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Statistical postprocessing techniques are nowadays key components of the forecasting suites in many national meteorological services (NMS), with, for most of them, the objective of correcting the impact of different types of errors on the forecasts. The final aim is to provide optimal, automated, seamless forecasts for end users. Many techniques are now flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias corrections to very sophisticated distribution-adjusting techniques that incorporate correlations among the prognostic variables. The paper is an attempt to summarize the main activities going on in this area from theoretical developments to operational applications, with a focus on the current challenges and potential avenues in the field. Among these challenges is the shift in NMS toward running ensemble numerical weather prediction (NWP) systems at the kilometer scale that produce very large datasets and require high-density high-quality observations, the necessity to preserve space-time correlation of high-dimensional corrected fields, the need to reduce the impact of model changes affecting the parameters of the corrections, the necessity for techniques to merge different types of forecasts and ensembles with different behaviors, and finally the ability to transfer research on statistical postprocessing to operations. Potential new avenues are also discussed.

In this paper we discuss the use of system dynamics as a methodology with which to address dynamically complex problems in water resources management. Problems in regional planning and river basin management, urban water management, flooding and irrigation exhibit important short-term and long-term effects, and are often contentious issues with high potential for conflict. We argue that system dynamics combined with stakeholder involvement provides an appropriate methodology to address these issues effectively. We trace the theoretical and practical evolution of system dynamics in these areas over the past 50 years. From this review of the literature and selected case studies we identify and discuss a number of best practices and common pitfalls in applications of system dynamics simulation.

Hydropedology is an interdisciplinary field that studies the interactions between soil and water, recognizing that soils inuflence hydrological processes through their hydraulic properties, and serve as indicators of hydrological behaviour through their morphological properties that are shaped by water regimes. Given the practical implications of hydropedology and its integration into South Africa's latest soil classicfiation system, an updated categorization of soil forms and 1 657 (1 629 + 28) families was necessary, organizing them into three overarching response groups based on their predominant hydrological responses: recharge, interflow, and responsive. Within these groups, recharge soils are further classified into deep, shallow, and slow subgroups, interflow soils encompass soil/bedrock, shallow, and slow categories, while responsive soils are subdivided into responsive shallow and responsive wet. This paper aims to enhance the reader's comprehension of hydrological responses and simplify the intricacies integrated into South Africa's oficial soil classification system.

An approach is presented for the evaluation of groundwater potential using remote sensing, geographic information system, geoelectrical, and multi-criteria decision analysis techniques. The approach divides the available hydrologic and hydrogeologic data into two groups, exogenous (hydrologic) and endogenous (subsurface). A case study in Salboni Block, West Bengal (India), uses six thematic layers of exogenous parameters and four thematic layers of endogenous parameters. These thematic layers and their features were assigned suitable weights which were normalized by analytic hierarchy process and eigenvector techniques. The layers were then integrated using ArcGIS software to generate two groundwater potential maps. The hydrologic parameters-based groundwater potential zone map indicated that the ‘good' groundwater potential zone covers 27.14% of the area, the ‘moderate' zone 45.33%, and the ‘poor' zone 27.53%. A comparison of this map with the groundwater potential map based on subsurface parameters revealed that the hydrologic parameters-based map accurately delineates groundwater potential zones in about 59% of the area, and hence it is dependable to a certain extent. More than 80% of the study area has moderate-to-poor groundwater potential, which necessitates efficient groundwater management for long-term water security. Overall, the integrated technique is useful for the assessment of groundwater resources at a basin or sub-basin scale.

A variety of methods are available to estimate values of meteorological variables at future times and at spatial scales that are appropriate for local climate change impact assessment. One commonly used method is Change Factor Methodology (CFM), sometimes referred to as delta change factor methodology. Although more sophisticated methods exist, CFM is still widely applicable and used in impact analysis studies. While there are a number of different ways by which change factors (CFs) can be calculated and used to estimate future climate scenarios, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. In this study several categories of CFM (additive versus multiplicative and single versus multiple) for a number of climate variables are compared and contrasted. The study employs several theoretical case studies, as well as a real example from Cannonsville watershed, which supplies water to New York City, USA. Results show that in cases when the frequency distribution of Global Climate Model (GCM) baseline climate is close to the frequency distribution of observed climate, or when the frequency distribution of GCM future climate is close to the frequency distribution of GCM baseline climate, additive and multiplicative single CFMs provide comparable results. Two options to guide the choice of CFM are suggested. The first option is a detailed methodological analysis for choosing the most appropriate CFM. The second option is a default method for use under circumstances in which a detailed methodological analysis is too cumbersome.

