Impact of land use changes on flash flood prediction using a sub-daily SWAT model in five Mediterranean ungauged watersheds (SE Spain)

Graph spiking neural network for advanced urban flood risk assessment

Urban flooding significantly impacts city planning and resident safety. Traditional flood risk models, divided into physical and data-driven types, face challenges like data requirements and limited scalability. To overcome these, this study developed a model combining graph convolutional network (GCN) and spiking neural network (SNN), enabling the extraction of both spatial and temporal features from diverse data sources. We built a comprehensive flood risk dataset by integrating social media reports with weather and geographical data from six Chinese cities. The proposed Graph SNN model demonstrated superior performance compared to GCN and LSTM models, achieving high accuracy (85.3%), precision (0.811), recall (0.832), and F1 score (0.821). It also exhibited higher energy efficiency, making it scalable for real-time flood prediction in various urban environments. This research advances flood risk assessment by efficiently processing heterogeneous data while reducing energy consumption, offering a sustainable solution for urban flood management.

Near future flash flood prediction in an arid region under climate change

Flash floods represent a significant threat, triggering severe natural disasters and leading to extensive damage to properties and infrastructure, which in turn results in the loss of lives and significant economic damages. In this study, a comprehensive statistical approach was applied to future flood predictions in the coastal basin of North Al-Abatinah, Oman. In this context, the initial step involves analyzing eighteen General Circulation Models (GCMs) to identify the most suitable one. Subsequently, we assessed four CMIP6 scenarios for future rainfall analysis. Next, different Machine Learning (ML) algorithms were employed through H2O-AutoML to identify the best model for downscaling future rainfall predictions. Forty distribution functions were then fitted to the future daily rainfall, and the best-fit model was selected to project future Intensity-Duration-Frequency (IDF) curves. Finally, the Soil and Water Assessment Tool (SWAT) model was utilized with sub-daily time steps to make accurate flash flood predictions in the study area. The findings reveal that IITM-ESM is the most effective among GCM models. Additionally, the application of stacked ensemble ML model proved to be the most reliable in downscaling future rainfall. Furthermore, this study highlighted that floods entering urbanized areas could reach 20.33 and 20.70 m³/s under pessimistic scenarios during rainfall events with 100 and 200-year return periods, respectively. This hierarchical comprehensive approach provides reliable results by utilizing the most effective model at each step, offering in-depth insight into future flash flood prediction.

Assessing current and future available resources to supply urban water demands using a high-resolution SWAT model coupled with recurrent neural networks and validated through the SIMPA model in karstic Mediterranean environments

Hydrological simulation in karstic areas is a hard task due to the intrinsic intricacy of these environments and the common lack of data related to their geometry. Hydrological dynamics of karstic sites in Mediterranean semiarid regions are difficult to be modelled mathematically owing to the existence of short wet episodes and long dry periods. In this paper, the suitability of an open-source SWAT method was checked to estimate the comportment of a karstic catchment in a Mediterranean semiarid domain (southeast of Spain), which wet and dry periods were evaluated using box-whisker plots and self-developed wavelet test. A novel expression of the Nash-Sutcliffe index for arid areas (ANSE) was considered through the calibration and validation of SWAT. Both steps were completed with 20- and 10-year discharge records of stream (1996-2015 to calibrate the model as this period depicts minimum gaps and 1985-1995 to validate it). Further, SWAT assessments were made with records of groundwater discharge and relating SWAT outputs with the SIMPA method, the Spain's national hydrological tool. These methods, along with recurrent neural network algorithms, were utilised to examine current and predicted water resources available to supply urban demands considering also groundwater abstractions from aquifers and the related exploitation index. According to the results, SWAT achieved a "very good" statistical performance (with ANSE of 0.96 and 0.78 in calibration and validation). Spatial distributions of the main hydrological processes, as surface runoff, evapotranspiration and aquifer recharge, were studied with SWAT and SIMPA obtaining similar results over the period with registers (1980-2016). During this period, the decreasing trend of rainfalls, characterised by short wet periods and long dry periods, has generated a progressive reduction of groundwater recharge. According to algorithms prediction (until 2050), this declining trend will continue reducing groundwater available to meet urban demands and increasing the exploitation index of aquifers. These results offer valuable information to authorities for assessing water accessibility and to provide water demands in karstic areas.

The impact of tropical cyclones and water conservancy projects on island's flash floods

The analysis of the influencing factors of flash floods, one of the most destructive natural disasters, is the basis of scientific disaster prevention and mitigation. There is little research considering the influence of tropical cyclones (TCs) and water conservancy projects on flash floods, which cannot be ignored in the island areas where flash floods often occur due to the complex influence of various factors. In this study, under the pressure-state-response framework (PSR framework), the factors affecting the distribution of flash floods on Hainan Island, China, from 1970 to 2010 were quantitatively analyzed by using the geographical detector method. By dividing the time period, give full play to the advantages of the PSR framework and show the evolution process of various factors. Different from inland areas, extreme precipitation and tropical cyclones play a major role in the spatial distribution of flash floods on Hainan Island, China, and the driving force of tropical cyclones is 1.1 times that of extreme precipitation on average. Medium-sized reservoirs play the greatest role in the prevention of flash floods on Hainan Island, and their driving forces reach 0.38 times of extreme precipitation on average, followed by large-sized reservoirs and small-sized reservoirs. Large-sized reservoirs are limited in quantity and have limited effectiveness in preventing flash floods on Hainan Island. Therefore, in the forecasting and risk management of flash flood in the island area, more attention should be paid to the impact of extreme precipitation and TCs, and the role of medium-sized reservoir should be fully exerted.

Assessing urban flooding risk in response to climate change and urbanization based on shared socio-economic pathways

Global climate change and rapid urbanization, mainly driven by anthropogenic activities, lead to urban flood vulnerability and uncertainty in sustainable stormwater management. This study projected the temporal and spatial variation in urban flood susceptibility during the period 2020-2050 on the basis of shared socioeconomic pathways (SSPs). A case study in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was conducted for verifying the feasibility and applicability of this approach. GBA is predicted to encounter the increase in extreme precipitation with high intensity and frequency, along with rapid expansion of constructed areas, resulting in exacerbating of urban flood susceptibility. The areas with medium and high flood susceptibility will be expected to increase continuously from 2020 to 2050, by 9.5 %, 12.0 %, and 14.4 % under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively. In terms of the assessment of spatial-temporal flooding pattern, the areas with high flood susceptibility are overlapped with that in the populated urban center in GBA, surrounding the existing risk areas, which is consistent with the tendency of construction land expansion. The approach in the present study will provide comprehensive insights into the reliable and accurate assessment of urban flooding susceptibility in response to climate change and urbanization.

