Gotowa bibliografia na temat „Flash droughts”

AbstractIt is essential to assess flash drought risk based on a reliable flash drought intensity (severity) index incorporating comprehensive information of the rapid decline (“flash”) in soil moisture toward drought conditions and soil moisture thresholds belonging to the “drought” category. In this study, we used the Gan River basin as an example to define a flash drought intensity index that can be calculated for individual time steps (pentads) during a flash drought period over a given grid (or station). The severity of a complete flash drought event is the sum of the intensity values during the flash drought. We explored the spatial and temporal characteristics of flash droughts with different grades based on their respective severities. The results show that decreases in total cloud cover, precipitation, and relative humidity, as well as increases in 500-hPa geopotential height, convective inhibition, temperature, vapor pressure deficit, and wind speed can create favorable conditions for the occurrence of flash droughts. Although flash droughts are relatively frequent in the central and southern parts of the basin, the severity is relatively high in the northern part of the basin due to longer duration. Flash drought severity shows a slightly downward trend due to decreases in frequency, duration, and intensity from 1961 to 2018. Extreme and exceptional flash droughts decrease significantly while moderate and severe flash droughts trend slightly upward. Flash drought severity appears to be more affected by the interaction between duration and intensity as the grade increases from mild to severe. The frequency and duration of flash droughts are higher in July–October. The southern part of the basin is more prone to moderate and severe flash droughts, while the northern parts of the basin are more vulnerable to extreme and exceptional flash droughts due to longer durations and greater severities than other parts. Moderate, severe, extreme, and exceptional flash droughts occurred at approximately 3–6-, 5–15-, 10–50-, and 30–200-yr intervals, respectively, based on the copula analysis.

Abstract. The term “flash drought” describes a type of drought with rapid onset and strong intensity, which is co-affected by both water-limited and energy-limited conditions. It has aroused widespread attention in related research communities due to its devastating impacts on agricultural production and natural systems. Based on a global reanalysis dataset, we identify flash droughts across China during 1979–2016 by focusing on the depletion rate of weekly soil moisture percentile. The relationship between the rate of intensification (RI) and nine related climate variables is constructed using three machine learning (ML) technologies, namely, multiple linear regression (MLR), long short-term memory (LSTM), and random forest (RF) models. On this basis, the capabilities of these algorithms in estimating RI and detecting droughts (flash droughts and traditional slowly evolving droughts) were analyzed. Results showed that the RF model achieved the highest skill in terms of RI estimation and flash drought identification among the three approaches. Spatially, the RF-based RI performed best in southeastern China, with an average CC of 0.90 and average RMSE of the 2.6 percentile per week, while poor performances were found in the Xinjiang region. For drought detection, all three ML technologies presented a better performance in monitoring flash droughts than in conventional slowly evolving droughts. Particularly, the probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) of flash drought derived from RF were 0.93, 0.15, and 0.80, respectively, indicating that RF technology is preferable in estimating the RI and monitoring flash droughts by considering multiple meteorological variable anomalies in adjacent weeks to drought onset. In terms of the meteorological driving mechanism of flash drought, the negative precipitation (P) anomalies and positive potential evapotranspiration (PET) anomalies exhibited a stronger synergistic effect on flash droughts compared to slowly developing droughts, along with asymmetrical compound influences in different regions of China. For the Xinjiang region, P deficit played a dominant role in triggering the onset of flash droughts, while in southwestern China, the lack of precipitation and enhanced evaporative demand almost contributed equally to the occurrence of flash drought. This study is valuable to enhance the understanding of flash droughts and highlight the potential of ML technologies in flash drought monitoring.

