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Vegetation protection and restoration, protective forest and grass construction, as the typical Slope Green Infrastructures (SGI), significantly effect water hydrological and environmental process on the slope. The change of water production and confluence impact the river discharge, which could determine the environmental condition of waters. This review investigated the relevant literature over the past 20 years via the bibliometric tool, and analyzed the relevant hotspots of SGI and water quantity-quality (WQQ). Findings confirm that urban, runoff, land use, stormwater, climate change had been paid attention. Then the potential response of the water cycle and water environmental process to the SGI construction were explored, including precipitation, evaporation, and dissolved oxygen, nitrate, etc. WQQ joint simulation methods were also listed. At last, we proposed the development trend and future research hotspots of the research on SGI and WQQ. The word of this paper could provide technique support for water problem treatment and natural resource management at the watershed scale.

Soil is an important component connecting atmosphere and vegetation, and is an important 'regulator' of slope hydrological process. Global warming accelerates the global water cycle, and Soil Moisture Content (SMC) will change, but this change is not yet clear. Here, we study the global trend of SMC at different depths over the past 70 years and the next 70 years, based on the GLDAS-NOAH025 dataset and precipitation and temperature data from 15 CMIP6 models. We found that compared with the long-term average of 70 years, the global 0-200 cm SMC is decreasing at a rate of 1.284 kg/m

The process of freshwater discharge into the oceans is a key component of global water cycle between land and ocean. Climate change and human activities are considerably affecting the amount of surface runoff entering the ocean. This paper examines how global continental discharge into the ocean has changed over the past seven decades. The results indicate that from 1951 to 2020, global annual amount of continental discharge entering the oceans is 39.33 trillion m³ on average. It exhibited an upward trend before 2000, but fell sharply thereafter, particularly showing a faster decrease in the recent decade and reaching the record low. The overall continental discharge specific to oceans has been diminishing, except for the Arctic Ocean with a growth. About 71% of the land area experienced an abrupt changing points in the continental discharge into the ocean, among which 97% areas saw a progressive decline after the changing point. Such change is directly related to reduced precipitation, increased evaporation, and expanded human water withdrawal. The shrinkage of continental discharge into the ocean will directly impact on ocean circulation, which may further accelerate the variation of global water cycle.

Water and soil losses from sloping farmlands potentially contribute to water eutrophication and land degradation. However, few studies explored the combined effects of ridge direction and ridge width on surface runoff and soil losses of sloping farmlands. Twenty-seven experimental plots (8 m long and 4 m wide) with nine treatments (three ridge direction: cross ridge, longitudinal ridge, and oblique ridge; and three ridge width: 40, 60, and 80 cm) were adopted under natural rainfall conditions for two years in the Luanhe River Basin of China. Results indicated that ridge direction had significant effects on runoff and sediment yield (p < 0.05). The ridge width had no significant effect on runoff and sediment yield. No significant interaction effect was found between ridge direction and width on runoff and sediment yield of the sloping farmland based on statistical analyses. Compared with cross-ridge (CR) tillage and oblique-ridge (OR) tillage, longitudinal-ridge (LR) tillage significantly decreased runoff by 78.9% and 64.9% and soil losses by 88.2 and 83.5%, respectively (p < 0.05). The effects of ridge directions on runoff and sediment yield were related to rainfall grade. When the rainfall grade reached rainstorm, the runoff yield under CR, LR, and SR had significant differences (p < 0.05). The runoff under LR and OR treatment was 5.16 and 3.3 times, respectively, of that under CR. When the rainfall level was heavy rain or rainstorm, the sediment yield under LR was significantly greater than that under CR. The sediment yield was 13.45 times of that under CR. Cross-ridge tillage with a ridge width of 40 cm is an optimally effective measure of soil and water conservation on sloping farmland in arid and semiarid regions of China.

