No abstract

Drought is a global phenomenon that occurs virtually in all landscapes causing significant damage both in natural environment and in human lives. Due to the random nature of contributing factors, occurrence and severity of droughts can be treated as stochastic in nature. Early indication of possible drought can help to set out drought mitigation strategies and measures in advance. Therefore drought forecasting plays an important role in the planning and management of water resource systems. In this study, linear stochastic models known as ARIMA and multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to forecast droughts based on the procedure of model development. The models were applied to forecast droughts using standardized precipitation index (SPI) series in the Kansabati river basin in India, which lies in the Purulia district of West Bengal state in eastern India. The predicted results using the best models were compared with the observed data. The predicted results show reasonably good agreement with the actual data, 1-2 months ahead. The predicted value decreases with increase in lead-time. So the models can be used to forecast droughts up to 2 months of lead-time with reasonably accuracy.

Hydrometric network design for surface water monitoring is employed to address a wide range of environmental and water resources problems. Historical overview of hydrometric network design is provided along with a discussion on new developments and challenges in the design of optimal hydrometric networks. This review starts with precise examples of decline in hydrometric network density, then highlights the increasing requirement of optimal network design in a context of climate and land use changes. An extensive survey of methodological development in hydrometric network design is provided along with discussion on the issue of uncertainty in hydrometric network design and the evolution in data collection techniques and technology. Finally, some conclusions are drawn on the future of hydrometric network design.

No abstract

No abstract