Distribution Of Annual Precipitation Research Articles

Data-driven analysis of annual rain distributions

Rainfall is an important component of the climate system, and its statistical properties are vital for prediction purposes. In this study, we have developed a statistical method for constructing the distribution of annual precipitation. The method is based on the convolution of the measured monthly rainfall distributions and does not depend on any presumed annual rainfall distribution. Using a simple statistical model, we demonstrate that our approach allows for a better prediction of extremely dry or wet years with a recurrence time several times longer than the original time series. The method that has been proposed can be utilized for other climate variables as well. Published by the American Physical Society 2024

Effects of precipitation changes on fractional vegetation cover in the Jinghe River basin from 1998 to 2019

Studying the spatiotemporal evolutionary characteristics of vegetation and the effect of precipitation changes is necessary for understanding the regional ecological environment. We used trend analysis, partial correlation analysis, significance tests, and residual trend analysis to analyze the spatiotemporal evolution characteristics and driving factors of fractional vegetation cover (FVC) in the Jinghe River Basin (JRB) from 1998 to 2019. The results showed that vegetation coverage in the JRB significantly improved from 1998 to 2019. FVC showed an increasing trend in 90.64% of the areas in the JRB, and the overall annual change in FVC was extremely significant (p ≤ 0.01). However, precipitation in the JRB showed an insignificant increasing trend; the annual distribution of precipitation developed in a uniform direction and the precipitation centroid tended to move backward. The area with a significant correlation between the FVC change and the precipitation concentration index accounted for the largest proportion (18.47%). Precipitation changes in the JRB generally favored vegetation recovery; however, the effect was limited and non-precipitation factors dominated the changes in FVC. Our study contributes to a more comprehensive understanding of the effects of changes in precipitation patterns on vegetation cover to facilitate regional ecological protection.

Determination of Onset and End of Growing Season in Nigeria using the Modified Dynamic (Optimal) Threshold Method and Satellite data

Understanding and accurately determining the onset and end of the growing season is essential for crop management, forecasting yields, and assessing the impacts of climate change, which are crucial for various sectors such as agriculture, ecology, and climate science. The study investigates the start and end of seasons using the optimal threshold method in different climate zones from 2001 to 2022. The climate zones include Tropical Rainforest (Af), Tropical Monsoon (Am), Tropical Wet (Aw), Hot Semi-Arid (BSh), Hot Arid (BWh), and Hot Summer Mediterranean climates. The relationship between climate parameters (temperature and precipitation) and phenology was examined using cross-correlation analysis. Furthermore, the research explores the annual distribution of precipitation and temperature, highlighting the variable nature of precipitation compared to temperature. Climate zone-specific analyses reveal trends in precipitation and temperature changes, indicating potential impacts on vegetation growth. The results show that the Af (BWh) climate zone indicated the longest (shortest) season length, and longer zones with a larger Length of Season (LOS) experienced delayed End of Season (EOS) and/or an early onset of the season. Moreover, Af climate seasons start earlier and finish later than those in the other climate zones. The findings have shown that season length (LOS) in Af, Aw, BSh, BWh, and Csb increased at 1.2, 0.4, 0.2, 0.9, and 0.5 days/yr, respectively. However, it is noteworthy that Am experiences a contraction at -0.6 days/yr. The study found that climatic fluctuation has an impact on vegetation phenology throughout all climate zones of Nigeria. Changes in agricultural growing seasons should be studied to maximize agricultural output.

Micro-ridge-furrow soil moisture regulation technology improves seedling quality and yield of winter rapeseed

