Drought forecasting through statistical models using standardised precipitation index: a systematic review and meta-regression analysis

Quality and reliable drought prediction is essential for mitigation strategies and planning in disaster-stricken regions globally. Prediction models such as empirical or data-driven models play a fundamental role in forecasting drought. However, selecting a suitable prediction model remains a challenge because of the lack of succinct information available on model performance. Therefore, this review evaluated the best model for drought forecasting and determined which differences if any were present in model performance using standardised precipitation index (SPI). In addition, the most effective combination of the SPI with its respective timescale and lead time was investigated. The effectiveness of data-driven models was analysed using meta-regression analysis by applying a linear mixed model to the coefficient of determination and the root mean square error of the validated model results. Wavelet-transformed neural networks had superior performance with the highest correlation and minimum error. Preprocessing data to eliminate non-stationarity performed substantially better than did the regular artificial neural network (ANN) model. Additionally, the best timescale to calculate the SPI was 24 and 12 months and a lead time of 1–3 months provided the most accurate forecasts. Studies from China and Sicily had the most variation based on geographical location as a random effect; while studies from India rendered consistent results overall. Variation in the result can be attributed to geographical differences, seasonal influence, incorporation of climate indices and author bias. Conclusively, this review recommends use of the wavelet-based ANN (WANN) model to forecast drought indices.

     

Landslide detection in the Himalayas using machine learning algorithms and U-Net

Landslides - Event-based landslide inventories are essential sources to broaden our understanding of the causal relationship between triggering events and the occurring landslides. Moreover,...     

The value of remotely sensed surface soil moisture for model calibration using SWAT

Remotely sensed (RS) data can add value to a hydrological model calibration. Among this, RS soil moisture (SM) data have mostly been assimilated into conceptual hydrological models using various transformed variable or indices. In this study, raw RS surface SM is used as a calibration variable in the Soil and Water Assessment Tool model. This means the SM values were not transformed into another variable (e.g., soil water index and root zone SM index). Using a nested catchment, calibration based only on RS SM and optimizing model parameters sensitive to SM using particle swarm optimization improved variations in streamflow predictions at some of the gauging stations compared to the uncalibrated model. This highlighted part of the catchments where the SM signal directly influenced the flow distribution. Additionally, highlighted high and low flow signals were mostly influenced. The seasonal breakdown indicates that the SM signal is more useful for calibrating in wetter seasons and in areas with higher variations in elevation. The results identified that calibration only on RS SM improved the general rainfall–runoff response simulation by introducing delays but cannot correct the overall routing effect. Furthermore, catchment characteristics (e.g., land use, elevation, soil types, and precipitation) regulating SM variation in different seasons highlighted by the model calibration are identified. This provides further opportunities to improve model parameterization.     

Qualitative and quantitative evaluation of the influence of anthropic pressure on subsidence in a sedimentary basin near Rome

This paper presents the results of analyses measuring variations in anthropic pressure and the influence of anthropic pressure on the variations in subsidence rates from 1954 to 2005 in the Tivoli-Guidonia area, located to the East of Rome, Italy. In the last 60 years, this area underwent exceptional demographic growth, as well as an increase in the quarrying and hydrothermal industries. The calculation of the increase in anthropic pressure was based on two factors: the expansion of built-up areas and the increase in quarrying. Photogrammetric techniques permitted a multi-temporal analysis of aerial photos taken in 1954, 1985, 1993, 1998 and 2005. The aim of this analysis was to estimate the increase in both urban surface area and travertine quarrying. Non-conventional techniques, such as the reconstruction of photograms using photo retouching software, allowed for the use of aerial photos from 1954. These photos were fundamental for establishing a medium-term evaluation of anthropic activity in the area. The results of the photogrammetric analysis were compared to the phases of acceleration and stabilization in subsidence phenomena, deduced from a RADAR interferometry study published by the Italian Ministry of the Environment. This comparison showed a close relationship between the rise and temporary halt of anthropic development and the rise and fall of subsidence rates. Furthermore, data on the distribution of private wells in the study area, variations in the groundwater table level and the precipitation regime were analyzed, but, although helpful in defining the geological context and considerable transformations of the territory, they were considered as qualitative data due to the lack of systematic measures or an unclear relationship to the variations in subsidence rate. Despite the difficulties involved in evaluating both the amount of anthropic pressure and the role of different human activities on environmental change, it was possible to estimate the variations in anthropic pressure and their influence on potentially dangerous geological processes.     

