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Future water availability in the largest freshwater Mediterranean lake is at great risk as evidenced from simulations with the SWAT model
Abstract
Climate change would augment water scarcity problems in Mediterranean catchments. • Future water level changes was simulated by linking SWAT model to ε-SVR model. • Climate change has a major impact on hydrology while effects of land use are minor. • Outflow management is critical to prevent Mediterranean lakes from diminishing. Inter-and intra-annual water level fluctuations and changes in water flow regime are intrinsic characteristics of Mediterranean lakes. Additionally, considering climate change projections for the water-limited Mediterranean region, increased air temperatures and decreased precipitation are anticipated, leading to dramatic declines in lake water levels as well as severe water scarcity problems. The study site, Lake Beyşehir, the largest freshwater lake in the Mediterranean basin, is – like other Mediterranean lakes – threatened by climatic changes and over-abstraction of water for irrigated crop farming. Therefore, implementation of strict water level management policies is required. In this study, an integrated modeling approach was used to predict the future water levels of Lake Beyşehir in response to potential future changes in climate and land use. Water level estimation was performed by linking the catchment model Soil and Water Assessment Tool (SWAT) with a Support Vector Regression model (ε-SVR). The projected increase in temperature and decrease in precipitation based on the climate change models led to an enhanced potential evapotranspiration and reduced total runoff. On the other hand, the effects of various land use scenarios within the catchment appeared to be comparatively insignificant. According to the ε-SVR model results, changes in hydrological processes caused a water level reduction for all scenarios. Moreover, the MPI-ESM-MR General Circulation Model outputs produced the most dramatic results by predicting that Lake Beyşehir may dry out by the 2040s with the current outflow regime. The results indicate
... The river water temperature increases slightly less than the air temperature. The least temperature rise occurs in basins fed by large amounts of groundwater (Bucak et al., 2017). Biological and chemical processes develop largely depending on the water temperature. ...
... In Turkey, with the rapid population growth, the decrease in the area per capita, the widespread use of industry, the mechanization of agriculture are the leading factors in the pollution of the environment and water (Bucak et al., 2017). It is known that today, pollution has reached significant levels in many water basins as a result of domestic, industrial wastewater and irregular agricultural activities that cannot be kept under control in Turkey (Yenici, 2010;Kaya et al., 2019;Menteş et al., 2019;Bozkurt, 2013;Yılmaz, 2019;Bucak et al., 2017). ...
... In Turkey, with the rapid population growth, the decrease in the area per capita, the widespread use of industry, the mechanization of agriculture are the leading factors in the pollution of the environment and water (Bucak et al., 2017). It is known that today, pollution has reached significant levels in many water basins as a result of domestic, industrial wastewater and irregular agricultural activities that cannot be kept under control in Turkey (Yenici, 2010;Kaya et al., 2019;Menteş et al., 2019;Bozkurt, 2013;Yılmaz, 2019;Bucak et al., 2017). Increased summer temperatures caused by climate change, reduced winter rainfall (especially in the western provinces), loss of surface waters, frequent drought, soil degradation, erosion in coastal areas, and frequent floods are threatening the existence of water resources and quality in Turkish basins (Republic of Turkey Ministry of Development, 2018). ...
Climate change, which is caused by the greenhouse gases released into the atmosphere by humans, disrupting the temperature, rainfall, and humidity balance on the earth, makes itself felt more and more every day. The effects of climate change are seen in oceans, habitats, briefly all over the world, from the equator to the poles. With the impacts of these effects, the polar glaciers are melting, the seawater level rises and soil losses increase in the coastal areas, while the severity and number of hurricanes, and floods increase in some parts of the world, while long-term droughts and desertification have started in some other regions. Climate change also affects water resources greatly, and it occurs as a decrease in water resources, forest fires, and related ecological deterioration. As a result of the decrease in the water flow in the river basins, water shortage started in the cities, agricultural production decreased and caused the expansion of arid or semi-arid areas. In this study, the impacts of climate change on Turkish basins were investigated and the measures to be taken were examined. Possible problems to be encountered in the future were mentioned and suggestions were made about what to do in the basins.
... Downward trends in precipitation were consistent with previous studies conducted in Southern Europe (Feyen et al. 2020) and in the Mediterranean Basin (Altın 2020; Erol and Randhir 2012;Ertürk et al. 2014). However, Bucak et al. (2017) indicated that precipitation would increase by 10 mm (HadGEM2-ES) or decrease by 35 mm (MPI-ESM-MR) from the 2010s to 2090s at the Lake Beyşehir watershed, adjacent to Altınapa Reservoir watershed, under the RCP4.5 scenario. GCM models could show regional characteristics and some uncertainties in simulating regional effects are possible (Monerie et al. 2017). ...
... A few previous studies investigated climate change impacts on water resources of semi-arid Turkey. Bucak et al. (2017) projected increase in temperature and decrease in precipitation in Beysehir Basin in Konya by using data from the GCMs downscaled to local conditions. They found that streamflow would decrease in the future, particularly towards the end of the century. ...
... GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-ER predicted that mean annual temperature would be 0.4 °C, 3.3 °C, and 3.3 °C higher during the 2071-2098 period, respectively. The temperature increases expected in the Altınapa Reservoir Watershed and in other Mediterranean basins in Turkey are consistent with expectations presented in the latest IPCC report (2018).At the local level,Bucak et al. (2017) andGorguner et al. (2019) also projected increases in temperatures by using data from GCMs downscaled to local conditions. All GCMs predicted temperature increases in spring, summer, and winter for the periods 2041-2070 and 2071-2098 compared to the 2021-2040 period. ...
Climate change can have severe impacts on the water availability in semi-arid regions. In this study, we assessed the impact of climatic changes on water availability in the Altınapa Reservoir Watershed, located in the Konya province, south-central Turkey. Altınapa Reservoir supplies drinking water to Konya, a city of about 2 million population. We investigated possible changes in streamflow and reservoir storage over 2021–2098 under two representative concentration pathway scenarios (RCP4.5 and RCP8.5) developed based on GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR global circulation models. We used a physically based model (SWAT-Soil and Water Assessment Tool) for understanding the hydrologic response of the basin to climatic changes. Results show that upward trends in air temperatures in the range of 0.01–0.04 °C/year and 0.005–0.06 °C/year are expected from 2021 to 2098 under the RCP4.5 and RCP8.5 scenarios, respectively. According to the HadGEM2-ES model, precipitation and streamflow would show a downward trend at a rate of 0.96 mm/year and 0.007 m³/s/year under the RCP4.5 scenario and at a rate of 1.62 mm/year and 0.01 m³/s/year under the RCP8.5 scenario, respectively. GFDL-ESM2M and MPI-ESM-MR models project upward trends in precipitation and streamflow under the RCP4.5 scenario (in the range of 0.64–1.28 mm/year and 0.0003–0.006 m³/s/year, respectively), and downward trends under the RCP8.5 scenario (in the range of 0.47–0.76 mm/year and 0.0015–0.003 m³/s/year, respectively). Reservoir storage is projected to increase slightly according to GFDL-ESM2M model and decrease according to the HadGEM2-ES, and MPI-ESM-MR models under both scenarios. Precipitation, streamflow, and reservoir storage predictions of GFDL-ESM2M and MPI-ESM-MR models are considerably lower than those observed in the basin in recent decades, showing that water resources will decrease in the future. The changes in water withdrawal patterns could cause further reductions in water availability. Good resilience to climate change can be achieved by a flexible water management system and by reducing water consumption and water losses in the watershed and from the reservoirs.
... Ellos concluyeron que el caudal se incrementó en un 10% por la conversión de la vegetación nativa a un uso de suelo mixto. Aunque se ha demostrado Bucak et al., 2017;Grey et al., 2014) que la cubierta forestal natural per se no garantiza más caudal o una regulación del flujo hídrico base con respecto a las cuencas hidrográficas deforestadas y la reforestación no aumenta el caudal o regulariza el flujo hídrico base en el corto y mediano plazo. Por lo que se ha concluido que la literatura de cuencas tropicales no es suficiente para evaluar los servicios hidrológicos (Ozment & Filoso, 2017), por ejemplo, los efectos de la edafología en la hidrología local. ...
... El modelo hidrológico Soil and Water Assesment Tool (SWAT) (Arnold et al., 1998) simula y predice el balance de agua bajo el efecto de la deforestación en escalas de cuencas (Zhang et al., 2016;Gassman et al., 2007). SWAT se ha utilizado para evaluar servicios hidrológicos en todo el mundo (Ahn y Merwade, 2016;Brauer et al., 2016;Francesconi et al., 2016;Bucak et al., 2017;Her et al. 2017), por lo que el modelo puede usarse como una herramienta efectiva para examinar las respuestas hidrológicas ante la deforestación (Pereira et al., 2016). Sin embargo, una de las limitaciones de la modelación es la ausencia de datos a escalas apropiadas para obtener buenas predicciones, y además se asume la necesidad de datos de resolución fina para realizar la modelación. ...
... The two GCMs used in the (Bucak et al. 2017) study were able to model the trends of contemporary climate data; however, the precipitation and temperature predictions for the future varied widely. Although the direction and seasonality of the changes exhibited similar patterns, the magnitude of the changes differed between the climate models. ...
La demanda de la población sobre los ecosistemas está creciendo y ejerciendo presión sobre los servicios ambientales hidrológicos de cuencas tropicales, como es la cantidad de agua y la regulación de las aguas de superficie y subterránea. Aunque, puede parecer que los bosques absorben el agua disponible, dejando menos cantidad para el uso humano. Una revisión de literatura sobre la relación bosque- agua en cuencas tropicales deja ver que esta relación es más compleja, y que los servicios hidrológicos de provisión y regulación que se comercializan en los esquemas de Pagos por Servicios Ambientales (PSA) normalmente no se cuantifican de manera adecuada, aunque se aceptan de forma pragmática. En esta tesis se evaluó la cantidad y regulación del agua en cuencas donde se ha concedido el PSA. Primero se analizó si las predicciones del caudal mejoran al utilizar datos de suelos y vegetación disponibles al público vs datos finos. Luego se analizó cómo la deforestación que ocurrió en la cuenca afectó el caudal y el flujo hídrico base, y cuál hubiera sido el impacto si continuara la deforestación. Por último, aunque el modelo SWAT es una herramienta que ayuda en la cuantificación de los servicios hidrológicos, se realizó una revisión sistemática de la literatura para conocer el alcance del modelo en la simulación y predicción de las alteraciones en los regímenes hidrológicos. Esfuerzos adicionales se realizaron para entender la relación bosque-agua, como son la exploración del comportamiento hidrológico a escalas de cuencas en la modelación SWAT y medición de lluvia-escurrimiento en cuencas pareadas.
... Asia Jiang et al. [137] Shibetsu River (Japan; 672) Simulation of streamflow and external flow contribution to discharge from the water balance equation, using measured data Tian et al. [138] Shibantang River (China; 2248) Assessment of trade-offs and synergic relationships between ecosystem services (water yield, sediment yield, and net primary productivity) Bucak et al. [139] Lake Beyşehir catchment (Turkey; 4704) Impacts of climate and land-use changes on the hydrological balance of a lake catchment and water levels Hou and Gao [140] Sancha River (China, 4068) 1 Simulation of the spatial variability of streamflow, surface runoff, and groundwater runoff, and analysis of their spatial correlation with environmental factors Jakada and Chen [141] Miaogou subbasin of Gaolan River Basin (China; 45) ...
... Several studies evaluated climate change impacts on watershed hydrology based on historical climate patterns and climate projections [113,118,129,135], as well as the effects of land-use change on the water budget [111]. Other studies assessed the combined impacts of land-use and climatic changes on watershed hydrology and or water quality [62,139], including the influence of future urbanization and impervious surface growth [114], and other anthropogenic factors, such as wastewater treatment [5]. ...
Karst water resources represent a primary source of freshwater supply, accounting for nearly 25% of the global population water needs. Karst aquifers have complex recharge characteristics, storage patterns, and flow dynamics. They also face a looming stress of depletion and quality degradation due to natural and anthropogenic pressures. This prompted hydrogeologists to apply innovative numerical approaches to better understand the functioning of karst watersheds and support karst water resources management. The Soil and Water Assessment Tool (SWAT) is a semi-distributed hydrological model that has been used to simulate flow and water pollutant transport, among other applications, in basins including karst watersheds. Its source code has also been modified by adding distinctive karst features and subsurface hydrology models to more accurately represent the karst aquifer discharge components. This review summarizes and discusses the findings of 75 SWAT-based studies in watersheds that are at least partially characterized by karst geology, with a primary focus on the hydrological assessment in modified SWAT models. Different karst processes were successfully implemented in SWAT, including the recharge in the epikarst, flows of the conduit and matrix systems, interbasin groundwater flow, and allogenic recharge from sinkholes and sinking streams. Nonetheless, additional improvements to the existing SWAT codes are still needed to better reproduce the heterogeneity and non-linearity of karst flow and storage mechanisms in future research.
