Dry Days Research Articles

Atmospheric Rivers and Weather Types in Aotearoa New Zealand: A Two‐Way Story

AbstractHere, we analyze the inter‐relationships between weather types (WTs) and atmospheric rivers (ARs) around Aotearoa New Zealand (ANZ), their respective properties, as well as their combined and separate influence on daily precipitation amounts and extremes. Results show that ARs are often associated with 3–4 WTs, but these WTs change depending on the regions where ARs landfall. The WTs most frequently associated with ARs generally correspond to those favoring anomalously strong westerly wind in the mid‐latitudes, especially for southern regions of ANZ, or northwesterly anomalies favoring moisture export from the lower latitudes, especially for the northern regions. WTs and ARs show strong within‐type and inter‐event diversity. The synoptic patterns of the WTs significantly differ when they are associated with AR occurrences, with atmospheric centers of actions being shifted so that moisture fluxes toward ANZ are enhanced. The location, angle, and persistence of ARs appear strongly driven by the synoptic configurations of the WTs. Although total moisture transport shows weaker WT‐dependency, it appears strongly related to zonal wind speed to the south of ANZ, or the moisture content of the air mass to the north. Finally, WT influence on daily precipitation may completely change depending on their association, or lack thereof, with AR events. WTs traditionally considered as favorable to wet conditions may conceal daily precipitation extremes occurring during AR days, and anomalously dry days or near‐climatological conditions during non‐AR days.

Insights into Rainfall Extremities Across the Agroclimatic Zones of Tamil Nadu, India

Rainfall is a crucial agrometeorological parameter that impacts hydrology and agricultural planning in a region. The spatiotemporal changes in the occurrences of precipitation extremes must be monitored to reduce the hazards caused by the fluctuating rainfall pattern. The extreme rainfall indices for each year categorized under excess, normal and deficit rainfall categories were calculated over the agroclimatic zones of Tamil Nadu using the high-resolution CHIRPS datasets from 1991 to 2022. The results highlighted that High Rainfall Zone has more consecutive wet days (22 days), minimum consecutive dry days (25 days) and Daily Intensity Index with threshold of 2.5 mm (28.6 mm) compared to other zones. The maximum consecutive dry days of 99 days, a high rainy day of 142 days, and minimum daily intensity of 8.9 mm are experienced by the Cauvery Delta Zone, High Altitude and Hilly Zone, and Western Zone, respectively. Overall, the High Rainfall Zone faces a higher number of extreme rainfall events in terms of wet days and intensity, whereas the average maximum consecutive dry days and minimum rainfall intensity is observed over the north eastern zone and north western zone, respectively indicating high dry periods.

Assessing spatiotemporal trends of total and extreme precipitation in a subtropical highland region: A climateperspective.

This study used a dataset of 30 years (1990-2020) of daily observations from 24 meteorological stations in the northern highlands of Pakistan to assess trends in extreme precipitation indices. The RClimDex model was used to analyze the indices, and the Modified Mann-Kendal test and the Theil-Sen slope estimator were applied to determine trends and slopes, respectively. The results showed a significant decrease in total annual precipitation amount (PRCPTOT) with varying rates of negative trend from -4.44 mm/year to -19.63 mm/year. The total winter and monsoon precipitation amounts were also decreased during the past three decades. The intensity-based precipitation indices (RX1Day, RX5Day, R95p, R99p, and SDII) showed a significant decrease in extreme intensity events over time, while the count of consecutive dry days (CDD) and consecutive wet days (CWD) indicated a significant decrease in duration at multiple stations. The annual counts of days with precipitation more than or equal to 10 mm (R10), 20 mm (R20), and 25 mm (R25) exhibited a significant decrease in frequency of extreme precipitation events, with the decrease more pronounced in the northern parts of the study domain. The findings of this study indicate a significant decline in the intensity, frequency, and extent of precipitation extremes across the northern highlands of Pakistan over the past 30 years.

