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Benthic macroinvertebrates can provide an integrated picture of environmental changes. Health of freshwaters can be assessed based on measured changes in the ecological structure of benthic macroinvertebrates. During the study period, 33 taxa were determined in Ilke Stream. As a result of principle component analysis (PCA), mainly nine components (T degrees C, EC, TDS, BOD5, NH4-N, NO2-N, NO3-N, PO4-P and CI-) account for 92% of the total variance among the water quality parameters. As a result of the UPGMA analysis, the highest similarity value was observed between the 1th and 2nd sampling points. SI, BMWP, ASPT and BBI indices were more proper than FBI index to determine the water quality of Ilke Stream. The results indicate that these indices should be adapted based on the ecological, geomorphological and environmental features of the regions.

Aim: We studied the distribution of freshwater macroinvertebrate taxa and traits to distinguish ecological gradients among the mining-controlled and natural headwaters, as well as rural and urban economic activities influences. Location: In 2016’s dry season, macroinvertebrate samples were collected at 40 locations in the Mashcon watershed, northern Peruvian Andes. Six locations were in the headwaters directly influenced by mining, eight near-pristine tributary headwaters,14 agricultural locations at midstream and 12 urban locations downstream. Methods: Eight traits (five biological and three ecological) were selected according to data availability, and modalities scores were assigned using the weighted and the dominant-trait approaches. The traits relative abundances and abiotic conditions were compared among watershed sections. The ecological interpretability of the ungrouped data was verified with a distance-based redundancy analysis. Results: The high-altitude mining section had fewer taxa types and abundance as well as distinct body forms distributions and prevalent body sizes in macroinvertebrate communities, relatable to the control of the mining headwaters. Physiological and ecological traits (respiration, mobility and attachment, food sources, feeding habits, saprobity and pH preferenda) differed among traits quantification approaches and were less informative at high altitudes. The ecological conditions from the near-pristine tributaries recovered in the vegetated midstream section, to again be affected in the downstream urban section. Main conclusions: Our results suggest the presence of ecological impairment despite the excellent physicochemical quality of the water discharged by the mine. The obtainment of autecological information at a higher taxonomic resolution, e.g. for ubiquitous taxa like Acari and Chironomidae, would be needed to advance the freshwater quality assessment of ecologically- and hydrogeochemically-complex Andean mining ecosystems. ispartof: Diversity And Distributions vol:28 issue:8 pages:1582-1596 status: accepted

Drought is one of the most devastating worldwide natural hazards that can occur in all climatic zones and cause considerable losses affecting many water-needing sectors. It is also one of the most complex and least understood hazards due to its high heterogeneity in space and variability in time. Therefore, for a proper spatial and temporal drought analysis, spatially dense and uniformly distributed ground-based precipitation data are needed. In practice, such data are generally lacking either due to missing data or to the nonuniform and scarce spatial distribution of ground stations. This gives a great potential to the Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data with a long period and high resolution for using in drought studies. The CHIRPS data also allow to tackle with the problem of sparse, unevenly distributed and erratic ground stations. Based on the CHIRPS data, the study aims to assess the drought condition over Kucuk Menderes River Basin in the western part of Turkey. The analysis was performed considering the seasonality as well as the spatial and temporal change in the drought characterization based on the Standardized Precipitation Index (SPI) calculated at 3-month (seasonal) time scale. Results showed that the CHIRPS and ground stations were highly correlated except for summer despite the overall good performance in the basin. The CHIRPS can properly capture drought characteristics. Droughts have a within-year variability in time and an insignificant variability in space over the basin while the over-year variability shows a significant decreasing trend which could be a signal for more severe droughts after being accumulated over years in the future. The study demonstrates the usefulness of CHIRPS in drought analysis due to the fact that ground-based data are still not at a level dense and long enough to understand the process precisely both in time and space.

Functional diversity (FD) is useful for the evaluation of freshwater ecosystems. The FD of macroinvertebrate families for river water quality (WQ) assessment in the Paute River Basin (PRB), Ecuador, was investigated. Macroinvertebrate samples and data about 26 physical, chemical, microbiological and hydro-geomorphological variables were available. Literature-based biological traits were allocated as scores to the macroinvertebrates data through fuzzy coding. The Generalised Additive Mixed Model (GAMM) was used to assess the performance of six FD indices using the referred 26 WQ descriptive variables. The best performing GAMM led to selecting the index based on functional dendrograms including the species community pool (wFDc) as the most suitable to characterise FD in the PRB. The sub-basins of the PRB were grouped in three classes applying Average Linkage Clustering (ALC) and using wFDc. The Random Forest (RF) algorithm was used with a global efficiency of 89% to assess the ALC clusters consistency and pre-identify the significant WQ descriptive variables, explaining most of the FD variability. The Kruskal-Wallis test was then applied to refine the outcomes of the previous analysis. Twelve WQ descriptive variables were finally identified as the best discriminant predictors for FD, including the riparian vegetation, electric conductivity, dissolved oxygen, total hardness, faecal coliforms and pH. It is believed that the implemented approach successfully assessed the stream WQ status of the PRB upon selecting a suitable macroinvertebrate FD index; as such, it could be applied to other tropical basins for WQ assessment.