Rapeseed (Brassica napus L.) is an important oil crop worldwide, and the Yangtze River Basin (YRB) region is one of the most vital rapeseeds producing areas in China. However, the uneven distribution of annual precipitation during the rapeseed seedling stage in this region often leads to droughts and waterlogging, resulting in declined rapeseed seedling quality and yield. Therefore, this study aimed to assess the impact of micro-ridge-furrow planting (MR) and conventional flat cropping planting (FC) under straw returning on rapeseed seedling growth and yield during two growing seasons: wet year (WY) and dry year (DY). In MR planting, rapeseed was sown either on the ridge surface (RS) or in the ridge furrow (RF). We found that MR planting had stronger regulation of soil temperature and humidity compared to FC. The average soil volume water content in RS was 19.2 % lower than FC, while in RF, it was 9.0 % higher than FC. Under MR planting, the daily temperature fluctuations in RF were smaller than in FC, whereas in RS, they were larger than in FC. Through the adjustment of temperature and humidity, MR increased the activities of β-glucosidase (β-Glu) and cellulose disaccharide hydrolase (CBH) in the soil, thereby accelerating rice straw decomposition. Importantly, MR led to improved root growth, seedling quality, precipitation water use efficiency (WUEP), and yield of rapeseed during both the WY and DY seasons. Notably, root morphological traits were significantly altered under straw returning (RT) in MR, particularly with an 11.0 % increase in root surface area, which showed a significant correlation with the indoleacetic acid and jasmonic acid contents in the root system. Furthermore, RT increased antioxidant enzymes activity in rapeseed roots. The H2O2 and ∙OH contents in MR were lower than in FC, indicating that the roots of MR were capable of self-protection and reducing the accumulation of superoxide radicals and peroxides by adapting actively to the soil water environment under straw returning. The yield and WUEP of MR were higher by 11.9 % and 21.0 %, respectively, compared to FC. In conclusion, MR planting has the potential to enhance seedling quality and increase rapeseed yield when combined with rice straw returning. This finding provides technical support for realizing the full and strong seedling establishment and improving the cultivation of direct-seeded rapeseed in the YRB region.

Characterization of the skill of the CORDEX-Africa regional climate models to simulate regional climate setting in the East African Transboundary Omo Gibe River Basin, Ethiopia

Regional climate models (RCMs) that produce good outputs in one region or for specific variables may underperform for others. Thereby, assessing the performance of various model simulations and their corresponding mean ensemble is critical in identifying the most suitable models. In this regard, a study was conducted to evaluate the performance of ten RCMs against observations from multiple ground-based stations in the East African Transboundary Omo Gibe River Basin, Ethiopia, during the baseline period of 1986–2005. The study evaluated the models' ability to replicate various aspects of climatic variables and their corresponding statistical indicators. The results confirmed that RCMs have varying abilities to reproduce climatic conditions across the basin. The ensembles and RACMO22T (EC-EARTH) were better at replicating the average annual precipitation distribution. Meanwhile, the CCLM4-8-17 (MPI) together with the ensembles better captured the measured precipitation annually, despite the discrepancies in the actual magnitudes. All RCMs were able to simulate the seasonal precipitation patterns effectively, with RACMO22T (EC-EARTH), CCLM4-8-17 (CNRM), RCA4 (CNRM), CCLM4-8-17 (MPI), and REMO2009 (MPI) models captured superior, excluding the maximum value. Interannual and seasonal rainfall pattern variations were more significant than variations in air temperature. Additionally, a better correlation was observed between actual and simulated precipitation at multiple separate monitoring places. The RCA4 (MPI) and CCLM4-8-17 (MPI) demonstrated reasonable minimum and maximum temperatures. The RCA4 (MIROC5) model was more effective in reproducing extreme precipitation events. However, all RCMs and their ensembles tended to overestimate the return periods of these events. In general, the research highlights the importance of selecting reliable RCMs that better replicate observed climatic settings and employing the ensemble mean of top-performing models following systematic bias adjustment for a specific application.

Spatio-Temporal Evolution of Rainfall over the Period 1981–2020 and Management of Surface Water Resources in the Nakanbe–Wayen Watershed in Burkina Faso

Spatio-temporal analysis of rainfall trends in a watershed is an effective tool for sustainable water resources management, as it allows for an understanding of the impacts of these changes at the watershed scale. The objective of the present study is to analyze the impacts of climate change on the availability of surface water resources in the Nakanbe–Wayen watershed over the period from 1981 to 2020. The analysis was conducted on in situ rainfall data collected from 14 meteorological stations distributed throughout the watershed and completed with CHIRPS data. Ten precipitation indices, recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices), were calculated using the RClimDex package. The results show changes in the distribution of annual precipitation and an increasing trend in annual precipitation. At the same time, a trend towards an increase in the occurrence and intensity of extreme events was also observed over the last 4 decades. In light of these analyses, it should be emphasized that the increase in precipitation observed in the Nakanbe–Wayen watershed is induced by the increase in the occurrence and intensity of events, as a trend towards an increase in persistent drought periods (CDD) is observed. This indicates that the watershed is suffering from water scarcity. Water stress and water-related hazards have a major impact on communities and ecosystems. In these conditions of vulnerability, the development of risk-management strategies related to water resources is necessary, especially at the local scale. This should be formulated in light of observed and projected climate extremes in order to propose an appropriate and anticipated management strategy for climate risks related to water resources at the watershed scale.