Distribution and ecological relevance of fine sediments in organic-enriched lagoons: the case study of the Cabras lagoon (Sardinia, Italy)

In organic-enriched sedimentary systems, like many Mediterranean coastal lagoons, a detailed analysis of sediment grain size composition and partitioning within the muds is crucial to investigate sedimentological trends related to both hydrodynamic energy and basin morphology. In these systems, sediment dynamics are particularly important because the partitioning and transport of fine sediments can strongly influence the redistribution and accumulation of large amounts of organic matter, and consequently the distribution of benthic assemblages and the trophic status and functioning of a lagoon. Nevertheless, studies on benthic-sediment relationships have been based mainly on a rather coarse analysis of sediment grain size features. In muddy systems, however, this approach may impede a proper evaluation of the relationships and effects of the distribution of fine sediment and organic matter on the biotic benthic components. Here we show that the distribution of sedimentary organic matter (OM) and total organic carbon (TOC) in the Cabras lagoon (Sardinia, Italy) can be explained (i.e., predicted) as a function of a nonlinear increase in the amount of the cohesive fraction of sediments (< or = 8 microm grain size particles) and that this fraction strongly influences the structure, composition and distribution of macrobenthic assemblages. Even in such a homogeneously muddy system, characterized by "naturally" occurring impoverished communities, impaired benthic assemblages were found at < or = 8 microm, OM, TOC contents of about 77%, 11% and 3.5%, respectively. A review of studies conducted in Mediterranean coastal lagoons highlighted a lack of direct integrated analysis of sediment features and the biotic components. We suggest that, especially in organic-enriched coastal lagoons, monitoring programs should primarily investigate and consider the cohesive fraction of sediments in order to allow a better assessment of benthic-sediment relationships and ecological quality of the system.     

Late Cretaceous scleractinian corals from the rocky shore of Ivö Klack, southern Sweden, including some of the northernmost zooxanthellate corals

A relatively low diversity coral fauna comprising eight zooxanthellate, three azooxanthellate, and one unidentified species is described from a Late Cretaceous rocky shore at Ivö Klack, southern Sweden. All species, except the solitary azooxanthellate Paracyathus? sp., are represented by one or two specimens only, indicating low preservation potential similar to the aragonite-shelled gastropod fauna from the same locality. The fauna comprises one out of two northernmost zooxanthellate forms known and adds important environmental information to the fauna and depositional conditions of the rocky shore at Ivö Klack.     

Landslide phenomena in the area of Pomarico (Basilicata–Italy): methods for modelling and monitoring

This paper takes into consideration landslide phenomena in the clayey slopes facing the built-up area of Pomarico which is situated in the southern part of the “Fossa Bradanica”, in Basilicata (Italy). Based on the great number of geologic, geomorphologic and historic informations a geotechnical model of the slope was built. Particular attention has been paid to define the geotechnical parameters of the soil and which mechanical models are to be used. The studies point out a correlation between the water level in the detritus cover and the stability condition of the slope showing that phenomena at first located at the foot of the slope spread quickly towards its summit as the piezometric height increases.     

Stream Temperature Modeling and Fiber Optic Temperature Sensing to Characterize Groundwater Discharge

The Ngongotaha Stream was used as a case study to assess the applicability of fiber optic distributed temperature sensing (FODTS) to identify the location of springs and quantify their discharge. Thirteen springs were identified, mostly located within a 115 m reach, five discharged from the right bank and eight from the left bank. To quantify groundwater discharge, a new approach was developed in which the one-dimensional transient heat transport model was fitted to the FODTS measurements, where the main calibration parameters of interest were the unknown spring discharges. The spatial disposition of the groundwater discharge estimation problem was constrained by two sources of information; first, the stream gains ∼500 L/s as determined by streamflow gauging. Second, the temperature profiles of the left and right banks provide the spatial disposition of springs and their relative discharges. FODTS was used to measure stream temperature near the left and right banks, which created two temperature datasets. A weighted average of the two datasets was then calculated, where the weights reflected the degree of mixing between the right and left banks downstream of a spring. The new approach in this study marks a departure from previous studies, in which the general approach was to use the steady-state thermal mixing model (Selker et al. 2006a; Westhoff et al. 2007; Briggs et al. 2012) to infer groundwater discharge, which is then used as an input into a transient model of the general form of equation to simulate stream temperature (Westhoff et al. 2007).     

Area-scale landslide hazard and risk assessment

The paper deals with a methodology for quantitative landslide hazard and risk assessments over wide-scale areas. The approach was designed to fulfil the following requirements: (1) rapid investigation of large study areas; (2) use of elementary information, in order to satisfy the first requirement and to ensure validation, repetition and real time updating of the assessments every time new data are available; (3) computation of the landslide frequency of occurrence, in order to compare objectively different hazard conditions and to minimize references to qualitative hazard attributes such as activity states. The idea of multi-temporal analysis set forth by Cardinali et al. (Nat Hazards Earth Syst Sci 2:57–72, 2002), has been stressed here to compute average recurrence time for individual landslides and to forecast their behaviour within reference time periods. The method is based on the observation of the landslide activity through aerial-photo surveys carried out in several time steps. The output is given by a landslide hazard map showing the mean return period of landslides reactivation. Assessing the hazard in a quantitative way allows for estimating quantitatively the risk as well; thus, the probability of the exposed elements (such as people and real estates) to suffer damages due to the occurrence of landslides can be calculated. The methodology here presented is illustrated with reference to a sample area in Central Italy (Umbria region), for which both the landslide hazard and risk for the human life are analysed and computed. Results show the powerful quantitative approach for assessing the exposure of human activities to the landslide threat for a best choice of the countermeasures needed to mitigate the risk.An erratum to this article can be found at