Stability Analyses of pearl Millet Genotypes (Pennisetum glaucum) and its Related Traits Using the Freeman and Perkins Model

In the present study, twenty-nine genotypes were carried out to determine the stability of morphological characters viz., dry fodder yield, Days to 50% flowering, and Days to maturity of pearl millet in eight different environments viz., ARS Mandor, Bikaner, RARI Jaipur, Jamnagar, Hisar, Gwalior, Ranchi and Jammu Kashmir using Freeman and Perkins model. Data was collected from ICAR- All India Coordinated Research Projects (AICRP) of pearl millet, Agricultural University, Mandor, Rajasthan, India for one year (2019). The combined analysis of variance showed significant differences among genotypes, environments and Genotype by Environment (G x E) interaction for all morphological characters under study. Mean, regression coefficient and deviation from regression were used as stability measures. Genotype G23 exhibited stability across all studied traits, while G10 and G29 demonstrated stability specifically for dry fodder yield and days to 50% flowering. Furthermore, genotype G22 displayed stability for dry fodder yield and days to maturity in all environments.

The Dichotomy of Wet and Dry Trends Over India by Aerosol Indirect Effects in CMIP5 Models

AbstractAerosol‐cloud interactions, also known as aerosol indirect effect (AIE), substantially impact rainfall frequency and intensity. Here, we analyze NEX‐GDDP, a multimodel ensemble of high‐resolution (0.25°) historical simulations and future projections statistically downscaled from 21 CMIP5 models, to quantify the importance of AIE on extreme climate indices, specifically consecutive dry days (CDD), consecutive wet days (CWD), and simple daily intensity index (SDII). The 21 NEX‐GDDP CMIP5 models are classified into models with reliable (REM) and unreliable (UREM) monsoon climate simulated over India based on their simulations of the climate indices. The REM group is further decomposed based on whether the models represent only the direct (REMADE) or the direct and indirect (REMALL) aerosol effects. Compared to REMADE, including all aerosol effects significantly improves the model skills in simulating the observed historical trends of all three climate indices over India. Specifically, AIE enhances dry days and reduces wet days in India in the historical period, consistent with the observed changes. However, by the middle and end of the 21st century, there is a relative decrease in dry days and an increase in wet days and precipitation intensity. Moreover, the REMALL simulated future CWD and CDD changes are mostly opposite to those in REMADE, indicating the substantial role of AIE in the future projection of dry and wet climates. These findings underscore the crucial role of AIE in future projections of the Indian hydroclimate and motivate efforts to accurately represent AIE in climate models.

Drought Potential in Borneo Based on the RCP 4.5 Scenario

One of the impacts of climate change is an increase in the frequency and intensity of hydrometeorological disasters such as prolonged droughts. Borneo is one of the areas threatened by drought due to climate change. Therefore, it is important to identify and implement appropriate mitigation and adaptation measures. This study used the dynamical downscaling method by the Conformal Cubic Atmospheric Model (CCAM) to evaluate the potential for drought events in Borneo based on the RCP 4.5 scenario. The annual rainfall in Borneo for 2021-2050 is projected to increase compared to 1991-2020. However, the increase in annual rainfall does not free Borneo from the possibility of drought events in the future. This study’s results indicate that areas in southern Borneo, such as Banjarmasin, Pangkalan Bun, and Pontianak, will have a higher frequency of meteorological drought events and are also expected to experience longer periods of consecutive dry days between 2021-2050 compared to 1991-2020.

Winter Precipitation Responses to Projected Arctic Sea Ice Loss and Global Ocean Warming and Their Opposing Influences over the Northeast Atlantic Region