... After the 2000s, the multi-year precipitation deficits and severe droughts led to the expansion of the salt-covered areas at Lake Tuz (Fig. 10). Recent regional studies (e.g., Temiz and Durduran (2016) and Bucak et al. (2017)) also confirmed the dramatic loss of the water volume of lakes at the Konya Closed Basin. Some of the largest lakes, including Burdur, Acıgöl, and Seyfe in the Central Anatolia Region, have shrunk. ...
... Some of the largest lakes, including Burdur, Acıgöl, and Seyfe in the Central Anatolia Region, have shrunk. Akgöl and Akşehir lakes have wholly dried out in the last 30 years (Temiz & Durduran, 2016;Bucak et al., 2017;Dervisoglu et al., 2017). In 1985, the total saline lakes in the Konya Closed Basin covered 64.2% of the overall water-covered natural lake surfaces; however, this percentage decreased to 52.5% in 2018 (Yagmur et al., 2020). ...
This study aims to reveal the relationship of the expansion of the salt-covered area of Lake Tuz in Turkey with the drought in the region and the change of the groundwater storage. The changes in the salt-covered area in Lake Tuz between 1985 and 2021 (37 years), which have been obtained by August satellite images, are compared with those in groundwater and the 12-month Standardized Precipitation–Evapotranspiration Index (SPEI) variations in the lake. The results show that the salt-covered area on the lake surface was most strongly correlated with the SPEI spring (−0.78, t test; p < 0.01) during the period of August 1985–2021, implying that the drought conditions in spring determines 62% of the salt-covered area on the lake in August. The groundwater storage (GWS) in June and July and the salt-covered area in August in Lake Tuz also depict a moderate correlation of −0.60 at 1% significance level from 1985 to 2021. The results illustrate that the SPEI and GWS values decreased, while the salt-covered area on the lake surface expanded in the Lake Tuz Basin over the past 37 years. The trends of the salt-covered area, SPEI, and GWS became especially pronounced after 1999, during which the SPEI change and similar changing trends appeared in the GWS and salt-covered area. These patterns of increase in drought severity and decreasing groundwater storage are expected to increasingly compromise the future of Lake Tuz and cause ecological and environmental problems in the near future.
... Previous studies (van Griensven et al. 2012;Tan et al. 2019) also showed that both NSE values and R 2 values reported in the literature also change within a wide range and sometimes these values were lower than the criteria proposed by Moriasi et al. (2007Moriasi et al. ( , 2015 for satisfactory model performance. Some previous studies conducted in Turkey (Bucak et al. 2017;Duru et al. 2018;Donmez et al. 2020), which used datasets similar to those used in this study, also reported model performances lower than the criteria proposed by Moriasi et al. (2007Moriasi et al. ( , 2015. Considering the spatial and temporal resolution of the data used in this study, we believe our results can be acceptable. ...
... much closer to the value determined in this study. In the Beysehir Lake Basin, groundwater contribution to runoff is found to be higher similar to the findings for the Altınapa Reservoir Watershed (Bucak et al. 2017). Based on this information, we can accept that the model provided the general representation of the hydrologic processes and hydrological dynamics in the basin (fit to reality). ...
The calibration of ecohydrological models is challenging in semi-arid regions, particularly for data-scarce conditions. Precise uncertainty analysis is also critical for determining the range of uncertainty in model predictions. In this study, we evaluated the applicability of a ecohydrological model, Soil and Water Assessment Tool (SWAT), for a data-scarce semi-arid basin (Altınapa Reservoir Watershed) in Turkey. We used multiple optimization algorithms for model calibration and uncertainty assessment and compared their performances. The SWAT model was set up using the digital elevation model, land use/cover, and soil data obtained from global datasets, and climate data obtained from local stations. The optimization algorithms included Sequential Uncertainty Fitting (SUFI-2), Parameter Solution (ParaSol), Generalized Likelihood Uncertainty Estimation (GLUE), and Particle Swarm Optimization (PSO). Twenty-four parameters with initial parameter ranges were chosen for parameter uncertainty analysis. The performance of four algorithms were evaluated based on the Nash-Sutcliffe Efficiency (NSE), determination coefficient (R2), P-factor, R-factor, and convenience of implementation of model. The models provided the general representation of the hydrologic processes and hydrological dynamics in the basin. Satisfactory model performance was obtained based on NSE (> 0.5) with the SUFI-2 algorithm during model calibration and validation. R2 criteria (> 0.6) was met by all algorithms, except for SUFI-2, during calibration, but it was not met during validation. 70 to 80% of the values were bracketed by the 95PPU during the calibration period and 50–60% during the validation period with all four algorithms. The R-factor was smaller than 1 with only SUFI-2 during calibration and with GLUE, ParaSol, and PSO during validation. Overall, the SUFI-2 calculation was accepted as a viable technique for calibration and uncertainty assessment, even though it requires more work and extra requirements for adjusting parameter ranges.
... Through a simulation of anticipated changes in water level by coupling SWAT to a Support Vector Regression model in Lake Beyşehir, which is the largest Mediterranea freshwater lake, Bucak et al. (2017) concluded that changes in climate have a more significant effect on the lake hydrology compared to land use. They also concluded that the ongoing intense water extraction may cause shallow lakes in the Mediterranean region to experience dramatic drought stress and lose their ecological value in the near future. ...
... Salvetti et al. (2008) A dry weather scenario was simulated by the QUAL2E model and a wet weather scenario was simulated by the BASINS-SWAT model in order to assess the nitrogen loads source apportionment. SVR Bucak et al. (2017) SWAT model and ε-SVR (a Support Vector Regression model) were linked to simulate future changes in water levels. ...
The Soil and Water Assessment Tool (SWAT) is a well-established eco-hydrological model that has been extensively applied to watersheds across the globe. This work reviews over two decades (2002–2022) of SWAT studies conducted on Mediterranean watersheds. A total of 260 articles have been identified since the earliest documented use of the model in a Mediterranean catchment back in 2002; of which 62% were carried out in Greece, Italy, or Spain. SWAT applications increased significantly in recent years since 86% of the reviewed papers were published in the past decade. A major objective for most of the reviewed works was to check the applicability of SWAT to specific watersheds. A great number of publications included procedures of calibration and validation and reported performance results. SWAT applications in the Mediterranean region mainly cover water resources quantity and quality assessment and hydrologic and environmental impacts evaluation of land use and climate changes. Nevertheless, a tendency towards a multi-purpose use of SWAT is revealed. The numerous examples of SWAT combined with other tools and techniques outline the model's flexibility. Several studies performed constructive comparisons between Mediterranean watersheds' responses or compared SWAT to other models or methods. The effects of inputs on SWAT outputs and innovative model modifications and improvements were also the focus of some of the surveyed articles. However, a significant number of studies reported difficulties regarding data availability, as these are either scarce, have poor resolution or are not freely available. Therefore, it is highly recommended to identify and develop accurate model inputs and testing data to optimize the SWAT performance.
... Delft3D was applied to simulate the effects of climate and nutrient changes in the IJsselmeer. Beyşehir (TUR) SWAT Beyşehir DYRESM-CAEDYM, PROTECH, PCLake [31][32][33] IJsselmeer (NLD) None IJsselmeer DELFT-3D, HABITAT [19] Once calibrated and tested (Section 3.2), the models were run for a baseline period of 1981-2010 and then for a scenario period of 2031-2060. The difference in the mean flow and concentrations simulated for the scenario and baseline periods were used to derive percentage changes. ...
... Changes in discharge also tend to reduce the differences between scenarios, making lake loadings less variable than the concentrations. The exception is Beyşehir, where reductions in both river discharge and river concentration cause a large change in load ( Figures S3 and S5) [32]. The changes in river discharge in the Yläneenjoki, Hobøl, and Vltava are small (1-10%), which makes the input loads of P and N less variable than the concentrations (Figures S3-S5). ...
Recent studies have demonstrated that projected climate change will likely enhance nitrogen (N) and phosphorus (P) loss from farms and farmland, with the potential to worsen freshwater eutrophication. Here, we investigate the relative importance of the climate and land use drivers of nutrient loss in nine study catchments in Europe and a neighboring country (Turkey), ranging in area from 50 to 12,000 km2. The aim was to quantify whether planned large-scale, land use change aimed at N and P loss reduction would be effective given projected climate change. To this end, catchment-scale biophysical models were applied within a common framework to quantify the integrated effects of projected changes in climate, land use (including wastewater inputs), N deposition, and water use on river and lake water quantity and quality for the mid-21st century. The proposed land use changes were derived from catchment stakeholder workshops, and the assessment quantified changes in mean annual N and P concentrations and loads. At most of the sites, the projected effects of climate change alone on nutrient concentrations and loads were small, whilst land use changes had a larger effect and were of sufficient magnitude that, overall, a move to more environmentally focused farming achieved a reduction in N and P concentrations and loads despite projected climate change. However, at Beyşehir lake in Turkey, increased temperatures and lower precipitation reduced water flows considerably, making climate change, rather than more intensive nutrient usage, the greatest threat to the freshwater ecosystem. Individual site responses did however vary and were dependent on the balance of diffuse and point source inputs. Simulated lake chlorophyll-a changes were not generally proportional to changes in nutrient loading. Further work is required to accurately simulate the flow and water quality extremes and determine how reductions in freshwater N and P translate into an aquatic ecosystem response.
... Natural elements include variability in precipitation and temperature changes, whereas human factors encompass water engineering, ecological restoration, and socio-economic development initiatives. From 1961 to 2015, the YRD saw a decrease in average annual precipitation by 241.8 mm and an increase in average temperature by 1.7 • C, which contributed to reduced runoff (Bucak et al., 2017;Han et al., 2018). Cumulative runoff and sediment at the Lijin station from 1975 to 2022 were significantly positively correlated, with a clear turning point (Fig. S5 (b)). ...
The Yellow River Delta (YRD), a wetland ecosystem formed by the interactions of the river, sea, and land, is influenced by both natural and anthropogenic factors. Understanding the characteristics of wetland landscape evolution in this region and its key driving factors is crucial for advancing wetland protection and restoration. This paper investigates the dynamics of wetland landscape evolution in the YRD from 1980 to 2023, and quantifies the impacts of natural and anthropogenic factors on this evolution, including their relative contribution rates. The results showed that over the past 40 years, the YRD has lost more than 63 % of its natural wetland area, primarily transforming into aquafarms, salt fields, and farmland. The fragmentation of the wetland landscape has increased, with decreased connectivity, and distinct spatial characteristics. Human activities, water-sediment fluxes, and nearshore hydrodynamics are closely related to wetland landscape evolution, with relative contribution rates of 49.41 %, 31.08 %, and 16.17 %, respectively. This study provides valuable insights for enhancing wetland ecological conservation efforts in the YRD.
... Banks are more likely to lend to the sector as it is more resilient to climate-related supply chain risks. As a result of adopting circular economy principles, the infrastructure sector is more attractive to lenders, reducing climate and environmental risks (Bucak et al. 2017). Increasing the lending to climate-resilient projects such as renewable energy, green buildings, and water management systems has been encouraged by the Indian government's push for sustainable infrastructure development, such as the National Infrastructure Pipeline and the National Monetization Pipeline. ...
This paper underscores the critical significance of climate-related risks within the banking and industrial sectors, emphasizing the need for a climate-resilient response system and strategic loan portfolio planning. The study introduces an efficient methodology for identifying key Climate-Linked Risks (CLRs) across impacted sectors, capturing their diverse impacts, quantifying them, and subsequently designing optimal loan portfolios. A comprehensive review of literature and primary responses from CLR experts, coupled with secondary data sources, forms the basis of our analysis. Initially, CLR impacts were categorized into push and pull indicators based on empirical weighted averages. Subsequently, fuzzy logic theory was employed to quantify CLR in form of composite index across industries. Finally, the study proposes portfolio planning for banks using mean variance portfolio. The proposed control approach assesses sectoral severity, prioritizes sectors, identifies root causes, and recommends cost-effective strategies, enhancing the overall resilience of the banking ecosystem.
... Interestingly, the SWAT hydrological model has been frequently chosen by researchers when preparing integrated modeling platforms, as is the case of Bucak et al. [78], which has linked SWAT with a Support Vector Regression model and an ensemble of future climate data projections to assess future water availability in Lake Beyşehir (Southwest Turkey), or the case of Pulighe et al. [79], which forced a restructured version of the SWAT model, called SWAT+, with future climate projections data generated with two RCMs for a watershed in Sardinia, Italy. SWAT has also been used in the assessment of possible alternative water and land use management, with the research of Rivas-Tabares et al. [80]. ...