Ecosystem service values are closely related to land use/cover change, however, the values affected by land use/cover change in the context of climate variability remain unclear. Based on the land use/cover data of 2000, 2010, and 2020 in the Yiluo River Basin, we quantitatively analyzed the impacts of historical land use/cover change on the ecosystem service values. Then the future land use simulation model was applied to predict the land use/cover distribution in 2030 under three Representative Concentration Pathways scenarios, and the influences on ecosystem service values were analyzed further. We found that the total ecosystem service values in the Yiluo River Basin presented a growth from 9217 million dollars (2000) to 9676 million dollars (2020), which attributed to the increase of forestland and water bodies in recent years. By 2030, the total ecosystem service values continued to present an upward trend, while also showing a difference under three scenarios, this discrepancy was mainly caused by different precipitation conditions. With the introduction of the ecological protection and high-quality development of the Yellow River basin in the new period, climate change may be the main factors affecting the ecological field in the future.

The foundation of managing excess nutrients in river is the identification of key physical processes and the control of decisive influencing factors. The existing studies seldom consider the influence of rainfall-runoff relationship and only focus on a few anthropogenic activities and natural attributes factors. To address this issue, a comprehensive set of influencing factors including rainfall-runoff relationship (represented by runoff coefficient), basic physical and chemical parameters of water quality, land use types, landscape patterns, topography, and socioeconomic development was constructed in this study. M–K test and cluster analysis were conducted to identify the temporal mutation and spatial clustering characteristics of NH3-N and TP in Huangshui River basin, respectively. Partial least squares regression was used to elucidate the linkages between water contaminants and the factors. As shown in the results, the temporal mutations of NH3-N and TP were obvious in the middle reaches, with 4 out of 7 catchments in the middle reaches have a larger number of mutations of NH3-N than other catchments. The cluster analysis results of NH3-N and TP among catchments were similar. This study also indicated that although the Huangshui River basin was located in the upper reaches of the Yellow River, the influences of rainfall-runoff relationship on spatiotemporal changes of NH3-N and TP in its sub-basins were limited. Only the temporal change of NH3-N in Jintan catchment in the upstream area was significantly affected by runoff coefficient. The indexes of proportion of water area (PWA), proportion of impervious area (PIA), and proportion of primary industry (PPI) were the top three influencing factors of temporal variation of NH3-N and TP for most catchments in the middle reaches. The temporal change of NH3-N in Jintan catchment in the upstream area was obviously affected by runoff coefficient. The spatial variation of NH3-N and TP were all affected by PWA and proportion of secondary industry significantly. The results of this study can provide theoretical basis and technical support for the control and management of nitrogen and phosphorus pollution in upper reaches of rivers.

Duckweed is a common category of floating plant which floats on or beneath the surface of still or slow-moving bodies of wetlands.Its growth has much effect on the hydro-ecological process of wetlands.However, in the existing wetland-ecosystem simulation models which contained floating- or emergent-plant modules, the shading effect of macrophytes and the relationship between macrophytes and phytoplankton in the wetland ecosystem were not considered sufficiently.When these models were directly used in the modeling of duckweed-dominated wetlands, the simulation effects of main state variables such as phytoplankton and dissolved inorganic phosphorus in water were poor and the models could not completely respond to the changes of the external variables. Through a field experiment and parameter calibrations, the shading effect of duckweed and the relationship between duckweed and phytoplankton were considered originally in this study. A duckweed-dominated wetland structurally dynamic (DWSD) model was developed for the Hanshiqiao wetland in Beijing. The development of this model included three procedures. (1) The relationship between the shading effect of duckweed and the biomass of duckweed was investigated based on a field experiment. (2)The equations of transmitted light intensity in water and of the growth of phytoplankton were revised according to the relationship obtained. (3)A module of duckweed was developed, and was incorporated into the structurally dynamic model. The DWSD model was calibrated and verified using the ecological survey data of the Hanshiqiao wetland in 2014. The decisive coefficients (R2) and Nash-Sutcliffe coefficients (ENS) for model calibration were not less than 0.9 in reproducing A and FP, and meanwhile R2 and ENS of A and FP for model validation were all above 0.8. They showed that this model had acceptable simulation efficiencies both in calibration and verification. The DWSD model was used to predict changes of main state variables in 2015. As the simulation results showed, the module of duckweed posed significant impacts on the modeling of results, which performed in various aspects. For instance, the precision of this model was increased. The simulated values of phytoplankton and detritus in water for the DWSD model were all closer to the observed values than that without the module of duckweed. The transmitted light intensity in water from July to October was decreased. The growth of phytoplankton was inhibited and the simulated values of the content of detritus and the concentration of phosphorus in water were increased.

