Losses of large volumes of soil through gully formation lead to serious environmental, societal, and economic problems for human societies. This study establishes a framework based on an artificial intelligence approach to investigate the impact of geo-environmental and topo-hydrological factors on gully occurrences in the Biram region, Iran. The maximum entropy, random forest, and boosted regression trees machine-learning models were applied. The relative importance of variables (RIV) was then determined and gully erosion susceptibility maps were generated. Model results were evaluated using cutoff-dependent and -independent metrics. All models identified road construction as the main cause of gully formation in the study region (RVI ranged between 27% and 34%), and a medium contribution of distance from stream (RVI = 15-18%), lithology (RVI = 12-15%) and land use (RVI = 8-12%). Other factors such as drainage density, topographic wetness index, aspect, slope, profile curvature, elevation and plan curvature showed lower relative importance (RIV < 10%). Planners should pay attention to minimizing gully erosion along roads, so that river systems and downstream communities are adequately protected.

Population growth is increasing the pressure on water resource availability. For useful assessment and planning for societal water availability impacts, it is imperative to disentangle the direct influences of human activities in the landscape from external climate-driven influences on water flows and their variation and change. In this study we used the water balance model, a gridded global hydrological model, to quantify and distinguish human-driven change components, modified by interventions such as dams, reservoirs, and water withdrawals for irrigation, industry, and households, from climate-driven change components on four key water balance variables in the terrestrial hydrological system (evapotranspiration, runoff, soil moisture, storage change). We also analyzed emergent effect patterns in and across different parts of the world, facilitating exploration of spatial variability and regional patterns on multiple spatial scales, from pixel to global, including previously uninvestigated parts of the world. Our results show that human activities drive changes in all hydrological variables, with different magnitudes and directions depending on geographical location. The differences between model scenarios with and without human activities were largest in regions with the highest population densities. In such regions, which also have relatively large numbers of dams for irrigation, water largely tends to be removed from storage and go to feed increased runoff and evapotranspiration fluxes. Our analysis considers a more complete set of hydrological variables than previous studies and can guide further research and management planning for future hydrological and water availability trends, including in relatively data-poor parts of the world.

European Center for Medium-Range Weather Forecasts Reanalysis (ERA), one of the most widely used precipitation products, has evolved from ERA-40 to ERA-20CM, ERA-20C, ERA-Interim, and ERA5. Studies evaluating the performance of individual ERA products cannot adequately assess the evolution of the products. We compared the performance of all ERA precipitation products at daily, monthly, and annual data (1980–2018) using more than 2100 Iran precipitation gauges. Results indicated that ERA-40 performed worst, followed by ERA-20CM, which showed only minor improvements over ERA-40. ERA-20C considerably outperformed its predecessors, benefiting from the assimilation of observational data. Although several previous studies have reported full superiority of ERA5 over ERA-Interim, our results revealed several shortcomings in ERA5 compared with the ERA-Interim estimates. Both ERA-Interim and ERA5 performed best overall, with ERA-Interim showing better statistical and categorical skill scores, and ERA5 performing better in estimating extreme precipitations. These results suggest that the accuracy of ERA precipitation products has improved from ERA-40 to ERA-Interim, but not consistently from ERA-Interim to ERA5. This study employed a grid-grid comparison approach by first creating a gridded reference data set through the spatial aggregation of point source observations, however, the results from a point-grid approach showed no change in the overall ranking of products (despite the slight changes in the error index values). These findings are useful for model development at a global scale and for hydrological applications in Iran.

Water bodies provide essential ecosystem services linked to morphometric features that might differ between natural lakes and reservoirs. We use the HydroLAKES global dataset to quantitatively compare large (area > 1 km²) reservoirs and natural lakes in terms of scaling exponents between morphometric measures (volume, area, shore length). These exponents are further compared to those expected from geometrical assumptions and constraints. Lakes cover a larger range of volumes for the same range of surface areas than reservoirs, and have a larger volume-area scaling exponent. The volume-area scaling exponent for reservoirs (but not natural lakes) and the area-shore length exponent for all water bodies follow the predictions for self-affine surfaces. Land cover and terrain influence the scaling relations more for lakes than for reservoirs. These morphometric differences may be used to model the impact of reservoirs and lakes on hydrological processes and associated ecosystem services at regional to global scales.

