At site flood frequency analysis (FFA) in arid/semi-arid watersheds poses unique challenges to researchers and practitioners due to the generally limited data records. This study presents a comprehensive evaluation of FFA in arid/semi-arid watersheds in relation to the unique characteristics of these regions, such as the limited number of floods occurring each year and the large variability of the flood peak discharges. Study cases in Israel and the US are examined and compared with non-arid watersheds, characterized by Mediterranean climate, and with synthetic flood records. Results show that the tail of extreme value distributions describing arid/semi-arid watersheds is found to be heavier than the one describing Mediterranean watersheds. The number of yearly floods and the variability of flood peak discharge are shown to have a crucial impact on the accuracy of the quantile estimates with smaller number of events per year and larger coefficient of variation of flood peak discharge being related to larger errors in the estimated quantiles. Partial duration series approach provides a slightly reduced bias in the estimates, but should not be blindly preferred over annual maxima series as it presents comparable estimation uncertainty. In general, the generalized extreme value and the generalized Pareto distribution are found to be non-optimal choices for the examined arid/semi-arid watersheds.
The metastatistical extreme value approach proved promising in the frequency analysis of daily precipitation from ordinary events, outperforming traditional methods based on sampled extremes. However, subdaily applications are currently restrained by two knowledge gaps: It is not known if ordinary events can be consistently examined over durations, and it is not clear to what extent their entire distributions represent extremes. We propose here a unified definition of ordinary events across durations and suggest the simplified metastatistical extreme value formulation for dealing with extremes emerging from the tail, rather than the entire distributions, of ordinary events. This unified framework provides robust estimates of extreme quantiles (\textless10% error on the 100 yr from a 26 yr long record) and allows representations in which ordinary and extreme events share the scaling exponent. Future applications could improve our knowledge of subdaily extreme precipitation and help investigate the impact of local factors and climatic forcing on their frequency.
Abstract Water volume estimates of shallow desert lakes are the basis for water balance calculations, important both for water resource management and paleohydrology/climatology. Water volumes are typically inferred from bathymetry mapping; however, being shallow, ephemeral and remote, bathymetric surveys are scarce in such lakes. We propose a new, remote-sensing based, method to derive the bathymetry of such lakes using the relation between water occurrence, during \textgreater30-yr of optical satellite data, and accurate elevation measurements from the new Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). We demonstrate our method at three locations where we map bathymetries with \~0.3 m error. This method complements other remotely sensed, bathymetry-mapping methods as it can be applied to: (a) complex lake systems with sub-basins, (b) remote lakes with no in-situ records, and (c) flooded lakes. The proposed method can be easily implemented in other shallow lakes as it builds on publically accessible global data sets.
Flood-fed aquifers along the sandy lower reach of the Kuiseb River sustain a 130-km-long green belt of lush oases across the hyperarid Namib desert. This oasis is a year-round source for water creating dense-tall woodland along the narrow corridor of the ephemeral river valley, which, in turn, supports human activity and fauna including during the long dry austral winters and multi-year droughts. Occasional floods, originating at the river's wetter headwaters, travel ∼280 km downstream, before recharging these aquifers. We analyzed the flood-aquifer-vegetation dynamics at-a-site and along the river, determining the relative impact of floods with diverse magnitude and frequency on downstream reaches. We find that flood discharge that feeds the alluvial aquifers also affects vegetation dynamics along the river. The downstream aquifers are fed only by the largest floods that allow the infrequent germination of plants; mean annual recharge volume is too low to support the aquifers level. These short-term vegetation cycles of green-up and then fast senescence in-between floods are easily detected by satellite-derived vegetation index. This index identifies historical floods and their magnitudes in arid and hyperarid regions; specifically, it determines occurrences of large floods in headwater-fed, ephemeral Namib streams as well as in other hyperarid regions. Our study reveals the importance of flood properties on the oasis life cycle, emphasizing the impact of drought and wet years on the Namib's riparian vegetation.
