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In the wake of global and regional climate change and heightened human activities, runoff from some rivers in the world, especially in the arid and semi-arid regions, has significantly decreased. To reveal the varying characteristics leading to the change in runoff, detecting the influencing factors has been important in recent scientific discussions for water resources management in drainage basins. In this paper, an investigation into attributing the runoff response to climate change and human activities were conducted in two catchments (Wushan and Shetang), situated in the upper reaches of Weihe River in China. Prior to the identification of the factors that influenced runoff changes, the Mann-Kendall test was adopted to identify the trends in hydro-climate series. Also, change-points in the annual runoff were detected through Pettitt's test and the precipitation-runoff double cumulative curve method. It is found that both catchments presented significant negative trend in annual runoff and the detected change-point in runoff occurs in 1993. Hence, the pre-change period and post-change period are defined before and after 1993, respectively. Then, runoff response to climate change and human activities was quantitatively evaluated on the basis of hydrologic sensitivity analysis and hydrologic model simulation. They provided similar estimates of the percentage change in mean annual runoff for the post-change period over the considered catchments. It is found that the decline in annual runoff over both catchments can be mainly attributed to the human activities, the reduction percentages due to human activities range from 59 to 77 %. The results of this study can provide a reference for the development, utilization and management of the regional water resources and ecological environment protection. [ABSTRACT FROM AUTHOR]

Aridity is a climatic phenomenon characterized by shortage of water availability in a given time and space resulting in low moisture and reduced carrying capacity of ecosystems. It is represented by a numerical indicator known as Aridity Index (AI), a function of rainfall and temperature. Aridification is a slow and steady effect of climate change and assessing its spread and change is vital in context of global climatic variations. Aridity is predominantly significant for agrarian countries like India, where a slight rise in drylands area can have a significant impact on the economy and community sustenance. AI is an inclusive indicator of climatic conditions in most arid and semi-arid regions. It helps in identifying and interpreting large scale trend in temperature and precipitation; and thus, classifying region into different climatic classes. The present study assessed long-term AI based on precipitation and temperature data obtained from the India Meteorological Department at the resolution of 1 × 1 degree for years 1969–2017. AI is estimated as a ratio of mean precipitation to mean potential evapotranspiration, calculated using Thornthwaite method. The results highlight the trend of aridity over pan-India with Innovative Trend Analysis and Mann–Kendall test. The study concludes that there is a relatively slow, however steadily progressive drier conditions being established in most of the regions. A shift from 'Semi-arid' towards 'Arid' class appeared in central mainland. The north-eastern Himalaya showed decrease in humid conditions ('Humid' to 'Sub-humid'). The study implies that there is a rising aridity trend over the years due to changing climatic conditions. The shifts in aridity can have serious implications on agriculture, long-term water resource utilization and land use management plans. Our results have scope for future landscape management studies in drylands and better adaptation methods in arid regions. [ABSTRACT FROM AUTHOR]

A comprehensive investigation of historical hydro-climatic changes at a county level is an essential prerequisite of developing any adaptation or mitigation strategies to deal with the destructive impacts of climate change. In this study, spatial distributions and trends in thirty-seven hydro-climatic mean and extreme indices across Iran were analyzed based on the state-of-the-art reanalysis datasets (ERA5-Land and AgERA5) at the county level from 1986 to 2015 using several nonparametric approaches such as multiple modified Mann–Kendall statistical tests and Sen's Slope estimator. Their interannual oscillations were also examined using continuous wavelet transform to portray a complete picture of the temporal variability of the variables. The micro-scale of the reanalysis datasets enabled us to deal with the sparse distribution of weather stations in Iran, study various hydro-climatic variables that have received less attention, and subsequently provide a comprehensive, all-in-one reference for later policy actions and further studies. Analyzing diverse, intercorrelated variables provides a great opportunity to explore the driving forces of the temporal patterns. The results showed that trends in hydro-climatic mean and extreme indices highly depended on their geographical location and climate zones. The snow and the warm temperate climates encountered larger hydro-climatic changes compared to the arid and semi-arid climates zones. The most noticeable trends were found for temperature which significantly increased over all counties while drying trends were observed in precipitation, surface reservoir content, and runoff. Wind speed and surface albedo in most counties experienced upward and downward trends, respectively, whereas solar radiation, surface air pressure, and evaporation exhibited a high spatial variability. In terms of extreme events, Iran was faced with an increase in hot climate extremes and a decrease in cold and precipitation extremes. At last, the wavelet power spectrum analysis demonstrated the annual and seasonal dominant periods for precipitation and an annual dominant period for temperature, and there were significant periodic variations at 2–3 years for hot and cold spell durations and intensity-based precipitation index and 4–6 years for consecutive dry and wet days. The annual fluctuation of precipitation reduced over the study period, but that of temperature remained almost constant. [ABSTRACT FROM AUTHOR]

As one of the most important climatic variables, annual evapotranspiration ( E) reflects the complex interactions between atmosphere, vegetation, soil and hydrological process at global and regional scales. It is largely determined by potential evapotranspiration ( E) and precipitation ( P). Aridity index ( E/ P) which can be defined as the ratio of annual potential evapotranspiration to annual precipitation, can be used to represent annual evapotranspiration. As result it has become an important indicator to assess water-related climate change. This study utilizes the aridity index to reveal the recent climate change patterns in the Lancang River Basin, China. A new non parametric estimator of climate elasticity has also been developed. Using the daily meteorological records (1961-2005) of precipitation, air temperature, wind speed, relative humidity and sunshine hours from 35 stations, changes in spatial and temporal characteristics of P, E , E, and E/ P are analyzed. The results reveal some important new findings, which can be summarized as: (a) new findings show that the spatial distribution of, and the correlation coefficients between P, E, E, and E/ P possess strong latitude zonality; (b) high consistency in the temporal variation of P and E has been detected. The main periodicity of the E and E/ P series varies greatly for the three sub basins, and an anti-phase relationship between them has also been found; (c) our newly developed nonparametric estimator of climate elasticity can be successfully used in assessing the sensitivity of climate system. Climate elasticity of E in relation to E and P increases for most of the regions in the study area, suggesting that E becomes more sensitive to changes in the corresponding climatic variable during the study period. The study demonstrates the importance of the aridity index in the water-related climate change studies which has been neglected for a long time by most hydrologists and managers. [ABSTRACT FROM AUTHOR]

Warm-season (from May to September) pan evaporation series recorded at nine sites in semi-arid Büyük Menderes Basin in Western Turkey were analyzed for evidence of long-term changes using non-parametric Mann-Kendall test. Only two sites showed significant linear trends, one in decreasing direction and the other in increasing direction. Area-averaged normalized anomalies of pan evaporation stayed unchanged over the period 1975-2006. Based on correlation and multiple regression analysis with visual inspection of the time series plots, sunshine duration which is used as a proxy for global radiation was found to be the major factor explaining the change and variability of pan evaporation in warm-season in semi-arid Büyük Menderes Basin. Stepwise multiple regression analysis showed no significant effect of rainfall on pan evaporation, which means that the effect of complementary relationship is rather weak and even non-existent. [ABSTRACT FROM AUTHOR]