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The changes of runoff in the middle reaches of the Yellow River basin of China have received considerable attention owing to their sharply decline during recent decades. In this paper, the impacts of rainfall characteristics and land use and cover change on water yields in the Jingle sub-basin of the middle reaches of the Yellow River basin were investigated using a combination of statistical analysis and hydrological simulations. The Levenberg Marquardt and Analysis of Variance methods were used to construct multivariate, nonlinear, model equations between runoff coefficient and rainfall intensity and vegetation coverage. The land use changes from 1971 to 2017 were ascertained using transition matrix analysis. The impact of land use on water yields was estimated using the M-EIES hydrological model. The results show that the runoff during flood season (July to September) decreased significantly after 2000, whereas slightly decreasing trend was detected for precipitation. Furthermore, there were increase in short, intense, rainfall events after 2000 and this rainfall events were more conducive to flood generation. The “Grain for Green” project was carried out in 1999, and the land use in the middle reaches of the Yellow River improved significantly, which make the vegetation coverage (Vc) of the Jingle sub-basin increased by 13%. When Vc approaches 48%, the runoff coefficient decreased to the lowest, and the vegetation conditions have the greatest effect on reducing runoff. Both land use and climate can change the water yield in the basin, but for areas where land use has significantly improved, the impact of land use change on water yield plays a dominant role. The results acquired in this study provide a useful reference for water resources planning and soil and water conservation in the erodible areas of the middle reaches of the Yellow River basin.

Rational allocation of water resources is very essential to cope with water scarcity. The optimal allocation of limited water resources is required for various purposes to achieve sustainable development. The Awash River Basin is currently faced with a scarcity of water due to increasing demands, urbanization, irrigation expansion, and variability of climates. The excessive abstraction of water resources in the basin without proper assessing of the available water resources contributed to water scarcity. This paper aimed to develop a water evaluation and planning (WEAP) model to allocate the water supplies to demanding sectors based on an economic parameter to maximize the economic benefits. The water demands, water shortages, and supply alternatives were analyzed under different scenarios. Three scenarios were developed, namely reference (1981–2016), medium-term development (2017–2030), and long-term development (2031–2050) future scenarios with the baseline period (1980). The results of this study showed that the total quantity of water needed to meet the irrigation demands of all the stations was 306.96 MCM from 1980 to 2016. Seasonally, March, April, May, and June require the maximum irrigation water demand. However, July, August, and September require minimum demand for water because of the rainy season. The seasonal unmet demand is observed in all months, which ranged from 6 × 106 m3 to 35.9 × 106 m3 in August and May respectively. The trend of streamflow in Melka Kuntre was a statistically significant increasing trend after 2008 (Z = 5.33) whereas the trends in other gauge stations showed a relatively decreasing trend. The results also showed that future water consumption would greatly increase in the Awash River Basin. The prevention of future water shortages requires the implementation of water-saving measures and the use of new water supply technologies. The findings of this study will serve as a reference for water resources managers and policy and decision makers.

Economic well-being is essential for assessing sustainability of human settlement in urbanizing regions; however, the geographic factors linking settlement characteristics to residents’ well-being remain underexplored, particularly in counties in China undergoing urban–rural transformation. In this study, six representative Chinese counties (Yanshou, Wafangdian, Bazhou, Yugan, Yongsheng, and Raoping) with varying urbanization levels are investigated to establish a multidimensional evaluation framework and reveal the geographic factors underlying economic well-being. Through original household surveys conducted across these six geographically and economically diverse counties, we collected primary data from 1659 households; these data provide unique insights into residents’ lived experiences. By integrating these original survey data with objective indicators from statistical yearbooks and geographic features from multisource spatial data, key drivers were identified using Pearson correlation and random forest models. The results show the following trends: (1) significant county-level variation in subjective well-being, with Wafangdian ranking the highest and Bazhou ranking the lowest, while well-being aligned more closely with economic development levels; (2) income and happiness were the dominant determinants of subjective well-being, with work-related factors also contributing substantially, whereas nighttime light intensity, building density, and construction land area drove fusion well-being; and (3) multifactor modeling demonstrated strong explanatory power for fusion well-being (training set R2 = 0.8313; validation set R2 = 0.7531), indicating generalizability. The primary data collection across varied settlement settings provides strong empirical grounding. The findings reveal the spatial differentiation of economic well-being in urbanizing settlements, offering empirical support for targeted settlement planning and urban governance policies to improve sustainability and residents’ well-being in developing countries.