Abstract Recent years have seen growing appreciation that rapidly intensifying flash droughts are significant climate hazards with major economic and ecological impacts. This has motivated efforts to inventory, monitor, and forecast flash drought events. Here we consider the question of whether the term “flash drought” comprises multiple distinct classes of event, which would imply that understanding and forecasting flash droughts might require more than one framework. To do this, we first extend and evaluate a soil moisture volatility–based flash drought definition that we introduced in previous work and use it to inventory the onset dates and severity of flash droughts across the contiguous United States (CONUS) for the period 1979–2018. Using this inventory, we examine meteorological and land surface conditions associated with flash drought onset and recovery. These same meteorological and land surface conditions are then used to classify the flash droughts based on precursor conditions that may represent predictable drivers of the event. We find that distinct classes of flash drought can be diagnosed in the event inventory. Specifically, we describe three classes of flash drought: “dry and demanding” events for which antecedent evaporative demand is high and soil moisture is low, “evaporative” events with more modest antecedent evaporative demand and soil moisture anomalies, but positive antecedent evaporative anomalies, and “stealth” flash droughts, which are different from the other two classes in that precursor meteorological anomalies are modest relative to the other classes. The three classes exhibit somewhat different geographic and seasonal distributions. We conclude that soil moisture flash droughts are indeed a composite of distinct types of rapidly intensifying droughts, and that flash drought analyses and forecasts would benefit from approaches that recognize the existence of multiple phenomenological pathways.

Abstract With the increasing use of the term “flash drought” within the scientific community, Otkin et al. provide a general definition that identifies flash droughts based on their unusually rapid rate of intensification. This study presents an objective percentile-based methodology that builds upon that work by identifying flash droughts using standardized evaporative stress ratio (SESR) values and changes in SESR over some period of time. Four criteria are specified to identify flash droughts: two that emphasize the vegetative impacts of flash drought and two that focus on the rapid rate of intensification. The methodology was applied to the North American Regional Reanalysis (NARR) to develop a 38-yr flash drought climatology (1979–2016) across the United States. It was found that SESR derived from NARR data compared well with the satellite-based evaporative stress index for four previously identified flash drought events. Furthermore, four additional flash drought cases were compared with the U.S. Drought Monitor (USDM), and SESR rapidly declined 1–2 weeks before a response was evident with the USDM. From the climatological analysis, a hot spot of flash drought occurrence was revealed over the Great Plains, the Corn Belt, and the western Great Lakes region. Relatively few flash drought events occurred over mountainous and arid regions. Flash droughts were categorized based on their rate of intensification, and it was found that the most intense flash droughts occurred over the central Great Plains, Corn Belt, and western Great Lakes region.

Abstract Flash drought refers to relatively short periods of warm surface temperature and anomalously low and rapid decreasing soil moisture (SM). Based on the physical mechanisms associated with flash droughts, these events are classified into two categories: heat wave and precipitation P deficit flash droughts. In previous work, the authors have defined heat wave flash droughts as resulting from the confluence of severe warm air temperature Tair, which increases evapotranspiration (ET), and anomalously low and decreasing SM. Here, a second type of flash drought caused by precipitation deficits is explored. The authors term these events P-deficit flash droughts, which they associate with lack of P. Precipitation deficits cause ET to decrease and temperature to increase. The P-deficit flash droughts are analyzed based on observations of P, Tair, and SM and ET reconstructed using land surface models for the period 1916–2013. The authors find that P-deficit flash droughts are more common than heat wave flash droughts. They are about twice as likely to occur as heat wave flash droughts over the conterminous United States. They are most prevalent over the southern United States with maxima over the southern Great Plains and the Southwest, in contrast to heat wave flash droughts that are mostly likely to occur over the Midwest and the Pacific Northwest, where the vegetation cover is dense.