Thus far, reanalysis-based meteorological products have drawn little attention to the influence of meteorological elements of products on hydrological modeling. This study aims to evaluate the hydrological application potential of the precipitation, temperature, and solar radiation of the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR) in an alpine basin. The precipitation, temperature, and solar radiation of the gauge-observed meteorological dataset (GD), CFSR, and CMADS were cross-combined, and 20 scenarios were constructed to drive the SWAT model. From the comprehensive comparisons of all scenarios, we drew the following conclusions: (1) among the three meteorological elements, precipitation has the greatest impact on the simulation results, and using GD precipitation from sparse stations yielded better performance than CMADS and CFSR; (2) although the SWAT modeling driven by CMADS and CFSR performed poorly, with CMADS underestimation and CFSR overestimation, the temperature and solar radiation of CMADS and CFSR can be an alternative data source for streamflow simulation; (3) models using GD precipitation, CFSR temperature, and CFSR solar radiation as input yielded the best performance in streamflow simulation, suggesting that these data sources can be applied to this data-scarce alpine region.

Water is one of the fundamental resources of economic prosperity, food security, human habitats, and the driver of many global phenomena, such as droughts, floods, contaminated water, disease, poverty, and hunger. Therefore, its deterioration and its inadequate use lead to heavy impacts on environmental resources and humans. Thus, we argue that to address these challenges, one can rely on hydrological management strategies. The objective of this study is to simulate and quantify water balance components based on a hydrologic model with available data at the R’Dom watershed in Morocco. For this purpose, the hydrologic model used is the Soil and Water Assessment Tool + (SWAT+) model. The streamflow model simulations were run at the monthly time step (from 2002 to 2016), during the calibration period 2002–2009, the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) values were 0.84 and 0.70, respectively, and 0.81 and 0.65, respectively, during the validation period 2010–2016. The results of the water balance modeling in the watershed during the validation period revealed that the average annual precipitation was about 484 mm, and out of this, 5.75 mm came from the development of irrigation in agricultural lands. The evapotranspiration accounted for about 72.28% of the input water of the watershed, while surface runoff (surq_gen) accounted for 12.04%, 11.90% was lost by lateral flow (latq), and 4.14% was lost by groundwater recharge (perco). Our approach is designed to capture a real image of a case study; zooming into other case studies with similar environments to uncover the situation of water resources is highly recommended. Moreover, the outcomes of this study will be helpful for policy and decision-makers, and it can be a good path for researchers for further directions based on the SWAT model to simulate water balance to achieve adequate management of water resources.

Genera and species of Elmidae (riffle beetles) are sensitive to water pollution; however, in tropical freshwater ecosystems, their requirements regarding environmental factors need to be investigated. Species distribution models (SDMs) were established for five elmid genera in the Paute river basin (southern Ecuador) using the Random Forest (RF) algorithm considering environmental variables, i.e., meteorology, land use, hydrology, and topography. Each RF-based model was trained and optimised using cross-validation. Environmental variables that explained most of the Elmidae spatial variability were land use (i.e., riparian vegetation alteration and presence/absence of canopy), precipitation, and topography, mainly elevation and slope. The highest probability of occurrence for elmids genera was predicted in streams located within well-preserved zones. Moreover, specific ecological niches were spatially predicted for each genus. Macrelmis was predicted in the lower and forested areas, with high precipitation levels, towards the Amazon basin. Austrelmis was predicted to be in the upper parts of the basin, i.e., páramo ecosystems, with an excellent level of conservation of their riparian ecosystems. Austrolimnius and Heterelmis were also predicted in the upper parts of the basin but in more widespread elevation ranges, in the Heterelmis case, and even in some areas with a medium level of anthropisation. Neoelmis was predicted to be in the mid-region of the study basin in high altitudinal streams with a high degree of meandering. The main findings of this research are likely to contribute significantly to local conservation and restoration efforts being implemented in the study basin and could be extrapolated to similar eco-hydrological systems.

ispartof: HYDROBIOLOGIA vol:849 issue:8 pages:1743-1762 status: published

STUDY REGION: Nile basin. STUDY FOCUS: Several studies have shown a relationship between climate change and changes in sediment yield. However, there are limited modeling applications that study this relationship at regional scales mainly due to data availability and computational cost. This study proposes a methodological framework using the SWAT+ model to predict and project sediment yield at a regional scale in data-scarce regions using global datasets. We implement a framework that (a) incorporates topographic factors from high/medium resolution DEMs (b) incorporates crop phenology data (c) introduces an areal threshold to linearize sediment yield in large model units and (d) apply a hydrological mass balance calibration. We test this methodology in the Nile Basin using a model application with (revised) and without (default) the framework under historical and future climate projections. NEW HYDROLOGICAL INSIGHTS FOR THE REGION: Results show improved sediment yield estimates in the revised model, both in absolute values and spatial distribution when compared to measured and reported estimates. The contemporary long term (1989 - 2019) annual mean sediment yield in the revised model was 1.79 t ha-1 yr-1 and projected to increase by 61 % (44 % more than the default estimates) in the future period (2071 - 2100), with the greatest sediment yield increase in the eastern part of the basin. Thus, the proposed framework improves and influences modeled and predicted sediment yield respectively. ispartof: JOURNAL OF HYDROLOGY-REGIONAL STUDIES vol:42 ispartof: location:Netherlands status: published

In response to the rising climatic impacts on worldwide urbanized deltas, the Netherlands has strategically and politically framed Dutch water management as a global water solution for improving water safety and flood protection in other countries such as Vietnam. Being renowned for its water management approach, the Netherlands is particularly active in sharing water knowledge, insights, and policies internationally. This paper connects a framing perspective to policy translation studies to understand the role of language and meaning-making in the cross-border travel of policies. Adopting a framing perspective, it presents four dimensions of water policy translation concerning how policy frames are being created and interpreted - during the cross-border travel. The paper follows the process of the Dutch water management approach being 'packaged' as global water solutions and 'translated' to inform the development of the Vietnamese Mekong Delta Plan of 2013. The results show that although similar concepts, metaphors and narratives could be witnessed in this translation process, the local use and interpretation of these concepts remain challenging. Inclusive engagement, shared and comprehensive understanding, and continuous exchange and learning processes could help to improve cross-border policy-making for sustainable delta management.

