Abstract The natural flow regimes of Andean‐Amazon tributaries play a vital role in sustaining their rich biodiversity and productive local fisheries, but ongoing and proposed alteration of river flow regimes by large dams threatens to negatively impact river ecosystems. Despite its importance, our understanding of how hydrologic variability influences ecological functions in the Andean Amazon is limited, particularly in regions with scarce data. In these regions, growing research highlights the value of fishers' local ecological knowledge in addressing these gaps. This study focused on increasing our knowledge of ecohydrological relationships in the Beni River of Bolivia through the analysis of fishers' knowledge through 28 individual semi‐structured interviews. Results indicate how key species rely on hydrologic variability, connectivity, and flooding dynamics to carry out their life stages of reproductive migration and access different habitats in the floodplains. Fishers mentioned using hydrologic indicators at multiple scales to guide their fishing activity. For instance, flooding extent and duration help anticipate fish abundance in the next years; connectivity between the main channel and oxbow lakes indicates fish migration; and within‐site observations of water level on the bank, water depth, flow direction, flow velocity, and backwater effects are used to select a fishing location. In addition, the fishers described characteristics of habitat such as substrate, vegetation, and turbidity, as well as fish feeding habits and sequential migration patterns that represent valuable observations about fish ecology. The comparison with scientific information not only confirmed existing insights but also extended our understanding of ecohydrological relationships and helped explain possible causes of relevant long‐term trends. In conclusion, our findings highlight the vital role of the flooding dynamics in the fishing practice and draw attention to the potential negative impacts of hydrologic alteration on the livelihoods of fishers.

The Agricultural water interventions can trigger human-water feedback, including unintended supply demand feedback-where increased water availability drives greater water use. In the Kamadhiya catchment, India, the introduction of check dams (CDs) led to a shift toward more water-intensive crops like cotton and wheat. This study formulates and tests hypotheses to understand these dynamics using an agent-based model (ABM) that integrates a spatially explicit hydrological model with a farmer behavior module. The ABM simulates 38,447 farmers using the RANAS behavioral framework, based on household surveys and observed data. Model results confirm the hypothesized feedback: increased water from CDs led to an 11.9% rise in cotton and 36.1% in wheat areas, boosting incomes and increasing adoption of drip and borewell irrigation, particularly near CDs. While drip irrigation systems improve water efficiency and post-monsoon groundwater levels, the saved water enables further wheat expansion-triggering a second supply demand feedback loop. These changes are spatially concentrated near CDs, exacerbating within-catchment disparities. Overall, about 54% of the additional recharge is used for irrigation expansion, lowering groundwater levels by 1.0 m and reducing the net benefit of recharge interventions. These findings underscore the need to critically understand human-water feedback and value of ABM as a tool to support more informed planning by offering strategies that mitigate negative externalities.

Denitrification in large tropical river systems is likely important for nitrogen retention estimates, but is limited by the need for measurements and the ability to scale these estimates to relate seasonal changes to river geomorphology and discharge. Geomorphic units (GUs), that describe the structure of a river system based on their inundation frequency and vegetation cover, may be useful to characterise features that influence denitrification rates. In this study, we tested the hypothesis that measurements of potential denitrification rate (PDR) using denitrification enzyme assays from different GUs could be used to1) relate PDR to soil, vegetation and different land use and land-cover (LULC) types as controlling factors and 2) that these characteristics could be assessed using remote sensing data to model PDR over a large spatial scale (along a 50 km reach) for the Padma River (Bangladesh). Specifically, 245 PDR measurements were made from the four LULC types with in eight GUs during the dry/winter season 2020. Linear regression using a mixed-modelling approach showed that PDR was highly related to vegetation cover and soil moisture across all GUs. Sentinel-2 data were then used to develop relationships between the Normalised Difference Vegetation Index. (NDVI) and vegetation cover and, specifically, between Sentinel-2 band 11 and soil moisture, which also reasonably described PDR rates. We then used this satellite data to estimate reach-scale PDR in post-monsoon, dry/winter and pre-monsoon seasons. The satellite-based model showed that PDR increased in GUs from post-monsoon 2019 to pre-monsoon 2020. The vegetation islands and the bars were the most important GUs for denitrification in all seasons. The satellite-assisted approach developed in this study can be applied to the GUs in large lowland rivers where inundation occurs frequently.