Causes and period of occurrence of forest fires in Brazilian federal protected areas from 2006 to 2012

Forest fires, regardless of their causes, represent one of the greatest threats to biodiversity in Brazilian protected areas. Collecting data on the causes, periods, and sites with the highest occurrence of fires allows for the adoption of more effective prevention strategies. The aim of this study was to characterize forest fires in Brazilian federal protected areas from 2006 to 2012, thus contributing to improving the knowledge of the dynamics of fires in these areas. Data were obtained from Fire Occurrence Records (ROIs, in Portuguese) available in the National Fire Information System (SISFOGO, in Portuguese) database. The total number of records found was 2,259, of which 88.2% had reported causes. Among the records with a reported cause, 42.2% correspond to unknown causes, 26.7% to debris burning, and 18.5% to arson events, which shows that the majority of fires with a known cause are the result of accidental or intentional human action. Forest fires were more frequent from July to October, with a mean of 50.6 occurrences per year, influenced by the annual precipitation distribution. Minas Gerais, Rio de Janeiro and Ceará were the states with the highest number of records, with 19.8%, 15.5%, and 12.0%, respectively. Forest fires reported without any cause information or reported as unknown cause indicate, respectively, a poor use of the tool (ROI) or an unsatisfactory expertise in identifying the cause of the fire, resulting in an obstacle for planning actions to prevent and fight forest fires in protected areas.

ОЦІНКА ОДНОРІДНОСТІ РЯДІВ СПОСТЕРЕЖЕНЬ ЗА КІЛЬКІСТЮ АТМОСФЕРНИХ ОПАДІВ ТА РІВНЯМИ ВОДИ НА ВОДНИХ ОБ’ЄКТАХ ЗОНИ ВПЛИВУ ХМЕЛЬНИЦЬКОЇ АЕС

The energy strategy of Ukraine until 2030 envisages the completion and commissioning of power units 3 and 4 at the Khmelnytskyi NPP. An important factor in the correct, uninterrupted operation of the Khao NPP is the availability of appropriate water resources and water levels that can be restored with the help of precipitation, as well as flow regulation. During the research period from 2019 to 2023, the cooling pond of Khao NPP was not recharged by pumping water from the Horyn River. The research methodology is based on the application of the hydrological-genetic and statistical method. The homogeneity of the series of observations according to statistical parametric and non-parametric criteria was determined; integrated total curves of water levels were constructed; graphs of surfaces are constructed; the precipitation unevenness coefficient was calculated. The possibility and expediency of applying statistical criteria to assess the significance of the presence of trends, which were revealed based on the data of observations of water levels and precipitation for the Horyn River near the village, is substantiated. Yampil and in the Khao NPP cooling pond. It was established that in most cases, the heterogeneity of the observation series can be influenced by anthropogenic factors, such as the regulation of the reservoir, the operation of reclamation systems, agricultural fields, overgrowth of the banks of the pond, siltation and waterlogging, floodplain meadows, and others. In cases of insignificant annual distribution of precipitation in the Yampil River and in the Khao NPP cooling pond, the latter does not have a significant impact on the distribution of water levels in them.