Drought is a temporal decrease in water availability and occurs in all climatic regions. Droughts propagate through the hydrological cycle, e.g., meteorological drought propagates to groundwater recharge drought. This research investigated drought propagation in the hydrological cycle in a semiarid context. Meteorological drought severity was determined using a standardized precipitation index (SPI). A variable threshold method and standardized groundwater index (SGI) was implemented to investigate groundwater recharge drought. Comparing meteorological drought (SPI) and groundwater drought (SGI) helps to assess drought propagation in the hydrological cycle. For drought analysis, time-series of rainfall and groundwater recharge needs to be available with high spatial and temporal resolution. Therefore, for this study, daily rainfall measurements were collected from 11 meteorological stations, and water balance modeling was used to estimate temporally and spatially distributed groundwater recharge. This research was carried out in the Bilate River catchment in the Rift Valley basin of Ethiopia. Results show that meteorological droughts were observed before every groundwater recharge drought and they propagate to groundwater recharge drought. Furthermore, analysis of the drought propagation indicates that not all meteorological droughts are propagated. The analysis also shows that a combination of mild to severe meteorological droughts can propagate to groundwater recharge and result in a major groundwater-recharge drought event.

Increasing drought patterns with profound effects on livelihoods and food security have been documented in Ethiopia. From previous studies', assessments at various timescales, Ethiopia is regarded as a drought-prone country in East Africa. However, there is no documentation available. This paper investigates the spatiotemporal patterns of drought characteristics in 16 woredas (districts) as well as in the 14 homogeneous rainfall zones of homogeneous using monthly rainfall and temperature data over the period 1983 to 2020. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were computed using time-series meteorological data to depict the spatial extent of drought characteristics and patterns at 4- and 12-month timescales. Within the period investigated, 12-month, 2015, and 2019 recorded the most extreme countrywide drought. The most prolonged drought duration lasted for 12 months in 2015. Although Ethiopia is a drought-prone country, the frequency, magnitude, and severity vary spatially by region. In planning for future actions, particular emphasis must be paid to the northeastern, eastern, northwestern, and southeastern parts of the country, which are more vulnerable. The findings could potentially influence and redirect national drought management and disaster preparedness programs for the affected areas.

Water is one of the most important ecosystem services because it is essential for food and energy production. The Tungabhadra basin, located in peninsular India, has a variety of challenges, including inter-basin water-sharing issues, low agricultural productivity and value, and rising need for renewable energy production. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) water yield model is used to analyze the consequences of climate change on water related services such as water yield and hydropower generation in the densely populated Tungabhadra basin. The impact of climate change on water supply services is studied for the period 1971–2000 as well as the future period 2021–2040. The model is calibrated using streamflow data collected at the Bawapuram gauge station in Telangana and there is a strong correlation between observed and simulated flow. The water yield for the entire basin declined by 33 and 50% under the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios, respectively. The RCP 4.5 scenario reduces hydropower production and its Net Present Value (NPV) by 41 to 59%, whereas the RCP 8.5 scenario reduces production and NPV by 56 to 67%. The assessment of ecosystem services at the catchment scale revealed that the basin could be vulnerable to climate change due to a dramatic drop in ecosystem services. The methodology developed in this study can be applied to other river basins where quantifying ecosystem services is critical. Accepted version

Mangrove wetlands provide essential ecosystem services such as coastal protection and fisheries. Metal pollution due to industrial and agricultural activities represents an issue of growing concern for the Guayas River Basin and related mangroves in Ecuador. Fisheries and the related human consumption of mangrove crabs are in need of scientific support. In order to protect human health and aid river management, we analyzed several elements in the Guayas Estuary. Zn, Cu, Ni, Cr, As, Pb, Cd, and Hg accumulation were assessed in different compartments of the commercial red mangrove crab Ucides occidentalis (hepatopancreas, carapax, and white meat) and the environment (sediment, leaves, and water), sampled at fifteen sites over five stations. Consistent spatial distribution of metals in the Guayas estuary was found. Nickel levels in the sediment warn for ecological caution. The presence of As in the crabs generated potential concerns on the consumers' health, and a maximum intake of eight crabs per month for adults is advised. The research outcomes are of global importance for at least nine Sustainable Development Goals (SDGs). The results presented can support raising awareness about the ongoing contamination of food and their related ecosystems and the corresponding consequences for environmental and human health worldwide. ispartof: FOODS vol:10 issue:8 ispartof: location:Switzerland status: published

Social-ecological systems and governance are complex systems and crises that affect those systems are likely to be complex as well. Environmental topics are multi-faceted with respect to both structure and content. Structural complexity is about societal and institutional organization and management, whereas contentual complexity deals with environmental (or societal) analyses, knowledge, and problem-solving. Interactions between both are manifold, and it is essential they are included in decision-making. Describing these interactions results in a series of nineteen units, arranged in a matrix according to their prevailing mutual dependencies. These units show dominant processes and concepts, representative of environmental analysis. This approach, called ACCU (aggregation of concepts and complex adapted systems units), is provided with evidence through practices of, in particular, water governance.

