Drought impacts, social organization, and public policies in northeastern Brazil: a case study of the upper Paraíba River basin

Non-conservative behavior of organic matter and its interaction with metals in an equatorial estuary, Brazil

Droughts are becoming more intense and frequent in the Brazilian semiarid because of El Niño and global climate changes. The Jaguaribe River estuary is a semiarid ecosystem that experiences a reduction in freshwater discharges due to droughts and river damming. The decrease in freshwater fluxes has increased metal availability through the water residence time increase in the Jaguaribe River estuary. Then, this study aimed to evaluate the dissolved organic matter quality and its interaction with metals in the Jaguaribe River estuary after a severe drought period. It was performed through carbon analyses, fluorescence spectroscopy, ultrafiltration technique, and determinations of metals by ICP-MS. Optical analysis showed that the dissolved organic carbon (DOC) was preponderantly composed of terrestrial-derived humic compounds, while the low ratio between the particulate organic carbon (POC) and chlorophyll-a indicated that POC was predominantly phytoplankton-derived. DOC and POC presented non-conservative removal during the estuarine mixing. DOM and dissolved elements were mostly distributed within the LMW fraction and presented a low percentage in the colloidal fraction. Li, Rb, Sr, Mo, and U showed conservative behavior, while Cu, Fe, Cr, and V had non-conservative behavior with a significant positive correlation with DOM, suggesting DOM as a relevant driver of metal availability at the Jaguaribe River estuary even during the rainy season.

Multi-datasets to monitor and assess meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes.

Evolution trend and hot topic measurement of climate migration research under the influence of climate change

Introduction

Global climate change, which is characterized by climate warming, has become one of the most prominent risk problems in society at present. Climate migration brings many accompanying problems to the environment, economy, politics, society, and culture. It is of great theoretical and practical significance to study the internal relationship between climate change and population migration.

Methods

The data were extracted from the Web of Science core collection database (WOS) and China Knowledge Network database (CNKI). A total of 785 documents and 157 documents in the field of climate migration from 2008 to 2021 were selected as analysis samples. Word frequency analysis, clustering analysis, sudden word detection analysis, and other methods were extensively used to build the evolution trend map of climate migration using CiteSpace visual bibliometric software.

Results

It is concluded that climate migration research has experienced three stages of development: initial exploration stage (2008-2011), development enrichment stage (2012-2017), and system deepening stage (2018).The hot topics of climate migration include: (1) different types of climate migration research; (2) Quantitative model research on climate migration; (3) Climate justice research. Different types of climate migration include 7 main types: (1) migration caused by sea level rise; (2) Resettlement caused by flood disaster; (3) Migration due to worsening drought; (4) Migration caused by extreme climate events; (5) Voluntary migration due to climate change discomfort; (6) Project resettlement caused by climate change response engineering measures; (7) Migrants whose livelihoods are broken due to climate change.

Discussion

The study points out that climate migration research is an interdisciplinary research field, which needs joint research by scholars from different academic backgrounds. In the future climate migration research, 1) strengthen the prediction ability of climate change population migration model; 2) Make use of China’s beneficial exploration in the migration fields such as engineering resettlement, ecological resettlement and poverty alleviation resettlement to formulate climate migration policies, regulations and strategic planning; 3) Establish a database cloud platform related to climate change and population migration; 4) Strengthen the exchange and cooperation between Chinese researchers in the field of climate migration and international scientific research institutions.

Remote sensing-based assessment of land degradation and drought impacts over terrestrial ecosystems in Northeastern Brazil

