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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]

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]