Determining the spatial contributions of land use changes on the streamflow and sediment transport regimes: a case study of the Gorganroud watershed in Iran

Human activities and climate change are recognized as two of the most important drivers of hydrologic variability and have attracted the interest of researchers over the past decade. Changes in land use, dam construction, agricultural development, and global warming are forces that directly or indirectly impact the global and local hydrologic regime. This study examines the effects of these drivers on streamflow and sediment transport in the Gorganroud watershed, located in the north of Iran. In addition, the most sensitive land use patterns are detected using statistical approaches and a hydrologic model. The current study's principal argument is based on the variability of land use patterns during the modeling procedure (2007-2019). The Soil and Water Assessment Tool (SWAT) model is used to consider the land use dynamics during the simulation period based on the hydrological regime of the reference period. The Simple Differential Method (SDM) and Climate Elasticity Method (CEM) are utilized to estimate the contribution rates of land use and climate change in streamflow and sediment transport changes. The results indicate that changes in land use have contributed more than 60% to streamflow and sediment regime changes in all subbasins. A sensitivity analysis of land uses and the spatial distribution of the Human Contribution Rate (HCR) over the study area reveal that an increase in orchard land use (8.7% during the computational period) is primarily responsible for these significant changes.

A review of Soil and Water Assessment Tool (SWAT) studies of Mediterranean catchments: Applications, feasibility, and future directions

The Soil and Water Assessment Tool (SWAT) is a well-established eco-hydrological model that has been extensively applied to watersheds across the globe. This work reviews over two decades (2002-2022) of SWAT studies conducted on Mediterranean watersheds. A total of 260 articles have been identified since the earliest documented use of the model in a Mediterranean catchment back in 2002; of which 62% were carried out in Greece, Italy, or Spain. SWAT applications increased significantly in recent years since 86% of the reviewed papers were published in the past decade. A major objective for most of the reviewed works was to check the applicability of SWAT to specific watersheds. A great number of publications included procedures of calibration and validation and reported performance results. SWAT applications in the Mediterranean region mainly cover water resources quantity and quality assessment and hydrologic and environmental impacts evaluation of land use and climate changes. Nevertheless, a tendency towards a multi-purpose use of SWAT is revealed. The numerous examples of SWAT combined with other tools and techniques outline the model's flexibility. Several studies performed constructive comparisons between Mediterranean watersheds' responses or compared SWAT to other models or methods. The effects of inputs on SWAT outputs and innovative model modifications and improvements were also the focus of some of the surveyed articles. However, a significant number of studies reported difficulties regarding data availability, as these are either scarce, have poor resolution or are not freely available. Therefore, it is highly recommended to identify and develop accurate model inputs and testing data to optimize the SWAT performance.

Predicting temporal and spatial variability in flood vulnerability and risk of rural communities at the watershed scale

Due to land-use and hydrology changes, people are constantly exposed to floods. The adverse impact of floods is greater on vulnerable populations that disproportionately inhabit flood-prone areas. This paper reports a comprehensive study on flood vulnerability of flood prone areas in residential areas of the Tajan watershed, Iran in two periods before 2006 and after 2006. Flood prone area were determined by the random forest (RF) and K-nearest neighbor (KNN) machine learning methods. To reduce time and cost, the vulnerability was assessed only in areas with very high flood hazard using 4 main criteria (social, policy, economic, infrastructure), 40 items, and 210 questionnaires across 40 villages. Independent t-test, Kruskal-Wallis, and paired t-test were used for statistical analysis of questionnaire data. The results of machine learning models (MLMs) showed that the RF model with AUC = 0.92% is more accurate in determining flood prone areas. The results of paired t-test showed that the three criteria of social (mean P1 = 2.97 and P2 = 3.35), infrastructure (mean P1 = 2.88 and P2 = 3.25), and policy (mean P1 = 3.02 and P2 = 3.50) had significant changes in both periods. The Kruskal-Wallis test also revealed the mean of all four criteria in both periods and all sub-watersheds, except three sub-watersheds 10 (Khalkhil village), 19 (Tellarem and Kerasp villages), and 23 (Dinehsar and Jafarabad), had a significant difference. The results of the t-test also showed a decrease in vulnerability in the second period (before 2006) compared to the first period (after 2006), so the number of sub-watersheds in the very high vulnerability class was more in the first period than in the second period. A vulnerability map was developed using three factors of risk zone area, area of each sub-watershed, and population of each sub-watershed.

Combining catastrophe technique and regression analysis to deduce leading landscape patterns for regional flood vulnerability: A case study of Nanjing, China

Urbanization leads to changes in land use, and the expansion of impervious surfaces leads to an increase in flood vulnerability. Predicting and analyzing these landscape pattern changes are important in the early stages of urban planning. In practice, the threshold for obtaining comprehensive and detailed hydrological and meteorological data is high, which makes it difficult for landscape and urban planners to quickly evaluate urban floods. To compensate for these trends, we took Nanjing, China, as the study site and discussed the leading flood vulnerability landscape patterns based on quantitative assessments. We introduced catastrophe theory to integrate three indicators and seven subfactors for flood vulnerability assessment: exposure, including precipitation; sensitivity, including elevation, slope, soil and drainage density; and adaptability, including land use and forest coverage. Then, we calculated the landscape pattern metrics (shape index, fractal dimension index, related circumscribing circle, contiguity index and landscape division index) at the class level. Finally, we divided the city into four subregions, established regression models for the subregions and the whole city, and deduced the leading flood vulnerability landscape patterns in each region and the whole city. We found that the leading landscape patterns varied among different regions. According to the research results, the landscape pattern indexes identified in this paper can be interpreted intuitively, which can provide a reference for modifying the planning layout of regional green infrastructure, optimizing the vulnerability of urban floods, and providing a basis for further improving Nanjing urban planning and alleviating the urban flood vulnerability. The methods proposed herein also will benefit land use and green infrastructure management in other regions lacking meteorological and hydrological data.