Study area Kikuletwa catchment, Upper Pangani River Basin, Tanzania. Study focus This study compared yearly blue and green water fluxes using four different methods: Senay’s method (SN) (Senay et al., 2016), van Eekelen method (EK) (van Eekelen et al., 2015), the Budyko method (Simons et al., 2020) and the Soil Water Balance (SWB) model (FAO and IHE Delft, 2019). The yearly blue and green water fluxes of different Land Use Land Cover (LULC) classes were estimated using an ensemble of seven global remote sensing-based evapotranspiration products (Ensemble ET) and the CHIRPS rainfall dataset. The Ensemble ET was created from seven global RS-based surface energy balance models (GLEAM, CMRS-ET, SSEBop, ALEXI, SEBS, ETMonitor and MOD16). New hydrological insights Our study found that the EK method was able to map blue and green water fluxes with realistic results for irrigated and non-irrigation cultivated areas. Budyko and SWB gave too high blue water fluxes for the non-irrigated agricultural areas, whereas the Budyko and SWB models were not able to show a clear difference in blue-water fluxes in irrigated versus non-irrigated areas. On the other hand, the SN method estimated no blue water fluxes in more than half of the identified irrigated areas. Three of the four methods estimate the highest blue water fluxes (318–582 mm/y) in forested areas, while the SWB model estimates the highest blue water fluxes in irrigated banana and coffee (278 mm/y). Overall, we conclude that the EK method yielded the most realistic spatial pattern of blue-water fluxes when compared to the irrigated land use map, whereas SWB could be considered after further calibration if higher temporal data resolution (e.g. monthly) is required.

The Lake Tana Basin, comprising the largest natural lake in Ethiopia, is the source and the uppermost part of the Upper Blue Nile Basin. In this review paper, research papers, mainly on the rainfall-runoff modeling and lake water balance, and on the hydrogeology, have been reviewed. The earlier water balance estimation attempts used simple conceptual and statistical approaches and calculate on a monthly timescale. More recent research has been using advanced semi-physically or physically based distributed hydrological models. Accordingly, mean annual precipitation over the lake was estimated in the range 36.1–53.1%; lake evaporation at 45.3–57.5%; river inflow (all gauged and estimated ungauged) at 43.6–63.9%; and river (lake) water outflow at 0–9.2%. With the few isotope studies, groundwater inflow and outflow are found insignificant. Different studies had estimated groundwater recharge, ranging from 57 mm to 850 mm. The basin has a heterogenous aquifer system consisting of different volcanic rocks and alluvio-lacustrine sediments. Generally, groundwater with low TDS, Ca–Mg–HCO3 type, isotopically relatively enriched, and high TDS, Na–HCO3 type, isotopically relatively depleted, water types have been identified. In this paper, major research gaps such as aquifer hydraulic characterization, surface-groundwater interaction, groundwater flow and groundwater balance have been identified. Hence, future research shall focus on the groundwater resources, so that existing surface water studies are updated and future water usage options are explored.

© 2019 Elsevier Ltd The application of remote sensing techniques for WP ET mapping in data scarce regions is gaining more recognition since it can cover large areas with minimal field observations. Important concerns are the generation of high-resolution WP ET maps and addressing the question on how accurate the results are. This study aims at high resolution (10 m) mapping and evaluation of the spatial variability of biomass, yield, ET and WP ET in the Makanya river catchment using the automated Surface Energy Balance Algorithm for Land (pySEBAL) with SENTINEL-2 and LANDSAT-8 images, local land use map and locally calibrated leaf area index (LAI) inputs. A coupled phenological variability and supervised classification approach on high resolution images generated a high accuracy LULC layer which was used to map the WP ET in the agricultural lands. The pySEBAL results were evaluated in view of local information on crop yields, water allocation and agricultural management practices in the different agro-ecological zones within the catchment. Calibration of high-resolution satellite LAI generated products with error estimates within acceptable levels of uncertainty. The simulated crop yields were in agreement with reported crop yields. The results showed relatively high WP ET in the highlands and low WP ET in the midland and lowland areas of the catchment. The latter was attributed to high transmission losses, low irrigation efficiencies, poor agricultural practices and pest/disease attack. When applying SEBAL in African cultivated catchments, it is highly recommended to use SENTINEL-2 data in addition to LANDSAT-8, and to use local information, especially for the ground truthing of land use maps, phenology, crop practices and crop yields. ispartof: PHYSICS AND CHEMISTRY OF THE EARTH vol:112 pages:36-49 ispartof: location:NAMIBIA, Swakopmund status: published

The river flow regime and water resources are highly important for economic growths, flood security, and ecosystem dynamics in the Mekong basin – an important transboundary river basin in South East Asia. The river flow, although remains relatively unregulated, is expected to be increasingly perturbed by climate change and rapidly accelerating socioeconomic developments. Current understanding about hydrological changes under the combined impacts of these drivers, however, remains limited. This study presents projected hydrological changes caused by multiple drivers, namely climate change, large-scale hydropower developments, and irrigated land expansions by 2050s. We found that the future flow regime is highly susceptible to all considered drivers, shown by substantial changes in both annual and seasonal flow distribution. While hydropower developments exhibit limited impacts on annual total flows, climate change and irrigation expansions cause changes of +15% and −3% in annual flows, respectively. However, hydropower developments show the largest seasonal impacts characterized by higher dry season flows (up to +70%) and lower wet season flows (−15%). These strong seasonal impacts tend to outplay those of the other drivers, resulting in the overall hydrological change pattern of strong increases of the dry season flow (up to +160%); flow reduction in the first half of the wet season (up to −25%); and slight flow increase in the second half of the wet season (up to 40%). Furthermore, the cumulative impacts of all drivers cause substantial flow reductions during the early wet season (up to −25% in July), posing challenges for crop production and saltwater intrusion in the downstream Mekong Delta. Substantial flow changes and their consequences require careful considerations of future development activities, as well as timely adaptation to future changes.

