Basin-Scale Approach to Integration of Agro- and Hydroecological Monitoring for Sustainable Environmental Management: A Case Study of Belgorod Oblast, European Russia

The quantitative and qualitative depletion of water resources (both surface and groundwater) is closely related to the need to protect soils against degradation, rationalization of land use, and regulation of surface water runoff within the watershed area. Belgorod Oblast (27,100 km2), one of the administrative regions of European Russia, was chosen as the study area. It is characterized by a high activity of soil erosion (the share of eroded soils is about 48% of the total area of arable land). The development phase of the River Basin Environmental Management Projects (217 river basins from the fourth to seventh order) allowed for the proceeding of the development of an integrated monitoring system for river systems and river basin systems. The methods used to establish a geoecological network for regional monitoring include the selection and application of GIS techniques to quantify the main indicators of ecological state and predisposition of river basins to soil erosion (the share of cropland and forestland, the share of the south-oriented slopes, soil erodibility, Slope Length and Steepness (LS) factor, erosion index of precipitation, and the river network density) and the method of a hierarchical classification of cluster analysis for the grouping of river basins. An approach considering the typology of river basins is also used to expand the regional network of hydrological gauging stations to rationalize the national hydrological monitoring network. By establishing 16 additional gauging stations on rivers from the fourth to seventh order, this approach allows for an increase in the area of hydro-agroecological monitoring by 1.26 times (i.e., up to 77.5% of the total area of Belgorod Oblast). Some integrated indicators of agroecological (on the watershed surface) and hydroecological (in river water flow) monitoring are proposed to improve basin environmental management projects. Six-year monitoring showed the effectiveness of water quality control measures on an example of a decrease in the concentrations of five major pollutants in river waters.

Multi-Model Assessment of Streamflow Simulations under Climate and Anthropogenic Changes Exemplified in Two Indian River Basins

This study aims to evaluate the climate- and human-induced impacts on two contrasting river basins in India, specifically, the Ganges and the Godavari. Monthly discharge simulations from global hydrological models (GHMs), run with and without human influence using CMIP5 projections under the framework of the Inter-Sectoral Impact Model Intercomparison Project, are utilized to address the scientific questions related to the quantification of the future impacts of climate change and the historical impacts of human activities on these river basins. The five state-of-the-art GHMs were considered and subsequently used to evaluate the human and climate change impacts on river discharges (seasonal mean discharge and extreme flows) during the pre-monsoon, monsoon, and post-monsoon seasons under the RCP2.6 and RCP8.5 emission scenarios. Results showed that human impacts during the baseline period on long-term seasonal discharge in the Ganges and Godavari River basins for the pre-monsoon season are around 40% and 23%, respectively, and these impacts are stronger than the future climate change impact in the pre-monsoon season for the Ganges basin, whereas, for the Godavari basin, the same pattern is observed with some exceptions. The human impact in the course of the historical period on the pre-monsoon flows of both the Ganges and the Godavari are more significant than on the monsoon and post-monsoon flows. In the near future (2010–39) time slice, the impact of climate change on the streamflow of the Ganges is highest for the post-monsoon season (13.4%) under RCP 8.5 as compared to other seasons. For Godavari, in the near-future period, this impact is highest for the pre-monsoon season (18.2%) under RCP 2.6. Climate-induced changes in both of the basins during both the monsoon and post-monsoon seasons is observed to have a higher impact on future flows than direct human impact-induced changes to flow during the current period. High flows (31.4% and 19.9%) and low flows (51.2% and 36.8%) gain greater influence due to anthropogenic actions in the time of the pre-monsoon season compared to other times of year for the Ganges and Godavari basins, respectively. High flows for the Ganges during the near future time slice are most affected in the monsoon season (15.8%) under RCP 8.5 and, in the case of the Godavari, in the pre-monsoon season (18.4%) under the RCP 2.6 scenario. Low flows of the Ganges during the near-future period are most affected during the monsoon season (22.3%) and for the Godavari, low flows are affected most for the post-monsoon season (22.1%) under RCP 2.6. Uncertainty in the streamflow estimates is more pronounced for the Godavari basin compared to the Ganges basin. The findings of this study enhance our understanding of the natural and human-influenced flow regimes in these river basins, which helps the formation of future strategies, especially for inter-state and transboundary river management.