Soil, a non-renewable resource, sustains life on Earth by supporting around 95% of global food production and providing ecosystem services such as biomass production, filtration of contaminants and transfer of mass and energy between spheres. Unsustainable management practices and climate change are threatening the natural capital of soils, particularly in the Mediterranean region, where increasing population, rapid land-use changes, associated socio-economic activities and climate change are imposing high pressures on the region's shallow soils. Despite evidence of high soil susceptibility to degradation and desertification, the true extent of soil degradation in the region is unknown. This paper reviews and summarises the scientific literature and relevant official reports, with the aim to advance this knowledge by synthesizing, mapping, and identifying gaps regarding the status, causes, and consequences of soil degradation processes in the European Mediterranean region. This is needed as scientific underpinning of efforts to counteract soil degradation in the region. Three main degradation categories are then considered: physical (soil sealing, compaction, erosion), chemical (soil organic matter, contamination, salinisation), and biological. We find some degradation processes to be relatively well documented (e.g. soil erosion), while others, such as loss of biodiversity, remain poorly addressed, with limited data availability. We suggest establishment of a continuous, harmonised soil monitoring system at national and regional scale in the Mediterranean region to provide comparable datasets and chart the spatial extent and temporal changes in soil degradation, and corresponding economic implications. This is critical to support decision making and fulfilment of related sustainable development goals.

Extreme precipitation events such as floods and droughts have occurred with higher frequency over the recent decades as a result of the climate change and anthropogenic activities. To understand and mitigate such events, it is crucial to investigate their spatio-temporal variations globally or regionally. Global precipitation products provide an alternative way to the in situ observations over such a region. In this study, we have evaluated the performance of the latest version of the Global Precipitation Measurement-Integrated Multi-satellitE Retrievals (GPM-IMERGV6.0 Final Run (GPM-IMERGF)). To this end, we have employed ten most common extreme precipitation indices, including maximum indices (Rx1day, Rx5day, CDD, and CWD), percentile indices (R95pTOT and R99pTOT), and absolute threshold indices (R10mm, R20mm, SDII, and PRCPTOT). Overall, the spatial distribution results for error metrics showed that the highest and lowest accuracy for GPM-IMERGF were reported for the absolute threshold indices and percentile indices, respectively. Considering the spatial distribution of the results, the highest accuracy of GPM-IMERGF in capturing extreme precipitations was observed over the western highlands, while the worst results were obtained along the Caspian Sea regions. Our analysis can significantly contribute to various hydro-metrological applications for the study region, including identifying drought and flood-prone areas and water resources planning.

Study region: Karkheh and Karun basins (29°−35°N, 46°−52°E) are two large river basins (area 51,000 and 67,000 km², respectively) with complex topography in southwest Iran.

Study focus: Access to spatio-temporally consistent precipitation data is a key requirement for hydrological studies, especially in data-scarce regions. This study evaluated 14 global precipitation products against gauge observations from 2003 to 2012 in Karun and Karkheh basins, southwest Iran. Different categorical and statistical indices at varying spatial and temporal resolution, including Kling-Gupta Efficiency (KGE), bias, correlation coefficient, and variability ratio, were used to evaluate the products.

New hydrological insights for the region: For daily time steps, TMPA-3B42V7.0, MERRA-2, and CMORPH-BLDV1.0 outperformed all other products, with KGE > 0.3. TMPA-3B42V7.0, MERRA-2, and PERSIANN-CDR were the best-performing products for monthly time steps, with KGE> 0.5. ERA5-Land showed the highest positive bias (bias>1.5) compared with in-situ observations, particularly for mountainous southeastern parts of Karun basin. Overall, bias-adjusted products obtained by merging ground-based observations in the estimations outperformed the unadjusted versions. The spatial distribution of statistical error metrics indicated that almost all products showed their greatest uncertainties for mountainous regions due to complex precipitation processes in these regions. These results can contribute significantly to hydrological and water resources planning measures in the study region, including early flood warning systems, drought monitoring, and optimization of dam operation.

