Changes In Potential Evapotranspiration Research Articles

A causal physics-informed deep learning formulation for groundwater flow modeling and climate change effect analysis

In this study, we propose and test a formulation for building causal physics-informed hybrid models over traditional physics-informed hybrid models (H-HBVo) and a convolutional neural network (1D-CNN) in groundwater level (GWL) modeling. Two types of models are built based on our formulation and named H-HBV and H-Lin, because they integrate two different hydrological models. The comparison is made in terms of performance and ability to learn cause-and-effect relationships between inputs and outputs. The novelty of this study lies in the CRC (Causal Relationship Constraints) conditions, derived from a mathematical development, that are imposed on the layers of the physics-informed hybrid model to force it to learn causal relationships. The results showed that the 1D-CNN algorithm performed slightly better than the hybrid algorithms, and that the H-Lin and H-HBV algorithms together achieved slightly better results than the traditional hybrid algorithm, H-HBVo. It is also obtained that the algorithms subjected to our formulations (H-Lin and H-HBV) are the ones with satisfactory causality properties and that the integration of domain knowledge is not sufficient to obtain causal and interpretable models within the framework of hybrid algorithms. Subsequently, an analysis of the effect of climate change is carried out for Quebec (Canada) using H-HBV models. The results show that the RCP and SSP scenarios give fairly similar results, i.e. an increase in GWL between 2011 and 2090 with median amplitudes varying between + 5.6 and + 7 cm. In some cases, the amplitude of increase can exceed between + 14 and + 23 cm, and even reach between + 35 and + 70 cm. The results of the climate change analysis are consistent with changes in vertical inflow and potential evapotranspiration, the input variables, for the different climate scenarios, confirming the robustness of our formulation.

Revisiting the contribution of different factors in determining the changes in potential evapotranspiration over China.

In this paper, a daily gridded observation data across China from 1961 to 2022 were used to calculate daily potential evapotranspiration (PET). The observed variables included daily temperature, sunshine hours, average wind speed, and average relative humidity. PET was determined using the Penman-Monteith method recommended by the Food and Agriculture Organization (FAO). The long-term trend of PET was investigated in six regions of China during different seasons. To further compressed the influence of various meteorological factors on the PET trend, the contribution of each meteorological element to the long-term trend of PET was analyzed. The results indicate the following: (1) PET reaches its peak during summer which values from 145 to 640 mm, while it is lowest during winter from 21 to 244 mm. (2) The spatial patterns of PET trend changes are relatively similar across the four seasons, characterized by a decrease in the eastern regions and an increase in the western regions. The reduction is most significant during the summer and the range of trend is from -2.04 to 1.48 mm/day, while the increase becomes more pronounced in the winter which trend is from -0.34 to 0.53 mm/day. (3) The contribution of factors varies significantly across different regions. In spring and autumn, RH and U have little difference in contribution from other factors. But tsun is varies different from regions, the contribution value is largest in the northwest and smallest in the northeast. However, during summer, tsun become the most significant contributor in the YZ and SE regions, while in winter, Tm emerges as the most significant contributor to the PET trend in all six subregions. In SW, the contribution from U2 is the smallest in all seasons, with RH and Tm being the two crucial factors determining the PET trend in this region.

