The challenge of unprecedented floods and droughts in risk management.

Risk management has reduced vulnerability to floods and droughts globally, yet their impacts are still increasing. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data. 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.