In order to find out the effects of different degrees of drought stress on the growth index and yield of semilate rice. In this experiment, a pot experiment was conducted with hybrid rice Tianyouhuazhan as material. Intermittent irrigation was used as control (CK) at tillering stage, booting stage, heading stage, and milk stage. Three water stress gradients of light drought (70% saturated moisture content), medium drought (60% saturated moisture content), and severe drought (50% saturated moisture content) were set to monitor soil moisture content. The plant height, number of tillers, leaf area, and chlorophyll content under different water gradients at different growth stages were measured, and the effects of different water stress treatments at different growth stages on rice growth index, yield, and its components were analyzed. The results showed that the inhibition of plant height at the jointing and booting stage was the most significant, the number of tillers and leaf area decreased most significantly at tillering stage, and the heading and flowering stage had the greatest effect on chlorophyll synthesis. As far as yield is concerned, the most sensitive stage is the heading and flowering stage. Different stress treatments reduced the effective panicle number, 1000-grain weight, and seed setting rate of rice, and reduced the yield by 27.57%, 44.23%, and 46.32% respectively compared with the normal control. The correlation analysis showed that the correlation degree of affecting yield from large to small was effective panicle, 1000-grain weight, and seed setting rate. Therefore, ensuring water supply at the heading and flowering stage can effectively improve 1000-grain weight, effective panicle, and seed setting rate, and increase rice yield and water use efficiency.

The development and operation of a decision support system (DSS) for irrigation water management can be a complex task, especially when the initial specifications require increased precision, the area under consideration is large and the cost of installation and maintenance of equipment should be sustainable. For this reason, the use of a sparse, network of reference agrometeorological stations, to gather data, based on which irrigation water management recommendations will be provided, is an adequate yet challenging option.

This paper attempts to present the challenges that arise when designing and operating such systems and approaches that have been used to address them. At the epicentre lie the methods that were used to process data from reference agrometeorological stations in order to generate virtual water management data entities for field level. Several examples that were found through literature review are presented and discussed along with facts from the experience resulted from the operation, of such a system in Greece.

The purpose is to encourage the exchange of ideas and methods with other parts of the scientific community involved in the development of IT tools for precision irrigation water management.

Lima Puluh Kota Regency in West Sumatera Province is one of regencies in Indonesia that often has flood problem every year since last decade. In case of such large-scale flooding, it is important to classify the hazard zone for efficiency of the flood mitigation. In this paper, rainfall-runoff inundation (RRI) model is applied to the Batang Sinamar River Basin in order to predict the widespread inundation, where both rainfall-runoff from surrounding mountain and rainfall on flood-plain contributed in the flood event. Flood simulation was conducted by using nationally available dataset including high resolution digital surface model and rainfall ground station data. The simulation was calibrated with discharge observation data in Batang Sinamar and gave a good result with Nash Sutcliffe Efficiency index and correlation value 0.768 and 0.908 consecutively. The result of simulation using 10-year and 25-year return showed the increasing discharge by 15.72 percent from 406.77 m3/s to 470.74 m3/s. Furthermore, the average of peak inundation water level had increased from less than 1.5 meters to more than 1.5 meters. Based on these results, it can be concluded that the model can predict the potential inundation area in Batang Sinamar River Basin in Lima Puluh Kota Regency.

A new SolWat technology has been developed that uses exclusively solar energy, called Large Open SolWat, as a possible tertiary treatment in a WWTP. This photochemical-photovoltaic hybrid system has a water disinfection reactor on a photovoltaic module, which consists of a pumping system that constantly cools the surface of the module by means of a thin film of water, and another open disinfection reactor with full solar exposure that stores the water sample during treatment. The water sample used was the wastewater effluent after secondary treatment of a WWTP. Large Open SolWat was operated with a flow rate of 8.9 L/min for the sample volumes of 4.2 and 6.2 L. The experiments took place on sunny days with climatic variability. Microbiological, physicochemical and photovoltaic performance analyses of the system were carried out. The results showed that good quality reclaimed water was obtained after a 4-hour SODIS treatment under real sunlight, which could be used for other purposes according to Spanish (RD 1620/2007) and European (R(EU) 2020/741) regulations. Simultaneously, the system generated energy with an energy efficiency that improved by 15 - 21% compared to the reference PV module, as a consequence of the successful cooling of the module temperatures (between 16.2 - 30.6°C during the experiments) with waste water. This would thus increase the performance and lifetime of the PV module. The energy generated could be used to self-supply the pumping system and to meet the energy demand of a WWTP in the future.

The results of this research showed a successful breakthrough in SolWat technology and demonstrated the feasibility of an appropriate and efficient use of water and energy.

Limited water resources are a major obstacle to ensuring food security. Considering that the agricultural sector accounts for most of the water consumption in Iran and worldwide, water management in the agricultural sector is of great importance. Water productivity is one of the sustainable development goals and the key indicator for studying and improving agricultural water management. The aim of this study is to determine the critical points of the Maroon- Jarahi basin from the view point of water productivity and water consumption using modern remote sensing methods, and find solutions to improve water productivity in these areas. Recently, the Food and Agriculture Organization of the United Nations (FAO) established the WaPOR open-access portal on water productivity to map countries facing with water crises in Africa and the Middle East, and estimation of actual evapotranspiration (ETa) is one of its main products. This portal makes it possible to determine water consumption and water productivity on a large scale with little time and cost, so it can be used to manage the agricultural sector. In this study, the actual evapotranspiration (AET), net primary production (NPP), and water productivity (WP) for the basin were estimated using the WaPOR portal and Google Earth Engine over a 10-day period with a spatial resolution of 250 meters (decadal data). Based on the obtained results, the areas with low water productivity were identified. By studying the existing cropping patterns, the type of irrigation system used and the water and soil conditions in these areas, it is possible to investigate the reason for the low water productivity and propose solutions to improve it.