Divergent future drought projections in UK river flows and groundwater levels

Abstract. Hydrological drought is a serious issue globally, which is likely to be amplified by 21st century climate change. In the UK, the impacts of changes in river flow and groundwater drought severity in a future of climate change and higher water demand are potentially severe. Recent publication of a new nationally consistent set of river flow and groundwater level projections (the eFLaG dataset), based on state-of-the-art UKCP18 climate projections, offers a unique opportunity to quantitatively assess future UK hydrological drought susceptibility. The dataset includes a transient, multi-model ensemble of hydrological projections driven by a single regional climate model (RCM), with a 12-member perturbed-parameter ensemble, for 200 catchments and 54 boreholes spanning a period from 1961 to 2080. Assessment of a baseline period (1989–2018) shows that the RCM-driven projections adequately reproduce observed river flow and groundwater level regimes, improving our confidence in using these models for assessment of future drought. Across all hydrological models and most catchments, future low river flows are projected to decline consistently out to 2080. Drought durations, intensities and severities are all projected to increase in most (over 90 %, pooling across different drought characteristics) UK catchments. However, the trajectory of low groundwater levels and groundwater drought characteristics diverges from that of river flows. Whilst groundwater levels at most (> 85 %) boreholes are projected to decline (consistent with river flows), these declines are relatively modest (< 10 % reduction) in transient low groundwater levels by 2080, and, in fact, six show moderate increases. Groundwater drought characteristics in the far future (2050–2079) are often similar to those of the baseline (1989–2018), with only 33 % of boreholes showing an increase (towards worsening drought) of more than 10 % for drought severity (48 % of boreholes for drought intensity). Interestingly, for some boreholes, droughts are projected to be more prolonged and severe in the near future (2020–2049) before returning to shorter durations and lower severity in the far future. A number of explanatory factors for this divergence between river flow and groundwater are discussed. The sensitivity to seasonal changes in precipitation and potential evapotranspiration is proposed as a principal driver of divergence because low river flows are more influenced by shorter-term rainfall deficits in the summer half-year, whilst groundwater drought appears to be offset somewhat by the wetter winter signal in the RCM projections. Our results have important implications for water management, demonstrating a widespread increase in river flow drought severity and diminishing low flows that could have profound societal and environmental impacts unless mitigated. Furthermore, the divergence in projections of drought in river flows and groundwater levels brings into question the balance between surface and subsurface water resources. The projected contrast in fortunes of surface and subsurface water resources identified for the UK may be replicated in other parts of the world where climate projections suggest a shift towards drier summers and wetter winters.

Hydrological changes in the drought‐prone region of Maharashtra (India): Implications for sustainable water use

Recent climatic changes and anthropogenic activities considerably affect regional water resources, particularly in water‐scarce regions. The present study, therefore, aims to understand the changes in monsoon rainfall, potential evapotranspiration (PET), surface runoff, dam storage and groundwater in the drought‐prone region of Maharashtra. The analyses of trend and step‐change were carried out using standard parametric tests. The results were verified with the application of non‐parametric statistical techniques. Notably, monsoon rainfall and runoff were observed to be declining. Exceptionally, the Yerala Basin witnessed significant increase in rainfall along with heavy rainfall events. Contradictorily, Agrani and Man Basins registered a notable decline in rainfall and runoff. As vulnerability to hydrological disasters is high, these basins should be carefully monitored. Although surface water harvesting brought a positive change in post‐monsoon groundwater level, it was the main reason for a decline in runoff volume at downstream reaches, which led to intra‐basin water disparity. The study area witnessed significant increase in groundwater extraction. Unfortunately, the misuse of government‐subsidized schemes exacerbates groundwater exploitation and stockpiling of water resources. Moreover, the increasing rate of PET augments hydrological losses and amplifies water distress. Interestingly, almost all the hydrological changes were notably experienced during the post‐2000 period. To cope with present and future water scarcity problems, it is therefore necessary to restrict irrational use and allocation of available limited water resources. The findings that emerge from this investigation may help to formulate judicious water policies and plans which could be implemented by the government, agronomists, water resource managers and farmers.

Examining the Water Scarcity Vulnerability in US River Basins Due To Changing Climate

AbstractAccurate assessment of changes in water availability with changing climate is vital for effective mitigation and adaptation. In this research, we employ a parsimonious Budyko curve method to evaluate changes in water availability under low‐ (SSP126) and high‐emission (SSP585) scenarios for 331 river basins in the contiguous United States. We also assess the relative role of changes in precipitation (∆P) and potential evapotranspiration (∆PET) with changing climate on the increase in water availability vulnerability. Results highlight that around 43% (28%) of basins are projected to experience increased vulnerability to changing climate in high‐emission (low‐emission) scenarios. Sub‐humid basins are most often impacted, while arid and semi‐arid basins exhibit lower sensitivity to changes. Intriguingly, ∆PET emerges as the dominant control on vulnerability, surpassing ∆P, particularly under SSP585 scenario. The analysis prompts water managers to focus on long‐term mitigation planning and scientists to further constraint climate and water budget forecasts in affected basins.