The performances of hydrological models in arid areas are significantly lower than other climates. The reasons are numerous, from the scales involved, to specific processes and the lack of adequate measurements. Effective parameters have been often observed to change between runoff events, limiting the predictive capacity of the models. We look at the problems that can be found in an operational setting and present an analysis to improve the understanding of the errors. Our method characterizes the conditions where the model fails systematically, and the conditions where the parameterization holds between floods. We applied KINEROS2 to 24 years of radar rainfall and streamflow data in 6 arid catchments. A GLUE probabilistic framework is used to characterize model performance, and a method is developed to identify floods with similar calibration. The analysis shows that uninformative conditions are difficult to generalize. A basin-specific analysis can help to identify conditions where the model fails and exclude them from calibration. Despite the large uncertainties, similar catchments display groups of floods with similar parameterization. In some basin we find that it is important to quantify antecedent moisture conditions. Hydrological models show some consistency within limited conditions. These conditions, however, depend on the errors involved, and are site-specific. There is some potential for parameter transfer, but proximity alone might not be enough, and other factors such as mean annual rainfall or storm type, should be taken into account.
Heavy precipitation events (HPEs) can lead to natural hazards (e.g. floods and debris flows) and contribute to water resources. Spatiotemporal rainfall patterns govern the hydrological, geomorphological, and societal effects of HPEs. Thus, a correct characterisation and prediction of rainfall patterns is crucial for coping with these events. Information from rain gauges is generally limited due to the sparseness of the networks, especially in the presence of sharp climatic gradients. Forecasting HPEs depends on the ability of weather models to generate credible rainfall patterns. This paper characterises rainfall patterns during HPEs based on high-resolution weather radar data and evaluates the performance of a high-resolution, convection-permitting Weather Research and Forecasting (WRF) model in simulating these patterns. We identified 41 HPEs in the eastern Mediterranean from a 24-year radar record using local thresholds based on quantiles for different durations, classified these events into two synoptic systems, and ran model simulations for them. For most durations, HPEs near the coastline were characterised by the highest rain intensities; however, for short durations, the highest rain intensities were found for the inland desert. During the rainy season, the rain field's centre of mass progresses from the sea inland. Rainfall during HPEs is highly localised in both space (less than a 10 km decorrelation distance) and time (less than 5 min). WRF model simulations were accurate in generating the structure and location of the rain fields in 39 out of 41 HPEs. However, they showed a positive bias relative to the radar estimates and exhibited errors in the spatial location of the heaviest precipitation. Our results indicate that convection-permitting model outputs can provide reliable climatological analyses of heavy precipitation patterns; conversely, flood forecasting requires the use of ensemble simulations to overcome the spatial location errors.
AbstractWhile CMIP5 models robustly project drying of the subtropics and more precipitation in the tropics and subpolar latitudes by the end of the century, the magnitude of these changes in precipitation varies widely across models: for example, some models simulate no drying in the eastern Mediterranean while others simulate more than a 50% reduction in precipitation relative to the model-simulated present-day value. Furthermore, the factors leading to changes in local subtropical precipitation remain unclear. The importance of zonal-mean changes in atmospheric structure for local precipitation changes is explored in 42 CMIP5 models. It is found that up to half of the local intermodel spread over the Mediterranean, northern Mexico, East Asia, southern Africa, southern Australia, and southern South America is related to the intermodel spread in large-scale processes such as the magnitude of globally averaged surface temperature increases, Hadley cell widening, polar amplification, stabilization of the tropical upper troposphere, or changes in the polar stratosphere. Globally averaged surface temperature increases account for intermodel spread in land subtropical drying in the Southern Hemisphere but are not important for land drying adjacent to the Mediterranean. The factors associated with drying over the eastern Mediterranean and western Mediterranean differ, with stabilization of the tropical upper troposphere being a crucial factor for the former only. Differences in precipitation between the western and eastern Mediterranean are also evident on interannual time scales. In contrast, the global factors examined here are unimportant over most of the United States, and more generally over the interior of continents. Much of the rest of the spread can be explained by variations in local relative humidity, a proxy also for zonally asymmetric circulation and thermodynamic changes.