Aquatic ecosystems provide valuable ecosystem services (e.g., habitat for fisheries) to surrounding communities but environmental degradation can diminish the quality of these ecosystem services. The Lake Tana basin, including the Gumara River and its associated wetlands in Ethiopia, has experienced rapid environmental change in the last several decades. Changes in the export of nutrients from the uplands might contribute to the rapid degradation of aquatic ecosystem services due to the expansion of water hyacinths and declines in fish biodiversity and yields. We estimate how human modification and climate change have impacted watershed nutrient retention from 1986 to 2020. Here we (1) examine trends in surface water chemistry, watershed land use/land cover change, and flow alterations; (2) estimate the watershed nutrient delivery ratio (NDR), a metric of watershed nutrient retention, through time; and (3) examine how fishery yields and water hyacinth infestation in Lake Tana at the outlet of the Gumara River change during a period of rapid increase in nutrient export from the Gumara River. Estimates of the surface load and export of both phosphorus (P) and nitrogen (N) from the Gumara River watershed were approximately stable between 1986 and 2009, but from 2014 to 2020 exports increased by 69 % for P and 80 % for N. Potential factors driving this rapid increase include an expansion in irrigation for agriculture, land conversion to eucalyptus plantations, decreases in dry season flow, and an increase in mean annual precipitation since 2009. In addition, the increase in nutrient export from the Gumara River watershed coincides with a near extirpation of fish in the Gumara River and a ten-fold expansion of water hyacinth downstream in Lake Tana. Human activity and hydrological alteration in the Gumara River watershed have resulted in water quality changes, declines in fish populations, and the expansion of invasive species. Long-term monitoring and watershed modeling can help inform the management of regionally important aquatic ecosystems such as the Gumara River and Lake Tana.

Study region: Upper Beles Basin, Ethiopia Focus: Data limitations significantly challenge accurate groundwater recharge estimation, especially in regions with sparse gauging stations and highly variable hydro-meteorological conditions, such as the Upper Beles Basin, Ethiopia. Using interpolated data often yields unreliable results. This study evaluates the use of remote sensing-based hydro-meteorological data to estimate spatially distributed groundwater recharge in such data-scarce regions, comparing it with point estimates derived from primary field data, using a case study of Upper Beles Basin. New hydrological insights for the region: The study employed TerraClimate and CHIRPS datasets to estimate spatially distributed recharge using the WetSpass model. Groundwater recharge was also estimated using the Water Table Fluctuation (WTF) and Chloride Mass Balance (CMB) methods, with data from 21 monitoring wells and 45 water samples. The estimated average annual recharge was 420 mm (WTF), 308 mm (CMB), and 365 mm (WetSpass). The substantial variability in point estimates reflects the basin's recharge heterogeneity, indicating the risks of relying solely on point data. A strong correlation (72 %) was found between the WTF-derived point estimates and WetSpass-generated values. Recharge variability is influenced by land use in the lowlands and by slope, soil, and rainfall in the highlands. This research demonstrates that remote sensing-based data can yield more reliable recharge estimates in regions with sparse gauging stations and highly variable hydro-meteorological conditions.

The human-water feedbacks associated with agricultural water interventions may result in unintended and adverse externalities such as the phenomenon of supply-demand feedback, i.e. of increasing water demand in response to measures that enhance water supply. By integrating a spatially explicit hydrological model with a farmer’s behavioral module, simulated using Risks-Attitudes-Norms-Abilities-Self-regulation (RANAS) behavioral theory based on household surveys and rules derived from observed data, this paper emulates the phenomenon of supply-demand feedback. The Kamadhiya catchment in India is studied, where the decisions of 38,447 farmers in response to the intensive development of check dams (CDs) are simulated. The results show that the perceived increase in water supply from CDs has led nearby farmers to increase their cotton and wheat cultivation areas by 11.9% and 36.1%, respectively. This increase in demand has nullified the expected benefits from CD recharge with approximately 54.0% of the additional recharge being used for expanding irrigation for cotton and wheat, and lowering groundwater levels by 1.0 m. These findings underscore the need to critically understand human-water feedbacks that lead to unintended consequences and inform future investments in agricultural water interventions.

