Hydroclimatic Processes Research Articles

Recent progress in atmospheric modeling over the Andes – part I: review of atmospheric processes

The Andes is the longest mountain range in the world, stretching from tropical South America to austral Patagonia (12°N-55°S). Along with the climate differences associated with latitude, the Andean region also features contrasting slopes and elevations, reaching altitudes of more than 4,000 m. a.s.l., in a relatively narrow crosswise section, and hosts diverse ecosystems and human settlements. This complex landscape poses a great challenge to weather and climate simulations. The interaction of the topography with the large-scale atmospheric motions controls meteorological phenomena at scales of a few kilometers, often inadequately represented in global (grid spacing ∼200–50 km) and regional (∼50–25 km) climate simulations previously studied for the Andes. These simulations typically exhibit large biases in precipitation, wind and near-surface temperature over the Andes, and they are not suited to represent strong gradients associated with the regional processes. In recent years (∼2010–2024), a number of modeling studies, including convection permitting simulations, have contributed to our understanding of the characteristics and distribution of a variety of systems and processes along the Andes, including orographic precipitation, precipitation hotspots, mountain circulations, gravity waves, among others. This is Part I of a two-part review about atmospheric modeling over the Andes. In Part I we review the current strengths and limitations of numerical modeling in simulating key atmospheric-orographic processes for the weather and climate of the Andean region, including low-level jets, downslope winds, gravity waves, and orographic precipitation, among others. In Part II, we review how climate models simulate surface-atmosphere interactions and hydroclimate processes in the Andes Cordillera to offer information on projections for land-cover/land-use change or climate change. With a focus on the hydroclimate, we also address some of the main challenges in numerical modeling for the region.

Recent progress in atmospheric modeling over the Andes – part II: projected changes and modeling challenges

In the Andes, the complex topography and unique latitudinal extension of the cordillera are responsible for a wide diversity of climate gradients and contrasts. Part I of this series reviews the current modeling efforts in simulating key atmospheric-orographic processes for the weather and climate of the Andean region. Building on this foundation, Part II focuses on global and regional climate models challenging task of correctly simulating changes in surface-atmosphere interactions and hydroclimate processes to provide reliable future projections of hydroclimatic trajectories in the Andes Cordillera. We provide a review of recent advances in atmospheric modeling to identify and produce reliable hydroclimate information in the Andes. In particular, we summarize the most recent modeling research on projected changes by the end of the 21st century in terms of temperature and precipitation over the Andes, the mountain elevation-dependent warming signal, and land cover changes. Recent improvements made in atmospheric kilometer-scale model configurations (e.g., resolution, parameterizations and surface forcing data) are briefly reviewed, highlighting their impact on modeling results in the Andes for precipitation, atmospheric and surface-atmosphere interaction processes, as mentioned in recent studies. Finally, we discuss the challenges and perspectives of climate modeling, with a focus on the hydroclimate of the Andes.

Global latitudinal patterns in forest ecosystem nitrous oxide emissions are related to hydroclimate

Nitrous oxide (N2O) emissions are a serious global issue, with substantial evidence indicating that hydroclimate processes significantly contribute to these emissions. Forests, covering one-third of global land, are key in the water cycle and influence hydroclimate processes, which vary with climate, latitude, and forest types. The role of hydroclimate in regulating global forest N2O emission remains largely unknown. Our global analysis shows that hydroclimate factors dominate the latitudinal gradient of forest N2O fluxes, which decrease with latitude. N2O fluxes are highest in tropical forests, followed by temperate and boreal forests. Hydroclimate factors contribute 78.2% to N2O fluxes, while soil factors contribute 21.8%. Our results urgently call for future studies to investigate the relationship between N2O flux and hydroclimate factors like radiation, evapotranspiration, and vapor pressure deficits. Collectively, these findings highlight hydroclimate significant impact on N2O emissions and suggest incorporating these factors into predictive models for greater accuracy.

