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This paper presents a validation of outputs from some GCMs of the CMIP6 project when used to assess climate projection and hydrological flows at a catchment scale for the case study area of the Lombardy region (Northern Italy). The modeling chain consists of (i) a choice of climatic scenarios from 10 GCMs of the CMIP6, (ii) the application of a stochastic downscaling procedure to make projections usable at the local scale, and (iii) the use of a semi-distributed physically based hydrological model Poli-Hydro for the generation of hydrological scenarios. Data on observed precipitation and temperature were collected from automatic weather stations, and the hydrological budget of four target catchments within the study area was assessed using Poli-Hydro. An ex-post (back-casting) analysis was performed upon the control data series from the GCMs by comparing statistics of relevant climate variables and model-simulated discharges against observed counterparts during the historical period 2002–2014. Then, during 2015–2021, the goodness of projections was assessed using confidence intervals. Our results show that the accuracy of GCMs in representing regional climate is not always reflected in a credible evaluation of local hydrology. The validation of climate patterns provides somewhat poor results; thus, the interaction among climate and hydrology needs to be explored carefully to warrant the credibility of hydrological scenarios. Overall, the spatial and temporal consistency of GCM projections, as explored here climatically and hydrologically, provides a clue about their dependability for basin scale management. [ABSTRACT FROM AUTHOR]

This paper studies the Upper Tigris River (UTR) drainage basin in Turkey for climate change impacted runoff estimations. Statistical downscaling method (SDM) is used by taking into consideration spatial dependence function (SDF) for the scenario precipitation projections at a set of available meteorology stations. Temporal adjustment between the climate scenarios and precipitation record time series is achieved by the white Markov (WM) stochastic process. Although various climate research center scenario data are considered, herein, only the general circulation model (GCM) A2 scenario data are adapted from the Hadley Center, England. The precipitation and runoff results are presented in decadal groups starting from 2001 to 2050 as cumulative monthly precipitation (CMP) and cumulative monthly runoff (CMR) graphs. It is observed that after 2021, precipitation decreases at about 12.5% and after 2030, it is 26%. Runoff projections indicate that they may decrease at about 30% especial after 2040. [ABSTRACT FROM AUTHOR]

Characterizing the response of temperature variables to agricultural irrigation is expected to be an important challenge for understanding the full impact of water management on regional climate change. In this paper, the trend analysis and abrupt change test were applied to detect the global warming effect. Then, the quantitative irrigation-induced cooling effects on temperature variables between April and August from 1970 to 2010 in the Lhasa River basin were estimated using historical time series of gridded meteorological records and a map of the area equipped for irrigation. Trends in the maximum temperature (Tmax) were statistically positive, and a significant increasing trend for the minimum temperature (Tmin) was detected at the 0.01 and 0.05 confidence levels. No abrupt changing point of warming was detected in the time series for Tmax. The abrupt changes in Tmin in the irrigation concentration period took place in 1995, 5 years later than the corresponding change in April. Affected by global warming, the increase in temperature was the largest in July and August, when the irrigation-induced cooling effect was also the most significant. The irrigation-induced cooling effect for Tmax and Tmin in April–August (except for June) ranged from − 0.017 to − 0.009 °C/decade and from − 0.011 to − 0.001 °C/decade, respectively, and the cooling effect for diurnal temperature range (DTR) ranged from − 0.011 to 0 °C/decade. The cooling effect on temperature reached above 0.01 °C in July and August, but for the growing seasons, the effect was weak, only 0.001 °C. The Tmax and Tmin trends during the whole growing seasons decreased by both 0.002 °C/decade, respectively, with a 10% increase in irrigation land proportion. Even in July and August, the trends were expected to decrease by about 0.005 °C/decade with a 10% increase in irrigation land proportion. The irrigation-induced cooling effect could partially slow global warming. [ABSTRACT FROM AUTHOR]

It is necessary to evaluate the impacts of climate change and human activities on vegetation dynamics. The purpose of this study is to assess the linkage of vegetation cover and climate fluctuations and distinguish the contribution of climate fluctuations and human activities on vegetation and its vulnerability in Namak Lake basin, Iran. For this purpose, changes in the enhanced vegetation index (EVI) in association with standardized precipitation evapotranspiration index (SPEI) were analyzed. The roles of climate fluctuations and human activities on vegetation vulnerability were then assessed in various land use land cover (LULC) classes using the residual analysis and probability of vegetation vulnerability index (PVVI). The EVI and land surface temperature (LST) maps for the period 2001–2019 were obtained from MOD13A2 and MOD11A2 products of MODIS, respectively. The results indicated that vegetation cover was mainly dependent on short-term climatic changes and their correlation decreased with increasing time scale of SPEI. It reflected that short-term water availability was vital for vegetation growth. Also, the sparse vegetation cover was mainly more vulnerable to climate fluctuations. Residual analysis showed that the vegetation dynamics was intensively attributed to the climate fluctuations, so that climate fluctuations affected vegetation cover in 78.94% of the basin, while 15.58% was affected by human activities and 5.48% was affected by both factors. The value of PVVI in the regions affected by climatic change was the highest (55.99); in the regions affected by human activities, it was lower (50.40); and in the regions affected by both factors, it was between the other two numbers (50.94). Therefore, climate fluctuations and human activities were both driving factors affecting vegetation covers over time in Namak Lake basin. [ABSTRACT FROM AUTHOR]

