Deciphering the expression of climate change within the Lower Colorado River basin by stochastic simulation of convective rainfall

In drylands, convective rainstorms typically control runoff, streamflow, water supply and flood risk to human populations, and ecological water availability at multiple spatial scales. Since drainage basin water balance is sensitive to climate, it is important to improve characterization of convective rainstorms in a manner that enables statistical assessment of rainfall at high spatial and temporal resolution, and the prediction of plausible manifestations of climate change. Here we present a simple rainstorm generator, STORM, for convective storm simulation. It was created using data from a rain gauge network in one dryland drainage basin, but is applicable anywhere. We employ STORMto assess watershed rainfall under climate change simulations that reflect differences in wetness/ storminess, and thus provide insight into observed or projected regional hydrologic trends. Our analysis documents historical, regional climate change manifesting as a multidecadal decline in rainfall intensity, which we suggest has negatively impacted ephemeral runoff in the Lower Colorado River basin, but has not contributed substantially to regional negative streamflow trends

STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change

Assessments of water balance changes, watershed response, and landscape evolution to climate change require representation of spatially and temporally varying rainfall fields over a drainage basin, as well as the flexibility to simply modify key driving climate variables (evaporative demand, overall wetness, storminess). An empirical–stochastic approach to the problem of rainstorm simulation enables statistical realism and the creation of multiple ensembles that allow for statistical characterization and/or time series of the driving rainfall over a fine grid for any climate scenario. Here, we provide details on the STOchastic Rainfall Model (STORM), which uses this approach to simulate drainage basin rainfall. STORM simulates individual storms based on Monte Carlo selection from probability density functions (PDFs) of storm area, storm duration, storm intensity at the core, and storm center location. The model accounts for seasonality, orography, and the probability of storm intensity for a given storm duration. STORM also generates time series of potential evapotranspiration (PET), which are required for most physically based applications. We explain how the model works and demonstrate its ability to simulate observed historical rainfall characteristics for a small watershed in southeast Arizona. We explain the data requirements for STORM and its flexibility for simulating rainfall for various classes of climate change. Finally, we discuss several potential applications of STORM

Compound-specific amino acid ¹⁵N stable isotope probing of nitrogen assimilation by the soil microbial biomass using gas chromatography/combustion/isotope ratio mass spectrometry

RATIONALE: Organic nitrogen (N) greatly exceeds inorganic N in soils, but the complexity and heterogeneity of this important soil N pool make investigations into the fate of N‐containing additions and soil organic N cycling challenging. This paper details a novel approach to investigate the fate of applied N in soils, generating quantitative measures of microbial assimilation and of newly synthesized soil protein. METHODS: Laboratory incubation experiments applying (15)N‐ammonium, (15)N‐nitrate and (15)N‐glutamate were carried out and the high sensitivity and selectivity of gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) exploited for compound‐specific (15)N stable isotope probing ((15)N‐SIP) of extracted incubation soil amino acids (AAs; as N‐acetyl, O‐isopropyl derivatives). We then describe the interpretation of these data to obtain a measure of the assimilation of the applied (15)N‐labelled substrate by the soil microbial biomass and an estimate of newly synthesised soil protein. RESULTS: The cycling of agriculturally relevant N additions is undetectable via bulk soil N content and δ (15)N values and AA concentrations. The assimilation pathways of the three substrates were revealed via patterns in AA δ (15)N values with time, reflecting known biosynthetic pathways (e.g. ammonium uptake occurs first via glutamate) and these data were used to expose differences in the rates and fluxes of the applied N substrates into the soil protein pool (glutamate > ammonium > nitrate). CONCLUSIONS: Our compound‐specific (15)N‐SIP approach using GC/C/IRMS offers a number of insights, inaccessible via existing techniques, into the fate of applied (15)N in soils and is potentially widely applicable to the study of N cycling in any soil, or indeed, in any complex ecosystem. © 2016 The Authors. Rapid Communications in Mass Spectrometry Published by John Wiley & Sons Ltd

Runoff- and erosion-driven transport of cattle slurry:linking molecular tracers to hydrological processes

The addition of cattle slurry to agricultural land is a widespread practise, but if not correctly managed it can pose a contamination risk to aquatic ecosystems. The transport of inorganic and organic components of cattle slurry to watercourses is a major concern, yet little is known about the physical transport mechanisms and associated fluxes and timings of contamination threats. Therefore, the aim of the study was to ascertain the importance of flow pathway partitioning in the transport (fluxes and timing) of dissolved and particulate slurry-derived compounds with implications for off-site contamination. A series of rainfall–runoff and erosion experiments were carried out using the TRACE (Test Rig for Advancing Connectivity Experiments) experimental hillslope facility. The experiments allowed the quantification of the impact of changing slope gradient and rainfall intensity on nutrient transport from cattle slurry applied to the hillslope, via surface, subsurface, and vertical percolated flow pathways, as well as particulate transport from erosion. The dissolved components were traced using a combination of ammonium (NH₄⁺) and fluorescence analysis, while the particulate fraction was traced using organic biomarkers, 5<i>β</i>-stanols. Results showed that rainfall events which produced flashy hydrological responses, resulting in large quantities of surface runoff, were likely to move sediment and also flush dissolved components of slurry-derived material from the slope, increasing the contamination risk. Rainfall events which produced slower hydrological responses were dominated by vertical percolated flows removing less sediment-associated material, but produced leachate which could contaminate deeper soil layers, and potentially groundwater, over a more prolonged period. Overall, this research provides new insights into the partitioning of slurry-derived material when applied to an unvegetated slope and the transport mechanisms by which contamination risks are created

