Runoff Patterns Research Articles

Detecting Annual and Seasonal Hydrological Change Using Marginal Distributions of Daily Flows

Changes in the hydrological regime are widely investigated using a variety of approaches. In this study, we assess changes in annual and seasonal flow characteristics based on a probabilistic representation of the seasonal runoff regime at the daily time scale. The probabilistic seasonal runoff pattern is constructed by determining quantiles from marginal distributions of daily flows for each day within the year. By applying Fourier transformation on the statistics of the daily flow partial series, we obtain smooth periodical functions of distribution parameters over the year and consequently of the quantiles. The main findings are based on the comparison of the dry, average, and wet hydrologic condition zones as defined by the daily flow quantiles of selected probabilities. This analysis was conducted for ten catchments in Serbia by considering changes between two 30-year nonoverlapping periods, 1961–1990 and 1991–2020. It was found that the relative change in runoff volume is the most pronounced in the extreme dry condition zone in the winter season (−33% to 34%). The annual time shift is the largest in the dry and average condition zones, ranging from −11 to 12 days. The applied methodology is not only applicable to the detection of hydrologic change, but could also be used in operational hydrology and extreme flow studies via drought indices such as the Standardized Streamflow Index.

Monthly-scale hydro-climatic forecasting and climate change impact evaluation based on a novel DCNN-Transformer network

Climate change has emerged as one of the foremost global challenges confronting humanity today, leading to a heightened frequency and intensity of extreme weather phenomena, including droughts, floods, and erratic rainfall patterns. Accurately predicting changes in runoff patterns under future climate conditions holds significant importance for effective regional water resource planning and management. Recent research on runoff forecast has centered on optimizing hyperparameters of ELM, RNN, LSTM models using PSO, GWO, SSA, and other algorithms. Additionally, key features are extracted through input variable decomposition and preprocessing methods like EMD, EEMD, and VMD. However, these approaches have difficulties in extracting the long-term dependencies information of sequence units, parallel computing, and hyperparameter sensitivity. To address these shortcomings, this study proposes a novel end-to-end deep runoff prediction model based on deep convolutional neural network and Transformer (DCTN). The deep convolutional modules of DCTN employs the deep convolutional operation to extract local features of climate data while the Transformer of DCTN makes full use of self-attention to capture the long-term dependencies, which can achieve more accurate runoff predictions. Experiments on historical runoff forecasting at the Shanjiaodi hydrology station in the Dagu River Basin show that the proposed DCTN obtains a notable improvement of approximately 30.9% compared to traditional models. Based on the prediction results of three shared socioeconomic pathways, the potential impacts of climate change on runoff in Dagu River Basin were evaluated using the DCTN model. The results reveal that the likelihood of spring floods is substantially amplified in the mid-century and late-century, while the probability of extreme summer runoff diminishes. This study advances the understanding of runoff prediction and its implications under changing climate scenarios, paving the way for more informed decision-making and effective water resource management strategies.

Tree Rings as Proxies of Historical Runoff in a National Park in Northern Mexico: A Major Ecosystem Service Provider

A dendrochronological network of conifers (Pinus leiophylla, Pinus cembroides, Pinus engelmannii) was developed in the Cumbres de Majalca National Park (CMNP) in Chihuahua, Mexico, to reconstruct historical runoff patterns and examine the impact of ocean–atmosphere phenomena. The CMNP plays a vital role as a runoff source for Conchos River tributaries and groundwater recharge for Chihuahua City and nearby populations. The ring-width chronologies displayed a common signal from 1859 to 2021, with the highest association found between P. engelmannii and P. leiophylla (r = 0.65) and the lowest between P. cembroides and P. engelmannii (r = 0.55). The first principal component explained 75.7% of the variance, and among the species, P. leiophylla exhibited the highest correlation (0.624, p < 0.05) with the accumulated streamflow records from the previous November to July, allowing the construction of a bootstrapped model for runoff reconstruction. The reconstructed streamflow spanned from 1859 to 2014, with an average of 2.732 × 108 m3. Periods of low runoff occurred in 1860–1880, 1940–1960, and 1994–2014, while extreme wet years with high runoff occurred in 1865, 1884, and 1987. The interannual streamflow variability correlated significantly with ENSO indices (SOI, MEI, TRI, and sea surface temperature anomalies), particularly during the winter–spring seasons, indicating that warm phases of the ENSO increased precipitation and runoff. The analysis of return periods revealed probabilities for specific runoff volumes, enabling stakeholders to use the information to develop effective strategies for sustainable water allocation and utilization in the region.