Changes in climate, land use, and land management impact the occurrence and severity of wildland fires in many parts of the world. This is particularly evident in Europe, where ongoing changes in land use have strongly modified fire patterns over the last decades. Although satellite data by the European Forest Fire Information System provide large-scale wildland fire statistics across European countries, there is still a crucial need to collect and summarize in-depth local analysis and understanding of the wildland fire condition and associated challenges across Europe. This article aims to provide a general overview of the current wildland fire patterns and challenges as perceived by national representatives, supplemented by national fire statistics (2009–2018) across Europe. For each of the 31 countries included, we present a perspective authored by scientists or practitioners from each respective country, representing a wide range of disciplines and cultural backgrounds. The authors were selected from members of the COST Action “Fire and the Earth System: Science & Society” funded by the European Commission with the aim to share knowledge and improve communication about wildland fire. Where relevant, a brief overview of key studies, particular wildland fire challenges a country is facing, and an overview of notable recent fire events are also presented. Key perceived challenges included (1) the lack of consistent and detailed records for wildland fire events, within and across countries, (2) an increase in wildland fires that pose a risk to properties and human life due to high population densities and sprawl into forested regions, and (3) the view that, irrespective of changes in management, climate change is likely to increase the frequency and impact of wildland fires in the coming decades. Addressing challenge (1) will not only be valuable in advancing national and pan-European wildland fire management strategies, but also in evaluating perceptions (2) and (3) against more robust quantitative evidence.

Large-scale covariations of freshwater fluxes and storages on land can critically regulate the balance of green (evapotranspiration) and blue (runoff) water fluxes, and related land-atmosphere interactions and hydroclimatic hazards. Such large-scale covariation patterns are not evident from smaller-scale hydrological studies that have been most common so far, and remain largely unknown for various regions and climates around the world. To contribute to bridging the large-scale knowledge gaps, we synthesize and decipher hydroclimatic data time series over the period 1980–2010 for 6,405 catchments around the world. From observation-based data, we identify dominant large-scale linear covariation patterns between monthly freshwater fluxes and soil moisture (SM) for different world parts and climates. These covariation patterns are also compared with those obtained from reanalysis products and Earth System Models (ESMs). The observation-based data sets robustly show the strongest large-scale hydrological relationship to be that between SM and runoff (R), consistently across the study catchments and their different climate characteristics. This predominantly strongest covariation between monthly SM and R is also the most misrepresented by ESMs and reanalysis products, followed by that between monthly precipitation and R. Comparison of observation-based and ESM results also shows that an ESM may perform well for individual monthly variables, but fail in representing the patterns of large-scale linear covariations between them. Observation-based quantification of these patterns, and ESM and reanalysis improvements for their representation are essential for fundamental understanding, and more accurate and reliable modeling and projection of large-scale hydrological conditions and changes under ongoing global and regional change.

Assessments of ecosystem service and function losses of wetlandscapes (i.e., wetlands and their hydrological catchments) suffer from knowledge gaps regarding impacts of ongoing hydro-climatic change. This study investigates hydro-climatic changes during 1976–2015 in 25 wetlandscapes distributed across the world’s tropical, arid, temperate and cold climate zones. Results show that the wetlandscapes were subject to precipitation (P) and temperature (T) changes consistent with mean changes over the world’s land area. However, arid and cold wetlandscapes experienced higher T increases than their respective climate zone. Also, average P decreased in arid and cold wetlandscapes, contrarily to P of arid and cold climate zones, suggesting that these wetlandscapes are located in regions of elevated climate pressures. For most wetlandscapes with available runoff (R) data, the decreases were larger in R than in P, which was attributed to aggravation of climate change impacts by enhanced evapotranspiration losses, e.g. caused by land-use changes.