Abstract Compared to traditional drought events, flash droughts evolve rapidly during short-term extreme atmospheric conditions, with a lasting period of one pentad to several weeks. There are two main categories of flash droughts: the heat wave flash drought (HWFD), which is mainly caused by persistent high temperatures (heat waves), and the precipitation deficit flash drought (PDFD), which is mainly triggered by precipitation deficits. The authors’ previous research focused on the characteristics and causes of flash drought based on meteorological observations and Variable Infiltration Capacity (VIC) model simulations in a humid subtropical basin (Gan River basin, China). In this study, the authors evaluated the downscaled phase 5 of the Coupled Model Intercomparison Project (CMIP5) models’ simulations, coupled with the VIC model (CMIP5–VIC) in reproducing flash droughts in a humid subtropical basin in China. Most downscaled CMIP5–VIC simulations can reproduce the spatial patterns of flash droughts with respect to the benchmarks. The coupled models fail to readily replicate interannual variation (interannual pentad change), but most models can reflect the interannual variability (temporal standard deviation) and long-term average pentads of flash droughts. It is difficult to simultaneously depict both the spatial and temporal features of flash droughts within only one coupled model. The climatological patterns of the best multimodel ensemble mean are close to those of the all-model ensemble mean, but the best multimodel ensemble mean has a minimal bias range and relatively low computational burden.

AbstractWe examine reforecasts of flash droughts over the United States for the late spring (April–May), midsummer (June–July), and late summer/early autumn (August–September) with lead times up to 3 pentads based on the NOAA second-generation Global Ensemble Forecast System reforecasts version 2 (GEFSv2). We consider forecasts of both heat wave and precipitation deficit (P deficit) flash droughts, where heat wave flash droughts are characterized by high temperature and depletion of soil moisture and P deficit flash droughts are caused by lack of precipitation that leads to (rather than being the cause of) high temperature. We find that the GEFSv2 reforecasts generally capture the frequency of occurrence (FOC) patterns. The equitable threat score (ETS) of heat wave flash drought forecasts for late spring in the regions where heat wave flash droughts are most likely to occur over the north-central and Pacific Northwest regions is statistically significant up to 2 pentads. The GEFSv2 reforecasts capture the basic pattern of the FOC of P-deficit flash droughts and also are skillful up to lead about 2 pentads. However, the reforecasts overestimate the P-deficit flash drought FOC over parts of the Southwest in late spring, leading to large false alarm rates. For autumn, the reforecasts underestimate P-deficit flash drought occurrence over California and Nevada. The GEFSv2 reforecasts are able to capture the approximately linear relationship between evaporation and soil moisture, but the lack of skill in precipitation forecasts limits the skill of P-deficit flash drought forecasts.

AbstractFlash droughts are extreme phenomena that have been identified using two different approaches. The first approach identifies these events based on unusually rapid intensification rates, whereas the second approach implicitly identifies short-term features. This latter approach classifies flash droughts into two types, namely, precipitation deficit and heat wave flash droughts (denoted as PDFD and HWFD). In this study, we evaluate these two approaches over the Yellow River basin (YRB) to determine which approach provides more accurate information about flash droughts and why. Based on the concept of intensification rate, a new quantitative flash drought identification method focused on soil moisture depletion during the onset–development phase is proposed. Its performance was evaluated by comparing the onset time and spatial dynamics of the identified flash droughts with PDFD and HWFD events identified using the second approach. The results show that the rapid-intensification approach is better able to capture the continuous evolution of a flash drought. Since the approach for identifying PDFD and HWFD events does not consider changes in soil moisture with time, it cannot ensure that the events exhibit rapid intensification, nor can it effectively capture flash droughts’ onset. Evaluation of the results showed that the chosen hydrometeorological variables and corresponding thresholds, particularly that of temperature, are the main reasons for the poor performance of the PDFD and HWFD identification approach. This study promotes a deeper understanding of flash droughts that is beneficial for drought monitoring, early warning, and mitigation.

AbstractGiven the increasing use of the term “flash drought” by the media and scientific community, it is prudent to develop a consistent definition that can be used to identify these events and to understand their salient characteristics. It is generally accepted that flash droughts occur more often during the summer owing to increased evaporative demand; however, two distinct approaches have been used to identify them. The first approach focuses on their rate of intensification, whereas the second approach implicitly focuses on their duration. These conflicting notions for what constitutes a flash drought (i.e., unusually fast intensification vs short duration) introduce ambiguity that affects our ability to detect their onset, monitor their development, and understand the mechanisms that control their evolution. Here, we propose that the definition for “flash drought” should explicitly focus on its rate of intensification rather than its duration, with droughts that develop much more rapidly than normal identified as flash droughts. There are two primary reasons for favoring the intensification approach over the duration approach. First, longevity and impact are fundamental characteristics of drought. Thus, short-term events lasting only a few days and having minimal impacts are inconsistent with the general understanding of drought and therefore should not be considered flash droughts. Second, by focusing on their rapid rate of intensification, the proposed “flash drought” definition highlights the unique challenges faced by vulnerable stakeholders who have less time to prepare for its adverse effects.

