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Strong convection nowcasting has been gaining importance in regional security, economic development, and water resource management. Rainfall nowcasting with strong timeliness needs to effectively forecast the intensity of rainfall in a local region in the short term. The forecast performance of traditional methods is limited. In this paper, a rainfall nowcasting model based on the Convolutional Long Short-Term Memory (ConvLSTM) is proposed. Combined reflectance (CR) and the retrieved wind field are selected as the key factors for prediction. The model considers the influence of water vapor content, transport, and change on rainfall by measuring CR and the retrieved wind field. Forecast results are compared to different models and different input data schemes. The analysis shows that the CSI scores of this method can reach about 0.8, which is 28% higher than that of the optical flow method. The ConvLSTM structure with spatial analysis and time memory can greatly enhance the predictive ability of the model, and the addition of wind field data also improves the forecasting performance of the model. Therefore, the idea of forecasting rainfall on the basis of water vapor content and water vapor transport is practical and effective, and the accuracy of a forecast can be improved by using ConvLSTM network to extract spatiotemporal features. [ABSTRACT FROM AUTHOR]

The change of water resources resulting from climate warming in the Yangtze River Source Region (YRSR) has aroused wide concern in recent years. This research used the soil and water assessment tool (SWAT) to estimate the blue water (BW), green water flow (GWF), and green water storage (GWS). Then, the spatial and temporal change of BW, GWF, and GWS over the recent decades and next several decades was investigated. Results show that (1) the BW and GWF have increased by 2.3 mm/10a and 34.2 mm/10a from 1960 to 2012, while the GWG has decreased slightly by 0.19 mm/10a during the same period. (2) The spatial patterns of BW, GWF, and GWS have been changed obviously from 1980s to 2000s, especially for BW and GWF. The BW and GWF in the west and north of the YRSR where the water resource is relatively less are more sensitive to climate change; (3) the annual average temperature and precipitation in the YRSR are projected to increase by 2.2 °C and 9.8% during 2021 to 2050 compared to that during the 1961 to 1990. There is higher uncertainty in BW and GWS projection and the model-averaged BW and GWS would change little. The projected percent changes of GWF and GWS would be 15% and − 11.1% with less uncertainty. The obvious change of BW, GWF, and GWS in the future would occur in the west and north of the YRSR, which is similar with the spatial change in the historical period. [ABSTRACT FROM AUTHOR]

Liu, J.; Xu, J.; Chen, J.; Hong, X., and Zhou, M., 2019. Spatio-temporal distribution characteristics of water quality in Miju River and Erhai Lake. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 31–38. Coconut Creek (Florida), ISSN 0749-0208. In the research related to the water resources management and prevention of pollution, it is of great practical significance to analyze the spatial and temporal distribution characteristics of the water quality. The present work deals with the study on the actual water quality monitoring data obtained from the Miju River monitoring sections in the Erhai Lake during 2011-2016. Six water quality indicators were selected for investigation using the comprehensive pollution index method and the principal component analysis method, in order to analyze the spatial and temporal distribution characteristics of water quality in the Miju River Basin. The results of the comprehensive pollution index method showed that the water quality of the Miju River has not changed much in the past 6 years, and the water body has only been slightly polluted. Additionally, the water quality of the Jiangweiqiao section was slightly inferior to that of the Yinqiaocun section. Principal component analysis method showed that the nitrogen pollution was the dominant factor in the wet season, followed by phosphorus, pH and dissolved oxygen. In the normal season, the dissolved oxygen and pH of the water were the main factors, followed by phosphorus and ammonia nitrogen. In the dry season, the dissolved oxygen, ammonia nitrogen and organic matter pollution were the main influencing factors followed by phosphorus and pH. The water quality of the Miju River in the past 3 years was slightly worse than that in the initial 3 years, and the overall performance of the water quality of the Miju River was relatively best during the dry season followed by the normal season, while the water quality was worst during the wet season. Furthermore, the water quality variation trends of Yinqiaocun and the Jiangweiqiao sections were observed to be similar. [ABSTRACT FROM AUTHOR]

Highlights • A couple-based interval-bistochastic programming method is proposed to address the regional water resources allocation under uncertainties. • An appropriate water allocation plan in Zhanghe Irrigation District is developed under uncertainties of reservoir inflow and local rainfall. • The independence hypothetical situation and linear relationship hypothetical situation are also discussed and compared. Abstract In regional water resources allcoation problems, the uncertainties of hydrological variables and socio-economic parameters are bringing huge challenges to water managers. So far, the stochastic programming models have difficulty in addressing uncertain problems, in which there are two correlated random variables. In order to address regional water resources allocation under two hydrological random variables and interval parameters, a couple-based interval-bistochastic programming (CIBSP) method is proposed. The CIBSP method includes several key steps: first, the marginal distributions of the two hydrological variables are analyzed and hydrological scenarios are set; then, the copula is chosen to analyze joint probability distribution of the two hydrological variables and the joint probabilities of scenarios are calculated; last, an interval-bistochastic model is formulated by incorporating two-stage stochastic programming, interval-parameter programming, and bivariate joint distribution. The CIBSP method can describe the probability of occurrence of a hydrological scenario and then make an optimized water allocation scheme under uncertainties. To demonstrate its applicability, the CIBSP method is applied to the Zhanghe Irrigation District located in China, to optimize available water allocation under the uncertainties of the annual inflow volume of the Zhanghe Reservoir and annual rainfall volume in the irrigated district. An appropriate water allocation plan can be obtained by the method, which provides a foundation to water managers for managing water resources in Zhanghe Irrigation District. Moreover, other two hypothetical situations named independence hypothetical situation and linear relationship hypothetical situation are discussed. The difference in the results between the two hypothetical situations and the case study indicates that an appropriate description of the joint probability of the annual inflow volume and annual rainfall volume by using CIBSP method is important for water resource allocation under uncertainties. [ABSTRACT FROM AUTHOR]

To gain an insight into the spatiotemporal variability of drought events and to assess trends under future climate change scenarios are fundamental for making sound mitigation and adaptation strategies. A new drought index, standardized supply-demand water index (SSDI), has been proposed in this research. The SSDI describes drought from the view of water supply-demand relations using a simple water balance model. It was used to assess historical drought events in the middle and lower Jinsha river basin (MLJRB) located in the southwest China and applied to address the drought conditions in the MLJRB under current and future climates. The results showed the following: (1) The average drought area during 2001 to 2011 reached up to 9.9 × 103 km2, accounting for 35.4% of the whole farmland area in the MLJRB, which was about twice as the drought area during 1961 to 2000. The region for greater drought severity with more drought events and longer duration was mainly distributed in Dali, Chuxiong, Kunming, and Yuxi. (2) For the period 2021 to 2050, total drought area was projected to increase by 43.2%. The drought-prone regions could move further towards the northwest of the MLJRB. [ABSTRACT FROM AUTHOR]