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.

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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.

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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.

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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.@en

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.

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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.

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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.@en

Geomorphic classification of large rivers identifies morphological patterns, as a foundation for estimating biogeochemical and ecological processes. In order to support the modelling of in-channel nutrient retention or export, the classification of geomorphic units (GUs) was done in the Padma River, Bangladesh, a large and geomorphically-complex lowland river. GUs were classified using the normalized difference vegetation index (NDVI) four times over a year, so as to cover the seasonal variation of water flows. GUs were categorized as primary and secondary channels (C & S); longitudinal bar (L); transverse bar (T); side bar (SB); unvegetated bank (EK); dry channel (ED); island (VI); and water depression (WD). All types of GUs were observed over the four distinct annual seasons, except ED, which was absent during the high flow, monsoon season. Seasonal variation of the surface area of GUs and discharge showed an inverse relation between discharge and exposed surface areas of VI, L, T, and SB. Nutrients mainly enter the river system through water and sediments, and during monsoon, the maximum portion of emergent GUs were submerged. Based on the assumption that nutrient retention is enhanced in the seasonally inundated portions of GUs, nutrient retention-/export-relevant geomorphic units (NREGUs) were identified. Seasonal variation in the area of NREGUs was similar to that of GUs. The mean NDVI values of the main identified NREGUs were different. The variation of NDVI values among seasons in these NREGUs resulted from changes of vegetation cover and type. The variation also occurred due to alteration of the surface area of GUs in different seasons. The changes of vegetation cover indicated by NDVI values across seasons are likely important drivers for biogeochemical and ecological processes.

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The Upper Indus Basin (UIB) heavily depends on its frozen water resources, and an accelerated melt due to the projected climate change may significantly alter future water availability. The future hydro-climatic regime and water availability of the Hunza basin (a sub-basin of UIB) were analysed using the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections. A data and parameter parsimonious precipitation-runoff model, the Distance Distribution Dynamics (DDD) model, was used with energy balance-based subroutines for snowmelt, glacier melt and evapotranspiration. The DDD model was set up for baseline (1991–2010), mid-century (2041–2060) and end-century (2081–2100) climates projections from two global circulation models (GCM), namely EC-Earth3 and MPI-ESM. The projections indicate a substantial increase in temperature (1.1–8.6 °C) and precipitation (12–32%) throughout the twenty-first century. The simulations show the future flow increase between 23–126% and the future glacier melt increase between 30–265%, depending on the scenarios and GCMs used. Moreover, the simulations suggest an increasing glacier melt contribution from all elevations with a significant increase from the higher elevations. The findings provide a basis for planning and modifying reservoir operation strategies with respect to hydropower generation, irrigation withdrawals, flood control, and drought management.

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Rainwater harvesting systems (RWHs) are implemented globally to bridge the frequent water supply-demand gaps. This study explores, through farmer household surveys (n = 492), how farmers perceived the benefits of RWHs, the equitability of benefits, and the role of contextual and psychological factors towards the behaviour of maintaining such systems. The study is carried out in a semi-arid catchment in the Indian state of Gujarat where RWHs, in the form of Check dams (CDs), have been implemented extensively. Results show that the benefits of CDs are perceived in good rainfall years through enhanced availability of water for expanding crops and irrigated areas. Farmers reported limited benefits of CDs in dry years. This is because of limited runoff and no carryover of stored groundwater, due to underlying shallow hard rock aquifer with little primary porosity, from wet years to dry years. Overall, ∼ 40%–50% of sampled farmers reported no benefits from CDs and the benefits decreased with distance. This reflects a spatially inequitable distribution of benefits skewed towards the farmers nearest to the CDs. The sustainability of CDs is a challenge with already ∼40% of CDs reportedly not working and 72.8% of farmers reported doing no maintenance activity. This is because 91.2% of farmers reported playing no role in its construction. The results show contextual (participation during construction, economic indicators) and sociopsychological factors (attention to CD condition, maintenance effort) significantly affect the behaviour towards maintaining the CDs. This highlights the need to complement RWHs with wider drought management and water demand management interventions to achieve drought resilience, and adherence to project exit protocols to secure the sustainability of investments.@en