The spatio-temporal assessment of water and carbon fluxes in Brazil's Northeast region (NEB) allows for a better understanding of these surface flux patterns in areas with different vegetation physiognomies. The NEB is divided into four biomes: Amazon, Cerrado, Caatinga, and Atlantic Forest. Land degradation is a growing problem, particularly in susceptible areas of the Caatinga biome, such as the seasonally dry tropical forest. Furthermore, this region has experienced climatic impacts, such as severe droughts. Due to increasing human pressure, the Caatinga's natural land cover undergoes drastic changes, making it a region particularly vulnerable to desertification. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) estimates of evapotranspiration (ET) and gross primary production (GPP) were validated in two contrasting areas, dense Caatinga and sparse Caatinga, using eddy covariance (EC) data and then investigated their behavior over 21 years (2000-2021) for the NEB. MODIS products explained around 60% of the variations in ET and GPP, showing higher accuracy in dense Caatinga, while areas of sparse Caatinga presented the lowest GPP, indicating that land degradation has reduced the photosynthetic activity of the vegetation in this area. Based on the analysis of ET and GPP over 21 years, we observed a greater dependence of the sparse Caatinga on climate variability, demonstrating a stronger resilience of dense Caatinga to climate effects. In comparison with the other biomes of the NEB region, we found lower rates of ET and GPP in the Caatinga biome, with averages similar to the Sparse Caatinga. In comparison with the other biomes in the NEB region, we found the lowest averages of ET and GPP in the Caatinga biome, similar to values found in the sparse Caatinga. In forest areas, similar to the monitored DC, they allowed the Caatinga to behave closer to the other biomes present in the region.

Drought and society: Scientific progress, blind spots, and future prospects

Human activities have increasingly intensified the severity, frequency, and negative impacts of droughts in several regions across the world. This trend has led to broader scientific conceptualizations of drought risk that account for human actions and their interplays with natural systems. This review focuses on physical and engineering sciences to examine the way and extent to which these disciplines account for social processes in relation to the production and distribution of drought risk. We conclude that this research has significantly progressed in terms of recognizing the role of humans in reshaping drought risk and its socioenvironmental impacts. We note an increasing engagement with and contribution to understanding vulnerability, resilience, and adaptation patterns. Moreover, by advancing (socio)hydrological models, developing numerical indexes, and enhancing data processing, physical and engineering scientists have determined the extent of human influences in the propagation of drought hazard. However, these studies do not fully capture the complexities of anthropogenic transformations. Very often, they portray society as homogeneous, and decision-making processes as apolitical, thereby concealing the power relations underlying the production of drought and the uneven distribution of its impacts. The resistance in engaging explicitly with politics and social power-despite their major role in producing anthropogenic drought-can be attributed to the strong influence of positivist epistemologies in engineering and physical sciences. We suggest that an active engagement with critical social sciences can further theorizations of drought risk by shedding light on the structural and historical systems of power that engender every socioenvironmental transformation. This article is categorized under:Climate, History, Society, Culture > Disciplinary Perspectives.

Geospatial cluster analysis of the state, duration and severity of drought over Paraíba State, northeastern Brazil

Droughts threaten water resources, agriculture, socio-economic activities and the population at the global and regional level, so identifying areas with homogeneous drought behaviors is an important consideration in improving the management of water resources. The objective of this study is to identify homogenous zones over Paraíba State in relation to the state, duration and severity of droughts that have occurred over the last 20 years (1998-2017) using hierarchical cluster analysis based on both gauge-measured and Tropical Rainfall Measuring Mission (TRMM) estimated rainfall data (TMPA 3B42). The drought series were calculated using the Standardized Precipitation Index (SPI) based on eight time scales and were grouped according to drought state, duration and severity time series. The integrated results of state, duration and severity of droughts indicate that there is a basis for dividing Paraíba State into two major regions (a) Zone I, formed by Mata Paraibana and Agreste Paraibano, and (b) Zone II, composed by Borborema and Sertão Paraibano. This division is evident when assessing short-term droughts, but in the case of long-term droughts, Paraíba State has a high similarity in terms of drought state, duration, and severity. Factors such as proximity to the ocean, active climatic systems, and the local relief configuration were identified as influencing the drought regime. Finally, it is concluded that TMPA rainfall estimates represent a valuable source of data to regionalize and identify drought patterns over this part of Brazil and that other studies of this type should be carried out to monitor these phenomena based on other satellite-based rainfall data, including the Global Precipitation Mission (GPM).

