Drought Hazard Research Articles

Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka

For Sri Lanka, as an agricultural country, a methodical drought monitoring mechanism, including spatial and temporal variations, may significantly contribute to its agricultural sustainability. Investigating long-term meteorological and agricultural drought occurrences in Sri Lanka and assessing drought hazard at the district level are the main objectives of the study. Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), and Vegetation Health Index (VHI) were used as drought indicators to investigate the spatial and temporal distribution of agriculture and meteorological droughts. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data from 1989 to 2019 was used to calculate SPI and RAI. MOD13A1 and MOD11A2 data from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2019, were used to generate the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Agricultural drought monitoring was done using VHI and generated using the spatial integration of VCI and TCI. Thus, various spatial data analysis techniques were extensively employed for vector and raster data integration and analysis. A methodology has been developed for the drought declaration of the country using the VHI-derived drought area percentage. Accordingly, for a particular year, if the country-wide annual extreme and severe drought area percentage based on VHI drought classes is ≥30%, it can be declared as a drought year. Moreover, administrative districts of Sri Lanka were classified into four hazard classes, No drought, Low drought, Moderate drought, and High drought, using the natural-beak classification scheme for both agricultural and meteorological droughts. The findings of this study can be used effectively by the relevant decision-makers for drought risk management (DRM), resilience, sustainable agriculture, and policymaking.

Construction and application of comprehensive drought index based on uncertainty cloud reasoning algorithm.

The establishment of comprehensive drought index is a fundamental task for the analysis of drought hazard system evolution. To fully explore the characteristics of drought variation process, the cloud uncertainty reasoning method was applied to construct comprehensive drought index integrating precipitation with soil moisture indicators. The application results of the proposed drought index in Anhui Province, China revealed that, (1) The overall drought evolution presented significant intensifying trend with the drought occurrence frequency increasing from 32% to 41% from south to north in Anhui Province, and the primary drought type in the northern area was moderate-level drought events and above, while the drought type in the central and southern region was dominated by light-level drought events. (2) Autumn drought was the dominant type from 1960 to 2007 in Anhui Province, with the average drought occurrence frequency of 40%. In addition, the evolution of spring and autumn drought all presented intensifying trends from 1960 to 2007, while the summer and winter drought evolution trends were opposite. (3) The Mann-Kendall trend test results revealed that the drought evolution presented evidently intensifying trend from August 1967 to February 1969, but slight declining trend from May 1974 to August 1978, July 1989 to August 2001 and February 2003 to December 2007, and the mutation of drought evolution occurred in November 1972, February 1978 and August 1998, etc. The above results were basically consistent with the historical statistics, indicating that the proposed comprehensive drought index and its construction framework were reliable, which can be further applied in the related research field of regional drought risk management.

Impact of Climate Change on Worlds Economy and Hydrological System

The Mediterranean region appears to be particularly responsive to global and climate change. The global mean temperature has increased by 0.8°C compared with preindustrial levels while Europe has warmed more than the global average, especially in the Mediterranean, the north-east region, and mountain areas. Increasingly drier conditions are observed in the Mediterranean region both in the wet and in the dry season (~20%) with an increasingly irregular precipitation in both seasons (~ 40% in the dry season). The annual river flows have also decreased in the Mediterranean region, a difference projected to exacerbate due to climate and global change, which made the Mediterranean region most prone to an increase in drought hazard and water stress. Iberian Peninsula has been already affected by several major droughts, e.g. the recent one in 2005. These driving forces of global change impacts on water availability, water quality, and ecosystem services in Mediterranean river basins of the Iberian Peninsula, as well as their impacts on the human society and economy, makes it an important issue on the EU agenda. This thesis is an approach to quantify and analyze the water quantity, hydrological ecosystem services, and water supply in temperate regions under environmental changes. A hydrological model is developed for a low flow Mediterranean river (Francolí River) to assess the water allocation situation in the river basin using MIKE BASIN. Since the Mediterranean regions are hard hit by the changes in the global climatic patterns, the hydrological model focuses on the water distribution system & flow in the region.

Agricultural drought risk assessment in upper progo watershed using multi-temporal landsat 8 imagery

Upper Progo watershed is one of the important agricultural areas in Temanggung Regency, Central Java. This research used the data obtained from Landsat 8 imagery to analyze the agricultural drought risk in the watershed. The hazard was analyzed using multi-temporal data every 16 days (to the Landsat 8’s temporal resolution) during the drought; from May to September 2015 combining the Landsat 8 imagery and the land’s physical condition. An agricultural drought hazard map was then created by summing the hazard class score in every recording time with overlay method. The crop’s vulnerability analyzed using NDVI difference, which indicates the crop’s ability to survive in dry conditions. The crop’s vulnerability was also analyzed every 16 days. A vulnerability map was then created by summing the vulnerability class of every recording time. The assessment of the drought risk was done by multiplying the hazard and the vulnerability scores. The result shows the high and very high classes of agricultural drought risk were located on the west research area which had a high class of hazard and vulnerability. Meanwhile, the moderate, low, and very low classes of agricultural risk were distributed evenly in the center and east area.

Development of a PCA-Based Vulnerability and Copula-Based Hazard Analysis for Assessing Regional Drought Risk

Vulnerability and hazard are terms that are generally applied to drought risk assessment. Vulnerability can be defined as the capacity of a region to cope with and resist the impacts of natural hazards, while hazard can be defined as the likelihood of a natural or human-induced physical event. In this study, principal component analysis (PCA) was used to generate an aggregate drought vulnerability index (DVI) using multiple socio-economic indicators and copula-based drought frequency analysis was performed to calculate a drought hazard index (DHI) considering meteorological drought occurrence patterns. Finally, regional drought risk was evaluated by combining the DVI and DHI among cities within the Chungcheong province, South Korea. Based on the drought risk index (DRI), Jecheon-si (DRI = 0.50) and Gongju-si (DRI = 0.65) were identified as the most hazardous cities in Chungcheongbuk-do and Chungcheongnam-do, respectively. The overall process of drought risk assessment developed in this study is useful for planning drought management and mitigation at the local level.

Quantitative assessment of soybean drought risk in Bengbu city based on disaster loss risk curve and DSSAT

Drought loss risk curves can quantitatively assess regional drought and indicate the mechanism of drought hazards. In this study, the drought events were identified using the run theory based on Standard Precipitation Index (SPI) and Composite meteorological drought Index (CI) separately calculated by daily weather data during 1955–2012. The frequency of drought events was calculated by using the Copula function. The yield loss of soybeans under different irrigation levels in dry years was simulated by DSSAT-CROPGRO-soybean model. Finally, the regional drought risk for soybeans in Bengbu city was analyzed by constructing a series of relationship curves among the drought frequency, soybean drought loss, and the irrigation level. The results indicated that (1) both the SPI and CI were applicable to identifying drought events in the selected city, but SPI was more sensitive in identifying short-term drought events, and CI was more reliable in recognizing medium-term drought events. (2) The frequency of drought events during the target crop's growing period and the corresponding yield loss rate satisfied the semi-logarithmic function, and the average values of their determinant coefficients were 0.68 and 0.74 based on SPI and CI, respectively. (3) Irrigation could significantly reduce soybean yield loss in non-extreme drought events. Therefore, drought loss risk curves can reflect regional drought risk more quantitatively and facilitate the assessment and management of regional drought risk.

Spatio-temporal analysis of meteorological and hydrological droughts in the Euphrates Basin, Turkey

Abstract In this study, the aim was to measure changes in the spatio-temporal distribution of a potential drought hazard area and determine the risk status of various meteorological and hydrological droughts by using the kriging, radial basis function (RBF), and inverse distance weighting (IDW) interpolation methods. With that goal, in monthly, three-month, and 12-month time periods drought indices were calculated. Spatio-temporal distributions of the droughts were determined with each drought index for the years in which the most severe droughts were experienced. According to the results, the basin is under risk of meteorological drought due to the occurrence of severe and extreme droughts in most of the area, and especially in the north, during the monthly and three-month time periods. During the 12-month period, it was found that most of the basin is under risk of hydrological drought due to the occurrence of severe and extreme droughts, especially in the southern parts. The most effective interpolation method for the prediction of meteorological and hydrological droughts was determined as kriging according to the results of the cross-validation test. It was concluded that a drought management plan should be made, and early warnings and precautions should be applied in the study area.

A slow rainy season onset is a reliable harbinger of drought in most food insecure regions in Sub-Saharan Africa.

Since 2015, Sub-Saharan Africa (SSA) has experienced an unprecedented rise in acute food insecurity (AFI), and current projections for the year 2020 indicate that more than 100 million Africans are estimated to receive emergency food assistance. Climate-driven drought is one of the main contributing factors to AFI, and timely and appropriate actions can be taken to mitigate impacts of AFI on lives and livelihoods through early warning systems. To support this goal, we use observations of peak Normalized Difference Vegetation Index (NDVI) as an indicator of seasonal drought conditions following a rainy season to show that delays in the onset of the rainy season (onset date) can be an effective early indicator of seasonal drought conditions. The core of this study is an evaluation of the relationship of the onset dates and peak NDVI, stratified by AFI risks, calculated using AFI reports by the United States Agency of International Development (USAID)-funded Famine Early Warning Systems Network (FEWS NET). Several parts of SSA, mostly located in East Africa (EA), reported the “Crisis” phase of AFI—requiring emergency food assistance—at least one-third of the time between April 2011 to present. The results show that the onset date can effectively explain much of the interannual variability in peak NDVI in the regions with the highest AFI risk level, particularly in EA where the median of correlation (across all the Administrative Unit 2) varies between -0.42 to -0.68. In general, an onset date delay of at least 1 dekad (10 days) increases the likelihood of seasonal drought conditions. In the regions with highest risks of AFI, an onset delay of just 1 dekad doubles the chance of the standardized anomaly of peak NDVI being below -1, making a -1 anomaly the most probable outcome. In those regions, a 2-dekads delay in the onset date is associated with a very high probability (50%) of seasonal drought conditions (-1 standardized anomaly of NDVI). Finally, a multivariate regression analysis between standardized anomaly and onset date anomaly further substantiates the negative impacts of delay in onset date on NDVI anomaly. This relationship is statistically significant over the SSA as a whole, particularly in the EA region. These results imply that the onset date can be used as an additional critical tool to provide alerts of seasonal drought development in the most food-insecure regions of SSA. Early warning systems using onset date as a tool can help trigger effective mid-season responses to save human lives, livestock, and livelihoods, and, therefore, mitigate the adverse impacts of drought hazards.

Assessing the vulnerability and risk of maize to drought in China based on the AquaCrop model

In the context of global climate change, droughts pose a serious threat to agricultural development and food security. Assessing the vulnerability and risk of regions to drought is important for its prevention. In this paper, to understand the vulnerability of maize to drought in different regions of China and quantify its risk, 241 prefecture-level administrative regions (including prefecture-level cities, autonomous prefectures, prefectures, and leagues) in the five main maize-growing regions of China are used as study area. By using a method of global sensitivity analysis, the extended Fourier amplitude sensitivity test (EFAST), we chose two parameters that are most sensitive to maize yield to calibrate the AquaCrop model. We then used it to simulate the water stress of maize in the study area under different irrigation scenarios as well as the corresponding production. We defined the drought hazard index (DHI) as the daily average of the crop water stress indicator during the growing season, and used it to describe the intensity of droughts. Vulnerability curves (the function of the DHI and rate of yield loss) of the entire growth season and various stages of growth were also formulated. These were used to determine the loss of maize yield under four levels of risk (return periods of 5, 10, 20, and 50 years). The results showed the following: 1) the vulnerability curve of maize for the entire growing season was consistent with logistic function, and the coefficient of determination of the equation of regression was R2 = 0.93. The rate of yield loss began increasing rapidly once the DHI had reached 0.2 and approached its maximum value when the DHI was 0.6. 2) The coefficients of determination of the results of regression in 14 scenarios, in which drought had occurred in different stages of growth, were between 0.28 and 0.92. Drought from the tasseling stage to the milk stage had the most significant negative effect on the maize yield, followed by the seventh leaf stage to the tasseling stage and the sowing stage to the seventh leaf stage. Drought from the milk stage to physiological maturity had the least negative effect on the maize yield. 3) Under all four risk levels, the DHI and the yield loss rate of maize in China decreased from the northwest to the southeast. The Northwest Irrigated Maize Region had the highest drought risk among the five maize-growing regions, followed by the North Spring Maize Region, the Huang-Huai-Hai Summer Maize Region, the South Hilly Maize Region, and the Southwest Mountain Maize Region. 4) The DHI calculated by the average method was more representative than that calculated using the accumulative method.

On the Bayesian network based data mining framework for the choice of appropriate time scale for regional analysis of drought Hazard

Data mining has a significant role in hyrdrologic research. Among several methods of data mining, Bayesian network theory has great importance and wide applications as well. The drought indices are very useful tools for drought monitoring and forecasting. However, the multi-scaling nature of standardized type drought indices creates several problems in data analysis and reanalysis at regional level. This paper presents a novel framework of data mining for hydrological research—the Bayesian Integrated Regional Drought Time Scale (BIRDts). The mechanism of BIRDts gives effective and sufficient time scales by considering dependency/interdependency probabilities from Bayesian network algorithm. The resultant time scales are proposed for further investigation and research related to the hydrological process. Application of the proposed method consists of 46 meteorological stations of Pakistan. In this research, we have employed Standardized Precipitation Temperature Index (SPTI) drought index for 1-, 3-, 6-, 9-, 12-, 24-, and ()month time scales. Outcomes associated with this research show that the proposed method has rationale to aggregate time scales at regional level by configuring marginal posterior probability as weights in the selection process of effective drought time scales.

Spatiotemporal characteristics and risk assessment of agricultural drought disasters during the winter wheat-growing season on the Huang-Huai-Hai Plain, China

Agricultural drought (AGD) is one of the most impactful natural disasters for rain-fed agricultural regions worldwide, including those in China. Spatiotemporal characteristics of the winter wheat drought season on the Huang-Huai-Hai (HHH) Plain, China, were studied by employing the Penman-Monteith (P-M) equation and a crop coefficient model based on daily meteorological datasets from 57 stations from 1980 to 2011. The crop water deficit index (CWDI) was employed as an index of AGD appraisal to depict the spatiotemporal changes in drought during the winter wheat growth stages in the HHH Plain, China. Besides, this study also intends to develop a drought disaster risk index (DDRI) of winter wheat for various growth stages based on risk formation theory. The spatial distribution patterns indicated higher CWDI values in the northern and middle parts of the HHH Plain and lower in the southern region throughout the wheat growth stages. Of the winter wheat growth stages on the northern HHH Plain, the drought frequency was the highest during the heading-mature stage, when it reached up to 80–100%. The high drought hazard was obvious during the heading-mature growth stage, with a more severe high drought hazard in the northern region of the HHH Plain than in the southern region. Spatially, the high DDRI values were distributed in the northern and central regions of the HHH Plain. The outcomes suggest that the DDRI model provides accurate spatiotemporal appraisals in both temporal and spatial scales, and these findings are important for enhancing the adaptability and mitigation ability of AGD risk on the HHH Plain.

Assessment of agricultural drought during crop-growing season in the Sudano–Sahelian region of Cameroon

Drought is a recurrent phenomenon in the Sudano–Sahelian region of Cameroon. However, it has received very little attention, especially, on its impacts on the growing season of crops. To fill this gap, this study assessed the drought hazard using standardized precipitation index at a 3-month scale, and phenology of the main crops in 19 rainfall stations in the Sudano–Sahelian region of Cameroon for the period 1980–2012. The trend of drought was studied using the Mann-Kendall technique. The agricultural drought hazard was quantified based on its frequency and intensity. Results show that there is a significant trend toward a more humid crop-growing period in the northern and southeastern parts of the study area, but significant dry trends during the maize and peanut growing periods in the southwestern part of the study area. Drought occurrence rates are 7.09, 4.22, and 3.17% for the moderate, severe, and extreme, respectively. Areas featuring high and very high agricultural drought hazards are distributed in the far north, central, and the southeastern parts of the study domain. Furthermore, the Sahelian and Sudanian climatic conditions were found to be very high agricultural drought hazard zones, especially, where the maize and peanut grain crops are concerned. However, significant dry trends and very high agricultural drought hazard zones during the maize and peanut growing periods are catastrophic for agriculture and, therefore, food security.

Projected drought risk assessment from water balance perspectives in a changing climate

AbstractIn the face of changing water environment due to climate change, the assessment of water demand and water supply capacity by region is needed to prevent and mitigate droughts. Herein, we propose a quantitative approach to identify high drought risk areas in South Korea by applying future climate and socio‐economic change scenarios to calculate the demand and supply of municipal, agricultural, and industrial water. Three Coupled Model Intercomparison Project 5 Global Climate Models were selected to assess future drought risk under different climate change scenarios by combining meteorological and socio‐economic factors. The drought hazard was assessed by calculating the severity and frequency of drought based on a rating method. Drought vulnerability was assessed by calculating water shortages in domestic, industrial, and agricultural waters based on water demand and supply capacity and applying entropy weightings. According to future climate change scenarios, the Youngsan River Basin was more vulnerable to drought than other basins. The results of the IPSL‐CM5‐LR model also suggest that the drought risk in the Youngsan River Basin will increase during the period 2071–2099. By demonstrating the relative sensitivity of drought risk on the Korean Peninsula to various future emission scenarios, our work provides valuable information to update mid‐ to long‐term drought mitigation strategies.

Applying Weibull distribution and Low Flow Frequency Curves for minimum flow prediction in an ungagged stream in Connecticut, New England

The necessity to conduct hydrological studies for water resources management, infrastructure design and, ecosystems protection can help mitigate flood and drought hazards. Prediction of low flows remains an important task for water management and ecosystems protection that can affect streams during low-flow periods. There have been many approaches to low flow prediction applying either statistical or deterministic methods, but there has not been any successful approach to link low flows between similar watersheds yet. The Fenton, Natchaug and Mount Hope Rivers watersheds are neighbors and are the major streams that discharge into the Mansfield Hollow Lake that belongs to the Thames River watershed, located in Northeast of the State of Connecticut in USA. A study to determine whether and how water withdrawals from the University’s Fenton River water supply wells affect the fisheries habitat of the Fenton River adjacent to the well field was conducted for four years at the beginning of 2002. The Mount Hope River was the only river with a long record of daily discharges available since the year 1940, meanwhile the Fenton and Natchaug River remained ungagged until the year 2006. This research developed and tested two mathematical models for the prediction of minimum discharges in the Fenton and Natchaug Rivers with the discharges available from the Mount Hope River. Yearly Low Flow Duration Curves (LFFC) and Weibull distribution methods were applied to the three rivers to predict the low flows in the Fenton and Natchaug Rivers taking as input the minimum flows and dates in the Mount Hope River. The results found that the Weibull distribution model showed a much better accuracy than the Low Flow Duration Curve method for the prediction of low flows discharges in the Fenton and Natchaug Rivers.

Regional drought risk assessment in the Central Highlands and the South of Vietnam

This study contributes to a proof-of-concept comprehensive drought risk assessment for Vietnam by (i) incorporating drought exposure and vulnerability based on specific socio-economic conditions of the regions; and (ii) using satellite data including World Meteorological Organization (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) products, and The National Aeronautics and Space Administration (NASA)-Enhanced U.S Department of Agriculture (USDA)'s Soil Moisture Active Passive (SMAP) Global Data for drought hazard assessment. Drought risk assessment which incorporated hazard, exposure and vulnerability components was conducted for 27 provinces from four administrative areas in Vietnam. Drought Hazard Index (DHI) was derived using the Standardised Precipitation Index (SPI), the Vegetation Health Index (VHI), and surface soil moisture (SSM) to take into account the impact of both meteorological and agricultural drought. Drought Exposure Index (DEI) and Drought Vulnerability Index (DVI) were calculated using statistical data of land use and socio-economic characteristics obtained from Vietnam’s statistical yearbooks. By combining DHI, DEI and DVI, a composite Drought Risk Index (DRI) was derived for drought risk assessment in the selected provinces for 2020. It was shown that the highest at-risk provinces were in the Mekong River Delta, the agricultural production centre of Vietnam. The South East regions were less impacted by drought compared to other regions. The proposed comprehensive approach to drought risk assessment in Vietnam has potential to contribute to improving drought preparedness and resilience of communities at-risk.

Drought vulnerability perceptions and food security status of rural lowland communities: An insight from Southwest Ethiopia

Food security is a common discourse across the globe. Drought affected Gamo rural lowland households are predisposed to food shortfalls. The study, therefore, mainly aimed to investigate the rural households' drought vulnerability perceptions and food security status in the Gamo lowlands. Primary data were obtained from 285 survey respondents, key informants, focus group discussants, agricultural professionals, and field observations. Secondary data were drawn from the published and unpublished relevant materials and complemented the primary data. A multistage sampling technique was used to select the sample respondents. Descriptive statistics, Rainfall Anomaly Index, correlation analysis, the Rasch and Logit models were used for quantitative data analysis. Discussions, narrations, and annotations were conducted to analyze the qualitative data. Multiple measures were employed to assess households' food security status. The findings showed that 53.68% of the households were food insecure in the light of the adapted Household Food Balance Model. The Household Dietary Diversity Score revealed low dietary diversity and poor nutritious quality. Food Insecurity Experience Scale showed only 13% of food security or mild food insecurity wherein 87% of the households were moderately and severely food insecure. The findings also indicated that drought hazard is a threat to communities' food security. To curb food problems, the studied households pursued strategies like selling out small animals, minimizing daily consumption frequency, reducing dietary quantity, and buying food on credit among the others. Importantly, more drought coping and food insecurity relieving strategies are recommended for all stakeholders to alleviate people's vulnerability to droughts and food insecurity.

Impact of climate change on water sector in Gumbasa Watershed, Central Sulawesi, Indonesia

Global climate change resulting in increased or decreased rainfall volume, rising temperatures, may also be associated with changes in season patterns, wind patterns, air humidity, and solar irradiance. This study aims to determine the potential hazards arising in the water sector due to climate change. This research was conducted in Gumbasa Watershed, Central Sulawesi, Indonesia. Primary data used in this research are characteristic of land, while secondary data include rain data, climatology data and earth map. The data of rain used by the nearest station are Bora Station, Kulawi, Palolo, Bangga Bawah, and Wuasa, whereas climatology data is used at Bora Station. Some of the methods used to complete this study are: 1) regional rainfall; 2) evapotranspiration; 3) water availability; 4) CDF statistical analysis; 5) climate change projections; 6) potential hazards. Based on the analysis performed, it can be concluded: 1) there is no danger of decreasing water availability for all periods (1993-2052); 2) there is a high flood hazard in the period 2013-2022, while the other periods do not occur due to flood hazard; 3) low drought hazards occur in the period 2003-2012, while for other periods there is no drought hazard.

Quantitative assessment of climate change impacts on the spatial characteristics of drought hazard in arid and semi-arid regions of Iran

Quantitative assessment of climate change impacts on the spatial characteristics of drought hazard in arid and semi-arid regions of Iran

Quantitative assessment of climate change impacts on the spatial characteristics of drought hazard in arid and semi-arid regions of Iran

Quantitative assessment of climate change impacts on the spatial characteristics of drought hazard in arid and semi-arid regions of Iran

Climate and cohesion: The effects of droughts on intra-ethnic and inter-ethnic trust

While a large body of research has highlighted the conflict-inducing effects of climate change, we still know very little about the mechanisms linking environmental conditions to violent conflict. This article investigates the plausibility of a prominent channel according to which scarcity of natural resources can foster violent conflict through deteriorating intergroup relations. In addition to assessing the direct effects of adverse environmental conditions on intra-ethnic and inter-ethnic trust, we suggest a conditional argument on the role of horizontal inequality of hazard exposure. Environmental hazards are ‘unequal’ if they systematically affect ethnic groups differently. While inequality may reinforce intra-ethnic ties and out-group suspicion, equal hazard exposure may create a sense of unity among diverse victims in their collective struggle to cope with harsh environmental conditions. We test these arguments in the context of the severe drought periods that affected most East African countries in the years 2004 and 2005. The empirical analysis combines gridded information on drought severity with geo-located survey data across six countries in the region (Afrobarometer survey 2005/2006). Our main analyses find that exposure to drought hazards correlates positively with self-reported trust within and across ethnic groups. The latter association, however, depends on the degree of intergroup equality of hazard exposure and wanes as inequality increases. Taken together, these findings indicate that if droughts increase the risk of violent conflict, they seem to do so through mechanisms other than intergroup polarization and despite their positive association with ethnic trust. This is most likely the case in contexts where there is pronounced horizontal inequality of drought hazards.