The adoption of agricultural water interventions for climate change adaptation has been slow and limited despite their established efficacy and benefits. While several studies have identified socio-economic, biophysical, technological and institutional factors that influence adoption, psychological factors have often been overlooked. This study examines the socio-economic and psychological factors, using RANAS behavioral model, that influence the adoption of agricultural water interventions in the semi-arid region of Saurashtra in India. Two contrasting and dominating agricultural water interventions in the area: drip irrigation and borewells are evaluated. Despite subsidies being available for drip irrigation systems, the adoption rate remains low (~16% adopting rate) compared to borewells (~ 24.5% adoption) with no subsidies reflecting farmer’s preference for supply augmentation measures over demand management. Incorporating psychological factors in the analysis improved the explanatory power of the logistic model by almost threefold, underscoring the significance of psychological factors in explaining farmers' adoption decisions. Based on the logistic model, major factors determining farmers adoption behaviour identified are farmer’s perceived ability, risk preference and positive beliefs about the technologies along with socio-economic (e.g., land size) and biophysical factors (e.g., proximity to water). The study recommends a multi-pronged approach to increase the adoption of interventions, including augmenting subsidies with efforts on extension services, post-adoption services, training, and awareness campaigns to build farmers' capacity and raise awareness.

To cope with the groundwater depletion problem and achieve sustainable groundwater development, groundwater conservation measures and managed aquifer recharge (MAR) have been implemented worldwide. However, knowledge gaps exit how does the aquifer system respond to these interventions differently and if these interventions are adequate to lead to long-term sustainable groundwater development under future climate change. In Beijing Plain, two measures have been implemented: reduction of groundwater abstraction by substituting groundwater abstraction with transferred surface water and implementation of managed aquifer recharge (MAR) in two major rivers. This study aims to assess how do the shallow and deep aquifers respond to these measures and if these measures can lead to long-term sustainable groundwater development in Beijing Plain under future climate change. A 3-D transient groundwater flow model was calibrated and used to simulate groundwater level and budget changes from 2021 to 2050. The monthly groundwater recharge was estimated using the projected monthly precipitation from three downscaled regional climate models under two scenarios (RCP4.5 and RCP8.5). The results show that declines in groundwater head and storage can be reversed with the combined two measures, thereby contributing to achieve sustainable groundwater development. The reduction of abstractions is a deciding measure to reverse the trend of groundwater depletion, especially in the deep confined aquifers, while large scale MAR schemes can restore the cones of depressions in shallow aquifers and maintain the groundwater abstraction. Climate variation has large impacts on groundwater resources, especially, consecutive dry years can cause rapid groundwater storage depletion. The projected monthly precipitation from 2021 to 2050 is not significantly different from the past. Therefore, the projected future precipitation has minor impacts on groundwater resources in the next 30 years. The findings from the study will support the Beijing municipality to maintain the tight control on groundwater abstraction and to implement large-scale MAR schemes in two rivers. This successful example will encourage managers of other heavily exploited aquifers to take similar measures to achieve sustainable groundwater development.

Environmental flows (e-flows) aim to mitigate the threat of altered hydrological regimes in river systems and connected waterbodies and are an important component of integrated strategies to address multiple threats to freshwater biodiversity. Expanding and accelerating implementation of e-flows can support river conservation and help to restore the biodiversity and resilience of hydrologically altered and water-stressed rivers and connected freshwater ecosystems. While there have been significant developments in e-flow science, assessment, and societal acceptance, implementation of e-flows within water resource management has been slower than required and geographically uneven. This review explores critical factors that enable successful e-flow implementation and biodiversity outcomes in particular, drawing on 13 case studies and the literature. It presents e-flow implementation as an adaptive management cycle enabled by 10 factors: legislation and governance, financial and human resourcing, stakeholder engagement and co-production of knowledge, collaborative monitoring of ecological and social-economic outcomes, capacity training and research, exploration of trade-offs among water users, removing or retrofitting water infrastructure to facilitate e-flows and connectivity, and adaptation to climate change. Recognising that there may be barriers and limitations to the full and effective enablement of each factor, the authors have identified corresponding options and generalizable recommendations for actions to overcome prominent constraints, drawing on the case studies and wider literature. The urgency of addressing flow-related freshwater biodiversity loss demands collaborative networks to train and empower a new generation of e-flow practitioners equipped with the latest tools and insights to lead adaptive environmental water management globally. Mainstreaming e-flows within conservation planning, integrated water resource management, river restoration strategies, and adaptations to climate change is imperative. The policy drivers and associated funding commitments of the Kunming–Montreal Global Biodiversity Framework offer crucial opportunities to achieve the human benefits contributed by e-flows as nature-based solutions, such as flood risk management, floodplain fisheries restoration, and increased river resilience to climate change.

