Budyko Framework Research Articles

Evapotranspiration in hydrological models under rising CO2: a jump into the unknown

Many hydrological models use the concept of potential evapotranspiration (PE) to simulate actual evapotranspiration (AE). PE formulations often neglect the effect of carbon dioxide (CO2), which challenges their relevance in a context of climate change and rapid changes in CO2 atmospheric concentrations. In this work, we implement three options from the literature to take into account the effect of CO2 on stomatal resistance in the well-known Penman–Monteith PE formulation. We assess their impact on future runoff using the Budyko framework over France. On the basis of an ensemble of Euro-Cordex climate projections using the RCP 4.5 and RCP 8.5 scenarios, we show that taking into account CO2 in PE formulations largely reduces PE values but also limits projections of runoff decrease, especially under an emissive scenario, namely, the RCP 8.5, whereas the classic Penman–Monteith formulation yields decreasing runoff projections over most of France, taking into account CO2 yields more contrasting results. Runoff increase becomes likely in the north of France, which is an energy-limited area, with different levels of runoff response produced by the three tested formulations. The results highlight the sensitivity of hydrological projections to the processes represented in the PE formulation.

Development of a simple Budyko-based framework for the simulation and attribution of ET variability in dry regions

Global changes have largely altered the magnitude and distribution of evapotranspiration (ET), which in turn significantly impacts regional water availability and water partitioning, particularly in semi-arid areas, such as the Agricultural-Pastoral Ecotone in Northwest China (APENC). In this study, the Budyko framework was revised and applied at a finer spatio-temporal scale for the simulation and attribution of monthly ET variability in dry regions. As a holistic approach for modeling water partitioning, the revised Budyko framework (RBF) is expected to achieve parsimony of data input and model parameters. Application of the Budyko-based framework in the APENC showed an accurate ET simulation (R2 = 0.96, RMSE = 3.45 mm/mon, NSE = 0.95), which is a better performance compared with two classical models, FAO crop coefficient model and Complimentary Relationship (CR) model with in situ observations. For the attribution of monthly ET variability, vegetation has the highest sensitivity coefficient, while the precipitation shows the largest actual contribution because of its larger variability. Subsequently, the RBF was assessed with two different groups of in situ observations in semi-arid areas with different environment and vegetation conditions, and showed credible results on ET simulation. This shows that the RBF with parsimony of model parameters is highly applicable in data lacking dry regions.

Variation characteristics and quantitative study of permafrost degradation in the upper reaches of Heihe River, China

To quantitatively investigate the permafrost degradation and its effects on hydrological processes in the upper reaches of Heihe River, a surface frost number model was firstly constructed to simulate the permafrost distribution and degradation from 1980 to 2015. The variation characteristics of the DDF, permafrost area, low limit of permafrost, and active layer thickness were then determined in the study area. Furthermore, the Budyko framework was applied to quantify the contribution of permafrost degradation to runoff. The results indicated that the permafrost degradation was significant in the past 36 years, with an average decreasing rate of 80.4 km2/a in the permafrost area, an average increasing rate of 13 m/a and 0.61 cm/a in the low limit elevation and in the active layer thickness, respectively. It is also found that basin characteristic parameter in the Budyko framework is closely related to permafrost degradation in cold regions, 40% of whose change is contributed by permafrost degradation. In addition, it is revealed that permafrost degradation contributed more than 20% to runoff change in study area. This investigation also indicated that the runoff response to permafrost degradation has a 3 months delayed effect. This study deepens the understanding of the impact of permafrost degradation on hydrological processes.