Lakeshore wetlands are thought to be hot spots for biogeochemical processes. However, many lakeshore wetlands have been hydrologically disconnected from the associated lake by levees that have altered the ecosystem services they provide. Lakeshore restoration projects have been undertaken to recover the hydrological connection; however, the effects of the various restoration practices on biogeochemical cycling remain unclear. Here, we compared variation in sediment nitrogen (N) cycling rates to assess the restoration benefits of N removal in a series of recently hydrologically restored lakeshore wetlands, including ponds and bottomlands, of Lake Dianchi, China. The results showed that nitrification rates were generally higher in the ponds, while denitrification rates were higher in the bottomlands. Hydrological reconnection stimulated the development of several sediment properties critical for N cycling rates in the ponds, including increases in sediment carbon (C) and N contents; however, bottomland reconnection increased sediment moisture and decreased sediment C and N contents likely due to erosion by wind-induced wave action. Correspondingly, hydrological reconnection significantly increased the sediment N cycling rates in ponds but decreased the sediment N cycling rates in bottomlands over time. Path analyses revealed that substrate characteristics, including moisture and C and N availability, were the critical drivers regulating wetland N cycling rates. These results imply that the restoration targets could not be met simply by hydrological reconnection. Future wetland restoration requires further understanding of the relationship between changes in sediment properties and biogeochemical processes.

Integrated modeling is a critical tool to evaluate the behavior of coupled human–freshwater systems. However, models that do not consider both fast and slow processes may not accurately reflect the feedbacks that define complex systems. We evaluated current coupled human–freshwater system modeling approaches in the literature with a focus on categorizing feedback loops as including economic and/or socio-cultural processes and identifying the simulation of fast and slow processes in human and biophysical systems. Fast human and fast biophysical processes are well represented in the literature, but very few studies incorporate slow human and slow biophysical system processes. Challenges in simulating coupled human–freshwater systems can be overcome by quantifying various monetary and non-monetary ecosystem values and by using data aggregation techniques. Studies that incorporate both fast and slow processes have the potential to improve complex system understanding and inform more sustainable decision-making that targets effective leverage points for system change. Electronic supplementary material The online version of this article (10.1007/s13280-018-1136-6) contains supplementary material, which is available to authorized users.

The Lower Mekong River basin (LMB) has experienced droughts in recent decades, causing detrimental economic losses and food security conundrums. This study quantified the impact of climate change on drought, and rainfed rice production in the LMB. The Soil and Water Assessment Tool (SWAT) and AquaCrop models were used to evaluate long-term drought indices and rainfed rice yields under historical and future climate conditions (1954–2099) with four climate models and two emission scenarios (RCP 4.5 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We found that rice yield might increase (24–43%) due to the elevated levels of atmospheric CO2 concentration (+ 34.3 to + 121.9%) and increases in precipitation. Contrastingly, considerable decreases in rice yield up to 1.5 ton/ha in the Vietnam Central High Plain (VCHP) region could be expected resulting from reduced precipitation by about 34% during drought years. To avert any major food crisis, an expansion of irrigation areas could be required to compensate for the expected reduction in rice yields. We conclude that a framework combining hydrology and crop models to assess climate change impacts on food production is key to develop adaptation strategies in the future.

In tropical small islands the application of hydrological modelling is challenged by the scarcity of input data. Using in-situ and statistically estimated data, a hydrological model was calibrated and validated for the Upper Navet watershed in Trinidad, a small Caribbean island. The model was built using the soil water assessment tool (SWAT). The sensitivity analysis, calibration and validation were performed in SWAT calibration and uncertainty program (SWAT-CUP) using sequential uncertainty fitting (SUFI-2). The results revealed that for the estimated volume of water flowing into the reservoir (Flow_In) there were six sensitive parameters. To estimate the reservoir volume (Res_Vol), a modification of only the effective hydraulic conductivity was required. The model’s performance for the Flow_In validation showed acceptable values (R2 = 0.91 and NSE = 0.81). The uncertainty analysis indicated lower than recommended values for both the R-factor (0.46) and P-factor (0.31). For Res_Vol, the model’s validation performance indicated acceptable values (R2 = 0.72 and NSE = 0.70) and the P- and R-factors were 0.80 and 0.64, respectively. Based on the statistical metrics, the uncertainty for the Res_Vol was regarded as reasonable. However, care must be taken with the model’s use in the dry season, as the simulated Flow_In was generally over-predicted. A second validation of the model was performed for the reservoir under different negative (removal) and positive (addition) water amounts which confirmed the model’s ability to estimate the Res_Vol. The hydrological model established can therefore serve as a useful tool for water managers for the estimation of the Res_Vol at the Navet reservoir.

This study aims to estimate the short and long-term drought periodicities, and trend component using the continuous wavelet transforms. The applied approach introduces a new concept, the maxima line, which defines the most dominant component affecting the trend in Standardized Precipitation Index (SPI) time series. The analysis of the short and long-term drought cycles was performed with data from 15 stations located in Gediz Basin, at western part of Turkey, obtained during the recording period of 1960–2016. The change point in the SPI time series was determined graphically via the continuous wavelet power spectrum, and the obtained results were verified with Pettitt's test. The significant change points, in the northwest, east and southwest part of the basin, occurred by the beginning of 1980s, by the end of 1980s, and by the mid of 1990s, respectively. The most dominating periodicities affecting the trend were varying between 24 and 48 months for the short-term drought cycles, whereas they were varying between 96 and 162 months for the long-term drought cycles.

ispartof: INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION vol:109 status: published