Abstract Using a large ensemble of simulations from the Polar Amplification Model Intercomparison Project (PAMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6), we compare the response of winter-mean precipitation and daily extremes across the Northern Hemisphere to future Arctic sea ice loss and global ocean warming. The North Atlantic is simulated to become drier in response to future Arctic sea ice loss, with reduced precipitation intensity and more dry days. A wetting response to sea ice loss is simulated over the midlatitude Atlantic Ocean. These responses are robust across the eight models analyzed, albeit with differences in their magnitude and spatial pattern. The precipitation response to global ocean warming is broadly opposite in sign, but larger in magnitude, compared to the response to sea ice loss, over these regions. The precipitation responses to both sea ice loss and ocean warming are strongly related to coincident changes in storm density and intensity. More specifically, there is an equatorward shift of the North Atlantic storm track in response to sea ice loss, and a northeastern extension of the North Atlantic storm track and a weakening of the Mediterranean storm track in response to ocean warming. The linear combination of the responses of future Arctic sea ice loss and global ocean warming explain well the spatial pattern of the precipitation change at 2°C global warming projected in CMIP6. Our results suggest that the projected future precipitation change over the North Atlantic reflects a “tug of war” between Arctic sea ice loss and global ocean warming, but the latter dominates over the former.

Association of dry matter intake, milk yield, and days to first ovulation with cytological endometritis in Holstein cows

Dry matter intake (DMI, kg/d) is closely related to the magnitude of negative energy and protein balance during the transition period, and the metabolic adaptations to support lactation in dairy cows. Thus, DMI might affect the development of cytological endometritis in the early postpartum period. Difficulty to adapt to these metabolic changes is related to impaired immune function and increased occurrence of reproductive disorders. We aimed to examine the association of pre- and postpartum DMI, body weight (BW), body condition score, milk yield and milk composition, and days to first ovulation with cytological endometritis at 15 (CYT15) and 30 DIM (CYT30). A second objective was to understand the association of vaginal discharge with CYT15 and CYT30 and performance. We conducted a pooled statistical analysis of 5 studies, including data from 280 multiparous Holstein cows. Based on the cutoffs for the percentage of uterine polymorphonuclear cells (PMN), determined by taking the median value of the data set for 15 and 30 DIM, cows were categorized as follows: LOW15 (PMN % at 15 DIM ≤24%; n = 125), HIGH15 (PMN % at 15 DIM >24%; n = 125), LOW30 (PMN % at 30DIM ≤7%; n = 141); and HIGH30 (PMN % at 30DIM >7%; n = 139). Cows in HIGH15 consumed an average of 1.97 ± 0.5 kg/d less DM than cows in LOW15 during prepartum, and 3.01 ± 0.5 kg/d less DM during postpartum. Dry matter intake (as a percentage of BW) was higher for cows in LOW15 during pre- and postpartum than for cows in HIGH15. Moreover, cows in HIGH15 tended to have lower milk yield than cows in LOW15 from the third until the fifth week postpartum. Although DMI was not associated with CYT30, DMI (as a percentage of BW) was lower for cows in LOW30 pre- and postpartum than for cows in HIGH30. There was no association between CYT30 and milk yield. Cows in LOW15 had greater days to first ovulation than cows in HIGH15, while cows in LOW30 also had greater days to first ovulation than cows in HIGH30. Simple regression analyses demonstrated linear associations of increased DMI, particularly postpartum, with decreased uterine PMN percentage and lower vaginal discharge score. Additionally, increased units of vaginal discharge score and increased percentage units of uterine PMN were linearly associated with decreased milk yield. Corroborating with the notion of the ovarian function being associated with uterine inflammatory status, cows in HIGH15 and HIGH30 ovulated on average 3 d before than cows in LOW15 and LOW30, respectively. Cytological endometritis at 15 DIM was associated with lower DMI from 4 wk before calving until 4 wk postpartum and was associated with lower milk yield. The association of vaginal discharge with cytological endometritis was variable and dependent on the day of evaluation.

Evaluating the Impact of Future Seasonal Climate Extremes on Crop Evapotranspiration of Maize in Western Kansas Using a Machine Learning Approach