Environmental flow (eflow) reference values play a key role in environmental water science and practice. In Mexico, eflow assessments are set by a norm in which the frequency of occurrence is the managing factor to integrate inter-annual and seasonal flow variability components into environmental water reserves. However, the frequency parameters have been used indistinctively between streamflow types. In this study, flow variability contributions in 40 rivers were evaluated based on hydrology, climate, and geography. Multivariate assessments were conducted based on a standardized contribution index for the river types grouping (principal components) and significant differences (one-way PERMANOVA). Eflow requirements for water allocation were calculated for different management objectives according to the frequency-of-occurrence baseline and an adjustment to reflect the differences between river types. Results reveal that there are significant differences in the flow variability between hydrological conditions and streamflow types (p-values < 0.05). The performance assessment reveals that the new frequency of occurrence delivers climate-smart reference values at least at an acceptable level (for 85–87% of the cases, r2 ≥ 0.8, slope ≤ 3.1), strengthening eflow assessments and implementations. @en

Intensive groundwater exploitation has depleted groundwater storage and led to a series of geo-environmental problems in Beijing Plain, China. Managed Aquifer Recharge (MAR) has been endorsed to mitigate the groundwater storage depletion and achieve groundwater sustainability. A pilot MAR has been tested in the Chaobai River catchment since 2015. An innovative large-scale MAR consisting of 9 cascade terraced infiltration ponds was proposed and its effectiveness was assessed in this study using an integrated modelling approach. The integrated model coupled the regional and local transient flow and transport processes. The transient regional flow model simulated historical groundwater level declines and storage depletion in the Beijing Plain from 1995 to 2018. The coupled regional and local flow model was used to simulate the pilot MAR test in the Chaobai River from 2015 to 2018. A significant groundwater level increase was observed nearby the pilot MAR since 2015. The transport model results indicate that approximately 40% of the infiltrated water was captured by pumping wells in the No.8 well field. The models were further used to assess the long-term effects of the large-scale MAR from 2020 to 2050. The simulation results show that the groundwater system will reach a new equilibrium state under the implementation of the large-scale MAR scheme. Almost 91% of the abstracted water in the No. 8 well field will come from the MAR infiltration. The proposed large-scale MAR is very effective in restoring the depleted aquifer storage and maintaining the groundwater abstraction in the No.8 well field. However, with the increase of the groundwater level, the infiltration rate of several ponds will decrease. Therefore, it is important to maintain a dynamic balance between artificial recharge and groundwater abstraction in order to achieve a sustainable long-term MAR operation in the region.

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In many high altitude river basins, the hydro-climatic regimes and the spatial and temporal distribution of precipitation are little known, complicating efforts to quantify current and future water availability. Scarce, or non-existent, gauged observations at high altitudes coupled with complex weather systems and orographic effects further prevent a realistic and comprehensive assessment of precipitation. Quantifying the contribution from seasonal snow and glacier melt to the river runoff for a high altitude, melt dependent region is especially difficult. Global scale precipitation products, in combination with precipitation-runoff modelling may provide insights to the hydro-climatic regimes for such data scarce regions. In this study two global precipitation products; the high resolution (0.1° × 0.1°), newly developed ERA5-Land, and a coarser resolution (0.55° × 0.55°) JRA-55, are used to simulate snow/glacier melts and runoff for the Gilgit Basin, a sub-basin of the Indus. A hydrological precipitation-runoff model, the Distance Distribution Dynamics (DDD), requires minimum input data and was developed for snow dominated catchments. The mean of total annual precipitation from 1995 to 2010 data was estimated at 888 mm and 951 mm by ERA5-Land and JRA-55, respectively. The daily runoff simulation obtained a Kling Gupta efficiency (KGE) of 0.78 and 0.72 with ERA5-Land and JRA-55 based simulations, respectively. The simulated snow cover area (SCA) was validated using MODIS SCA and the results are quite promising on daily, monthly and annual scales. Our result showed an overall contribution to the river flow as about 26% from rainfall, 37–38% from snow melt, 31% from glacier melt and 5% from soil moisture. These melt simulations are in good agreement with the overall hydro-climatic regimes and seasonality of the area. The proxy energy balance approach in the DDD model, used to estimate snow melt and evapotranspiration, showed robust behaviour and potential for being employed in data poor basins.