As a consequence of global warming, extreme weather events have become much more common in many countries. Extreme weather events negatively impact on mortal social and environmental issues, and recognizing the dynamical aspects of extreme weather is absolutely essential for forecasting and mitigating the implications of extreme weather occurrences on people and the planet. This research looked at the variations in space and time of 11 extreme precipitation indices and 16 extreme temperature indices in the Liaohe River Basin within Jilin Province and their associations with normalized-difference vegetation index (NDVI) and atmospheric circulation indices were evaluated. The results showed that: (1) The extreme warmth index showed a growing pattern and the extreme coldness index showed a declining tendency. The average consecutive dry days and consecutive wet days (CWD) indices showed a slow decreasing trend, and all other extreme precipitation indices showed a slowly intensifying trend. (2) There was a favorable connection between the NDVI and the extreme climate index, and most of the NDVI showed a significant correlation with the extreme temperature index, which shows that the dominant factor causing changes in the NDVI is extreme temperature. (3) The Arctic Oscillation index has a significant effect on extreme low temperatures. The Pacific Decadal Oscillation (PDO) has a large influence on extremely high temperatures. The CWD index in the extreme precipitation index had significant negative and positive correlations with the Southern Oscillation index and the PDO index, respectively. The results of the study contribute to further understanding and forecasting of extreme weather events in the Liaohe River Basin of Jilin Province and provide insights for appropriate measures to reduce the social and environmental impacts associated with extreme weather events in the study area. [ABSTRACT FROM AUTHOR]

The present study intends to assess the climatic controls on the streamflow and its impacts on the changing form of hydrological extremes in the Jhelum basin. The study entails robust statistical analysis of the observed hydroclimatic data (1980–2016) using the standard procedures of trend and abrupt change point detection, flood frequency analysis (FFA), and streamflow drought index (SDI). The coupled impact of rising temperatures (0.024 °C/year) and diminishing precipitation (− 5.71 mm/year) is yielding substantial decreases in the streamflow of the Jhelum basin. The other manifestations of changing climatic regimes are the increasing trends in the spring season (March-May) streamflow and the concurrence of abrupt change points in the streamflow data with climatic variables. The climate change signals are well evident over the hydrological extremes, reflected in an enhanced occurrence of droughts through the latter half of the examined period. Moreover, the flood frequency estimates show that the magnitude of the peak discharges about different return periods has increased significantly during 1986–2016 compared to 1956–1985 estimates. The magnitude of 100-year recurrence interval flood has increased by 10.54–79.58% during 1986–2016. The current study calls for the inclusive restructuring of water management practices to offset the impacts of changing hydrological extremes in the basin. [ABSTRACT FROM AUTHOR]

Landuse and climate change are the two main dynamics significantly affecting watershed hydrology. Adequate knowledge about how these changes will alter the hydrologic regime provides valuable information for future water resources planning and management. The current study attempts to analyze the joint consequences of these dynamics on the future hydrological response of the Gorganroud watershed in northern Iran. For landuse, the integrated Markov Chain analysis and Multi-Layer Perceptron Neural Network (MC-MLPNN) algorithm were used to obtain landuse for 2030 and 2050. For climate, we developed future scenarios based on the downscaled data from MPI-ESM-MR for 2021–2040 and 2041–2060. Soil and Water Assessment Tool (SWAT) was used to simulate watershed hydrology. We found that (1) from 1986 to 2050, agriculture and rangeland are likely to expand by 18.6% and 10.7% of the total watershed area, respectively, at the expense of forest covers. (2) Temperature and precipitation are expected to increase by 1.3 °C and 2.5 °C and by 31.7% and 27.1% for Representative Concentration Pathway 8.5 (RCP8.5) during 2021–2040 and 2041–2060, respectively, compared to the baseline of 1976–1995. (3) We found that the integrated landuse and climate change will likely increase annual evapotranspiration during 2021–2040 and 2041–2060 by 113.9% and 11.4%, lateral flow by 14.6% and 7%, baseflow by 166.7% and 77.2%, surface runoff by 54.2% and 41%, water yield by 50.5% and 35.9%, and streamflow by 48.6% and 32.1% for RCP8.5 compared to the baseline of 1976–1995. [ABSTRACT FROM AUTHOR]

The most practical methods to predict climate change are global climate models (GCMs). This research set out to evaluate the ability of 19 GCMs from the Coupled Model Intercomparison Project 6 (CMIP6) to reproduce the historical precipitation, maximum, and minimum temperature (Pr, Tmx, and Tmn) of climate prediction center data for the Amu Darya river basin (ADRB), as well as to project the climate of the basin using the chosen GCMs. The Kling-Gupta efficiency (KGE) metric was used to assess the effectiveness of GCMs to simulate the annual geographic variability of Pr, Tmx, and Tmn. A multi-criteria decision-making approach (MCDMA) was used to integrate the KGE values to rank GCMs. The findings showed that AWI-CM-1–1-MR, CMCC-ESM2, INM-CM4-8, and MPI-ESM1-2-LR best replicate observed Pr, Tmx, and Tmn in ADRB. Projection of climate employing the selected GCMs indicated an increase in precipitation (9.9–12.4%), Tmx (1.3–4.9 °C), and Tmn (1.3–5.5 °C) in the basin for all the shared socioeconomic pathways (SSPs), particularly for the far future (2060–2099). A significant variation can be seen in Tmx and Tmn over the different climatic zone. However, the intercomparison of selected GCM projected revealed high uncertainty in the projected climate. The projection uncertainty is noticed highest for Tmx. The uncertainty is also noticed higher in the far future and higher SSPs compared to the near future and lower SSPs. [ABSTRACT FROM AUTHOR]

A large body of scientific research has demonstrated a changing climate, which affects river flow regimes and extreme flood frequencies and magnitudes. The magnitude and frequency of extreme events are of critical importance in the evaluation of river systems to inform flood risk reduction under current and future conditions. The global climate projections from the Coupled Model Intercomparison Project, Phase 5 (CMIP5) datasets were used by the Variable Infiltration Capacity (VIC) land surface model to produce a runoff dataset, implementing a Bias-Correction Spatial Disaggregation (BCSD) approach. The resulting runoff was then used as input to the Routing Application for Parallel computatIon of Discharge (RAPID) river routing model to simulate daily flows within all 1.2 million Mississippi River Basin river reaches for years 1950 through 2099. This research effort analyzed the performance of the models for the historical time period, comparing with the observations at 64 gage locations for 16 different climate models. A recurrence interval analysis was performed to determine the 2-, 5-, 10-, 50-, 100-, 500-, and 1000-year events within both the historical and projected time periods, highlighting the relative changes predicted into the future. Anticipated seasonal changes are demonstrated by comparing monthly average streamflows for three different time periods (1951–2005, 2006–2049, and 2050–2099). Results indicate that the hydrologic conditions of the Lower Mississippi River are not stationary. Based on all 16 models considered in this study, the median of the model projections shows an 8% increase in the 100-year return period discharge at Vicksburg, Mississippi, into the future time period, although the full range of 16 models varies widely from − 11 to + 85% change in the 100-year discharge in the future. [ABSTRACT FROM AUTHOR]