Flash droughts challenge early warnings due to their rapid onset, which requires a proper drought index and skillful nowcasting system. A few studies have assessed the nowcast skill for flash droughts using a one-dimensional index, but whether the models can capture their spatiotemporal evolution remains unclear. In this study, a three-dimensional meteorological flash drought index based on the percentile of 15-day moving average precipitation minus evapotranspiration (P-ET) is developed. The index is then used to investigate the spatiotemporal evolution of a mega-flash drought that occurred in the Yangtze River basin during the summer of 2022. The results show that the mega-flash drought started at the beginning of July in the upper reaches of the river and expanded to the middle and lower reaches at the beginning of August due to the spread of the high-pressure system. The evolution is well captured by the proposed three-dimensional index. The spatial correlations between the China Meteorological Administration global medium-range ensemble forecast system (CMA-GFS)’s nowcast and reanalysis ranged from 0.58 to 0.85, and the hit rate and equitable threat score are 0.54 and 0.26, respectively. This study shows that the CMA-GFS nowcast of the P-ET index roughly captured the drought’s evolution, which can be used for flash drought early warnings and water resource management.

Drought is conventionally known as a slow-developing natural hazard. In recent years, a subset of drought events characterized by rapid onset has been identified and deemed “flash” droughts. These flash droughts can result in rapid soil drying and rapid vegetation degradation making them damaging to agriculture and the economy, so it is essential to develop reliable early warning systems for flash drought events. This study aims to compare the climatology between flash and non-flash droughts across the Contiguous United States (CONUS) and regionally to identify key differences in the drought types to improve early warning. Flash drought is defined as a two- or more category degradation in the U.S. Drought Monitor (USDM) in 4 weeks or less. Potential evapotranspiration (PET), vapor pressure deficit (VPD), maximum temperature (Tmax), and minimum temperature (Tmin) from the Gridded Surface Meteorological Dataset (gridMET) were also analyzed for flash and non-flash drought. It was found that using this definition of flash drought, flash droughts are up to 70% more likely to occur than non-flash droughts over all of the CONUS except the west coast. The South and Southwest regions are more likely to have more frequent and longer flash drought events than the Northwest and Plains regions. This study concludes that PET and VPD are the most reliable variables for differentiating between a flash and non-flash drought event. Furthermore, flash drought is most prevalent and will be the most difficult to predict in the South and Southwest regions and easier to predict in the Northwest and Plains. Also, using a flash drought definition of a drop in two or more categories in the USDM may be too lenient. A narrower flash drought definition, such as a drop in two categories over a two- or three-week period, may be more reflective of the more damaging nature of flash drought events.