The generation of hydrological data for accurate flood predictions requires robust and, ideally, dense monitoring systems. This requirement is challenging in locations such as the Himalayas, which are characterised by unpredictable hydroclimatic behaviour with dramatic small‐scale spatial and temporal variability. River level monitoring sensors that are affordable and easy‐to‐operate could support flood risk management activities in the region. We therefore identify potential for a local participatory monitoring network that also serve to overcome existing data gaps, which represent the main bottleneck for establishing an effective community‐based flood early‐warning system. We have applied a citizen science‐based hydrological monitoring approach in which we tested low‐cost river level sensors. Initial results, collected over summer 2017 from two stations on the River Karnali, suggest that our system can successfully be operated by non‐scientists, producing river level data that match those obtained from an adjacent government‐operated high‐tech radar sensor. We discuss potential opportunities to integrate these low‐cost sensors into existing hydrological monitoring practice. Combined with an adaptive, community‐led approach to resilience building, we argue that our low‐cost sensing technology has the potential not only to increase spatial network coverage in data‐scarce regions, but also to empower and educate local stakeholders to build flood resilience.

Lake Tana is the most important freshwater lake in Ethiopia. Besides pressures on water quality resulting from urbanization and deforestation, the invasion of the exotic water hyacinth (Eichhornia crassipes) poses new threats to the ecosystem. Water hyacinth, endemic to South America, is widely considered as the world's worst aquatic invasive weed. In 2011, the weed appeared on the northern shores of Lake Tana, expanding in south-eastern direction. The lake area affected by water hyacinth was last estimated in 2015 at 34,500 ha, which equals 16% of the total lake surface. In this research, the benefits of water hyacinth control and eradication for the rural population inhabiting the northern and northeastern villages bordering Lake Tana, are investigated. In the area, the population largely depends on farming and fishing. An assessment of the total economic benefit of eradication was conducted. The stakeholder-centered approach led to measuring the willingness to contribute in labor and cash terms. Results showed smallholders in the study are willing to contribute over half-a-million euros annually. Costs of management actions can be weighed to the benefits, where further research is needed on the impact on other stakeholder groups. Moreover, wetland management should advance to explore multiple pathways in an integrated approach: water hyacinth control, water hyacinth utilization and sustainable waste water management. (C) 2020 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved. The authors would like to thank the VLIR-UOS project for funding this research through Bahir Dar University-Institutional University Cooperation (BDU-IUC) program. Moreover, the authors acknowledge the financial support of the UNESCO MAB Programme and the Belgian Science Policy, within the frame of the EVAMAB project. This manuscript is one of the outputs of Work Packages B and D of the EVAMAB Project (Economic valuation of ecosystem services in Biosphere Reserves: testing effective rapid assessment methods in selected African Biosphere Reserves). The lead author, Van Oijstaeijen W., has received financial support for the research stay in the form of a VLIR-UOS Travel Grant and obtained a PhD fellowship strategic basic research by FWO under contract No 1S46420N. The authors would like to thank the associate editor and the reviewers for their thorough reviews and constructive feedback. Van Oijstaeijen, W (corresponding author), Univ Antwerp, Dept Engn Management, Antwerp, Belgium. wito.vanoijstaeijen@uantwerpen.be

The Amazon Basin is an unquestionable biodiversity hotspot, containing the highest freshwater biodiversity on earth and facing off a recent increase in anthropogenic threats. The current knowledge on the spatial distribution of the freshwater fish species is greatly deficient in this basin, preventing a comprehensive understanding of this hyper-diverse ecosystem as a whole. Filling this gap was the priority of a transnational collaborative project, i.e. the AmazonFish project - https://www.amazon-fish.com/. Relying on the outputs of this project, we provide the most complete fish species distribution records covering the whole Amazon drainage. The database, including 2,406 validated freshwater native fish species, 232,936 georeferenced records, results from an extensive survey of species distribution including 590 different sources (e.g. published articles, grey literature, online biodiversity databases and scientific collections from museums and universities worldwide) and field expeditions conducted during the project. This database, delivered at both georeferenced localities (21,500 localities) and sub-drainages grains (144 units), represents a highly valuable source of information for further studies on freshwater fish biodiversity, biogeography and conservation., Measurement(s)Diversity • Fish • spatial patternTechnology Type(s)digital curationFactor Type(s)geographic locationSample Characteristic - OrganismfishSample Characteristic - Environmentdrainage basinSample Characteristic - LocationAmazon Basin Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11920800

The upper Ganga Basin in Uttarakhand, India, has high hydropower potential and plays an important role in the development of the state economy. Thus, an accurate knowledge of annual water yield is of paramount importance to this region. This paper deals with use of contemporary water yield estimation models such as the distributed Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the Lumped Zhang model and their validation to identify the most suited one for water yield estimation in the upper Ganga Basin. In previous studies utilizing these models, water yield was estimated by considering a single value of some important model parameters for the entire basin, which in fact show distributed variation at a finer (pixel) scale. Therefore, in this study, pixel-level computations are performed to assess and ascertain the need for incorporating the spatial variation of such parameters in model applications. To validate the findings, the observed sub-basin discharge data are analyzed with the computed water yield for 4 decades, i.e., 1980, 1990, 2001 and 2015. The results obtained are in good agreement with the water yield obtained at the pixel scale.