The 2303 Wetlands of International Importance distribute unevenly in different continents. Europe owns the largest number of sites, while Africa has the largest area of sites. More than half of the sites are affected by three or four impact factors (55%). The most significant impact factors are pollution (54%), biological resources use (53%), natural system modification (53%), and agriculture and aquaculture (42%). The main affected objects are land area and environment of the wetlands, occurred in 75% and 69% of the sites, respectively. The types most affected by land area occupation are river wetlands and lake wetlands, the types with the greatest impact on environment are marine/coastal wetlands and river wetlands, the type with the greatest impact on biodiversity is river wetlands, the types most affected by water resources regulation are marsh wetlands and river wetlands, and the types most affected by climate change are lake wetlands and marine/coastal wetlands. About one-third of the wetland sites have been artificially reconstructed. However, it is found that the proportions of natural wetland sites not affected or affected by only one factor are generally higher than that of wetland sites both containing natural wetlands and human-made wetlands, while the proportions of wetland sites both containing natural wetlands and human-made wetlands affected by three or four factors are generally higher than that of natural wetland sites. Wetland sites in the UK and Ireland are least affected among all countries. Wetland management plans in different regions still have large space for improvement, especially in Africa and Asia. The protection and restoration of global wetlands can be carried out in five aspects, including management and policy, monitoring, restoration, knowledge, and funding.

Tracking and quantifying the moisture sources of precipitation in different drainage basins in the Tibetan Plateau (TP) help to reveal basin-scale hydrological cycle characteristics under the interactions between the westerlies and Indian summer monsoon (ISM) systems and to improve our understanding on the mechanisms of water resource changes in the ‘Asian Water Tower’ under climate changes. Based on a Eulerian moisture tracking model (WAM-2) and three atmospheric reanalysis products (ERA-I, MERRA-2, and JRA-55), the contributions of moisture sources to the precipitation in six major sub-basins in the TP were tracked during an approximately 35-year period (1979/1980–2015). The results showed that in the upper Indus (UI), upper Tarim River (UT), and Qaidam Basin (QB), the moisture sources mainly extended westward along the mid-latitude westerlies to the western part of the Eurasian continent. In contrast, in the Yarlung Zangbo River Basin (YB), inner TP (ITP), and the source area of three eastern rivers (TER, including the Nujiang River, Lancang River, and Yangtze River), the moisture sources extended both westward and southward, but mainly southward along the ISM. In winter and spring, all of the sub-basins were dominated by western moisture sources. In summer, the western sources migrated northward with the zonal movement of the westerlies, and simultaneously the southern sources of the YB, ITP, and TER expanded largely toward the Indian Ocean along the ISM. In autumn, the moisture sources of the UI, UT, and QB shrank to the western sources, and the moisture sources of the YB, ITP, and TER shrank to the central-southern TP and the Indian subcontinent. By quantifying the moisture contributions from multiple sources, we found that the terrestrial moisture dominated in all of the sub-basins, particularly in the UT and QB (62–73%). The oceanic contributions were relatively high in the UI (38–42%) and YB (38–41%). In winter, evaporation from the large western water bodies (such as the Mediterranean, Red Sea, and Persian Gulf) was significantly higher than that from the continental areas. This contributed to the peak (valley) values of the oceanic (terrestrial) moisture contributions to all of the sub-basins. In summer, the terrestrial moisture contributions to the UI, UT, and QB reached their annual maximum, but the abundant oceanic moisture transported by the ISM restrained the appearance of land source contribution peaks in the YB, ITP, and TER, resulting in almost equal moisture contributions in the YB from the ocean and land.

Land use/land cover change and climate change have diverse impacts on the water resources of river basins. This study investigated the trends of climate change and land use/land cover change in the Nile River Basin. The climate trends were analyzed using the Mann–Kendall test, Sen’s slope estimator test and an innovative trend analysis method. Land use/land cover (LULC) change was examined using Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper (ETM+) with a resolution of 30 m during 2012–2022. The findings revealed that forestland and shrub land area decreased by 5.18 and 2.39%, respectively. On the other hand, area of grassland, cropland, settlements and water bodies increased by 1.56, 6.18, 0.05 and 0.11%, respectively. A significant increasing trend in precipitation was observed at the Gondar (Z = 1.69) and Motta (Z = 0.93) stations. However, the trend was decreasing at the Adet (Z = −0.32), Dangla (Z = −0.37) and Bahir Dar stations. The trend in temperature increased at all stations. The significant changes in land use/land cover may be caused by human-induced activities in the basin.