Floods and Drought are some of the most catastrophic natural disasters for humanity, averaging 1 to 5 billion dollar of annually damage for flood events and 6 to 8 billion dollars respectively for drought events. To avoid this phenomena risk management science has grown in the last years and allows us to assess the risk and the possible benefits if some specific measures are implemented (e.g. mitigation / adaptation measures). A methodology for Non-Structural Measures (NSM) implementation in risk assessment has been developed for flood event management. Likewise, an uncertainty analysis has been done in order to identify the variation of the possible results in the risk assessment. An analysis has been done based on the Expected Annual Damage (EAD) to determine the optimal return period of design of a structural measure. A new indicator has been proposed based on this analysis: The Optimal Expected Annual Damage indicator (OEAD). In the present document the results of pluvial flood risk assessment are described. These results include structural and non-structural measures based on a developed methodology for Arenys de Munt basin, which belongs to the region of Catalonia in Spain. To include non-structural measures in risk assessment, mitigation coefficients where built in the methodology, and are described in the methodology. Also, steps for the optimization of their possible implementation are defined. This research shows that potential economic losses are decreasing with the construction of structural measures from approximately 6.6 M€ to 3 M€ (box culvert of €14Million), and in combination with the implementation of non-structural measures this could even decrease to 0.7 M€ if the non-structural measures are implemented (for 500 year return period event). Related potential casualties results decrease from approx. 11 casualties to 8 and even as low as 2 casualties respectively if non-structural measures are implemented (for 500 year return period). This, demonstrate that non-structural measures are a way to follow in the flood risk mitigation. For drought events, a new methodology has been developed in order to relate quantitative potential economic losses for rainfed crops with "Meteorological Drought". In the same, a method for the hazard (through the Palmer index) and vulnerability assessment was developed. The susceptibility of a particular crop due to a drought event was linked with a classification of the phenological stages according two seasons: the sowing and harvesting season. The case study was focus on the Llobregat basin, in which both, hydrometeorological and crop statistics data series were available. Results illustrate that the Llobregat basin has suffered at least 2 important periods of drought (2000/2001 and 2005/2006) during the length of the considered 16 year crop production record statistics. These periods of drought caused potential economic losses of approximately 40.13 M€ and 55.84 M€ in the geopolitical subdivision called "Comarcas" of the Llobregat basin. The related methodology, demonstrates coherence in the detection of "important" drought events, and in the quantification of individual potential losses per crop type, which shows that crops, like olives (classified in category woody crop type) are more resistant to drought than vegetables (tomato, lettuce chard etc.). Finally, in addition to the presented methodology the potential losses of crop efficiency curves are proposed, as indicators for agricultural drought risk assessment.
Les inundacions i les sequeres són alguns dels desastres més catastròfics per a la humanitat, promitjant anualment al voltant d'1 a 5 x 10³ milions de dòlars i 6 a 8 x 10³ milions de dòlars en pèrdues econòmiques respectivament. Per combatre aquests fenòmens, la ciència de la "gestió del riscs" ha anat desenvolupant al llarg dels últims anys, permetent-nos quantificar el risc i els possibles beneficis en el cas que algunes mesures siguin implementades (tals com mesures de mitigació/adaptació etc.). En el present document es presenta una metodologia per a la quantificació del risc considerant la implementació de mesures no-estructurals (NSM). Així mateix, es va desenvolupar una anàlisi d'incertesa per identificar les fonts de variància sobre els resultats en el càlcul del risc. Amb l'indicador EAD (Expected Annual Damage), es va realitzar una anàlisi per determinar el període de tornada òptima en el disseny de mesures estructurals, com a resultat del mateix, es proposa un nou indicador: l "Optimal Expected Annual Damage" (OEAD). En el present document s'exposen els resultats per a la quantificació del risc pluvial. Aquests resultats inclouen mesures estructurals i no-estructurals d'acord amb la metodologia desenvolupada per a la conca d'Arenys de Munt a Catalunya-Espanya. Per incloure en el càlcul del risc a les mesures no-estructurals, es van desenvolupar coeficients de mitigació els quals són explicats dins de la metodologia. Igualment, es defineixen els passos a seguir per a l'optimització en la implementació d'aquestes mesures. En aquesta investigació, s'il·lustra que les pèrdues potencials econòmiques disminueixen si una mesura estructural és implementada (canalització per Box Culvert de 14 M€), des de 6.6 M€ a 3 M€ (T=500 anys), i si s'implementen mesures no-estructurals en combinació amb la mesura estructural, les pèrdues potencials poden disminuir-se fins a 0.7 M€ per al període de tornada de 500 anys. Sobre les pèrdues potencials de vides humanes, la mitigació obtinguda segueix el mateix comportament que les pèrdues potencials econòmiques, disminuint des d'11 possibles víctimes a 8 amb la mesura estructural i a 2 en combinació amb la mesura no estructural. Pel fenomen de la sequera, es va desenvolupar una metodologia per relacionar la "Sequera Meteorològica" amb les pèrdues potencials econòmiques en cultius de secà. En la mateixa, es proposa un mètode per a la quantificació de la perillositat (mitjançant els índexs de Palmer) i la vulnerabilitat. La susceptibilitat d'un cultiu de secà a un esdeveniment de sequera (vulnerabilitat) es va relacionar fent una classificació d'acord a dos estats fenològics: l'època de sembra i de recol·lecció. El cas d'estudi es va enfocar a la conca del riu Llobregat-Espanya, de la qual es va disposar d'informació hidrometeorològica i de les estadístiques de producció de diferents tipus de cultius de secà. De l'anàlisi realitzada sobre la conca, es va observar que al llarg dels 16 anys d'estadístiques en els cultius, van ocórrer dos períodes importants de sequera (2000/2001 i 2005/2006). Aquests períodes de sequera van deixar respectivament pèrdues potencials econòmiques d'aproximadament 40.13 M€ i 55.84 M€ per a les comarques associades a la conca del riu Llobregat. La metodologia desenvolupada, demostra eficàcia en la detecció d'esdeveniments importants de sequera, així mateix, il·lustra una coherència en la quantificació de les pèrdues individuals en els tipus de cultiu, en les que cultius com l'oliva (classificat com a cultiu llenyós), demostra més resistència a la sequera respecte a altres cultius com l'enciam, tomàquets etc.. Finalment, com a complement a la metodologia desenvolupada, es proposa a les corbes de pèrdua d'eficiència de cultiu, com a indicadors per a la gestió del risc de sequeres en cultius de secà.