Intra-annual variations in isotopic composition of atmospheric water vapour in a semi-arid monsoon region: observations and inferences

The isotopic composition of atmospheric water vapour dynamically changes due to the complex interplay between the moisture-contributing sources (precipitation, evaporating soil moisture, transpiration, evaporating water bodies, etc.), operating ecohydrological processes, and the climatic conditions. In the present study, the isotopic composition of different sources of water was sampled; air moisture (n = 47) twice a month for the period December, 2021 to January, 2023; transpiration samples (n = 76); evaporation and rain samples (n = 12 each). The samples were analyzed using the mass spectrometry to investigate the dynamic nature of the isotopic composition of the atmospheric vapour and the factors influencing it. The research findings showed that the isotopic composition of atmospheric moisture rapidly depleted after the onset of the monsoon, indicating the replacement of pre-monsoon local vapour by monsoon moisture of depleted isotopic composition. The process of evaporation from the soil surface during the post-monsoon period was found to progress parallel to other soil hydrological processes, such as capillary action and diffusion-driven downward flux of enriched water molecules. This resulted in the broadening of an isotopically enriched layer of soil moisture in the vadose zone with time, and accordingly, there was transpiration of this enriched soil moisture from the deeper layers of soils with time by plants/trees. Evaporation of soil water and the transpiration of plants and trees of enriched water vapour gradually altered the isotopic composition of the atmospheric water vapour composition from the depleted isotopic composition of the monsoon period to an enriched isotopic composition. The transpiration of enriched water vapour from deep-rooted trees indicated more prolonged arid climate conditions. The findings of the study are useful in understanding the regional hydrological and hydroclimatic processes which can be implemented in agro-climatic studies and water resource management.

Scientific logic and spatio-temporal dependence in analyzing extreme-precipitation frequency: negligible or neglected?

Abstract. Statistics is often misused in hydro-climatology, thus causing research to get stuck on unscientific concepts that hinder scientific advances. In particular, neglecting the scientific rationale of statistical inference results in logical and operational fallacies that prevent the discernment of facts, assumptions, and models, thus leading to systematic misinterpretations of the output of data analysis. This study discusses how epistemological principles are not just philosophical concepts but also have very practical effects. To this aim, we focus on the iterated underestimation and misinterpretation of the role of spatio-temporal dependence in statistical analysis of hydro-climatic processes by analyzing the occurrence process of extreme precipitation (P) derived from 100-year daily time series recorded at 1106 worldwide gauges of the Global Historical Climatology Network. The analysis contrasts a model-based approach that is compliant with the well-devised but often neglected logic of statistical inference and a widespread but theoretically problematic test-based approach relying on statistical hypothesis tests applied to unrepeatable hydro-climatic records. The model-based approach highlights the actual impact of spatio-temporal dependence and a finite sample size on statistical inference, resulting in over-dispersed marginal distributions and biased estimates of dependence properties, such as autocorrelation and power spectrum density. These issues also affect the outcome and interpretation of statistical tests for trend detection. Overall, the model-based approach results in a theoretically coherent modeling framework where stationary stochastic processes incorporating the empirical spatio-temporal correlation and its effects provide a faithful description of the occurrence process of extreme P at various spatio-temporal scales. On the other hand, the test-based approach leads to theoretically unsubstantiated results and interpretations, along with logically contradictory conclusions such as the simultaneous equi-dispersion and over-dispersion of extreme P. Therefore, accounting for the effect of dependence in the analysis of the frequency of extreme P has a huge impact that cannot be ignored, and, more importantly, any data analysis can be scientifically meaningful only if it considers the epistemological principles of statistical inference such as the asymmetry between confirmatory and disconfirmatory empiricism, the inverse-probability problem affecting statistical tests, and the difference between assumptions and models.

PyCoSMoS: An advanced toolbox for simulating real-world hydroclimatic data

Simulation models are a fundamental tool for investigating hydrological processes and for water resource management. In this study, we introduce PyCoSMoS, a Python toolbox that enables researchers to simulate observed univariate time series mimicking hydroclimatic processes. This toolbox preserves arbitrary marginal distribution and autocorrelation functions, while significantly reducing computational burden. PyCoSMoS is built upon the mixed-Uniform CoSMoS method recently proposed by Papalexiou et al. (2023). The toolbox is designed to minimize the user’s input, requiring only observed time series, marginal distribution, correlation function, and the number of lags. The output provides both visual and quantitative comparisons between the observed and simulated time series. We evaluate the performance of the package using various synthetic case studies and the results demonstrate satisfactory accuracy. Furthermore, we apply the toolbox to three real case studies: precipitation, temperature, and relative humidity, for which the toolbox can successfully simulate the observed time series in each case.

