Modeling the Effects of Anthropogenic Land Cover Changes to the Main Hydrometeorological Factors in a Regional Watershed, Central Greece

Unravelling Precipitation Trends in Greece since 1950s Using ERA5 Climate Reanalysis Data

Precipitation is one of the most variable climatic parameters, as it is determined by many physical processes. The spatiotemporal characteristics of precipitation have been significantly affected by climate change during the past decades. Analysis of precipitation trends is challenging, especially in regions such as Greece, which is characterized by complex topography and includes several ungauged areas. With this study, we aim to shed new light on the climatic characteristics and inter-annual trends of precipitation over Greece. For this purpose, we used ERA5 monthly precipitation data from 1950 to 2020 to estimate annual Theil–Sen trends and Mann–Kendall significance over Greece and surrounding areas. Additionally, in order to analyze and model the nonlinear relationships of monthly precipitation time series, we used generalized additive models (GAMs). The results indicated significant declining inter-annual trends of areal precipitation over the study area. Declining trends were more pronounced in winter over western and eastern Greece, but trends in spring, summer and autumn were mostly not significant. GAMs showcased that the trends were generally characterized by nonlinearity and precipitation over the study area presented high inter-decadal variability. Combining the results, we concluded that precipitation did not linearly change during the past 7 decades, but it first increased from the 1950s to the late 1960s, consequently decreased until the early 1990s and, afterwards, presented an increase until 2020 with a smaller rate than the 1950–1960s.

Long and Short-Term Coastal Changes Assessment Using Earth Observation Data and GIS Analysis: The Case of Sperchios River Delta

The present study provides information about the evolution of the Sperchios River deltaic area over the last 6500 years. Coastal changes, due to natural phenomena and anthropogenic activities, were analyzed utilizing a variety of geospatial data such as historic records, topographic maps, aerial photos, and satellite images, covering a period from 4500 BC to 2020. A qualitative approach for the period, from 4500 BC to 1852, and a quantitative analysis, from 1852 to the present day, were employed. Considering their scale and overall quality, the data were processed and georeferenced in detail based on the very high-resolution orthophoto datasets of the area. Then, the multitemporal shorelines were delineated in a geographical information system platform. Two different methods were utilized for the estimation of the shoreline changes and trends, namely the coastal change area method and the cross-section analysis, by implementing the digital shoreline analysis system with two statistical approaches, the end point rate and the linear regression rate. Significant river flow and coastline changes were observed with the overall increase in the delta area throughout the study period reaching 135 km2 (mean annual growth of 0.02 km2/yr) and the higher accretion rates to be detected during the periods 1805–1852, 1908–1945 and 1960–1986, especially at the central and north part of the gulf. During the last three decades, the coastline has remained relatively stable with a decreasing tendency, which, along with the expected sea-level rise due to climate change, can infer significant threats for the coastal zone in the near future.

Delineating the relative contribution of climate related variables to chlorophyll-a and phytoplankton biomass in lakes using the ERA5-Land climate reanalysis data

Understanding the climatic drivers of eutrophication is critical for lake management under the prism of the global change. Yet the complex interplay between climatic variables and lake processes makes prediction of phytoplankton biomass a rather difficult task. Quantifying the relative influence of climate-related variables on the regulation of phytoplankton biomass requires modelling approaches that use extensive field measurements paired with accurate meteorological observations. In this study we used climate and lake related variables obtained from the ERA5-Land reanalysis dataset combined with a large dataset of in-situ measurements of chlorophyll-a and phytoplankton biomass from 50 water bodies to develop models of phytoplankton related responses as functions of the climate reanalysis data. We used chlorophyll-a and phytoplankton biomass as response metrics of phytoplankton growth and we employed two different modelling techniques, boosted regression trees (BRT) and generalized additive models for location scale and shape (GAMLSS). According to our results, the fitted models had a relatively high explanatory power and predictive performance. Boosted regression trees had a high pseudo R² with the type of the lake, the total layer temperature, and the mix-layer depth being the three predictors with the higher relative influence. The best GAMLSS model retained mix-layer depth, mix-layer temperature, total layer temperature, total runoff and 10-m wind speed as significant predictors (p<0.001). Regarding the phytoplankton biomass both modelling approaches had less explanatory power than those for chlorophyll-a. Concerning the predictive performance of the models both the BRT and GAMLSS models for chlorophyll-a outperformed those for phytoplankton biomass. Overall, we consider these findings promising for future limnological studies as they bring forth new perspectives in modelling ecosystem responses to a wide range of climate and lake variables. As a concluding remark, climate reanalysis can be an extremely useful asset for lake research and management.