Heterogeneity analysis of main driving factors affecting potential evapotranspiration changes across different climate regions

Exploring the influencing factors of potential evapotranspiration (PET) is of great significance for further understanding the causes of climate change and improving agricultural irrigation efficiency. In this study, modified Mann–Kendall analysis was used to elucidate the temporal variation characteristics of meteorological factors and PET based on a dataset from 710 meteorological stations in China. Furthermore, we revealed the main factors that influence the temporal and climate heterogeneity of PET by combining sensitivity analysis with the contribution analysis method. The results showed that 1) climate factors and PET exhibited trend changes on a yearly scale, with slope variation ranges of temperature (T), relative humidity (RH), net radiation (RN), wind speed (U) and PET of 0.03–0.04 °C/a, 0.03–0.08 %/a, 0.001–0.007[MJ/(m2/day)]/a, −0.005 to −0.012(m/s)/a and −0.30–0.38 mm/a, respectively. 2) The sensitivity coefficient fluctuated greatly inter-annually, but the trend was more pronounced inter-annually. Most sensitive factor for PET was RN in hyperarid (HAR), arid (AR) and semiarid regions (SAR), while it changed to RH in semihumid (SHR) and humid regions (HR). PET was more sensitive to RN in dry and relatively wet hot seasons, while it changed to RH during wet and relatively dry cold seasons. 3) PET changes were determined by the relative changes and the sensitivity coefficient, and significant temporal heterogeneity was observed. In HAR, AR, SAR and SHR, the relative changes in T and U result in higher contributions. In HR, PET changes were primarily caused by its higher sensitivity to RH and RN. 4) In dry region and humid-cold seasons, the bigger relative changes of climate factors were the main drivers affecting PET changes, but in humid region and arid-hot seasons, the they were determined by the strong nonlinear relationship between PET and factors. This finding holds great significance for the scientific understanding of the evolution mechanism of PET under changing environments.

Will the ‘evapotranspiration paradox’ phenomenon exist across China in the future?

AbstractThe uneven changes in potential evapotranspiration (PET) in response to temperature rise are called the ‘evapotranspiration paradox’ phenomenon, which is expected to intensify further under a warming climate. In this paper, we explored the spatial–temporal changes in the future ‘evapotranspiration paradox’ phenomenon over China and its 10 major river sub‐regions under different climate change scenarios. Thus, this paper uses four global climate model outputs under seven shared socioeconomic pathway‐based scenarios (SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, SSP4‐3.4, SSP4‐6.0 and SSP5‐8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Considering the latest IPCC's 6th Assessment Report (AR6), this research emphasizes the 2021–2040 (near‐term), 2041–2060 (mid‐term) and 2081–2100 (long‐term) periods to anticipate the ‘evapotranspiration paradox’ phenomenon. In this study, PET is estimated based on the modified Penman–Monteith (P‐M) method (considering CO2). Furthermore, the paradox phenomenon in this study is defined considering two pivotal conditions: the surface temperature increases but the evaporation decreases (Type I), and the temperature decreases but the evaporation still tends to increase (Type II). The results show that there were only Type I ‘evapotranspiration paradoxes’ that existed in the historical period, which were dominant especially before the 1990s. Nearly 50% of the areas experienced the Type I ‘evapotranspiration paradox’ phenomenon that occurred during 1975–1994 and 1995–2014. Spatially, it covered 100% of the area of the Southeast River (SER) and the Liaohe River (LR) during 1975–1994 and the area of the SER, the HAR, the HHR and the LR during 1995–2014. In the future, the interdecadal growth rate of PET in China is projected to be the highest under the SSP5‐8.5 and the lowest under the SSP3‐7.0 with spatial variation. Importantly, the largest areas of approximately 36% and 45% with the Type I phenomenon are inclined to occur under the SSP1‐1.9 and SSP4‐6.0, respectively, over the long‐term period (2081–2100). The area with the Type I phenomenon will be less than 20% in the near‐term, and it is less than 12% in the mid‐term period. For the Type II evapotranspiration paradox, the uppermost 45% of the area is expected to experience the Type II phenomenon under SSP1‐1.9 during the mid‐term period, while it is 30% under SSP1‐2.6 during the long‐term period. However, this study's findings provide the scientific basis for formulating adaptation and mitigation strategies to combat ‘evapotranspiration paradox’‐related extremes at regional scales.