The influence of climate change on the catchment-scale hydrologic processes can have a profound impact on river flow and the availability of fresh water. Here, we develop an integrated modeling framework to assess the near- and long-term hydrological response to climate change in a mountain river basin. The framework samples climate model outputs under different representative concentration pathways to force the calibrated hydrologic model and generate daily streamflow projections. We implement a framework in the Modi River basin, with an elevation ranging from 750 m to over 8000 m above sea level. Under the highest warming scenario, the mean annual precipitation and temperature are projected to vary to be as high as 4531 mm and 25.7 °C, respectively. The study results show that the future streamflow of the Modi River basin will increase during the latter time windows, i.e., far future (2075–2099) > > mid future (2050–2074) > > near future (2025–2049). Exploring how climate change can alter different hydrological processes can help improve the fundamental understanding of water balance and hydrologic controls, which are critical in ensuring the functionality of the natural ecosystems. [ABSTRACT FROM AUTHOR]

Hydrological drought is a highly complex and extreme natural disaster, which has increased in deficit, areal extent, and frequency with the penetration of climate change impact. For better anticipating hydrological droughts, it is crucial to evaluate hydrological drought and its teleconnections with large-scale climate indices (LSCI) effectively. This study estimated the dynamics and patterns of hydrological drought in the near-real river networks by virtue of the standardized runoff index (SRI) based on VIC and large-scale routing model in the Xijiang River basin, and revealed their teleconnections with the climate indices. Results show that model simulation can reasonably reveal the hydrological drought evolutions in near-real river networks and effectively expose the drought downward spread along main channels. The drought spread distances in Hongshuihe and Yujiang Rivers are farther under the comprehensive influence of climate, topography, and watershed shape. Hydrological drought evolutions in the upper reaches are mainly manifested as three patterns, including S12 (simultaneous significant changes in drought intensity, concentration degree, and frequency), S7(simultaneous significant changes in drought intensity and frequency), and S1(single significant change in drought intensity). These drought dynamic patterns are majority affected by climate variation patterns M1 (warm and cold AMO), M3 (cold PDO), and M7 (warm AMO/AO). For decision-makers, this work is beneficial for understanding and anticipating hydrological droughts in the river networks, and further selecting management strategies for water resources. Highlights: The quantitative results of model simulation are reliable for drought evaluation. Drought concentration period delays and drought risk increases significantly. Dynamic evolutions of drought mainly manifest as three combinations patterns. Upstream drought is mainly affected by AMO, PDO, and AMO/AO. [ABSTRACT FROM AUTHOR]

In this study, air temperature and precipitation seasonality and their correlation with large-scale atmospheric circulations over the Sava River Basin (SRB), i.e., over the areas of Slovenia, Croatia, and Serbia, are analyzed. We used daily air temperature and precipitation measurements from 12 meteorological stations for the period from 1981 to 2010. In addition, mean (Ta), maximum (Tmax), and minimum (Tmin) daily temperatures and daily precipitation (P) were included in the analysis. Temperature values were correlated with atmospheric circulation patterns (ACPs), i.e., daily indices Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Mediterranean Oscillation (MO) for the same study period. The daily air temperature and precipitation data were obtained from European Climate Assessment & Dataset (ECA&D). The results generally show increasing trends in air temperatures, mainly during the spring and summer seasons, but also non-significant trends for precipitation. Moreover, the correlation results show no or weak influence of ACPs on seasonal air temperatures and precipitation, but the dominant effects differ by ACP type as well as at different seasonal levels. Among the selected ACPs, MO proved to be the most significant for the Sava River Basin. [ABSTRACT FROM AUTHOR]

Climate change is adversely affecting the development, management, and planning of surface and groundwater resources. The meteorological drought becomes a severe natural problem, and it can occur in any climatic region of the world. Thus, monitoring and minimizing drought is crucial for analyzing and predicting drought impacts. The meteorological drought is considered basin or region-specific since atmospheric conditions are highly variable from region to region. However, agricultural drought links the various characteristics of hydrological or meteorological drought to agricultural impacts focusing on groundwater deficit, soil moisture deficit, etc. A single drought index cannot assess each aspect of the meteorological drought. In this study, we considered seven drought indices such as the Standardized Precipitation Index (SPI), China Z Index (CZI), Modified China Z Index (MCZI), Percent Normal Drought Index (PNI), Deciles Index (DI), Rainfall Anomaly Index (RAI), and Z-score Index (ZSI). The drought was analyzed for 3, 6, 9, and 12 months' time step, and drought classification and threshold values were estimated. SPI showed maximum correlation values (0.389, 0.412, 0.560, and 0.996) for 3, 6, 9, and 12 month time steps compared to the other drought indices. The value of correlation is increased with the increase in time step for all drought indices; therefore, the accuracy of drought assessment also increases with an increase in time step. The Mann–Kendall's trend test was analyzed at a 5% significance level for drought assessments. The drought magnitude and the severity of the Betwa River basin were estimated based on the meteorological data (Rainfall) from 1970 to 2014. [ABSTRACT FROM AUTHOR]