The present study aimed to evaluate the temporal dynamics of water stored in a reservoir using satellite remote sensing data integrated with a GIS application. The study is carried out in three reservoirs, which include Koga, Shina, and Selamko reservoirs located in the upper Blue Nile Basin. The techniques used to carry out this study have been pre and post-processing of Landsat images, modeling and identifying water pixels, evaluating reservoir capacity, and compression of results with recent bathymetric survey data. The Normalized Difference Water Index (NDWI) has been also employed to determine open water features and to improve the presence of water pixels in satellite imagery. Percentage Difference Area Index (PDAI) and Normal Difference Area Index (NDAI) techniques have been used to assess the deviation of storage area from satellite remote sensing, topo of bed elevation, and bathymetric survey. Results indicated that the Koga reservoir storage capacity has reduced from 83.10 to 81.179 Mm3, showing an annual storage loss of 0.33

Intensive groundwater exploitation has depleted groundwater storage and led to a series of geo-environmental problems in Beijing Plain, China. To cope with the groundwater depletion problem and achieve sustainable groundwater development, groundwater abstraction has been reduced and Managed Aquifer Recharge (MAR) and Environmental Flow Release (EFR) projects have been piloted and planned. To evaluate the effectiveness of the proposed measures in restoring groundwater storage depletion in Beijing Plain, a 3D transient groundwater was constructed to simulate the effects of these proposed measures regionally and locally. Results show that with the reduction of groundwater abstraction, the declining trend of groundwater level has been stopped. The implementation of MAR and EFR projects have successfully enhanced the groundwater recharge and restored the connectivity of the surface water and groundwater. Prediction model results also show that with the large-scale MAR implementation and current level of groundwater abstraction, groundwater levels and groundwater storage will slowly increase in the next 30 years. With these combined measures in Beijing Plain, sustainable development of groundwater resources is expected to be achieved in the near future.

The present investigation was carried out over a 50 km reach, the Padma River of Bangladesh, downstream of the confluence of the Ganges and Brahmaputra rivers. The study area is highly dynamic, with diverse geomorphic units, with high rates of bank erosion, and sediment abstraction. Sentinel-2 imagery (2019-2020) was processed using NDVI values to classify in-channel geomorphic units (GUs). The identified GUs were categorised as islands (human-dominated and vegetated), bars (side bar and mid bar), primary channel, secondary channels, water depressions and dry channels. Monsoonal water flow was considered an essential factor for reshaping and supplying nutrients to GUs. Based on discharge and the surface area of the identified GUs in different seasons, the dynamics of nutrient-retention-relevant geomorphic units (NRRGUs) were assessed. A field study was carried out to validate the classification of GUs and to measure the potential denitrification rate (PDR) in each type. Results of the analysis showed that changes in the surface area of GUs across seasons influence the rate of PDR significantly. Along the surface area, the number of GUs impacted PDR estimation, mainly regulated by river discharge. This type of systematic investigation of the spatial and temporal distribution of geomorphological and biogeochemical process measuring and monitoring will be useful for planning river restoration and ecosystem management programs.

Following a 2015 Memorandum of Understanding, efforts began to develop a transboundary water allocation plan in the Mara River Basin between Kenya and Tanzania. Many lessons were learned along that way, including the importance of involving basin and national water authorities in all phases of data collection, planning and decision-making; understanding existing water management structures to promote communication and cooperation within countries; and using locally collected data whenever possible. Applying these concepts to future efforts can promote, although not ensure, ownership of the process within each country, trust between countries, and productive discussions around transboundary water resources.