Warming and drying trends in the Mediterranean Basin exacerbate regional water scarcity and threaten agricultural production, putting global food security at risk. This study aimed to review the most significant research on future water availability for the Mediterranean agricultural sector under climate change (CC) scenarios published during 2009–2024. Two searches were performed in the Scopus and Web of Science databases, to which previously identified significant studies from different periods were also added. By applying a methodology duly protocoled in the PRISMA2020-based guideline, a final number of 44 particularly relevant studies was selected for review. A bibliometric analysis has shown that most of the published research was focused on Southwestern European countries (i.e., Spain, Italy, Portugal) and grapevine and olive tree crops. Overall, the reviewed studies state that future Mediterranean water reserves may not meet agricultural water demands, due to reduced reservoir inflows and higher irrigation demands under future CC and socioeconomic scenarios. Regarding adaptation measures to improve water-use management in agriculture, the majority of the reviewed studies indicate that the use of integrated modelling platforms and decision–support systems can significantly contribute to the development and implementation of improved water/land-management practices.
... Throughout history, significant changes in water availability have been observed, influenced by natural and anthropogenic factors. Available research points to a worrying trend towards a decrease in rainfall and an increase in temperatures that directly impacts runoff and water availability in all of the Mediterranean region (Senatore et al. 2011;Lelieveld et al. 2012;Piras et al. 2014;Lutz et al. 2016;Bucak et al. 2017;Abrantes et al. 2017;Lobanova et al. 2018;Gorguner and Kavvas 2020). Critical basins of the southern Iberian Peninsula may be impacted by these effects, and certain semi-arid and arid areas of the western Mediterranean may be at increased risk of water scarcity (Miranda et al. 2011;Santos et al. 2019;Zapata-Sierra et al. 2022). ...
Water availability is of paramount importance for sustainable development and environmental planning, specifically in regions such as the Iberian Peninsula, renowned for diverse landscapes and varying climatic conditions. Due to climate change, understanding the potential impacts on water resources becomes essential for effective water management strategies. This research effort aims to assess future potential water availability for the Iberian Peninsula in different climate scenarios, employing cutting-edge water resource modelling techniques integrated within a geographic information system (GIS) framework. In this study, potential water availability is defined as the annual demand for water that can be satisfied at a specific point in the fluvial network with certain reliability. An ensemble of state-of-the-art climate models is utilised to project runoff for the Iberian Peninsula during the mid- and late-twenty-first century periods. These climate projections were subsequently processed using the GIS-based water resource management model, WAAPA, to derive potential water availability under a range of realistic hypotheses. The results indicate that anticipated shifts in precipitation patterns will lead to alterations in hydrological regimes across the region, significantly impacting future water availability. By using GIS-based methodologies, we can facilitate the identification of vulnerable areas susceptible to changes in water availability, offering spatially explicit information along the main rivers of the Iberian Peninsula for decision-makers and stakeholders. High-resolution spatial outputs from this research and detailed water availability estimates serve as valuable input for integrated water resource management and climate change adaptation planning. By combining advanced GIS-based hydrological modelling with climate scenarios, this research presents a robust framework for assessing water resources amidst a changing climate, applicable to other regions struggling with analogous challenges. Ultimately, our study provides vital insights for policymakers and stakeholders, empowering them to make informed decisions and devise adaptive measures to ensure sustainable use of water resources despite uncertain future climatic conditions.
... Evapotranspiration magnitudes gradually decrease from upstream (39-41 mm) towards the downstream of the Wadi Mina upstream basin (22-28 mm). Studies by Ertürk (2014), Bucak (2017) and Grusson (2018) have attributed this decrease in evapotranspiration to a reduction in the water level in the soil caused by decreased precipitation and higher temperature. ...
Modelling the hydrological balance in semi-arid zones is essential for effective water resource management, encompassing both surface water and groundwater. This study aims to model the monthly hydrological water cycle in the Wadi Mina upstream watershed (northwest Algeria) by applying the Soil and Water Assessment Tool (SWAT) hydrological model. SWAT modelling integrates spatial data such as the Digital Elevation Model (DEM), land use, soil types and various meteorological parameters including precipitation, maximum and minimum temperatures, relative humidity, solar radiation and wind speed. The SWAT model was calibrated and validated using data from January 2012 to December 2014, with a calibration period from January 2012 to August 2013 and a validation period from September 2013 to December 2014. Sensitivity and parameter calibration were conducted using the SWAT-SA program, and model performance evaluation relied on comparing the observed discharge at the outlet of the basin with model simulated discharge, assessed through statistical coefficients including Nash-Sutcliffe Efficiency (NSE), coefficient of determination (R2) and Percent Bias (PBAIS). Calibration results indicated favourable objec�tive function values (NSE=0.79, R2=0.93, PBAIS=−8.53%), although a slight decrease was observed during validation (NSE=0.69, R2=0.86, and PBAIS= −11.41%). The application of the SWAT model to the Wadi Mina upstream watershed highlighted its utility in simulating the spatial distribution of different components of the hydrological balance in this basin. The SWAT model revealed that approximately 71% of the precipitation in the basin evaporates, while only 29% contributes to surface runoff or infiltration into the soil.
... These techniques have made it possible to estimate groundwater depletion at different scales. In ungauged basins characterized by data scarcity, which includes the study area of the present research, pairing remote sensing data with hydrological models ought to provide promising results as demonstrated in different climatic contexts (Arshad et al., 2022;Bucak et al., 2017;Dekongmen et al., 2022;Zhang et al., 2020). ...
Study region: The upstream part of the Essaouira basin, a data-scare region in Morocco, Northwestern Africa.
Study focus: The scarcity of hydro-climate data is a significant challenge found in several regions worldwide, where qualitative and quantitative water resource information remains limited. Estimating and predicting groundwater levels (GWL) in such areas is a significant challenge in producing knowledge for effective water resource management. To address this issue, the present study aimed to use the Soil and Water Assessment Tool (SWAT) model in conjunction with downscaled total water storage (TWS) data (9 km) obtained from Gravity Recovery And Climate Experiment (GRACE) and machine learning techniques, specifically random forest (RF) and support vector machine (SVM), to estimate and predict the variation in GWL.
New hydrological insights for the region: This study constitutes a first of its kind in the study area; the SWAT model was set up for 10 years, with a warm-up period from 2000 to 2001, calibration from 2002 to 2007, and validation from 2008 to 2010. The statistical indices (Coefficient of Determination (R2) ≥ 0.73, R2 ≥ 0.78, Nash–Sutcliffe model efficiency coefficient (NSE) ≥ 0.67, NSE ≥ 0.80 respectively for calibration and validation) highlight a significant correlation, implying the model’s capability to faithfully reproduce the streamflow. The downscaled TWS demonstrates an impressive ability to identify and monitor fluctuations in GWL. Using machine learning algorithms (RF and SVR), the prediction of GWL yielded satisfactory results, NSE = 0.78 and root mean square error (RMSE) = 0.33, NSE = 0.51 and RMSE = 0.49 for the RF and SVR, respectively. Despite some limitations, our approach provided promising results in GWL prediction, with the possibility of expanding to other data-scarce regions.
... Water levels in lakes and reservoirs will probably decline. For example, the largest Mediterranean lake, Beyşehir in Turkey, may dry out by the 2040s if its outflow regime is not modified 35 . The seasonality of stream flows is very likely to change, with earlier declines of high flows from snow melt in spring, intensification of low flows in summer and greater and more irregular discharge in winter 36 . ...
On November 12, 2019, an exceptional flood event took place in Venice, second only to the one that occurred on November 4, 1966. The sea level reached a peak value of 1.89 m above the local datum determining the flooding of almost 90% of the pedestrian surface of the historical city. Several processes concurred to raise the water level in Venice and the northern Adriatic Sea on November 12, 2019. Among these, a fast‐moving mesoscale cyclone travelled at about 12 m · s in the northwestward direction over the northern Adriatic Sea, raising the sea levels at the shore in front of the Lagoon of Venice. High‐resolution numerical simulations indicated that atmosphere–ocean resonance occurred on November 12, 2019, generating a meteotsunami‐like wave that contributed significantly to the extreme sea level in Venice. The relative contributions of the wind and air pressure to the peak sea level were also estimated. Additional numerical experiments were performed to prove the occurrence of Proudman resonance and to determine a transfer function of such high‐frequency sea‐level perturbations for the Lagoon of Venice.
... Hydrologic models are also required to predict extreme events such as floods and droughts that are common in many parts of the world including India. However, the reliability and robustness of hydrological models depend on the availability of appropriate input data and proper model calibration (Chen et al. 2023;Bucak et al. 2017)). In many parts of the world, lack of appropriate input data is a major constraint for hydrologic modeling (Abbaspour et al. 2019). ...
Process-based hydrologic models can provide necessary information for water resources management. However, the reliability of hydrological models depends on the availability of appropriate input data and proper model calibration. In this study, we demonstrate that common calibration procedures that assume stationarity of hydrological processes can lead to unsatisfactory model performance in areas that experience a strong seasonal climate. Moreover, we develop a more robust calibration procedure for the Soil and Water Assessment Tool (SWAT) in the Adyar catchment of Chennai, India. Calibration was carried out based on seasonal decomposition and by successively shifting the calibration period. Daily and monthly streamflow records were used to investigate how these different calibration procedures influence model parameterization. Results show that SWAT model performance improved when calibrated after separating the streamflow into wet and dry seasons. The wet season calibration increased the Kling Gupta Efficiency coefficient and Nash-Sutcliffe Efficiency coefficient values from 0.56 to 0.68 and 0.19 to 0.51, respectively, compared to calibration based on wet and dry seasons together. In addition, when calibration time periods were shifted, resultant sets of model parameter values and performance metrics differed. Calibration based on the 2004-2009 period resulted in an overestimation of streamflow by 8.2%, whereas the overestimation was
... For instance, the impact of climate change and reservoirs on the water resources of the Susurluk Basin, a semi-arid Mediterranean Basin in Turkey, was evaluated using the SWAT model; it was estimated that the water resources in the basin tend to decrease under RCPs and that water scarcity may occur in the basin in the future (Akbas et al. 2020). In another study prepared by using the SWAT model, it was determined that Beysehir Lake, located in the south of Turkey and the largest freshwater source in the Mediterranean Basin, is facing the risk of drying up as a result of the increase in air temperatures and decrease in precipitation due to climate change (Bucak et al. 2017). The North Aegean Basin is one of the 26 hydrographic basins in Turkey, where the negative effects of climate change are seen. ...
Climate change is a global phenomenon that directly affects agriculture by altering crop yield, nutritional quality, pests, and plant diseases. The North Aegean Basin located in Turkey has considerable agricultural importance due to its fertile soils. Agricultural activities have increased significantly and uncontrollably in the last decade, resulting in dramatic changes in nitrate and phosphorus levels in surface water within the watershed. Changes in climatic conditions have the potential to impact the quantity and quality of water resources. Best management practices (BMPs) are presently utilized as a planning tool to enhance the quality of water resources. To develop policies in this regard, it is necessary to evaluate the effectiveness of BMPs. To this end, this study aims to investigate the potential effect of climate change on the surface water quality of the North Aegean Basin. For the period between 2010 and 2030, global climate data retrieved from Concentration Pathway (RCP) scenarios 4.5 and 8.5 and regionally downscaled were used to feed the Soil and Water Assessment Tool (SWAT) model. The various potential BMP scenarios were developed and simulated in the hydrological model by considering the effects of climate change. The RCP4.5 scenario reduced the precipitation by 15.11%, while the RCP8.5 scenario reduced the precipitation by 10.97%. Decreased precipitation also affected the runoff and the nutrient loads and concentrations. As a result of the RCP4.5 simulation, TP and TN concentrations increased by 24.42% and 58.45%, respectively, in the IST_KEN014 station. Improvements were observed in TN and TP concentrations with the effect of applied BMP simulations. Also, the results revealed that the applied BMP scenarios may contribute to considerable reductions in nutrient loads. Considering the RCP4.5 scenario, BMPs reduced TN loads in the basin by 2.42–10.97%, while reducing TP loads by around 3.60–16.81%. Considering the RCP8.5 scenario, the BMPs reduced the TN loads in the basin between 2.21 and 10.04%, while they reduced the TP loads between 3.57 and 16.67%.
... Precipitation (mm), minimum/ maximum temperature ( o C), and relative humidity (%) of Ulus weather station (17615) between 1970 and 2020 were obtained from the Turkish State Meteorological Service (TSMS), and the gauge data of Emirce-Ulus station (D13A088) between 2016 and 2020 was acquired from the Turkish Hydraulic Service (DSI) for calibration (Fig. 1). The sensitive parameters model was manually calibrated based on the suggestion of Abbaspour et al., (2015), and the NSE value was found as 0.3 on a daily scale which is sufficient to use in the model (Bucak et al., 2017). ...