Climate change and its impacts at global warming of 1.5 °C and 2 °C are major concerns of the international community. Based on the multi-model dynamical downscaling outputs, by using the quantile–quantile (Q-Q) adjustment method to correct the biases for the future periods, projections are made for the variation trend of the extreme precipitation events over the middle and upper Yangtze River in the context of global warming of 1.5 °C and 2 °C. The results show that the Q-Q adjustment method significantly reduces the bias of simulated extreme precipitation. In the dynamical downscaling simulation over the middle and upper Yangtze River, the bias of the number of rainy days for daily precipitation exceeding 25 mm (R25) is reduced from 6 to 1d after correction, and the 95th percentile of precipitation (pq95) is reduced from 40 to 10% over the whole region. At 1.5 °C and 2 °C warming thresholds, precipitation will be more extreme, with increasing frequency and much greater intensity. Under the RCP4.5 scenario, the precipitation intensity (SDII), extreme precipitation contribution rate (pfl95), R25, and pq95 increase more at 2 °C than at 1.5 °C warming level, but the maximum consecutive 1-day and 5-day precipitation (R1d, R5d) increase slightly less. Under the RCP8.5 scenario, SDII, pq95, R1d, and R5d increase more at 2 °C than at 1.5 °C warming target, but pfl95 and R25 increase slightly less. From the perspective of spatial distribution, the future changes of each extreme precipitation indices show significant regional differences. All show a significant increasing trend in the upper Jialing River, the Wu River Basin, and the southern Sichuan Basin, but decreases trend in pq95, pfl95, R1d, and, R5d over the Northern Sichuan Basin. [ABSTRACT FROM AUTHOR]

It is a known fact that the size, frequency, and spatial variability of hydrometeorological variables will irregularly increase under the impact of climate change. Among the hydrometeorological variables, rainfall is one of the most important. Trend analysis is one of the most effective methods of observing the effects of climate change on rainfall. Recently, new graphical methods have been proposed as an alternative to classical trend analysis methods. Innovative Polygon Trend Analysis (IPTA), which evolved from Innovative Trend Analysis (ITA), is currently one of the proposed methods and it does not contain any assumptions. The aim of this study is to compare IPTA, ITA with the Significance Test and Mann-Kendall (MK) methods. To achieve this, the monthly total rainfall trends of 15 stations in the Vu Gia-Thu Bon River Basin (VGTBRB) of Vietnam have been examined for the period 1979–2016. The analyses show that rainfall tends to increase (decrease) in March (June) at nearly all stations. IPTA and ITA with the Significance Test are more sensitive than MK in determining the trends. While trends were detected in approximately 90% of all months in IPTA and ITA with the Significance Test, this rate was only 23% in the MK test. Although the arithmetic mean graphs in the 1-year hydrometeorological cycle are considerably regular at almost all stations, their standard deviations are relatively irregular. The most critical month for trend transitions between consecutive months for all the stations is October, which has an average trend slope of −1.35 and a trend slope ranging from −3.98 to −0.21, which shows a decreasing trend. [ABSTRACT FROM AUTHOR]

Objective evaluation of the relationships among different types of droughts remains a challenging task due to the combined impacts of climate change and land surface modification caused by human activities. Based on the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) at the 3- and 6-month timescales, this study presents a systematic analysis of the relationships between the severity (S) and duration (D) of meteorological (MD) and hydrological droughts (HD) in the three catchments of the upper Huai River Basin in China. The relation between SPI and SRI is explored by the maximal information coefficient and the mutual entropy. The spatial propagation mechanism of MD is identified by the centroid trajectory, and the response of HD to MD is quantified by the model averaging method. The results indicate a drying (wetting) trend in the upstream (downstream) area, while the centroid trajectory of MD is found in the midstream area, but not associated with the large (or small) S and D simultaneously. There is a strong correlation (determination coefficient > 0.55) between SPI and SRI in all three subareas, particularly at the 6-month timescale. The increasing influences of human activities (e.g., regulation of water conservancy facilities) from upstream to downstream lead to a weaker correlation between SPI and SRI as well as a decreasing threshold of D for MD to trigger HD in downstream. By contrast, the drier climatic conditions are the main reason for the increasing threshold of S for MD to trigger HD from upstream to downstream. [ABSTRACT FROM AUTHOR]

This study aims to propose a framework for assessing climate change in Mediterranean data-sparse contexts. For that purpose, the 309-km2 Lebanese Nahr Ibrahim watershed, extending over 3% of Lebanon's surface, was chosen as a representative of the targeted settings. Generally, holistic climate change assessments encompass both climate trend analysis and future forecasting. According to the World Meteorological Organization, a continuous, homogenous, and uninterrupted climatic record for at least 30 years is needed to fulfill these tasks. Often, some Mediterranean watersheds lack such data and are hence characterized by climatic data scarcity. Such is the case of Lebanon where 30 years of wars have considerably disrupted the country's climatic record. In an effort to overcome this state of data scarcity, remote sensing–derived drought indicators were used to determine the climate's evolution during the last 28 years. For that purpose, several remote sensing indices were extracted from LANDSAT imageries for the period 1990–2018 at a 3-year interval, and were coupled to meteorological indicators. Forecasting was then performed using autoregressive integrated moving average (ARIMA) models. Meteorological indices showed increased variability of precipitations and aridity periods, while remote sensing indicators collectively revealed slight shifts towards increasing droughts. Projections using ARIMA models forecasted increases of 0.9 °C, 0.7 °C, and 0.8 °C for average, maximal, minimal temperatures, and an average 6 mm decrease of precipitations at the 95% confidence level for the year 2030. The presented approach can serve as a tool for proactive climate change mitigation or adaptation plans. [ABSTRACT FROM AUTHOR]

Drought has become one of the most serious meteorological disasters for agricultural production in many areas around the world, and the situation could be worse under the impact of climate change. To facilitate better adaptation planning, this study proposed a drought assessment framework integrating downscaling method, drought index, copula technique, and bivariate frequency analysis, and applied it to investigate the change of the drought characteristics and drought risks from the past to the future in Huang-Huai-Hai River basin (HRB), North China. Drought was firstly defined by standardized precipitation evapotranspiration index (SPEI) based on 1497 observed grid data from 1979 to 2004. Then, we constructed the joint distribution of drought duration and severity based on copulas to detect and quantify the drought risks. To address the effect of climate change, similar calculation process was applied to the future climate data, which was downscaled using delta change method from representative concentration pathway (RCP 8.5) of 12 general circulation models (GCMs). The study results suggested that, under climate change condition, most irrigation districts over HRB would generally experience lower frequency of drought events but with extended duration; some districts would have more serious drought, but majority would experience similar or even lower level of severity. In light of the mean joint occurrence probability, the irrigation district at the south part of Huai River basin would likely experience the highest increase of drought risks in near future (by 0.86%) and distant future (by 0.76%), while most of other districts over HRB would face low risk of serious drought risks. The obtained results offer useful information to agricultural managers or water resources authorities who are interested in the development of effective long-term adaptation strategies for drought management. [ABSTRACT FROM AUTHOR]