Extreme Precipitation Strongly Impacts the Interaction of Skewness and Kurtosis of Annual Precipitation Distribution on the Qinghai–Tibetan Plateau

Characterizing extreme precipitation precisely is crucial for predicting vegetation response to drought or storms. However, current precipitation generators in vegetation models do not simulate the occurrence and amount of extreme precipitation well. This study examined the effects of extreme precipitation on the skewness, kurtosis, and skewness–kurtosis interaction of annual precipitation distribution. The examination was based on theoretical calculations and monitoring data from 78 meteorological stations on the Qinghai–Tibetan Plateau (QTP). The results showed that extreme precipitation generally increased the skewness and kurtosis of annual precipitation distribution. A higher mean annual precipitation amplified the effects of precipitation extremes on promoting skewness and kurtosis in normal distribution scenarios. In contrast, these effects tended to be saturated for scenarios of higher mean annual precipitation in probability-based distributions. A reduction of dry days in a year markedly intensified the interaction of the skewness and the kurtosis, while the skewness–kurtosis interaction weakened with decreased maximum daily precipitation in a year. Moreover, the effect of extreme precipitation on the skewness–kurtosis interaction was stronger in arid or low-altitude areas. This study illustrates the fact that considering the skewness and kurtosis of annual precipitation distributions will be very helpful for simulating extreme precipitation on the QTP in the future. This will allow us to better understand the impact of climate change on alpine plants.

Precipitation Over Southern Africa: Moisture Sources and Isotopic Composition

AbstractSouthern Africa, with its vast arid to semiarid areas, is considered vulnerable to precipitation changes and amplifying weather extremes. However, during the last 100 ka, huge lakes existed in the currently dry central Kalahari. It has been suggested that these lakes could have existed due to altered atmospheric circulation pattern, leading to an increase in precipitation or to changes in the annual precipitation distribution. Past climate changes are recorded in paleo‐archives, yet, for a proper interpretation of paleo‐records, for example, from sedimentological archives or fossils, it is essential to put them in a context with recent observations. This study’s objective is, therefore, to analyze spatially differing annual precipitation distributions at multiple locations in southern Africa with respect to their stable water isotope composition, moisture transport pathways, and sources. Five different precipitation distributions are identified by end‐member modeling and respective rainfall zones are inferred, which differ significantly in their isotopic compositions. By calculating backward trajectories, different moisture source regions are identified for the rainfall zones and linked to typical circulation patterns. Our results furthermore show the importance of the seasonality, the amount effect, and the traveled distance of the moisture for the general isotopic composition over the entire southern Africa. The identified pattern and relationships can be useful in the evaluation of isotope‐enabled climate models for the region and are potentially of major importance for the interpretation of stable water isotope composition in paleo‐records in future research.

Variation in Water Uptake Dynamics of Dominant Wood Plants of Pinus taiwanensis Hayata Communities Based on Stable Isotopes

Plant community formation is determined by plant competition, while the water uptake depth of vegetation is regarded as a critical factor in maintaining species coexistence under competition. However, the source variation of montane plant water uptake remains poorly understood, especially under the condition of climate change. We introduced stable hydrogen and oxygen isotopes to investigate the water uptake pattern of the trees and shrubs in a Pinus taiwanensis Hayata community in subtropical mountains. The results showed that the main sources of water uptake in plants varied with soil water content, due to variations in annual precipitation distribution. In July and September, under extremely wet conditions, the evergreen conifer species P. taiwanensis and the shrub Eurya muricata mainly absorbed water from the deep soil layer (40–80 cm, more than 70%). By contrast, the deciduous shrub Rhododendron dilatatum largely relied on upper soil water (0–40 cm, 75.4%) in July but the same deep water source in September. In August and the non-growing season (January), when soil moisture content was low, plants preferred surface layer soil water (0–20 cm, above 50%). In October, the soil water in the middle (20–40 cm) and deep layers (40–80 cm) were the main water source of the three plants. However, the plant water sources showed great difference between P. taiwanensis and shrubs in November: P. taiwanensis absorbed more water from the soil surface layers (89.5%), while R. dilatatum mainly took up surface soil water (54.2%) and E. muricata predominantly obtained water from surface soil water (49.6%) and the deep soil layer (39.3%). These findings suggest that the water uptake of dominant woody plants in a P. taiwanensis community has great plasticity, and its water uptake depth varies with soil water content. In addition, these co-existing species generally absorbed water from similar soil layers in the P. taiwanensis community and exhibited a hydrological niche overlap, indicating a very possible competition between species in future water-limited conditions caused by climate change.