Floods are natural phenomena that increase their impact every year due to increasing natural and anthropogenic variables, which are effective individually or together. Many research studies have focused on understanding the causative factors. This study aims to reveal whether there is a consistency in the results of the basin morphometry and hydrodynamic model used to understand the flood generation potential of river basins. Both analyses have been discussed individually in many papers but are not comprehensively compared. Ulus settlement (Türkiye), where Ulus upstream, Suleyman, Alpi, and Eldes tributaries converge, was chosen as a study area. The results of the two analyses were evaluated in terms of their potential ability to produce floods over the subbasins and the Ulus settlement. Eight basin morphometric parameters were applied to the 10 m resolution TopoDEM data, and the results were evaluated according to the Normalised Morfometric Flood Index (NMFI) method, which helps decrease subjectivity in ranking the results. Flow data of the ungauged subbasins were produced using the SWAT rainfall-runoff model, and 2, 5, 10, 20, 50, 100, 200, 500, and 1000 years maximum flow data were generated using flood frequency analysis, and the different flow data were modelled based on 1m LiDAR DEM using the LISFLOOD-FP 2D-hydrodynamic model. According to the results, the Suleyman subbasin has the highest flood generation potential in basin morphometry and hydrodynamic modelling. It is followed by the Alpi subbasin at high potential, Ulus upstream and Eldes subbasins at medium potential. As a result, we determine there is a consistency in basin morphometry and hydrodynamic modelling results. The basin morphometry and the developed NMFI can be used to determine and understand the flood-generating potential of basins or subbasins in data-scarce regions regarding flood modelling.
... According to the report of the Intergovernmental Panel on Climate Change (IPCC 2007), the climate is changing, and that cannot be associated and explained by natural variability (Yilmaz and Imteaz 2011). Most of the studies carried out in the context of water resource show that the projections of future climate change could significantly affect the water cycle components and socioeconomic sectors of the basins around the world (Zerouali et al. 2021a, b;Bucak et al. 2017;Arnell 2004;Ragab and Prudhomme 2002). According to Somot et al. 2008, the Mediterranean basin will experience a significant rise in temperatures during the twenty-first century. ...
Due to its location in the Mediterranean basin, Algeria is one of the most countries vulnerable to the effects of climate change. The aim of this study is to assess future flow rate projections of Sebaou basin (Northern Algeria), using the coupling of statistical downscaling approach (SDSM) based on the general circulation model Hadley Centre Coupled Model version 3 (GCM-HadCM3) of the Royaume-Uni with an anthropogenic forcing SRES A2a (pessimist) and SRES B2a (optimistic) and GR2M model for rainfall-runoff transformation. The use of GR2M rainfall-runoff model has been able to control the hydrological functioning of the basin with very satisfactory performance values expressed by the Nash values over 80% for most subbasins, except for the degradation the Nash coefficient after the commissioning of the Taksebt dam in the Oued Aissi subbasin after 2001. The combining approach showed, on one hand, a decrease in rainfall ranging from 18% to 14% and that the maximum, average, and minimum temperatures could continue to increase with a maximum of 1.1–0.65 °C, 1.1–1.25 °C, and 2.7–3.4 °C, respectively, for the H3A2 and H3B2 emission scenarios until the long-term horizon 2080. On the other hand, the model indicated that these climatic changes have an effect on decreases in the basin’s water resources and that the 2050 and 2080 horizons are the most deficient with a decrease in flows estimated from −35% to −49% for A2 and from −45 to −57% for B2 scenarios, respectively, which represents approximately 500–300 Hm3 by the end of the twenty-first century.
... For example, Pan. (2011) found that the water resources system of the Yarkent River basin was expected to be more vulnerable in the future 20 years because of the effect of climatic warming and accelerating glacier melt. Bucak et al. (2017) demonstrated that the water-scarce Mediterranean region may be at risk of losing 14 % to 52 % of freshwater resources due to climate change by the end of the century. These studies provided managers with recommendations such as strict abstraction management measures incorporated into important policies (such as Water Withdrawal Management and Special Treatment Action issued by the Ministry of Water Resources of China in 2022). ...
Despite being one of the most abundant water resources globally, the Yangtze River Basin (YRB) region is facing substantial risks aggravated by climatic and anthropogenic changes. Here, we adopted an integrated framework to investigate the plausible futures of water resource provisioning in YRB under current and future conditions on the sub-watershed level: (i) a process-based model (InVEST) was used to project the water yield of the whole of YRB in the nearest future (2040-2060) and distant future (2080-2100) and (ii) a socio-ecological index was developed to assess the spatio-temporal patterns of water resources vulnerability (WRV). Model projections indicated that several water-rich areas in the southeastern YRB would suffer declining water yield in the future. While water yield was projected to increase in some drier regions in the northwest. Future changes in the basin-level vulnerability were projected to decrease under low emissions scenarios (RCP2.6) combined with a sustainability socioeconomic scenario (SSP1). The greatest increase in vulnerability was projected under the medium-to-high end (RCP7.0) rather than high-end (RCP8.5) climate change scenario. The areas with high WRV were distributed in sub-watersheds near Taihu Lake and the source of the Yangtze River. Climate and socioeconomic change were projected to have different roles in shaping the future dynamics of WRV, with precipitation reduction and water consumption increase being likely to result in increased WRV levels in the southeastern lower reaches and the middle reaches, respectively. Our study added new spatial data on projected water resource dynamics for the region of vital ecological and economic importance in Asia. The areas prone to increased WRV should be prioritised in future water resources management practices. The assessment approach used in this study integrated concurrent measures from both subjective and objective perspectives and could be used in relevant studies on exploring how future vulnerability could respond to environmental changes.
... Recent studies concern not only trends in stream discharge at a variety of temporal and spatial scales, e.g., [2,3,[6][7][8][9][10][11][12][13][14], but also the groundwater response to these changes, e.g., [5,[15][16][17][18][19][20][21][22]. Finally, the said changes affect the amount of freshwater in catchments that may be used as drinking water by human populations [23][24][25][26]. ...
Global warming affects, among many other things, groundwater recharge conditions. Over recent decades, this phenomenon in the Carpathians has been emphasized by the changing role of snowmelt recharge in winter and spring. The aim of the study was to assess baseflow trends in 20 medium-sized Carpathian catchments in Poland and Slovakia. The baseflow was calculated using Eckhardt’s digital filter. The trend analysis was performed using the non-parametric method separately for the series representing the baseflow throughout the whole year, and separately for seasons. The most evident changes were noted for the low baseflow in the summer and autumn, especially in foothill catchments. Statistically significant decreases in the low daily baseflow were expressed as a relative change, and ranged from −9% to −66% per 10 years for the summer, and from −12% to −82% per 10 years for the autumn. In winter and spring, trends in the low baseflow were not significant, except in high mountain catchments where 14% of increases in the low baseflow were noted in the winter and spring. The results indicate the changing role of snowmelt recharge in the Carpathians and the increasing problem of groundwater depletion in the summer and autumn, mainly in foothill areas.
... and quality (Section 3.1.3.5) (Bucak et al. 2017), ecosys-39 Parts of this chapter have been published by Linares et al. (2020). tem degradation (Section 4.3) (e.g., Coll et al. 2010) and increased risk of forest fires (Section 4.3.2.1) (e.g., Turco et al. 2014), the vulnerability of the Mediterranean population to human health risks is increasing significantly. ...
... The consequences on the hydrological cycle of the observed and projected change in the precipitation and temperature regimes in the Mediterranean affect the whole ecosystem and, consequently, essential socio-economic activities, like drinking water distribution (UN, 2021;Maiolo et al., 2017), food production (FAO, 2016;Ronco et al., 2017) or preparedness to hydrometeorological extremes (Madsen et al., 2014). Therefore, in the last years, the climate change impact studies dealing with the projected hydrological variability in Mediterranean catchments has increased tremendously, addressing either the whole region (e.g., Hertig andTramblay, 2016, Hartmann et al., 2017) or smaller areas (e.g., Spain: Estrela et al., 2012;Majone et al., 2012;Olmos Giménez et al., 2016;France: Lafaysse et al., 2014;Prats et al., 2018;Dayon et al., 2018;northern Africa: Beyene et al., 2010;Sellami et al., 2016;Taïbi et al., 2019;Hadour et al., 2020;Greece: Tigkas et al., 2012;Koutroulis et al., 2013;Nerantzaki et al., 2020;Middle East: Smiatek et al., 2014;Bucak et al., 2017;Gorguner et al., 2019;Italy: Senatore et el., 2011;Ravazzani et al., 2015;Pumo et al., 2016;Majone et al., 2016;Perra et al., 2018;D'Oria et al., 2019;Peres et al., 2019;Citrini et al., 2020). ...
Study region
Crati River Basin, Southern Italy, Central Mediterranean.
Study focus
We evaluate the combined effect of multiple global and regional climate model (GCM-RCM) combinations and bias correction (BC) methods on the hydrological impact of projected climate change. Under the representative concentration pathway RCP4.5, 15 EURO-CORDEX members, combining 6 GCMs and five high-resolution (0.11°) RCMs, provide the meteorological input for a spatially distributed hydrological model. RCM-derived input data are uncorrected and corrected through three empirical methods, leading to 60 different simulations for three ~30-year future periods in 2020–2096, compared to the baseline 1975–2005. The combined uncertainty of the climate models and correction methods is evaluated for the main hydrological variables using an analysis of variance (ANOVA) method.
New hydrological insights for the region
Results highlight a considerable agreement in projecting a decreasing trend of available water resources (on average, −70 % for snow, −8 % for root zone soil moisture and −17 % for river runoff in the period 2070–2096), due to the remarkable mean temperature increase and less accentuated precipitation reduction. The uncertainty evaluation shows that (1) the primary source of uncertainty is the driving GCM, and (2) BC methods smooth the projected hydrological impact in a not negligible way, especially concerning discharge (for each future period, the reduction projected without bias correction is about 3 % higher than with BC), therefore contributing to the total uncertainty.
... The above trends can be observed in all of the four climate change models (scenario RCP 8.5) that were used. Similar findings with regard to the trends of the above parameters under different climate change models and scenarios were reported from many other researchers [67,68] for the Eastern Mediterranean region. ...
Lakes, either artificial or natural, are greatly important as a component in their catchments’ hydrology, but also as ecosystem service providers. However, due to climate change, they have begun to face numerous problems with their water quality and quantity. Furthermore, general circulation models (GCMs) show future climate change with a reduction in rainfall and increase in temperature. The aim of the current study is to present an application where GCMs and state-of-the-art hydrological modelling system MIKE SHE/MIKE 11 are combined for assessing the response of a Greek lake in terms of its water balance and water level under climate change. Four general circulation models (GCMs; GFDL-CM3, MIROC-ESM-CHEM, MIROC-ESM, IPSL-CM5A-LR) for the extreme climate change scenario of RCP8.5 were used in the basin of Lake Zazari in Greece as a case study. Results showed that, by keeping the irrigated demands (the main water user) unchanged in the future, the lake exhibited a lower water level for all GCMs, fluctuating from −0.70 to −1.8 m for the mean (min) water level and from −0.30 to −1.20 m for the mean (max) water level. Instead of the above and by preserving the amount of withdraw water n from the lake at a certain percentage of inflows, the irrigated area should be reduced from 54.1% to 64.05% depending on the circulation model.
... and quality (Section 3.1.3.5) (Bucak et al. 2017), ecosys-39 Parts of this chapter have been published by Linares et al. (2020). tem degradation (Section 4.3) (e.g., Coll et al. 2010) and increased risk of forest fires (Section 4.3.2.1) (e.g., Turco et al. 2014), the vulnerability of the Mediterranean population to human health risks is increasing significantly. ...
... It remains challenging to quantitatively predict future lake volume changes, due to the lack of detailed information about regional lake watersheds and lack of numerical models that represent detailed lake dynamics and interactions with the environment. Water level changes of specific lakes have been projected based on observation-guided water budget analysis, indicating potential water level drop for Great Lakes 28 and substantial drying for the largest freshwater 43 and salt 44 lakes in the Mediterranean, which are consistent with our qualitative prediction shown in Fig. 1e, f. The projected lake changes under global warming may have already emerged in observations, which feature drying lakes in the Mediterranean 44,45 and expanding lakes in Tibetan Plateau 46 . ...
Lakes are critical natural resources that are vulnerable to climate change. In a warmer climate, lake evaporation is projected to increase globally, but with substantial variation between regions. Here, based on ensemble projections of climate and lake models and an attribution method, we show that future lake evaporation increase is strongly modulated by regional hydroclimate change. Specifically, a drying hydroclimate will amplify evaporation increase by enlarging surface vapor pressure deficit and reducing cloud shortwave reflection. Future lake evaporation increase is amplified in tropical America, the Mediterranean and Southeast China with drier future hydroclimates, and dampened in high latitudes and the Tibetan Plateau with wetter future hydroclimates. Such spatially coupled changes in lake evaporation and hydroclimate have important implications on regional lake water balance and volume change, which can aggravate water scarcity and flood risks.