Data-driven technologies are employed in agriculture to optimize the use of limited resources. Crop evapotranspiration (ET) estimates the actual amount of water that crops require at different growth stages, thereby proving to be the essential information needed for precision irrigation. Crop ET is essential in areas like the US High Plains, where farmers rely on groundwater for irrigation. The sustainability of irrigated agriculture in the region is threatened by diminishing groundwater levels, and the increasing frequency of extreme events caused by climate change further exacerbates the situation. These conditions can significantly affect crop ET rates, leading to water stress, which adversely affects crop yields. In this study, we analyze historical climate data using a machine learning model to determine which of the climate extreme indices most influences crop ET. Crop ET is estimated using reference ET derived from the FAO Penman–Monteith equation, which is multiplied with the crop coefficient data estimated from the remotely sensed normalized difference vegetation index (NDVI). We found that the climate extreme indices of consecutive dry days and the mean weekly maximum temperatures most influenced crop ET. It was found that temperature-derived indices influenced crop ET more than precipitation-derived indices. Under the future climate scenarios, we predict that crop ET will increase by 0.4% and 1.7% in the near term, by 3.1% and 5.9% in the middle term, and by 3.8% and 9.6% at the end of the century under low greenhouse gas emission and high greenhouse gas emission scenarios, respectively. These predicted changes in seasonal crop ET can help agricultural producers to make well-informed decisions to optimize groundwater resources.

Selection of Intermittent Irrigation to Increase Growth and Yield of Some Local Rice Varieties (Oryza sativa L.) in the Rainy Season

This study aims to examine the influence of various varieties and methods of irrigation on the response to rice growth and yield. The research was conducted in the Experimental Land of the Faculty of Agriculture, University of Muhammadiyah Yogyakarta, in January 2020. The study was conducted in the area using a factorial strip plot design in a Randomized Completely Block Design with three replications. Thirty-six experimental units were obtained. This research consists of two factors. Factor I consists of 4 methods of irrigation, namely continuous flooding, ten days flooding, six dry days, eight days flooding, eight dry days, and six days flooding, ten dry days. Factor II consists of 3 varieties: Ciherang, Cempo Hitam, and Mentik Susu. The observed parameters are the height of plants, number of tillers, leaves area, length of roots, fresh weight of plants, dry weight of plants, harvest index, panicle number, and weight of grain/ hectare. This study showed that Cempo Hitam and Mentik Susu varietas rice plants were higher, and the leaves were more expansive than the Ciherang variety. Irrigation does not affect plant height, number of tillers, leaf area, root length, or rice panicles. There is a mutual influence between variety with irrigation on the fresh and dry weight of rice plants, panicle length, harvest index, and yield per hectare of rice. A variety of Mentik Susu with conventional irrigation, ten days flooded, six days dry, six days flooded, and ten days dry, showed higher yields per hectare compared to the combination of other varieties and irrigations.

Impact of bias correction on climate change signals over central Europe and the Iberian Peninsula

Vegetation models for climate adaptation and mitigation strategies require spatially high-resolution climate input data in which the error with respect to observations has been previously corrected. To quantify the impact of bias correction, we examine the effects of quantile-mapping bias correction on the climate change signal (CCS) of climate, extremes, and biological variables from the convective regional climate model COSMO-CLM and two dynamic vegetation models (LPJ-GUESS and CARAIB). COSMO-CLM was driven and analyzed at 3 km horizontal resolution over Central Europe (CE) and the Iberian Peninsula (IP) for the transient period 1980–2070 under the RCP8.5 scenario. Bias-corrected and uncorrected climate simulations served as input to run the dynamic vegetation models over Wallonia. Main result of the impact of bias correction on the climate is a reduction of seasonal absolute precipitation by up to −55% with respect to uncorrected simulations. Yet, seasonal climate changes of precipitation and also temperature are marginally affected by bias correction. Main result of the impact of bias correction on changes in extremes is a robust spatial mean CCS of climate extreme indices over both domains. Yet, local biases can both over- and underestimate changes in these indices and be as large as the raw CCS. Changes in extremely wet days are locally enhanced by bias correction by more than 100%. Droughts in southern IP are exacerbated by bias correction, which increases changes in consecutive dry days by up to 14 days/year. Changes in growing season length in CE are affected by quantile mapping due to local biases ranging from 24 days/year in western CE to −24 days/year in eastern CE. The increase of tropical nights and summer days in both domains is largely affected by bias correction at the grid scale because of local biases ranging within ±14 days/year. Bias correction of this study strongly reduces the precipitation amount which has a strong impact on the results of the vegetation models with a reduced vegetation biomass and increases in net primary productivity. Nevertheless, there are large differences in the results of the two applied vegetation models.

