Different Types Of Drought Research Articles

Assessing urban flood and drought risks under climate change, China

AbstractRisk analysis of urban flood and drought can provide useful guidance for urban rainwater management. Based on an analysis of urban climate characteristics in 2,264 Chinese cities from 1958 to 2017, this study evaluated urban flood and drought risks. The results demonstrated that the annual average values of precipitation, aridity index, frequency and intensity of extreme precipitation and extreme drought events differed significantly in these cities. The values of the above six climatic indicators in the cities ranged from 9.29–2639.30 mm, 0.47–54.73, 1.08–8.79 time, 7.82–107.25 mm, 0.76–2.99 time, and 10.30–131.19 days, respectively. The geographical patterns of urban precipitation, aridity index, intensity and frequency of extreme precipitation and drought events in China fit well to the Hu‐Huanyong Line that was created in 1940s to identify the pattern of population distribution. Extreme precipitation in most cities has upward trends, except for those around the Hu‐Huanyong Line. The extreme drought events had upward trends in the cities east of the Hu‐Huanyong Line, but there were downward trends in the cities west of the line. The risk assessment indicated that 3.80% cities were facing serious flood and 6.01% cities were facing serious drought risks, which are located in the coast of southern China and northwestern China, respectively, and other 90.19% cities were facing different types of drought and flood risks in terms of their intensity and frequency.

Modified version for SPEI to evaluate and modeling the agricultural drought severity.

Drought is a climatic phenomenon that can occur in various regions with different climate conditions. Generally, drought has negative impacts on different fields such as environment, rangelands, and water resources. The agricultural section (especially rain-fed agriculture) is one of the parts that is directly affected by different types of drought especially meteorological and agricultural droughts. The standardized precipitation evapotranspiration index (SPEI) is one of the newest and most applied indices to assess drought characteristics. In this paper, a modification is suggested for SPEI with the substitution of observed precipitation (OP) with effective precipitation (EP) to evaluate drought, with an emphasis on consideration of drought effects on agricultural section. To calculate EP, Food and Agriculture Organization of the united nation method (FAO), US Bureau of Reclamation (USBR), the Simplified version of Soil Conservation Service of the US Department of Agriculture method (USDA-SCS simplified), and the CROPWAT version of USDA-SCS method (USDA-SCS CROPWAT) were used. To compare the calculated SPEI based on OP (SPEIOP) and EP (SPEIEP) (based on different EP calculation methods), the correlation coefficients (CC) between SPEIOP and SPEIEP in four synoptic stations with at least 30years of climatic data and annual yield loss (%) in winter wheat (Triticum sativum) (simulated using AquaCrop model) in the suitable reference periods for agricultural drought were used. Results showed, in Fasa, Drodzan, and Zarghan stations, the CC between SPEI based on EP using the USBR method (SPEIUSBR) and annual YL% had the highest values (in 42.11%, 68.42%, and 36.84% of Triticum sativum all reference periods, respectively). In Shiraz station, the CC between SPEI based on EP using the FAO method (SPEIFAO) and annual YL% had the highest values (in 47.37% of all reference periods). In all stations, the SPEIUSBR had the most reference periods with significant CC at 0.05 or 0.01 levels.

A water-energy balance approach for multi-category drought assessment across globally diverse hydrological basins