Spatio-Temporal Variations of Climate Variables and Extreme Indices over the Aral Sea Basin during 1960 - 2017

The Aral Sea plays a key role in the socio-economic development of Central Asia. In the past few decades, with the combined effects of global warming and human activities, the ecological environment of the Aral Sea has undergone significant changes, such as the reduction of the basin area and the drop in water levels. In this study uses the observed climate data, combined with remote sensing to systematically analyze the characteristics of changes in climate in the Aral Sea Basin (ASB). We used linear regression, Pearson's correlation and Pettit's test to determine climate change. The main conclusions are as follows. Based on the analysis of the temporal and spatial changes of temperature, precipitation, and potential evapotranspiration in the Aral Sea Basin from 1960 to 2017, it was found that the annual average temperature, precipitation, and potential evapotranspiration increased by 0.32 ℃ decade-1, 0.16 mm decade-1, and 0.04 mm day-1 decade-1, respectively. In addition, the changes of these climatic variables were different in the growing season (April - September) and the non-growing season (October - March). Temperature and potential evapotranspiration increased in both growing and non-growing seasons; however, the precipitation decreased (increased) in the growing (non-growing) season. This means that the climate in the growing season showed a warming and drying trend. HIGHLIGHTS In this study, we present the complex and detailed analysis that we performed by combining temporal and spatial changes in key climate parameters temperature, precipitation and potential evapotranspiration and change of climate extreme indices in the entire Aral Sea Basin and its sub-regions. GRAPHICAL ABSTRACT

Contrasting hydrological responses to climate change in two adjacent catchments dominated by karst and nonkarst

Karst systems are well-known for their special features, such as epikarst zone and quick flow, compared to other hydrological systems. However, few studies explored the difference in hydrological responses to climate change between karst and nonkarst catchments. In this paper, two adjacent catchments dominated by karst and nonkarst in Southwest China (subtropical monsoon climate) were selected to investigate their different hydrological behaviors under future climates. To account for potential model structure uncertainties, three different karst hydrological models and three traditional catchment models were used to simulate these two catchments. The results demonstrate that different models yield comparable streamflow simulations within each catchment, allowing for the focus to be on the impact of climate change and catchment hydrological characteristics. The karst-dominated catchment is modeled to have larger actual evapotranspiration (AET) than the nonkarst-dominated catchment under similar climate conditions, with the AET of the former being more sensitive to changes in precipitation and potential evapotranspiration. These differences are primarily due to the presence of the epikarst in the unsaturated zone of the karst system, which can store more infiltration rainwater for evapotranspiration. Both catchments are expected to experience a wetter projection in the wet season and a drier projection in the dry season in the future. However, the karst-dominated catchment will face a drier climate with a significant increase in precipitation in just two months (July and August). Additionally, because of a higher sensitivity of monthly AET to climate change, the karst-dominated catchment will experience a greater monthly discharge reduction in the first two wet months (April and May), a relatively lower discharge increase in other wet months, and a lower monthly discharge in dry months, while the monthly discharge of the nonkarst-dominated catchment increases in the wet season and decrease in the dry season. Furthermore, the karst-dominated catchment will have a much lower annual discharge than the nonkarst-dominated catchment, particularly during extremely dry years in the future period due to its larger AET consumption. These all suggest that the karst-dominated catchment will be more vulnerable to droughts. Overall, due to the drier climate and the different hydrological backgrounds of the karst-dominated catchment, it is expected to have much drier hydrological conditions in the future compared to the nonkarst-dominated catchment.

Contribution of climate and catchment characteristics to runoff variations in Indian river basins: a climate elasticity approach

ABSTRACT The relative influence of climate and catchment characteristics to the variations in runoff in five Indian river basins is assessed using the climate elasticity approach based on the Budyko hypothesis. From 1980 to 1999, catchment characteristics are found to be the main contributor to runoff variation for all of the basins except Upper Mahanadi sub-basin, where climatic factors are the major contributor. Among the climatic factors, runoff is more responsive to changes in precipitation than to changes in potential evapotranspiration. The mean contribution of climate (catchment) to runoff variation is largest at the Cauvery (Krishna) basin. The findings may be useful in planning sustainable water resources infrastructure. Investigation of the relationship between runoff changes in the basins and their land use and land cover changes, as well as the vegetation index, adds to the novelty and usefulness of the study.