... Water temperature, directly influenced by air temperature, is expected to rise across different habitats [6]. Additionally, the occurrence of heatwaves will likely increase, resulting in extended periods of drought associated with a low flow of freshwater systems, a decrease in water level and in dissolved oxygen concentrations [7][8][9]. Consequently, reduced dilution of freshwater streams will also affect ion balance levels [10,11]. These biotic changes will impact ecosystem dynamics and promote disruptions in species equilibrium [9,12]. ...
Climate change is expected to create environmental disruptions that will impact a wide array of biota. Projections for freshwater ecosystems include severe alterations with gradients across geographical areas. Life traits in bacteria are modulated by environmental parameters, but there is still uncertainty regarding bacterial responses to changes caused by climatic alterations. In this study, we used a river water microcosm model to evaluate how Aeromonas spp., an important pathogenic and zoonotic genus ubiquitary in aquatic ecosystems, responds to environmental variations of temperature and pH as expected by future projections. Namely, we evaluated bacterial growth, biofilm production and antimicrobial resistance profiles of Aeromonas species in pure and mixed cultures. Biofilm production was significantly influenced by temperature and culture, while temperature and pH affected bacterial growth. Reversion of antimicrobial susceptibility status occurred in the majority of strains and tested antimicrobial compounds, with several combinations of temperature and pH contributing to this effect. Current results highlight the consequences that bacterial genus such as Aeromonas will experience with climatic alterations, specifically how their proliferation and virulence and phenotypic resistance expression will be modulated. Such information is fundamental to predict and prevent future outbreaks and deleterious effects that these bacterial species might have in human and animal populations.
... Mediterranean climate regions have witnessed one of the most severe warming events in the world, and increases in the severity and longevity of droughts (Molina et al., 2020), threatening their sensitive endemic fauna and flora (Myers et al., 2000). Even though Mediterranean species are adapted to climatic fluctuations, climate change scenarios projected for the next decades will pose serious challenges to local wildlife (Bucchignani et al., 2018), particularly to freshwater organisms (Bucak et al., 2017). ...
Freshwater habitats worldwide are experiencing many threats from environmental and anthropogenic sources, affecting biodiversity and ecosystem functioning. In Africa, particularly in Mediterranean climate zones, rapid human population growth is predicted to have great impact on natural habitats besides naturally occurring events such as unpredictable drought frequency and severity. Here, we analyze the potential correlation between odonate assemblage conservation priority (measured with the Dragonfly Biotic Index: DBI) and the magnitude of climate change and human perturbation in African regions with a dominant Mediterranean climate, namely Northern (NAR: Morocco, Algeria and Tunisia) and Southern African region (SAR: South Africa). Using a compilation of studies assessing odonate assemblages in lotic and lentic habitats of both regions (295 sites in NAR and 151 sites in SAR), we estimated DBI, temporal change in average annual temperature (T), annual precipitation (P), and human footprint index (HFI) in each site, then we tested whether sites with different levels of DBI were associated with different magnitudes of climatic and anthropogenic change. We estimated past (between 1980–1999 and 2000–2018) and future changes (between 1980–1999 and 2081–2100) in T and P based on three CMIP6 scenarios representing low (SSP126), moderate (SSP245), and high emission (SSP585), as well as the change in HFI from 1993 to 2009. We found that assemblages with higher DBI (i.e. higher conservation priority) encountered lower increase in T and slightly greater decrease in P than assemblages with lower DBI (i.e. lower conservation priority) in NAR during 1980–2018, but are projected to experience higher increase in T and lower decrease in P in future projections for 2081–2100. In SAR, the increase in T was mostly similar across assemblages but the decline in P was higher for assemblages with higher DBI during 1980–2018 and 2081–2100, suggesting that assemblages of higher conservation priority in SAR are threatened by drought. While HFI showed an overall increase in NAR but not in SAR, its temporal change showed only minor differences across assemblages with different DBI levels. We discuss the importance of management plans to mitigate the effects of climatic and anthropogenic threats, so improving conservation of odonate assemblages in these regions.
... and quality (Section 3.1.3.5) (Bucak et al. 2017), ecosystem degradation (Section 4.3) (e.g., Coll et al. 2010) and increased risk of forest fires (Section 4.3.2.1) (e.g., Turco et al. 2014), the vulnerability of the Mediterranean population to human health risks is increasing significantly. ...
The Mediterranean Basin is a significant area will be affected by drought and water scarcity in future. In this context, Bursa urban area, the fourth largest city in terms of population in Türkiye was used for quantification. A high-resolution global climate model of MPI-ESM-MR based RCP4.5 and 8.5, and population projections based on arithmetic and exponential growth models until 2100 was utilised. Support Vector Machine (SVM) regression was established between observed precipitation, evapotranspiration, runoff and reservoir volume for the reference period. Climate model outputs like precipitation and derived outputs such as evapotranspiration based on Penman-Monteith, runoff from SCS-Curve Number were used for SVM future dam volume prediction. Reference (observed data) and near and distant future (projected) dam volumes were converted to the Standardized Reservoir Index (SRI), and water scarcity as water per capita was also calculated. As a result, increased droughts and extreme conditions are identified in the near and distant future compared to the reference period. In addition, decrease in water per capita was determined with respect to the reference period. Therefore, results demonstrate that water scarcity is worsened by both semi-arid climate and population in urban area. Hence, water management in urban areas should address climatic variability and economic processes together.
Lakes are an essential part of the terrestrial water system in which storage changes are controlled by water balance
and human impact. Although there are some attempts to define storage changes on a global scale, examination
of spatial relations is poorly quantified. In this study, therefore, lake storage changes have been investigated
using remote-sensing-derived data around the globe. Hence, 372 artificial/natural lakes were obtained, covering
between 1992 and 2019. Watersheds belong to river was extracted via HydroSHED data. Based on watershed,
dominant climate types were determined via Köppen-Geiger classification. Similarly, the areal average CRU TS
v.4.05 monthly gridded precipitation time series and human footprint data based on watersheds were obtained
to understand the drivers of lake storage changes. The nonparametric Mann-Kendall and Sen's slope trend analyses
were applied to the lake storage change and precipiation values in order to determine long-term increases and
decreases. A bivariate map was constructed between storage changes trend vs precipitation trend and human
footprint to reveal the drivers of lake storage changes in terms of spatial aspects. The trend analysis and bivariate
map results show that North America, the East African Highlands, and the Tibet plateau are important increasing
hotspots, where precipitation is a significant driver for storage oscillations, except for the Tibet plateau. Besides,
the Brazilian Highlands, Pacific Mountain System, and Intermontane of conterminous USA are other decreasing
hotspots in which human footprint and decreasing precipitation collectively affect these changes. Furthermore,
results clearly show that anthropogenic influence is low in the northern and mountainous areas, and storage
changes have a linear relationship with precipitation. In contrast, intense human climate interaction influences
lake changes in plains areas and arid/temperate climates.
The accurate and reliable simulation and prediction of runoff in the Beas River Basin are becoming more and more important due to the increased uncertainty posed by climate change, which is making it difficult to manage water resources efficiently. In order to minimize the effect of flash floods, estimating the accurate peak flow is essential. It can be challenging to comprehend and anticipate peak flow due to natural streamflow variance as well as the streamflow management offered by dams and reservoirs. Which makes it difficult to mimic hydrologic behavior on a daily scale with reliable accuracy. This study evaluated the efficacy of physics-aided machine learning (ML) based regression models for modeling streamflow in combination with process-based hydrological SWAT (soil and water assessment tool). Performance of eight machine learning (ML) models including linear regression (LR), multi-layer perceptron (MLP), light gradient-boosting machine (LGBM), extreme gradient boosting (XGBoost), kernel ridge (KR), elastic net (EN), Bayesian ridge (BR), and gradient boosting (GB) have been analyzed and compared with the calibrated-SWAT (cSWAT) model. The Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE) and coefficient of determination (R2) were used to assess the effectiveness of both models. Results showed that the uncalibrated SWAT in combination with ML regression models (cSWAT-ML) performed well and found comparable to calibrated SWAT (cSWAT), though, few ML regression models in combination with uncalibrated SWAT (uSWAT-MLmodels models) performed superior. cSWAT model performed well with R2 values of 0.73, RMSE value of 276.92 m3/s and NSE value of 0.72. In uSWAT-ML, EN and BR have obtained better results with R2 values of 0.89 and 0.89, NSE values of 0.87 and 0.87, and RMSE values of 158.31 m3/s and 159.48 m3/s. The approached uSWAT-ML models have effectively predicted the peak stream flow rates with models BR and EN have predicted with better results of R2 value of 0.71 each. This study’s findings highlight the potential of all the eight ML models as promising techniques for predicting the peak flow discharge values when uncalibrated process-based models are combined.
Water budget components of endorheic basins of semi-arid and karstic characters are difficult to assess. In this study, we attempt to estimate the water budget components of the Konya Endorheic Basin (KEB), which is a semi-arid, karstic basin in central Anatolia, using The Gravity Recovery and Climate Experiment mission (GRACE) observations and Global Land Data Assimilation System (GLDAS) data over the period 2002-2019. We also investigate the trends and sub-trends in the time series of the hydrometeorological parameters. The results indicate that the available water potential in the basin has a decreasing trend over the study period. Precipitation and evapotranspiration show increasing trends in the basin, however, the other hydrometeorological parameters demonstrate decreasing trends. Both Terrestrial Water Storage Anomaly (TWSA) and groundwater level decrease significantly (20.21 mm/yr and 122.34 mm/yr, respectively). The dry 2008 and subsequent wet year created a hydrological breaking point in the time series. The weights of soil moisture and groundwater storages are relatively large amongst the TWSA components (49.61% and 33.12%, respectively). The surface water storage anomaly comes at the third place with a 14% weight. It is assessed that the groundwater storage system responds to precipitation with a delay of 6 months. Limestone zones respond more sharply to groundwater depletion than alluvial zones. It should be noted that the GRACE and GLDAS data could be used together to successfully estimate the water budget components for sustainable management of the limited water resources of the basin.
Climate change will likely increase the frequency and magnitude of extreme precipitation events and floods, increasing design peak flows that could lead to underestimates in current spillway capacity. Therefore, new methodologies for hydrological dam safety assessment considering climate change are required. This study presents a methodology that considers the impact of climate change on both inflow hydrographs and initial reservoir water levels. Moreover, the uncertainty in the procedure is assessed. The methodology is applied to the Eugui Dam in the River Arga catchment (Spain). An ensemble of 12 climate models is used. The results show an increase in the maximum reservoir water level during flood events and in the overtopping probability in the Representative Concentration Pathway 8.5 (RCP 8.5 scenario), especially in the 2071–2100 time window. The proposed methodology can be useful to assess future hydrological dam safety, fulfilling the requirements of recent regulations to consider the impact of climate change on dams.
In the Mediterranean region, annual mean air temperature will continue to increase during the 21st century, while seasonal precipitation is expected to decrease and extreme events to be more frequent. Human-induced climate change will severely impact aquatic ecosystems. A subdecadal stratigraphic diatom record of Lake Montcortès (central Pyrenees) was investigated, focusing on the potential responses of diatoms to anthropogenic warming and catchment alteration. The study includes the end of the Little Ice Age (LIA), the transition to the industrial and postindustrial eras, and the recent global warming and its current acceleration. Sediment samples were treated and diatoms taxonomically identified. Relationships between diatom taxa abundances and climatic (temperature and precipitation) and environmental (land use, soil erosion, and eutrophication) variables were investigated using multivariate statistical methods. The results indicate that, from ca. 1716 to 1971 CE, the diatom community was dominated by Cyclotella cyclopuncta and showed small perturbations, despite the pressure of important stressors such as strong cooling episodes, droughts and an intense use of the lake for hemp retting during the 18th and 19th centuries. However, during the 20th century, other centric species gained relevance, and from the 1970s on, Cyclotella ocellata competed with C. cyclopuncta for dominance. These changes coincided with pulse-like disturbances in the form of extreme rainfall events along with the gradual 20th century increase in global temperature. These perturbations affected the planktonic diatom community and led to instability dynamics. The benthic diatom community did not reflect any comparable shifts under the effect of the same climatic and environmental variables. Because heavy rainfall episodes are likely to intensify with current climate change in the Mediterranean region, their importance as stressors of planktonic primary producers should be taken into account as potential disrupters of biogeochemical cycles and trophic networks of lakes and ponds.