Spatial multicriteria approach to support water resources management with multiple sources in semi-arid areas in Brazil

Semi-arid regions often face severe drought events that reduce agricultural and livestock production. In recent years, some international studies have used multicriteria decision analysis (MCDA) approaches combined with geographic information systems (GIS-MCDA) to support decision-makers in assessing the suitability of agricultural land for irrigation in semi-arid regions. Unlike previous studies, which have only considered a single source of water for crop irrigation, this study proposes a GIS-MCDA approach that considers all potentially available local water sources (e.g., groundwater, surface water, and wastewater) as possible alternatives for better multisource water resource management (MWRM) in regions facing water shortages. The geospatial multicriteria evaluation implemented in this study considers a series of technical, environmental, and agricultural productivity criteria using the analytical hierarchy process (AHP) method. Three independent baseline maps were generated, showing the spatial distribution of suitable areas for crop irrigation for each considered water source in the studied area. Surface water, groundwater, and wastewater offered suitable crop irrigation for 83%, 70%, and 26% of the study area, respectively. Overlapping these areas produced a final map showing all the feasible areas for each crop irrigation alternative at the same time. The MWRM approach considering all water sources increased the coverage of suitable areas to be irrigated in the study area by 2.2%, 20.4%, and more than 225% compared to considering surface water, groundwater, and wastewater, respectively, independently. The GIS-MCDA framework proposed in this study provides better support for decision-makers and stakeholders, favouring a reduction in possible conflicts over water scarcity, the diversification of irrigated crops, and an improvement in the quality-quantitative management of water resources in semi-arid regions.

Evaluation of the TRMM product for monitoring drought over Paraíba State, northeastern Brazil: a trend analysis

Droughts are complex natural phenomena that influence society's development in different aspects; therefore, monitoring their behavior and future trends is a useful task to assist the management of natural resources. In addition, the use of satellite-estimated rainfall data emerges as a promising tool to monitor these phenomena in large spatial domains. The Tropical Rainfall Measuring Mission (TRMM) products have been validated in several studies and stand out among the available products. Therefore, this work seeks to evaluate TRMM-estimated rainfall data's performance for monitoring the behavior and spatiotemporal trends of meteorological droughts over Paraíba State, based on the standardized precipitation index (SPI) from 1998 to 2017. Then, 78 rain gauge-measured and 187 TRMM-estimated rainfall time series were used, and trends of drought behavior, duration, and severity at eight time scales were evaluated using the Mann-Kendall and Sen tests. The results show that the TRMM-estimated rainfall data accurately captured the pattern of recent extreme rainfall events that occurred over Paraíba State. Drought events tend to be drier, longer-lasting, and more severe in most of the state. The greatest inconsistencies between the results obtained from rain gauge-measured and TRMM-estimated rainfall data are concentrated in the area closest to the coast. Furthermore, long-term drought trends are more pronounced than short-term drought, and the TRMM-estimated rainfall data correctly identified this pattern. Thus, TRMM-estimated rainfall data are a valuable source of data for identifying drought behavior and trends over much of the region.

Geospatial drought severity analysis based on PERSIANN-CDR-estimated rainfall data for Odisha state in India (1983-2018)

Studying the behavior of drought and its short-, medium- and long-term features throughout a region is very important for the creation of adequate public policies and actions aimed at the economic and social development of the region. Furthermore, the frequency and intensity of weather-related natural hazards (rainfall, heatwaves and droughts) are increasing every year, and these extreme weather-related events are potent threats worldwide, particularly in developing countries, such as India. Thus, this paper aims to evaluate the drought behavior in the Odisha region of India (1983-2018) by using the standardized precipitation index (SPI) and the new drought severity classification (DS). PERSIANN-CDR-estimated rainfall data were used to provide 271 time series, which were equally spaced at intervals of 0.25°, over Odisha state. The accuracy of these time series was evaluated with rain gauge-measured data at multiple time scales, and it was observed that the PERSIANN-CDR-estimated rainfall data effectively captured the pattern of rainfall over Odisha state. It was noted that almost half of the mean annual rainfall was concentrated in July and August. On addition, northeastern Odisha and areas near the coast were the rainiest regions. Furthermore, the drought pattern was evaluated based on nine distinct four-year periods (SPI-48), and the results indicated that there was high spatiotemporal variability in drought occurrence among those periods; e.g., in the last four years, extreme drought events occurred throughout the state. For the DS severity index analysis, it was noted that the values tended to be more significant with the increase in the drought time scale. For short-term droughts, DS values were less significant throughout the region, whereas for the medium-term droughts, there was an increase in the DS values in all regions of Odisha, especially in the north-central region. For long-term droughts, the values were more significant throughout the region, especially in the areas with the highest rainfall levels. Finally, the PERSIANN-CDR data should also be analyzed in other regions of India, and the obtained results are useful for the identification of droughts throughout the region and for the management of water resources and can be replicated in any part of the world.