Soil nitrogen in farmland ecosystems is affected by climate, soil physical and chemical properties and planting activities. To clarify the effects of these factors on soil nitrogen in sloping farmland quantitatively, the distribution of soil total nitrogen (TN) content, nitrate nitrogen (NO3-N) content and ammonium nitrogen (NH4-N) content at depth of 0–100 cm on 11 profiles of the Luanhe River Basin were analyzed. Meanwhile, soil physical and chemical properties, climatic factors and NDVI (Normalized Difference Vegetation Index) were used to construct a structural equation which reflected the influence mechanism of environmental factors on soil nitrogen concentration. The results showed that TN and NO3-N content decreased with the increase of soil depth in the Luanhe River Basin, while the variation of NH4-N content with soil depth was not obvious. Soil organic carbon (SOC) content, soil pH, soil area average particle size (SMD) and NDVI6 (NDVI of June) explained variation of TN content by 77.4%. SOC was the most important environmental factor contributing to the variation of TN content. NDVI5 (NDVI of May), annual average precipitation (MAP), soil pH and SOC explained 49.1% variation of NO3-N content. Among all environmental factors, only NDVI8 (NDVI of August) had significant correlation with soil NH4-N content, which explained the change of NH4-N content by 24.2%. The results showed that soil nitrogen content in the sloping farmland ecosystem was mainly affected by natural factors such as soil parent material and climate.

Quality and representative precipitation data play an essential role in hydro-meteorological analyses. However, the required reliability and coverage is often unavailable from conventional gauge observations. As a result, globally available precipitation datasets are being used as an alternative or supplementary to gauge observations. In this study, the accuracy of three recently released, high-resolution precipitation datasets with a spatial resolution of 0.1&deg, and a daily temporal resolution is evaluated over the Upper Blue Nile River Basin (UBNRB) for the period of 2007 to 2016. The datasets are Integrated Multi-satellitE Retrievals for GPM version 6 (IMERG6), Multi-Source Weighted-Ensemble Precipitation version 2.2 (MSWEP2.2) and soil moisture to rain using Advanced SCATterometer version 1.1 (SM2RAIN-ASCAT1.1). The comparison was made between rain gauge observations and two other high-resolution precipitation datasets named Enhancing National Climate Services (ENACTS) and Climate Hazards Group Infrared Precipitation with Stations version 2 (CHIRPS2). The modified Kling-Gupta efficiency (KGE&rsquo, ) and four categorical indices named probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and frequency bias (fBIAS) was used to measure the skills of each dataset. Results revealed that, except SM2RAIN-ASCAT1.1, all other datasets show a better ability on a monthly time scale for areas with an elevation below 1500 m above sea level (m.a.s.l). The overall performance was better in the wetter months of March to August than the drier months of September to February. Besides, all products including SM2RAIN-ASCAT1.1 could detect no rain events (rain &lt, 1 mm) correctly, but their skill deteriorates on identifying higher intensity events. By comparison, ENACTS (calibrated with most quality gauges of Ethiopia) and CHIRPS2 exhibited the best performance due to their high-resolution nature and inclusion of physiographic information in their data generation procedures. IMERG6 and MSWEP2.2 showed the next best performance according to both the continuous and categorical indices used. SM2RAIN-ASCAT1.1 demonstrates the least skill everywhere due to problems that could be associated with misinterpretations of soil moisture signals by the SM2RAIN algorithm. Considering the scarcity of gauged datasets over UBNRB, IMERG6 and MSWEP2.2 could be regarded as valuable datasets for hydro-climatic analysis, mainly where gauge density is low. SM2RAIN-ASCAT1.1, on the other hand, needs significant bias correction to treat its apparent wet biases before any application.