The availability of water at the regional and river basin scales in the future will be significantly impacted by climate change. Effective water management in the sub-basin is essential for ensuring long-term sustainability in the face of changing climatic conditions. The Maner River basin is a significant contributor to the Godavari River, and agriculture serves as the primary source of income for the majority of individuals residing in the subbasin. Nearly 50–65% of irrigational fields in the Maner basin are cultivated using local Tank Cascade Systems (TCS) and reservoirs that are managed by monsoon precipitation. The regional level climate change impact on the water resources of these tank cascade systems is important for sustainable management of water resources. In this study, The NEX-GDDP RCM models of CCSM4, MPI-ESM-LR and MIROC-ESM-CHEM were utilized to examine climate patterns during historical and future periods under RCP 4.5 and RCP 8.5 scenarios. The Maner sub-basin and KTCS (Katakshapur Tank Cascade System) were modeled using the SWAT hydrological model to simulate runoff and water availability. The average monsoon (July-October) streamflow increase in the Maner basin during the near, mid, and far futures is projected to be 47%, 66%, and 114% under the RCP 4.5 scenario, and 53%, 72%, and 69% under the RCP 8.5 scenario, respectively. Excess flow may overflow from Ramchandrapur, Mallampalli, and Dharmaraopalli tanks to the downstream Katakshapur tank since it can accommodate the up to 18.91 Mm3. To enhance water management in response to climate change, one potential adaptation strategy is to utilize the surplus inflow to refill downstream artificial ponds, which can aid in the replenishment of groundwater and the provision of water supply to tail end tanks.
Tanks are the small water storage reservoirs colonized in arid and semi-arid regions of southern India. Tanks were constructed to collect the local runoff and have been an important source of irrigation in Andhra Pradesh, Karnataka, Tamilnadu and Telangana states. The irrigation tanks are accounted for more than one-third of the irrigated area in South India. Accordingly, there is a need to address hydrological issues of the irrigation tanks for effective utilization and management of water within the tank system and river basin. The semi-arid region of Telangana has numerous ungauged tanks. Hence, in this paper, an attempt was made to model the hydrologic processes of the ungauged tanks in the selected study area Salivagu watershed, Telangana, India. This study used geospatially extracted tank area and volumes from the Water Body Information System (WBIS) provided by Bhuvan, National Remote Sensing Centre (NRSC), India. The SWAT hydrological model was used to simulate the flow in the Salivagu river by considering the tanks in the watershed. The model performance statistics of NSE, R2 and PBIAS are 0.84, 0.78 and −5.3 during calibration and 0.92, 0.93 and −10.8 during validation, respectively. The study evidenced that; SWAT model can be effectively used for flow simulation of the watershed with tanks using WBIS data of NRSC-Bhuvan.
Havzalarda aletli gözlemler havza süreçlerini anlamak için oldukça önemli bir konuma sahip olmasına rağmen tüm alanlarda aletli gözlem verilerini bulmak oldukça zordur. Bu çalışma ile akım gözlem istasyonu (AGİ) olmayan havzalarda düşük/yüksek akım karakteristiklerinin SWAT ile modellenmesi ve gözlemle arasındaki farklılıklarının karşılaştırılması amaçlanmıştır. Bu amaçla, Bartın Çayı havzası örnek alan olarak seçilmiş ve ALOS SYM temelinde 90 adet alt-havza çıkarılmıştır. Bu havzalarda arazi kullanımı, eğim ve toprak verisi çakıştırılarak Hidrolojik Tepki Birimleri/HRU elde edilmiştir. HRU ve havza içinde tüm hidrolojik süreçler su dengesi temelinde elde edilen meteorolojik verilerle simüle edilmiştir. Model sonuçları, E13A031 istasyonuna dayalı olarak SWAT-CUP vasıtasıyla kalibre edilmiştir. Modellenen sonuçların havza içi süreçleri modellemek için yeterli olduğu görülmüştür. Elde edilen sonuçlara göre hem düşük hem de yüksek akımlara ait farklı zaman serisi karakteristikleri (büyüklük, sıklık, süre, zamanlama) hesaplanmış ve gözlem verisiyle karşılaştırılmıştır. Modellenen düşük ve yüksek akım metrikleri genel olarak gözlem ile uyuşsa da, birçok belirsizlik kaynağından dolayı bazı akım metriklerini fazla veya düşük hesapladığını göstermiştir. Öte yandan, tüm alt-havzalara ait metrikler hesaplanmıştır. Sonuçlara göre, Kocanaz havzası diğer havzalara oranla düşük ve yüksek akım metriklerinde farklılık yansıtmıştır. Hidrolojik modellemeler bu bağlamda iklim değişikliği ve arazi kullanımı değişiminin anlaşılması açısından planlama ve havza yönetimi açısından fırsatlar sunmaktadır.
Data limitations often challenge the reliability of water quality models, especially in intensively managed watersheds. While numerous studies report successful hydrological model setup and calibration, few have addressed in detail the data challenges for multisite and multivariable model calibration to an intensively managed watershed. In this study, we address some of these challenges based on our reflective experience calibrating the Soil and Water Assessment Tool (SWAT) to the Upper Sangamon River Watershed in central Illinois based on daily flow, annual crop yield, and monthly sediment, nitrate, and total phosphorus loads. We highlight some challenges in SWAT calibration processes due to data errors and inconsistencies, and insufficient precipitation and water quality observations. Following, we demonstrate the merits of additional weather and water quality observations that could help reduce input uncertainties, and we provide suggestions for selecting appropriate observations for the model calibration. After dealing with the data issues, we show that the SWAT model could be calibrated with acceptable results for the case study watershed.
Lakes are major surface water resource in semi-arid regions, providing water for agriculture and domestic use. Prediction of future water availability in lakes of semi-arid regions is important as they are highly sensitive to climate variability. This study is to examine the water level fluctuations in Pakhal Lake, Telangana, India using a combination of a process-based hydrological model and machine learning technique under climate change scenarios. Pakhal is an artificial lake built to meet the irrigation requirements of the region. Predictions of lake level can help with effective planning and management of water resources. In this study, an integrated approach is adopted to predict future water level fluctuations in Pakhal Lake in response to potential climate change. This study makes use of the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset which contains 21 Global Climate Models (GCMs) at a resolution of 0.25 × 0.25° is used for the study. The Reliability Ensemble Averaging (REA) method is applied to the 21 models to create an ensemble model. The hydrological model outputs from Soil and Water Assessment Tool (SWAT) are used to develop the machine-learning based Support Vector Regression (ν-SVR) model for predicting future water levels in Pakhal Lake. The scores of the three metrics, correlation coefficient (R2), RMSE and MEA are 0.79, 0.018 m, and 0.13 m, respectively for the training period. The values for the validation periods are 0.72, 0.6, and 0.25 m, indicating that the model captures the observed lake water level trends satisfactorily. The SWAT simulation results showed a decrease in surface runoff in the Representative Concentration Pathways (RCP) 4.5 scenario and an increase in the RCP 8.5 scenario. Further, the results from ν-SVR model for the future time period indicate a decrease in future lake levels during crop growth seasons. This study aids in planning of necessary water management options for Pakhal Lake under climate change scenarios. With limited observed datasets, this study can be easily extended to the other lake systems.
Climate hazards and vulnerabilities in cities are multidimensional. Natural features determine heat, floods and wildfires. Social features determine vulnerability and resilience. This study examined multidimensional hazards, vulnerabilities, and resilience in Haifa, a socially diverse Mediterranean city. Spatial indices of heatwaves, floods, wildfires and social vulnerability were developed by Geographic Information Systems geoprocessing functions using Digital Elevation Model, land use and welfare data. An online survey assessing risk perceptions, sense of danger and community resilience was distributed to residents (N = 549), and geocoded using street identification. The results show that climate hazards and vulnerabilities vary within the city and reflect its geographical and social characteristics: lower regions are prone to heat and floods and elevated neighborhoods to wildfires. All zones and segments of the population are in certain danger, but climate hazards and vulnerabilities are heterogeneous and unequally distributed, with certain neighborhoods more exposed. The downtown area is most vulnerable in social features, yet its residents have higher resilience perceptions compared to uptown, where the main hazard is wildfires and the main vulnerability is aging. Implications for urban climate policy: local stressors should be mitigated at the neighborhood level by investing in suitable infrastructure and fostering community resilience.
The great civilizations of the world flourished at the banks of the major rivers like Indus, Ganges, Nile, Tigris, Yellow River. In the ancient times, the population was less and resources were enormous. The pollution levels were almost nonexistent and the carrying and regeneration capacity of the earth was high. The waste generated was not toxic and killing as it is these days. The lifestyle of human beings was very much in consonance with natural capacity of assimilation and regeneration of the nature. Over the decades and centuries, the life began to change with the emergence of industrialization and new kind of urbanization. The change was slow and restricted in the initial decades, but the things changed drastically in the last few decades. In the initial decades, with the emergence of new kind of growth and development, the change was not very prominent but with increasing population and pollution, there are many human induced pressures like industrialization, urbanization, land use pattern, waste generation, plastic, nonjudicious use of water, electricity and other natural resources, and natural resource based products. They act as drivers to change in the ecological balance. The change is visible in every sphere of our lives. It has hampered almost every part of the earth. In addition to these there are many other anthropogenic factors responsible for the degradation of the rivers which have been explained in the chapter. Thus, based on the enormous significance of the rivers and their unique role in the survival of the human civilization, this chapter is an attempt to explain the significance of the river ecosystems on one hand and anthropogenic pressures as the prime and key challenges to the deteriorating condition of the rivers along with the ways to overcome such challenges on the other with river restoration as one of the key steps.
In the semi-arid regions of South Asia, tank systems are the major source of irrigation. In India, the Telangana state government has initiated the Mission Kakatiya program to rejuvenate irrigation tank systems. Understanding the hydrological processes that supply water to these systems is critical to the success of these types of programs in India. The current study attempted to comprehend the hydrological processes and flow routing in the Salivagu watershed tank cascade system in Telangana. There are a lot of ungauged tank cascade systems in this region. Soil Water Assessment Tool (SWAT), a physically-based model, was used to simulate flow patterns in the Salivagu watershed with and without tank systems. The geospatially extracted area and volume were used for this study provided by WBIS-Bhuvan-NRSC. Additionally, the Katakshapur Tank Cascade System (KTCS) was chosen to analyze the water availability in each tank using the water balance approach. The Salivagu watershed flow simulation without tanks overestimated streamflow. The volume difference in flow between with and without tank was 606 Mm3, 615.9 Mm3, and 1011 Mm3 in 2017, 2018, and 2019, respectively. The SWAT simulated volumes of the Ramchandrapur and Dharmaraopalle tanks in KTCS were merely satisfied because the tank size was less than 0.7 km2 and the storage capacity was up to 1 Mm3. Due to tank sizes more than 0.8 km2 and capacities greater than 2 Mm3, the Mallampalli and Katakshapur tank simulation findings were in good agreement with WBIS-Bhuvan-NRSC. This research advances our understanding of the hydrological processes in ungauged cascading tank systems in tropical semi-arid regions.
Soil erosion caused by climate change and changes in land use increases or decreases depending on the geographic location, climate scenarios, precipitation patterns, topographic potential, and land management practices. Forf this reason, the impact of climate change on soil erosion needs to be analysed at the regional and/or local levels. Bearing in mind that climate and land use will change in the future, the purpose of this chapter is to quantify the current intensity of soil erosion, taking the Vranjska Valley (southern Serbia) as an example, to simulate soil losses for 2050 and 2100 due to changes in climate and land use, and to analyse the spatial and temporal grouping of clusters of soil loss for 2015 and 2100. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) of the sediment delivery ratio (SDR) model integrated with the EBU-POM (Eta Belgrade University-Princeton Ocean Model) regional climate model was used with the aim of quantifying erosion intensity in the Vranjska Valley region. The results of research in the Vranjska Valley region show that average erosion intensity during 2015 amounted to 5.33 t ha⁻¹ yr⁻¹. According to the A1B scenario, average annual soil loss is expected to fall for the two periods in the future, by 6.6% (2050) and 41.8% (2100), mainly as a result of a reduction in the rainfall erosivity factor. Measures which could protect soil effectively in the future include reforestation with drought-resistant species, soil conservation, no-till practices, and an evaluation of current erosion models.
Climate change is known to affect world’s lakes in many ways. Lake warming is perhaps the most prominent impact of climate change but there is evidence that changes of precipitation and wind speed over the surface of the lakes may also have a significant effect on key limnological processes. With this study we explored the interannual trends of surface temperature, precipitation, and wind speed over 18 lakes of Greece using ERA5-Land data spanning over a period of almost four decades. We used generalized additive models (GAMs) to conduct time-series analysis in order to identify significant trends of change. Our results showed that surface temperature has significantly increased in all lakes with an average rate of change for annual temperature of 0.43 °C decade−1. With regard to precipitation, we identified significant trends for most lakes and particularly we found that precipitation decreased during the first two decades (1981–2000), but since 2000 it increased notably. Finally, wind speed did not show any significant change over the examined period with the exception for one lake. In summary, our work highlights the major climatic changes that have occurred in several freshwater bodies of Greece. Thus, it improves our understanding on how climate change may have impacted the ecology of these important ecosystems and may aid us to identify systems that are more vulnerable to future changes.