The past few decades have produced a wealth of research investigating the extent and severity of global climate change. Patterns in climate variability and change have been studied at global, continental and regional scales. Trends observed at these larger spatial scales are expected to be observable at smaller scales, although research in this regard has been limited in South Africa. This study presents an investigation into the microclimatic trends of a key catchment in the KwaZulu-Natal province, South Africa, with particular focus on water resources. Long-term (1980–2017) historical daily meteorological data were analysed using the RClimDex software package as well as other multi-temporal regression and time series analyses. Results indicate an overall warming of the study sites between 1 and 4 °C century−1. Atmospheric water vapour pressure was found to be increasing significantly at three of the sites. Total annual rainfall, an important variable for water resources of the catchment, did not display significant change in the catchment but high levels of inter-annual variability were observed. The results of the study indicate that the catchment microclimate has changed, and is changing, but at different rates from global and continental estimates. The study emphasises the importance of catchment scale analyses using ground-based historical meteorological data. [ABSTRACT FROM AUTHOR]

Low flow is very sensitive to climate change and human intervention, especially in arid regions. In this study, changes of the 7-day low flow along the most important rivers of Iran's Namak Lake Basin were investigated using nonparametric (Mann-Kendall and modified-Mann-Kendall) tests. A significant diminishing trend was observed in 72.2% of stations during the period of 1970–2012. The northern part of the basin lacked a significant trend, while in other parts of the basin, the descending trend was distributed uniformly. On the other hand, the changes of the annual rainfall during this period showed no clear trend (a significant trend in 36% and non-significant trend in 64% of stations), and the identified pattern of its changes was complicated on the basin scale and during the year. On a monthly scale, a significant decreasing trend was observed in March as one of the most productive months of the year in 49% of the stations. In addition, rainfall reduction was significant (over 35%) over the past 15 years in more than 71% of the stations. Also, changes in the proportion of seasonal rainfall and rainfall regime were considerable. The share of winter and spring rainfall showed a diminishing trend in 90% and 82% of stations, respectively. Also, rainfall regime based on precipitation concentration index (PCI) revealed a tendency to disorder (in 53% of stations). The annual temperature and temperature of October and February indicated a strong ascending trend in 92%, 71%, and 64% of stations, respectively, which can be effective during snow melting in basins with snow-rainy regimes and increasing evapotranspiration. Groundwater level changes also showed that, in the studied plains, the average water table drawdown was between 0.31 and 1.33 m/year. Therefore, the observed trend of low flow rates in this basin reflects the impact of climate change, where both direct and indirect human interference has led to the exacerbation of this situation. [ABSTRACT FROM AUTHOR]

Drought projection is of critical significance for designing long-term drought adaptation strategies to cope with changing climate. This study presents an application of multi-class models for characterizing future droughts in the Yellow River basin (YRB). Using meteorological observations and simulations of three CMIP5 climatic models as input into VIC hydrologic model, the standardized Palmer drought index-based joint drought index (SPDI-JDI) is calculated to investigate spatiotemporal patterns and possible changes of future drought in the YRB, through an approach of bivariate modeling and analysis. It is concluded that moderate drought will be alleviated with decreased duration and severity, but extreme drought risk is likely to increase for future climate scenarios (2021–2050) relative to baseline period (1961–2000). From the perspective of bivariate analyses, the concurrence probability of drought events with extreme duration and severity might rise in the future, while increasing variability and heterogeneity of duration, severity and bivariate joint/concurrent return period would also increase the stochastic occurrence of extreme drought over time and space. These findings can provide insights into projection of climate change impacts on drought trends for the next 30 years, and help to preparations for strict control of socio-economic water consumption as well as eco-environmental protection and restoration in the YRB. [ABSTRACT FROM AUTHOR]

Studying the shifts of vegetation phenology and the response of vegetation phenology to climate change helps to understand the dynamics of future ecosystems. However, since previous studies mostly focused on temperate ecosystems, much less is known about the biogeographic phenological shifts in sub-tropical regions, which have abundant biodiversity. The Yangtze River Basin (YRB) is located in the subtropical region of China and has abundant natural resources, a large population, and rapid economic development. Studying the variation characteristics of phenology and its responses to recent climate changes in YRB are important for understanding the impact of regional climate on subtropical ecosystems. In this study, we extracted the phenological parameters using Global Inventory Modeling and Mapping Studies (GIMMS) data to investigate the spatial and temporal variations of vegetation phenology across YRB during 1982–2015 and to examine how vegetation phenology responds to climate within different ecological zones. The results revealed that the start of growing season (SOS) was significantly advanced by 0.2 days/year (p < 0.01). However, there has been no significant trend in the end of growing season (EOS) throughout the whole study area for the past 34 years. The spatial pattern of the phenology metrics showed a high spatial heterogeneity: the SOS in the central YRB was earlier than that in other regions; the EOS in the southeast YRB was later than that in any other regions. Meanwhile, the SOS had a higher correlation with temperature than with precipitation. In particular, the spring temperature had a strong impact on the SOS and the effects of winter temperatures cannot be ignored. Although there were no significant correlations between the EOS and precipitation/temperature, it is interesting to note that when examining the interactions between phonological parameters, the EOS was positively correlated with the SOS. Furthermore, the pre-season temperature had a lag effect on the SOS, but no significant lag effect was observed for the EOS in YRB. In all, the present study can enhance our understanding of phenology dynamics and its relationship with climate in YRB and provide a useful reference to put forward a corresponding ecological protection policy. [ABSTRACT FROM AUTHOR]