Biocrusts intensify water redistribution and improve water availability to dryland vegetation: insights from a spatially-explicit ecohydrological model.

Biocrusts are ecosystem engineers in drylands and structure the landscape through their ecohydrological effects. They regulate soil infiltration and evaporation but also surface water redistribution, providing important resources for vascular vegetation. Spatially-explicit ecohydrological models are useful tools to explore such ecohydrological mechanisms, but biocrusts have rarely been included in them. We contribute to closing this gap and assess how biocrusts shape spatio-temporal water fluxes and availability in a dryland landscape and how landscape hydrology is affected by climate-change induced shifts in the biocrust community. We extended the spatially-explicit, process-based ecohydrological dryland model EcoHyD by a biocrust layer which modifies water in- and outputs from the soil and affects surface runoff. The model was parameterized for a dryland hillslope in South-East Spain using field and literature data. We assessed the effect of biocrusts on landscape-scale soil moisture distribution, plant-available water and the hydrological processes behind it. To quantify the biocrust effects, we ran the model with and without biocrusts for a wet and dry year. Finally, we compared the effect of incipient and well-developed cyanobacteria- and lichen biocrusts on surface hydrology to evaluate possible paths forward if biocrust communities change due to climate change. Our model reproduced the runoff source-sink patterns typical of the landscape. The spatial differentiation of soil moisture in deeper layers matched the observed distribution of vascular vegetation. Biocrusts in the model led to higher water availability overall and in vegetated areas of the landscape and that this positive effect in part also held for a dry year. Compared to bare soil and incipient biocrusts, well-developed biocrusts protected the soil from evaporation thus preserving soil moisture despite lower infiltration while at the same time redistributing water toward downhill vegetation. Biocrust cover is vital for water redistribution and plant-available water but potential changes of biocrust composition and cover can reduce their ability of being a water source and sustaining dryland vegetation. The process-based model used in this study is a promising tool to further quantify and assess long-term scenarios of climate change and how it affects ecohydrological feedbacks that shape and stabilize dryland landscapes.

Hydrological and Precipitation Extremes and Trends over the Paraiba do Sul River Basin, Brazil

The Paraiba do Sul River Basin (PSRB) is a vital source of water resources in Brazil, providing water for human consumption, industry, agriculture, and hydroelectric energy generation. As part of one of the most developed areas of the country, in the Southeast of Brazil, the region is vulnerable to the impacts of climate change, with evidence of extreme events such as droughts and floods affecting the availability and quality of water. Hence, this study analyzes precipitation and streamflow rates data from the PSRB between 1939–2020 to investigate the spatial variability of average patterns and extreme events, trends, and their relationship with urban growth and socioeconomic development. The analysis reveals significant spatial variations in precipitation and runoff rates, with higher altitude areas, such as the Serra da Mantiqueira, exhibiting higher average values. Moreover, the Mann–Kendall trend results showed in most of the sites no significant trend regarding precipitation data; however, about 50% of the sites in the PSRB presented a decreasing trend of runoff rates. Since the precipitation does not explain identified changes in the hydrological patterns, the evaluation of the area’s urban growth and socioeconomic development throughout the decades suggested that human activities, such as those associated with urbanization, have played a significant role in altering the runoff patterns in the basin. These findings highlight the importance of sustainable land-use planning and water resource-management practices in the PSRB to mitigate the negative impacts of urbanization on the hydrological cycle and to enhance the resilience of the region’s water resources.