Flash droughts refer to those droughts that intensify rapidly in spring and summer, coupled with a strong increase in summer extreme temperatures, such as those that occurred over Texas in 2011 and the Great Plains in 2012. Climate models failed to predict these flash droughts in 2011 and 2012 and are ambiguous in projecting their future changes, largely because of models’ weaknesses in predicting summer rainfall and soil moisture feedbacks. In contrast, climate models are more reliable in simulating changes of large‐scale circulation and temperatures during winter and spring seasons. Thus, we developed and tested a physical climate indicator of the risk of “flash” droughts in summer by using the large-scale circulation and land surface conditions in winter and spring based on observed relationships between these conditions and their underlying physical mechanisms established by previous observational studies and numerical model simulations. My master research focuses on the spatial distribution of this indicator globally to see how broadly it could be applied. We also compare the different factors to see which one is the dominant contributor to drought in different area. We find that the indicator performs well at capturing the development and termination of a drought. There is much opportunity to develop and improve the indicator further.
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This chapter examines climate change and variability emergency disaster risks on agricultural food security of the local communities in Africa with a focus on gender equality lens in Uganda. Ugandan women contribute up to 75% of domestic food production and yet they are often overburdened with reproduction, household management, gender-specific discrimination, and adverse climate change effects like agricultural droughts, flash flooding, violent windstorms, or water stress. To ensure sustainable food security in the face of climate change vulnerability risks, the role of women is vital. Communication strategy to promote local climate information service (CIS) delivery system has been developed by the local government district planners in the park areas, but there is a lack of capacity to raise public awareness of the gender equality for the empowerment of women and girls for sustainable food security through agriculture production in Uganda for enhanced livelihood assets.

This chapter examines climate change and variability emergency disaster risks on agricultural food security of the local communities in Africa with a focus on gender equality lens in Uganda. Ugandan women contribute up to 75% of domestic food production and yet they are often overburdened with reproduction, household management, gender-specific discrimination, and adverse climate change effects like agricultural droughts, flash flooding, violent windstorms, or water stress. To ensure sustainable food security in the face of climate change vulnerability risks, the role of women is vital. Communication strategy to promote local climate information service (CIS) delivery system has been developed by the local government district planners in the park areas, but there is a lack of capacity to raise public awareness of the gender equality for the empowerment of women and girls for sustainable food security through agriculture production in Uganda for enhanced livelihood assets.