Spatial variability in stable isotopes from Lesotho surface waters: insights into regional moisture transport

Precipitation in Lesotho is highly spatially variable, a feature of the high altitude and rugged topography. The hydroclimate dynamics, despite being critical to the water security of Lesotho and adjacent South Africa, are poorly understood. Ratios of oxygen and hydrogen isotopes in meteoric water are excellent tracers of hydroclimatic processes. This study presents the first analysis of stable isotopes from surface waters in Lesotho, and an investigation into the moisture sources. Our results demonstrate considerable variability in isotope values. There are statistically significant relationships between both oxygen and hydrogen isotopes and the altitude of the site and source of rivers sampled, and with hydrogen isotopes and longitude. The meteoric water line for the Lesotho samples is most closely aligned with that of the Global Network of Isotopes in Precipitation (GNIP) station at Harare, in Zimbabwe. The meteoric water line for Windhoek is more closely aligned to the Lesotho samples than the more proximate Cape Town or Pretoria meteoric water lines, which would more closely represent the South African winter- and summer-rainfall zones respectively. HYSPLIT back-trajectory air parcel analysis supports these findings, demonstrating a frequent continental anticyclonic track through southern Zimbabwe. Deuterium excess values vary widely, although are most likely related to processes during moisture transport rather than differences in moisture source. These findings are of particular importance in the context of the future water security of both Lesotho and South Africa, especially as the poleward displacement of the westerly moisture corridor has raised concerns for winter precipitation in the region.

Holocene stratigraphic architecture of a Mediterranean delta and implication for sediment budget evolution: Example of the Rhône delta

Deltaic systems evolve as a result of interactions between the hydroclimatic processes that occur in the catchment area and the coastal marine processes that reshape the coastline. The Holocene evolution of these environments is controlled by climate and anthropization, which are rarely considered in models of the evolution of deltaic systems. The Rhône delta has recorded the impact of climatic variations as well as the development and evolution of human societies over the Holocene period. This system underwent a post-glacial evolution controlled by global climatic warming punctuated by short periods of cooling, fluvial metamorphoses and a rapid marine transgression generated by the melting of the ice caps, followed by the initiation of delta progradation from around 7000 cal yr BP. Sedimentological and chronostratigraphic studies of 17 cores, supplementing an existing dataset on the deltaic plain and the prodelta, have enabled us to construct well-constrained stratigraphic correlations, making it possible to specify the spatio-temporal evolution of the Rhône delta. The variation in sedimentary fluxes was assessed for the different sequences identified, using 95 new core datings to constrain the sequential evolution of the different lobes. From the stratigraphic correlations on the delta and the estimated volumes of sediments exported out of the deltaic system, the total sediment volume between 11,700 cal yr BP and today is estimated at 126 billion m3. The variation of sediment fluxes has been adjusted according to the different phases of lobe progradation linked with the climate oscillations and the anthropic activity evolution during the Holocene. Taken together, these data highlight contrasting periods corresponding to the Roman period, the Little Ice Age and finally the ‘Anthropocene’, that can be compared to the main Mediterranean deltaic systems during the Holocene.

Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments

Abstract. It has been well established that during the late Quaternary, the Khvalynian transgression of the Caspian Sea occurred, when the sea level rose tens of meters above the present level. Here, we evaluate the physical feasibility of the hypothesis that the maximum phase of this extraordinary event (known as the “Early Khvalynian transgression”) could be initiated and maintained for several thousand years solely by hydroclimatic factors. The hypothesis is based on recent studies dating the highest sea level stage (well above +10 m a.s.l.) to the final period of deglaciation, 17–13 kyr BP, and studies estimating the contribution of the glacial waters in the sea level rise for this period as negligible. To evaluate the hypothesis put forward, we first applied the coupled ocean and sea-ice general circulation model driven by the climate model and estimated the equilibrium water inflow (irrespective of its origin) sufficient to maintain the sea level at the well-dated marks of the Early Khvalynian transgression as 400–470 km3 yr−1. Secondly, we conducted an extensive radiocarbon dating of the large paleochannels (signs of high flow of atmospheric origin) located in the Volga basin and found that the period of their origin (17.5–14 ka BP) is almost identical to the recent dating of the main phase of the Early Khvalynian transgression. Water flow that could form these paleochannels was earlier estimated for the ancient Volga River as 420 km3 yr−1, i.e., close to the equilibrium runoff we determined. Thirdly, we applied a hydrological model forced by paleoclimate data to reveal physically consistent mechanisms of an extraordinarily high water inflow into the Caspian Sea in the absence of a visible glacial meltwater effect. We found that the inflow could be caused by the spread of post-glacial permafrost in the Volga paleocatchment. The numerical experiments demonstrated that the permafrost resulted in a sharp drop in infiltration into the frozen ground and reduced evaporation, which all together generated the Volga runoff during the Oldest Dryas, 17–14.8 kyr BP, up to 360 km3 yr−1 (i.e., the total inflow into the Caspian Sea could reach 450 km3 yr−1). The closeness of the estimates of river inflow into the sea, obtained by three independent methods, in combination with the previously obtained results, gave us reason to conclude that the hypothesis put forward is physically consistent.