Heading toward the consequences of the climate change, long periods of drought, and lack of monitoring the city’s storm drain system, tend higher flood chances when an extreme flood event occurs. Preventing the extent of the flood in rural and urban areas is crucial to protect human wellbeing, private and public land and avoiding human casualties. Modeling potential floods and studying historic ones, are key parameters to prevent damages from this natural disaster. European Union Directive 2007/60/EK, obligated Member States to compile flood risk maps, showing the potential flood’s extent and depth. Using Cyprus river flood risk maps of the region of Larnaca, Corine land cover data and open-access cadaster data, this study attempts to assess the economic damage. Cadaster data of buildings, floor number and basement existence, are incorporated in the damage functions used for flood extents of 20, 100 and 500 years return period. The study found that in the 500yr flood period 842 buildings will be potentially affected. The flood risk areas in the region of Larnaca, consist of mainly urban (48%) and cultivation zones (50%), both economically important. The results suggest that economic damage assessment based on the used data, combined with flood risk maps, can provide valuable information to disaster responders.

Accurate precipitation measurements are very important as an input for water resources management and various hydrometeorological applications. Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) satellite precipitation products (SPP) have been widely used to complement rain gauge measurements. However, they must be evaluated before use and are still lacking in the Lake Titicaca Basin (LTB). In this research, the evaluation of the performance of GPM IMERG on the LTB at different time scales (daily, monthly and annual) was carried out. The evaluation was performed using rain gauge observations for the period 2003-2016 and three IMERG SPPs, namely early (IMERG-E), late (IMERG-L), and final (IMERG-F). Accordingly, three performance metrics were used that evaluated the accuracy (correlation coefficient, CC), error (root mean square error, RMSE), and bias (percent bias, PBIAS) of the satellite estimates. In general, monthly IMERG SPP correlated best with rain gauge measurements. In all evaluations performed (daily, monthly, and annual), IMERG-F was in better agreement with rain gauge measurements at the LTB, with small differences with IMERG-E and IMERG-L. The IMERG SPPs show potential for use in various hydrometeorological applications in the LTB.

Both ecosystems and human societies acknowledge the importance of water. The impact of human activities on both land and water have become more apparent due to various global changes. These include climate change, urbanization, socioeconomic development, and population growth. Although it is widely believed that securing water security is the key to sustainable development, studies on its evolution and various environmental factors are still in their early stages of development. This study aims to provide an overview of the concept. This concept aims to provide all people with safe water. It goes beyond merely providing adequate supplies to every person in the world, and it also aims to ensure healthy and productive lives. Despite the technological advancements being made in the water resource management industry, the lackadaisical approach to addressing the various challenges associated with water security continues to be a major issue globally. This study will help to overview of the various facets of the water security concept and its evolution in developing countries due to the environmental changes that have occurred. It also explores the multiple sustainable methods that can be used to address these issues.

The measurement of raw water turbidity is essential to determine its degree of potabilization. However, an erroneous measurement of this treatment can cause the water to be of insufficient quality to be purified, generating health problems for consumers. Unfortunately, in rural treatment plants in Colombia, it is common to find this type of deficiency because they use rudimentary techniques to evaluate turbidity, making it impossible to guarantee sufficient quality for water to be considered fit for human consumption.
This article proposes the use of machine learning models in the treatment plants from the municipalities of Santander de Quilichao, Timbío, and Mercaderes in the department of Cauca (Colombia), in order to estimate the turbidity value of raw water considering only available data such as pH, temperature, vapor pressure, and precipitation captured manually by plant's operators.
To develop these modeles, Linear Regression, Random Forest Regressor, Kneighbors Regressor, and Extra Trees Regressor algorithms were trained with data provided by the Aquarisc project and the Colombian Institute of Hydrology, Meteorology and Environment Studies (IDEAM). The study determined that the best-performing algorithm in this context was the Random Forest Regressor. This algorithm had the best RMSE among all the models and was also the one that best fitted the situation of the treatment plants studied. Furthermore, this model did not consider outliers and obtained a result of an RMSE of 20.98 and 3.49 for the training and test data sets, respectively. Finally, it was determined that this algorithm could acceptably estimate the water's turbidity and may support the operators in the decision-making process for applying an adequate treatment to the drinking water.

This study aims to estimate the marginal cost of the drinking water supply and analyze the implications for more efficient, equitable, and revenue-sufficient water rates in Tunisia. However, pricing in Tunisian water utilities has focused on setting water prices to cover average costs, usually using increasing block rate designs. This leads to a huge waste of drinking water. In an attempt to contribute to the efficient estimation of the pricing, model, we tried to introduce a multi-product Generalized Translog (GT) cost specification that incorporates Box-Cox transformation. Findings show that the marginal social costs of providing one m³ must be composed of a two-part tariff: volumetric charges of 0,048 euro/m³ and fixed connection charges of 0,055 euro/km.