Integrating the Budyko framework with the emerging hot spot analysis in local land use planning for regulating surface evapotranspiration ratio

Land use planning regulates surface hydrological processes by adjusting land properties with varied evapotranspiration ratios. However, a dearth of empirical spatial information hampers the regulation of place-specific hydrological processes. Therefore, this study proposed a Local Land Use Planning framework for EvapoTranspiration Ratio regulations (ETR-LLUP), which was tested for the developments of spatially-varied land use strategies in the Dongjiang River Basin (DRB) in Southern China. With the first attempt at integrating the Emerging Hot Spots Analysis (EHSA) with the Budyko framework, the spatiotemporal trends of evapotranspiration ratios based on evaporative index and dryness index, from 1992 to 2018, were illustrated. Then, representative land-cover types in each sub-basin were defined using Geographically Weighted Principal Component Analysis, in two wet years (1998 and 2016) and three dry years (2004, 2009, and 2018), which in turn were identified using the Standard Precipitation Index. Finally, Geographically Weighted Regressions (GWRs) were used to detect spatially-varied relationships between land-cover proportions and evaporative index in both dry and wet climates. Results showed that the DRB was consistently a water-limited region from 1992 to 2018, and the situation was getting worse. We also identified the upper DRB as hotspots for hydrological management. Forests and croplands experienced increasingly water stress compared to other vegetation types. More importantly, the spatial results of GWR models enabled us to adjust basin land use by 1) expanding and contracting a combination of ‘mosaic natural vegetation’ and ‘broadleaved deciduous trees’ in the western and eastern parts of the basin, respectively; and 2) increasing ‘broadleaved evergreen trees’ in the upstream parts of the basin. These spatially-varied land use strategies based on the ETR-LLUP framework allow for place-specific hydrological management during both dry and wet climates.

Annual water deficit in response to climate variabilities across the globe

Severe water deficits due to abnormal climatic conditions can be observed in hydrology and agriculture and can be assessed by various characteristics of the water system that showdifferent responses to climate variability. This paper comprehensively investigates the sensitivities of hydrological (i.e. streamflow and water storage) and agricultural (i.e. plant water availability) water deficits to climate variability at a global scale from a hydrological cycle perspective. The sensitivities of 77 large basins across the globe are quantified by both multiple linear regression (MLR) and the Budyko framework based on a newly released terrestrial water cycle dataset. We find that streamflow and water storage deficits are generally more sensitive to rainfall variation, while plant water availability is more responsive to variations of potential evapotranspiration. The climate sensitivities of the water deficit indices are shown to vary with the wetness index and are shaped by catchment surface properties like water storage capacity. The sensitivities of streamflow deficits to rainfall are higher in wetter regions, while the sensitivities of plant water availability to potential evapotranspiration are higher in drier regions. The findings about the divergent responses in water deficit indices can be conducive to developing region-dependent water resource management strategies to alleviate water deficits under a changing environment.

Hydrological effects of the snow fraction and its ecohydrological explication within the Budyko framework

Understanding the effects of climate and catchment characteristics on hydrological behavior is critical in hydrological sciences. Furthermore, improving the clarity associated with the physical meaning of the Budyko hypothesis on how it can be incorporated into ecohydrological processes remains a significant challenge, while the conciseness it affords in addressing hydrological responses has promoted its application. This study explores the hydrological effects of the snow fraction (fs) and assesses the ecohydrological meaning of the catchment parameter (n) within the Budyko framework, employing 1576 globally investigated catchments. Results showed that the Budyko hypothesis decreased systematic errors (NS = 0.76, RMSE = 181.01 mm a−1) when incorporating the fs compared with no snow fraction incorporated it (NS = 0.54, RMSE = 248.85 mm a−1), especially for catchments with higher fs. In these catchments, a higher fs was generally consistent with a higher normalized mean streamflow (Q), while the opposite was true for normalized evaporation (E/P). Under the Budyko framework, n and fs distribution generally exhibited opposite trends. Moreover, higher n was mainly distributed near water limited and the highest energy limited boundaries, while higher fs represented lower (P-Q)/P (i.e., the mean (P-Q)/P was 0.59, 0.57, and 0.38 for catchments with lower (fs < 0.15), medium (0.15 ≤ fs < 0.50), and higher (fs ≥ 0.50) fs). Statistical relationships among ecohydrological processes and catchment parameter suggested that: (i) higher storm depth (α) generally indicated higher normalized mean Q; (ii) a higher plant-available water holding capacity (κ) resulted in a reduction in Q/P, especially when κ was > 0.12; (iii) the effective rooting depth (Ze) exhibited a complex regulatory effect on P partitioning; and (iv) α, Ze, and κ controlled n by 65%, 22%, and 13%, respectively, in all catchments. The ecohydrological processes incorporated into catchment parameters will broaden the ability of the Budyko hypothesis to describe hydrological behavior in a changing world, especially in the ungauged catchment.