Variations in triple oxygen isotope of speleothems from the Asian monsoon region reveal moisture sources over the past 300 years

Characterization of moisture origins is crucial to understanding hydroclimatic processes. Nevertheless, documenting past atmospheric moisture contents and their sources remains challenging partially due to insufficient moisture-tracing proxies. Here, we present triple oxygen isotope compositions in 21 cave speleothems from monsoonal Asia to examine spatial moisture origin differences in eastern Asia over the past 300 years. Our data suggest an isotopic equilibrium fractionation during speleothem formation, and thus parent water 17O anomalies (Δ′17O) values reconstructed from speleothems preserve information on moisture origins and recycling across space. Notably, speleothem Δ′17O records exhibit a distinct geographical distribution, with low values in central-eastern and southern China, high values in northwestern and northern China, and relatively high values in the Yangtze River region. This spatial pattern underscores the diverse influence of different moisture sources regulated by regional hydrological circulation, and demonstrates the potential use of speleothem Δ′17O in reconstructing the moisture cycle at spatial scales.

Optimization-Based Prediction Uncertainty Qualification of Climatic Parameters

Abstract Point predictions of hydroclimatic processes through nonlinear modeling tools are associated with uncertainty. The main goal of this research was to construct prediction intervals (PIs) for nonlinear artificial neural network (ANN)-based models of evaporation and the standardized precipitation index (SPI). These are two critical indicators for climate for four stations in Iran (i.e., Tabriz, Urmia, Ardabil, and Ahvaz) to qualify their predicted uncertainty values (UVs). We used classical techniques of bootstrap (BS), mean variance estimation (MVE), and Delta, as well as an optimization-based method of lower upper bound estimation (LUBE), to construct and compare the PIs. The wavelet-based denoising method was also adopted to denoise input data, enhancing the modeling performance. The obtained results indicate the ability of the BS and LUBE methods to estimate the uncertainty bound. The Delta method mostly failed to find the desired coverage due to its narrow PIs. On the other hand, the MVE method, due to its wide bound, did not convey valuable information about uncertainty. According to the obtained results, denoising the input vector could enhance the PI quality in the modeling of the SPI by up to 76%. It was more prominent than reducing the UV for evaporation models, which was observed the most at the Ardabil station, up to 30%. The inherently more random nature of drought than the evaporation process was interpreted as the cause of this reaction. From the results, Urmia station seems the riskiest regarding drought ventures. Significance Statement The point predictions of evaporation and precipitation (in the form of SPI) are subject to uncertainty. The best way is to provide an area with the highest contingency as a prediction interval. The reduction in the width of such an interval leads to increased confidence in explaining and predicting these processes. We investigated different methods and found that by utilizing the optimization-based method for denoised inputs, uncertainty values of the output were conveyed better. Additionally, we concluded that the more random the process, the greater its uncertainty. A primary sense of the drought risk was made from the uncertainty perspective.