Analyzing the contribution of gully erosion to land degradation in the upper Blue Nile basin, Ethiopia

Soil erosion has become a worldwide problem that threatens the environment and the future of economic and social development. The purpose of this study is to investigate the contribution of steep slopes and gullies to erosion in high precipitation tropical areas of the Ethiopian highlands. A trapezoidal weir was installed at the head and tail of the gully to monitor the discharge and sediment concentration from 2017 to 2020. Sediment yield and runoff are heavily influenced by the amount and timing of precipitation. The coefficients of variation for total sediment loads ranged from 65.1 to 96.1% at the head and 17.1–78.1% at the tail; the lowest coefficients were found in 2018 and the highest in 2020. Furthermore, 85% of the sediment at the tail comes from the gully, according to the four-year sediment budget. Further, a hysteretic analysis of suspended sediment concentration and runoff revealed that hilly sediment sources are limited (clockwise), then sediment can be transported through the gully via bank failures (counterclockwise). Study findings contributed to a classification of runoff patterns and an investigation of suspended sediment dynamics. In the gully tail, sediment yield was higher than in the head, suggesting gully sediment contributed more to sediment yield than large upland catchments. As a result of the study, we have been able to develop practical recommendations for managing gully erosion in the future.

Enhanced Hydrological Simulations in Paddy-Dominated Watersheds Using the Hourly SWAT-MODFLOW-PADDY Modeling Approach

Accurate hydrological simulations are crucial for managing water resources and promoting sustainable agriculture in submerged paddy agricultural watersheds. The SWAT-MODFLOW, which couples the Soil and Water Assessment Tool (SWAT) and the Modular Groundwater Flow (MODFLOW) model, is a widely used tool for hydrologic simulations that consider surface water and groundwater (SW-GW) interactions. However, it falls short of effectively simulating the hydrological processes of submerged rice paddy field areas. To address this, we developed the hourly SWAT-MODFLOW-PADDY model, which enables integrated surface and groundwater simulations and effectively represents the hydrological responses of submerged paddy fields to high-resolution rainfall data. Our findings demonstrated that the hourly SWAT-MODFLOW-PADDY model could dynamically simulate soil moisture and runoff patterns in submerged paddy fields. Notably, the developed model showed enhanced performance throughout the entire period for hourly flow in the watershed, with an average coefficient of determination (R2) of 0.75, Nash and Sutcliffe efficiency (NSE) of 0.76, and percent bias (PBIAS) of 13.22 compared to the original model (R2 = 0.62, NSE = 0.70, PBIAS = 48.21). The model’s performance in predicting water quality was improved, and it highlighted the significant impact of complex hydrological mechanisms within submerged paddy fields on the spatial distribution of groundwater recharge and stream water volumes exchanged through SW-GW interactions. Given these promising results, the SWAT-MODFLOW-PADDY model could be a valuable resource for managing submerged paddy-dominated agricultural watersheds across various climates and regions.

Changes in the hydrological and sediment regimes of two neighboring catchments in the past sixty years

Despite advances in watershed hydrology research, little is known about the hydrologic differences and similarities between neighboring catchments. Two neighboring catchments, the Nanliu River catchment (NLRC) and the Qinjiang River catchment (QJRC), were studied to see how they differed in annual precipitation, runoff, and sediment load in the last 60 years. Four hydrological signatures (river regime, periodicity, change trends, and precipitation-runoff-sediment correlations) estimated from a wide variety of catchment classification and corresponding indices, such as the runoff ratio (RQP) and baseflow index (BFI). The findings revealed that the two catchments shared similar general features, including similar runoff patterns (RQP= 0.45 and 0.43, and BFI = 2.83% and 2.12% in NLRC and QJRC respectively), minor differences in periodicities, and similar annual precipitation, runoff, and sediment load changes. The annual sediment load has been steadily decreasing due to human activity. The simple precipitation-runoff regression model developed in one catchment can be transferred to another. Nash–Sutcliffe efficiency (NSE) coefficients were 0.79 and 0.62, respectively. The runoff-sediment load regression model, on the other hand, showed poor performance (NSE of −0.34 and −0.99, respectively), despite capturing the main patterns with correlation coefficients of 0.82 (p < 0.001) and 0.74 (p < 0.001), respectively. These findings suggested that (1) annual runoff ratios are influenced more by climate (particularly precipitation) than by surface and subsurface characteristics of the earth. The rainfall-runoff model for the neighboring catchment can recreate runoff dynamics at yearly scales. Human activities, such as dam construction and sand mining, significantly impacted the annual sediment yield. (2) The two neighboring catchments had similar hydrologic ages because of similar climate, geology, tectonics, and human disturbance. These findings provided a solid evidence for predicting runoff and sediment in ungauged basins.