Spatiotemporal Variations and Climatological Trends in Precipitation Indices in Shaanxi Province, China

Precipitation, as an important part of the hydrological cycle, is often related to flood and drought. In this study, we collected daily rainfall data from 21 rainfall stations in Shaanxi Province from 1961 to 2017, and calculated eight extreme climate indices. Annual and seasonal concentration indices (CI) were also calculated. The trends in the changes in precipitation were calculated using the M–K test and Sen’s slope. The results show that the precipitation correlation index and CI (concentration index) in Shaanxi Province are higher in the south and lower in the north. For the annual scale, the CI value ranges from 0.6369 to 0.6820, indicating that Shaanxi Province has a high precipitation concentration and an uneven distribution of annual precipitation. The eight extreme precipitation indices of most rainfall stations showed a downward trend during the study period, and more than half of the stations passed the 0.05 confidence interval test. Among them, the Z value of PRCPTOT (annual total precipitation in wet days) at Huashan station reached −6.5270. The lowest slope of PRCPTOT reached −14.3395. This shows that annual rainfall in Shaanxi Province has been decreasing in recent decades. These findings could be used to make decisions about water resources and drought risk management in Shaanxi Province, China.

INFLUENCE OF ATMOSPHERIC PRECIPITATIONS ON THE RUN OF THE PUTIL RIVER

Research of precipitation, water balance of river basins, and the impact of precipitation on river runoff remain relevant in the context of global and regional climate change. Nowadays, many scientific research all over the world are devoted to the research of the problem of river runoff change under the influence of climatic factors. This kind of research has been developing strongly in Ukraine in recent decades. In particular, they concern the rivers of the Ukrainian Carpathians. The basin of the river Putyla to the line of the village of Putyla has an area of 181 km2. It is located in the south-eastern part of the Carpathian and characterized by a significant influence of warm rains on the formation of water runoff. The average annual runoff is characterized by rather complex patterns of change both in time and space. There are periodic, cyclical and unidirectional changes that occur under the influence of a complex system of factors. Climate is a major factor of the water change. Thus, the research of the average runoff of the Putila River has different aspects.To determine the effect of precipitation on river runoff, the method of comparing difference-integral curves of annual runoff and precipitation, as well as water-balance methods are used. Long-term changes and intra-annual distribution of precipitation, in particular rainfall, according to the observations of the meteorological station Selyatyn were analyzed. We constructed a differential integrated curve of modular coefficients of the average annual precipitation in the Putil district. It clearly reflects the cyclical changes in precipitation. Long-term changes and intra-annual distribution of water runoff in the Putyla River also were analyzed. During the observation period, periods of long-term fluctuations of the average annual precipitation were revealed. The average annual rainfall is 842.9 mm. The annual course is stable, ie the greatest amount of precipitation falls in the summer, when there are intense thunderstorms and showers, the least – in winter. Based on the data of hydrological observations, the average long-term value of water consumption according to GP Putila is 2.47 m3/s. We calculated the coefficient of variability (variation). The coefficient of variation for average costs is 0.21 (21%), and for precipitation – 0.7 (7%). The connection between precipitation and runoff was established. We have built a comprehensive schedule of annual distribution of precipitation and costs of the Putyla River for 2010. You can see that in the spring due to snowmelt there is an influx of water and there is a spring flood. It is known that 2010 in Putilsky district was full of water. The reduction of water consumption in the Putyla River in the cold period of the year with a decrease in precipitation is also observed. Graph of the dependence of the runoff of the Putyla River on precipitation in the village of Selyatyn showed a fairly clear relationship between the variable values of runoff and precipitation (the coefficient of variation is 0,66). The feeding structure of the Putyla River is mixed. The main share is occupied by rain, less - snow and groundwater.
 Key words: climate change, precipitation, runoff, rivers, long-term changes in runoff, intra-annual distribution of precipitation and runoff, Putyla river.