Spatial assessment of nighttime anthropization in the Comoé National Park in Côte d’Ivoira (West Africa)

Abstract Protected areas play a crucial role in preserving biological diversity, providing ecosystem services, and regulating hydroclimatic processes. However, the environmental balance of these areas is increasingly under threat due to rapid population growth, high demand for natural resources, and the effects of global warming. To address this, sustainable management of protected areas is essential. This study aims to develop a methodology for monitoring and assessing levels of nocturnal anthropogenic aggression in the Comoé National Park (CNP) in Côte d’Ivoire. By using geospatial data from the Day/Night Band of the Visible Infrared Imaging Radiometer Suite (VIIRS/DNB), the study characterizes the nocturnal anthropization of CNP through the use of several indices. First, light reflectance density is used to identify nighttime light emission foci. Second, the lighted area density index (LADI) is employed to understand the nature of nocturnal activities taking place within CNP, as indicated by artificial light at night (ALAN). Finally, the light intensity index (LII) is used to evaluate the degree of influence of nocturnal anthropogenic activities on biodiversity. The study also found important activities through LADI and observed a high level of light pollution in CNP. Ultimately, the findings of this study indicate that there is a significant level of nocturnal anthropization within CNP, highlighting the need for effective management and conservation efforts in the area.

Multimodal multiscale characterization of cascading hazard on mountain terrain

Extreme precipitation (rain or/and snow) in upstream areas of the Himalayan region often triggers water and sediment hazards, including flash floods, landslides, debris flow, and river damming. These hazards often interact with the environmental and human systems, resulting in acute and chronic disasters that deleteriously impact the economy, infrastructure, and livelihoods. As cascading and compound hazards become more common in the Himalayan region, a more holistic approach is needed to understand the complex interaction among human, natural, and engineered systems and tackle problems connected to several system constraints. Recent catastrophes like the 2021 Melamchi disaster cannot be attributed to a single cause; rather, they result from several geomorphologic and hydroclimatic factors and physical processes. Individual and interacting dynamics and their cascading and compounding effects occurred in various settings, from high elevations to river valleys along the Melamchi River. This study diagnoses the likely causal effects of hydroclimatic processes of the 2021 Melamchi disaster by integrating space-borne remotely sensed data, hydrologic and hydrodynamic modeling, and machine learning techniques. We have evaluated several scenarios of landslide damming and breaching and analyzed flooding impacts on major settlements across the Melamchi River. Model outputs evaluated using satellite flood imagery, field-based surveys, and published reports were used to understand the characteristics of the 2021 Melamchi disaster. We find that earlier rain episodes had saturated the soil and increased the river’s water level. Therefore, after the outburst of the landslide dam coupled with heavy downpours, a sudden release of huge water had enormous energy to inundate vast areas of flood plains and damaged settlements near riverbanks far downstream up to the Melamchi Bazar. It was not just one extreme event that led to the devastation but a series of non-extreme events. This further reinforces the idea that not just extreme events, but several not-extreme series of events may lead to disaster. Thus, the chances of such a sequence of cascading events must be investigated for risk computation along with extreme events.

Large‐Domain Multisite Precipitation Generation: Operational Blueprint and Demonstration for 1,000 Sites

AbstractStochastic simulations of spatiotemporal patterns of hydroclimatic processes, such as precipitation, are needed to build alternative but equally plausible inputs for water‐related design and management, and to estimate uncertainty and assess risks. However, while existing stochastic simulation methods are mature enough to deal with relatively small domains and coarse spatiotemporal scales, additional work is required to develop simulation tools for large‐domain analyses, which are more and more common in an increasingly interconnected world. This study proposes a methodological advancement in the CoSMoS framework, which is a flexible simulation framework preserving arbitrary marginal distributions and correlations, to dramatically decrease the computational burden and make the algorithm fast enough to perform large‐domain simulations in short time. The proposed approach focuses on correlated processes with mixed (zero‐inflated) Uniform marginal distributions. These correlated processes act as intermediates between the target process to simulate (precipitation) and parent Gaussian processes that are the core of the simulation algorithm. Working in the mixed‐Uniform space enables a substantial simplification of the so‐called correlation transformation functions, which represent a computational bottle neck in the original CoSMoS formulation. As a proof of concept, we simulate 40 years of daily precipitation records from 1,000 gauging stations in the Mississippi River basin. Moreover, we extend CoSMoS incorporating parent non‐Gaussian processes with different degrees of tail dependence and suggest potential improvements including the separate simulation of occurrence and intensity processes, and the use of advection, anisotropy, and nonstationary spatiotemporal correlation functions.