Attribution of decadal runoff changes by considering remotely sensed snow/ice melt and actual evapotranspiration in two contrasting watersheds in the Tienshan Mountains

Water processes in the Tienshan Mountains have undergone great changes under the impacts of climate warming and human activities. Here, based on the Budyko framework, we investigated the respective contributions of climate change and human activities to decadal runoff changes (1982–2014) in two contrary watersheds, i.e., the humid Kashi watershed in the Yili River valley and the arid Boertala watershed in the Ebinur Lake basin, in the Tienshan Mountains, where closing the water balance is difficult due to the scarcity of precipitation gauges. To achieve closure of the decadal water balance of the study watersheds, we estimated evapotranspiration from a complementary relationship model and snow/ice melt using the degree-day method with the remote sensing snow cover product. We found that the increase of rainfall (+61.6 mm) and snow/ice melt (+57.3 mm) dominated the increase of runoff (+87.2 mm, from 398.2 mm in 1982–1992 to 485.4 mm in 1993–2014) in the Kashi watershed, contributing 47.1 mm (54.8%) and 43.8 mm (51.0%), respectively, to the increase of runoff. Unlike the Kashi watershed, human activities contributed −13.8 mm (−103.7%) to the runoff (+13.9 mm, from 61.4 mm in 1982–1997 to 75.3 mm in 1998–2014) in the Boertala watershed. Most of the increase in rainfall (+62.5 mm) and snow/ice melt (+13.6 mm) was consumed by the increase of ET (+64.0 mm) instead of runoff. Further analysis showed that most of the increases in snow/ice melt and ET were contributed from the high (>2500 m) and low (<1500 m) elevation regions, respectively. Snowmelt showed a decreasing trend in low elevation regions. Our study highlighted the importance of snow/ice melt and ET in understanding decadal changes in runoff in the Tienshan Mountains.

Trends in the Frequency of Water and Heat Stress in Mid-Latitude North America since 1980

The water-energy balance of many mid-latitude watersheds has been changing in recent decades due to global warming. These changes manifest themselves over both long timescales (e.g., hydrologic drought) and short timescales (e.g., agricultural drought) and may be ameliorated or exacerbated by vegetative response. We apply a Budyko framework to assess short-term response to long-term trends in water and heat stress (HS) across mid-latitude North America. Using high-resolution meteorological data and streamflow records, we calculate the frequency of HS every year since 1980 for every gaged watershed with adequate data (n = 1528). We find that HS has become more frequent in most watersheds in the western US, New England, and southeastern Canada. However, we find that HS has become less frequent in the Midwest and the relatively humid eastern US. By assessing the relationship between trends in HS frequency and proximate forcing variables (annual PPT, annual streamflow, minimum and maximum daily temperatures, actual evapotranspiration, and potential evapotranspiration), we find that these trends in HS frequency are primarily driven by meteorological forcings rather than vegetative response. Finally, we contextualize our findings within the Budyko framework, which assumes a landscape in equilibrium with its climate, with the implication that these trends in HS are only likely to be realized after local vegetation has adapted to new meteorological norms.

