The challenge of unprecedented floods and droughts in risk management.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Weed cover controls soil and water losses in rainfed olive groves in Sierra de Enguera, eastern Iberian Peninsula.

Soil erosion is a threat for the sustainability of agriculture and severely affects the Mediterranean crops. Olive groves are among the rainfed agriculture lands that exhibit soil and water losses due to the impact of unsustainable practices such as conventional tillage and herbicides abuse. To achieve a more sustainable olive oil production, alternative, greener crop management practices need to be tested in the field. Here, a weed cover (CW) treatment is tested at an olive tree plantation that has undergone conventional mechanical tillage for 20 years and results were compared against an adjacent control plantation that maintained tillage as a weed control strategy (CO). Both plantations were under the same tillage management for centuries and macroscopic analysis confirms they are otherwise comparable. Compared to the CO, where tilled soil cover was zero, 20 years of CW (weeds cover 64%; litter cover 5%) had led to significantly higher values of soil bulk density and soil organic matter. Results from rainfall simulation experiments at 55 mm h-1 on 0.25 m2 plots under CO (N = 25) and CW (N = 25) show that as a result of the improved soil structure, CW (i) reduced soil losses by two orders of magnitude (140 times), (ii) decreased runoff yield by one order of magnitude (from 2.65 till 27.6% of the rainfall), (iii) significantly reduced runoff sediment concentration (from 18.6 till 1.43 g l-1), and (iv) significantly delayed runoff generation (CO = 273 s; CW = 788 s). These results indicate that weed cover is a sustainable land management practice in Mediterranean olive groves and promotes sustainable agriculture production in mountainous areas under rainfed conditions, which are typically affected by high erosion rates such those found in the CO plots. Due to the spontaneous recovery of plant cover, we conclude that weed cover is an excellent nature-based solution to increase in the soil organic matter content and soil erosion reduction in rainfed olive orchards.

Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain.

Early season fruit production for the northern European market is highly intensive in fertilization, machinery, irrigation and the use of herbicides. Those conditions increase the soil losses and soil compaction and threaten the Sustainable Goals for Development of the United Nations by 2030. Long-term soil erosion measurements are necessary to determine the sustainability of agriculture managements. Moreover, soil erosion on flood irrigation land is a topic that request more surveys and research as rainfed sloping terrains attracted all the attention of scientists and research investment. Improved Stock Unearthing Method (ISUM) was applied to two 15 years-old herbicide treated fields of Saturn peaches (Prunus persica var. platycarpa) to determine long-term soil erosion rates (2004-2019). Using ISUM, a 1 mm thick nylon rope (700 mm length) was used to connect trees perpendicular to the direction of rows at the height of the graft. To detection soil lowering, the vertical distance of the rope to the soil surface was measured at 10 cm intervals along the rope. The ring method (264 samples at 0-6 cm) was used to determine the soil bulk density, which was in average 1.15 gr cm-3 for both plots. There was found a compaction in the centre of both plots due to the pass of machinery with mean bulk density values of 1.23 gr cm-3, meanwhile underneath of the trees, the soil bulk density was 1.05 gr cm-3. The topography survey carried out with ISUM (2508 sampling points) informed that flood irrigation redistributed the soil from the upper to the lower field position, where a sedimentation layer was measured. We found that the two studied fields showed a contrasted response, with low soil erosion values in Benimodo and high in L'Alcúdia study sites. Soil erosion rates were in average 1.46 Mg ha-1 yr-1 and 8.02 Mg ha-1 yr-1 for Benimodo and L'Alcúdia, respectively. However, the maps development using ISUM allow to inform that the pattern of soil redistribution is similar for both fields as the highest soil lowering was found in the upper field part, where the flood discharge detach soil particles. In the lower field position sedimentation takes place. The dataset allows us to conclude that soil erosion in Saturn peaches fields is non-sustainable and more soil conservation management should be applied to reduce the soil erosion rates due to the bare soils as a consequence of the use of herbicides. This research informs that soil erosion in flood irrigated fields is a relevant process that needs more investigations around the world, where 94% of the irrigated land is under flood or furrow irrigation, and where irrigation is growing year after year.

Helping stakeholders select and apply appraisal tools to mitigate soil threats: Researchers' experiences from across Europe.