Modelling Water Flow and Soil Erosion in Mediterranean Headwaters (with or without Check Dams) under Land-Use and Climate Change Scenarios Using SWAT

The use of check dams is a common strategy to reduce soil erosion in the Mediterranean headwaters. However, the effects of these control works on water flow rates and sediment yields have been scarcely investigated under possible scenarios of climate and land-use changes. On this regard, the use of hydrological models, such as SWAT, provide reliable hydrological predictions under variable environmental conditions. To fill this gap, this study has evaluated the effectiveness of check dams on the hydrological response of a forest headwater in Calabria (Southern Italy) in comparison with an unregulated subcatchment with very similar environmental conditions. In this regard, the effects of different combined scenarios of climate change (through three GCMs and two RCPs applied to a time period of the next 80 years) and land use (forest, pasture, and cropland) on water flow rates and sediment yields in the two headwaters were analysed using the SWAT model. The SWAT model was first calibrated in a third headwater with very similar climatic, soil, and land-use conditions, and this verification showed a satisfactory prediction capacity of water flow rate. The water flow rate prediction capacity of the model was satisfactory (coefficients of determination and efficiency of Nash and Sutcliffe equal to 0.71 and 0.67, respectively, and percent bias of 14.9%). No significant differences were detected for the water flow rates and sediment yields between the two subcatchments (with or without check dams) among the different land-use and climate change scenarios. This was linked to the low hydrological response of both headwaters to the forcing actions, which influenced the low effectiveness of the control works. SWAT estimated higher values of both mean and maximum values of water flow rates and sediment yields under RCP2.6 compared with RCP8.5. Both water flow rates and sediment yields were predicted to be very low under all climate and land-use scenarios. The regulated headwater with check dams was predicted to always produce more runoff and erosion compared with the subcatchment without check dams. The increases were predicted to be up to 60% for the maximum flow rate and 30–35% for the sediment yield in forest land use under RCP2.6. Although there was a limitation in this study due to the lack of validation of the erosion data (due to unavailable records of sediment yield), this study demonstrated how the use of check dams in headwater catchments may be not effective for soil conservation purposes several decades after their installation in Mediterranean semiarid areas, where the water flow and erosion rate are limited.

The qualitative analysis of the nexus dynamics in the Pekalongan coastal area, Indonesia

Several studies investigated the dynamics of coastal areas, investigating some issues such as sea-level rise, floods, and water scarcity. Despite existing studies discussing coastal areas, there are limited studies investigating Asian coastal areas and their proposed solutions may not overcome extreme events. This study investigates the dynamics of the Pekalongan coastal area, Central Java, Indonesia. Despite efforts such as the development of dikes and groundwater pumping, people in Pekalongan have currently experienced more frequent floods and land subsidence that have led to larger inundated areas and people migration. Using the system archetypes, this study shows that the coastal area consists of renowned nexus elements (water, land, and food) and less recognized nexus elements (health and wellbeing). This means that changes in one nexus element may threaten other nexus elements, exacerbating problems in the observed system. For instance, unsustainable nexus actions such as overexploited groundwater tend to increase flooded areas, threatening people health, and inducing people migration. The system archetypes also show that the coastal area consists of Limits to Growth structures. As such, growth engines such as land-use change and groundwater pumping should be managed or restricted properly. Managing growth engines can prevent us from natural disasters such as floods and water scarcity. Likewise, as the system archetypes describe generic patterns and solutions, some findings of this study can be useful for the other coastal areas.

The Effects of Agricultural Conservation Practices on the Small Water Cycle: From the Farm- to the Management-Scale

Reinforcing the small water cycle is considered to be a holistic approach to both water resource and landscape management. In an agricultural landscape, this can be accomplished by incorporating agricultural conservation practices; their incorporation can reduce surface runoff, increase infiltration, and increase the water holding capacity of a soil. Some typical agricultural conservation practices include: conservation tillage, contour farming, residue incorporation, and reducing field sizes; these efforts aim to keep both water and soil in the landscape. The incorporation of such practices has been extensively studied over the last 40 years. The Soil and Water Assessment Tool (SWAT) was used to model two basins in the Czech Republic (one at the farm-scale and a second at the management-scale) to determine the effects of agriculture conservation practice adoption at each scale. We found that at the farm-scale, contour farming was the most effective practice at reinforcing the small water cycle, followed by residue incorporation. At the management-scale, we found that the widespread incorporation of agricultural conservation practices significantly reinforced the small water cycle, but the relative scale and spatial distribution of their incorporation were not reflected in the SWAT scenario analysis. Individual farmers should be incentivized to adopt agricultural conservation practices, as these practices can have great effects at the farm-scale. At the management-scale, the spatial distribution of agricultural conservation practice adoption was not significant in this study, implying that managers should incentivize any adoption of such practices and that the small water cycle would be reinforced regardless.

Land-use changes and precipitation cycles to understand hydrodynamic responses in semiarid Mediterranean karstic watersheds

Non-planned agricultural land abandonment is affecting natural hydrological processes. This is especially relevant in vulnerable arid karstic watersheds, where water resources are scarce but vital for sustaining natural ecosystems and human settlements. However, studies assessing the spatiotemporal evolution of the hydrological responses considering land-use changes and precipitation cycles for long periods are rare in karstic environments. In this research, we selected a representative karstic watershed in a Mediterranean semiarid domain, since in this belt, karst environments are prone to land degradation processes due to human impacts. Geographic Information Systems-based tools and hydrological modeling considering daily time steps were combined with temporal analysis of climate variables (wavelet analysis) to demonstrate possible interactions and vulnerable responses. Observed daily flow data were used to calibrate/validate these hydrological models by applying statistic indicators such as the NSE efficiency and a self-developed index (the ANSE index). This new index could enhance goodness-of-fit measurements obtained with traditional statistics during the model optimization. We hypothesize that this is key to adding new inputs to this research line. Our results revealed that: i) changes in the type of sclerophyllous vegetation (Quercus calliprinos, ilex, rotundifolia, suber, etc.) from 81.5% during the initial stage (1990) to natural grasslands by 81.6% (2018); and, ii) decreases in agricultural areas (crops) by approximately 60% and their transformation into coniferous forests, rock outcrops, sparsely natural grasslands, etc. in the same period. Consequently, increases in the curve number (CN) rates were identified as a result of land abandonment. As a result, an increase in peak flow events jointly with a relevant decrease of the average flow rates (water scarcity) in the watershed was predicted by the HEC-HMS model and verified through the observed data. This research provides useful information about the effects of anthropogenic changes in the hydrodynamic behaviour of karstic watersheds and water resource impacts, especially key in water-scarce areas that depict important hazards for the water supply of related populations and natural ecosystems.