Cloud model combined with multiple weighting methods to evaluate hydrological alteration and its contributing factors

Understanding the hydrological alterations caused by climate change and human activities and the underlying impact factors are essential for sustainable water resource management in river basins. Several statistical methods, particularly the Indicator of Hydrologic Alteration (IHA), have been successfully employed to assess the degree of hydrologic alteration. This study proposed a new approach, the cloud model combined with the multiple weighting method (CM-MW), for better quantification of the overall degree of hydrologic alteration. This approach adopts game theory to select reasonable weights for the IHA parameters, therefore improving the accuracy and reliability of the evaluation. By estimating the similarity between the evaluation cloud and the category cloud, this method quantifies the percent data for which the overall degree of hydrological alteration (ODHA) would fall into the respective category. Analysis based on the Budyko framework indicated that in the Illinois River Basin, the dominant causes of hydrologic alteration for watersheds with moderate ODHA and low ODHA were human activities and climate change. The proposed method had a distinct advantage over the conventional approach in classifying the overall hydrological alteration, which would provide more accurate information for comprehensive and adaptive river basin management.

Improved Understanding of How Catchment Properties Control Hydrological Partitioning Through Machine Learning

AbstractLong‐term hydrological partitioning of catchments can be well described by the Budyko framework with a parameter (e.g., Fu's equations with parameter ω). The Budyko framework considers aridity index as the dominant control on hydrological partitioning, while the parameter represents integrated influences of catchment properties. Our understanding regarding the controls of catchment properties on the parameter is still limited. In this study, two machine learning methods, that is, boosted regression tree (BRT) and CUBIST, were used to model ω. Interpretable machine learning methods were adopted for better physical understanding including feature importance, accumulated local effects (ALE), and local interpretable model‐agnostic explanations. Among the 15 properties of 443 Australian catchments, analysis of feature importance showed that root zone storage capacity (SR), vapor pressure, vegetation coverage (M), precipitation depth, climate seasonality and asynchrony index (SAI), and water use efficiency (WUE) were the six primary control factors on ω. ALE showed that ω varied nonlinearly with all factors, and varied non‐monotonically with M, SAI, and WUE. LIME showed that the importance of the six dominant factors on ω varied between regions. CUBIST was further used to build regionally varying relationships between ω and the primary factors. Continental scale ω and evapotranspiration were further mapped across Australia based on the most robust BRT‐trained parameterization scheme with a resolution of 0.05°. Instead of using the machine learning method as a black box, we employed interpretability approaches to identify the controls. Our findings not only improved the capability of the Budyko method for hydrological partitioning across Australia, but also demonstrated that the controls of catchment properties on hydrological partitioning vary in different regions.

Quantifying the contribution of terrestrial water storage to actual evapotranspiration trends by the extended Budyko model in Northwest China

Actual evapotranspiration (AE) is a key component of water cycle. The arid climate of northwest China makes water supply a major constraint on AE. Water source analysis is of great significance to study the causes of AE change. In this paper, we presented an assessment of AE trends in northwest China based on GLEAM (AE_GLEAM), an ensemble of six reanalyses (AE_reanalyses), and a complementary-relationship-based AE dataset (AE_CR). Both AE_GLEAM and AE_reanalyses increased significantly (p < 0.001) during 1981–2017. AE_CR also increased to a certain extent, but the rate was slower. In general, the increasing trends of AE were mainly found in mountainous areas, such as the Altai, Tianshan, Karakoram, Kunlun, Altun, and Qilian Mountains. For these regions, AE was even higher than precipitation in terms of both the climatological mean and the linear trends. It demonstrated that terrestrial water storage (S) could give supplementary supply for AE. Therefore, we extended the Budyko framework to evaluate the effect of S on AE. Taking the landscape parameter n = 1.8 as a reference, S contributed approximately 27% of total water availability for AE. Overall, S seemed to be a major contributor to the increasing AE in the Altai, Tianshan, Qilian, and Altun Mountains. Precipitation was the main source of evaporated water in the western Tianshan to Karakoram Mountains, where potential evapotranspiration also contributed to the increase in AE. In the case of different n values, the contribution from S had a deviation range of −16.9% to 8.5%. This model provides an opportunity to assess the response of AE to S in the absence of observational data.