Different categories of droughts (e.g., meteorological, agricultural, hydrological), and their multi-scalar features often make description of drought onset, persistence, and termination challenging and often subjective. Here we show that a water-energy balance based indicator, named Standardized Moisture Anomaly Index (SZI), better captures multiple categories of droughts and their multi-scalar features. We globally evaluate and compare the performance of SZI with existing drought indicators that use potential evapotranspiration (PET) as a measure of atmospheric water demand including the Standardized Precipitation Evapotranspiration Index (SPEI) and self-calibrated Palmer Drought Severity Index (scPDSI). We show that while PET is a good indicator for characterizing the climate aridity, using it as a measure of atmospheric water demand for drought analysis leads to misrepresentation of droughts, especially over water-limited (non-humid) regions where the actual evapotranspiration is primarily dominated by water availability rather than energy (or PET). The main advantage of SZI is that, instead of PET, it uses a variable termed climatically appropriate precipitation for existing conditions (Pˆ) as the atmospheric water demand metric. Investigating droughts over 32 large basins across the globe, we show that the SZI can better represent meteorological, hydrological, and agricultural droughts compared to SPEI (especially in non-humid basins; 18 out of 32 basins) and scPDSI at multiple time scales. Given that SZI is physically more reasonable in reflecting surface water-energy balance over both humid and non-humid regions, it enables better characterization of different types of droughts in different climatic regions.

Evaluating CMIP5 Model Agreement for Multiple Drought Metrics

Abstract Global climate models play an important role in quantifying past and projecting future changes in drought. Previous studies have pointed to shortcomings in these models for simulating droughts, but systematic evaluation of their level of agreement has been limited. Here, historical simulations (1950–2004) for 20 models from the latest Coupled Model Intercomparison Project (CMIP5) were analyzed for a variety of drought metrics and thresholds using a standardized drought index. Model agreement was investigated for different types of drought (precipitation, runoff, and soil moisture) and how this varied with drought severity and duration. At the global scale, climate models were shown to agree well on most precipitation drought metrics, but systematically underestimated precipitation drought intensity compared to observations. Conversely, simulated runoff and soil moisture droughts varied significantly across models, particularly for intensity. Differences in precipitation simulations were found to explain model differences in runoff and soil moisture drought metrics over some regions, but predominantly with respect to drought intensity. This suggests it is insufficient to evaluate models for precipitation droughts to increase confidence in model performance for other types of drought. This study shows large but metric-dependent discrepancies in CMIP5 for modeling different types of droughts that relate strongly to the component models (i.e., atmospheric or land surface scheme) used in the coupled modeling systems. Our results point to a need to consider multiple models in drought impact studies to account for high model uncertainties.

Climate Change and Drought: a Perspective on Drought Indices

Droughts occur naturally, but climate change has generally accelerated the hydrological processes to make them set in quicker and become more intense, with many consequences, not the least of which is increased wildfire risk. There are different types of drought being studied, such as meteorological, agricultural, hydrological, and socioeconomic droughts; however, a lack of unanimous definition complicates drought study. Drought indices are used as proxies to track and quantify droughts; therefore, accurate formulation of robust drought indices is important to investigate drought characteristics under the warming climate. Because different drought indices show different degrees of sensitivity to the same level of continental warming, robustness of drought indices against change in temperature and other variables should be prioritized. A formulation of drought indices without considering the factors that govern the background state may lead to drought artifacts under a warming climate. Consideration of downscaling techniques, availability of climate data, estimation of potential evapotranspiration (PET), baseline period, non-stationary climate information, and anthropogenic forcing can be additional challenges for a reliable drought assessment under climate change. As one formulation of PET based on temperatures can lead to overestimation of future drying, estimation of PET based on the energy budget framework can be a better approach compared to only temperature-based equations. Although the performance of drought indicators can be improved by incorporating reliable soil moisture estimates, a challenge arises due to limited reliable observed data for verification. Moreover, the uncertainties associated with meteorological forcings in hydrological models can lead to unreliable soil moisture estimates under climate change scenarios.

Standardized Drought Indices: A Novel Univariate and Multivariate Approach

SummaryAs drought is among the natural hazards which affect people and economies world wide and often results in huge monetary losses, sophisticated methods for drought monitoring and decision making are needed. Many approaches to quantify drought severity have been developed during recent decades. However, most of these drought indices suffer from different shortcomings, account only for one or two driving factors which promote drought conditions and neglect their interdependences. We provide novel methodology for the calculation of (multivariate) drought indices, which combines the advantages of existing approaches and omits their disadvantages. It can be used flexibly in different applications to model different types of drought on the basis of user-selected, drought relevant variables. The methodology benefits from the flexibility of vine copulas in modelling multivariate non-Gaussian intervariable dependence structures. Based on a three-variate data set, an exemplary agrometeorological drought index is developed. The data analysis illustrates and reasons the methodology described. A validation of the exemplary multivariate agrometeorological drought index against observed soybean yield affirms the validity and abilities of the methodology. A comparison with established drought indices shows the benefits of our multivariate approach.

Climate change: A trend of increasingly frequent droughts in Kakheti Region (East Georgia)

Abstract Following the global warming, in Kakheti Region, in East Georgia (by municipalities), the trends of changes (increase or decrease) in agro-climatic characteristics for the development of agricultural crops were identified. Such changes result in the prolonged vegetation period, increased sum of temperatures and mostly, decreased sum of precipitations. Based on the latter indicators, a trend of a decreasing index of the hydrothermal coefficient is observed evidencing more frequent droughts with low or moderate intensity. The data of the 60-year-long period of meteorological observations (1949–2008) were divided into two 30-year-long periods in order to compare them. It was found that in the second period (1979–2008), the indices of a hydrothermal coefficient in all municipalities (except Kvareli) are decreased in the active vegetation period (VI-VIII). The dynamics of the course of a hydrothermal coefficient is shown with trends. Based on the many-year meteorological observation data (1949–2008) in different municipalities, the sums of active annual temperatures (>10 °C) and atmospheric precipitations were calculated. On the background of global warming, the repeated nature of droughts of different types was identified. The nomograms of the frequency of the droughts of the type typical to the study object and moisture evaporation have been drafted. Based on the sums of the annual active temperatures (>10 °C) and atmospheric precipitations, an equation to calculate the hydrothermal coefficient was given. A correlation between the date of the temperature rising over 10 °C and the sum of temperatures was identified (r=0.80) and a regression equation to forecast different types of droughts was designed. Against frequent droughts following the global warming, it is recommended to take relevant adaptation measures to avoid negative events.

Impact of soil moisture over Palmer Drought Severity Index and its future projections in Brazil

ABSTRACT Soil moisture is a main factor for the study of drought impacts on vegetation. Drought is a regional phenomenon and affects the food security more than any other natural disaster. Currently, the monitoring of different types of drought is based on indexes that standardize in temporal and regional level allowing, thus, comparison of water conditions in different areas. Therefore, in order to assess the impact of soil moisture during periods of drought, drought Palmer Severity Index was estimated for the entire region of the territory. For this were used meteorological data (rainfall and evapotranspiration) and soil (field capacity, permanent wilting point and water storage in the soil). The data field capacity and wilting point were obtained from the physical properties of soil; while the water storage in soil was calculated considering the water balance model. The results of the PSDI were evaluated during the years 2000 to 2015, which correspond to periods with and without occurrence of drought. In order to assess the future drought projections, considering the set of the Coupled Model Intercomparison rainfall data Project Phase 5 (CMIP5). Climate projections precipitation in CMIP5 for the period 2071-2100 was extracted generating entitled forcing scenarios Representative Concentration Pathways - RCPs, and referred to as RCOP 8.5, corresponding to an approximate radiative forcing the end the twenty-first century of 8.5 Wm-2. The results showed that the PDSI is directly associated with climatological patterns of precipitation and soil moisture in any spatial and temporal scale (including future projections). Therefore, it is concluded that the PDSI is an important index to assess soil moisture different water conditions, as well as the association with economic and social information to create risk maps for subsidies to decision makers.

Drought prediction using a wavelet based approach to model the temporal consequences of different types of droughts

Summary Droughts are expected to propagate from one type to another – meteorological to agricultural to hydrological to socio-economic. However, they do not possess a universal, straightforward temporal dependence. Rather, assessment of one type of drought (successor) from another (predecessor) is a complex problem depending on the basin’s physiographic and climatic characteristics, such as, spatial extent, topography, land use, land cover and climate regime. In this paper, a wavelet decomposition based approach is proposed to model the temporal dependence between different types of droughts. The idea behind is to separate the rapidly and slowly moving components of drought indices. It is shown that the temporal dependence of predecessor (say meteorological drought) on the successor (say hydrological drought) can be better captured at its constituting components level. Such components are obtained through wavelet decomposition retaining its temporal correspondence. Thus, in the proposed approach, predictand drought index is predicted using the decomposed components of predecessor drought. Several alternative models are investigated to arrive at the best possible model structure for predicting different types of drought. The proposed approach is found to be very useful for foreseeing the agricultural or hydrological droughts knowing the meteorological drought status, offering the scope for better management of drought consequences. The mathematical framework of the proposed approach is general in nature and can be applied to different basins. However, the limitation is the requirement of region/catchment specific calibration of some parameters before using the proposed model, which is not very difficult and uncommon though.

Agricultural Drought Severity Assessment using Remotely Sensed Data: A Review

Drought is natural hazard which is caused due to shortage of rainfall. Among the natural hazards, drought is hard to find out because it grows gradually and have huge impact on nature, human habitat and economy. Many satellite based drought indices have so far been suggested for regional and national levels. Meteorological and satellite based indices are used to detect different types of drought, including meteorological, agricultural and hydrological drought. NOAA-AVHRR, MODIS data are used in worldwide for vegetation analysis and drought monitoring and drought assessment. The several meteorological variables (indicators) such as precipitation, temperature, humidity and evapotranspiration are required to calculate drought severity level. The nature of drought indices shows different climate dryness, precipitation deficit or correspond to delayed hydrological impacts such as lowered water level in reservoir, lake, river streams, soil moisture level and agriculture crop health. The long term historical records of satellite imagery and climatic data are essential to calculate drought severity level and to determine drought risk prone area. The agriculture sector is vulnerable to the drought. Now day’s satellite imagery has been used in agriculture drought assessment. The government agencies and district based municipal department can create drought mitigation plan based on drought monitoring model. This review paper has discussed the use of remotely sensed data for agriculture drought assessment.

The soil–peace nexus: our common future

The strong soil–peace link is governed by the need for finite, but essential, resources intricately connected with ecosystem services and functions. Access to adequate and nutritious food is essential to human wellbeing, peace and tranquillity. The relation between soil/environmental scarcity and conflict is complex, and security can only be universal, rather than local or regional, in the present era of globalization. Civil strife and conflict can be caused by both resource paucity and rapacity. Anthropogenic perturbations leading to soil degradation, climate volatility and growing human demands (e.g., food, energy, water, minerals) derived from soil are potential flash points triggering violence at local, regional and global scales. Among different types of drought, pedological and agronomic droughts are triggered by soil degradation, decline in available water capacity of the root zone and changes in the hydrological cycle. Several regions with unstable governments are prone to water scarcity and conflicts. Soil affects world peace through its impact on the quest for victuals, which enhances the relevance of the “Peak Soil” concept. Economic development and environmental enhancement must go hand in hand, and the highest priority must be given to development of the ecosphere. Depicting soil as a work of art for portraying cultural, aesthetical and ecological values can increase public awareness. A Greener Revolution can be ushered in through judicious soil and environmental governance. Maintaining peace and harmony necessitates that soil resources are used, improved, restored and never taken for granted.

Exploring spatiotemporal relationships among meteorological, agricultural, and hydrological droughts in Southwest China

Each type of drought has different characteristics in different regions. It is important to distinguish different types of droughts and their correlations. Based on gauged precipitation, temperature, simulated soil moisture, and runoff data during the period 1951–2012, the relationships among meteorological, agricultural, and hydrological droughts were analyzed at different time scales in Southwest China. The standardized precipitation evapotranspiration index (SPEI), soil moisture anomaly percentage index (SMAPI), and standardized runoff index (SRI) were used to describe meteorological, agricultural, and hydrological droughts, respectively. The results show that there was a good correlation among the three indices. SMAPI had the best correlation with the 3 month SPEI and SRI values. It indicates that agricultural drought was characterized by a 3-month scale. The three drought indices displayed the similar special features such as drought scope, drought level, and drought center during the extreme drought of 2009–2010. However, the scope and level of SPEI were bigger than those of SMAPI and SRI. The propagation characteristics of the three types of droughts were significantly different. The temporal drought process in typical grids reflect that the meteorological drought occurred ahead of agricultural and hydrological droughts by about 1 and 3 months, respectively. Agricultural drought showed a stable drought process and reasonable time periods for the drought beginning and end. These results showed the quantitative relationships among three types of drought and thus provided an important supporting evidence for regional drought monitoring and strategic decisions.

Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)

One major characteristic of the Standardized Precipitation Index (SPI) is its flexibility to be calculated in a variety of time scales and hence being aware of different types of droughts. However, various time scales may result in confusion of the water resources’ researchers, decision makers and users in identifying and specifying drought periods in a certain region. To solve this problem in this article, a multivariate approach has been utilized having the ability to aggregate a variety of the SPI time series into a new time series called the Multivariate Standardized Precipitation Index (MSPI). The MSPI is based on the principal components analysis (PCA) of the SPI time series in a certain location. Having specified the first principal component’s (PC1’s) scores, the MSPI would be simply attained by dividing PC1’s values by the monthly standard deviation. In this article, MSPI’s capability in depicting the variability of the SPI time series (in five ranges of time scales, including 3–6, 6–12, 3–12, 12–24, and 24–48 months) was studied at four weather stations representing the four different climates in Iran from the driest to the wettest climates. The results showed that the PC1 is able to justify more than 74 % of the variability for the selected sets of the SPI time scales in the studied climates. Also, it became clear that the drought and wet severity classes monitored by MSPIs matched very satisfyingly to those of the five sets of the SPI time scales. Therefore, in cases where the aggregation time scales for calculating the SPI are not previously known, this study recommends the researchers use the MSPI.

Phenotyping for drought tolerance in grain crops: when is it useful to breeders?

Breeding for drought tolerance in grain crops is not a generic issue. Periods of drought vary in length, timing and intensity and different traits are important with different types of drought. The search for generic drought tolerance using single-gene transformations has been disappointing. It has typically concentrated on survival of plants suffering from severe water stress, which is rarely an important trait in crops. More promising approaches that target complex traits tailored to specific requirements at the different main stages of the life of a crop, during: establishment, vegetative development, floral development and grain growth are outlined. The challenge is to devise inexpensive and effective ways of identifying promising phenotypes with the aim of aligning them with genomic information to identify molecular markers useful to breeders. Controlled environments offer the stability to search for attractive phenotypes or genotypes in a specific type of drought. The recent availability of robots for measuring large number of plants means that large numbers of genotypes can be readily phenotyped. However, controlled environments differ greatly from those in the field. Devising pot experiments that cater for important yield-determining processes in the field is difficult, especially when water is limiting. Thus, breeders are unlikely to take much notice of research in controlled environments unless the worth of specific traits has been demonstrated in the field. An essential link in translating laboratory research to the field is the development of novel genotypes that incorporate gene(s) expressing a promising trait into breeding lines that are adapted to target field environments. Only if the novel genotypes perform well in the field are they likely to gain the interest of breeders. High throughput phenotyping will play a pivotal role in this process.

Modeling the hydrologic responses of the Pampanga River basin, Philippines: A quantitative approach for identifying droughts

Drought in the Philippines has been monitored for agricultural and economic losses, but spatial and temporal characterization at the basin scale has not been quantified. The relationship between different drought types, and how these can be integrated into timely water‐resource‐management planning in the agriculture and water sector of the Pampanga River basin, were considered. Specifically, the objectives of this study are as follows: (1) to propose a standardized anomaly (SA) index for assessing different types of drought impacts at the basin scale; (2) to quantify vulnerability of the agriculture and water sectors using physically consistent hydrological parameters with temporal variation and spatial heterogeneity; (3) to develop a method for combining the drought index calculated from the inputs and outputs of WEB‐DHM on the basis of sturdy algorithms for the physics of water and energy movement in the basin using monthly and seasonal differences of various drought types; and (4) to combine hydrological parameters with crop production to determine its effects on rice. The SA was calculated for the variables related to each drought type: rainfall (meteorological), streamflow and groundwater (hydrological), and soil moisture (agricultural) during 1983, 1987, 1990–1992, and 1998 droughts. El Niño is one of the major driving forces leading to drought in the country. The drought intensified on the second year of the average two‐year El Niño Southern‐Oscillation (ENSO) composites with a 1 to 7 month time lag between parameters and hot spots in the upland and central plains of the basin. Recommended adaptation strategies include crop scheduling, crop/livelihood substitutes, and alternative water sources.

Establishment of agricultural drought monitoring at different spatial scales in southeastern Europe

To detect temporal and spatial variability of drought is one of the most challenging issues of drought monitoring in the specific country or region due to the fact that there is no standard definition of severity and duration of different types of drought. Crop water deficit (CWD) simulated by crop water balance model IRRFIB supplemented with some in-situ soil water measurements by Time-Domain Reflectometry (TDR) measurement technique are proposed as tools for local agricultural drought monitoring in this study. Moving to regional drought monitoring the main constraint represents data availability of different sources. Available global data sets are of assistance for preparing regional drought monitoring products. In the study two specific products designed for regional scale are described: preliminary maps of the SPI (Standardized Precipitation Index) and products generated by implementation of numerical weather prediction model. It seems to be a lot of potential in both products for a first overview of key meteorological parameters in the region. The development of drought in the year 2009 was under examination and also yearly results for different periods after 1971. Dry periods in the year 2009 heavily impacted cereals in Slovenia. Maize yield showed best agreement with crop water deficit (r = 0.65) and SPI on the time scale of six months for September (r = 0.61). SPI was not suitable for describing agricultural drought in the periods with higher evapotranspiration rate. For more agricultural oriented drought monitoring more indices should be included into the consideration.

Establishment of agricultural drought monitoring at different spatial scales in southeastern Europe

To detect temporal and spatial variability of drought is one of the most challenging issues of drought monitoring in the specific country or region due to the fact that there is no standard definition of severity and duration of different types of drought. Crop water deficit (CWD) simulated by crop water balance model IRRFIB supplemented with some in-situ soil water measurements by Time-Domain Reflectometry (TDR) measurement technique are proposed as tools for local agricultural drought monitoring in this study. Moving to regional drought monitoring the main constraint represents data availability of different sources. Available global data sets are of assistance for preparing regional drought monitoring products. In the study two specific products designed for regional scale are described: preliminary maps of the SPI (Standardized Precipitation Index) and products generated by implementation of numerical weather prediction model. It seems to be a lot of potential in both products for a first overview of key meteorological parameters in the region. The development of drought in the year 2009 was under examination and also yearly results for different periods after 1971. Dry periods in the year 2009 heavily impacted cereals in Slovenia. Maize yield showed best agreement with crop water deficit (r = 0.65) and SPI on the time scale of six months for September (r = 0.61). SPI was not suitable for describing agricultural drought in the periods with higher evapotranspiration rate. For more agricultural oriented drought monitoring more indices should be included into the consideration.

Basin‐scale, integrated observations of the early 21st century multiyear drought in southeast Australia

The Murray‐Darling Basin in southeast Australia is experiencing one of the most severe droughts observed recently in the world, driven by several years of rainfall deficits and record high temperatures. This paper provides new basin‐scale observations of the multiyear drought, integrated to a degree rarely achieved on such a large scale, to assess the response of water resources and the severity of the drought. A combination of Gravity Recovery and Climate Experiment (GRACE) data with in situ and modeled hydrological data shows the propagation of the water deficit through the hydrological cycle and the rise of different types of drought. Our observations show the rapid drying of soil moisture and surface water storages, which reached near‐stationary low levels only ∼2 years after the onset of the drought in 2001, with a loss of ∼80 and ∼12 km3 between January 2001 and January 2003, respectively. The multiyear drought has led to the almost complete drying of surface water resources which account for most of the water used for irrigation and domestic purposes. High correlation between observed groundwater variations and GRACE data substantiates the persistent reduction in groundwater storage, with groundwater levels still declining 6 years after the onset of the drought (groundwater loss of ∼104 km3 between 2001 and 2007). The hydrological drought continues even though the region returned to average annual rainfall during 2007.

Review of Wadi Hydrology by Zekai SenWadi HydrologyCRC Press978-1-4200-6154-3

In preface of the book, the author states the purpose of the book is to “ P rovide a comprehensive presentation of up-to-date models for utilization with arid and semiarid region water resources and their applications. In addition to an overview of fundamentals in the field, readers will find a useful summary of current developments as reported in the world’s leading hydrology journals.” The book is reviewed keeping this objective in mind. The subject matter of the book is divided into seven chapters. The first chapter is introductory, providing a general overview of arid regions, problems faced by these regions, and factors effecting hydrologic phenomena and processes occurring in these regions. Arid regions are classified, based on precipitation as humid, extremely humid, semiarid, arid, and extremely arid; when temperature is used then they are classified as cold, warm, and hot. Desertification is discussed next. Then follows a discussion of droughts, including different types of droughts, such as meteorological, hydrologic, and agricultural. For better understanding of droughts different events are considered: aridity, drought, water shortage, and desertification. The chapter then goes on to discuss climate change impacts and wadi hydrology, and is concluded with a discussion of methodological distinctions between wadi hydrology and humid region hydrology. The chapter provides a very good overview of wadi hydrology and the issues and problems involved, and sets a context for the chapters to follow. Looking at the references, one notices that one reference is dated 2005, two are dated 2002, and the remainder are at least ten years old. Chapter 2 deals with wadi characteristics. Providing a general overview, it goes on to discuss geomorphology; soils; land forms, including alluvial fans, alluvial fills, sand dune, delta deposits, coastal and plain deposits, and playas; rock environments; drainage basin features, including drainage areas, stream slope, drainage density, centroid, length, and elevation features; and time of concentration, including the average time of concentration. It is not clear from the discussion if the empirical laws of geomorphology, such as Horton’s and others, will apply to wadi hydrology. Also, the concept of lag time does not figure prominently in the discussion, although it is an important concept in rainfall-runoff hydrograph synthesis. Excepting one reference, all other references in the chapter are at least ten years old. Rainfall pattern constitutes the subject matter of chapter 3. It discusses rainfall features; temporal distribution of rainfall; aridity index; accumulative rainfall curves; rainfall intensity, including duration, intensity-duration-frequency relationships, and

Yield response of rice ( Oryza sativa L.) genotypes to different types of drought under rainfed lowlands : Part 1. Grain yield and yield components

Responses of rice genotypes to drought stress may be different when characteristics of the drought stress environments differ. The performance of 128 genotypes was examined under irrigation and four different types of drought stress, to determine genotypic consistency in yield and factors determining yields under different drought stress conditions. The different drought conditions were mild drought during grain filling, short and severe drought at flowering, prolonged severe drought during the reproductive to grain filling, and prolonged mild drought during vegetative and grain filling. Genotypic grain yield under mild stress conditions was associated with yield under irrigated conditions, indicating the importance of potential yield in environments where the yield reduction was less than 50%. However, yields under irrigated conditions differed over time and locations. Under prolonged or severe drought conditions, flowering time was an important determinant of grain yield. Earlier flowering genotypes escaped the severe stress and had higher grain yields indicating large genotype by environment (G×E) interactions which have implications for plant breeding even for mild stress. It is suggested that variations in flowering time, potential yields and drought patterns need to be considered for development of drought-resistant cultivars using specific physiological traits.