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.

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 porous-fiber module (PFM) is an advanced product used for rainfall regulation and storage. Most studies focus on the characteristics of its constituent material while ignoring the impacts of PFM application on infiltration and runoff. In this study, several factors were comprehensively considered in the field control simulated rainfall experiments conducted on bare land, including two types of rainfall intensities, four PFM volumes, and two arrangements of the PFM, to evaluate the impacts. The experiments consisted of measuring soil water content variation, surface runoff of each treatment plot, and the cumulative infiltration obtained by water balance. The results demonstrated that the effect of PFM volume on infiltration and runoff was much greater than that of the PFM arrangement. The addition of PFM could improve the water-holding capacity of soil; this effect initially strengthened and subsequently weakened with the increase in the PFM volume. The PFM embedding increased the cumulative infiltration of the experimental plots by 5.1-79.2%, delayed the runoff start time by 0-20 min, weakened the peak by 13.6-51.1%, and reduced the runoff-yielding amount by 11.23-62.53%, compared with those of the control plot. These effects were enhanced as PFM volume increased. An empirical formula, presented as the theoretical influence of PFM volume on the product of the cumulative infiltration multiplied by the Philip model derived by the control plot, was further established for simulating the infiltration process with various PFM volumes.

As basic data, the river networks and water resources zones (WRZ) are critical for planning, utilization, development, conservation and management of water resources. Currently, the river network and WRZ of world are most obtained based on digital elevation model data automatically, which are not accuracy enough, especially in plains. In addition, the WRZ code is inconsistent with the river network, hindering the efficiency of data in hydrology and water resources research. Based on the global 90-meter DEM data combined with a large number of auxiliary data, this paper proposed a series of methods for generating river network and water resources zones, and then obtained high-precision global river network and corresponding WRZs at level 1 to 4. The dataset provides generated rivers with high prevision and more accurate position, reasonable basin boundaries especially in inland and plain area, also the first set of global WRZ at level 1 to 4 with unified code. It can provide an important basis and support for reasonable use of water resources and sustainable social development in the world.

The changes in climatic variables in Ethiopia are not entirely understood. This paper investigated the recent trends of precipitation and temperature on two eco-regions of Ethiopia. This study used the observed historical meteorological data from 1980 to 2016 to analyze the trends. Trend detection was done by using the non-parametric Mann-Kendall (MK), Sen's slope estimator test, and Innovative Trend Analysis Method (ITAM). The results showed that a significant increasing trend was observed in the Gondar, Bahir Dar, Gewane, Dembi-Dolo, and Negele stations. However, a slightly decreasing trend was observed in the Sekoru, Degahabur, and Maichew stations regarding precipitation trends. As far as the trend of temperature was concerned, an increasing trend was detected in the Gondar, Bahir Dar, Gewane, Degahabur, Negele, Dembi-Dolo, and Maichew stations. However, the temperature trend in Sekoru station showed a sharp decreasing trend. The effects of precipitation and temperature changes on water resources are significant after 1998. The consistency in the precipitation and temperature trends over the two eco-regions confirms the robustness of the changes. The findings of this study will serve as a reference for climate researchers, policy and decision makers.

Machine learning algorithms are becoming more and more popular in natural disaster assessment. Although the technology has been tested in flood susceptibility analysis of several watersheds, research on global flood disaster risk assessment based on machine learning methods is still rare. Considering that the watershed is the basic unit of water management, the purpose of this study was to conduct a risk assessment of floods in the global fourth-level watersheds. Thirteen conditioning factors were selected, including: maximum daily precipitation, precipitation concentration degree, altitude, slope, relief degree of land surface, soil type, Manning coefficient, proportion of forest and shrubland, proportion of artificial surface, proportion of cropland, drainage density, population, and gross domestic product. Four machine learning algorithms were selected in this study: logistic regression, naive Bayes, AdaBoost, and random forest. The global susceptibility assessment model was constructed based on four machine learning algorithms, thirteen conditioning factors, and global flood inventories. The evaluation results of the model show that the random forest performed better in the test, and is an efficient and reliable tool in flood susceptibility assessment. Sensitivity analysis of the conditioning factors showed that precipitation concentration degree and Manning coefficient were the main factors affecting flood risk in the watersheds. The susceptibility map showed that fourth-level watersheds in the global high-risk area accounted for a large proportion of the total watersheds. With the increase of extreme hydrological events caused by climate change, global flood disasters are still one of the most threatening natural disasters. The global flood susceptibility map from this study can provide a reference for global flood management.

Abstract. The interbasin long-distance water transfer project is key support for the reasonable allocation of water resources in a large-scale area, which can optimize the spatiotemporal change of water resources to secure the amount of water available. Large-scale water transfer projects have a deep influence on ecosystems; besides, global climate change causes uncertainty and additive effect of the environmental impact of water transfer projects. Therefore, how to assess the ecological and environmental impact of megaprojects in both construction and operation phases has triggered a lot of attention. The water-output area of the western route of China's South-North Water Transfer Project was taken as the study area of the present article. According to relevant evaluation principles and on the basis of background analysis, we identified the influencing factors and established the diagnostic index system. The climate-hydrology-ecology coupled simulation model was used to simulate and predict ecological and environmental responses of the water resource area in a changing environment. The emphasis of impact evaluation was placed on the reservoir construction and operation scheduling, representative river corridors and wetlands, natural reserves and the water environment below the dam sites. In the end, an overall evaluation of the comprehensive influence of the project was conducted. The research results were as follows: the environmental impacts of the western route project in the water resource area were concentrated on two aspects: the permanent destruction of vegetation during the phase of dam construction and river impoundment, and the significant influence on the hydrological situation of natural river corridor after the implementation of water extraction. The impact on local climate, vegetation ecology, typical wetlands, natural reserves and the water environment of river basins below the dam sites was small.

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.