Participatory modelling increases the transparency of environmental planning and management processes and enhances the mutual understanding among different parties. We present a sequential probabilistic approach to involve stakeholders' views in the formal decision support process. A continuous Bayesian Belief Network (BBN) model is used to estimate population parameters for stakeholder groups, based on samples of individual value judgements. The approach allows quantification and visualization of the variability in views among and within stakeholder groups. Discrete BBN is populated with these parameters, to summarize and visualize the information and to link it to a larger decision analytic influence diagram (ID). As part of ID, the resulting discrete BBN element serves as a distribution-form decision criteria in probabilistic evaluation of alternative management strategies, to help find a solution that represents the optimal compromise in the presence of potentially conflicting objectives. We demonstrate our idea using example data from the field of marine spatial planning. However, this approach is applicable to many types of management cases. We suggest that by advancing the mutual understanding and concrete participation this approach can further facilitate the stakeholder involvement also during the various stages of the environmental management process. (C) 2019 The Authors. Published by Elsevier B.V.

Global climate change and human activities are expected to have far-reaching implications for the associations between ecosystem services (ESs), especially in arid regions. Here, Central Asia (CA) was taken as a case study to describe the complex relationship among key ESs under the combined effects of future climate change and so cioeconomic development. We propose a new framework that integrates the future land-use simulation (FLUS) model and integrated valuation of ESs and trade-offs (InVEST) model. A four-model ensemble mean from the Coupled Model Intercomparison Project 6 (CMIP6) was chosen to project future (2021–2100) variations in water yield (WY), soil conservation (SC), carbon storage (CS) and habitat quality (HQ). Spearman correlation was adopted to analyze the trade-offs and synergies between multiple ESs. Results showed that cropland degradation (− 4.11% to − 19.93%) and urban (+33.14% to +127.96%) and forestland (+5.31% to +25.52%) expansion will be the main forms of future land-use change in CA. Compared with the reference period (1995–2015), four ESs will exhibit different decreasing trends across CA under the three scenarios. We observed that the risk of soil erosion will increase in the mountainous areas of Kyrgyzstan and Tajikistan; cropland degradation and urban expansion would lead to a sharp reduction of CS and HQ in the Amu Darya Basin, Syr Darya Basin and southern Turkmenistan, especially in SSP245 scenario. We found that the weak pairwise correlations between HQ, SC and CS will be strengthened (R = 0.22–0.58; p < 0.05) in Kyrgyzstan and Tajikistan, whereas the significant positive correlation (R = 0.47–0.60; p < 0.01) between WY and SC will be weakened. An important information/ recommendation provided by this study is that different management strategies should be designed in accor dance with the major interactions among water, soil, carbon and biodiversity services.

Optimizing a multi-reservoir system is complicated, since the operation of one reservoir depends on other reservoir and may also have conflicting multiple objectives. The conflicting purposes of a multi-reservoir system requires a systematic multi-objective study. Recently, multi-objective evolutionary algorithms (MOEAs) have been widely used for the multi-objective analysis of the reservoir systems. However, the simple MOEAs result in premature convergence and local optimal solution for complex non-linear multi-objective optimization problems. To improve the performance and maintain the diversity in the population, chaos is being combined with the evolutionary algorithms for optimizing complex problems. In the present study, the chaos algorithm is coupled with MOEAs such as non-dominated genetic algorithm-II (CNSGA-II) and multi-objective differential evolution algorithm (CMODE) to derive an optimal crop planning for a multi-reservoir system having intra-basin water transfer. The model is developed with the objective of maximizing the net benefits and maximizing the crop production, subject to various physical, land and water availability constraints. The resulted optimal policy is further assessed using a simulation model and its performance is evaluated using various statistical indices. It is found that CMODE has resulted in slightly higher net benefits of Rs. 1921.77 Million and 1201.55 thousand tons of crop production with an irrigation intensity of 106.29% compared to other techniques used in this study. It has also resulted in an optimal spatial and temporal intra-basin water transfer from the upstream reservoirs to the downstream reservoir. The simulation of optimal results showed that the optimal policies obtained from CMODE performed well for longer period with less irrigation deficits. All the reservoirs in the system achieved more than 95% reliability in meeting the irrigation demands and intra-basin water transfer. (C) 2017 Elsevier B.V. All rights reserved.

The Zayandeh-Rud River basin, Iran, is projected to face spatiotemporally heterogeneous temperature increase and precipitation reduction that will decrease water supply by mid-century. With projected increase (0.70–1.03 °C) in spring temperature and reduction (6– 55%) in winter precipitation, the upper Zayandeh-Rud sub-basin, the main source of renewable water supply, will likely become warmer and drier. In the lower sub-basin, 1.1–1.5 °C increase in temperature and 11–31% decrease in annual precipitation are likely. A system dynamics model was used to analyze adaptation strategies taking into account feedbacks between water resources development and biophysical and socioeconomic sub-systems. Results suggest that infrastructural improvements, rigorous water demand management (e.g., replacing high water demand crops such as rice, corn, and alfalfa), and ecosystem-based regulatory prioritization, complemented by supply augmentation can temporarily alleviate water stress in a basin that is essentially governed by the Limits to Growth archetype

Multiple water sources and the physiographic heterogeneity of glacierized catchments hamper a complete conceptualization of runoff response to meltwater dynamics. In this study, we used environmental tracers (stable isotopes of water and electrical conductivity) to obtain new insight into the hydrology of glacierized catchments, using the Saldur River catchment, Italian Alps, as a pilot site. We analysed the controls on the spatial and temporal patterns of the tracer signature in the main stream, its selected tributaries, shallow groundwater, snowmelt and glacier melt over a 3-year period. We found that stream water electrical conductivity and isotopic composition showed consistent patterns in snowmelt-dominated periods, whereas the streamflow contribution of glacier melt altered the correlations between the two tracers. By applying two- and three-component mixing models, we quantified the seasonally variable proportion of groundwater, snowmelt and glacier melt at different locations along the stream. We provided four model scenarios based on different tracer signatures of the end-members; the highest contributions of snowmelt to streamflow occurred in late spring–early summer and ranged between 70 and 79 %, according to different scenarios, whereas the largest inputs by glacier melt were observed in mid-summer, and ranged between 57 and 69 %. In addition to the identification of the main sources of uncertainty, we demonstrated how a careful sampling design is critical in order to avoid underestimation of the meltwater component in streamflow. The results of this study supported the development of a conceptual model of streamflow response to meltwater dynamics in the Saldur catchment, which is likely valid for other glacierized catchments worldwide.