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As part of water resources management policy, water resources projects undertake environmental flow assessments (EFA) to determine how much water should be maintained or released to the downstream part of rivers to protect the health of aquatic and riparian ecosystems and societal wellbeing. In Ethiopia, EFA is being undertaken mostly in relation to dam projects. Most of dam projects in Ethiopia consider the 95% exceedance probability flow (Q95) as acceptable for downstream releases, which does not consider the variable and dynamic nature of rivers or the impacts on societal livelihoods dependent on ecosystem services. This paper aims to explore the application of EFA in Ethiopia based on global and national experiences. The paper begins with an overview of the water resources and biodiversity that need protection; second, systematic review of the current status of application of EFA methodologies in Ethiopia; and finally, the main types of environmental flow methodologies available globally that can be utilized in different parts of the country were explored, with emphasis on projects and research endeavors. It is found that environmental flow is strongly considered in Ethiopia, which is critical as the country is a custodian to precious aquatic and riparian biodiversity resources which have national and global importance. However, it is found also that there is little research on the topic for advising appropriate EFA methodology application in Ethiopia. Thus, it is suggested a holistic approach of environmental flow assessment that can entertain all other types of methods in tropical highland rivers.

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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.

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Three alternative groundwater flow models were evaluated for Beijing Plain, China. The first model (AM1) was constructed with the “thin layer approach” in which all 9 model layers, including five aquifers separated by four aquitards, are continuously present in the same model area. The second model (AM2) was constructed with the “quasi-3D approach” in which the hydrogeological formations were classified into five aquifer units consisting of mixed permeable and semi-permeable layers at different depth ranges. The third model (AM3) was constructed with the “true layer approach” in which aquifers and aquitards were defined according to hydrostratigraphic properties, and model layers are absent in the area where corresponding hydrogeological formations intersect bedrocks. All 3 models were calibrated with the parameter optimization method under the steady state flow condition with the same hydrological stresses and observation data. All three models fit to observations well with the similar calibration criteria values. Furthermore, AIC and BIC information criteria could not distinguish three alternative models. Only KIC could identify AM3 as the best model. Major differences of the three alternative models were identified from a hydrogeological perspective. The AM1 model depicted an illusion through contour maps that groundwater was present everywhere in the deep aquifers. The model computed larger vertical leakages because more abstraction rates were assigned improperly in deep aquifers. The AM2 model was able to compute regional groundwater balances and depicted spatial groundwater level variations. However, the AM2 model computed longer groundwater travel times around the wellfield and should not be used for the delineation of the well field protection zones and contaminant transport simulation. The AM3 model could not only compute the regional groundwater balances and describe spatial groundwater distribution in deep confined aquifers, but also delineate the capture zone of the wellfield. It can therefore be used for simulating contaminant transport. Furthermore, the AM3 model is suitable to construct a coupled regional and local flow model for simulating a managed aquifer recharge scheme.

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Ethiopia depends on rain-fed agriculture with limited use of irrigation for agricultural production. More than 90% of the food supply in the country comes from low productivity rain-fed smallholder agriculture. Since the livelihoods of many farmers depend on rainfed agriculture, this paper investigates how smallholders adapt to climate variability. Dhidhessa sub-basin of the Blue Nile river basin is home to many vulnerable immigrant smallholders from other parts of Ethiopia. Our study focuses on this sub-basin to understand how crop production and patterns have depended on rainfall. Secondary data on land cover and croplands, the number of households growing crops, crop yields, crop prices and area covered by three major crops (teff, maize, and sorghum) are analyzed over a period 2000–2019 and interpreted in light of a primary household survey of 135 farmers in the basin. Results show that almost 40% of the basin is under crop cultivation, and the area under cultivation has been growing 8.6‰ per year. Irrespective of rainfall variability, the number of households practicing crop cultivation has also been growing over the years. This means that more farmers are moving into the basin to cultivate. Analysis reveals that adaptation strategies are at play. Farmer decisions to grow which crops are sensitive to rainfall and their expectations of crop prices resulting from rainfall variability. Their decisions and crop prices are endogenous to the smallholder sociohydrology of the basin, leading more farmers to grow Teff relative to other crops in years of lower rainfall. These decisions are due to the lower sensitivity of Teff prices to rainfall variability and farmers' expectations of higher Teff prices relative to other crops as rainfall decreases. Such behavior also induces climate resilience, enabling farmers to respond to climate variability rather than migrating out of the basin. Moreover, it allows more farmers to migrate in and engage in crop cultivation within the basin. Such an adaptive strategy based on past experiences offers a way forward to incorporating adaptation mechanisms in sociohydrological models to simulate and assess water futures for similar basins worldwide.@en