Attribution of runoff changes in the Danjiang River Basin in the Qinba Mountains, China

IntroductionThe Danjiang River Basin has experienced significant alterations to its runoff patterns in recent years, primarily as a result of climate change and anthropogenic activities.MethodsThis study aims to investigate these factors’ influence on the basin’s runoff between 1960 and 2016 using the Mann–Kendall (M-K) test and Accumulative Anomaly Curve (AAC) to assess the abrupt change characteristics of runoff. Furthermore, the study evaluates the effects of climate and anthropogenic factors on runoff evolution using eight independent Budyko hypotheses.ResultsThe findings indicate that annual precipitation in the basin remained stable (P &amp;gt; 0.1), while annual runoff decreases significantly to −4.08 mm/a (P &amp;lt; 0.05) and the annual potential evapotranspiration slightly decreases to −1.76 mm/a (P &amp;lt; 0.05). The study also reveales that the reduction of runoff is primarily attributable to anthropogenic activities, contributing between 133.66 and 147.50%, while climate change contributes between −33.66 and −47.50%.DiscussionThe increased vegetation cover in the basin is identified as the primary cause of the reduction in runoff production and increase in evapotranspiration. Additionally, the construction of hydraulic engineering facilities in the basin is found to have had some impact on reducing runoff. These findings have significant implications for water resource management and soil and water conservation in the Danjiang River Basin.

Application of an integrated catchment-lake model approach for simulating effects of climate change on lake inputs and biogeochemistry

Climate change is simultaneously affecting lakes and their catchments, resulting in altered runoff patterns in the catchment and modified mixing and biogeochemical dynamics in lakes. The effects of climate change in a catchment will eventually have an impact on the dynamics of a downstream water body as well. An integrated model would allow considering how changes in the watershed affect the lake, but coupled modelling studies are rare. In this study we integrate a catchment model (SWAT+) and a lake model (GOTM-WET) to obtain holistic predictions for Lake Erken, Sweden. Using five different global climate models, projections of climate, catchment loads and lake water quality for the mid and end of the 21st century have been obtained under two future scenarios (SSP 2-45 and SSP 5-85). Temperature, precipitation and evapotranspiration will increase in the future, overall resulting in an increase in water inflow to the lake. An increasing importance of surface runoff will also have consequences on the catchment soil, hydrologic flow paths, and the input of nutrients to the lake. In the lake, water temperatures will rise, leading to increased stratification and a drop in oxygen levels. Nitrate levels are predicted to remain unchanged, while phosphate and ammonium levels increase. A coupled catchment-lake configuration such as that illustrated here allows prediction of future biogeochemical conditions of a lake, including linking land use changes to changing lake conditions, as well as eutrophication and browning studies. Since climate affects both the lake and the catchment, simulations of climate change should ideally take into account both systems.

Research on the clogging law of floating particles on the rain grate of road surface