In this chapter, a geomorphic modelling is presented and as a tool for geospatial flood hazard and flash flood thresholds forecasting in drainage basins. The flash flood thresholds have been estimated in terms of flash flood guidance values for the various tributary watersheds of a drainage basin considered. It has been demonstrated using the Limpopo drainage basin in southern Africa. This transboundary basin was chosen because of its importance to water supply for the growing population and water demands in its four riparian states. The basin is also subject to frequent flood and drought hazards. Even though, well established hydrological and flood frequency models do exist for flood forecasting, the purpose of this manuscript is to produce indicative flash flood guidance from a drainage basin of diverse regional development and intensive catchment land-use land cover dynamics by shading light on the geospatial portrayal of flood producing determinants. This will be important in lieu of the need for designing flood forecasting and flood early warning systems for this basin which is subject to frequent flooding hazards. Recommendations on flood forecasting and mitigation of flood hazards is provided considering the technical, human capital and institutional challenges that exist in this part of Africa.

The NICRA project is being implemented in two villages viz., Chamua (since 2010–2011) and Ganakdalani (since 2012–2013 till 2016–2017), which are situated in the west of Lakhimpur district of North Bank Plains Zone of Assam. Chamua village is situated in Kherajkhat Mauza (Taluka), which is 45 km away from North Lakhimpur, the headquarter of district Lakhimpur. On the other hand, Ganakdoloni is situated at Dhalpur Mauza, situated 60 km away from North Lakhimpur and 15 km away from the local township Narayanpur. During 2017–2018 four villages viz., Jakaipelua, Borbali, Borkhet, and Nogaya were adopted under the project. Analysis of long-term rainfall data confirmed the significant decreasing trend of annual as well as monsoonal rainfall in both the Brahmaputra and Barak basins of Assam, India. Variability of rainfall has been increasing in terms of the increased frequency of high-intensity rains and the reduced number of rainy days, leading to localized flash floods and the occurrence of multiple dry spells. Mean season-wise rainfall 2011–2021 indicates long dry periods during the winter season, leading to prolonged dry spells affecting crop growth. About 69% of total rainfall (average annual rainfall of Assam is 2000 mm) is received during the monsoon season, resulting in flash floods leading to crop damage. Out of 12 years of investigation, 10 years are deficit years, resulting in crop stress both during the monsoon and post-monsoon period. Preparation and implementation of real-time crop contingencies are important in responding to weather aberrations in different strategies like preparedness, real-time response, etc. Identification of various adaptation strategies, including climate-resilient crops and cultivars, rainwater harvesting and recycling, efficient energy management through farm mechanization, dissemination of weather information, and weather-based agro-advisories to farmers in a real-time basis, is important adaptation technologies for building climate-resilient agriculture. The study showed that adaption of climate-resilient crop and cropping system and use of harvested rainwater resulted in a 12 to 30% increase in yield observed by the cultivation of high-yielding rice varieties (HYVs) (Ranjit, Gitesh, Mahsuri, etc.) when sown in time (before 15th June) over late sowing conditions (after 20th June). In the case of early season drought, replacement of long duration traditional varieties with short duration HYV and life-saving irrigation using harvested rainwater increased yield by about 59% (short duration var. Dishang) over non-irrigated fields. In case of mid-season and terminal drought, application of an additional dose of 22 kg ha−1 MOP at maximum tillering to grain growth period an increase in yield of about 33% (Ranjit), 32% (Gitesh), 64% (Shraboni), and 57.5% (Mulagabharu) has been observed over farmers’ practice. In highly flood-affected areas under lowland situations replacement of submergence tolerant varieties (Jalashree and Jalkuwari) with traditional deepwater rice varieties resulted in reduced crop loss due to the genetic trait of the deepwater rice, which can withstand water logging for a long period. With an increase in the level of mechanization through the use of machinery available in the custom hiring center the human and animal hour requirement for paddy cultivation was reduced from 795 to 350 hrha−1 and 353 to 23 hrha−1, respectively. Alternate land use in terms of low-cost poly house, vermicompost production, and mushroom cultivation also resulted in nutritional security and generation of higher income for the farmers