Many streams and rivers outside conservation areas across the Afrotropics face multiple stressors from land use change, urbanization, and excessive water withdrawals. Thus, there is a need to develop cost-effective tools for assessing and monitoring ecological changes to inform management decisions. Studies utilizing macroinvertebrate communities as indicators of the ecological condition of streams and rivers in the Afrotropics use diverse methods, including diversity, richness, biotic and multimetric indices. However, some of these indices are region- or country-specific, which limits their general use across multiple regions or countries. In this study, we address this challenge by testing and comparing the performance of diversity and richness indices (e.g., Shannon-Wiener and Simpson), regional biotic indices (the African Scoring System Version 5 [SASS5], Tanzanian River Scoring System [TARISS] and a biotic index developed for the Ethiopian highlands [ETHbios]), and a macroinvertebrate-based index of biotic integrity (M-IBI) in assessing the ecological condition of Afrotropical rivers with the transboundary Mara River, Kenya and Tanzania, as a case study. In this study, we analyzed water and habitat quality degradation caused by multiple stressors such as land use change, organic pollution and flow alteration and the corresponding responses in macroinvertebrate communities. We utilized macroinvertebrates data collected from 143 sites covering the entire gradient of the river and its major tributaries in Kenya and Tanzania. To develop the M-IBI, we used 12 metrics that describe macroinvertebrate community richness, composition, tolerance to disturbances (indicator taxa), and the composition of functional feeding groups. Although all the biotic indices were sensitive to poor water quality and human disturbance of the river, the M-IBI performed better than biotic indices (SASS5, Tanzanian River Scoring System, and Ethiopian highlands), diversity and richness indices by having a higher discriminatory ability of site categories according to different levels and types of disturbance. Diversity and richness indices performed poorly and failed to discriminate between stressor gradients in the river. This study demonstrates a need for testing and evaluating indices or protocols before adoption and use in biomonitoring streams and rivers in other countries and regions. There is an even greater need to assess the tolerance of macroinvertebrate taxa before inclusion in biotic indices for improved performance as discriminators of multiple stressors.

The Yongding River (Beijing, China) was dry most times of the year, and groundwater storage was severely depleted. To address this issue, a river rehabilitation project was initiated. A downstream environmental flow release (EFR) project from upstream reservoirs has been implemented since 2019. This study evaluated the impact of EFR by constructing transient groundwater-flow and numerical tracer transport models to simulate the hydrogeological responses to the water release events in 2019–2020. The study identified two factors that significantly influence the river leakage rate, which are operational factors (i.e., water release rate and duration) and physical factors (i.e., hydraulic properties of the riverbed, regional hydraulic gradients, and groundwater depth) that determine the maximum water availability for groundwater recharge and maximum infiltration capacity, respectively. Predictive modelling was performed to assess the long-term effects of the proposed EFR scheme from 2021 to 2050, which showed that groundwater levels along the river will increase by 10–20 m by 2050. Groundwater storage is expected to be largely recovered and groundwater/surface-water connectivity in the middle reach of the river will be restored. This restoration will not only maintain the environmental flow for the benefit of ecosystems but also enhance groundwater recharge, promoting sustainable groundwater development in the region. Overall, this study provides valuable insights into the effectiveness of the proposed EFR scheme in achieving sustainable groundwater development in the region.

In most water balance studies, basins are considered closed systems; however, interbasin groundwater flow (IGF), which is an unaccounted hydrological component in most studies, could occur at basin boundaries where there is a hydraulic gradient and appropriate permeability of the geologic formations. IGF is a complex hydrogeological process and hidden from direct observation, thus identifying and characterizing it is difficult. This study investigated IGF in the case of the contact between the Tana and Beles basins, located at the northwestern margin of the Ethiopian Highlands, using a multimethod approach: (1) morphotectonic analysis; (2) lithostratigraphy and geological structure analysis; (3) regional groundwater potentiometric-surface map; (4) presence of large-volume springs; (5) hydrochemistry and isotope tracing; and (6) water budget imbalances. Primary data (geological investigation, water point inventory, and water sampling), satellite images and gravity data, and other secondary data, were collected and analyzed. The results illustrate the extension of the fractured basaltic aquifer, high topographic contrast, and high lineament density along the boundary between the Tana and Beles basins. The connection of the hydro-stratigraphic units, fracture distribution and orientation, high hydraulic gradient, spatial distribution of high-flux springs, and water budget imbalance of Tana Basin revealed that there is IGF from Tana Basin to Beles Basin, despite poor indications from results for hydrochemistry and stable isotopes. These findings will have practical implications for groundwater and water balance studies of the two basins. The study demonstrates the importance of a multimethod approach to investigate IGF where a single approach is imprecise.