The dry and hot American Southwest under the present and future climates

The American Southwest is undergoing alarming climate crises, suffering from the on-going mega drought, frequent flash flooding, heat waves, and wildfires that cause air pollution. The climate crises are mainly associated with hydroclimatic processes and particularly water fluxes across the different components of the climate system. This study serves to discuss where the author stand in terms of scientific understanding of hydroclimatic systems in this region and their physical drivers (e.g., the North American Summer monsoon and Pacific North American teleconnections). This work highlights the relative contributions of precipitation and temperature to droughts through the lens of theories and modeling tools. More importantly, it is crucial to characterize the relative roles of internal variability and external forcing in shaping the hydroclimatic system in the southwestern United States. Future pathways are also described including high-resolution global modeling system, advancing understanding relative roles of precipitation and temperature in modulating hydroclimate system, further understanding the role of external forcing, as well as the partnership between scientists and other stakeholders.摘要由于正在持续的特⼤⼲旱, 更频繁的洪⽔, 热浪以及导致空⽓污染的⼭⽕, 美国西南部⽬前正在 经历⽓候危机. 这些⽓候危机主要与⽔⽂⽓候过程相关, 尤其是⽓候系统各圈层之间的⽔汽通量. 本研究主要讨论⽬前⼀些⽔⽂系统的科学基站以及物理驱动因素, ⽐如北美夏季风以及太平洋北美遥相关. 本研究指出降⽔以及⽓温对于⼲旱的相对作⽤的理论和⼯具. 确定内部变率和外部强迫对于美国西南部⽔⽂⽓候系统的相对作⽤尤为重要. 展望未来, 需要研究⾼分辨率模拟系统, 加强降⽔以及温度对于⽔⽂⽓候系统相对作⽤的理解, 外部强迫的作⽤以及通过科学家以及 其他利益相关者之间的合作.

Water Availability and Land Management Control Catchment‐Scale Agricultural Nitrogen and Phosphorous Use Efficiencies

AbstractIn arable systems, large amounts of nutrients, particularly of nitrogen (N) and phosphorus (P), are not efficiently converted into harvestable products and are lost from agricultural systems, with negative consequences for agricultural productivity and the environment. These nutrient losses are mediated by hydroclimatic processes causing nutrient leaching and volatilization. We quantify over the period 1987–2012 how water availability through the evaporative ratio (actual evapotranspiration divided by precipitation) and irrigation, agricultural practices, and edaphic conditions jointly affect nutrient use efficiencies in 110 agricultural catchments in the United States. We consider N and P use efficiencies (nitrogen use efficiency [NUE] and phosphorous use efficiency [PUE]) defined as ratios of catchment‐scale N and P in harvested products over their respective inputs, as well as the NUE/PUE ratio, as an indication of catchment‐scale N and P imbalance. Both efficiencies increase through time because of changes in climate and agronomic practices. Setting all else at the median value of the data set, NUE and PUE increased with evaporative ratio by 0.5% and 0.2% when increasing the evaporative ratio by 20% and by 4.9% and 18.8% in the presence of irrigation. NUE was also higher in catchments where maize and soybean were dominant (increasing by 2.3% for a 20% increase in maize and soybean fractional area). Soil properties, represented by mineral soil texture and organic matter content, had only small effects on the efficiencies. Our results show that both climatic conditions and crop choice are important drivers of nutrient use efficiencies in agricultural catchments.

Future Changes in Global Runoff and Runoff Coefficient From CMIP6 Multi‐Model Simulation Under SSP1‐2.6 and SSP5‐8.5 Scenarios

AbstractThis paper assesses the performances of runoff (Ro) and runoff coefficient (α, the ratio of runoff to precipitation) simulations from 23 models during the historical period and then projects their future changes under the two emission scenarios (SSP1‐2.6 and SSP5‐8.5) in the Coupled Model Intercomparison Project. Compared with the UNH/GRDC Ro dataset (0.82 mm day−1), the multi‐model median (MME) Ro of 1995–2014 produces a comparable global mean magnitude (0.80 mm day−1), displays a similar spatial distribution of mean Ro, and also well captures the seasonal cycles at both global and basin scales. The global mean Ro of MME is projected to be increased by 0.01–0.02 mm day−1 (SSP1‐2.6) and 0.02–0.10 mm day−1 (SSP5‐8.5) during the twenty‐first century. Regional hotspots for strong increasing Ro appear across most areas of northern high latitudes, Africa, and southeastern Asia, with high inter‐model consistency. The global mean α is projected to be slightly decreased (−0.17 to −0.63%) except for the long‐term under the SSP5‐8.5 (0.26%). Although signs of changes in Ro vary with the river basins, periods, and scenarios, α in more than half (7 out of 12) river basins are projected to decrease. The uneven distributions of projected Ro changes over global land areas are related to the response of multiple hydroclimatic variables to the global warming. Given regions with inconstancy change signs of the projected precipitation, we speculate that changes in Ro are affected by more complicated hydroclimatic processes that warrant further investigations with physical‐based approaches.