Reliable drought projections are crucial for the effective managements of future drought risk. Most of the existing drought projections over Southern Africa are based on precipitation alone, neglecting the influence of potential evapotranspiration (PET). The present study shows that inclusion of PET may alter the magnitude and robustness of the drought projections. The study used two drought indices to project potential impacts of global warming on Southern African droughts, focusing on four major river basins. One of the drought indices (SPEI: Standardized Precipitation Evapotranspiration Index) is obtained from climate water balance (i.e. precipitation minus potential evapotranspiration) while the other (SPI: Standardized Precipitation Index) is calculated from precipitation alone. For the projections, we analyzed multi-model regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the pre-industrial level and used the self-organizing maps to classify the drought projections into groups based on their similarities. Our results show that the CORDEX simulations give a realistic representation of all the necessary climate variables for quantifying droughts over Southern Africa. The simulations project a robust increase in SPEI drought intensity and frequency over Southern Africa and indicate that the magnitude of the projection increases with increasing GWLs, especially over the various river basins. In contrast, they project a non-significant change in SPI droughts at all the GWLs. The majority of the simulations clearly distinguish between the projected SPEI and SPI drought patterns, and the distinction becomes clearer with increasing GWLs. Hence, using precipitation alone for drought projection over Southern Africa may underestimate the magnitude and robustness of the projections. This study has application in mitigating climate change impacts on drought risk over Southern African river basins in the future. [ABSTRACT FROM AUTHOR]

The Yarlung Zangbo River Basin (YZRB) is the longest plateau river in China and is one of the highest rivers in the world. In the context of climate change, the ecological environment of the YZRB has become increasingly fragile because of its unique location and environment. In this study, four machine learning techniques, multiple linear regression (MLR), artificial neural network (ANN), support vector machine (SVM), and random forest (RF) model, were applied to downscale the daily extreme temperatures (maximum and minimum) at 20 meteorological stations located in and around the YZRB. The performance of these methods was evaluated using four comparison criteria. The best identified model was adopted to simulate future temperatures under two extreme scenarios (the lowest rate emission scenario (RCP2.6) and the highest rate emission scenario (RCP8.5)) from 2016 to 2050 using outputs from the MPI-ESM-LR climate model. The four comparison criteria showed that the RF model yielded the highest efficiency; therefore, this model was chosen to simulate the future temperatures. The results indicate that the extreme temperatures at the 20 stations increase continually under both extreme scenarios. The increases in the maximum temperature at the 20 stations under the two extreme emission scenarios are 0.46 and 0.83 °C, and the increases in the minimum temperature at the 20 stations are 0.30 and 0.68 °C for the period 2016–2050, respectively. [ABSTRACT FROM AUTHOR]

The variability and uncertainty of water resources associated with climate change are critical issues in arid and semi-arid regions. In this study, we used the soil and water assessment tool (SWAT) to evaluate the impact of climate change on the spatial and temporal variability of water resources in the Bazoft watershed, Iran. The analysis was based on changes of blue water flow, green water flow, and green water storage for a future period (2010–2099) compared to a historical period (1992–2008). The r-factor, p-factor, R2, and Nash–Sutcliff coefficients for discharge were 1.02, 0.89, 0.80, and 0.80 for the calibration period and 1.03, 0.76, 0.57, and 0.59 for the validation period, respectively. General circulation models (GCMs) under 18 emission scenarios from the IPCC's Fourth (AR4) and Fifth (AR5) Assessment Reports were fed into the SWAT model. At the sub-basin level, blue water tended to decrease, while green water flow tended to increase in the future scenario, and green water storage was predicted to continue its historical trend into the future. At the monthly time scale, the 95% prediction uncertainty bands (95PPUs) of blue and green water flows varied widely in the watershed. A large number (18) of climate change scenarios fell within the estimated uncertainty band of the historical period. The large differences among scenarios indicated high levels of uncertainty in the watershed. Our results reveal that the spatial patterns of water resource components and their uncertainties in the context of climate change are notably different between IPCC AR4 and AR5 in the Bazoft watershed. This study provides a strong basis for water supply-demand analyses, and the general analytical framework can be applied to other study areas with similar challenges. [ABSTRACT FROM AUTHOR]

This study intended to estimate the spatial and temporal variation of current and projected water demand and water availability under climate change scenarios in Weyib River basin, Bale mountainous area of Southeastern Ethiopia. Future downscaled climate variables from three Earth System Models under the three RCP emission scenarios were inputted into ArcSWAT hydrological model to simulate different components of water resources of a basin whereas current and projected human and livestock population of the basin is considered to estimate the total annual water demand for various purposes. Results revealed that the current total annual water demand of the basin is found to be about 289 Mm3, and this has to increase by 83.47% after 15 years, 200.67% after 45 years, and 328.78% after 75 years by the 2020s, 2050s, and 2080s, respectively, from base period water demand mainly due to very rapid increasing population (40.81, 130.80, and 229.12% by the 2020s, 2050s, and 2080s, respectively) and climatic variability. The future average annual total water availability in the basin is observed to be increased by ranging from 15.04 to 21.61, 20.08 to 23.34, and 16.21 to 39.53% by the 2020s, 2050s, and 2080s time slice, respectively, from base period available water resources (2333.39 Mm3). The current water availability per capita per year of the basin is about 3112.23 m3 and tends to decline ranging from 11.78 to 17.49, 46.02 to 47.45, and 57.18 to 64.34% by the 2020s, 2050s, and 2080s, respectively, from base period per capita per year water availability. This indicated that there might be possibility to fall the basin under water stress condition in the long term. [ABSTRACT FROM AUTHOR]