The Konya Closed Basin (KCB) in Turkey has a cold semiarid to warm Mediterranean climate and hosts the largest Turkish freshwater lake, Lake Beyşehir, and the iconic saline Lake Tuz. Using published as well as our own ground-truth and remote sensing data, we provide (1) a brief description of the paleoenvironmental changes in the KCB; followed by (2) a detailed description of the changes in land use, crop farming, groundwater and surface water levels, and climate; and (3) associated changes in lake water surface area and salinity as well as in waterbird and fish communities during the past 40 years. The KCB is intensively farmed, and the farming of mainly water intensive crops has increased substantially, especially since 2000. This, combined with climate warming, has led to a substantial rate of reduction of the groundwater level (up to 1 m/yr) and the surface area of the lakes and wetlands, followed by an increase in salinisation, and even complete loss of several wetlands. Three globally threatened waterbird species face extinction in the basin, and 18 of the 62 previous breeding species have already been lost. The KCB has 38 fish species, of which 74% are endemic and 61% are considered threatened or near threatened. Modelling projections using various climate and land use scenarios predict serious additional reductions of the water level in the future due to climate change, leading to deterioration (or complete loss) of lake ecosystems and the services they provide.
Global warming is exacerbating weather, and climate extremes events and is projected to aggravate multi-sectorial risks. A multiplicity of climate hazards will be involved, triggering cumulative and interactive impacts on a variety of natural and human systems.
An improved understanding of risk interactions and dynamics is required to support decision makers in their ability to better manage current and future climate change risks. To face this issue, the research community has been starting to test new methodological approaches and tools, including the application of Machine Learning (ML) leveraging the potential of the large availability and variety of spatio-temporal big data for environmental applications. Given the increasing attention on the application of ML methods to Climate Change Risk Assessment (CCRA), this review mapped out the state of art and potential of these methods to this field of research. Scientometric and systematic analysis were jointly applied providing an in-depth review of publications across the 2000–2020 timeframe. The resulting output from the analysis showed that a huge variety of ML algorithms have been already applied within CCRA, among them, the most recurrent are Decision Tree, Random Forest, and Artificial Neural Network. These algorithms are often applied in an ensemble or hybridized way to analyze most of all floods and landslides risk events. Moreover, the application of ML to deal with remote sensing data is consistent and effective across reviewed CCRA applications, allowing the identification and classification of targets and the detection of environmental and structural features. On the contrary concerning future climate change scenarios, literature seems not to be very widespread into scientific production, compared to studies evaluating risks under current conditions. The same lack can be noted also for the assessment of cascading and compound hazards and risks, since these concepts are recently emerging in CCRA literature but not yet in combination with ML-based applications.
مدلهای مختلفی جهت شرح و پیشبینی هیدرولوژی آبخیز ارائه شده که از نظر اهداف و مقیاس زمانی و مکانی متفاوتاند. در این مطالعه از مدل SWAT جهت شبیهسازی پاسخ هیدرولوژیکی حوضه دویرج استفاده شد. ورودیهای اصلی مدل شامل اطلاعات هواشناسی، نقشه مدل رقومی ارتفاعی حوضه، نقشه خاک¬شناسی و نقشه کاربری اراضی است. با استفاده از مدل SWAT_CUP با وارد کردن داده¬های مشاهداتی دبی خروجی از حوضه و انجام مراحل واسنجی طی دوره 1996 تا 2008 کارایی مدل افزایش یافت و سپس مرحله اعتبارسنجی از سال 2009 تا 2012 توانایی مدل را برای شبیه¬سازی بارش- رواناب و استفاده از آن را برای اهداف مطالعه تایید نمود. میانگین دراز¬مدت رطوبت خاک در سال 1996، 2008 و 2013 به¬ترتیب برابر با 24/524، 59/337 و 77/468میلی¬متر می¬باشد. مطالعه اجزای بیلان شبیه¬سازی شده توسط مدل SWAT نشان داد که برای سال 1996 علارغم بارندگی شدید بیلان آبی تقریباً برابر صفر است؛ مشخص شد عمده تلفات در این سال به¬وسیله¬ی تبخیر و تعرق اتفاق افتاد. برای سالهای 2008 و 2013 بیلان آبی مثبت است زیرا مجموع تبخیر و تعرق، جریان برگشتی به رودخانه، جریان جانبی، نفوذ و رواناب سطحی از مجموع بارش کمتر است.
The SWAT model was modified to simulate the hydrologic and chemical response of karstic systems and assess the impacts of land use management and climate change of an intensively managed Mediterranean watershed in Crete, Greece. A methodology was developed for the determination of the extended karst area contributing to the spring flow as well as the degree of dilution of nitrates due to permanent karst water volume. The modified SWAT model has been able to capture the temporal variability of both karst flow and surface runoff using high frequency monitoring data collected since 2004 in addition to long term flow time series collected since 1973. The overall hydrologic budget of the karst was estimated and its evaporative losses were calculated to be 28% suggesting a very high rate of karst infiltration. Nitrate chemistry of the karst was simulated by calibrating a dilution factor allowing for the estimation of the total karstic groundwater volume to approximately 500 million m3 of reserve water. The nitrate simulation results suggested a significant impact of livestock grazing on the karstic groundwater and on surface water quality. Finally, simulation results for a set of climate change scenarios suggested a 17% decrease in precipitation, 8% decrease in ET and 22% decrease in flow in 2030–2050 compared to 2010–2020. A validated tool for integrated water management of karst areas has been developed, providing policy makers an instrument for water management that could tackle the increasing water scarcity in the island.
An ecohydrological watershed model can be used to develop an efficient watershed management plan for improving water quality. However, karst geology poses unique challenges in accurately simulating management impacts to both surface and groundwater hydrology. Two versions of the Soil and Water Assessment Tool (SWAT), Regular-SWAT and Topo-SWAT (which incorporates variable source area hydrology), were assessed for their robustness in simulating hydrology of the karstic Spring Creek watershed of Centre County, Pennsylvania, USA. Appropriate representations of surface water – groundwater interactions and of spring recharge – discharge areas were critical for simulating this karst watershed. Both Regular-SWAT and Topo-SWAT described the watershed discharge adequately with daily Nash-Sutcliffe efficiencies (NSE) ranging from 0.77 to 0.79 for calibration and 0.68–0.73 for validation, respectively. Because Topo-SWAT more accurately represented measured daily streamflow, with statistically significant improvement of NSE over Regular-SWAT during validation (p-value=0.05) and, unlike Regular-SWAT, had the capability of spatially mapping recharge/infiltration and runoff generation areas within the watershed, Topo-SWAT was selected to predict nutrient and sediment loads. Total watershed load estimates (518t nitrogen/year, 45t phosphorus/year, and 13600t sediment/year) were within 10% of observed values (−9.2% percent bias for nitrogen, 6.6% for phosphorous, and 5.4% for sediment). Nutrient distributions among transport pathways, such as leaching and overland flow, corresponded with observed values. This study demonstrates that Topo-SWAT can be a valuable tool in future studies of agricultural land management change in karst regions.
Regional climates are the complex outcome of local physical processes and the non-local responses to large-scale phenomena such as the El Niño-Southern Oscillation (ENSO) and other dominant modes of climate variability. The dynamics of regional climates are determined by local weather systems that control the net transport of heat, moisture and momentum into a region. Regional climate is interpreted in the
widest sense to mean the whole joint probability distribution of climate variables for a region including the time mean state, the variance and co-variance and the extremes.
This chapter assesses the physical basis of future regional climate change in the context of changes in the following types of phenomena: monsoons and tropical convergence zones, large-scale
modes of climate variability and tropical and extratropical cyclones. Assessment
of future changes in these phenomena is based on climate model projections (e.g., the Coupled Model Intercomparison Project Phase 3 (CMIP3) and CMIP5 multi-model ensembles described in Chapter 12) and an understanding of how well such models represent the key processes in these phenomena. More generic processes relevant to regional climate change, such as thermodynamic processes and land–atmosphere feedback processes, are assessed in Chapter 12. Local processes such as snow–albedo feedback, moisture feedbacks due to local vegetation, effects of steep complex terrain etc. can be important for changes but are in general beyond the scope of this chapter. The main focus here is on large-scale atmospheric phenomena rather than more local feedback processes or impacts such as floods and droughts.
Sections 14.1.1 to 14.1.3 introduce the three main classes of phenomena addressed in this Assessment and then Section 14.1.4 summarizes their main impacts on precipitation and surface temperature. Specific climate phenomena are then addressed in Sections 14.2 to 14.7, which build on key findings from the Fourth Assessment Report, AR4 (IPCC, 2007a), and provide an assessment of process understanding
and how well models simulate the phenomenon and an assessment of future projections for the phenomena. In Section 14.8, future regional climate changes are assessed, and where possible, interpreted in terms
of future changes in phenomena. In particular, the relevance of the various phenomena addressed in this chapter for future climate change in the regions covered in Annex I are emphasized. The regions are those
defined in previous regional climate change assessments (IPCC, 2007a, 2007b, 2012). Regional Climate Models (RCMs) and other downscaling tools required for local impact assessments are assessed in Section 9.6 and results from these studies are used where such supporting information adds additional relevant details to the assessment.
14.1.1 Monsoons and Tropical Convergence Zones
The major monsoon systems are associated with the seasonal movement of convergence zones over land, leading to profound seasonal changes in local hydrological cycles. Section 14.2 assesses current understanding of monsoonal behaviour in the present and future climate, how monsoon characteristics are influenced by the large-scale tropical modes of variability and their potential changes and how the monsoons in turn affect regional extremes. Convergence zones over the tropical oceans not only play a fundamental role in determining regional climates but also influence the global atmospheric circulation. Section 14.3 presents an assessment of these and other important tropical phenomena.
A semi-distributed hydrological model of the Niger River above and including the Inner Delta is developed. GCM-related uncertainty in climate change impacts are investigated using seven GCMs for a 2°C increase in global mean temperature, the hypothesised threshold of “dangerous” climate change. Declines in precipitation predominate, although some GCMs project increases for some sub-catchments, whilst PET increases for all scenarios. Inter-GCM uncertainty in projected precipitation is three to five times that of PET. With the exception of one GCM (HadGEM1), which projects a very small increase (3.9%), river inflows to the Delta decline. There is considerable uncertainty in the magnitude of these reductions, ranging from 0.8% (HadCM3) to 52.7% (IPSL). Whilst flood extent for HadGEM1 increases (mean annual peak +1405 km2/+10.2%), for other GCMs it declines. These declines range from almost negligible changes to a 7903 km2 (57.3%) reduction in the mean annual peak.
Orange is a machine learning and data mining suite for data analysis through Python scripting and visual programming. Here we report on the scripting part, which features interactive data analysis and component-based assembly of data mining procedures. In the selection and design of components, we focus on the flexibility of their reuse: our principal intention is to let the user write simple and clear scripts in Python, which build upon C++ implementations of computationallyintensive tasks. Orange is intended both for experienced users and programmers, as well as for students of data mining. © 2013 Janez Demšar, Tomaž Curk, Aleš Erjavec, Črt Gorup, Tomaž Hočevar, Mitar Milutinovič, Martin Možina, Matija Polajnar, Marko Toplak, Anže Starič, Miha Stajdohar, Lan Umek, Lan Žagar, Jure Žbontar, Marinka Žitnik and Blaž Zupan.
The impacts of climate and land use changes on streamflow and sediment export were evaluated for a humid (São Lourenço) and a dry (Guadalupe) Mediterranean catchment, using the SWAT model. SWAT was able to produce viable streamflow and sediment export simulations for both catchments, which provided a baseline for investigating climate and land use changes under the A1B and B1 emission scenarios for 2071-2100. Compared to the baseline scenario (1971-2000), climate change scenarios showed a decrease in annual rainfall for both catchments (humid: -12%; dry: -8%), together with strong increases in rainfall during winter. Land use changes were derived from a socio-economic storyline in which traditional agriculture is replaced by more profitable land uses (i.e. corn and commercial forestry at the humid site; sunflower at the dry site). Climate change projections showed a decrease in streamflow for both catchments, whereas sediment export decreased only for the São Lourenço catchment. Land use changes resulted in an increase in streamflow, but the erosive response differed between catchments. The combination of climate and land use change scenarios led to a reduction in streamflow for both catchments, suggesting a domain of the climatic response. As for sediments, contrasting results were observed for the humid (A1B: -29%; B1: -22%) and dry catchment (A1B: +222%; B1: +5%), which is mainly due to differences in the present-day and forecasted vegetation types. The results highlight the importance of climate-induced land-use change impacts, which could be similar to or more severe than the direct impacts of climate change alone.
