Development of a Decision Support System for Sustainable Environmental Management and Stakeholder Engagement

Using ARIMA and ETS models for forecasting water level changes for sustainable environmental management

It is vital to provide useful hydrological forecasts for urban and agricultural water management, hydropower generation, flood protection and management, drought mitigation and alleviation, and river basin planning and management, among other things. This paper introduces a simple and flexible hydrological time series forecasting framework. Predicting water levels is crucial, given the need for sustainable environmental management. The prognosis should be reasonable to persuade individuals to take proper precautions. While many methods have been developed to predict water levels, here the effectiveness of two approaches to predicting river water levels was assessed. For this purpose, nine years of data were used, which were divided into input data (2014-2021) and validation data (2022), on water levels in the Morava e Binçës river for the Vitia station, in the form of monthly time series records, to identify the best model among those used and to identify the information necessary for water resource management and hazard control. Models Autoregressive Integrated Moving Average(ARIMA) and Error Trend and Seasonality, or Exponential Smoothing (ETS), were examined using the R package to determine the most accurate. The results indicate the applicability of both models, as evidenced by the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The predictive analysis based on historical water levels allowed the identification of distinct periods characterized by high and low water levels between 2022 and 2024, which is important for the area in question due to the numerous flood events occurring here.

Study on the Spatio-Temporal Evolution of China's Smart Water Co-Governance in G-E-P Mode

Smart water co-governance (SWCG) is a fundamental driving force to reduce the water crisis and promote the sustainable development of water resources. To explore the applicability and development of SWCG in different regions, the authors of this paper took 31 provinces of China (with the exception Hong Kong, Macao, and Taiwan) as research districts and used the three-stage data envelopment analysis (DEA) method to measure and compare the efficiency of smart water governance (SWG) in the government-enterprise-public (G-E-P) mode and without public participation in the government-enterprise (G-E) mode in 2019. Then, the Malmquist model was used to measure the spatio-temporal evolution of the G-E-P mode from 2010 to 2019, focusing on the analysis of the top ten provinces of the China Internet Development Index in 2019. According to the empirical analysis, the following results were obtained: (1) the efficiency of SWCG in the G-E-P mode was significantly higher than that in G-E model, as 13 provinces showed a significant decline and 10 provinces had a small change. In addition, SWCG in the G-E-P mode showed a good development trend in the eastern and southern regions. (2) The governance efficiency, pure technical efficiency, and scale efficiency showed upward trends, but the technological progress index and total factor productivity were still low. Therefore, SWG should vigorously promote public participation and the independent implementation of enterprises under the guidance and restriction of the government. Meanwhile, the construction of an SWG infrastructure and the level of science and technology should be strengthened. In addition, each province should adjust the input-output structure according to its redundancy or deficiency, weigh the suitability of the input level and scale, and strengthen the matching and support of the ability of multi-subjects and factors to ensure that an appropriate input-output scale level is reached and the efficiency of SWCG is improved.

Resistance to Change and Perceived Risk as Determinants of Water-Saving Intention

Both the academic literature and global organizations have emphasized the need for responsible water consumption, as stated in Sustainable Development Goal 12. However, individuals’ water-saving behaviors in their current state are not enough. This situation entails a resistance to change (RC) in consumer habits and a lack of perceived risk of scarcity. The novelty of this study lies in examining the influence of RC (through its emotional, cognitive, and confidence components) and perceived risk on water-saving intention. Interviews (n = 384) were conducted in the southeast Mediterranean area of Spain by interviewers using a paper-and-pencil questionnaire. The results of the structural equation modeling show that the perceived risk and the components of cognitive rigidity and negative emotions exert a direct influence on water-saving habits and an indirect influence on water-saving intention. None of the components of RC directly influence intention, and a lack of confidence in the outcomes of water saving does not influence water-saving habits or water-saving intention. In addition to the results obtained, the novelty of the work lies in the idea that in order to influence the perception of the risk of water scarcity through awareness campaigns, it is better to use an emotional message rather than showing facts or information because this does not drive water-saving behavior.