Environmental and Biophysical Effects of the Bowen Ratio over Typical Farmland Ecosystems in the Loess Plateau

The Bowen ratio (β) comprehensively reflects physical characteristics of the land-surface climate. In this study, eddy covariance systems installed at Dingxi and Qingyang were used to conduct energy distribution measurements and observations characteristic of semi-arid and semi-humid farmland ecosystems on the China Loess Plateau. We studied mechanisms by which eco-environmental factors influence β. Additionally, we investigated responses of physiological and ecological factors to water and heat exchange under seasonally dry and wet conditions within each farmland ecosystem. Our results showed that sensible heat flux in the semi-arid farmland was the main consumer of available energy. In the semi-humid area, latent heat flux in summer had the dominant role in energy distribution (mean β 0.71). The β in the semi-arid region was 1.5 times higher than that in the semi-humid region during the growing season. β increased with an increase in the vapor pressure deficit (VPD) and ground–air temperature difference (Ts − Ta), and decreased significantly with an increase in effective precipitation and soil moisture. The change in β with environmental factors was more clear-cut in semi-arid areas than in semi-humid areas. The Priestley–Taylor coefficient (α) and β satisfied a power function law in the growing season. There was a strong correlation between them, with the coefficients of determination for semi-humid and semi-arid areas being 0.62 and 0.72, respectively. β decreased with an increase in the normalized difference vegetative index (NDVI), with this phenomenon being more obvious in the semi-humid zone (R2 = 0.40). β responded more rapidly to NDVI in the semi-arid area than in the semi-humid area. There was a negative exponential relationship between canopy stomatal conductance (Gs) and β, which displayed a stronger declining trend with the increase in Gs in the semi-arid area than in the semi-humid area. This study provides an important reference for the determination of land-surface characteristics of semi-arid and semi-humid farmland ecosystems on the Loess Plateau and for improving parameterization of land-surface processes.

Surface runoff response to long-term land use changes: Spatial rearrangement of runoff-generating areas reveals a shift in flash flood drivers

Nowadays, rapid growths of urban areas and associated land use/land cover (LULC) changes notably affect the surface runoff response to rainfall in urbanised catchments. This effect of urbanisation on surface runoff is frequently addressed since it relates to the increasing incidence of pluvial floods worldwide. Studies on this issue commonly assess runoff changes over several most recent decades. However, human-induced factors likely resulted in increased surface runoff and associated flash floods in rural catchments even in the past centuries. Such long-term changes have been rarely studied and thus are not well documented. This paper aims to fill this gap and assess the surface runoff response to LULC changes in a small catchment in southwestern Slovakia over more than two centuries. To meet this goal, we applied the Soil Conservation Service Curve Number (SCS-CN) method. We mapped past (1784) and present (2018) LULC classes based on historical maps and modern remote sensing data. Then, we estimated surface runoff depths for specific design rainstorms for both periods by executing CN method equations in the ArcGIS environment. Results revealed significant changes in surface runoff conditions between evaluated periods. In total, surface runoff magnitudes increased by ~230 and ~ 130% for 40- and 65-mm design rainstorms, respectively, compared to 1784. Moreover, surface runoff values show different spatial patterns on historical and present-day output raster images revealing spatial redistribution of runoff-enhancing and runoff-preventing areas during the evaluated period. Although both infiltration-enhancing and runoff-enhancing effects of LULC changes were identified, the latter effect associated with urbanised lowland areas was recognised as prevailing at present. In contrast, runoff-promoting conditions were associated with hilly vineyard areas in the past. These findings likely have important implications for understanding the past and present LULC-based controls of surface runoff generation and flash floods initiation.

Flood impact on the Spanish Mediterranean coast since 1960 based on the prevailing synoptic patterns

In a changing climate and in social context, tools and databases with high spatiotemporal resolution are needed for increasing the knowledge on the relationship between meteorological events and flood impacts; hence, analysis of high-resolution spatiotemporal databases with detailed information on the frequency, intensity, and impact of floods is necessary. However, the methodological nature of flood databases hinders relating specific flood events to the weather events that cause them; hence, methodologies for classifying flood cases according to the synoptic patterns that generate them are also necessary. Knowing which synoptic patterns are likely to generate risk situations allows for a probabilistic approach with high spatial resolution regarding the timing of occurrence, affected area, and expected damage from floods. To achieve these objectives, we use the SMC-Flood Database, a high-resolution spatiotemporal flood database covering the 1960-2015 period for all municipalities along the Spanish Mediterranean coast. To relate floods with the synoptic conditions that generated them, we used a multivariate analysis method on the corrected daily anomalies of the surface pressure fields, 850 hPa temperature, and 500 hPa geopotential height, all of which were obtained from the 20th Century Reanalysis Project V2. Results show that 12 atmospheric synoptic patterns can statistically explain the 3608 flood cases that occurred in the study area between 1960 and 2015. These flood cases were classified into 847 atmospherically induced flood events. These results reduce the uncertainty during decision making because of the classification of potential risk situations. The Mediterranean Basin is a region where floods have serious socioeconomic impacts; hence, this work helps improving prevention measures and providing information for policymakers, mainly regarding land use planning and early warning systems.

Impact of Climate Change on the Hydrology of the Forested Watershed That Drains to Lake Erken in Sweden: An Analysis Using SWAT+ and CMIP6 Scenarios

Precipitation and temperature around the world are expected to be altered by climate change. This will cause regional alterations to the hydrological cycle. For proper water management, anticipating these changes is necessary. In this study, the basin of Lake Erken (Sweden) was simulated with the recently released software SWAT+ to study such alterations in a short (2026–2050), medium (2051–2075) and long (2076–2100) period, under two different climate change scenarios (SSP2-45 and SSP5-85). Seven global climate models from the latest projections of future climates that are available (CIMP 6) were compared and ensembled. A bias-correction of the models’ data was performed with five different methods to select the most appropriate one. Results showed that the temperature is expected to increase in the future from 2 to 4 °C, and precipitation from 6% to 20%, depending on the scenario. As a result, water discharge would also increase by about 18% in the best-case scenario and by 50% in the worst-case scenario, and the surface runoff would increase between 5% and 30%. The floods and torrential precipitations would also increase in the basin. This trend could lead to soil impoverishment and reduced water availability in the basin, which could damage the watershed’s forests. In addition, rising temperatures would result in a 65% reduction in the snow water equivalent at best and 92% at worst.

Investigation of Flood Management and Mitigation Measures in Ungauged NATURA Protected Watersheds

The aim of this study is to investigate the flood management and mitigation measures in ungauged NATURA protected watersheds. The examined watersheds are located in one the most European significant NATURA areas (Prespa Natural Park North Greece). SCS-CN model was applied to perform the hydrological modeling for extreme rainfalls of 50, 100 and 1000 return periods. Extensive field research was conducted to record all the hydrotechnical works of the study area, to evaluate their current condition and measure the respective hydraulic characteristics. The results of the hydrological modeling showed that the flood danger in the study area is generally low. However, almost the half of the hydrotechnical works could not discharge the high and medium probability (50 and 100 years) peak flows. The main causes are the extremely dense riparian vegetation that has been developed on the banks and the thalweg of the riverbeds and in some cases the inappropriate dimensioning of the technical works. The intense development of the riparian vegetation, has increased the roughness coefficient and reduced the dimensions and discharge capability of the technical works, while NATURA restrictions and regulations may be limiting any logging and trimming activities within the streams, especially in priority habitat types. Special Ecological Evaluation studies and educating the public about the necessity of the flood control measures and impact, could provide a framework for a thorough discussion about the flood management in NATURA areas.