Landscape Evolution as a Diversification Driver in Freshwater Fishes

The exceptional concentration of vertebrate diversity in continental freshwaters has been termed the “freshwater fish paradox,” with > 15,000 fish species representing more than 20% of all vertebrate species compressed into tiny fractions of the Earth’s land surface area (<0.5%) or total aquatic habitat volume (<0.001%). This study asks if the fish species richness of the world’s river basins is explainable in terms of river captures using topographic metrics as proxies. The River Capture Hypothesis posits that drainage-network rearrangements have accelerated biotic diversification through their combined effects on dispersal, speciation, and extinction. Yet rates of river capture are poorly constrained at the basin scale worldwide. Here we assess correlations between fish species density (data for 14,953 obligate freshwater fish species) and basin-wide metrics of landscape evolution (data for 3,119 river basins), including: topography (elevation, average relief, slope, drainage area) and climate (average rainfall and air temperature). We assess the results in the context of both static landscapes (e.g., species-area and habitat heterogeneity relationships) and transient landscapes (e.g., river capture, tectonic activity, landscape disequilibrium). We also relax assumptions of functional neutrality of basins (tropical vs. extratropical, tectonically stable vs. active terrains). We found a disproportionate number of freshwater species in large, lowland river basins of tropical South America, Africa, and Southeast Asia, under predictable conditions of large geographic area, tropical climate, low topographic relief, and high habitat volume (i.e., high rainfall rates). However, our results show that these conditions are only necessary, but not fully sufficient, to explain the basins with the highest diversity. Basins with highest diversity are all located on tectonically stable regions, places where river capture is predicted to be most conducive to the formation of high fish species richness over evolutionary timescales. Our results are consistent with predictions of several landscape evolution models, including the River Capture Hypothesis, Mega Capture Hypothesis, and Intermediate Capture Rate Hypothesis, and support conclusions of numerical modeling studies indicating landscape transience as a mechanistic driver of net diversification in riverine and riparian organisms with widespread continental distributions.

Comparison of Crop Evapotranspiration and Water Productivity of Typical Delta Irrigation Areas in Aral Sea Basin

The intensity of agricultural activities and the characteristics of water consumption affect the hydrological processes of inland river basins in Central Asia. The crop water requirements and water productivity are different between the Amu Darya and Syr Darya river basins due to the different water resource development and utilization policies of Uzbekistan and Kazakhstan, which have resulted in more severe agricultural water consumption of the Amu Darya delta than the Syr Darya delta, and the differences in the surface runoff are injected into the Aral Sea. To reveal the difference in water resource dissipation, water productivity, and its influencing factors between the two basins, this study selected the irrigation areas of Amu Darya delta (IAAD) and Syr Darya delta (IASD) as typical examples; the actual evapotranspiration (ETa) was retrieved by using the modified surface energy balance algorithm for land model (SEBAL) based on high spatial resolution Landsat images from 2000 to 2020. Land use and cover change (LUCC) and streamflow data were obtained to analyze the reasons for the spatio-temporal heterogeneity of regional ETa. The water productivity of typical crops in two irrigation areas was compared and combined with statistical data. The results indicate that: (1) the ETa simulated by the SEBAL model matched the crop evapotranspiration (ETc) calculated by the Penman–Monteith method and ground-measured data well, with all the correlation coefficients higher than 0.7. (2) In IAAD, the average ETa was 1150 mm, and the ETa had shown a decreasing trend; for the IASD, the average ETa was 800 mm. The ETa showed an increasing trend with low stability due to a large amount of developable cultivated land. The change of cultivated land dominated the spatio-temporal characteristics of ETa in the two irrigation areas (3). Combined with high spatial resolution ETa inversion results, the water productivity of cotton and rice in IAAD was significantly lower than in IASD, and wheat was not significantly different, but all were far lower than the international average. This study can provide useful information for agricultural water management in the Aral Sea region.

Influences of Shifted Vegetation Phenology on Runoff Across a Hydroclimatic Gradient

Climate warming has changed vegetation phenology, and the phenology-associated impacts on terrestrial water fluxes remain largely unquantified. The impacts are linked to plant adjustments and responses to climate change and can be different in different hydroclimatic regions. Based on remote sensing data and observed river runoff of hydrological station from six river basins across a hydroclimatic gradient from northeast to southwest in China, the relative contributions of the vegetation (including spring and autumn phenology, growing season length (GSL), and gross primary productivity) and climatic factors affecting the river runoffs over 1982–2015 were investigated by applying gray relational analysis (GRA). We found that the average GSLs in humid regions (190–241 days) were longer than that in semi-humid regions (186–192 days), and the average GSLs were consistently extended by 4.8–13.9 days in 1982–2015 period in six river basins. The extensions were mainly linked to the delayed autumn phenology in the humid regions and to advanced spring phenology in the semi-humid regions. Across all river basins, the GRA results showed that precipitation (r = 0.74) and soil moisture (r = 0.73) determine the river runoffs, and the vegetation factors (VFs) especially the vegetation phenology also affected the river runoffs (spring phenology: r = 0.66; GSL: r = 0.61; autumn phenology: r = 0.59), even larger than the contribution from temperature (r = 0.57), but its relative importance is climatic region-dependent. Interestingly, the spring phenology is the main VF in the humid region for runoffs reduction, while both spring and autumn growth phenology are the main VFs in the semi-humid region, because large autumn phenology delay and less water supply capacity in spring amplify the effect of advanced spring phenology. This article reveals diverse linkages between climatic and VFs, and runoff in different hydroclimatic regions, and provides insights that vegetation phenology influences the ecohydrology process largely depending on the local hydroclimatic conditions, which improve our understanding of terrestrial hydrological responses to climate change.