Soil improvement measures need to be ecologically credible, socially acceptable and economically affordable if they are to enter widespread use. However, in real world decision contexts not all measures can sufficiently meet these criteria. As such, developing, selecting and using appropriate tools to support more systematic appraisal of soil improvement measures in different decision-making contexts represents an important challenge. Tools differ in their aims, ranging from those focused on appraising issues of cost-effectiveness, wider ecosystem services impacts and adoption barriers/opportunities, to those seeking to foster participatory engagement and social learning. Despite the growing complexity of the decision-support tool landscape, comprehensive guidance for selecting tools that are best suited to appraise soil improvement measures, as well as those well-adapted to enable participatory deployment, has generally been lacking. We address this gap using the experience and survey data from an EU-funded project (RECARE: Preventing and REmediating degradation of soils in Europe through land CARE). RECARE applied different socio-cultural, biophysical and monetary appraisal tools to assess the costs, benefits and adoption of soil improvement measures across Europe. We focused on these appraisal tools and evaluated their performance against three broad attributes that gauge their differences and suitability for widespread deployment to aid stakeholder decision making in soil management. Data were collected using an online questionnaire administered to RECARE researchers. Although some tools worked better than others across case studies, the information collated was used to provide guiding strategies for choosing appropriate tools, considering resources and data availability, characterisation of uncertainty, and the purpose for which a specific soil improvement measure is being developed or promoted. This paper provides insights to others working in practical soil improvement contexts as to why getting the tools right matters. It demonstrates how use of the right tools can add value to decision-making in ameliorating soil threats, supporting the sustainable management of the services that our soil ecosystems provide.

A SIFT-Based DEM Extraction Approach Using GEOEYE-1 Satellite Stereo Pairs.

A module for Very High Resolution (VHR) satellite stereo-pair imagery processing and Digital Elevation Model (DEM) extraction is presented. A large file size of VHR satellite imagery is handled using the parallel processing of cascading image tiles. The Scale-Invariant Feature Transform (SIFT) algorithm detects potentially tentative feature matches, and the resulting feature pairs are filtered using a variable distance threshold RANdom SAmple Consensus (RANSAC) algorithm. Finally, point cloud ground coordinates for DEM generation are extracted from the homologous pairs. The criteria of average point spacing irregularity is introduced to assess the effective resolution of the produced DEMs. The module is tested with a 0.5 m × 0.5 m Geoeye-1 stereo pair over the island of Crete, Greece. Sensitivity analysis determines the optimum module parameterization. The resulting 1.5-m DEM has superior detail over reference DEMs, and results in a Root Mean Square Error (RMSE) of about 1 m compared to ground truth measurements.

Land subsidence hazard modeling: Machine learning to identify predictors and the role of human activities.

Land subsidence caused by land use change and overexploitation of groundwater is an example of mismanagement of natural resources, yet subsidence remains difficult to predict. In this study, the relationship between land subsidence features and geo-environmental factors is investigated by comparing two machine learning algorithms (MLA): maximum entropy (MaxEnt) and genetic algorithm rule-set production (GARP) algorithms in the Kashmar Region, Iran. Land subsidence features (N = 79) were mapped using field surveys. Land use, lithology, the distance from traditional groundwater abstraction systems (Qanats), from afforestation projects, from neighboring faults, and the drawdown of groundwater level (DGL) (1991-2016) were used as predictive variables. Jackknife resampling showed that DGL, distance from afforestation projects, and distance from Qanat systems are major factors influencing land subsidence, with geology and faults being less important. The GARP algorithm outperformed the MaxEnt algorithm for all performance metrics. The performance of both models, as measured by the area under the receiver-operator characteristic curve (AUROC), decreased from 88.9-94.4% to 82.5-90.3% when DGL was excluded as a predictor, though the performance of GARP was still good to excellent even without DGL. MLAs produced maps of subsidence risk with acceptable accuracy, both with and without data on groundwater drawdown, suggesting that MLAs can usefully inform efforts to manage subsidence in data-scarce regions, though the highest accuracy requires data on changes in groundwater level.

Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach.

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R² values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies.

A web-based GIS platform supporting innovative irrigation management techniques at farm-scale for the Mediterranean island of Crete.