As one of nature’s most destructive calamities, floods cause fatalities, property destruction, and infrastructure damage, affecting millions of people worldwide. Due to its ability to accurately anticipate and successfully mitigate the effects of floods, flood modeling is an important approach in flood control. This study provides a thorough summary of flood modeling’s current condition, problems, and probable future directions. The study of flood modeling includes models based on hydrologic, hydraulic, numerical, rainfall–runoff, remote sensing and GIS, artificial intelligence and machine learning, and multiple-criteria decision analysis. Additionally, it covers the heuristic and metaheuristic techniques employed in flood control. The evaluation examines the advantages and disadvantages of various models, and evaluates how well they are able to predict the course and impacts of floods. The constraints of the data, the unpredictable nature of the model, and the complexity of the model are some of the difficulties that flood modeling must overcome. In the study’s conclusion, prospects for development and advancement in the field of flood modeling are discussed, including the use of advanced technologies and integrated models. To improve flood risk management and lessen the effects of floods on society, the report emphasizes the necessity for ongoing research in flood modeling.

It is well-known that climate change significantly impacts ecosystems (at the macro-level) and individual species (at the micro-level). Among the former, estuaries are the most vulnerable and affected ecosystems. However, despite the strong relations between climate change and estuaries, there is a gap in the literature regarding international studies across different regions investigating the impacts of climate change and variability on estuaries in different geographical zones. This paper addresses this need and reviews the impacts of climate change, variability and extreme weather on estuaries. It emphasises the following: (i) a set of climate parameters governing estuarine hydrology and processes; and (ii) a sample of countries in Asia (Bangladesh), Europe (Portugal) and South America (Uruguay). We reviewed the influences of the climatic drivers of the estuarine hydrology, ecological processes and specific species in estuarine communities across the selected geographical regions, along with an analysis of their long-term implications. The key results from the three estuaries are as following: (i) Hilsa fish, of which the catches contribute to 10% of the total earnings of the fishery sector (1% of GDP), are affected by climate-forced hydrological and productivity changes in the Meghna; (ii) extreme droughts and short-term severe precipitation have driven the long-term abundance and spatial distribution of both fish larvae and juveniles/adults in the Mondego; and (iii) the river inflow and fluctuations increases since the early 1970s have contributed to variations in the salinity, the stratification, the oxygen, nutrient and trophic levels and the spatial pattern for the life stages of planktonic species, fish biomass and captures in the Rio de la Plata. The results suggested that immediate action is needed to reduce the vulnerability of estuaries to climate stressors, mainly the changing river flows, storms and sea-level rise. As a contribution to addressing current problems, we described a set of adaptation strategies to foster climate resilience and adaptive capacity (e.g., early-warning systems, dam management to prevent overflows and adaptive fisheries management). The implications of this paper are two-fold. Firstly, it showcases a variety of problems that estuaries face from changing climate conditions. Secondly, the paper outlines the need for suitable adaptive management strategies to safeguard the integrity of such vital ecosystems.

Studies of restoration ecology are well established for northern peatlands, but at an early stage for tropical peatlands. Extensive peatland areas in Southeast Asia have been degraded through deforestation, drainage and fire, leading to on- and off-site environmental and socio-economic impacts of local to global significance. To address these problems, landscape-scale restoration measures are urgently required. This paper reviews and illustrates, using information from on-going trials in Kalimantan, Indonesia, the current state of knowledge pertaining to (i) land-cover dynamics of degraded peatlands, (ii) vegetation rehabilitation, (iii) restoration of hydrology, (iv) rehabilitation of carbon sequestration and storage, and (v) promotion of sustainable livelihoods for local communities. For a 4500 km² study site in Central Kalimantan, Indonesia, we show a 78% reduction in forest cover between 1973 and 2003 and demonstrate that fire, exacerbated by drainage, is the principal driver of land-use change. Progressive vegetation succession follows infrequent, low-intensity fires, but repeated and high-intensity fires result in retrogressive succession towards non-forest communities. Re-wetting the peat is an important key to vegetation restoration and protection of remaining peat carbon stocks. The effectiveness of hydrological restoration is discussed and likely impacts on greenhouse gas emissions evaluated. Initial results indicate that raised water levels have limited short-term impact on reducing CO₂ emissions, but could be critical in reducing fire risk. We conclude that successful restoration of degraded peatlands must be grounded in scientific knowledge, relevant to socio-economic circumstances, and should not proceed without the consent and co-operation of local communities.

Invasive bivalves may cause great ecological, evolutionary, and economic impacts in freshwater ecosystems. Species such as Corbicula fluminea , Dreissena bugensis , Dreissena polymorpha , Limnoperna fortunei, and Sinanodonta woodiana are widely distributed hyper-successful invaders, but several others not yet invasive (or at least not considered as such) may become so in the near future. These species can affect hydrology, biogeochemical cycling, and biotic interactions through several mechanisms, with impacts ranging from individuals to ecosystems. Freshwater invasive bivalves can create no-analog ecosystems, posing serious difficulties for management, but new techniques are becoming available which may enhance options to detect early introductions and mitigate impacts. Although knowledge about the biology of these bivalves has increased considerably in the last two decades, several fundamental gaps still persist; we suggest new research directions that are worth exploring in the near future.