Snowmelt from the Tianshan Mountains (TS) is a major contributor to the water resources of the Central Asian region. Thus, changes in snow phenology over the TS have significant implications for regional water supplies and ecosystem services. However, the characteristics of changes in snow phenology and their influences on the climate are poorly understood throughout the entire TS due to the lack of in situ observations, limitations of optical remote sensing due to clouds, and decentralized political landscapes. Using passive microwave remote sensing snow data from 1979 to 2016 across the TS, this study investigates the spatiotemporal variations of snow phenology and their attributes and implications. The results show that the mean snow onset day (Do), snow end day (De), snow cover duration days (Dd), and maximum snow depth (SDmax) from 1979 to 2016 were the 78.2nd day of hydrological year (DOY), 222.4th DOY, 146.2 days, and 16.1 cm over the TS, respectively. Dd exhibited a spatial distribution of days with a temperature of

© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. In this study, how well the climate models reproduce variability in observed rainfall was assessed based on General Circulation Models (GCMs) from phase 3 and phase 5 of the Coupled Model Inter-comparison Project, i.e., CMIP3 and CMIP5, respectively as well as the Regional Climate Models (RCMs) of COordinated Regional Climate Downscaling EXperiment (CORDEX) over Africa. Observed and climate model based daily rainfall across the Lake Victoria Basin, which is one of the wettest parts of Africa, was considered. Temporal variability was assessed based on the coefficient of variation of daily and annual rainfall, and the maximum dry and wet spell in each year. Furthermore, variation in daily rainfall was assessed in terms of the long-range dependence. Comparison of variability results from observed and climate model based rainfall was made. It was found that the capacity to reproduce variability in observed wet and dry conditions depends on the specific GCM (of CMIP3 or CMIP5) or CORDEX RCM. However, the CORDEX RCMs replicated variability in observed daily rainfall better than the CMIP3 and CMIP5 GCMs. This was due to the spatial resolutions of the CORDEX RCMs which are higher than those of the CMIP3 and CMIP5 GCMs. The ensemble mean of the coefficients of correlation between the variability in observed and that of climate model based rainfall was close to zero for both the GCMs or RCMs. This suggests that analyses can be done on a case by case basis. In other words, GCMs or RCMs which adequately reproduce variability in observed wet and dry conditions can be considered for further statistical analysis of the changes especially on the basis of statistical methods for downscaling. For daily timescale, both the GCMs and RCMs from all the three sets of climate models generally exhibited poor performance in capturing the time of occurrences and the magnitudes of rainfall events (when considered in a combined way). To reliably assess long-term rainfall changes, it is vital to characterize natural variation in terms of the statistical dependence. With respect to natural variability of rainfall at local scales, there is room for further improvement of the climate models; however, whether theory of fractals and/or concepts of scaling behavior or self-similarity can explicitly contribute in that respect is a crucial consideration. Results from this study gave some insights in the reasonableness of the future rainfall projections. ispartof: STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT vol:33 issue:3 pages:687-707 status: published

Floods not only provide a large amount of water resources, but they also cause serious disasters. Although there have been numerous hydrological studies on flood processes, most of these investigations were based on rainfall-type floods in plain areas. Few studies have examined high temporal resolution snowmelt floods in high-altitude mountainous areas. The Soil Water Assessment Tool (SWAT) model is a typical semi-distributed, hydrological model widely used in runoff and water quality simulations. The degree-day factor method used in SWAT utilizes only the average daily temperature as the criterion of snow melting and ignores the influence of accumulated temperature. Therefore, the influence of accumulated temperature on snowmelt was added by increasing the discriminating conditions of rain and snow, making that more suitable for the simulation of snowmelt processes in high-altitude mountainous areas. On the basis of the daily scale, the simulation of the flood process was modeled on an hourly scale. This research compared the results before and after the modification and revealed that the peak error decreased by 77% and the time error was reduced from &plusmn, 11 h to &plusmn, 1 h. This study provides an important reference for flood simulation and forecasting in mountainous areas.

0000-0002-3895-5553 WOS: 000382045600013 The introduced goby Padogobius bonelli has established abundant populations in the River Tiber basin (Central Italy) and its expansion coincided with the decrease of the endemic P. nigricans. P. bonelli exhibits a more aggressive behaviour than P. nigricans, but other biological attributes may advance its colonization success. To test this hypothesis, some reproductive parameters (gonado-somatic index, age at maturity, egg size, absolute and relative fecundity) of a long-time established non-native population of P. bonelli were analysed and compared to a population from the native area as well as to those of P. nigricans inhabiting the same river. As a result, no differences between non-native and native populations of P. bonelli were observed. On the contrary, non-native P. bonelli showed higher values of gonado-somatic index for both sexes, a more protracted spawning season and produced a greater number of eggs than P. nigricans. These results indicated a greater reproductive output of P. bonelli that can enhance its invasion process and favour the expansion outside of its native range, causing further decline of P. nigricans populations.