Drivers of Dry Day Sensitivity to Increased CO2

AbstractPersistent precipitation deficits are among the most impactful consequences of global warming. Here we focus on changes in the annual number of dry days (NDD) and in the annual maximum length of dry spells due to a quadrupling of atmospheric CO2. We use atmosphere‐only simulations to decompose the projected changes into additive contributions. A fast adjustment leads to a global increase in NDD despite notable regional exceptions (e.g., South Asia and Sahel). The effect of the uniform component of the surface ocean warming is model‐dependent but shapes the regional distribution of the NDD response in each model. Finally, the ocean warming pattern also contributes to large uncertainties, likely through contrasting changes in large‐scale circulation. Our results thus highlight the complexity of the NDD response, with policy‐relevant practical implications for mitigation and adaptation strategies.

HydroPol2D — Distributed hydrodynamic and water quality model: Challenges and opportunities in poorly-gauged catchments

Floods are one of the deadliest natural hazards and are exacerbated by changes in land-use and climate. Urban development decreases infiltration by reducing pervious areas and increases the accumulation of pollutants during dry weather. It also decreases infiltration by reducing pervious areas and increases the accumulation of pollutants during dry periods. During rainy events, there is an increase in pollution concentrations and runoff that may be a source of water supply during drought periods. Modeling the quantity and quality dynamics of stormwater runoff requires a coupled hydrodynamic module capable of estimating the transport and fate of pollutants. In this paper, we evaluate the applicability of a distributed hydrodynamic model coupled with a water quality model (HydroPol2D). First, the model is compared to GSSHA and WCA2D in the V-Tilted catchment, and the limitation of the critical velocity of WCA2D is investigated. We also applied the model in a laboratory wooden board catchment, focusing on the validation of the numerical approach to simulate water quality dynamics. Then, we apply HydroPol2D in the Tijuco Preto catchment, in São Carlos - Brazil, and compare the modeled results with the full momentum solver of the HEC-RAS 2D. This catchment shares similar characteristics with many poorly-gauged and human-impacted catchments worldwide. The implementation of the model, the governing equations, and the estimation of input data are discussed, indicating the challenges and opportunities to scale HydroPol2D into the reality of data scarcity of larger poorly-gauged catchments. For a 1-yr return period of rainfall and antecedent dry days, and assuming an uncertainty of 40% in the water quality parameters, the results indicate that the maximum concentration of total suspended solids (TSS), the maximum load and the mass of the pollutant washed in 30% of the volume are, 456±260 mgL-1km-2, 2.56±0.4 kgs-1km-2, and 89%±10%, respectively.

Pemodelan Numerik Hubungan Pola Curah Hujan Wilayah Equatorial di Pulau Sumatera Terhadap Fenomena ENSO dan IOD

A numerical modeling has been built for the relationship between rainfall in the equatorial region of Sumatra to the ENSO and IOD phenomena by taking data from 1991 to 2020 at three stations located in the western region of Sumatra Island, namely SM Japura, SM Minangkabau and SM Hang Nadim. The method used in this study is the method of correlation and linear regression on the Niño3.4 Index variable and the Dipole Mode Index on the amount of rainfall. The data visualization process is carried out with the output in the form of plots and graphs with Goole Colab coding. The resulting graph is a graph of the ENSO and IOD phenomena, as well as a regression graph between The Niño3.4, DMI and the amount of rainfall per month. This study was conducted with the aim of knowing how much influence the El Niño Southern Oscillation (ENSO) variable represented by the Niño3.4 Index and the Indian Ocean Dipole (IOD) represented by DMI had on rainfall in the equatorial region in the 1991 – 2020 period and to see the trend of significance between the two towards the equatorial region on the island of Sumatra. Rainfall in Indonesia's equatorial region tends to be influenced by IOD compared to ENSO. The combination of the two at the same time can cause a significant change in the amount of rainfall. La-Niña and negative IOD occurred in 1992, 1996, 1999, 2000, 2005, 2008, 2011 and 2016. The average rainy day index (SDII) tended to decrease in Japura Island in 1996, 2005, 2011, 2016 , at SM Minangkabau in 1992, 1996, 1999, 2000, 2016 and at SM Hang Nadim in 1996, 1999 and 2008. Meanwhile the longest series of wet days tended to decrease in SM Japura in 1992, 1996, 1999, 2005, in SM Minangkabau in 1992, 1996, 2005, 2008, and in SM Hang Nadim in 1992, 2000, 2005, 2008 and 2011. The longest series of dry days tended to increase in SM Japura in 1996, 2011, in SM Minangkabau in 1996, 2000, 2011, and at SM Hang Nadim in 1996.