In this study, maximum dry spell length and number of dry spell periods of rainy seasons in the upper Baro-Akobo River basin which is a part of the Nile basin, Western Ethiopia, were investigated to analyse the drought trend. Daily rainfall records of the period 1972-2000 from eight rain gauge stations were used in the analysis, and Mann-Kendall test was used to test trends for significance. Furthermore, the beginning and end of the trend development in the dry spell were also tested using the sequential version of Mann-Kendall test. Results have shown that there is neither clear monotonic trend found in dry spell for the basin nor significant fluctuation in the onset, cession and duration of rainfall in the Baro-Akobo river basin. This sufficiently explains why rain-fed agriculture has suffered little in the western part of Ethiopia. The predictable nature of dry spell pattern may have allowed farmers to adjust to rainfall variability in the basin. Unlike many parts of Ethiopia, the Baro-Akobo basin climate variability is not a limiting factor for rain-fed agriculture productivity which may contribute significantly to national food security. [ABSTRACT FROM AUTHOR]

Climate change has become an important issue for scientific community, for its numerous impacts, especially on agriculture and environment. To shed light on this phenomenon, long data-sets of meteorological data as well as temperature and rainfall extreme events are needed, since they are important climate variability indicators. In a small semi-agricultural catchment of the Italian Apennines, drained by the Centonara Stream, weather data have been monitored for 30 years (1986-2015). Here, their trend was identified with Mann-Kendall test, and the temperature and precipitation extremes were characterized by means of specific indices. Data were analyzed at event, daily, seasonal, and annual bases. In addition, to understand implications of rainfall patterns on catchment hydrological response, a total of 388 rainfall-streamflow events (recorded during 1994-2009) were analyzed. Results showed a significant increase of temperature (minimum (Tn), mean (Tm), and maximum (Tx)), both at annual and seasonal base, except for Winter, with an annual mean increase of 0.08, 0.09, and 0.13 °C year for Tn, Tm, and Tx, respectively. Annual rainfall data showed a positive trend for the number of wet days, but not in the quantity. In Winter, the rainfall amount and the number of wet days increased. The annual number of rainfall extreme events ( P > 20.2 mm and D > 18.3 h) significantly increased, especially in spring and autumn. The rainfall-streamflow relationship suggested that the flow response of the Centonara Stream depends mainly on the rainfall amount. So, since the number of extreme events ( P > 20.2 mm) is increasing in spring and autumn, an increase of events with high streamflow in these seasons may occur. [ABSTRACT FROM AUTHOR]

Prior to hydrological assessment of climate change at catchment scale, an applied methodology is necessary to evaluate the performance of climate models available for a given catchment. This study presents a grid-based performance evaluation approach as well as an intercomparison framework to evaluate the uncertainty of climate models for rainfall reproduction. For this purpose, we used outputs of two general circulation models (GCMs), namely ECHAM5 and CCSM3, downscaled by a regional climate model (RCM), namely RegCM3, over ten small to mid-size catchments in Rize Province, Turkey. To this end, five rainfall-borne climatic statistics are computed from the outputs of ECHAM5-RegCM3 and CCSM3-RegCM3 combinations in order to compare with those of observations in the province for the reference period 1961-1990. Performance of each combination is tested by means of scatter diagram, bias, mean absolute bias, root mean squared error, and model performance index (MPI) measures. Our results indicated that ECHAM5-RegCM3 overestimates the total monthly rainfall observations whereas CCSM3-RegCM3 tends to underestimate. In terms of maximum monthly and annual maximum rainfall reproduction, ECHAM5-RegCM3 shows higher performance than CCSM3-RegCM3, particularly in the coastland areas. In contrast, CCSM3-RegCM3 outperforms ECHAM5-RegCM3 in reproducing the number of rainy days, especially in the inland areas. The results also revealed that if a GCM-RCM combination performs well for a portion (statistic) of a catchment, it is not necessarily appropriate for the other portions (statistics). Moreover, the MPI measure demonstrated the superiority of ECHAM5-RegCM3 to CCSM3-RegCM3 up to 33 % excelling for annual rainfall reproduction in Rize Province. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of anthropogenic climate change in the hydroclimatology of Senegal with a focus over the lake of Guiers basin for the middle (2041-2060) and late twenty-first century (2080-2099). To this end, high-resolution multimodel ensemble based on regional climate model experiments considering two Representative Concentration Pathways (RCP4.5 and RCP8.5) is used. The results indicate that an elevated warming, leading to substantial increase of atmospheric water demand, is projected over the whole of Senegal. In the Lake basin, these increases in potential evapotranspiration (PE) range between 10 and 25 % in the near future and for RCP4.5 while for the far future and RCP8.5, they exceed 50 %. In addition, mean precipitation unveils contrasting changes with wetter (10 to 25 % more) conditions by the middle of the century and drier conditions (more than 50 %) during the late twenty-first century. Such changes cause more/less evapotranspiration and soil moisture respectively during the two future periods. Furthermore, surface runoff shows a tendency to increase in most areas amid few locations including the Lake basin with substantial reduction. Finally, it is found that while semi-arid climates develop in the RCP4.5 scenario, generalized arid conditions prevail over the whole Senegal for RCP8.5. It is thus evident that these future climate conditions substantially threaten freshwater availability for the country and irrigated cropping over the Lake basin. Therefore, strong governmental politics are needed to help design response options to cope with the challenges posed by the projected climate change for the country. [ABSTRACT FROM AUTHOR]

Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992-2005, four evaluation criteria including Nash-Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination ( R ) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006-2037; mid-century, 2037-2070; and late-century, 2070-2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann-Kendall non-parametric test (MK) was also employed. The results of Mann-Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56-3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced. [ABSTRACT FROM AUTHOR]