Theoretical and empirical evidence against the Budyko catchment trajectory conjecture

Abstract. The Budyko framework posits that a catchment's long-term mean evapotranspiration (ET) is primarily governed by the availabilities of water and energy, represented by long-term mean precipitation (P) and potential evapotranspiration (PET), respectively. This assertion is supported by the distinctive clustering pattern that catchments take in Budyko space. Several semi-empirical, nonparametric curves have been shown to generally represent this clustering pattern but cannot explain deviations from the central tendency. Parametric Budyko equations attempt to generalize the nonparametric framework, through the introduction of a catchment-specific parameter (n or w). Prevailing interpretations of Budyko curves suggest that the explicit functional forms represent trajectories through Budyko space for individual catchments undergoing changes in the aridity index, PETP, while the n and w values represent catchment biophysical features; however, neither of these interpretations arise from the derivation of the Budyko equations. In this study, we reexamine, reinterpret, and test these two key assumptions of the current Budyko framework both theoretically and empirically. In our theoretical test, we use a biophysical model for ET to demonstrate that n and w values can change without invoking changes in landscape biophysical features and that catchments are not required to follow Budyko curve trajectories. Our empirical test uses data from 728 reference catchments in the United Kingdom (UK) and United States (US) to illustrate that catchments rarely follow Budyko curve trajectories and that n and w are not transferable between catchments or across time for individual catchments. This nontransferability implies that n and w are proxy variables for ETP, rendering the parametric Budyko equations underdetermined and lacking predictive ability. Finally, we show that the parametric Budyko equations are nonunique, suggesting their physical interpretations are unfounded. Overall, we conclude that, while the shape of Budyko curves generally captures the global behavior of multiple catchments, their specific functional forms are arbitrary and not reflective of the dynamic behavior of individual catchments.

A novel Budyko-based approach to quantify post-forest-fire streamflow response and recovery timescales

Recent increases in the incidences of wildfires have necessitated the development of methodologies to quantify the effect of these fires on streamflows. Climate variability has been cited as a major challenge in revealing the true contribution of disturbance to streamflow changes. To address this, we developed an annual Budyko “decomposition” method for (1) statistical change detection of hydrologic signatures post-fire, (2) separating climate-driven and fire-driven changes in streamflow, and (3) estimating hydrologic recovery timescales after fire. We demonstrate the use of this methodology for 17 watersheds in Southern California with high interannual variability in precipitation. We show that while traditional metrics like changes in flow or runoff ratio might not detect a disturbance effect due to confounding climate signals, the Budyko framework can be used successfully for statistical change detection. The Budyko approach was also found to be robust in detecting changes in 5 highly burned catchments (>40% burned area ratio), while changes in less burned (2) and unburned catchments (10) were insignificant. We further used the Budyko approach to quantify the contribution of fire-driven versus climate driven changes in streamflow and found that fire contributed to an average increase in streamflow on the order of 80 mm yr−1, though the effect varied greatly between years. Finally, we estimated hydrologic recovery timescales that varied between 5 and 45 years for four burned catchments. We found a significant linear relationship between recovery time and burned area at medium and high severity for our study catchments, with about 4 years of recovery time per 10% of the watershed burned.

Application of Budyko framework to irrigation districts in China under various climatic conditions

AbstractBudyko's framework has been widely used to study basin‐scale water balance. In this study, we focus on the extended application of Fu's equation (one formulation of the Budyko‐type curves) to 371 large irrigation districts in China over a period of 2010–2017. Water balance method was used to estimate actual evapotranspiration in the irrigated areas. Considering the contribution of shallow groundwater to , the water availability in the Budyko framework defined as equivalent precipitation for irrigation areas is the sum of irrigation water , precipitation and groundwater evaporation . Results showed that the relationships between evapotranspiration , water availability and energy supply can be accurately described by the Budyko's curves. The optimal values of Budyko parameter ω for each irrigation district was obtained with multi‐annual data using least square method. The Fu's equation performed better in humid and semi‐humid regions than arid and semi‐arid regions. The comparison between and confirmed the relative effect of water availability and energy supply on according to the variation of climatic conditions. Normalized difference vegetation index (NDVI) and soil properties (denoted by the proportion of clay and sand) were selected to develop empirical equation for parameter ω using multiple linear regression analysis method. This study shows that the Budyko framework can be extended to irrigation areas and provides useful information on evapotranspiration to assist in water management in irrigation areas.