The shrinking of water resources along with the frequent droughts plays an effective role in intensifying the water crisis. Climate change adversely affects the hydrological cycle at the basin level. These are often reflected in the water and food insecurity, frequent hydrologic extremes, frequent drought, flooding, and deteriorating ecosystem health. This study aims to calibrate and validate the stream flows in Awash River basin using a distributed hydrological Water Evaluation And Planning (WEAP) model. Mean monthly Precipitation; temperature and stream flow are used to run the model. The model was calibrated and validated using mean stream flow. The trends of climate over the study basin were also investigated using Mann Kendall trend tests. The results revealed that the value of R 2 ranged from 0.73 to 0.91 during calibration periods. On the other hand, the value of Nash-Sutcliffe efficiency (NSE) is ranged from 0.65 to 0.83. However, the values of coefficient of determination (R 2 ) during validation periods ranged from 0.54 to 0.91 and the values of Nash-Sutcliffe efficiency (NSE), ranges from 0.50 to 0.84. Thus, The results at two important parts of the main river (upstream and downstream) gauges showed good agreement between the simulated and observed stream flow. The basin receives a significant amount of water during the rainy season (June to September). The mean annual rainfall of the basin ranges from 100 to 1700 mm with great spatiotemporal variation. The annual stream flow of the Awash River basin shows a sharp decreasing trend (Z = −0.120 during the study period. Thus, the findings of this study could provide insights for concerned bodies to implement effective water resources management techniques. The study also proposed that, to ensure the sustainability of water resources, better long-term management policies are required to be implemented in the basin and to meet future downstream water needs.

Flood risk assessment is an important tool for disaster warning and prevention. In this study, an integrated approach based on a D-number-improved analytic hierarchy process (D-AHP) and a self-organizing map (SOM) clustering algorithm are proposed for urban flooding risk assessment. The urban flood inundation model and geographic information system (GIS) technology were used to quantify the assessment indices of urban flood risk. The D-AHP approach was adopted to determine the weights of the indices, which effectively makes up for the shortcomings of the AHP in dealing with uncertain evaluation information (such as fuzzy and incomplete information). In addition, the SOM clustering algorithm was applied to determine the flood risk level. It is a data-driven approach that avoids the subjective determination of a flood risk classification threshold. The proposed approach for flood risk assessment was implemented in Zhengzhou, China. The flood risk was classified into five levels: highest risk, higher risk, medium risk, lower risk, and the lowest risk. The proportion of the highest risk areas was 9.86%; such areas were mainly distributed in the central and eastern parts of the Jinshui District, the eastern part of the Huiji District, and the northeastern part of the Guancheng District, where there were low terrain and serious waterlogging. The higher risk areas accounted for 24.26% of the study area, and were mainly distributed in the western and southern parts of the Jinshui District, the southern part of the Huiji District, the middle and eastern parts of the Zhongyuan District, the northeastern part of the Erqi District, and the northwestern part of the Guancheng District, which consisted of economically developed areas of dense population and buildings, matching well with historical flooding events. To verify the effectiveness of the proposed approach, traditional approaches for risk assessment were compared. The comparison indicated that the proposed approach is more reasonable and accurate than the traditional approaches. This study showed the potential of a novel approach to flood risk assessment. The results can provide a reference for urban flood management and disaster reduction in the study area.

A catchment is the basic unit for studying hydrologic cycle processes and associated climate change impacts. Accurate catchment delineation is essential in the field of hydrology, environment, and meteorology. Traditionally, catchment delineation is most easily carried out where the outflow area can be easily determined because of a well-defined outlet. The obstacle of the current study is to determine accurately the catchment boundary of lakes that are internally draining and, therefore, lack a well-defined outflow (i.e. inland lakes). This study describes a catchment delineation method which demarcated all the catchments of the lakes in the Qiangtang Plateau, especially for the inland lakes and their closed catchments. Lake catchment boundaries determined for the Qiangtang Plateau provide a significant advancement for water resource and climate change evaluation and agriculture production in the area.Design Type(s)modeling and simulation objective • data transformation objective • image processing objectiveMeasurement Type(s)drainage basinTechnology Type(s)computational modeling techniqueFactor Type(s)ClassificationSample Characteristic(s)Tibetan Plateau • lakeMachine-accessible metadata file describing the reported data (ISA-Tab format)

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.