A shallow low-lying coastal sand aquifer in southern Finland is vulnerable to the climate change and human activities. Under future climate change, a rise in sea-level would cause some parts of the aquifer and the water intake well to be under seawater. This, together with the predicted increase in precipitation, would enhance groundwater recharge and raise the water table, consequently contributing to the potential deterioration of groundwater quality or potential flooding in the low-lying aquifer area. An information on geological and hydrogeological characteristics of the aquifer for the climate change adaptation plan including the possible new locations of water intake wells was needed. This study aimed to construct a three-dimensional geological model and evaluate heterogeneity of the aquifer to provide a geological framework for groundwater flow model and the assessment of groundwater vulnerability. The methods used consist of a stochastic-geostatistical approach incorporated with groundwater flow model to predict the distributions of the superficial layers of a heterogeneous aquifer and to identify the distributions of the aquifer medias (sand and gravel) as well as groundwater flow system. In addition, the LiDAR-based digital elevation model was utilized to define the flood prone areas under the climate change scenarios. The three-dimensional geological model provides a better characterization of the heterogeneity of the aquifer and improved reliability of subsequent groundwater flow model and vulnerability assessment in the aquifer area. The proposed new locations of water intake wells and the results of the study provided useful information for local authorities for groundwater management in future.

The Surface Water Supply Index (SWSI) may be considered for studying hydrologic conditions and agricultural water management. By using this indicator, water resources conditions of Colorado and Oregon basins were investigated from extremely wet to extreme drought. The SWSI values can also be plotted as a time series graph while critical years were specified. This allows the user to graphically visualize the values from year to year and to see how the current year's values change from year to year. Managers can then refer to records from critical years in determining strategies for dealing with the current years’ water supply. Also evident is whether the streamflow component or the reservoir component is the predominant driving force at any given time. SWSI's can be an excellent water management tool in determining overall risk and management strategies. It gives the water user and manager more information than simply streamflow or reservoir level alone. According to the results, obtained categories based of SWSI values are indicated hydrologic conditions for Colorado and Oregon States with two different climates. Although decisions only based on geographic and climatic information due to the insufficient and sometimes contradictory results than the SWSI can cause water loss or increase the risk of drought.

In this study, critical areas of Iran were determined using 50-year rainfall data and ARIMA model. For this purpose, annual rainfall data of 112 different synoptic stations in Iran were gathered. To summarize, it could be concluded that: ARIMA model was an appropriate tool to forecast annual rainfall. According to obtained results from relative error (RE) between observed and forecasted values, five stations include IRANSHAHR, SIRJAN, NAEIN, ZAHEDAN, and KISH, were in critical condition. Therefore, in these areas due to lack of accurate forecasting, agriculture water management and crop pattern presenting must be done very carefully. As the figure 1 in 65% from forecasted annual rainfalls by ARIMA model amount of relative error was less than 0.1 (10%). These areas were in the safe range. 35% of forecasting had a relative error between 0.1-0.2 (10-20%) and these areas were in the alarm range. Finally only 5% of all ARIMA forecasting occurred in the critical range. This showed a high ability of ARIMA model in annual rainfall forecasting. At 45 stations accrued rainfalls with amounts of less than half of average in the 50-year period. Therefore, in these 45 areas, chance of drought is more than other areas of Iran.

In this paper, irrigated agriculture has been estimated in Asia Pacific using three different scenarios by 2035 and 2060. The number of 10 indices (as the main indices) was selected to assess agricultural water management based on their importance and other indices were not studied due to lack of adequate data. These indices are permanent crops per cultivated area, rural population per total population, total economically active population in agriculture per total economically active population, human development index (HDI), value added to gross domestic product (GDP) by agriculture, national rainfall index (NRI), irrigation water requirement, difference between NRI and irrigation water requirement, percent of total cultivated area drained, and irrigated agriculture per cultivated area. The changes of the main indices in the previous half of century indicated that they had similar values in some regions and had very different values in other regions due to the nature of the indices and conditions of the regions. In the first step, the author studied variations of the main indices during the previous half of the century using linear regression and R² value then amount of each index was estimated in 2035 and 2060 by obtained equations and three different scenarios. The results show that trends of permanent crops per cultivated area (with the exception of Caucasus, Maritime Southeast Asia, and Oceania), HDI, irrigation water requirement, and percent of total cultivated area drained are increasing and trends of rural population per total population, total economically active population in agriculture per total economically active population, value added to GDP by agriculture, and difference between NRI and irrigation water requirement (with the exception of East Asia Pacific) are decreasing. The maximum value of irrigated agriculture is related to Central Asia; 69.2% and 81.8% by 2035 and 2060, respectively.

Wastewater treatment and nutrient removal alternatives for large size communities are very
well-established and are feasible in many cases. When it comes to the small rural and especially
for low-income disadvantaged communities, this is not the case, particularly with regard to nutrient
removal. The alternatives for small communities are often viewed as cost-prohibitive and
unreliable. While this is partly true, careful selection and implementation of appropriate
technologies can result in high performance, energy and cost efficient and environmental-friendly
solutions.
Assessment of water and wastewater is very crucial to safeguard public health and the
environment. However, water quality data on fresh and marine waters in the Mississippi coastal
region, especially in Jourdan watershed are still sparse and uncoordinated. Therefore, monitoring
these parameters is important for safety assessment of the environment and human public health
and the water bodies. We have identified a few small and decentralized communities in the Jourdan
River watershed area to assess the current wastewater treatment and management practices and
their impacts on the receiving water bodies. This paper will discuss our preliminary
evaluation and understanding on the local water quality issues of the watershed.