Evaluating Nature-Based Solution for Flood Reduction in Spercheios River Basin under Current and Future Climate Conditions

Nature-based solutions (NBS) are being deployed around the world in order to address hydrometeorological hazards, including flooding, droughts, landslides and many others. The term refers to techniques inspired, supported and copied from nature, avoiding large constructions and other harmful interventions. In this work the development and evaluation of an NBS applied to the Spercheios river basin in Central Greece is presented. The river is susceptible to heavy rainfall and bank overflow, therefore the intervention selected is a natural water retention measure that aims to moderate the impact of flooding and drought in the area. After the deployment of the NBS, we examine the benefits under current and future climate conditions, using various climate change scenarios. Even though the NBS deployed is small compared to the rest of the river, its presence leads to a decrease in the maximum depth of flooding, maximum velocity and smaller flooded areas. Regarding the subsurface/groundwater storage under current and future climate change and weather conditions, the NBS construction seems to favor long-term groundwater recharge.

Assessing Annual Actual Evapotranspiration Based on Climate, Topography and Soil in Natural and Agricultural Ecosystems

Simple formulas for estimating annual actual evapotranspiration (AET) based on annual climate data are widely used in large scale applications. Such formulas do not have distinct compartments related to topography, soil and irrigation, and for this reason may be limited in basins with high slopes, where runoff is the dominant water balance component, and in basins where irrigated agriculture is dominant. Thus, a simplistic method for assessing AET in both natural ecosystems and agricultural systems considering the aforementioned elements is proposed in this study. The method solves AET through water balance based on a set of formulas that estimate runoff and percolation. These formulas are calibrated by the results of the deterministic hydrological model GLEAMS (Groundwater Loading Effects of Agricultural Management Systems) for a reference surface. The proposed methodology is applied to the country of Greece and compared with the widely used climate-based methods of Oldekop, Coutagne and Turk. The results show that the proposed methodology agrees very well with the method of Turk for the lowland regions but presents significant differences in places where runoff is expected to be very high (sloppy areas and areas of high rainfall, especially during December–February), suggesting that the proposed method performs better due to its runoff compartment. The method can also be applied in a single application considering irrigation only for the irrigated lands to more accurately estimate AET in basins with a high percentage of irrigated agriculture.

Quantifying the impacts of land use/land cover change on the water balance in the afforested River Basin, Pakistan

Land use and land cover (LULC) change is one of the key driving elements responsible for altering the hydrology of a watershed. In this study, we investigated the spatio-temporal LULC changes between 2001 and 2018 and their impacts on the water balance of the Jhelum River Basin. The Soil and Water Assessment Tool (SWAT) was used to analyze the impacts on water yield (WY) and evapotranspiration (ET). The model was calibrated and validated with discharge data between 1995 and 2005 and then simulated with different land use. The increase was observed in forest, settlement and water areas during the study period. At the catchment scale, we found that afforestation has reduced the WY and surface runoff, while enhanced the ET. Moreover, this change was more pronounced at the sub-basin scale. Some sub-basins, especially in the northern part of the study area, exhibited an increase in WY due to an increase in the snow cover area. Similarly, extremes land use scenarios also showed significant impact on water balance components. The basin WY has decreased by 38 mm/year and ET has increased about 36 mm/year. The findings of this study could guide the watershed manager in the development of sustainable LULC planning and water resources management.

Implementation of a Nowcasting Hydrometeorological System for Studying Flash Flood Events: The Case of Mandra, Greece

Severe hydrometeorological hazards such as floods, droughts, and thunderstorms are expected to increase in the future due to climate change. Due to the significant impacts of these phenomena, it is essential to develop new and advanced early warning systems for advance preparation of the population and local authorities (civil protection, government agencies, etc.). Therefore, reliable forecasts of extreme events, with high spatial and temporal resolution and a very short time horizon are needed, due to the very fast development and localized nature of these events. In very short time-periods (up to 6 h), small-scale phenomena can be described accurately by adopting a “nowcasting” approach, providing reliable short-term forecasts and warnings. To this end, a novel nowcasting system was developed and presented in this study, combining a data assimilation system (LAPS), a large amount of observed data, including XPOL radar precipitation measurements, the Chemical Hydrological Atmospheric Ocean wave System (CHAOS), and the WRF-Hydro model. The system was evaluated on the catastrophic flash flood event that occurred in the sub-urban area of Mandra in Western Attica, Greece, on 15 November 2017. The event was one of the most catastrophic flash floods with human fatalities (24 people died) and extensive infrastructure damage. The update of the simulations with assimilated radar data improved the initial precipitation description and led to an improved simulation of the evolution of the phenomenon. Statistical evaluation and comparison with flood data from the FloodHub showed that the nowcasting system could have provided reliable early warning of the flood event 1, 2, and even to 3 h in advance, giving vital time to the local authorities to mobilize and even prevent fatalities and injuries to the local population.