In the high altitude Hindukush Karakoram Himalaya (HKH) mountains, the complex weather system, inaccessible terrain and sparse measurements make the elevation-distributed precipitation and temperature among the most significant unknowns. The elevation-distributed snow and glacier dynamics in the HKH region are also little known, leading to serious concerns about the current and future water availability and management. The Hunza Basin in the HKH region is a scarcely monitored, and snow- and glacier-dominated part of the Upper Indus Basin (UIB). The current study investigates the elevation-distributed hydrological regime in the Hunza Basin. The Distance Distribution Dynamics (DDD) model, with a degree day and an energy balance approach for simulating glacial melt, is forced with precipitation derived from two global datasets (ERA5-Land and JRA-55). The mean annual precipitation for 1997–2010 is estimated as 947 and 1,322 mm by ERA5-Land and JRA-55, respectively. The elevation-distributed precipitation estimates showed that the basin receives more precipitation at lower elevations. The daily river flow is well simulated, with KGE ranging between 0.84 and 0.88 and NSE between 0.80 and 0.82. The flow regime in the basin is dominated by glacier melt (45%–48%), followed by snowmelt (30%–34%) and rainfall (21%–23%). The simulated snow cover area (SCA) is in good agreement with the MODIS satellite-derived SCA. The elevation-distributed glacier melt simulation suggested that the glacial melt is highest at the lower elevations, with a maximum in the elevation 3,218–3,755 masl (14%–21% of total melt). The findings improve the understanding of the local hydrology by providing helpful information about the elevation-distributed meltwater contributions, water balance and hydro-climatic regimes. The simulation showed that the DDD model reproduces the hydrological processes satisfactorily for such a data-scarce basin.

Increased variability of the water cycle manifested by climate change is a growing global threat to agriculture with strong implications for food and livelihood security. Thus, there is an urgent need for adaptation in agriculture. Agricultural water management (AWM) interventions, interventions for managing water supply and demand, are extensively promoted and implemented as adaptation measures in multiple development programs globally. Studies assessing these adaptation measures overwhelmingly focus on positive impacts, however, there is a concern that these studies may be biased towards well-managed and successful projects and often miss out on reporting negative externalities. These externalities result from coevolutionary dynamics of human–water systems as AWM interventions impact hydrological flows and their use and adoption is shaped by the societal response. We review the documented externalities of AWM interventions and present a conceptual framework classifying negative externalities linked to water and human systems into negative hydrological externalities and unexpected societal feedbacks. We show that these externalities can lead to long term unsustainable and inequitable outcomes. Understanding how the externalities lead to undesirable outcomes demands rigorous modeling of the feedbacks between human and water systems, for which we discuss the key criteria that such models should meet. Based on these criteria, we showcase that differentiated and limited inclusion of key feedbacks in current water modeling approaches (e.g. hydrological models, hydro-economic, and water resource models) is a critical limitation and bottleneck to understanding and predicting negative externalities of AWM interventions. To account for the key feedback, we find agent-based modeling (ABM) as the method that has the potential to meet the key criteria. Yet there are gaps that need to be addressed in the context of ABM as a tool to unravel the negative externalities of AWM interventions. We carry out a systemic review of ABM application to agricultural systems, capturing how it is currently being applied and identifying the knowledge gaps that need to be bridged to unravel the negative externalities of AWM interventions. We find that ABM has been extensively used to model agricultural systems and, in many cases, the resulting externalities with unsustainable and inequitable outcomes. However, gaps remain in terms of limited use of integrated surface–groundwater hydrological models, inadequate representation of farmers’ behavior with heavy reliance on rational choice or simple heuristics and ignoring heterogeneity of farmers’ characteristics within a population.