Changes in Extreme Temperature and Precipitation over the Southern Extratropical Continents in Response to Antarctic Sea Ice Loss

Abstract Current climate models project that Antarctic sea ice will decrease by the end of the twenty-first century. Previous studies have suggested that Antarctic sea ice changes have impacts on atmospheric circulation and the mean state of the Southern Hemisphere. However, little is known about whether Antarctic sea ice loss may have a tangible impact on climate extremes over the southern continents and whether ocean–atmosphere coupling plays an important role in changes of climate extremes over the southern continents. In this study, we conduct a set of fully coupled and atmosphere-only model experiments forced by present and future Antarctic sea ice cover. It is found that the projected Antarctic sea ice loss by the end of the twenty-first century leads to an increase in the frequency and duration of warm extremes (especially warm nights) over the southern continents and a decrease in cold extremes over most regions. The frequency and duration of wet extremes are projected to increase over South America and Antarctica, whereas changes in dry days and the longest dry spell vary with regions. Further Antarctic sea ice loss under a quadrupling of CO2 leads to similar but larger changes. Comparison between the coupled and atmosphere-only model experiments suggests that ocean dynamics and their interactions with the atmosphere induced by Antarctic sea ice loss play a key role in driving the identified changes in temperature and precipitation extremes over southern continents. By comparing with global warming experiments, we find that Antarctic sea ice loss may affect temperature and precipitation extremes for some regions under greenhouse warming, especially Antarctica.

Projected changes in extreme precipitation indices over the Lake Urmia basin in Iran

Abstract This study investigates the future changes in precipitation extreme indices in the Lake Urmia Basin during the period 2021–2100 compared to the base period (1987–2016), using the Coupled Model Intercomparison Project Phase 5 models. Trend analysis was performed using Mann–Kendall test and Sen's estimator. The output of these models was downscaled by the Long Ashton Research Station Weather Generator method for the representative concentration pathway (RCPs) 4.5 and 8.5. A model averaging technique was employed to create an ensemble model. The results showed that the average precipitation of the basin will decrease by the end of the 21st century. The projection also showed that the consecutive dry day's index increases based on both scenarios. However, other indices (maximum 1-day precipitation, maximum 5-day precipitation, very wet days, consecutive wet days, simple daily intensity index, and wet-day precipitation) are reduced compared to the base period. Moreover, the slope of significant trends in the RCP8.5 is greater and more severe than that in RCP4.5.

Enhanced relationship between February Aleutian low and spring extreme consecutive dry days in the Yangtze-Huai River region in recent two decades: roles of Bering Sea ice and stratospheric polar vortex

Enhanced relationship between February Aleutian low and spring extreme consecutive dry days in the Yangtze-Huai River region in recent two decades: roles of Bering Sea ice and stratospheric polar vortex

Forecasting landslides using community detection on geophysical satellite data.