The aim of this paper is the creation of an integrated and free-access web platform for parcel irrigation water management on a large spatial scale (Water District of Crete, in Greece) in order to: a) accurately determine the irrigation needs of the main crops for Crete such as olives, citrus, avocados and vineyards, b) design strategies, for optimal adaptation of the agricultural sector in the context of climate change, and c) incorporate the dynamic integration of the above information through the creation of a digital platform. In the proposed decision-making system, essential factors are taken into account, such as real-time meteorological data, information about the type and spatial distribution of the agricultural parcels in Crete, algorithms for calculation crop evapotranspiration per development stage and age of the crops, satellite remote sensing techniques in combination with field surveys to depict accurate soil texture map for the whole island of Crete as well as sustainable cultivation practices for saving water per crop and parcel geomorphology. Based on the proposed decision-making system, users will have the opportunity in any specific location/farm in Crete to know the irrigation needs of the crops in real-time and obtain information about proper climate-water adaptation practices. The main novelty points of the proposed platform include the derivation of parcel-level soil texture data from Sentinel-2 satellite imagery and field samples, the comprehensiveness of the irrigation management information, the relatively low data requirements and the application interface simplicity provided to the end-user.

TERRAenVISION: Science for Society. Environmental issues today.

Our Planet suffers from human activities. As scientists, we know more and more about our environment, about processes, rates of change, new threats, and risks. However, the challenges we face seem to grow quicker than the solutions we can create. To achieve sustainability, the key is to make solutions not only functional from an environmental point of view, but also socially acceptable and economically viable. In this context, the TERRAenVISION conference series gathers diverse groups of scientists to discuss sustainability. The first TERRAenVISION meeting in January 2018 was framed around 7 themes: (1) Climate Change: Mitigation and Adaptation, (2) Water Resources: Quality and Quantity, (3) Land Degradation and Restoration, (4) Nature-based Solutions, (5) Fire in the Earth System, Effects, and Prevention, (6) Ecosystem Services and Health, and (7) Science Interface with Policy and Public. Among the works presented in the conference, this Special Issue collates 22 papers that illustrate the best, problems and solutions the scientific community is currently working on to achieve sustainability. Similar to the concept of the SDGs, paper subjects often intertwine and bridge the conference themes. The papers are grouped in two main chapters dealing with Water and Land, with two additional cross cutting chapters of Scientific Tools and Science-Policy Interface. Drawing from the conclusions of these works as well as those of the TERRAenVISION 2018 conference, we make recommendations regarding raising awareness, connecting scientific fields, and supporting robust economic and policy transitions.

Data-driven competitive facilitative tree interactions and their implications on nature-based solutions.

Spatio-temporal data are more ubiquitous and richer than even before and the availability of such data poses great challenges in data analytics. Ecological facilitation, the positive effect of density of individuals on the individual's survival across a stress gradient, is a complex phenomenon. A large number of tree individuals coupled with soil moisture, temperature, and water stress data across a long temporal period were followed. Data-driven analysis in the absence of hypothesis was performed. Information theoretic analysis of multiple statistical models was employed in order to quantify the best data-driven index of vegetation density and spatial scale of interactions. Sequentially, tree survival was quantified as a function of the size of the individual, vegetation density, and time at the optimal spatial interaction scale. Land surface temperature and soil moisture were also statistically explained by tree size, density, and time. Results indicated that in space both facilitation and competition co-exist in the same ecosystem and the sign and magnitude of this depend on the spatial scale. Overall, within the optimal data-driven spatial scale, tree survival was best explained by the interaction between density and year, sifting overall from facilitation to competition through time. However, small sized trees were always facilitated by increased densities, while large sized trees had either negative or no density effects. Tree size was more important predictor than density in survival and this has implications for nature-based solutions: maintaining large tree individuals or planting species that can become large-sized can safeguard against tree-less areas by promoting survival at long time periods through harsh environmental conditions. Large trees had also a significant effect in moderating land surface temperature and this effect was higher than the one of vegetation density on temperature.

Abrupt events and population synchrony in the dynamics of Bovine Tuberculosis.

Disease control strategies can have both intended and unintended effects on the dynamics of infectious diseases. Routine testing for the harmful pathogen Bovine Tuberculosis (bTB) was suspended briefly during the foot and mouth disease epidemic of 2001 in Great Britain. Here we utilize bTB incidence data and mathematical models to demonstrate how a lapse in management can alter epidemiological parameters, including the rate of new infections and duration of infection cycles. Testing interruption shifted the dynamics from annual to 4-year cycles, and created long-lasting shifts in the spatial synchrony of new infections among regions of Great Britain. After annual testing was introduced in some GB regions, new infections have become more de-synchronised, a result also confirmed by a stochastic model. These results demonstrate that abrupt events can synchronise disease dynamics and that changes in the epidemiological parameters can lead to chaotic patterns, which are hard to be quantified, predicted, and controlled.