Timing and duration of ephemeral Antarctic water tracks and wetlands using high temporal–resolution satellite imagery, high spatial–resolution satellite imagery, and ground-based sensors in the McMurdo Dry Valleys

ABSTRACT Antarctic water tracks and ephemeral wetlands are a primary location for biogeochemical soil processes driving cold desert soil formation. Though the spatial extent of water tracks and wetted soils has been mapped in the McMurdo Dry Valleys (MDV) on the basis of mapping darkened pixels in high-resolution commercial satellite imagery, the timescale over which water tracks and wetlands form and the duration of these biogeochemically active environments remain unknown. Here, we determine the start date and end dates and the duration of wetted soils at ten sites located across the MDV using a combination of in situ soil sensors and two complementary remote imaging platforms (Planet and WorldView) to understand the hydroclimatic processes that drive water track and wetland formation. Our remote sensing employs a terrain correction workflow that removes the contribution of differential direct illumination and small-scale shadowing on pixel brightness, reducing false positives (soils identified as wetted when in fact they are shadowed or darkened as a consequence of high phase angle). Our findings extend the water track and wetland hydroperiod by over a month, showing darkening occurring from November to March, suggesting hydrological contributions from ground ice thaw, snowmelt, and salt deliquescence and soil brine growth.

Estimating the Statistical Significance of Cross–Correlations between Hydroclimatic Processes in the Presence of Long–Range Dependence

Hydroclimatic processes such as precipitation, temperature, wind speed and dew point are usually considered to be independent of each other. In this study, the cross–correlations between key hydrological-cycle processes are examined, initially by conducting statistical tests, then adding the impact of long-range dependence, which is shown to govern all these processes. Subsequently, an innovative stochastic test that can validate the significance of the cross–correlation among these processes is introduced based on Monte-Carlo simulations. The test works as follows: observations obtained from numerous global-scale timeseries were used for application to, and a comparison of, the traditional methods of validation of statistical significance, such as the t-test, after filtering the data based on length and quality, and then by estimating the cross–correlations on an annual-scale. The proposed method has two main benefits: it negates the need of the pre-whitening data series which could disrupt the stochastic properties of hydroclimatic processes, and indicates tighter limits for upper and lower boundaries of statistical significance when analyzing cross–correlations of processes that exhibit long-range dependence, compared to classical statistical tests. The results of this analysis highlight the need to acquire cross–correlations between processes, which may be significant in the case of long-range dependence behavior.

Understanding the patterns and processes underlying water quality and pollution risk in West-Africa River using self-organizing maps and multivariate analyses.

Rivers are dynamic systems in complex interactions with their surrounding environments. Reliable and fast interpretation of water quality is therefore needed for sustainable river management. Unfortunately, water quality and environmental status interactions have not yet been documented sufficiently in West-Africa. This study explored the spatial-latitudinal and seasonal features of water quality along the Sô River Basin (SRB, West Africa) using self-organizing map (SOM) and principal component analysis. Twenty-two water quality variables were measured in the surface layer at 12 different sampling sites during a twenty-four-month period from July 2016 to June 2018. The results revealed three water quality groups, following an upstream-downstream pollution gradient: (1) upstream and middle reach sites with high dissolved oxygen and Secchi disk depth values, which are more suitable for the aquatic biota; (2) downstream sites with high concentrations of ammonium, biochemical oxygen demand, and heavy metals especially in flood period, reflecting both high organic and heavy metal pollution; and (3) brackish downstream sites characterized by less heavy metal and organic pollutions. No significant variation was observed between seasons. However, the SRB relatively suffered from higher risks of heavy metal contamination and organic pollution in wet seasons. Although hydroclimatic processes affect the water quality, anthropogenic inputs of point and non-point sources were identified and discussed as a more prominent factor contributing to variation in the water quality condition. These results offer insights into the water quality dynamics in river-estuary system as well as potential pollution sources, crucial for defining sanitation, and management measures.