Analyzing the instream environmental flow demand by coupling the hydrological cycle and the hydrodynamic process with aquatic ecological processes at watershed scale remains one of the most important yet most difficult issues. One or two of the above processes have been the focus in the evaluation of intra-annual ecological water demand in recent studies. In this study, a hydrology–hydrodynamic–habitat model was developed and applied to the Huangshui River basin. A new classification method for instream ecological water demand (IEWD), which considered sensitive species was proposed. The suitable level of IEWD and crucial values with different flow frequencies were analysed, including runoff, water level, water surface width and weighted usable areas (WUA). The results of the study indicated that monthly IEWD had an increasing trend during the flood season and a decreasing trend during the non-flood season in three sections at different suitable levels. With the increase of suitable levels, the range of IEWD in three sections also increased. The IEWD and crucial values were the lowest in March with the smallest range and were the highest from July to October because the amount of precipitation during that period accounted for nearly 84.3% of that of the entire year. Furthermore, the lower the flow frequency in three sections, the higher the suitable levels of IEWD, as well as water level and water surface width every month. When the flow frequency of 90% decreased to 75%, the value of IEWD increased by at least 55% during the wet season and doubled during the dry season. The WUA with the lowest or highest flow frequencies were relatively poor, especially reproduction period. The IEWD and crucial values at different suitable levels agreed with the actual situations. Thus, this study provided a new method for implementing river ecosystem restoration and aquatic ecosystem management.

Slope ecological restoration and climate change are important factors affecting the hydrological processes of the Huangshui River Basin in Qinghai province, China. How to quantitatively identify the impact of slope ecological restoration on runoff and whether slope ecological restoration can mitigate the impact of future climate change on runoff are both very important. In this paper, the Huangshui River above the center of Minhe county was taken as the research area, and the Pinus tabulaeformis and shrubs were taken as the main forest land types of slope ecological restoration. First, based on the law of forest land variation, the construction scales of slope ecological restoration in different periods were identified. The influence of slope ecological restoration on runoff was then quantitatively evaluated by using a distributed hydrological model. Second, the future climate scenarios of five general circulation models (GCMs) under three representative concentration pathways (RCPs) (i.e., RCP2.6, RCP4.5, and RCP8.5) from 2021 to 2050 were selected and modified by model integration. Combined with the slope ecological restoration scenarios, the influence of slope ecological restoration on runoff under future climate scenarios was explored. The results showed that the effect of slope ecological restoration was significant. Compared with 1980, the area of slope ecological restoration increased by 24% in 2017. Under the present climate conditions (1960&ndash, 2017), different periods of slope ecological restoration have an effect on the process of runoff in the wet season (June, July, August, and September) and dry season (January, February, March, and December), which eliminates the maximum, replenishes the minimum, and reduces the variability of runoff processes in the watershed. Under the future climate scenario (2021&ndash, 50), slope ecological restoration will reduce runoff. On the other hand, climate change will increase runoff, and the combination of the two effects will have a certain offsetting effect. On the whole, comparing the influence of slope ecological restoration on the runoff process with that of climate change in different seasons, due to the main influence of slope ecological restoration, the runoff decreased by about 55% in the temperate season (April, May, October, and November), and increased by about 50% in the dry season or wet season due to the main influence of future climate scenarios.