Precipitation variability can bias estimates of ecological controls on ecosystem productivity response to precipitation change

AbstractAnnual vegetation aboveground net primary productivity (ANPP) exhibits a non‐linear dependence on annual precipitation. A common pattern of non‐linearity, called asymmetry, arises when productivity responses in wet years are larger than declines in dry years. To date, ANPP asymmetry has been attributed primarily to vegetation water stress, an internal ecosystem response to precipitation and soil water availability. However, when quantified via the asymmetry index (AI) estimated from productivity measurements, the asymmetry can be a sampling artefact that arises from a positively skewed annual precipitation distribution. In this paper, we aimed to separate the sampling effect (from external precipitation variability) from the non‐linear response of the system (the internal ecosystem dynamics). We constructed a probabilistic model that integrates the precipitation distribution with the precipitation‐productivity response curve (PPT‐ANPP curve), derived using empirical formulae and a process‐based soil water balance model. The model was used to derive the probability density function of AI and to attribute its shape to the PPT distribution and the PPT‐ANPP response curve. The models were compared to data from 47 grasslands. Results demonstrated that positively skewed precipitation produces a positive AI as a statistical artefact. The non‐linear ecosystem PPT‐ANPP dependence can further enhance or dampen this statistical artefact. In all sites, the precipitation skew highly affected the probability of correctly identifying asymmetry using AI. Observed negative asymmetry arises from a larger soil water holding capacity and positive asymmetry from plant water stress. More robust statistical indicators of non‐linear ecological responses to climate variability are needed to improve ecosystem forecasts.

Evaluation of the Ability of CMIP6 Global Climate Models to Simulate Precipitation in the Yellow River Basin, China

Choosing an appropriate GCM (Global Climate Model, GCM) is of great significance for the simulation of the hydrological cycle over a basin under future climate scenarios. In this study, the Rank Score Method (RS) with eight indicators were applied to comprehensively evaluate the suitability of 19 GCMs issued in the Sixth Global Atmosphere and Coupled Model Intercomparison Project (CMIP6) to the Yellow River Basin (YRB). The results indicated that: 1) The GCMs perform differently in simulating precipitation over the YRB with the top six GCMs ranking from MRI-ESM2-0, ACCESS-CM2, CNRM-CM6-1, CNRM-ESM2-1, FGOALS-f3-L, to MPI-ESM1-2-HR. 2) Most GCMs overestimated the precipitation, and poorly simulated the phase distribution of extremes mainly due to overstimulation of wet season span and precipitation amount in the season, although all GCMs could capture decadal feature of annual precipitation. Meanwhile, it is also found that most GCMs underestimated summer precipitation and overestimated spring precipitation. 3) The GCMs well simulated the spatial distribution of annual precipitation, with an overestimation in the source area, and an underestimation in the northern part of the middle reaches of YRB.

Studies of meteorological elements and climate change in the Uruçuí river basin/Brazil

The objective is to show the variability of meteorological elements in the hydrographic basin area of the hydrographic basin of the Uruçuí Preto River–PI/Brazil, aiming to contribute to sustainable development in the productive areas of agriculture, laser, and hydrology. The meteorological elements studied are air temperature and relative humidity and their fluctuations, thermal amplitude, wind (intensity and direction), total insolation, cloud cover, evaporation, evapotranspiration, and rainfall. The data were from the 1960-1990 series, acquired by the Superintendency of the Development of the Northeast and by the Technical Assistance and Rural Extension Company of Piauí. The maximum annual temperature is 32.1°C, its minimum 20.0°C, with an average annual temperature of 26.1°C. A climatic classification was used according to the KÖPPEN systems, where two climatic types are distinguished in the Uruçuí Preto/PI river basin, the Aw, tropical hot and humid, with rain in summer and dry in winter; Bsh, warm semi-arid, with summer rains and dry winter. The variation of the thermal amplitude is from 11.9 to 14.9ºC. The average relative humidity of the air was 47 to 79%; the average annual precipitation was 937.7 mm; it was observed that the annual march of relative humidity follows the annual distribution of precipitation because the precipitation was the feeding process from natural sources of water vapor and moisture. Total Sunstroke in the BHRUP area ranges from 2520 to 2750 hours. It is concluded that the maximum annual temperatures increased during the period, which can cause several socioeconomic problems, and human health.

Characters of Precipitation Change in Heilongjiang from 2000 to 2020

Analyzing the precipitation in Heilongjiang Province, the result shows that the zonal difference of precipitation in Heilongjiang province is significant and the annual distribution of precipitation in Heilongjiang Province is very uneven. Generally, the precipitation in the east of Heilongjiang is better than that in the west. Through M-K trend test, it is found that during the period of 2000--2020 the annual precipitation in Heilongjiang Province generally showed a rising trend. And the precipitation in Heilongjiang Province increased steadily after 2002, while the abrupt point when the rainfall began to increase significantly was 2015.