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This chapter reviews the scientific evidence published since the IPCC Fourth Assessment Report (AR4) on observed and projected impacts of anthropogenic climate change in Europe and adaptation responses. The geographical scope of this chapter is the same as in AR4 with the inclusion of Turkey. Thus, the European region includes all countries from Iceland in the west to the Russian Federation (west of the Urals) and the Caspian Sea in the east, and from the northern shores of the Mediterranean and Black Seas and the Caucasus in the south to the Arctic Ocean in the north. Impacts above the Arctic Circle are addressed in Chapter 28 and impacts in the Baltic and Mediterranean Seas in Chapter 30. Impacts in Malta, Cyprus, and other island states in Europe are discussed in Chapter 29. The European region has been divided into five sub-regions (see Figure 23-1): Atlantic, Alpine, Southern, Northern, and Continental. The sub-regions are derived by aggregating the climate zones developed by Metzger et al. (2005) and therefore represent geographical and ecological zones rather than political boundaries. The scientific evidence has been evaluated to compare impacts across (rather than within) sub-regions, although this was not always possible depending on the scientific information available. 23.1.1. Scope and Route Map of Chapter, The chapter is structured around key policy areas. Sections 23.3 to 23.6 summarize the latest scientific evidence on sensitivity climate, observed impacts and attribution, projected impacts, and adaptation options, with respect to four main categories of impacts: • Production systems and physical infrastructure • Agriculture, fisheries, forestry, and bioenergy production • Health protection and social welfare • Protection of environmental quality and biological conservation The benefit of assessing evidence in a regional chapter is that impacts across sectors can be described, and interactions between impacts can be identified. Further, the cross-sectoral decision making required to address climate change can be reviewed. The chapter also includes sections that were not in AR4.
Most climate change projections show important decreases in water availability in the Mediterranean region by the end of this century. We assess those main climate change impacts on water resources in three medium-sized catchments with varying climatic conditions in north-eastern Spain. A combination of hydrological modelling and climate projections with B1 and A2 IPCC emission scenarios is performed to infer future stream flows. The largest reduction (34% mean value for 2076-2100) of stream flows is expected in the headwaters of the two wettest catchments, while lower decreases (25% mean value for 2076-2100) are expected in the drier one. In all three catchments, autumn and summer are the seasons with the most notable projected decreases in stream flow, 50% and 30%, respectively. Thus, ecological flows might be noticeably impacted by climate change in the catchments, especially in the headwaters of those wet catchments.
Significance
Increasing concentrations of greenhouse gases in the atmosphere are widely expected to influence global climate over the coming century. The impact on drought is uncertain because of the complexity of the processes but can be estimated using outputs from an ensemble of global models (hydrological and climate models). Using an ensemble of 35 simulations, we show a likely increase in the global severity of drought by the end of 21st century, with regional hotspots including South America and Central and Western Europe in which the frequency of drought increases by more than 20%. The main source of uncertainty in the results comes from the hydrological models, with climate models contributing to a substantial but smaller amount of uncertainty.
Key-words: fish, macrophytes, water level fluctuation, water quality, zooplankton Water level fluctuations play a significant role in the lake nutrient dynam-ics, and consequently may have a strong influence on the biological com-munities and productivity. In this article we investigated the effects of a long term water level reduction on key chemistry parameters and major biological communities in an eastern Mediterranean lake. Our approach is based on temporal data regarding water quality, fish, zooplankton and aquatic vegetation that are representative of different water level periods. The results revealed significant correlations between water level, conduc-tivity and chloride concentration suggesting a clear effect of the water level reduction on the water quality. Among the key findings of this study is the significant increase of zoobenthivorous fish (roach and carp) from 1973 to 1999 that correlates with the water level reduction. A decline of charo-phytes is also noted whereas the reed beds appear to have expanded at the shallower parts of the lake. The zooplankton composition of the lake is mostly dominated by nauplii, rotifer and small-sized crustaceans indicat-ing a possible effect of fish predation. Overall, this article has ascertained an alarming shift of water quality and composition of biological communi-ties that can be attributed to the combined effects of eutrophication and the extreme water level decrease.
General circulation models (GCMs) project an increasing frequency and
intensity of heavy rainfall events due to global climate change. This
rather holds true for regions that are even expected to experience an
overall decrease in average annual precipitation. Consequently, this may
be attended by an increasing frequency and magnitude of flood events.
However, time series of GCMs show a bias in simulating 20th century
precipitation and temperature fields and, therefore, cannot directly be
used to force hydrological models in order to assess the impact of the
projected climate change on certain components of the hydrological
cycle. For a posteriori correction, the so-called delta change approach
is widely-used which adds the 30-year monthly differences for
temperature or ratios for precipitation of the GCM data to each month of
a historic climate data set. As the variability of the climate variables
in the scenario period is not transferred, this approach is especially
questionable if discharge extremes are to be analyzed. In order to
preserve the variability given by the GCM, methods of statistical bias
correction are applied. This study aims to investigate the impact of two
methods of bias correction, the delta change approach and a statistical
bias correction, on the large scale modeling of flood discharges, using
the example of 25 macroscale catchments in Europe. The discharge
simulation is carried out with the global integrated model WaterGAP3
(Water - Global Assessment and Prognosis). Results show that the two
bias correction methods lead to distinctively different trends in future
flood flows.
Major rivers worldwide have experienced dramatic changes in flow, reducing their natural ability to adjust to and absorb disturbances. Given expected changes in global climate and water needs, this may create serious problems; including loss of native biodiversity and risks to ecosystems and humans from increased flooding or water shortages. Here, we project river discharge under different climate and water withdrawal scenarios and combine this with data on the impact of dams on large river basins to create global maps illustrating potential changes in discharge and water stress for dam-impacted and free-flowing basins. The projections indicate that every populated basin in the world will experience changes in river discharge and many will experience water stress. The magnitude of these impacts is used to identify basins likely and almost certain to require proactive or reactive management intervention. Our analysis indicates that the area in need of management action to mitigate the impacts of climate change is much greater for basins impacted by dams than for basins with free-flowing rivers. Nearly one billion people live in areas likely to require action and approximately 365 million people live in basins almost certain to require action. Proactive management efforts will minimize risks to ecosystems and people and may be less costly than reactive efforts taken only once problems have arisen.
Impact of climate change on ecohydrologic processes of Mediterranean watersheds are significant and require quick action toward improving adaptation and management of fragile system. Increase in water shortages and land use can alter the water balance and ecological health of the watershed systems. Intensification of land use, increase in water abstraction, and decline in water quality can be enhanced by changes in temperature and precipitation regimes. Ecohydrologic changes from climatic impacts alter runoff, evapotranspiration, surface storage, and soil moisture that directly affect biota and habitat of the region. This paper reviews expected impacts of climatic change on the ecohydrology of watershed systems of the Mediterranean and identifies adaptation strategies to increase the resilience of the systems. A spatial assessment of changes in temperature and precipitation estimates from a multimodel ensemble is used to identify potential climatic impacts on watershed systems. This is augmented with literature on ecohydrologic impacts in watershed systems of the region. Hydrologic implications are discussed through the lens of geographic distribution and upstream-downstream dynamics in watershed systems. Specific implications of climatic change studied are on runoff, evapotranspiration, soil moisture, lake levels, water quality, habitat, species distribution, biodiversity, and economic status of countries. It is observed that climatic change can have significant impacts on the ecohydrologic processes in the Mediterranean watersheds. Vulnerability varied depending on the geography, landscape characteristics, and human activities in a watershed. Increasing the resilience of watershed systems can be an effective strategy to adapt to climatic impacts. Several strategies are identified that can increase the resilience of the watersheds to climatic and land use change stress. Understanding the ecohydrologic processes is vital to development of effective long-term strategies to improve the resilience of watersheds. There is need for further research into ecohydrologic dynamics at multiple scales, improved resolution of climatic predictions to local scales, and implications of disruptions on regional economies.
The SWAT model was modified to simulate the hydrologic and chemical response of karstic systems and assess the impacts of land use management and climate change of an intensively managed Mediterranean watershed in Crete, Greece. A methodology was developed for the determination of the extended karst area contributing to the spring flow as well as the degree of dilution of nitrates due to permanent karst water volume. The modified SWAT model has been able to capture the temporal variability of both karst flow and surface runoff using high frequency monitoring data collected since 2004 and long term flow time series collected since 1973. The overall hydrologic budget of the karst was estimated and its evaporative losses were calculated to be 28% suggesting a very high rate of karst infiltration. Nitrate chemistry of the karst was simulated by calibrating a dilution factor allowing for the estimation of the total karstic groundwater volume to approximately 500 million m(3) of reserve water. The nitrate simulation results suggested a significant impact of livestock grazing on the karstic groundwater and on surface water quality. Finally, simulation results for a set of climate change scenarios suggested a 17% decrease in precipitation, 8% decrease in ET and 22% decrease in flow in 2030-2050 compared to 2010-2029. A tool for integrated water management of karst areas has been developed, providing policy makers an instrument for water management that could tackle the increasing water scarcity in the island.
A probabilistic framework is presented for combining information from an ensemble of four general circulation models (GCMs), two greenhouse gas emission scenarios, two statistical downscaling techniques, two hydrological model structures, and two sets of hydrological model parameters. GCMs were weighted according to an index of reliability for downscaled effective rainfall, a key determinant of low flows in the River Thames. Hydrological model structures were weighted by performance at reproducing annual low-flow series. Weights were also assigned to sets of water resource model (CATCHMOD) parameters using the Nash-Sutcliffe efficiency criterion. Emission scenarios and downscaling methods were unweighted. A Monte Carlo approach was then used to explore components of uncertainty affecting projections for the River Thames by the 2080s. The resulting cumulative distribution functions (CDFs) of low flows were most sensitive to uncertainty in the climate change scenarios and downscaling of different GCMs. Uncertainties due to the hydrological model parameters and emission scenario increase with time but were less important. Abrupt changes in low-flow CDFs were attributed to uncertainties in statistically downscaled summer rainfall. This was linked to different behavior of atmospheric moisture among the chosen GCMs.
2013): Current state of Mediterranean water resources and future trends under climatic and anthropogenic changes, Hydrological Sciences Journal, 58:3, 498-518 This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.
The functioning of shallow lakes is supposedly very sensitive to water level fluctuations (WLF). Relationships between WLF and submerged macrophyte development were investigated in five Turkish shallow lakes located in a semi-arid to arid Mediterranean climate where the hydrological event of WLF is a common phenomenon. In all lakes, WLF emerged as a major factor determining submerged plant development. High submerged plant coverage was observed in four of the study lakes, Lake Beyşehir, Lake Uluabat, Lake Marmara and Lake Mogan when the water level was low throughout the year or during growing season, submerged plants expanded; however, in Lake Işıklı extensive submerged plant development was observed at high water levels during winter. In Lake Işıklı, an increase of 25 % in the surface area was recorded, which, in turn, might have resulted in an increased potential for expansion of submerged plants. Furthermore, in all the lakes excluding Lake Beyşehir, high sub-merged plant coverage coincided with a significant decrease in the amplitude of intra-annual water level fluctuations. The depth profile, expressed as the morphometry index (Zmean/Zmax), appeared to be critical for the development of extensive vegetation. Expansion of vegetation coincided with either an increased morphometry index or a flatter bottom profile. However, the impact of hydrology on lake morphometry differed between the lakes. In Lake Işıklı, the high water level generated a slightly flatter, albeit not significantly so, bottom; however, in the remaining lakes the same effect was observed at low water level. Differences in the morphometry index in response to WLF appeared to depend on the original bottom profile, which is either conical or ellipsoid. Therefore, the impact of hydrology on the bottom profile of a lake may profoundly affect the extent of the littoral zone. Biomass of carp (Cyprinus carpio) had a strong inverse correlation with vegetation development in Lake Marmara and Lake Uluabat, therefore, carp might also have been important in macrophyte development. It may be concluded that littoral plant communities in shallow lakes located in semi-arid to arid regions appear to be particularly susceptible to water level fluctuations.
The impact of climate change on water resources is usually assessed at the local scale. However, regional climate models (RCMs) are known to exhibit systematic biases in precipitation. Hence, RCM simulations need to be post-processed in order to produce reliable estimates of local scale climate. Popular post-processing approaches are based on statistical transformations, which attempt to adjust the distribution of modelled data such that it closely resembles the observed climatology. However, the diversity of suggested methods renders the selection of optimal techniques difficult and therefore there is a need for clarification. In this paper, statistical transformations for post-processing RCM output are reviewed and classified into (1) distribution derived transformations, (2) parametric transformations and (3) nonparametric transformations, each differing with respect to their underlying assumptions. A real world application, using observations of 82 precipitation stations in Norway, showed that nonparametric transformations have the highest skill in systematically reducing biases in RCM precipitation.