The study aimed to evaluate the influence of the rainfall and aridity index variability on the process of land degradation (desertification) in order to establish the current degree of increase or decrease in dryness in the watershed of the upper Paraíba River. It included all or part of 18 municipalities, distributed in the western and eastern Cariri regions of Paraíba state. The monthly average values of reference evapotranspiration according to Penman-Monteith method were applied in the annual hydrological balance for obtaining the annual time series of the aridity index for the period from 1950 to 2013. The Mann-Kendall test (MK) was used for trend identification in the annual time series of rainfall and aridity index, at a significance level of α = 0.05. The slope of the trends was obtained by Sen's method, and the values of rainfall, aridity index, and statistics MK were spatially kriging, to generate thematic maps. The results indicate an increase in rainfall and reduced dryness in the watershed of the upper Paraíba River, conditions that do not contribute to trigger the process of land degradation (desertification), indicating that the cause of this environmental problem is not climatic. Thus, it can be suggested that the observed manifestations of land degradation (desertification) derive much of human than climatic actions. However, there is a trend of increasing dryness and reducing rainfall in the central portion of the watershed, with stronger core in the location of Camalaú. The spatial distribution of rainfall and aridity index shows that minimum values of rainfall coincide with maximum values of the aridity index. Higher values of rainfall were observed in the northwestern portion of the watershed, while the northeast and southeast portions had the lower rainfall values, with the strongest core in the locality of Cabaceiras. The eastern sector of the watershed has high dryness, unlike the western sector, rainier, with minimum values of dryness. In the western portion of the watershed, the aridity index was in the range considered semiarid, with moderate susceptibility to land degradation process. Similarly, in the eastern portion, the dryness stood in the range considered arid, with high susceptibility. The cores with more pronounced dryness correspond to the municipalities of Cabaceiras, Caraúbas, and São João do Cariri. [ABSTRACT FROM AUTHOR]

Meteorological trend analysis is a useful tool for understanding climate change and can provide useful information on the possibility of future change. Lake Dianchi is the sixth largest freshwater body in China with serious eutrophication. Algal blooms outbreak was proven to be closely associated with some climatic factors in Lake Dianchi. It is therefore essential to explore the trends of climatic time series to understand the mechanism of climate change on lake eutrophication. We proposed an integrated method of Mann-Kendall (MK) test, seasonal-trend decomposition using locally weighted regression (LOESS) (STL), and regime shift index (RSI) to decompose the trend analysis and identify the stable and abrupt changes of some climate variables from 1951 to 2009. The variables include mean air temperature (Tm), maximum air temperatures (Tmax), minimum air temperatures (Tmin), precipitation (Prec), average relative humidity (Hum), and average wind speed (Wind). The results showed that (a) annual Tm, Tmax, and Tmin have a significant increasing trend with the increasing rates of 0.26, 0.15and 0.43 °C per decade, respectively; (b) annual precipitation has an insignificant decreasing trend with the decreasing rate of 3.17 mm per decade; (c) annual Hum has a significant decreasing trend in all seasons; and (d) there are two turning points for temperature rise around 1980 and 1995 and two abrupt change periods for precipitation with the extreme points appearing in 1963 and 1976. Temperature rise and precipitation decline in summer and autumn as well as wind speed decrease after the 1990s may be an important reason for algal blooms outbreak in Lake Dianchi. This study was expected to provide foundation and reference for regional water resource management. [ABSTRACT FROM AUTHOR]

Under global climate change, the change in temperature has greatly affected the hydrological processes and water resource security in the source region of the Yellow River, which is located in the Qinghai-Tibet Plateau and serves as a major source of domestic and agricultural water supply in the watershed. Multiple spatiotemporal analysis methods, including the S-mode empirical orthogonal function analysis, the inverse distance weighted interpolation, the weighted moving average method, and the Mann-Kendall test method were used to comprehensively analyze the temperatures of 14 meteorological stations at yearly and seasonal scales from 1961 to 2010. The results indicated that (1) general trends of temperature change have been rising, with an especially significant warming trend since the late 1990s; (2) in the last five decades, temperature trends in the study area underwent three stages, namely a cool stage (approximately 1961-1980), a fluctuating stage (approximately 1981-1997), and a warm stage (approximately 1998-2010); and (3) due to the combined effects of monsoons and geographic features, the source region could be divided into three zones according to the annual temperature variations: a low-value zone centered on Henan station in the northeastern edge; a high-value zone situated in the central, southern, and western area; and a transitional zone between the two zones mentioned above. This study is helpful for understanding temperature trends under climate change and can provide a basis for ecological protection. [ABSTRACT FROM AUTHOR]

For 50 years of long observation period (1960-2009), on a high level of statistical significance (95 %), a decreasing trend of annual precipitation amounts and an increasing trend of the number of rainy days during the year (64 %) were found. For the seasonal changes (V-X), similarly, there was found a statistically significant (94 %) decreasing precipitation amount trend and an increasing trend of the number of rainy days (50 %). As far as the intensity of maximum precipitation is concerned, a very statistically significant increasing trend (95 %) was found. Taking as the basis, the model for a trend, defined for the period of 1960-2009, the increase of weighted average interval values of maximum precipitation amounts ( h ≥ 0.75 t) in the year 2059 was estimated to be about 26 %, in comparison with the starting year 1960. An increasing trend of maximum precipitation frequency in Wrocław was also proved. To a safe sewerage systems designing in Wrocław according to current standards (EN 752 ; DWA-A118 ), the precipitation frequency to the simulations of excessive accumulation occurrences to the land level should be changed. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to evaluate the impacts of climate change on Izmir-Tahtali freshwater basin, which is located in the Aegean Region of Turkey. For this purpose, a developed strategy involving statistical downscaling and hydrological modeling is illustrated through its application to the basin. Prior to statistical downscaling of precipitation and temperature, the explanatory variables are obtained from National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data set. All possible regression approach is used to establish the most parsimonious relationship between precipitation, temperature, and climatic variables. Selected predictors have been used in training of artificial neural networks-based downscaling models and the trained models with the obtained relationships have been operated to produce scenario precipitation and temperature from the simulations of third Generation Coupled Climate Model. Biases from downscaled outputs have been reduced after downscaling process. Finally, the corrected downscaled outputs have been transformed to runoff by means of a monthly parametric hydrological model GR2M to assess the probable impacts of temperature and precipitation changes on runoff. According to the A1B climate scenario results, statistically significant trends are foreseen for precipitation, temperature, and runoff in the study basin. [ABSTRACT FROM AUTHOR]