PurposeSince surface runoff clogs stormwater grates, leading to deterioration of drainage capacity, and also it is difficult to complete the study with actual dimensions in experiments, a numerical simulation work was established in this study to investigate the surface runoff clogging stormwater grate patterns. The purpose of this study is to describe the mechanisms of storm grate clogging and storm well deposition for different flow rate floods and granular materials.Design/methodology/approachIn the work of this study, the volume of fluid (VOF) method and the discrete element method (DEM) are used to solve the gas–liquid and particle flows. In order to solve the evolution of the gas–liquid interface during surface runoff, the VOF was used. To simulate the rain grate and set up different material particles to represent the surface floating materials, the DEM was utilized.FindingsThe research results show that the clogging distribution and clogging rate of the rainwater grate are closely related to the fluid flow velocity and the physical characteristics of the particles, and the higher the clogging rate of the rainwater grate and the higher the number of particles deposited in the rainwater well at the same surface runoff velocity, the higher the density of the clogged particles. The surface runoff velocity (0.5 m/s, 1 m/s) shows that the rapid change of particle movement state at high runoff velocity makes the particle clogging more obvious.Originality/valueA multi-scale CFD-DEM approach was used to simulate the particulate motion of the road surface with different incoming runoff velocities. The innovative use of DEM to model the storm grate simulation ensures the accuracy of the traction model.

Hydroclimate Drives Seasonal Riverine Export Across a Gradient of Glacierized High‐Latitude Coastal Catchments

AbstractGlacierized coastal catchments of the Gulf of Alaska (GoA) are undergoing rapid hydrologic fluctuations in response to climate change. These catchments deliver dissolved and suspended inorganic and organic matter to nearshore marine environments, however, these glacierized coastal catchments are relatively understudied and little is known about total solute and particulate fluxes to the ocean. We present hydrologic, physical, and geochemical data collected during April–October 2019–2021 from 10 streams along gradients of glacial fed to non‐glacial (i.e., precipitation) fed, in one Southcentral and one Southeast Alaska region. Hydrologic data reveal that glaciers drive the seasonal runoff patterns. The ẟ18O signature and specific conductance show distinctive seasonal variations in stream water sources between the study regions apparently due to the large amounts of rain in Southeast Alaska. Total dissolved solids concentrations and yields were elevated in the Southcentral region, due to lithologic influence on dissolved loads, however, the hydroclimate is the primary driver of the timing of dissolved and suspended yields. We show the yields of dissolved organic carbon is higher and that the δ13CPOC is enriched in the Southeast streams illustrating contrasts in organic carbon export across the GoA. Finally, we illustrate how future yields of solutes and sediments to the GoA may change as watersheds evolve from glacial influenced to precipitation dominated. This integrated analysis provides insights into how watershed characteristics beyond glacier coverage control properties of freshwater inputs to the GoA and the importance of expanding study regions to multiple hydroclimate regimes.

Reconstruction of Recharge and Discharge Pattern in the Polder Drainage Canal Network

Rainfed agriculture is dependent on rainfall and runoff patterns, especially in lowland areas that rely on pumping operation to remove excess water from the drainage network. Polder areas are extremely vulnerable to saltwater intrusion and subsequent soil salinization driven by rising sea levels and accelerated by climate change. The aim of this paper is to reconstruct the recharge and discharge pattern in the Vidrice polder, a drainage canal network within the Neretva River Delta agroecosystem used to collect the surface and subsurface runoff from the agricultural land and saltwater infiltration through the aquifer. Water regime data are collected over an 18-month period of real-time monitoring at 15 min intervals on three stations along the primary drainage canal and one station at the secondary canal. Analysis of water level flashiness in the Vidrice polder using the Richards-Baker flashiness index (R-Bindex) indicates that daily pumping of water infiltrated in the canal network is sub-optimal: discharge fluctuates significantly more than recharge, by 46% on average, resulting in unnecessary lowering of the water level in the drainage network. The results show that the correlation between the intensive rainfall events (&gt;10 mm/day) and the recharge rates can be used to modify the daily pumping operation and maintain high freshwater levels in the canal network to increase the resistance to infiltration and reduce saltwater intrusion into the polder.