Impacts and social implications of landuse-environment conflicts in a typical Mediterranean watershed

In coastal watersheds, services and landuse favour coastal tourism and urbanization, depriving rural upstream of infrastructure and attention. This unbalanced management leads to an intensification of socioeconomic changes that generate a structural heterogeneity of the landscape and a reduction in the livelihoods of the rural population. The incessant dissociation between the objectives of the stakeholders triggers landuse-environment-economy conflicts which threaten to mutate large-scale development programs. Here, we used multi-assessment techniques in a Mediterranean watershed from Morocco to evaluate the effects of landuse change on water, vegetation, and perception of the rural population towards environmental issues. We combined complementary vegetation indexes (NDVI and EVI) to study long-term landuse change and phenological statistical pixel-based trends. We assessed the exposure of rural households to the risk of groundwater pollution through a water analysis supplemented by the calculation of an Integrated Water Quality Index. Later, we contrasted the findings with the results of a social survey with a representative sample of 401 households from 7 villages. We found that rapid coastal linear urbanization has resulted in a 12-fold increase in construction over the past 35 years, to the detriment of natural spaces and the lack of equipment and means in rural areas upstream. We show that the worst water qualities are linked to the negative impact of anthropogenic activities on immediately accessible water points. We observe that rural households are aware of the existence and gravity of environmental issues but act confusedly because of their low education level which generates a weak capacity to understand cause and effect relationships. We anticipate the pressing need to improve the well-being and education of the population and synergistically correct management plans to target the watershed as a consolidated system. Broadly, stakeholders should restore lost territorial harmony and reallocate landuse according to a sustainable environment-socioeconomic vision.

Urbanization and climate change impacts on future flood risk in the Pearl River Delta under shared socioeconomic pathways

Climate change and urbanization are converging to challenge the flood control in the Pearl River Delta (PRD) due to their adverse impacts on precipitation extremes and the urban areas environment. Previous studies have investigated temporal changes in flood risk with various single factor, few have considered the joint effects of climate change, urbanization and socio-economic development. Here, based on the representative concentration pathway (RCP) scenarios, we conducted a comprehensive assessment of future (2030-2050) flood risk over the PRD combined with a thorough investigation of climate change, urbanization and socio-economic development. Precipitation extremes were projected using the regional climate model RegCM4.6, and urbanization growth was projected based on the CA-Markov model. The economic and population development was estimated by the shared socio-economic pathways (SSPs). Flood risk mapping with different RCPs-urbanization-SSPs scenarios was developed for the PRD based on the set pair analyze theory. The results show that climate change and urbanization are expected to exacerbate flood risk in most parts of the PRD during the next few decades, concurrently with more intense extreme precipitation events. The high flood risk areas are projected mainly in the urban regions with unfavorable terrain and dense population. The highest flood risk areas are expected to increase by 8.72% and 19.80% under RCP4.5 and RCP8.5 scenarios, respectively. Reducing greenhouse gas emissions may effectively mitigate the flood risk over the PRD. This study highlight the links between flood risk and changing environment, suggesting that flood risk management and preventative actions should be included in regional adaptation strategies.

Research of Impacts of the 2018 Hokkaido Eastern Iburi Earthquake on Sediment Transport in the Atsuma River Basin Using the SWAT Model

Landslides, debris flows, and other secondary disasters caused by earthquakes threaten the safety and stability of river basins. Earthquakes occur frequently in Japan. Therefore, it is necessary to study the impact of earthquakes on sediment transport in river basins. In this study, considering the influence of reservoirs, the Soil and Water Assessment Tool-calibration and uncertainty program (SWAT-CUP) was employed to analyze the runoff parameter sensitivity and to optimize the parameters. We manually corrected the sediment transport parameters after earthquake, using the Soil and Water Assessment Tool (SWAT) model to assess the process of runoff and sediment transport in the Atsuma River basin before and after the 2018 Hokkaido Eastern Iburi Earthquake. The applicability of the SWAT model to runoff simulation in the Atsuma River basin and the changes of sediment transport process after the earthquake were studied. The research results show that the SWAT model can accurately simulate the runoff process in the Atsuma River basin, the Nash–Sutcliffe efficiency coefficient (NSE) is 0.61 in the calibration period, and is 0.74 in the verification period. The sediment transport increased greatly after the earthquake and it is roughly estimated that the amount of sediment transport per unit rainfall increased from 3.5 tons/mm/year before the earthquake to 6.2 tons/mm/year after the earthquake.

Geostatistical Analysis of the Spatial Correlation between Territorial Anthropization and Flooding Vulnerability: Application to the DANA Phenomenon in a Mediterranean Watershed

Climate change is making intense DANA (depresión aislada en niveles altos) type rains a more frequent phenomenon in Mediterranean basins. This trend, combined with the transformation of the territory derived from diffuse anthropization processes, has created an explosive cocktail for many coastal towns due to flooding events. To evaluate this problem and the impact of its main guiding parameters, a geostatistical analysis of the territory based on GIS indicators and an NDVI (Normalized Difference Vegetation Index) analysis is developed. The assessment of the validity of a proposed methodology is applied to the case study of the Campo de Cartagena watershed located around the Mar Menor, a Mediterranean coastal lagoon in Southeastern Spain. This area has suffered three catastrophic floods derived from the DANA phenomenon between 2016 and 2019. The results show that apart from the effects derived from climate change, the real issue that amplifies the damage caused by floods is the diffuse anthropization process in the area, which has caused the loss of the natural hydrographic network that traditionally existed in the basin.