DRYP 1.0: a parsimonious hydrological model of DRYland Partitioning of the water balance

Dryland regions are characterized by water scarcity and are facing major challenges under climate change. One difficulty is anticipating how rainfall will be partitioned into evaporative losses, groundwater, soil moisture and runoff (the water balance) in the future, which has important implications for water resources and dryland ecosystems. However, in order to effectively estimate the water balance, hydrological models in drylands need to capture the key processes at the appropriate spatiotemporal scales including spatially restricted and temporally brief rainfall, high evaporation rates, transmission losses and focused groundwater recharge. Lack of available data and the high computational costs of explicit representation of ephemeral surface-groundwater interactions restrict the usefulness of most hydrological models in these environments. Therefore, here we have developed a parsimonious hydrological model (DRYP) that incorporates the key processes of water partitioning in dryland regions, and we tested it in the data-rich Walnut Gulch Experimental Watershed against measurements of streamflow, soil moisture and evapotranspiration. Overall, DRYP showed skill in quantifying the main components of the dryland water balance including monthly observations of streamflow (Nash efficiency (NSE) ~0.7), evapotranspiration (NSE > 0.6) and soil moisture (NSE ~0.7). The model showed that evapotranspiration consumes > 90 % of the total precipitation input to the catchment, and that < 1 % leaves the catchment as streamflow. Greater than 90 % of the overland flow generated in the catchment is lost through ephemeral channels as transmission losses. However, only ~35 % of the total transmission losses percolate to the groundwater aquifer as focused groundwater recharge, whereas the rest is lost to the atmosphere as riparian evapotranspiration. Overall, DRYP is a modular, versatile and parsimonious Python-based model which can be used to anticipate and plan for climatic and anthropogenic changes to water fluxes and storage in dryland region

Sensitivity of rainfall extremes to unprecedented Indian Ocean Dipole events

Strong positive Indian Ocean Dipole (pIOD) events like those in 1997 and 2019 caused significant flooding in East Africa. While future projections indicate an increase in pIOD events, limited historical data hinders a comprehensive understanding of these extremes, particularly for unprecedented events. To overcome this we utilize a large ensemble of seasonal reforecast simulations, which show that regional rainfall continues to increase with pIOD magnitude, with no apparent limit. In particular we find that extreme rain days are highly sensitive to the pIOD index and their seasonal frequency increases super‐linearly with higher pIOD magnitudes. It is vital that socio‐economic systems and infrastructure are able to handle not only the increasing frequency of events like 1997 and 2019 but also unprecedented seasons of extreme rainfall driven by as‐yet‐unseen pIOD events. Future studies should prioritize understanding the hydrological implications and population exposure to these unprecedented extremes in East Africa

Sustained water storage in Horn of Africa drylands dominated by seasonal rainfall extremes

Rural communities in the Horn of Africa Drylands (HAD) are increasingly vulnerable to multi-season droughts due to the strong dependence of livelihoods on seasonal rainfall. We analysed multiple observational rainfall datasets for recent decadal trends in mean and extreme seasonal rainfall, as well as satellite-derived terrestrial water storage and soil moisture trends arising from two key rainfall seasons across various subregions of HAD. We show that, despite decreases in total March-April-May rainfall, total water storage in the HAD has increased. This trend correlates strongly with seasonal totals and especially with extreme rainfall in the two dominant HAD rainy seasons between 2003 and 2016. We further show that high-intensity October-November-December rainfall associated with positive Indian Ocean Dipole events lead to the largest seasonal increases in water storage that persist over multiple years. These findings suggest that developing groundwater resources in HAD could offset or mitigate the impacts of increasingly common droughts

Exploring exogenous controls on short- versus long-term erosion rates globally

Erosion is directly tied to landscape evolution through the relationship between sediment flux and vertical lowering of the land surface. Therefore, the analysis of erosion rates across the planet measured over different temporal domains may provide perspectives on the drivers and processes of land surface change over various timescales. Different metrics are commonly used to quantify erosion (or denudation) over timescales of <101 years (suspended sediment flux) and 103–106 years (cosmogenic radionuclides), meaning that reconciling potentially contrasting rates at these timescales at any location is challenging. Studies over the last several decades into erosion rates and their controls have yielded valuable insights into geomorphic processes and landforms over time and space, but many are focused at local or regional scales. Gaps remain in understanding large-scale patterns and exogenous drivers (climatic, anthropogenic, tectonic) of erosion across the globe. Here we leverage the expanding availability and coverage of cosmogenic-derived erosion data and historical archives of suspended sediment yield to explore these controls more broadly and place them in the context of classical geomorphic theory. We make the following findings in this paper: (1) there are relationships between both long- and short-term erosion rates and mean annual precipitation, as well as aridity, similar to that proposed in classic geomorphic literature on erosion; (2) agricultural activities have apparently increased short-term erosion rates, outpacing natural drivers; (3) short-term erosion rates exceed long-term rates in all climatic regions except in mid- and high latitudes, where long-terms rates are higher due to the influence of repeated glacial cycles; and (4) tectonically active margins have generally higher long-term erosion rates and apparently lower rainfall thresholds for erosion which potentially arise due to steeper slopes and associated landslides, overcoming vegetative root reinforcement. These results highlight the complex interplay of external controls on land surface processes and reinforce the view that timescale of observation may reveal different erosion rates and principal controls