The Fogera Plain, Ethiopia, is affected by recurrent flooding of the Ribb and Gumara Rivers. A large dam on the Ribb River is under construction for irrigation, but also to reduce flooding. We investigated the effects of the dam on the flood regime of the floodplain wetlands using a combination of hydrodynamic and a rainfall-runoff models. The model was calibrated based on inundation maps retrieved from Landsat images. Pre- and post-dam model comparison for 10 years shows that the dam will reduce the flooding extent by 11%, as it only regulates 23.8% of the upstream watershed. The flood extent and duration necessary to maintain ecologically significant water depths (≥ 0.5 m) show no notable changes. The developed hydrologic and hydrodynamic models can be used to analyze other dam operation and climate change scenarios even though there are uncertainties related to terrain resolution and analysis of hydrological data.

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The Caucasus region is a meeting point for culture and nature, lying at the nexus of Europe, the Middle East, Central Asia, and Africa, and identified as one of 36 global biodiversity hotspots. The Republic of Georgia, the center of the Caucasus biodiversity hotspot, encompasses a geographically diverse landscape inhabited by a remarkable, endemic, and understudied flora and fauna under increasing threat from human activities. A wave of new and proposed dams for hydropower presents one of the most pressing challenges for freshwater biodiversity conservation in Georgia, a country where hydropower accounts for >90% of electricity. However, this situation remains largely unknown to the international scientific community and there is limited scientific information available about Georgia in the internationally indexed peer-reviewed literature. In this article, we describe the geography, politics, and freshwater biodiversity of rivers of Georgia, with a focus on fishes. We examine trends in hydropower development over the past century and identify four distinct periods: the pre-Soviet period (until 1921), the Soviet period (1921–1991), the 1990s immediately following Georgia's declaration of independence, and the 21st century. We explore the effects of existing and proposed dams on the connectivity of rivers of western Georgia and their potential consequences for conservation of diadromous, potamodromous, and resident fish. Using the Dendritic Connectivity Index (DCI) as an analytical lens, we found serial decreases in DCI values following different periods of hydropower development in the country. Finally, we offer four considerations for future research and conservation in light of ongoing hydropower development: i) expand biodiversity research and environmental monitoring, ii) assess and implement environmental flows for Georgian rivers, iii) implement strategic planning for new hydropower development, and iv) establish strict conservation areas for protection of endangered sturgeons.

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A coupled regional and local model is required when groundwater flow and solute transport are to be simulated in local areas of interest with a finer grid while regional aquifer boundary and major stresses should be retained with a coarser grid. The coupled model should also maintain interactions between the regional and local flow systems. In the Beijing Plain (China), assessment of managed aquifer recharge (MAR), groundwater pollution caused by rivers, capture zone of well fields, and land subsidence at the cone of depression requires a coupled regional and local model. This study evaluates three methods for coupling regional and local flow models for simulating MAR in the Chaobai River catchment in the Beijing Plain. These methods are the conventional grid refinement (CGR) method, the local grid refinement (LGR) method and the unstructured grid (USG) method. The assessment included the comparison of the complexity of the coupled model construction, the goodness of fit of the computed and observed groundwater heads, the consistency of regional and local groundwater budgets, and the capture zone of a well filed influenced by the MAR site. The results indicated that the CGR method based on MODFLOW-2005 is the easiest to implement the coupled model, capable of reproducing regional and local groundwater heads and budget, and already coupled with density and viscosity dependent model codes for transport simulation. However, the CGR method inherits shortcomings of finite difference grids to create multiple local models with inefficient computing efforts. The USG method based on MODFLOW-USG has the advantage of creating multi-scale models and is flexible to simulate rivers, wells, irregular boundaries, heterogeneities and the MAR site. However, it is more difficult to construct the coupled models with the unstructured grids, therefore, a good graphic user interface is necessary for efficient model construction. The LGR method based on MODFLOW-LGR can be used to create multiple local models in uniform aquifer systems. So far, little effort has been devoted to upgrade the LGR method for complex aquifer structures and develop the coupled transport models.@en