A temporal record of microplastic pollution in Mediterranean seagrass soils

Plastic pollution is emerging as a potential threat to the marine environment. In the current study, we selected seagrass meadows, known to efficiently trap organic and inorganic particles, to investigate the concentrations and dynamics of microplastics in their soil. We assessed microplastic contamination and accumulation in 210Pb dated soil cores collected in Posidonia oceanica meadows at three locations along the Spanish Mediterranean coast, with two sites located in the Almería region (Agua Amarga and Roquetas) and one at Cabrera Island (Santa Maria). Almería is known for its intense agricultural industry with 30 000 ha of plastic-covered greenhouses, while the Cabrera Island is situated far from urban areas. Microplastics were extracted using enzymatic digestion and density separation. The particles were characterized by visual identification and with Fourier-transformed infrared (FTIR) spectroscopy, and related to soil age-depth chronologies. Our findings showed that the microplastic contamination and accumulation was negligible until the mid-1970s, after which plastic particles increased dramatically, with the highest concentrations of microplastic particles (MPP) found in the recent (since 2012) surface soil of Agua Amarga (3819 MPP kg-1), followed by the top-most layers of the soil of the meadows in Roquetas (2173 kg-1) and Santa Maria (68-362 kg-1). The highest accumulation rate was seen in the Roquetas site (8832 MPP m-2 yr-1). The increase in microplastics in the seagrass soil was associated to land-use change following the intensification of the agricultural industry in the area, with a clear relationship between the development of the greenhouse industry in Almería and the concentration of microplastics in the historical soil record. This study shows a direct linkage between intense anthropogenic activity, an extensive use of plastics and high plastic contamination in coastal marine ecosystems such as seagrass meadows. We highlight the need of proper waste management to protect the coastal environment from continuous pollution.

Advanced hydrological streamflow simulation in a watershed using adjusted radar-rainfall estimates as meteorological input data

Among the input data of the watershed model for simulating changes of flowrate in the watershed, weather input data, especially input data related to rainfall, are the most important. Therefore, it is important to ensure the accuracy of rainfall input data to increase the accuracy of the watershed model results. Securing rainfall measurements with finer spatial and temporal resolutions is important in predicting flowrate variations at a sub-catchment, especially as they relate to global and local climate changes in weather conditions such as rainfall depth, rainfall intensity, etc. In this study, adjusted radar-rainfall estimates were suggested as alternative input data for watershed modeling. Through a statistical analysis of the representativeness of a ground rainfall measurement (10 km × 10 km grid), the necessity of radar-rainfall estimates (2 km × 2 km grid) was identified. By applying calibration factors to initial radar-rainfall estimates and comparing adjusted radar-rainfall estimates with ground rainfall measurements, it was proven that adjusted radar-rainfall estimates could be used as input data for watershed simulations (NSE > 0.92; n = 12). Adjusted radar-rainfall estimates and ground rainfall measurements were used as input data of the Soil and Water Assessment Tool model to predict flowrate variations at the outlets of a tributary and the entire watershed. As a result, the accuracies of the simulation results were improved for the outlets of a tributary and the entire watershed (NSE: 0.33 to 0.48 and 0.19 to 0.55, respectively). To obtain more reliable rainfall data, radar images easily accessible to users were applied, and the accuracy of the data was increased by applying simple equations to numerical data extracted from radar image processing. Additionally, the applicability of the adjusted radar-rainfall estimates was demonstrated by comparing the modeling results using the suggested rainfall data and existing ground-based rainfall data. The suggested methodologies are expected to contribute to more accurately predict the possibility of flood disasters in other regions and countries lacking infrastructure related to rainfall measurements and to establish appropriate countermeasures.

Farm-Scale Biofuel Crop Adoption and Its Effects on In-Basin Water Balance

In the face of future climate change, Europe has encouraged the adoption of biofuel crops by its farmers. Such land-use changes can have significant impacts on the water balance and hydrological behavior of a system. While the heavy pesticide use associated with biofuel crops has been extensively studied, the water balance impacts of these crops have been far less studied. We conducted scenario analyses using the Soil and Water Assessment Tool (SWAT) to determine the effects of farm-scale biofuel crop adoption (rapeseed) on a basin’s water balance. We found that rapeseed adoption does not support the goal of developing a sustainable agricultural landscape in the Czech Republic. The adoption of rapeseed also had disproportionate effects on a basin’s water balance depending on its location in the basin. Additionally, discharge (especially surface runoff ratios), evapotranspiration, and available soil water content display significant shifts in the rapeseed adoption scenarios.

Multi-Criteria Evaluation (MCE) Method for the Management of Woodland Plantations in Floodplain Areas

The potential of woodland and floodplain woodland plantations in a wide area, of high flood risk, along the Spey River (Scotland) is investigated, to mitigate the floods’ catastrophic impact. The spatial analysis required various datasets to be overlaid, to define the suitable sites for woodland and floodplain woodland establishment. These datasets that concern the topography, the physical and technical characteristics (existing woodland, road system, urban and rural areas, river system and open water areas, railway) and the protected sites of the study area were obtained and merged using Geographical Information System (GIS) techniques. The most suitable and unsuitable areas within the region were identified, using multi-criteria evaluation methods (Boolean approach). In total, 13 constraints were created by expressing true/false statements for each factor, and were combined together using spatial analysis tools. The results revealed the high potential of woodland and floodplain woodland plantations to prevent floods, with 59.2% of the total study area (177.5 km2) determined to be appropriate for such practices’ application. The River Dulnain tributary demonstrated the highest potential for floodplain woodland planting, followed by Rivers Avon and Fiddich, and the southwestern and northeastern Spey River parts. The methodology proposed is simple and provides rapid and accurate results at low cost, while the datasets can be easily accessed and are available in convenient type/format. This useful methodology for researchers and authorities could be applied successfully to similar watersheds, contributing significantly to flood risk mitigation and the enhancement of the flood-preventative measures’ planning efficiency.

Future Flood Risk Assessment under the Effects of Land Use and Climate Change in the Tiaoxi Basin

Global warming and land-use change affects runoff in the regional basin. Affected by different factors, such as abundant rainfall and increased impervious surface, the Taihu basin becomes more vulnerable to floods. As a result, a future flood risk analysis is of great significance. This paper simulated the land-use expansion and analyzed the surface change from 2020 to 2050 using the neural network Cellular Automata Markov (CA-Markov) model. Moreover, the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) dataset was corrected for deviation and used to analyze the climate trend. Second, the verified SWAT model was applied to simulate future runoff and to analyze the future flood risk. The results show that (1) land use is dominated by cultivated land and forests. In the future, the area of cultivated land will decrease and construction land will expand to 1.5 times its present size. (2) The average annual precipitation and temperature will increase by 1.2% and 1.5 degrees from 2020 to 2050, respectively. During the verified period, the NSE and r-square values of the SWAT model are greater than 0.7. (3) Compared with the historical extreme runoff, the extreme runoff in the return period will increase 10%~25% under the eight climate models in 2050. In general, the flood risk will increase further under the climate scenarios.