Legacy earthen berms influence vegetation and hydrologic complexity in the Altar Valley, Arizona

Across the American Southwest water development has played a critical role in managing rangelands. Earthen berms have been constructed throughout US rangelands to manage runoff and reduce erosion. The berms altered runoff patterns to increase soil moisture with positive local vegetative response. However, altered runoff patterns can be considered a disturbance that affects broader scale vegetation patterns. We hypothesized that the hydrologic impacts of earthen berms in semiarid rangelands will be reflected in contrasting upslope and downslope vegetation patterns. A supervised classification of grass, shrubs, and bare soil was performed using orthographic imagery taken in June 2016 to quantify the effects of 181 earthen berms in the uplands and floodplain of the Altar Valley in Southern Arizona, US. Intact berms blocked runoff, creating downslope runoff “shadows” within which the precipitation is the dominant water input. We documented more bare soil downslope of intact berms in comparison with upslope. Grass and shrub cover affected by berms were related to soil texture. Grass and shrub cover were not different above and below intact berms on fine textured soils, but on sites with coarser textured soil, grass cover was lower downslope of berms. Where breaches occurred on coarser textured soils, the up and downslope differences in grass cover diminished. This study points to the role of conservation structures in adding additional complexity to already heterogeneous landscapes by creating patchwork assemblages of vegetation and bare soil proximal to earthen runoff and erosion control berms.

Integrating simulation models and statistical models using causal modelling principles to predict aquatic macroinvertebrate responses to climate change

Climate change is projected to threaten ecological communities through changes in temperature, rainfall, runoff patterns, and mediated changes in other environmental variables. Their combined effects are difficult to comprehend without the mathematical machinery of causal modelling. Using piecewise structural equation modelling, we aim to predict the responses of aquatic macroinvertebrate total abundance and richness to disturbances generated by climate change. Our approach involves integrating an existing hydroclimate-salinity model for the Murray-Darling Basin, Australia, into our recently developed statistical models for macroinvertebrates using long-term monitoring data on macroinvertebrates, water quality, climate, and hydrology, spanning 2,300 km of the Murray River. Our exercise demonstrates the potential of causal modelling for integrating data and models from different sources. As such, optimal use of valuable existing data and merits of previously developed models in the field can be made for exploring the effects of future climate change and management interventions.

How do belowground bedrock fissures impact soil erosion on karst hillslopes under different rainfall intensity conditions?

AbstractIn karst regions, bedrock fissures are developed via karstification, which may cause belowground soil erosion (BSE). However, few studies have quantitatively assessed the effect of bedrock fissures on BSE because BSE measurement is difficult on karst hillslopes. The objective of this study was to investigate the differences in runoff and soil erosion at the surface and belowground on karst hillslopes with and without bedrock fissures (hereafter called HS1 and HS2, respectively) under different rainfall intensities (50, 75, and 100 mm hr−1). The slope gradient was 5°. In the rainfall process, surface runoff (SR), subsurface runoff (SBR), soil–rock interface flow (SRIF), and underground fissure flow (UFF) data were collected on HS1 and HS2. The results showed that the SR coefficients of HS1 and HS2 were negligible (less than 1%) under rainfall intensities of 50 and 75 mm hr−1, and UFF (56%–57%) of HS1 and SRIF (40%–44%) of HS2 dominated the runoff pattern. Under a rainfall intensity of 100 mm hr−1, the SR coefficient increased to approximately 30% under the two treatments, and the coefficients of UFF of HS1 and SRIF of HS2 decreased to 29% and 24%, respectively. Compared to HS2, UFF of HS1 increased by 18%–39%. The SBR coefficient was lower than 10% for all rainfall events. Because SR and SBR were low under rainfall intensities of 50 and 75 mm hr−1, the soil loss was dominated by UFF (99%–100% of the total sediment) of HS1 and by SRIF (86%–97% of the total sediment) of HS2. Under the 100 mm hr−1 rainfall intensity, almost all sediment was lost via SR under the two treatments, and the sediment loss of HS2 was 33% higher than that of HS1. Our results indicated that bedrock fissures caused more underground rainwater leakage at the SRI and further decreased surface soil erosion on karst hillslopes.