Climate elasticity assessment on groundwater recharge to the Edwards Balcones Fault Zone Aquifer, United States

AbstractThis study presents a comprehensive analysis of the characteristics of precipitation, temperature, and groundwater recharge in the recharge zone of the nine basins of the San Antonio segment of the Edwards Balcones Fault Zone Aquifer, which is one of the major groundwater systems in the United States and serves as primary water sources for approximately 1.7 million people in south‐central Texas. Datasets of monthly precipitation and average temperature (1895–2019) and groundwater recharge (1934–2019) are used to examine the decadal variability in precipitation, temperature, and groundwater recharge on the annual scale with a normalized 20‐year moving average of variance. Climate elasticity (precipitation and potential evapotranspiration) of groundwater recharge is estimated to evaluate impacts of climate change on groundwater recharge. The results of this study show that precipitation and temperature variability exhibit decadal cyclic patterns. Elasticity analysis of groundwater recharge indicates that a 1% change in annual precipitation may result in 2%, with a likely range of 0.15%–2.8%, change in groundwater recharge, and a 1% change in annual potential evapotranspiration may lead to −3.3% change in groundwater recharge with a likely range of −8.9% to 4% in the study area. This study suggests that climate elasticity of groundwater recharge may provide an alternative means for evaluating climate impacts on groundwater recharge to an aquifer.

Revealing the trend and change point in Hargreaves equation based on potential evapotranspiration values with various statistical approaches.

Hotter and drier weather conditions due to climate change negatively affect water resources and agricultural production. For this reason, it is vital to analyze the change in potential evapotranspiration (PET) values, which is one of the most important parameters related to plant growth and agricultural irrigation planning. This study analyses the trends and changes in monthly and annual PET values between 1965 and 2018 at Erzincan, Bayburt and Gümüşhane meteorological stations in Turkey. For this purpose, monotonic trends in PET values were determined by Spearman's rho (SR), Mann-Kendall (MK), Şen slope (SS), and innovative trend analysis (ITA) tests and change points were analyzed with the sequential MK (SQMK) test. The Hargreaves equation was used to calculate the PET values. As a result of the study, according to MK and SR tests, while increasing trends at 95% and 99% significance levels were dominant at Erzincan and Bayburt stations, no statistically significant trends were found at Gümüşhane station except in February. ITA generally detected more than 5% increasing trends in PET data's low, medium, and high values. According to ITA slope analysis, there are significant increase trends in PET values at all periods, trend 1% significance level. According to the SQMK test, it was revealed that the trend started in PET values, especially in 1995, 2005, and 2010. The findings emphasized the importance of taking measures against decreased agricultural production and managing water resources effectively.

Climate and aridity measures relationships with spectral vegetation indices across desert fringe shrublands in the South-Eastern Mediterranean Basin

Mediterranean regions are hot spots of climate change, where the expected decrease in water resources threatens the sustainability of shrublands at their arid margins. Studying spectral vegetation indices' relationships with rainfall and potential evapotranspiration (PET) changes across Mediterranean to arid transition zones is instrumental for developing methods for mapping and monitoring the effects of climate change on desert fringe shrublands. Here we examined relationships between 17 spectral vegetation indices (VIs) and four climate and aridity measures, i.e., rainfall, PET, aridity index (AI), and water deficit (WD), calculated at accumulation lags between 1 and 6months. For this purpose, VIs for 38 sites (100 × 100m each) representing less disturbed areas were extracted from Sentinel 2A images for 3years with high (2016), low (2017), and average (2018) annual rainfall. Most of the VIs had shown the highest correlation with the four climate and aridity measures at 2-month accumulation interval. While NDVI relationships with climate measures gained the widest use, our data suggest that indices combining NIR and SWIR bands better correlate with climate parameters. AI is one of the leading annual measures of dryness worldwide; when calculating it monthly, WD was found to represent better the balance between precipitation and PET across the climate transition zone and to be better correlated with VIs. Relationships between NIR and SWIR VIs and water deficit may thus facilitate improvements in monitoring and mapping desert fringe shrublands' responses to climate change if supported by similar results from other areas.

Interaction between dry and hot extremes at a global scale using a cascade modeling framework

Climate change amplifies dry and hot extremes, yet the mechanism, extent, scope, and temporal scale of causal linkages between dry and hot extremes remain underexplored. Here using the concept of system dynamics, we investigate cross-scale interactions within dry-to-hot and hot-to-dry extreme event networks and quantify the magnitude, temporal-scale, and physical drivers of cascading effects (CEs) of drying-on-heating and vice-versa, across the globe. We find that locations exhibiting exceptionally strong CE (hotspots) for dry-to-hot and hot-to-dry extremes generally coincide. However, the CEs differ strongly in their timescale of interaction, hydroclimatic drivers, and sensitivity to changes in the soil-plant-atmosphere continuum and background aridity. The CE of drying-on-heating in the hotspot locations reaches its peak immediately driven by the compounding influence of vapor pressure deficit, potential evapotranspiration, and precipitation. In contrast, the CE of heating-on-drying peaks gradually dominated by concurrent changes in potential evapotranspiration, precipitation, and net-radiation with the effect of vapor pressure deficit being strongly controlled by ecosystem isohydricity and background aridity. Our results help improve our understanding of the causal linkages and the predictability of compound extremes and related impacts.

How desertification in northern China will change under a rapidly warming climate in the near future (2021–2050)

Arid, semi-arid, and semi-humid regions (drylands) with fragile ecological balance have undergone dramatic climate change in past decades, and how the desertification will change under a continuous warming background still remain uncertain. In this study, the bias-corrected Community Earth System Model outputs from Coupled Model Intercomparison Project phase 5 were dynamically downscaled using the Weather Research and Forecasting (WRF) model, based on which the evolution trend of desertification over northern China (NC) in the past (1972–2000) and the near future period (2021–2050) under the RCP8.5 scenario were analyzed using the dune mobility index, and the impacts of climate change on the intensification or reversal of desertification over NC in the near future were explored. The results show that WRF downscaling can reproduce the desertification changes over NC in the past. The regions with a high risk of desertification are mainly located on the border of the desert and gobi. Under a rapidly warming climate in the near future, desertification will likely reverse in most regions of NC, especially for regions north of 40°N over NC. Potential evapotranspiration changes will exacerbate desertification, while precipitation changes will promote rehabilitation, and wind speed changes show obvious local impacts on desertification. The results in this study imply that, with rising temperatures in the future, the extent of desertification will not always continue, desertification will likely reverse at the front and margin of deserts and gobi, and responses of desertification to climate change have significant spatial differences.

Characteristics of Potential Evapotranspiration Changes and Its Climatic Causes in Heilongjiang Province from 1960 to 2019

Climate change refers to the statistically significant changes in the mean and dispersion values of meteorological factors. Characterizing potential evapotranspiration (ET0) and its climatic causes will contribute to the estimation of the atmospheric water cycle under climate change. In this study, based on daily meteorological data from 26 meteorological stations in Heilongjiang Province from 1960 to 2019, ET0 was calculated by the Penman–Monteith formula, linear regression method and the Mann–Kendall trend test were used to reveal the seasonal and inter-annual changing trend of ET0. The sensitivity-contribution rate method was used to clarify the climatic factors affecting ET0. The results showed that: (1) From 1960 to 2019, the maximum temperature (Tmax), minimum temperature (Tmin) and average temperature (Tmean) showed an increasing trend, with climate tendency rate of 0.22 °C per decade (10a), 0.49 °C/(10a), 0.36 °C/(10a), respectively. The relative humidity (RH), wind speed (U) and net radiation (Rn) showed a decreasing trend, with a climate tendency rate of −0.42%/(10a), −0.18 m/s/(10a), −0.08 MJ/m2/(10a), respectively. (2) ET0 showed a decreasing trend on seasonal and inter-annual scales. Inter-annually, the average climate tendency rate of ET0 was −8.69 mm/(10a). seasonally, the lowest climate tendency rate was −6.33 mm/(10a) in spring. (3) ET0 was negatively sensitive to Tmin, and RH, while positively sensitive to Tmax, TmeanU and Rn, its sensitivity coefficient of U was the highest, which was 1.22. (4) The contribution rate of U to ET0 was the highest on an inter-annual scale as well as in spring and autumn, which were −8.96%, −9.79% and −13.14%, respectively, and the highest contribution rate to ET0 were Rn and Tmin in summer and winter, whose contribution rates were −4.37% and −11.46%, respectively. This study provides an understanding on the response of evapotranspiration to climatic change and further provides support on the optimal allocation of regional water resource and agricultural water management under climate change.

Water scarcity down to earth surface in a Mediterranean climate: The extreme future of soil moisture in Portugal

Climate change constitutes a major threat for all the Mediterranean countries due to the combination of large precipitation reductions and temperature increases and the higher frequency of climate extremes, especially driving water scarcity and all the derived multi-sectoral impacts. Portugal, as most of the Mediterranean countries, already endures larger frequencies of droughts and deficits in soil moisture and water storage. In the current study, the future projections of soil moisture are examined using a multi-model EURO-CORDEX regional climate ensemble, in agreement with three future emission scenarios (RCP2.6, 4.5 and 8.5). The drivers of future soil moisture dynamics are also analysed and its effect on relative humidity and evaporation rates. As expected, the projections show a clear reduction of soil moisture through the entire annual cycle, in response to the large decrease in precipitation and temperature increase, via a massive growth of potential evapotranspiration. The overall total soil moisture decreases ranges from −5% for the RCP2.6 to −20% (-10%) for the RCP8.5 (RCP4.5), w.r.t. the present climate. In the historical period, soil moisture deficits rarely reach values 3x over the standard deviation, but projections reveal that for the RCP4.5 (RCP8.5) for the mid-century deficits up to 5x (6x) are projected to occur, and for the end-of-century even 7x for the RCP8.5. The annual cycle of soil moisture is in present and future climate determined by precipitation and potential evapotranspiration, and deficit is both enhanced and covers a wider monthly window in the future, especially for the RCP8.5. The surface humidity also decreases importantly, up to −4% and −8% in spring and summer in the end-of-the-century, in agreement with RCP4.5 and RCP8.5, respectively. Resulting from the projected changes in precipitation and potential evapotranspiration, the typical semi-arid climate, which in present climate is confined to a small south-eastern region of Portugal, is expected to cover almost 2/3 of the mainland in the case of RCP8.5. Finally, this study was developed in the framework of the National Roadmap for Adaptation XXI - Portuguese Territorial Climate Change Vulnerability Assessment for XXI Century (RNA2100) project and aims at delivering a deeper and different featuring of terrestrial water for adaptation purposes in a Mediterranean country.

A Mixed-Level Factorial Inference Approach for Ensemble Long-Term Hydrological Projections over the Jing River Basin

Abstract Long-term hydrological projections can vary substantially depending on the combination of meteorological forcing dataset, hydrologic model (HM), emissions scenario, and natural climate variability. Identifying dominant sources of model spread in an ensemble of hydrologic projections is critically important for developing reliable hydrological projections in support of flooding risk assessment and water resources management; however, it is not well understood due to the multifactor and multiscale complexities involved in the long-term hydrological projections. Therefore, a stepwise clustered Bayesian (SCB) ensemble method will be first developed to improve the performance of long-term hydrological projections. Meanwhile, a mixed-level factorial inference (MLFI) approach is employed to estimate multiple uncertainties in hydrological projections over the Jing River basin (JRB). MLFI is able to reveal the main and interactive effects of the anthropogenic emission and model choices on the SCB ensemble projections. The results suggest that the daily maximum temperature under RCP8.5 in the 2050s and 2080s is expected to respectively increase by 3.2° and 5.2°C, which are much higher than the increases under RCP4.5. The maximum increase of the RegCM driven by CanESM2 (CARM)-projected changes in streamflow for the 2050s and 2080s under RCP4.5 is 0.30 and 0.59 × 103 m s−3 in November, respectively. In addition, in a multimodel GCM–RCM–HM ensemble, hydroclimate is found to be most sensitive to the choice of GCM. Moreover, it is revealed that the percentage of contribution of anthropogenic emissions to the changes in monthly precipitation is relatively smaller, but it makes a more significant contribution to the total variance of changes in potential evapotranspiration and streamflow. Significance Statement Increasing concerns have been paid to climate change due to its aggravating impacts on the hydrologic regime, leading to water-related disasters. Such impacts can be investigated through long-term hydrological projection under climate change. However, it is not well understood what factor plays a dominant role in inducing extensive uncertainties associated with the long-term hydrological projections due to plausible meteorological forcings, multiple hydrologic models, and internal variability. The stepwise cluster Bayesian ensemble method and mixed-level factorial inference approach are employed to quantify the contribution of multiple uncertainty sources. We find that the total variance of changes in monthly precipitation, potential evapotranspiration, and streamflow can be mainly explained by the model choices. The identified dominant factor accounting for projection uncertainties is critically important for developing reliable hydrological projections in support of flooding risk assessment and water resources management. It is suggested that more reliable models should be taken into consideration in order to improve the projection robustness from a perspective of the Loess Plateau.

Topography regulates the responses of water partitioning to climate and vegetation seasonality

This study investigates the relationships between water partitioning, climate and vegetation dynamics, and their influencing factors, using a method combining scenario analysis and a modified Choudhury's formula that considers climate and vegetation seasonality. Comparing the results in ten major catchments in southwestern China with similar climate and vegetation but drastically different topography, shows that the climate and vegetation seasonality jointly control the variance in the catchment parameter n of the Choudhury's formula (R2 = 0.81 ± 0.13), which determines the amount of water being depleted through evapotranspiration under a given climate. What's interesting is that the relationships among the parameter n, climate and vegetation seasonality are affected obviously by the catchment's properties, such as the POK (portion of karst landform), MS (mean slope) and MTWI (mean topographic wetness index), NDVI and aridity index (AI). Notably, the parameter n is affected more (less) by climate and vegetation seasonality in catchments with better vegetation and drier climate (with steeper topography). Moreover, the relative contribution from the changes in precipitation (P) and potential evapotranspiration (PET) amount is negatively correlated to MS (r = 0.87, α < 0.05), and that from climate seasonality is positively correlated to MS (r = −0.81, α < 0.05), indicating that changes in P and PET amount are less important, but climate seasonality plays a more important role in controlling water partitioning in steeper catchments. The results demonstrate that the topography has an important role in influencing the responses of water partitioning to climate and vegetation seasonality.

Future Changes in Drought Frequency Due To Changes in the Mean and Shape of the PDSI Probability Density Function Under RCP4.5 Scenario

This study investigates the changes in the drought frequency in 2070–2099 relative to 1970–1999, due to the mean and shape changes of the probability density function (PDF) of the self-calibrated Palmer Drought Severity Index (PDSI), using CMIP5 multi-model historical simulations and projections under the RCP4.5 scenario. For severe droughts defined with PDSIs less than the 10th percentile, it is shown that over 41% of the global land, the increase in the severe drought frequency due to the shape change exacerbates the increase due to the mean change. Over 28% of the global land, the decrease in the drought frequency due to the shape change partially offsets the increase due to the mean change. Over 31% of the global land, the drought frequency increases due to the shape changes, but decreases due to the mean changes. The severe drought frequency due to both PDSI PDF mean and shape changes increases over almost the entire global land. We show that the PDSI standard deviation change is mainly determined by the mean precipitation change, while the PDSI mean change is determined by both mean precipitation and potential evapotranspiration changes. In particular, the PDSI standard deviation increases with the increase in mean precipitation which broadens the PDSI PDF, and thus enhances the severe drought frequency, and vice versa. On the other hand, the PDSI mean decreases with the decrease (increase) in mean precipitation (mean potential evapotranspiration). The difference in the attribution of drought frequency changes to the mean and shape changes over different regions can thus be largely explained by the mean precipitation and potential evapotranspiration changes. We also examine the moderate droughts defined with PDSIs between 10th and 20th percentiles in this study. For the moderate drought frequency, the spatial pattern of its changes due to the PDSI mean changes is similar to that of severe drought but with much smaller magnitudes, while its change in the spatial pattern due to the shape changes differs from severe drought with no significant changes. The moderate drought frequency due to both PDSI PDF mean and shape changes increases over 71% of the global land but decreases over 29% of the land.