Examining evaporative demand and water availability in recent past for sustainable agricultural water management in India at sub-basin scale

This study explores recent changes in evaporative demand and water availability across 100 river sub-basins in India by partitioning the actual evapotranspiration (AET) into green water evapotranspiration (ET-Green) and blue water evapotranspiration (ET-Blue). For computation of ET-Green and ET-Blue, the Budyko framework is applied to long-term scenario (2003–2017) and to intra-annual averaged series (i.e. 2003-2007, 2008–2012 and 2013–2017). For the Budyko analysis, the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Global Land Data Assimilation System (GLDAS) AET and Climate Research Unit Global Data Assimilation System (CRU GDAS) Potential ET (PET) climate forcing variables have been utilized. Multiple hydro-climatic indicators, such as dryness index (DI), evaporative index (EI), and responsivity with respect to theoretical Budyko curve are computed and they show substantial variations across sub-basins from far past time (2003) to recent past (2017). The changes in DI and EI highlight the diversity in evaporative demand and dryness condition across the country. Results reveal that India's evaporative water demand is largely influenced by ET-Green (up to 65%) that depends mainly on precipitation. At the same time, in many river sub-basins, ET-Blue that depends on external sources of water like diversion or stored water, is significant. The shape parameter (ω) of Fu's Budyko equation, that can be utilized for the future assessment of ET-Green and ET-Blue, has been optimized. The results of this study would of immense value for sustainable irrigation water management and improving water use efficiency in agriculture and overall water availability in river basins in India.

Attribution Assessment and Prediction of Runoff Change in the Han River Basin, China.

The ecological environment and water resources of the Han River Basin (HRB) are incredibly susceptible to global warming. Naturally, the analysis of future runoff in HRB is believed to offer a theoretical basis for water resources management and ecological protection in HRB. The purpose of this study is to investigate and forecast the effects of climate change and land use change on runoff in the HRB. This study uses CMIP6 data to simulate three future climate change scenarios (SSP126, SSP245 and SSP585) for changes in precipitation and temperature, a CA-Markov model to simulate future land use change scenarios, and the Budyko framework to predict future runoff changes. The results show that: (1) Between 1974 and 2014, annual runoff (R) and annual precipitation (P) in the HRB decline not so significantly with a rate of 1.3673 mm/a and 1.2709 mm/a, while maximum temperature (Tmax) and minimum temperature (Tmin) and potential evapotranspiration (E0) show a non-significantly increasing trend with 0.0296 °C/a, 0.0204 °C/a and 1.3313 mm/a, respectively. Precipitation is considered as main contributor to the decline in Han River runoff, accounting for 54.1%. (2) In the HRB, overall precipitation and temperature are estimated to rise in the coming years, with all other hydrological variables. The comparison of precipitation rise under each scenario is as follows: SSP126 scenario > SSP585 scenario > SSP245 scenario. The comparison of the temperature increase under each scenario is as follows: SSP585 scenario > SSP245 scenario > SSP126 scenario. (3) In the HRB, farmland and grassland land will continue to decline in the future. The amount of forest acreage is projected to decline but not so significantly. (4) The future runoff of the HRB shows an increasing trend, and the future runoff varies in different scenarios and periods. Under the land use scenarios of maintaining LUCC1992–2014 and LUCC2040 and LUCC2060, the R change rates in 2015–2040 are 8.27–25.47% and −8.04–19.35%, respectively, and the R in 2040–2060 are 2.09–13.66% and 19.35–31.52%. At the same time, it is very likely to overestimate the future runoff of the HRB without considering the changes in the land use data of the underlying surface in the future.