Evaluation of sustainability of river Krishna under present and future climate scenarios

The rise in greenhouse gases, carbon dioxide concentrations in the atmosphere, along with the warmer climate and Land Use/Land Cover (LULC) changes may have a significant impact on water resources of the local hydrological regime. Hence, it is essential to assess the river basin response to corresponding changes to providing a reliable, resilient, sustainable management system in future. So, the present study focuses on providing a robust framework to evaluate sustainability of river Krishna under future climate scenarios. A novel framework was developed with the help of Bayesian Networks (BNs) known as the River Sustainability Bayesian Network (RSBN) model. It contains twenty-one parameters, which covers socio-economic and environmental dimensions of sustainability. In these twenty-one parameters, ten parameters are root (independent) nodes, and the other eleven parameters were child nodes of these root nodes. The proposed RSBN model offers a unique combination of parameters, which includes various aspects of river basin such as water quality, quantity, climatic conditions, and LULC changes along with ecological management in the basin. The parameters used are flexible enough to modify based on user requirements. Under the Representative Concentration Pathway (RCP) 8.5 scenario, the model shows basin progress towards medium sustainability from mid-century onwards, whereas there is no significant change in river sustainability under the RCP 4.5 scenario. The sustainability of the basin is expected to be highly sensitive to extreme events followed by changes to water stress, environmental flow. The present model framework may help policymakers and water managers for sustainable planning and management of water resources of the basin.

Hydrologic Assessment of TRMM and GPM-Based Precipitation Products in Transboundary River Catchment (Chenab River, Pakistan)

Water resources planning and management depend on the quality of climatic data, particularly rainfall data, for reliable hydrological modeling. This can be very problematic in transboundary rivers with limited disclosing of data among the riparian countries. Satellite precipitation products are recognized as a promising source to substitute the ground-based observations in these conditions. This research aims to assess the feasibility of using a satellite-based precipitation product for better hydrological modeling in an ungauged and riparian river in Pakistan, i.e., the Chenab River. A semidistributed hydrological model of The soil and water assessment tool (SWAT) was set up and two renowned satellite precipitation products, i.e., global precipitation mission (GPM) IMERG-F v6 and tropical rainfall measuring mission (TRMM) 3B42 v7, were selected to assess the runoff pattern in Chenab River. The calibration was done from 2001–2006 with two years of a warmup period. The validation (2007–2010) results exhibit higher correlation between observed and simulated discharges at monthly timescale simulations, IMERG-F (R2 = 0.89, NSE = 0.82), 3B42 (R2 = 0.85, NSE = 0.72), rather than daily timescale simulations, IMERG-F (R2 = 0.66, NSE = 0.61), 3B42 (R2 = 0.64, NSE = 0.54). Moreover, the comparison between IMERG-F and 3B42, shows that IMERG-F is superior to 3B42 by indicating higher R2, NSE and lower percent bias (PBIAS) at both monthly and daily timescale. The results are strengthened by Taylor diagram statistics, which represent a higher correlation (R) and less RMS error between observed and simulated values for IMERG-F. IMERG-F has great potential utility in the Chenab River catchment as it outperformed the 3B42 precipitation in this study. However, its poor skill of capturing peaks at daily timescale remains, leaving a room for IMERG-F to improve its algorithm in the upcoming release.

Investigating the impact of climate and land-use land cover changes on hydrological predictions over the Krishna river basin under present and future scenarios

The climate and Land Use/Land Cover (LULC) changes evince the considerable impact on water balance components by altering the hydrological processes. So, the present work focuses on the evaluation of the combined impact of both the climate and LULC changes along with and without water storage structures on water balance components of the Krishna river basin, India under present and future scenarios with the help of Soil Water and Assessment Tool (SWAT). Sequential Uncertainty Fitting algorithm (SUFI-2) was used for the model calibration and validation, which were carried out at the Vijayawada gauge station. The coefficient of determination (R²) and Nash-Sutcliffe efficiency (NSE) values obtained during the calibration period were 0.63 and 0.61, respectively, whereas, in validation, these values were found to be 0.61 and 0.56, indicates satisfactory results. The results showed that the model simulations and performance were significantly influenced by the presence of water storage structures, whereas the LULC changes were effective at the sub-watershed level. Future LULC maps of 2025, 2055, and 2085 were simulated from the Cellular Automata (CA) Markov Chain model, and they were used along with future climate projections to investigate its impact on water balance components. The climate model projects an increase of water balance components specifically, surface runoff, streamflow, and water yield, except for evapotranspiration in the future. Whereas, the future LULC changes may influence in offsetting the streamflow 20 to 30% reference to the observed flow. Thus, LULC changes were significantly influenced the model simulations; therefore, it is essential to consider the LULC changes along with climate scenarios in climate change studies. Overall, the surface runoff, water yield, and streamflow may increase by 50% under Representative Concentration Pathway (RCP) 4.5, and they may double under the RCP 8.5 scenario by the end of the century.

Social Capital and Disaster Resilience Nexus: A Study of Flash Flood Recovery in Jeddah City

Governments, researchers, and humanitarian agencies have increasingly focused on reducing disaster impacts and enhancing the resilience of individuals, households, and communities, as the human and economic costs of natural disaster events have dramatically increased over the past century. Achieving resilience in a disaster context means the ability to survive future natural disasters with minimum loss of life and property as well as the ability to create a greater sense of place among residents, a stronger, more diverse economy, and a more economically integrated and diverse population. However, less attention has been paid to the significance of social capital in a post-disaster context and its contribution in building community resilience. It is very obvious that the contribution of social capital to post-disaster resilience in a Middle Eastern/Saudi Arabian context is virtually unknown. With a focus on the Saudi Arabian context, this research paper develops a social capital framework centered on resilience and post-disaster recovery. To conduct this study, a holistic approach to data collection is followed through questionnaire surveys, structured and non-structured interviews with citizens, and informal discussions with government and major stakeholders related to flash flood disaster management in the City of Jeddah. It is interesting to note that several religious institutions have played important roles in evacuating people and providing help for a quick recovery. In addition, government organizations are taking the recovery process seriously by providing necessary help in the flood-stricken areas. Within the scope of the given framework, the research explores and evaluates the role of social capital in post-disaster recovery efforts through a case study of the 2009 and 2011 Jeddah flash floods.