Abstract. Catchment scale hydrological studies on drylands are lacking because of the scarcity of consistent data: observations are often available at the plot scale, but their relevance for the catchment scale remains unclear. A database of 24 years of stream gauge discharge and homogeneous high-resolution radar data over the eastern Mediterranean allows to describe the properties of moderate floods over catchments spanning from Desert to Mediterranean climates. Comparing two climatic regions, Desert and Mediterranean, we are able to better identify specific rainfall-runoff properties. Despite the large differences in rainfall forcing between the two regions, the resulting unit peak discharges and runoff coefficients are comparable. In Mediterranean areas rain depth and antecedent conditions are the most important properties to shape flood response. In Deserts, instead, storm core properties display a strong correlation with unit peak discharge and, to a less extent, with runoff coefficient. In this region, an inverse correlation with mean catchment annual precipitation suggests also a strong influence of local surface properties. Preliminary analyses suggest that floods in catchments with wet headwater and dry lower section are more similar to desert catchments, with a strong influence of storm core properties on runoff generation.
Adjustment of weather radar estimates using observed precipitation has been an accepted procedure for decades. Ground observations of precipitation typically come from rain gauges, but can also include data from diverse networks of sensors, with different levels of reliability. This study presents a standardized framework for evaluating adjustment algorithms using synthetically constructed, but realistic, rain grids and weather radar rainfall. Ground observation points are randomly placed throughout the synthetic storm domain and the precipitation for each sensor is extracted from the true rain. Then a subset of the sensors are defined as unreliable, and a log-normal error factor is applied at those locations. This double network of rain sensors could be applicable, for example, when rainfall is derived from signal attenuation between commercial microwave link (CML) antennas. Past research has tested CML observations as a source of precipitation data and validated various radar adjustment algorithms. However, a comprehensive evaluation of adjustment algorithms using accurate gauge data mixed with CML observations at different densities is lacking. Five adjustment algorithms are applied to the synthetic radar grid: Mean Field Bias (MFB), a Multiplicative algorithm, Mixed (additive and multiplicative), Conditional Merge (CondMerge) and Kriging with External Drift (KED). Generation of the synthetic framework, and application of the adjustment algorithms is repeated for 150 realizations. Comparison of coefficient of determination (R2), root mean square error and linear regression for all adjustment procedures over all realizations indicates the following results. Only MFB and KED adjustments performed well when using accurate gauges. The kriging based KED was able to achieve good adjustment also with the addition of error-prone sensors. CondMerge and the Mixed and Multiplicative, however, resulted in poorer adjustments.
The Dead Sea sedimentary fill is the basis for interpreting limnological conditions and regional paleo- hydrology. Such interpretations require an understanding of present-day hydroclimatology to reveal the relative impact of different atmospheric circulation patterns on water and sediment delivery to the Dead Sea. Here we address the most important meteorological conditions governing regional and local rain- storm occurrences, with different discharge characteristics. These meteorological controls over the Dead Sea watershed offer insights into past hydrometeorological processes that could have governed the Dead Sea water budget, seasonal and annual flows, floods, and the resultant sedimentology. Rainfall is typically associated with synoptic-scale circulation patterns forced by an upper-level trough that include Medi- terranean cyclones (MCs), active Red Sea troughs (ARSTs), and active subtropical jets (STJs), although other rainstorms and sub-synoptic processes also affect the region. We point to their relative importance in inflow volume, peak discharges, and delivery of sediments from the various environments of the basin. MCs control the annual water amount discharging into the Dead Sea. A change in their frequency, in- tensity, or latitude can substantially alter the lake water balance. A change in frequency or intensity of ARSTs and STJs affects extreme flood and sediment discharge. Floods reach the lake through (a) the Mediterranean-climate-controlled Lower Jordan River, (b) desert-climate-controlled Nahal HaArava, and (c) the arid wadies draining directly into the Dead Sea, some with wetter headwaters. Floods in the wetter parts of the watershed are mainly controlled by MCs, and characterized by larger frequency, volume, and duration, but lower peak discharges and possibly sediment delivery, than floods in the desert parts, which can be produced by the three synoptic types. ARSTs contribute to heavy rainfall, typically of a spotty nature, in the desert parts of the watershed. STJs are currently rare, but their rainfall accumulation may be greater than the annual mean over a broad area in the southern dry Dead Sea watershed. This article presents a review of recent studies, which is extended with new analyses of meteorological, rainfall and flood data, underlining the importance of the Lower Jordan River in sup- plying water volume to the Dead Sea, as compared to the high-discharge, low-volume floods of the arid part of the watershed. Our analyses will help interpret paleoenvironmental conditions in the Dead Sea sedimentary record, and cope with the region's changing climate.
Information on extreme precipitation is essential to managing weather-related risks and designing hydraulic structures. Research attention to frequency analyses based on remotely sensed precipitation datasets, such as those obtained from weather radars and satellites, has been rapidly increasing owing to their potential to provide information for ungauged regions worldwide. Together with the ability to measure the areal scale directly, these analyses promise to overcome the sampling limitations of traditional methods based on rain gauges. This focused review of the literature depicts the state of the art after a decade of efforts, and identifies the crucial gaps in knowledge and methodology that currently hinder the quantitative use of remotely sensed datasets in water resources system design and operation. It concludes by highlighting a set of research directions promising immediate impact with regard to the separation of the sources of uncertainty currently affecting applications based on remotely sensed datasets, the development of statistical methods that can cope with the peculiar characteristics of these datasets, and the improvement of validation methods. Important gains in knowledge are expected from the explicit inclusion of the areal dimension in the analyses and from the fine-scale investigation of extreme precipitation climatology.
This paper presents a Simplified Metastatistical Extreme Value formulation (SMEV) able to model hydro- meteorological extremes emerging from multiple underlying processes. The formulation explicitly includes the average intensity and probability of occurrence of the processes allowing to parsimoniously model changes in these quantities to quantify changes in the probability of occurrence of extremes. SMEV allows (a) frequency analyses of extremes emerging from multiple underlying processes and (b) computationally efficient analyses of the sensitivity of extreme quantiles to changes in the characteristics of the underlying processes; moreover, (c) it provides a robust framework for explanatory models, nonstationary frequency analyses, and climate projections. The methodology is applied to daily precipitation data from long recording stations in the eastern Mediter- ranean, using Weibull distributions to model daily precipitation amounts generated by two classes of synoptic systems. At-site application of SMEV provides spatially consistent estimates of extreme quantiles, in line with regional GEV estimates and generally characterized by reduced uncertainties. The sensitivity of extreme quan- tiles to changes and uncertainty in the intensity and yearly occurrences of events generated by different synoptic classes is examined, and an application of SMEV for the projection of future extremes is provided.
The last decade has witnessed the development of methodologies for the post‐flood documentation of both hydrogeomorphological and social response to extreme precipitation. These investigations are particularly interesting for the case of flash floods, whose space–time scales make their observations by conventional hydrometeorological monitoring networks particularly challenging. Effective flash flood documentation requires post‐flood survey strategies encompassing accurate radar estimation of rainfall, field and remote‐sensing observations of the geomorphic processes, indirect reconstruction of peak discharges—as well eyewitness interviews. These latter can give valuable information on both flood dynamics and the related individual and collective responses. This study describes methods for post‐flood surveys based on interdisciplinary collaborations between natural and social scientists. These surveys may help to better understand the links between hydrometeorological dynamics and geomorphic processes as well as the relationship between flood dynamics and behavioral response in the context of fast space–time changes of flooding conditions. This article is categorized under: Science of Water > Methods Science of Water > Hydrological Processes A flash flood and its forensic analysis.
The lack of knowledge on precipitation frequency over ungauged areas introduces a significant source of uncertainty in relevant engineering designs and risk estimation procedures. Radar-based observations offer precipitation information over ungauged areas and thus have gained increasing attention as a potential solution to this problem. However, due to their relative short data records and inherent uncertainty sources, their ability to provide accurate estimates on the frequency of precipitation extremes requires evaluation. This study involves the evaluation of at-site precipitation frequency estimates from NEXRAD Stage IV radar precipitation dataset. We derive precipitation annual maxima series from the 16yrs record (2002-2017) of NEXRAD and we compare against 539 long-term (50yrs) hourly gauge records. In addition, Intensity-Duration-Frequency (IDF) curves are estimated from both radar and gauge dataset and compared. IDF estimation is based on fitting the Generalize Extreme Value distribution to annual precipitation maxima. Evaluation is carried out over the contiguous United States and results are grouped and presented for five dominant climate classes and for a range of return period and precipitation durations. NEXRAD was shown to overestimate intensities at shorter durations (1- and 3-hr) and low quantiles, while it tends to underestimate higher quantiles at longer durations (24hr). In addition, evaluation of the IDF curves estimated from NEXRAD revealed a distinct geographic dependence with certain regions exhibiting a tendency to overestimation (e.g. east of the Rocky Mountains) or underestimation (Midwest). Overall, this analysis suggests that, while significant discrepancies may exist, there are several cases where NEXRAD provide estimates within the uncertainty bounds of the reference rain gauge dataset. The climate/geographic region and the temporal duration are important aspects to consider. Findings provided in this work on these aspects will hopefully serve as a general guideline for those interested in using NEXRAD estimates for further research or applications on precipitation extremes.
Rainfall thresholds for landslides occurrence derived in real applications tend to be lower than the ones one would obtain using exact data. This letter shows how the use of coarse temporal resolution rainfall data causes a systematic overestimation of the duration of the triggering rainfall events that directly contributes to thresholds underestimation. A numeri- cal experiment is devised to quantify this systematic effect for the relevant case of power- law depth/intensity–duration thresholds. In the examined conditions, i.e., the frequentist method at 5% non-exceedance probability level, \~ 70% underestimation of the scale param- eter and \~ 60% overestimation of the shape parameter of the thresholds is to be expected using daily resolution rainfall data, but the exact quantification depends on the specific characteristics of each study case. The underestimation increases as the temporal resolu- tion becomes larger than the expected minimal duration of the triggering events. Under operational conditions, sensitivity analyses based on the methods and datasets of interest are advised.
Current literature suggests that wheat production models are limited either to wide-scale or plot-based predictions ignoring pattern of habitat conditions and surficial hydrological processes. We present here a high-spatial resolution (50 m) non-calibrated GIS-based wheat production model for predictions of aboveground wheat biomass (AGB) and grain yield (GY). The model is an integration of three sub-models, each simulating elemental processes relevant for wheat growth dynamics in water-limited environments: (1) HYDRUS-1D, a finite element model that simulates one-dimensional movement of water in the soil profile; (2) a two-dimensional GIS-based surface runoff model; and (3) a one-dimensional process-driven mechanistic wheat growth model. By integrating the three sub-models, we aimed to achieve a more accurate spatially continuous water balance simulation with a better representation of root zone soil water content (SWC) impacts on plant development. High-resolution grid-based rainfall data from a meteorological radar system were used as input to HYDRUS-1D. Twenty-two commercial wheat fields in Israel were used to validate the model in two seasons (2010/11 and 2011/12). Results show that root zone SWC was accurately simulated by HYDRUS-1D in both seasons, particularly at the top 10-cm soil layer. Observed vs simulated AGB and GY were highly correlated with R2 = 0.93 and 0.72 (RMSE = 171 g m−2 and 70 g m−2) having low biases of -41 g m−2 (8%) and 52 g m−2 (10%), respectively. Model sensitivity test showed that HYDRUS-1D was mainly driven by spatial variability in the input soil characteristics while the integrated wheat production model was mostly affected by rainfall spatial variability indicating the importance of using accurate high-resolution rainfall data as model input. Using the integrated model, we predict decreases in AGB and GY of c. 10.5% and c. 12%, respectively, for 1 °C of warming and c. 7.7% and c. 7.3% for 5% reduction in rainfall amount in our study sites. The suggested model could be used by scientists to better understand the causes of spatial and temporal variability in wheat production and the consequences of future scenarios such as climate change.
Identifying climates favoring extreme weather phenomena is a primary aim of paleoclimate and paleohydrological research. Here, we present a well-dated, late Holocene Dead Sea sediment record of debris flows covering 3.3 to 1.9 cal ka BP. Twenty-three graded layers deposited in shallow waters near the western Dead Sea shore were identified by microfacies analysis. These layers represent distal subaquatic deposits of debris flows triggered by torrential rainstorms over the adjacent western Dead Sea escarpment. Modern debris flows on this escarpment are induced by rare rainstorms with intensities exceeding \textgreater30mm h−1 for at least one hour and originate primarily from the Active Red Sea Trough synoptic pattern. The observed late Holocene clustering of such debris flows during a regional drought indicates an increased influence of Active Red Sea Troughs resulting from a shift in synoptic atmospheric circulation patterns. This shift likely decreased the passages of eastern Mediterranean cyclones, leading to drier conditions, but favored rainstorms triggered by the Active Red Sea Trough. This is in accord with present-day meteorological data showing an increased frequency of torrential rainstorms in regions of drier climate. Hence, this study provides conclusive evidence for a shift in synoptic atmospheric circulation patterns during a late Holocene drought.
A novel quantitative assessment of late Holocene precipitation in the Levant is presented, including mean and variance of annual precipitation and their trends. A stochastic framework was utilized and allowed, possibly for the first time, linking high-quality, reconstructed rises/declines in Dead Sea levels with precipitation trends in its watershed. We determined the change in mean annual precipitation for 12 specific intervals over the past 4500 yr, concluding that: (1) the twentieth century was substantially wetter than most of the late Holocene; (2) a representative reference value of mean annual precipitation is 75% of the present-day parameter; (3) during the late Holocene, mean annual precipitation ranged between −17 and +66% of the reference value (−37 to +25% of present-day conditions); (4) the driest intervals were 1500–1200 BC and AD 755–890, and the wettest intervals were 2500–2460 BC, 130–40 BC, AD 350–490, and AD 1770–1940; (5) lake-level rises and declines probably occurred in response to trends in precipitation means and are less likely to occur when precipitation mean is constant; (6) average trends in mean annual precipitation during intervals of ≥200 yr did not exceed 15mm per decade. The precipitation trends probably reflect shifts in eastern Mediterranean cyclone tracks.
The Sahara was wetter and greener during multiple interglacial periods of the Quaternary, when some have suggested it featured very large (mega) lakes, ranging in surface area from 30,000 to 350,000km2. In this paper, we review the physical and biological evidence for these large lakes, especially during the African Humid Period (AHP) 11–5 ka. Megalake systems from around the world provide a checklist of diagnostic features, such as multiple well-defined shore- line benches, wave-rounded beach gravels where coarse material is present, landscape smoothing by lacustrine sediment, large-scale deltaic deposits, and in places, tufas encrusting shorelines. Our survey reveals no clear evidence of these fea- tures in the Sahara, except in the Chad basin. Hydrologic modeling of the proposed megalakes requires mean annual rain- fall ≥1.2 m/yr and a northward displacement of tropical rainfall belts by ≥1000 km. Such a profound displacement is not supported by other paleo-climate proxies and comprehensive climate models, challenging the existence of megalakes in the Sahara. Rather than megalakes, isolated wetlands and small lakes are more consistent with the Sahelo-Sudanian paleoenvironment that prevailed in the Sahara during the AHP. A pale-green and discontinuously wet Sahara is the like- lier context for human migrations out of Africa during the late Quaternary.