Estimation of time-varying parameter in Budyko framework using long short-term memory network over the Loess Plateau, China

Accurate estimation of the basin-specific parameter in the Budyko framework (e.g., parameter n in the Choudhury-Yang equation) is critical to quantify precipitation partitioning into evapotranspiration (E) and runoff. However, n is difficult to estimate due to complex interactions between the water balance and various environmental factors. In this study, we identified the controlling factors of n using random forest during 1981–2015 for 30 basins in the Loess Plateau of China. We then used the long short-term memory (LSTM) network combined with an 11-year moving window to develop a model to estimate time-varying n. This model was further incorporated into the Choudhury-Yang equation to simulate E. Our results showed that correlations between parameter n and environmental factors presented obvious spatial heterogeneity. Three land use type factors (i.e., the proportions of cropland, shrubland, and built-up land area), two climatic factors (i.e., precipitation and potential evapotranspiration), and a water use factor (i.e., irrigation water use) were identified as the controlling factors for n. Based on these controls, the LSTM model outperformed the traditional multiple linear regression model (MLR model) in estimating time-varying n, with root mean square error (RMSE) of 0.31/0.49 and coefficient of determination (R2) of 0.88/0.67 for the LSTM/MLR model, respectively. Moreover, compared with the original Choudhury-Yang equation (using constant n calibrated by long-term average water balance), the improved equation (using time-varying n estimated by the LSTM) better reproduced the time series of water balance-based E. This study could enhance the applicability of the Budyko framework and provide scientific guidance for water resources management.

Drivers of drought-induced shifts in the water balance through a Budyko approach

Abstract. An inconsistent relationship between precipitation and runoff has been observed between drought and non-drought periods, with less runoff usually observed during droughts than would be expected based solely on precipitation deficit. Predictability of these shifts in the precipitation–runoff relationship is still challenging, largely because the underlying hydrologic mechanisms are poorly constrained. Using 30 years of data for 14 basins in California, we show how the Budyko framework can be leveraged to decompose shifts in precipitation versus runoff during droughts into “regime” shifts, which result from changes in the aridity index along the same Budyko curve, and “partitioning shifts”, which imply a change in the Budyko parameter ω and thus in the relationship among water balance components that governs partitioning of available water. Regime shifts are primarily due to measurable interannual changes in precipitation or temperature, making them predictable based on drought conditions. Partitioning shifts involve further nonlinear and indirect catchment feedbacks to drought conditions and are thus harder to predict a priori. We show that regime shifts dominate changes in absolute runoff during droughts but that gains or losses due to partitioning shifts are still significant. Low aridity, high baseflow, a shift from snow to rain, and resilience of high-elevation runoff correlate with higher annual runoff during droughts than would be predicted by the precipitation–runoff ratio during non-drought years. Differentiating between these shifts in the precipitation–runoff relationship using a Budyko approach will help water resource managers, particularly in arid, drought-prone regions, to better project runoff magnitudes during droughts based on available climate data and, furthermore, understand under what circumstances and to what extent their forecasts may be less reliable due to nonlinear basin–climate feedbacks.

Global climate-driven trade-offs between the water retention and cooling benefits of urban greening

Urban greening can potentially help mitigate heat-related mortality and flooding facing the >4 billion urban population worldwide. However, the geographical variation of the relative combined hydrological and thermal performance benefits of such interventions are unknown. Here we quantify globally, using a hydrological model, how climate-driven trade-offs exist between hydrological retention and cooling potential of urban greening such as green roofs and parks. Using a Budyko framework, we show that water retention generally increases with aridity in water-limited environments, while cooling potential favors energy-limited climates. Our models suggest that common urban greening strategies cannot yield high performance simultaneously for addressing both urban heat-island and urban flooding problems in most cities globally. Irrigation, if sustainable, may enhance cooling while maintaining retention performance in more arid locations. Increased precipitation variability with climate change may reduce performance of thinner green-infrastructure more quickly compared to greened areas with thicker soils and root systems. Our results provide a conceptual framework and first-order quantitative guide for urban development, renewal and policymaking.

Quantifying the effects of climate and watershed structure changes on runoff variations in the Tao River basin by using three different methods under the Budyko framework

Quantifying the effects of climate and watershed structure changes on runoff variations in the Tao River basin by using three different methods under the Budyko framework