate that changes in focused channel recharge are determined primarily by the WPE pathway. As a result, WPE should be given consideration when assessing the vulnerability of groundwater aquifers to climate change.

Closing the Loop of Satellite Soil Moisture Estimation via Scale Invariance of Hydrologic Simulations.

Surface soil moisture plays a crucial role on the terrestrial water, energy, and carbon cycles. Characterizing its variability in space and time is critical to increase our capability to forecast extreme weather events, manage water resources, and optimize agricultural practices. Global estimates of surface soil moisture are provided by satellite sensors, but at coarse spatial resolutions. Here, we show that the resolution of satellite soil moisture products can be increased to scales representative of ground measurements by reproducing the scale invariance properties of soil moisture derived from hydrologic simulations at hyperresolutions of less than 100 m. Specifically, we find that surface soil moisture is scale invariant over regimes extending from a satellite footprint to 100 m. We use this evidence to calibrate a statistical downscaling algorithm that reproduces the scale invariance properties of soil moisture and test the approach against 1-km aircraft remote sensing products and through comparisons of downscaled satellite products to ground observations. We demonstrate that hyperresolution hydrologic models can close the loop of satellite soil moisture downscaling for local applications such as agricultural irrigation, flood event prediction, and drought and fire management.

MOD-LSP, MODIS-based parameters for hydrologic modeling of North American land cover change.

Earth systems models require gridded land surface properties to compute fluxes of water, energy, and carbon within the landscape and to the atmosphere. However, most parameter sets contain time-invariant properties despite their known variability. Here we present new MODerate Resolution Imaging Spectroradiometer (MODIS)-based land surface parameters (MOD-LSP) formatted for the Variable Infiltration Capacity (VIC) hydrologic model that account for seasonal and interannual variability and longer-term change over the continental United States, Mexico, and southern Canada at 0.0625° spatial resolution and monthly temporal resolution. MOD-LSP improves over previously-available parameter sets via: (1) land cover maps of higher native spatial resolution; (2) multiple versions corresponding to the land cover of years 1992, 2001, and 2011; (3) spatially-explicit mean annual cycles of land surface properties, including leaf area index, canopy fraction, and albedo, derived from 17 years of observations; and (4) additional 17-year time series of these properties. The MOD-LSP parameters are useful as inputs to the VIC model, as an example land surface scheme, to assess the hydrologic impacts of land cover change from interannual to decadal scales; and as stand-alone datasets characterizing the temporal variability of these properties as a function of land cover class.

Comment on "Short-lived pause in Central California subsidence after heavy winter precipitation of 2017" by K. D. Murray and R. B. Lohman.

In a study by Murray and Lohman (M&L), the authors suggest that remote sensing data are useful for monitoring land subsidence due to aquifer system compaction. We agree. To infer aquifer dynamics, we provide a more detailed and joint analysis of deformation and groundwater data. Investigating well data in the Tulare Basin, we find that groundwater levels stabilized before 2015 and show that M&L's observed continued subsidence through July 2016 is likely caused by the delayed compaction of the aquitard. Our analysis suggests the observed 2017 transient uplift is not due to recharge of the aquifer system after heavy winter rainfall because it requires an unrealistic vertical hydraulic gradient nearly five orders of magnitude larger than that typical of Tulare Basin. We find that, regardless of the amount of rainfall, transient annual uplifts of ~3 cm occur in May to June. Using an elastic skeletal storage coefficient of 5 × 10-3, we link this ground uplift to annual groundwater level changes.

Co-Producing Interdisciplinary Knowledge and Action for Sustainable Water Governance: Lessons from the Development of a Water Resources Decision Support System in Pernambuco, Brazil.

One of the most pressing global challenges for sustainable development is freshwater management. Sustainable water governance requires interdisciplinary knowledge about environmental and social processes as well as participatory strategies that bring scientists, managers, policymakers, and other stakeholders together to cooperatively produce knowledge and solutions, promote social learning, and build enduring institutional capacity. Cooperative production of knowledge and action is designed to enhance the likelihood that the findings, models, simulations, and decision support tools developed are scientifically credible, solutions-oriented, and relevant to management needs and stakeholders' perspectives. To explore how interdisciplinary science and sustainable water management can be co-developed in practice, the experiences of an international collaboration are drawn on to improve local capacity to manage existing and future water resources efficiently, sustainably, and equitably in the State of Pernambuco in northeastern Brazil. Systems are developed to model and simulate rainfall, reservoir management, and flood forecasting that allow users to create, save, and compare future scenarios. A web-enabled decision support system is also designed to integrate models to inform water management and climate adaptation. The challenges and lessons learned from this project, the transferability of this approach, and strategies for evaluating the impacts on management decisions and sustainability outcomes are discussed.

Impacts of climate change on precipitation and discharge extremes through the use of statistical downscaling approaches in a Mediterranean basin.

Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5km(2)), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs.