Longer Dry Spells Research Articles

Prolonged drought moderates flood effects on soil nutrient pools across a rainfall gradient

Climate change is manifesting through increased intensity and frequency of extreme events such as droughts and floods. Drought causes significant stress by limiting water availability, resulting in reduced plant growth and belowground carbon (C) inputs as well as plant nutrient uptake and microbial activity, thus impacting C and nutrient cycling. Severe floods can increase leaching of nutrients, which affect nutrient availability for plants and microorganisms potentially compounding drought-induced effects on C and nutrient cycles. However, few studies have assessed the interactions between drought and floods, constraining our ability to predict ecosystem-level effects of projected climate shifts toward fewer but larger rainfall events with longer dry spells between events. We conducted a study to assess how long-term drought moderates the effect of flooding on soil C, nitrogen (N) and phosphorus (P) pools across a rainfall gradient in south-eastern Australia. We collected soil monoliths from field rainfall manipulation facilities with a 5–7 years history of simulated reduced rainfall at three sites representing a rainfall gradient (∼200–800 mm) and exposed them to a 1-in-100-year flood event under laboratory conditions. We assessed nutrients and C in soil and microbial pools before and after the flood and in flood-induced leachates. The results showed that flooding caused significantly greater losses of N in leachates, with greater effect sizes in the drought treatments compared to ambient rainfall. This response was particularly pronounced for nitrate (152 % increase on average), especially at the site with the highest mean annual precipitation (>25-fold increase). This suggest that drought may significantly reduce the capacity of ecosystems to retain N following flood events, particularly in mesic ecosystems where C and nutrient pools are greater.

Heuristic data-inspired scheme to characterize meteorological and groundwater droughts in a semi-arid karstic region under a warming climate

Study regionThe Edwards Aquifer Region is located in south-central Texas United States.Study focusThe paper focuses on the development and implementation of a data-inspired heuristic drought identification scheme to (i) quantify the intensity, duration, and frequency of precipitation deficit- and high temperature-driven meteorological droughts (PMet- and TMet-droughts), and (ii) link their propagation to groundwater droughts (GW-droughts) using baseline hydroclimatic measures and prevailing drought conditions derived from historical climate data and regional mitigation strategies.New hydrological insights for the regionBased on the intensity, duration, and timing of PMet- and TMet-droughts in the semi-arid karstic region, we identified three distinct GW-droughts, including persistence-driven, preconditions-driven, and intensity-driven droughts. The analysis revealed that successive heavy precipitation events are needed to end GW-droughts. The scheme also identified TMet-droughts with the longest dry spells, TMet- and PMet-droughts with the highest intensity, and GW-drought with the second-highest intensity on record all occurred over the past 15 years. These findings provide evidence for a warming climate, intensified meteorological droughts, and increasing stress on the aquifer. Among the artificial intelligence models used, Extremely Randomized Trees (ERT) regressor predicted time series of intensity & duration of GW-droughts from hydroclimatic features with high accuracy. The ERT classifier revealed that the duration of PMet droughts and the intensity of TMet droughts are the topmost decisive features in predicting GW-drought intensity in the region.

Effects of Meteorological Conditions and Irrigation Levels during Different Growth Stages on Maize Yield in the Jing-Jin-Ji Region

Maize is a major crop that is particularly sensitive to climate change. In addition, the extreme shortage of water resources threatens crop production. Thus, improving the effective utilization rate of water is an important problem to discuss. In this regard, we quantified the combined effects of meteorological conditions and irrigation levels during different growth stages on city-level maize yields in the Jing-Jin-Ji region from 1993 to 2019. The results show that the sowing period was affected by the minimum temperature, while the other growth stages were affected by the maximum temperature. At the ear stage of summer maize, when the effective irrigation rate reached the average level (52%), the inflection point of the total precipitation was 401.42 mm in the Jing-Jin-Ji region. When the total precipitation was higher than 401.42 mm, the summer maize yield decreased with the increasing total precipitation. Furthermore, the summer maize growth was significantly affected by drought at the seedling stage. At high effective irrigation rates and over long dry spells, as the mean daily temperature during dry spells increased, the maize yield easily increased. The increase in the effective irrigation rate can reverse the decrease in the summer maize yield. Moreover, the effective irrigation rate increased the maize yield with the increase rise in the temperature during longer dry spells, but the maize yield decreased with warmer temperatures during shorter dry spells. As such, our evaluation results will be useful for assessing food security and moving gradually toward achieving a water–energy–food nexus.

Fiber Quality, Yield, and Profitability of Cotton in Response to Supplemental Irrigation with Treated Wastewater and NPK Fertilization

Cotton yield under the rainfed farming system in tropical semi-arid regions is significantly decreased by prolonged dry spells. In this context, supplemental irrigation (SI) with treated wastewater emerges as a strategy for the sustainability of agricultural production besides contributing to the reduction of fertilizer costs. The objective of this research was to evaluate the productivity, photosynthetic parameters, fiber quality, and profitability of cotton cultivation, under supplemental irrigation (SI) with municipal treated wastewater (MTW), with and without mineral fertilization. The treatments consisted of three water scenarios (normal, drought, and severe drought), defined by the historical series of precipitation data of 30 years, and two treatments of supplemental irrigation with MTW, with or without NPK fertilization. SI with treated wastewater increased cotton yield in all three scenarios (normal, drought, and severe drought) by approximately 29%, 255%, and 251%. Longer dry spells in drought and severe drought scenarios increased the volume of SI with MTW, resulting in greater nutrient input to the soil, improved photosynthetic response, higher physical water productivity, reduction in fertilizer costs, and higher farmers’ income. Therefore, our results show the importance of using treated wastewater in supplemental irrigation of cotton under scenarios of water scarcity in tropical semi-arid regions.

Hydrological Intensification Will Increase the Complexity of Water Resource Management

AbstractGlobal warming intensifies the hydrological cycle by altering the rate of water fluxes to and from the terrestrial surface, resulting in an increase in extreme precipitation events and longer dry spells. Prior hydrological intensification work has largely focused on precipitation without joint consideration of evaporative demand changes and how plants respond to these changes. Informed by state‐of‐the‐art climate models, we examine projected changes in hydrological intensification and its role in complicating water resources management using a framework that accounts for precipitation surplus and evaporative demand. Using a metric that combines the difference between daily precipitation and daily evaporative demand (surplus events) and consecutive days when evaporative demand exceeds precipitation (deficit time), we show that, globally, surplus events will become larger (+11.5% and +18.5% for moderate and high emission scenarios, respectively) and the duration between them longer (+5.1%; +9.6%) by the end of the century, with the largest changes in the northern latitudes. The intra‐annual occurrence of these extremes will stress existing water management infrastructure in major river basins, where over one third of years during 2070–2100 under a moderate emissions scenario will be hydrologically intense (large intra‐annual increases in surplus intensity and deficit time), tripling that of the historical baseline. Larger increases in hydrologically intense years are found in basins with large reservoir capacity (e.g., Amazon, Congo, and Danube River Basins), which have significant populations, irrigate considerable farmland, and support threatened and endangered aquatic species. Incorporating flexibility into water resource infrastructure and management will be paramount with continued hydrological intensification.

Future precipitation changes in Egypt under the 1.5 and 2.0 °C global warming goals using CMIP6 multimodel ensemble

Rainfall projections for 1.5 and 2.0 °C warming can explain regional precipitation response to emission reductions under the Paris Agreements' goals. Assessment of such changes is vital for Egypt, a global climate change hotspot. The performance of 29 CMIP6 GCMs' hindcasts was evaluated according to their capability to replicate the spatial patterns of annual, winter, and summer precipitation for 1971–2014 to select a suitable GCM subset to form a robust multimodel ensemble (MME). The MME median was used to project precipitation and precipitation extremes of Egypt at the end of the century (2081–2100) for two shared socioeconomic pathways (SSP) scenarios, SSP1–1.9 and SSP1–2.6, representing 1.5 and 2.0 °C warming at the end of the present century, respectively. The results showed an increase in precipitation in the northern high precipitation region by 37% and 54% for SSP1–1.9 and SSP1–2.6, respectively, and a decrease in the southwestern low precipitation region by −35% for both scenarios. The projected increase would be mostly in winter and almost no change in summer. The projection of precipitation extremes revealed an increase in extreme precipitation amount in the northern coast between 0% and 14% and the longest dry spell over most of the country by 160%. The results indicate more heterogeneity in the spatial distribution in Egypt's precipitation, increasing extreme precipitation amount in some regions and dry spell length over the whole country. The results indicate a large increase in hydrological hazard susceptibility in Egypt, even if the global warming can be limited to 2 °C at the end of the century following the Paris Agreement.

English

This work aims at characterizing the conditional probability of single or consecutive dry and wet days in West Africa using the first-order Markov chain approach during the monsoon season (June to October). The results show that the probabilities of having a wet day (PW), a wet day preceded by another wet day (PWW) and a wet day preceded by a dry day (PDW) are stronger in regions where the rainfall is maximum (mountain regions). In contrast, the probabilities of having a dry day (PD), a dry day preceded by a wet day (PWD) and a dry day preceded by another dry day (PDD) are lower in the regions with higher precipitation. The seasonal cycle of PWW (PDD) is consistent with that of PW (PD), respectively in Western Sahel and Central Sahel regions. At the interannual timescale, MK test results show that PW and PDW (PD and PDD) exhibit statistically significant increasing (decreasing) trends the Western Sahel and the Central Sahel. Besides, the shorter dry spells (3 days) show statistically significant decreasing trends only in the Western Sahel. The longer dry spells (5, 7 and 10 days) show statistically significant downward trends over the Western and Central Sahel. Wet spells probabilities show non-significant decreasing trends in all sub-domains, except in the Western Sahel for the 10 days spells. Knowledge of theses probabilities will contribute to develop efficient strategies for water resources management and agricultural decision making in West African countries. Key words: Markov chain, rainfall, occurrence, wet spell, dry spell, West Africa.

Future Changes in Wet and Dry Season Characteristics in CMIP5 and CMIP6 simulations

AbstractClimate change will result in more dry days and longer dry spells, however, the resulting impacts on crop growth depend on the timing of these longer dry spells in the annual cycle. Using an ensemble of Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6) simulations, and a range of emission scenarios, here we examine changes in wet and dry spell characteristics under future climate change across the extended tropics in wet and dry seasons separately. Delays in the wet seasons by up to two weeks are projected by 2070-2099 across South America, Southern Africa, West Africa and the Sahel. An increase in both mean and maximum dry spell length during the dry season is found across Central and South America, Southern Africa and Australia, with a reduction in dry season rainfall also found in these regions. Mean dry season dry spell lengths increase by 5-10 days over north-east South America and south-west Africa. However, changes in dry spell length during the wet season are much smaller across the tropics with limited model consensus. Mean dry season maximum temperature increases are found to be up to 3°C higher than mean wet season maximum temperature increases over South America, Southern Africa and parts of Asia. Longer dry spells, fewer wet days, and higher temperatures during the dry season may lead to increasing dry season aridity, and have detrimental consequences for perennial crops.

Combined heat and drought suppress rainfed maize and soybean yields and modify irrigation benefits in the USA

Heat and water stress can drastically reduce crop yields, particularly when they co-occur, but their combined effects and the mitigating potential of irrigation have not been simultaneously assessed at the regional scale. We quantified the combined effects of temperature and precipitation on county-level maize and soybean yields from irrigated and rainfed cropping in the USA in 1970–2010, and estimated the yield changes due to expected future changes in temperature and precipitation. We hypothesized that yield reductions would be induced jointly by water and heat stress during the growing season, caused by low total precipitation (P GS) and high mean temperatures (T GS) over the whole growing season, or by many consecutive dry days (CDD GS) and high mean temperature during such dry spells (T CDD) within the season. Whole growing season (T GS, P GS) and intra-seasonal climatic indices (T CDD, CDD GS) had comparable explanatory power. Rainfed maize and soybean yielded least under warm and dry conditions over the season, and with longer dry spells and higher dry spell temperature. Yields were lost faster by warming under dry conditions, and by lengthening dry spells under warm conditions. For whole season climatic indices, maize yield loss per degree increase in temperature was larger in wet compared with dry conditions, and the benefit of increased precipitation greater under cooler conditions. The reverse was true for soybean. An increase of 2 °C in T GS and no change in precipitation gave a predicted mean yield reduction across counties of 15.2% for maize and 27.6% for soybean. Irrigation alleviated both water and heat stresses, in maize even reverting the response to changes in temperature, but dependencies on temperature and precipitation remained. We provide carefully parameterized statistical models including interaction terms between temperature and precipitation to improve predictions of climate change effects on crop yield and context-dependent benefits of irrigation.

How does El Niño Southern Oscillation affect rice-producing environments in central Colombia?

The rice industry plays an important role in the agricultural economy of Colombia and its success dependents largely on weather conditions. Rice farmers, policymakers and other stakeholders thus need to understand and manage the risks associated with climate variability, including those related to El Niño Southern Oscillation (ENSO) – the most important source of variability affecting Colombian climates. The objectives of this study were to (1) assess the ENSO influence on the spatio-temporal variability of agro-climatic conditions (crop water requirements, dry and wet spells, and heatwaves) and rice yield across the central producing region of Colombia; and (2) identify the main agro-climatic factors driving crop yield variability. Results showed that rice irrigation water requirements under positive ENSO phases (El Niño) increased by up to 14% compared to the long-term average. These increases were associated with less total precipitation, more dry days and longer dry spells, together with a greater number of day-and-night heatwave episodes. During negative phases (La Niña), on the other hand, irrigation requirements decreased by 16% with respect to the long-term average due to longer and more frequent wet spells, and more total precipitation. Analyses of simulated yields indicated that El Niño years reduce crop yield in about 86% of the study region, while La Niña affects 62% of the region positively. The number of heat nights (i.e. nights with minimum temperature > 23°C) during the growing season was the most important agro-climatic factor causing yield losses during ENSO events. Our results represent an important step towards understanding the interaction between climate variability and rice production in Colombia, which is useful for improving climate risk management at local levels.

Spatial and temporal analysis of mean and frequency variations of dry spells in Iran

For probabilistic modeling of variations in averages and frequencies of length of dry spells in Iran and obtaining a set of suitable patterns in this relation, the data on daily precipitation from 41 synoptic meteorological stations for a 30-year period (1989-2018) were obtained from the Iran Meteorological Organization. A dry spell is defined as a sequence of consecutive dry days with precipitation equal to or less than 0.1 mm per day. In order to evaluate the probabilistic distribution of the mean length and frequency of short (1-10 days), medium (11-20 days), and long dry spells (21-30 days), a first-order Markov chain model, a second-order Markov chain model, an exponential distribution model, and a negative binomial distribution were used. The results showed that there were longer dry spells at more southern latitudes and shorter dry spells at more northern latitudes in Iran. At an annual scale, the longest dry spell in southeastern Iran was 351 days and the longest in northern Iran was 37 days. Simulation of seasonal variations in mean and frequency of different lengths of dry spells using the four probabilistic models showed that the exponential and the negative binomial distributions gave the closest approximations to the empirical mean of the length of dry spells at the studied stations. However, these estimates were relatively simulated well only for mean length of dry spells that lasted less than 10 days and were not simulated well at all for dry spells with lengths of more than 10 days. Moreover, considering that the average frequencies of medium dry spells (11-20 days) and long dry spells (21-30 days) indicated the length and severity of dry spells in different parts of Iran, it was observed that the exponential and negative binomial distributions provided closer approximations to the empirical averages compared to the other two models. In general, we can conclude that the selected models performed poorly in simulating the average length of dry spells but performed better in simulating the average number of short, medium, and long dry spells.

Changing Trends in Rainfall Extremes in the Metropolitan Area of São Paulo: Causes and Impacts

This study analyses observed trends in extreme rainfall events in the Metropolitan Area of São Paulo (MASP). Rainfall data sets with more than 60 years of record in MASP are used. In MASP, extreme rainfall events represent hydro meteorological hazards that trigger flash floods and landslides. Changes in rainfall extremes can be partly due to natural climate variability. In addition, it can also be related to global warming and/or urbanization. Total annual precipitation and the number of days with precipitation of 20 mm exhibit the largest significant increase during 1930-2019. This is better noticed during summer. This tendency is also noticed in the number of days with precipitation of 100 mm or more. Therefore, the positive trend in annual precipitation is mainly due to an increase in the frequency of extreme precipitation events. On the other hand, our analysis shows that the number of consecutive dry days increased. Though these results appear to be contradictory, they indicate an important climate change in recent times. Intense precipitation is concentrated in few days, separated by longer dry spells. The focus is on how atmospheric circulation variations are contributing to these changes. During 1960-2019 the South Atlantic Subtropical Anticyclone has intensified and slightly moved southwestward of its normal position. This change influences the transport of humidity and therefore impact precipitation. This can explain the increase in the precipitation extremes in the MASP. However, other atmospheric systems may also be important.

Ecological strategies begin at germination: Traits, plasticity and survival in the first 4 days of plant life

Abstract We commonly use trait variation to characterize plant function within and among species and understand how vegetation responds to the environment. Seedling emergence is an especially vulnerable window affecting population and community dynamics, yet trait‐based frameworks often bypass this earliest stage of plant life. Here we assess whether traits vary in ecologically meaningful ways when seedlings are just days old. How do shared evolutionary history and environmental conditions shape trait expression, and can traits explain which seedlings endure drought? We measured seedling traits in the first 4 days of life for 16 annual plant species under two water treatments, exploring trait trade‐offs, species‐level plasticity and the ability of traits to predict duration of survival under drought. Nearly half of traits showed the imprint of evolutionary history (i.e. significant phylogenetic signal), often reflecting differences between grasses and forbs, two groups separated by a deep evolutionary split. Water availability altered trait expression in most cases, though species‐level plastic responses also reflected evolutionary history. On average, new seedlings exhibited substantial trait variation structured as multiple trade‐offs like those found in mature plants. Some species invested in thick roots and shoots, whereas others invested in more efficient tissues. Separately, some invested in tougher roots and others in deeper roots. We also observed trade‐offs related to growth rates (fast or slow) and biomass allocation (above‐ or below‐ground). Drought survival time was correlated most strongly with seed mass, root construction and allocation traits, and phylogeny (grasses vs. forbs). Synthesis. Our results show that seed and seedling trait variation among annual species is substantial, and that a few attributes could capture major dimensions of ecological strategies during emergence. With seedling survival times ranging twofold among annuals (from 7.5 to 14.5 days), these strategies could mitigate recruitment responses to more frequent or longer dry spells. Multivariate trait and plasticity strategies should be further explored in studies designed to assess trait‐fitness linkages during recruitment. A free Plain Language Summary can be found within the Supporting Information of this article.

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Testing two methods for mapping water hyacinth (Eichhornia crassipes) in the Greater Letaba river system, South Africa: discrimination and mapping potential of the polar-orbiting Sentinel-2 MSI and Landsat 8 OLI sensors

ABSTRACTEarly detection and mapping of the spatio-temporal distribution of invasive water hyacinth (Eichhornia crassipes) in inland hydrological systems are vital for a number of water resource management-related reasons. Field surveys and current climate change projections (associated with longer dry spells, and shortened rain seasons) have shown that climate change and the rapid spread of aquatic invasive species are increasingly affecting inland surface water availability in semi-arid regions of Southern Africa. It is upon this premise that accurate, reliable, and timely information on the spatio-temporal distribution and configuration of water hyacinth is required in tracing their evolution and propagation in affected areas as well as in potential vulnerable areas. This work, therefore, attempts to test two robust push-broom multispectral sensors: Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) in identifying, detecting, and mapping the spatial distribution and configuration of invasive water hyacinth in a river system. The results of the study show that water hyacinth in small reservoirs can be mapped with an overall accuracy of 68.44% and 77.56% using Landsat 8 and Sentinel-2 data, respectively. The results further demonstrated the blue, red, red edge (RE) 1, short-wavelength infrared (SWIR)-1, and SWIR-2 of both satellite data sets as the critical and outstanding spectral regions in detecting and mapping water hyacinth from other land-cover types. Overall, the study highlights the unexploited prospects of the new noncommercial multispectral sensors in monitoring invasive species infestation from inland surface waterbodies in semi-arid regions (i.e. smaller reservoirs).

Two Simple Metrics for Quantifying Rainfall Intermittency: The Burstiness and Memory of Interamount Times

Abstract Precipitation displays a remarkable variability in space and time. An important yet poorly documented aspect of this variability is intermittency. In this paper, a new way of quantifying intermittency based on the burstiness B and memory M of interamount times is proposed. The method is applied to a unique dataset of 325 high-resolution rain gauges in the United States and Europe. Results show that the M–B diagram provides useful insight into local precipitation patterns and can be used to study intermittency over a wide range of temporal scales. It is found that precipitation tends to be more intermittent in warm and dry climates with the largest observed values in the southwest of the United States (i.e., California, Nevada, Arizona, and Texas). Low-to-moderate values are reported for the northeastern United States, the United Kingdom, the Netherlands, and Germany. In the second half of the paper, the new metrics are applied to daily rainfall data for 1954–2013 to investigate regional trends in intermittency due to climate variability and global warming. No evidence is found of a global shift in intermittency but a weak trend toward burstier precipitation patterns and longer dry spells in the south of Europe (i.e., Portugal, Spain, and Italy) and an opposite trend toward steadier and more correlated precipitation patterns in Norway, Sweden, and Finland is observed.

Nitrogen and Phosphorus Removal in a Rain Garden Flooded with Wastewater and Simulated Stormwater

Rain gardens, also known as bioretention cells, are low-impact developments designed to mitigate several problems associated with urban stormwater. This four-month field study involved a rain garden at a wastewater treatment plant in north-central Texas in the United States of America. Partially treated wastewater from an anaerobic digester spilled into the rain garden at the beginning of the study. Subsequently, inflow and outflow concentrations of nitrogen and phosphorus were measured for nine simulated floods, preceded by dry-spell intervals of 5, 8, or 12 days. Despite large inputs from the wastewater spill, the rain garden gradually processed and flushed the nitrogen. Longer dry spells tended to produce relatively higher outflow nitrate concentrations. A large pool of phosphorus in the soil restricted the rain garden's ability to reduce outflow orthophosphate concentrations, which were stable and lower than inflow concentrations throughout the study; however, adsorptive processes attenuated a relatively high inflow concentration by the end of the study.

Análisis espacial y temporal de las sequías en el nordeste de Brasil

El nordeste de Brasil (NEB) es una región afectada por sequías que causan severos impactos sobre los sectores agrícola, hidroeléctrico y de abastecimiento hídrico. Se evaluaron las características más relevantes de las sequías severas acaecidas en el NEB entre 1901-2010 (en lo sucesivo, rachas secas). Se empleó el índice de precipitación estandarizada para medir la anomalía de la precipitación acumulada a escala trimestral (SPI-3). Los patrones subyacentes que configura el SPI-3 en el dominio espacio-temporal, se identificaron aplicando un análisis por componentes principales seguido de un análisis de conglomerados. La periodicidad de las rachas secas se evaluó aplicando un análisis de ondoleta. Entre los resultados, destacan: i) las rachas secas más extensas se ajustan a cuatro patrones espaciales que se intercalan en el tiempo; ii) el área afectada por rachas secas, a escala mensual, tiene un periodo aproximado de 10 meses, mientras que el número de eventos por año muestra periodos de entre 2 y 8, 10 y 30 años, respectivamente; iii) las rachas secas en cuanto a su duración, cantidad de eventos por año, recurrencia mensual y área afectada por estos eventos no muestran tendencias de largo plazo, aunque los episodios más extensos inciden con más frecuencia en la temporada húmeda.

A framework for assessing hydrological regime sensitivity to climate change in a convective rainfall environment: a case study of two medium-sized eastern Mediterranean catchments, Israel

Abstract. A modeling framework is formulated and applied to assess the sensitivity of the hydrological regime of two catchments in a convective rainfall environment with respect to projected climate change. The study uses likely rainfall scenarios with high spatiotemporal resolution that are dependent on projected changes in the driving regional meteorological synoptic systems. The framework was applied to a case study in two medium-sized Mediterranean catchments in Israel, affected by convective rainfall, by combining the HiReS-WG rainfall generator and the SAC-SMA hydrological model. The projected climate change impact on the hydrological regime was examined for the RCP4.5 and RCP8.5 emission scenarios, comparing the historical (beginning of the 21st century) and future (mid-21st-century) periods from three general circulation model simulations available from CMIP5. Focusing on changes in the occurrence frequency of regional synoptic systems and their impact on rainfall and streamflow patterns, we find that the mean annual rainfall over the catchments is projected to be reduced by 15% (outer range 2–23%) and 18% (7–25%) for the RCP4.5 sand RCP8.5 emission scenarios, respectively. The mean annual streamflow volumes are projected to be reduced by 45% (10–60%) and 47% (16–66%). The average events' streamflow volumes for a given event rainfall depth are projected to be lower by a factor of 1.4–2.1. Moreover, the streamflow season in these ephemeral streams is projected to be shorter by 22% and 26–28% for the RCP4.5 and RCP8.5, respectively. The amplification in reduction of streamflow volumes relative to rainfall amounts is related to the projected reduction in soil moisture, as a result of fewer rainfall events and longer dry spells between rainfall events during the wet season. The dominant factors for the projected reduction in rainfall amount were the reduction in occurrence of wet synoptic systems and the shortening of the wet synoptic systems durations. Changes in the occurrence frequency of the two dominant types of the regional wet synoptic systems (active Red Sea trough and Mediterranean low) were found to have a minor impact on the total rainfall.

Regional differences in aridity/drought conditions over Northeast Brazil: present state and future projections

The focus of this study is to investigate the risk of aridification in the semiarid lands of Northeast Brazil, using a variety of observational information and climate change projections for the future, by means of aridity indices. We use the Budyko and United Nations aridity indices to assess the extent of areas with semi-arid and arid conditions in the present, and for the future out to 2100. Climate projections are derived from the downscaling of the HadCM3 model for the A1B scenario using the Eta regional model with horizontal resolution of 40 km. Consistent with global climate model projections from IPCC AR5, regional climate change projections suggest an increase in dryness in the region, with rainfall reductions, temperature increases and water deficits and longer dry spells, leading to drought and arid conditions expected to prevail by the second half of the 21th century. The area with arid conditions is projected to grow to cover areas currently with dry sub humid conditions, and become larger by 2100. This increase in aridity, combined with land degradation may increase the risk of desertification.