This study aims to estimate the potential evapotranspiration as well as to extract categorized maps of climate parameters that are applicable for civil and architectural design . The results showed that the Albrecht model estimates the potential evapotranspiration better than other models in the most provinces of Iran. The best values of R² were 0.9854 and 0.9826 for the Brockamp-Wenner and Albrecht models in Bushehr (BU) and TE provinces, respectively. Finally, a list of the best performance of each model has been presented. The best weather conditions (not only for Iran but also for all countries) to use mass transfer-based equations are 23.6-24.6 MJ/m²/day, 12-26 ℃, 18-30 ℃, 5-21 ℃, and 2.50-3.25 m.s^-1 for solar radiation, mean, maximum, and minimum temperature, and wind speed, respectively. The results are also useful for selecting the best model when researchers must apply humidity-based models on the basis of available data. In addition, the designed maps and categories are applicable for considering the role of climatic parameters in architectural evaluations over Iran.

The Elbow River watershed, located in the foothills of the Rocky Mountains, has experienced several extreme hydrological events such as droughts and floods over the last century. It is therefore critical to understand the future possible responses of the hydrological processes to changes in climate and land-use/land-cover (LULC) since they can induce considerable stress to the watershed along with economic and social costs. Very little attention has been given so far in the literature to the combined impact of climate and LULC change on hydrological processes at the watershed scale, which might result in an over- or under-estimation of the responses. This study was undertaken to investigate the responses of hydrological processes to the combined impact of climate and LULC change in the watershed in the 2020s and 2050s. The physically-based, distributed MIKE SHE/MIKE 11 model was coupled with a LULC cellular automata model to simulate hydrological processes using two extreme GCM-scenarios and two LULC change scenarios. Results reveal that LULC change is the dominant factor affecting the majority of the hydrological processes, especially streamflow, and that it plays a key role in amplifying a rise in flow discharge in the Elbow River. Evapotranspiration and infiltration are more strongly affected by both climate and LULC change in winter while streamflow is more impacted in the spring. The separated impacts of climate and LULC change on streamflow are positively correlated in winter and spring, which intensifies their influence. This is particularly the case in spring when the combined impact of climate and LULC results in a significant rise in streamflow, which may increase the vulnerability of the watershed to floods in this season. The flow duration curves (FDC) indicate that LULC change has a greater contribution to peak flows than climate change in both the 2020s and 2050s. This study highlights the importance of investigating the combined impact of climate and LULC change to avoid underestimating or overestimating water storage in the watershed.

The study develops a rule operation model for gated spillways which improves the performance of the volumetric evaluation method (MEV). MEV was proposed by Giron (1988) and is largely used in common practice in Spain. The improvement was made by applying a corrective factor to the outflow discharge proposed by MEV method. The choice of the corrective factor was based on a multi-decision environment accounting for the number of improved cases and the amount of improvement. A Monte Carlo simulation environment was created to evaluate the method under a wide range of operating conditions. The environment includes the generation of storms and inflow hydrographs and their routing through the reservoir. The methodology was applied to the Talave basin, in the south-east of Spain. The improved method (called K method) was compared with other methods for the operation of gate-controlled spillways as the MEV and PLEM methods. The results showed that if the corrective factor K is higher than 1 the number of improved cases was significant, while if it is lower than 1 there was not improvement. The analysis of the relation between the return period and the devised method showed that by using the K method the percentage of improvement of both reducing maximum outflows and reducing maximum levels reached in the reservoir is greater for events with higher return periods than for the lower ones.

Drinking water treatment plants (DWTP) using surface water as potable source could be particularly vulnerable to short term transient events leading to sudden rise in suspended sediments, organic matter, nutrients, pathogens and other organic and inorganic contaminants. The prediction of source water parameters using early warning systems could be one solution to drinking water operators to manage short term transient water quality contamination events. In the context of climate changes where an intensification of rainfall-runoff events and consecutive pollution episodes is predicted, using data mining techniques could be of particular interest as forecasting tools to adapt efficiently drinking water treatment during transient pollution episodes. This study focuses on the development of data mining techniques using neural networks and trend analysis to forecast turbidity peaks in a drinking water source located in a humid continental climate (Quebec, Canada). The DWTP uses surface water to provide drinking water to almost 300 000 inhabitants. High frequency data from 2012 to 2016, from on-line measurements, are used for source water turbidity. Rainfall indicators (number of dry days, sum of the daily precipitation for 1, 2, 5 and 10 days prior to turbidity event start, days since daily precipitation of at least 10, 20 and 50 mm prior to event start) have been created using five meteorological stations located within the watershed as input parameters for models. The results of this study could help water treatment plant operators to anticipate the variability of key water quality parameters.