Extreme black-swan occurrences like earthquakes, glacial lake outbursts, flash floods, landslides, etc. are important concerns in Himalayan countries like Nepal, which are highly susceptible, geologically active, and exquisitely fragile. Nepal generates 97 percent of its electricity from hydropower, where 56.08 percent of it is coming from seasonal run-off-river (RoR) hydro plants. Landslides and mudflows are common in the monsoon, and low discharge is common in the winter season. These RoR plants must be able to withstand high-impact events like earthquakes and lengthy droughts in order for the Nepalese grid to remain secure. This study gives a presentation and overview of previously occured natural hazards in Nepal related to hydropower plants. In particular, the 2014 Sunkoshi landslide and the 2021 Melamchi flood are evaluated as extreme events and their impacts on hydropower plant has been studied. In addition, an in-depth investigation on a ROR plant is carried out. Moreover, the water discharge and extreme rainfall peaks in time series data is evaluated using an ARIMA-based model. This paper shows the feasibility of predicting the energy produced by a run-off river hydropower plant. The purpose is to forecast discharge and hence the ROR power generation with the aim to facilitate the hydropower operators for their availability declaration which will again help in the overall energy planning. The results are discussed together with performance metrics, and indicates that the implemented technique is promising.These predictions can be further used for planning and estimating the power generation on a more complex level.

Due to climate change, extreme rainfall is more frequent, and the phenomenon of drought and desertification in some parts of the world is accentuated. Scientists forecast that these trends to continue as the planet continue to warm. An increasingly common phenomenon is the occurrence of flash floods in areas where human intervention on natural conditions has been significant. Over this intervention is superimposed the modification of the characteristics of extreme rainfalls (duration, intensity, height), resulting a series of negative consequences on the ecosystems of the watersheds. For their protection, a more accurate forecast of the size and times of occurrence of the maximum water flows and levels in different sections are needed. This forecast must be made with appropriate methods, such as the use of advanced hydroinformatic tools. This paper analyses the influence of rainfall characteristics on runoff in a small watershed, using rainfall-runoff phenomenon modelling. The modelling is realized using advanced hydroinformatic tool MIKE11, developed by Danish Hydraulic Institute (DHI).

Hydrological extremes (drought-flood) are a phenomenon that is occurring more and more frequently because of climate change. The human-altered landscape cannot sufficiently withstand these extreme phenomena. For this reason, society feels pressure on the design, and assessment, but especially the implementation of adaptation and mitigation measures in the landscape. For best-designed measures, it is crucial to determine where the given problem arises and what are the possibilities of its solution with subsequent quantification of effectiveness. In the Czech Republic, this problem is solved in the long term by processing flood maps and determining flood areas. In 2009, a methodology was created for the identification of places that are potentially threatened by flash floods [1]. In the interest area of the Dyje basin, 1356 critical points were determined by this methodology. The work's main goal was to evaluate these points and their contributing areas based on current data, and the summary and evaluation of the accessible data that will be used for proposals for measures. All analyses were made by using geographic information systems. It was specifically about evaluating the percentage representation of arable land, as one of the main criteria for determining the critical point. It was found that in almost 42 % of the critical points (or in their contributing areas) there was a decrease in arable land by more than 10 %. Furthermore, the occurrence of recorded erosion events was addressed. According to information from the Research Institute for Soil and Water Conservation, there were 622 erosion events in the Dyje basin area, and 43 % were in catchment areas of critical points. One of the crucial topics that are currently resonating in society in terms of proposals for measures in the landscape is drainage areas. According to vectorized documents from the Agricultural Water Management Company, these areas are in 57 % of the collection areas of critical points. The evaluation will further enter a multi-criteria analysis for the selection of a priority area, as the Dyje basin is quite extensive for more detailed analyses. Subsequently, protective measures close to nature will be designed and evaluated in the priority area using mathematical modelling.