This study investigated the annual and seasonal rainfall variability at five selected stations of Amhara Regional State, by using the innovative trend analysis method (ITAM), Mann-Kendall (MK) and Sen’s slope estimator test. The result showed that the trend of annual rainfall was increasing in Gondar (Z = 1.69), Motta (Z = 0.93), and Bahir Dar (Z = 0.07) stations. However, the trends in Dangla (Z = −0.37) and Adet (Z = −0.32) stations showed a decreasing trend. As far as monthly and seasonal variability of rainfall are concerned, all the stations exhibited sensitivity of change. The trend of rainfall in May, June, July, August, and September was increasing. However, the trend on the rest of other months showed a decreasing trend. The increase in rainfall during Kiremt season, along with the decrease in number of rainy days, leads to an increase of extreme rainfall events over the region during 1980–2016. The consistency in rainfall trends over the study region confirms the robustness of the change in trends. Innovative trend analysis method is very crucial method for detecting the trends in rainfall time series data due to its potential to present the results in graphical format as well. The findings of this paper could help researchers to understand the annual and seasonal variability of rainfall over the study region and become a foundation for further studies.

The Awash river basin has been the most extensively developed and used river basin in Ethiopia since modern agriculture was introduced. This paper investigated the annual precipitation, temperature, and river discharge variability using the innovative trend analysis method (ITAM), Mann–Kendall (MK) test, and Sen’s slope estimator test. The results showed that the trend of annual precipitation was significantly increasing in Fitche (Z = 0.82) and Gewane (Z = 0.80), whereas the trend in Bui (Z = 69) was slightly decreasing and the trend in Sekoru (Z = 0.45) was sharply decreasing. As far as temperature trends were concerned, a statistically significant increasing trend was observed in Fitche (Z = 3.77), Bui (Z = 4.84), and Gewane (Z = 5.59). However, the trend in Sekoru (Z = 1.37) was decreasing with statistical significance. The discharge in the study basin showed a decreasing trend during the study period. Generally, the increasing and decreasing levels of precipitation, temperature, and discharge across the stations in this study indicate the change in trends. The results of this study could help researchers, policymakers, and water resources managers to understand the variability of precipitation, temperature, and river discharge over the study basin.

The upper part of the Huai River basin is spatially extensive, with pronounced environmental gradients driven primarily by precipitation and temperature on broad scales. Therefore, it is an ideal region in which to examine the climate dynamics of the region. This study investigates the annual precipitation and temperature time serious variability, at six designated representative stations, by using the innovative trend analysis method (ITA), Mann-Kendall (MK) and Sen’s slope test estimator. The result showed that the trend of annual precipitation was slightly decreasing in Xiangcheng (Z = -2.04), Zhumadian ( Z= -0.43), Gushi (Z = 0.26), Xinyang (Z = -2.22), and Xichong (Z = -0.59) stations. Increasing trend was observed only in Fuyang station (Z = -0.97). Summer is characterized by high temperature and its major rain season in the study area, which contributes about 49.3% of total rainfall. In all stations the trend of annual temperature in Xiangcheng (Z = 6.72), Zhumadian (Z = 7.04), Gushi (Z = 6.96), Fuyang (Z = 7.07), Xinyang (Z = 7.04) and Xichong (Z = 2.85) sharply increased. The average air temperature has significantly increased by 1.2ºC during the past 56 years. The ITA was found to be reliable and consistent as MK and Sen’s slope test estimators for the study region. Furthermore, ITA can present the data in graphical format for better understanding of the results through detecting a sub trend series. Therefore, this study can be an inordinate resource to other researchers for studying climate variability and their impacts to eco-hydrology using the ITA method.

Mongolia’s Selenga sub-basin of the Lake Baikal basin is spatially extensive, with pronounced environmental gradients driven primarily by precipitation and air temperature on broad scales. Therefore, it is an ideal region to examine the dynamics of the climate and the hydrological system. This study investigated the annual precipitation, air temperature, and river discharge variability at five selected stations of the sub-basin by using Mann-Kendall (MK), Innovative trend analysis method (ITAM), and Sen’s slope estimator test. The result showed that the trend of annual precipitation was slightly increasing in Ulaanbaatar (Z = 0.71), Erdenet (Z = 0.13), and Tsetserleg (Z = 0.26) stations. Whereas Murun (Z = 2.45) and Sukhbaatar (Z = 1.06) stations showed a significant increasing trend. And also, the trend of annual air temperature in Ulaanbaatar (Z = 5.88), Erdenet (Z = 3.87), Tsetserleg (Z = 4.38), Murun (Z = 4.77), and Sukhbaatar (Z = 2.85) was sharply increased. The average air temperature has significantly increased by 1.4 °C in the past 38 years. This is very high in the semi-arid zone of central Asia. The river discharge showed a significantly decreasing trend during the study period years. It has been apparent since 1995. The findings of this paper could help researchers to understand the annual variability of precipitation, air temperature, and river discharge over the study region and, therefore, become a foundation for further studies.

The Ugii Nuur Lake is not only one of the small hydrologically closed lakes located in the Orkhon River Basin in Central Mongolia but also the most vulnerable area for global climate change. Therefore, this study aims to investigate the impacts of recent global climate change on the water surface area. The data we analyzed were various measured hydro-meteorological variables of the lake basin and the lake surface area, which was estimated from Landsat series satellite data from 1986 to 2018. The methods we used were Mann-Kendall (MK), Innovative trend analysis method (ITAM), Sen’s slope estimator test, correlation, and regression analysis. The variation of lake water surface area has a strong positive correlation with the change of the lake water level (r = 0.95). The Mann-Kendall trend analysis has indicated that under a significant decrease in total annual precipitation ( $\mathrm{Z}$ = −0.902) and inflow river discharge ( $\mathrm{Z}$ = −5.392) and a considerable increase in total annual evaporation ( $\mathrm{Z}$ = 4.385) and annual average air temperature ( $\mathrm{Z}$ = 4.595), the surface area of the Ugii Nuur Lake has decreased sharply ( $\mathrm{Z}$ = −6.021). The total annual evaporation (r = −0.64) and inflow river discharge (r = 0.67) were the essential hydro-meteorological factors affecting the surface area of the Ugii Nuur Lake. The lake surface area decreased by 13.5% in 2018 compared with 1986. In the near future, it is vital to conduct scientific studies considering the volume of lake water, groundwater, and the anthropogenic impact.

In a context of climate change, precipitation patterns show substantial disturbances and the occurrence of precipitation anomalies has tended to increase in the Huang-Huai-Hai River Basin. These anomalies are likely influencing vegetation dynamics and ecosystem stability. This paper aims to have a comprehensive understanding of vegetation growth response towards the precipitation pattern in the Huang-Huai-Hai River Basin. The study used NDVI (Normalized Difference Vegetation Index) data and mapped precipitation datasets from 1982 to 2011. NDVI and precipitation show a similar spatial distribution: they decrease from the southeast coast to the northwest inland. Regions with sparse vegetation are mainly distributed in arid and semi-arid areas or densely-populated areas. Vegetation coverage and the regular precipitation pattern show a positive correlation (61.6% of the whole region), while the correlation between vegetation coverage and precipitation anomalies is negative (62.7% for rainless days and 60.3% for rainstorm days). The clustering result shows that abundant vegetation is mainly situated in high precipitation or low anomaly areas. On the contrary, the degraded regions are mainly distributed in low precipitation or high anomaly areas. However, some special regions, mainly located in the Three North Shelterbelt Program region, the Tibetan Plateau, and other regions along the rivers, present improved vegetation cover when precipitation decreases or extreme events occur.