Impact of Climate Change on the Streamflow Modulated by Changes in Precipitation and Temperature in the North Latitude Watershed of Nepal

It is unambiguous that climate change alters the intensity and frequency of precipitation and temperature distribution at the global and local levels. The rate of change in temperature in the northern latitudes is higher than the worldwide average. The annual distribution of precipitation over the Himalayas in the northern latitudes shows substantial spatial and temporal heterogeneity. Precipitation and temperature are the major driving factors that impact the streamflow and water availability in the basin, illustrating the importance of research on the impact of climate change on streamflow by varying the precipitation and temperature in the Thuli Bheri River Basin (TBRB). Multiple climate models were used to project and evaluate the precipitation and temperature distribution changes in temporal and spatial domains. To analyze the potential impact of climate change on the streamflow in the basin, the Soil and Water Assessment Tool (SWAT) hydrological model was used. The climate projection was carried out in three future time windows. The result shows that the precipitation fluctuates between approximately +12% and +50%, the maximum temperature varies between −7% and +7%, and the minimum temperature rises from +0.7% to +5% in intermediate- and high-emission scenarios. In contrast, the streamflow in the basin varies from −40% to +85%. Thus, there is a significant trend in the temperature increase and precipitation reduction in the basin. Further, the relationship between precipitation and temperature with streamflow shows a substantial dependency between them. The variability in precipitation and streamflow is successfully represented by the water yield in the basin, which plays an important role in the sustainability of the water-related projects in the basin and downstream to it. This also helps quantify the amount of water available for hydropower generation, agricultural production, and the water ecosystem in the TBRB.

An evaluation model for landslide and debris flow prediction using multiple hydrometeorological variables

Landslide and debris flows are typically triggered by rainfall-related weather conditions, including short-duration storms and long-lasting rainfall. The critical precipitation of landslides and debris flow occurrence is different under various hydrometeorological conditions. In this study, the trigger sensitivities of different daily hydrological variables were assessed using 50 days-worth of recorded landslide and debris flows using the Soil and Water Assessment Tool model. The event days were divided into long-lasting rainfall trigger (LLR-trigger) event days and short-duration storm trigger (SDS-trigger) event days with six determinate criteria based on modeled wetness states. The landslide and debris flow prediction model was built using nine hydrometeorological variables, and the predictive performance was tested with simulated data from 2010 to 2012. The results suggest that, except for rainfall, historical hydrological variables and their development provide important information for triggering landslides and debris flows. The prediction model with an area under curve (AUC) value of 0.85 was able to capture most of the landslides and debris flows. The temporal distribution of the two triggering events predicted by the model was consistent with the annual precipitation distribution. In addition, the spatial variations of the specific trigger types could be attributed to the different land covers. Despite some uncertainty, this study provides an idea of improving the landslide and debris flow prediction model.

Comparison of spatial interpolation methods for estimating the precipitation distribution in Portugal

Precipitation has a strong and constant impact on different economic sectors, environment and social activities all over the world. An increasing interest for monitoring and estimating the precipitation characteristics can be claimed in the last decades. However, in some areas, the ground-based network is still sparse and the spatial data coverage insufficiently addresses the needs. In the last decades, different interpolation methods provide an efficient response for describing the spatial distribution of precipitation. In this study, we compare the performance of seven interpolation methods used for retrieving the mean annual precipitation over the mainland Portugal, as follows: local polynomial interpolation (LPI), global polynomial interpolation (GPI), radial basis function (RBF), inverse distance weighted (IDW), ordinary cokriging (OCK), universal cokriging (UCK) and empirical Bayesian kriging regression (EBKR). We generate the mean annual precipitation distribution using data from 128 rain gauge stations covering the period 1991 to 2000. The interpolation results were evaluated using cross-validation techniques and the performance of each method was evaluated using mean error (ME), mean absolute error (MAE), root mean square error (RMSE), Pearson’s correlation coefficient (R) and Taylor diagram. The results indicate that EBKR performs the best spatial distribution. In order to determine the accuracy of spatial distribution generated by the spatial interpolation methods, we calculate the prediction standard error (PSE). The PSE result of EBKR prediction over mainland Portugal increases from south to north.