Using GIS, Remote Sensing, and Machine Learning to Highlight the Correlation between the Land-Use/Land-Cover Changes and Flash-Flood Potential

The aim of the present study was to explore the correlation between the land-use/land cover change and the flash-flood potential changes in Zăbala catchment (Romania) between 1989 and 2019. In this regard, the efficiency of GIS, remote sensing and machine learning techniques in detecting spatial patterns of the relationship between the two variables was tested. The paper elaborated upon an answer to the increase in flash flooding frequency across the study area and across the earth due to the occurred land-use/land-cover changes, as well as due to the present climate change, which determined the multiplication of extreme meteorological phenomena. In order to reach the above-mentioned purpose, two land-uses/land-covers (for 1989 and 2019) were obtained using Landsat image processing and were included in a relative evolution indicator (total relative difference-synthetic dynamic land-use index), aggregated at a grid-cell level of 1 km2. The assessment of runoff potential was made with a multilayer perceptron (MLP) neural network, which was trained for 1989 and 2019 with the help of 10 flash-flood predictors, 127 flash-flood locations, and 127 non-flash-flood locations. For the year 1989, the high and very high surface runoff potential covered around 34% of the study area, while for 2019, the same values accounted for approximately 46%. The MLP models performed very well, the area under curve (AUC) values being higher than 0.837. Finally, the land-use/land-cover change indicator, as well as the relative evolution of the flash flood potential index, was included in a geographically weighted regression (GWR). The results of the GWR highlights that high values of the Pearson coefficient (r) occupied around 17.4% of the study area. Therefore, in these areas of the Zăbala river catchment, the land-use/land-cover changes were highly correlated with the changes that occurred in flash-flood potential.

Improved Model Parameter Transferability Method for Hydrological Simulation with SWAT in Ungauged Mountainous Catchments

The sustainability of water resources in mountainous areas has a significant contribution to the stabilization and persistence of the ecological and agriculture systems in arid and semi-arid areas. However, the insufficient understanding of hydrological processes in ungauged mountainous catchments (UMCs) is not able to scientifically support the sustainable management of water resources. The conventional parameter transferability method (transplanting the parameters of the donor catchment model with similar distances or attributes to the target catchment model) still has great potential for improving the accuracy of the hydrological simulation in UMC. In this study, 46 river catchments, with discharge survey stations and multi-type catchment characteristics in Xinjiang, are separated into the target catchments and donor catchments to promote an improved model parameter transferability method (IMPTM). This method synthetically processes the SWAT model parameters based on the distance approximation principle (DAP) and the attribute similarity principle (ASP). The performance of this method is tested in a random gauged catchment and compared with other traditional methods (DAP and ASP). The daily runoff simulation results in the target catchment have relatively low accuracy by both the DAP method ( N S = 0.27, R 2 = 0.55) and ASP method ( N S = 0.36, R 2 = 0.65), which implies the conventional approach is not capable of processing the parameters in the target regions. However, the simulation result by IMPTM is a significant improvement ( N S = 0.69, R 2 = 0.85). Moreover, the IMPTM can accurately catch the flow peak, appearance time, and recession curve. The current study provides a compatible method to overcome the difficulties of hydrological simulation in UMCs in the world and can benefit hydrological forecasting and water resource estimation in mountainous areas.

Evaluation of Hydrological and Hydraulic Models Applied in Typical Mediterranean Ungauged Watersheds Using Post-Flash-Flood Measurements

In this paper, three different flash floods episodes were analyzed, which occurred in October 2006, February 2010, and June 2018 in the Chalkidiki peninsula (North Greece). The Soil Conservation Service (SCS) model and a revised assessment of the CN parameter were applied to estimate the flood hydrographs, and Hydrologic Engineering Center’s-River Analysis System (HEC-RAS) software was used for the flood simulations. Initially, hydrological and hydraulic models were calibrated at Vatonias watershed (240.90 km2, North Greece), where three rain gauges and one water level station are located. Vatonias is located very close to the Stavros ungauged watersheds and presents similar geomorphology and land use conditions. The effectiveness and accuracy of the methodology were validated using post-flash-flood measurements. The root mean square error goodness of fit was used to compare the observed and simulated flood depths. Critical success index was calculated for the assessment of the accuracy of observed and modeled flooded areas. The results showed that the dense forest vegetation was not capable of preventing the flash flood generation or reducing the peak discharge, especially in small watersheds characterized by short concentration times. The main cause of flash flood generation was the human interference that influenced the hydraulic characteristics of streams and floodplains. The revised assessment of the CN parameter enhanced the estimation and spatial distribution of CN over the entire watershed. The results revealed that the proposed methodology could be a very useful tool to researchers and policy makers for flood risk assessment of higher accuracy and effectiveness in ungauged Mediterranean watersheds.

Model Uncertainty Analysis Methods for Semi-Arid Watersheds with Different Characteristics: A Comparative SWAT Case Study

Distributed hydrological models play a vital role in water resources management. With the rapid development of distributed hydrological models, research into model uncertainty has become a very important field. When studying traditional hydrological model uncertainty, it is very common to use multisite observation data to evaluate the performance of the model in the same watershed, but there are few studies on uncertainty in watersheds with different characteristics. This study is based on the Soil and Water Assessment Tool (SWAT) model, and uses two common methods: Sequential Uncertainty Fitting Version 2 (SUFI-2) and Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis. We compared these methods in terms of parameter uncertainty, model prediction uncertainty, and simulation effects. The Xiaoqing River basin and the Xinxue River basin, which have different characteristics, including watershed geography and scale, were used for the study areas. The results show that the GLUE method had better applicability in the Xiaoqing River basin, and that the SUFI-2 method provided more reasonable and accurate analysis results in the Xinxue River basin; thus, the applicability was higher. The uncertainty analysis method is affected to some extent by the characteristics of the watershed.

Assessing Water Shortage through a Balance Model among Transfers, Groundwater, Desalination, Wastewater Reuse, and Water Demands (SE Spain)

Currently, water demands are increasing notoriously, spreading the pressure on available water resources around the world in both quantity and quality. Similarly, the expected reduction of natural water inputs, due to climate change, depicts a new level of uncertainty. Specifically, Southeast Spain presents water scarcity due to its aridity—irregular and scarce precipitation and high evapotranspiration rates—combined with the competition between several water demands: environment, agricultural dynamics, urban-tourist activities, and industry. The study area of this work is the most relevant functional urban area of Alicante province (SE Spain), where the administration of water management is carried out by a range of authorities at different levels as the consequence of a complex historical development of water governance schemes: at the national, regional, and local levels. This study analyzes 21 municipalities and proposes a conceptual model which was developed by including different origins of water inputs—surface resources, groundwater, desalination, wastewater reuse, or interbasin transfers—and water demands with information obtained from 16 different sources. Our main results denote a relevant water deficit of 72.6 hm3/year even when one of the greatest rates of desalinated water and reused wastewater in Europe are identified here. This negative balance entails restrictions in urban development and agricultural growth. Thus, presented results are noteworthy for the water policy makers and planning authorities, by balancing the demand for water among various end users and providing a way for understanding water distribution in a context of scarcity and increasing demand, which will become one of the most challenging tasks in the 21st century.