Tools and Inventories

Glacier Inventory
HighNoon collected glacier outlines from various databases and compiled a comprehensive inventory of the best available glacier data for the Himalaya. For the entire Himalaya including regions in the western Himalaya that have not been covered by the global glacier databases until today, new outlines were created by remote sensing techniques. Initial estimates of volumes of ice stored in the Himalayas were subsequently derived. Regional Climate Models, such as applied within the HighNoon project, can use these glacier areas and glacier volumes, which will allow a dynamical coupling of glaciers with climate. Furthermore the dataset can be used as a benchmark against which future changes in glaciers can be compared. Glacier areas coverage over the whole Hindu-Kush-Karakoram Himalaya mountain ranges, gridded for use in the REMO climate model.

Glacier Lake Inventory
HighNoon presents a first area-wide glacier lake inventory for the Indian Himalayas, including a qualitative lake classification. Glacier lake hazards and glacier lake distributions are investigated in many glaciated regions of the world, but comparably little attention has been given to this topic in the Indian Himalayas. 251 glacier lakes larger than 1 hectare were detected in the five states spanning the Indian Himalayas. Lake distribution pattern and lake characteristics were found to differ significantly between different regions, with most critical lakes lying in Sikkim. The lake classification can be used to select the most critical areas and target investments in early warning systems. Furthermore it provides an indication of erosion risk, which is of interest for the hydropower sector. Glacier lake inventory with mapped and classified glacier lakes >1 ha over the entire Indian Himalayas. Three critical glacier lakes for which a detailed risk assessment was carried out are indicated by arrows.

Agricultural Forecasting tool
In HighNoon the potential of using short-term weather forecasts to increase irrigation efficiency in rice cultivation, as a potential adaptation option to future climate change, was explored. Field tests and modeling revealed that basing the decision to irrigate rice on short-term weather forecasts could reduce water application by 17-60% if 5-days rainfall forecasts would be very accurate. Modelling showed that using accurate forecasts under future climate conditions can potentially lead to an additional saving of irrigation water. Skill in forecasting future weather and climate in India, on the short (days), medium (seasons) and long term (decades) is improving. However at present, forecasts issued by the Indian Meteorological Department (IMD) for West Bengal, the region studied are not accurate enough to achieve the desired water savings. The HighNoon approach combines weather forecasting with site specific modelling of soil moisture, nutrient status and crop water stress. This creates a more tailor-made advise for both small and large scale farmers.

Indicator framework tool & Water Resources GIS server
In the HighNoon project an indicator framework is developed to summarise and visualise the impact of climate change on different sectors. The framework characterizes the baseline and future water resources and livelihood status. Main indicators for a variety of stresses for the three case study sites are summarised below.

The use of indicators in the water sector has become more important in recent years, and legislations have given prominence to use indicators as evaluation and management tools. The indicator framework can be used by policy makers to target their attention and resources to specific sectors and areas. It helps in identifying adaptation measures as well as in evaluating impacts of proposed adaptation measures. A user friendly interface has been developed for deployment of the indicator framework. The NATCOM Hydrological Information System is an interactive website where model results and analysis of climate change research are presented, amongst others from HighNoon. It covers not only the Ganges but all of India’s river basins. Easy viewing and querying of the outputs of the indicator framework for the case study sites of the Ganges basin have been provided at:
http://gisserver.civil.iitd.ac.in/HighNoon/HighNoon.aspx.