The Effect of Soil Surface Mounds and Depressions on Runoff

Surface mounds and depressions are the basic patterns of microtopography. Their geometric forms and physical properties affect rainfall infiltration, runoff generation and runoff confluence process. In this study, soil beds were set up with seven different types of microtopography to study the effects of surface mounds and depressions on runoff. They were the control check (CK), alternate mounds (AM), continuous mounds (CM), alternate depressions (AD), continuous depressions (CD), alternate mounds and depressions (AMD) and continuous mounds and depressions (CMD). There was only one microtopography type for monomorphic surface relief (MSR) while two for compound surface relief (CSR). All soil beds were exposed under 60, 90 or 120 mm/h rainfall intensity for 90 min. The main results are as follows: surface mounds could promote surface runoff, triggering and shortening runoff generation time, while surface depressions showed contrary results. Whether there was an interval between mounds or depressions also affected the characteristics of runoff. The runoff generation time was 3.8–5.0 times higher for continuous slope than for interval slope, while the runoff yield and runoff coefficient both decreased by approximately 40%. CSR can significantly neutralize the flow-promoting effects of the mounds and the flow-inhibiting effects of the depressions, making the runoff yield and runoff process present a neutral state between the mounds and depressions. CSR prolongs runoff generation time from 1–10 min of MSR to 5–16 min. The runoff yield of CSR presented as 0.12, between 0.17 for mounds and 0.10 for depressions, and so did the runoff coefficient and hydrodynamic parameters. In addition, with rainfall intensity increased, the runoff pattern of CSR and MSR became more similar to each other, and the retarding effects of topography on overland flow were more effective.

Climatic Asynchrony and Hydrologic Inefficiency Explain the Global Pattern of Water Availability

AbstractThe mechanisms underlying observed global patterns of partitioning precipitation () to evapotranspiration () and runoff () are controversially debated. We test the hypothesis that asynchrony between climatic water supply and demand is sufficient to explain spatio‐temporal variability of water availability. We developed a simple analytical model for that is determined by four dimensionless characteristics of intra‐annual water supply and demand asynchrony. The analytical model, populated with gridded climate data, accurately predicted global runoff patterns within 2%–4% of independent estimates from global climate models, with spatial patterns closely correlated to observations (). The supply‐demand asynchrony hypothesis provides a physically based explanation for variability of water availability using easily measurable characteristics of climate. The model revealed widespread responsiveness of water budgets to changes in climate asynchrony in almost every global region. Furthermore, the analytical model using global averages independently reproduced the Budyko curve () providing theoretical foundation for this widely used empirical relationship.

Hydrological Response of Tropical Catchments to Climate Change as Modeled by the GR2M Model: A Case Study in Costa Rica

This study aimed to assess the impacts of climate change on streamflow characteristics of five tropical catchments located in Costa Rica. An ensemble of five General Circulation Models (GCMs), namely HadGEM2-ES, CanESM2, EC-EARTH, MIROC5, MPI-ESM-LR dynamically downscaled by two Regional Climate Models (RCMs), specifically HadRM3P and RCA4, was selected to provide an overview of the impacts of different climate change scenarios under Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 using the 1961–1990 baseline period. The GR2M hydrological model was used to reproduce the historical monthly surface runoff patterns of each catchment. Following calibration and validation of the GRM2 model, the projected impact of climate change on streamflow was simulated for a near-future (2011–2040), mid-future (2041–2070) and far-future (2071–2100) for each catchment using the bias-corrected GCM-RCM multimodel ensemble-mean (MEM). Results anticipate wetter conditions for all catchments in the near-future and mid-future periods under RCPs 2.6 and 4.5, whereas dryer conditions are expected for the far-future period under RCP 8.5. Projected temperature trends indicate consistently warmer conditions with increasing radiative forcing and future periods. Streamflow changes across all catchments however are dominated by variations in projected precipitation. Wetter conditions for the near-future and mid-future horizons under RCPs 2.6 and 4.5 would result in higher runoff volumes, particularly during the late wet season (LWS). Conversely, dryer conditions for the far-future period under RCP8.5 would result in considerably lower runoff volumes during the early wet season (EWS) and the Mid-Summer Drought (MSD). In consequence, projected seasonal changes on streamflow across all catchments may result in more frequent flooding, droughts, and water supply shortage compared to historical hydrological regimes.

Spatial Patterns of Dense Water Runoff on the Antarctic Shelf and Continental Slope

Spatial Patterns of Dense Water Runoff on the Antarctic Shelf and Continental Slope