As a result of extreme weather conditions, such as heavy precipitation, natural hillslopes can fail dramatically; these slope failures can occur on a dry day, due to time lags between rainfall and pore-water pressure change at depth, or even after days to years of slow motion. While the prefailure deformation is sometimes apparent in retrospect, it remains challenging to predict the sudden transition from gradual deformation (creep) to runaway failure. We use a network science method-multilayer modularity optimization-to investigate the spatiotemporal patterns of deformation in a region near the 2017 Mud Creek, California landslide. We transform satellite radar data from the study site into a spatially embedded network in which the nodes are patches of ground and the edges connect the nearest neighbors, with a series of layers representing consecutive transits of the satellite. Each edge is weighted by the product of the local slope (susceptibility to failure) measured from a digital elevation model and ground surface deformation (current rheological state) from interferometric synthetic aperture radar (InSAR). We use multilayer modularity optimization to identify strongly connected clusters of nodes (communities) and are able to identify both the location of Mud Creek and nearby creeping landslides which have not yet failed. We develop a metric, i.e., community persistence, to quantify patterns of ground deformation leading up to failure, and find that this metric increased from a baseline value in the weeks leading up to Mud Creek's failure. These methods hold promise as a technique for highlighting regions at risk of catastrophic failure.

Heat pulse velocity method for determining water requirements in rainfed sweet cherry trees (Prunus avium L.)

It is imperative to possess a comprehensive understanding of the water consumption patterns of sweet cherry trees under rainfed conditions. This study investigates the water use of sweet cherry using the heat pulse velocity sap flow method. Tree response to drying soil conditions over two consecutive measurement periods (September 2017 to December 2018) in the eastern Free State, South Africa, is also evaluated. During the post-harvest period (December), there was a continuous increase in daily water consumption by trees, in conjunction with an increase in canopy cover, even though the crop load was reduced. Measured sap flow was positively correlated to net radiation, air temperature, and water vapour pressure deficit. The transpiration rates ranged from 1.2 to 3.5 L d-1 during the flowering stage (day of year, DOY, 244 – 270) and showed an increasing trend as the days progressed. During the ripening stage (DOY 271 – 292), transpiration rates decreased from 4.5 to 1.1 L d-1 over the 2018 season. This decreasing trend from the previous growth stage was due to soil drying and scorching weather conditions that led to trees experiencing water stress. Sap flow measurements, however, showed typical characteristics of the diurnal trend during selected days during varying weather conditions. The fraction of transpirable soil water (FTSW) threshold varied for different fruit growth stages and approached 1.0 for different stress levels. FTSW exceeded 0.4 when sweet cherry trees utilised stored soil water, while the transpiration rates declined during prolonged hot days. Moreover, the stress coefficient factor ranged between 0.45 – 0.65 for different growth stages. The daily soil water content varied, and soil evaporation was expected to increase during hot and dry days. In the early stage of a dry spell, soil water content did not directly affect the transpiration rate. Sweet cherry trees are susceptible to soil water deficit at different stages of fruit development. More research is required to understand transpiration as an irrigation management and planning indicator.

Recent Changes in Hydrometeorological Extremes in the Bilate River Basin of Rift Valley, Ethiopia

The hydroclimatic extremes such as floods and droughts have been causing damage and losses with rising frequency than ever before. The human-induced and internal climate variability create extreme events and local hydrometeorological changes influencing climate-sensitive sectors. This research is aimed at analyzing the recent changes in the hydrometeorological extremes using indices over the Bilate basin in Ethiopia. Mann-Kendall and Sen’s slope estimator were used to examine changes in hydrometeorological extreme indices. The rainy days’ rate of change falls between +10.64 mm in the downstream to −10.67 mm in the upstream north. The wet day rainfall and heavy rainfall day indices were stronger in the basin’s southwest, implying more likely flood events. The consecutive dry days show a rising tendency with more variability, while the consecutive wet days show no trend with less variability. The change point analysis revealed inconsistencies for the majority of the extreme indices. The stations’ average warmest nights and days significantly increased at a rate of 0.0358°C and 0.0320°C per annum, respectively. The coldest nights in most of the stations show a significant and negligible rise in the basin while on the coldest days more than half of the stations declining. The peak flow in the annual and seasonal time series shows a rising trend and a dominant rise in most low flow indices, which possibly flashes downstream flooding. The global and local climate anomalies revealed a weak correlation, but with overlap of wet and drought years. Basin water resource plans may benefit from identified overlap cross of threshold years for improved flood control and drought monitoring.