Climate is the main biophysical factor controlling the hydrometeorological characteristics that eventually determines the rain harvesting potential of a given location. For example precipitation dynamics governs the input of water to the system whereas temperature, wind and radiation affects the ET mechanism. The complexity of the hydrological cycle as influence by the weather and climate is critical on the water balance and hence on the Rain Water Harvesting Potential. With climate change the hydrometeorological variables changes differently in space and time and it will have an impact on the Rain Water Harvesting potential. Thus, it is important to have an idea on the long term climate dynamics in the NENA region. This module will generate the time series of the selected meteorological variable for the selected time periods for any location in any of the selected NENA  countries. The map generated is the average monthly map of the selected meteorological variable. Because this is generated from a very large data it will take some time to process. Zoom into the specific location you are interested and click the cursor to get the time series for that location.

Agriculture is a large consumer of water (both rain water as well as ground water) with ET being the main pathway of water loss to the atmosphere. Achieving Food Security in the future while using water resources in a sustainable manner is a major challenge for us and the next generations. A  careful monitoring of ET and water productivity in this sector and exploring opportunities to increase it are required. FAO, in partnership with and with funding from the Government of the Netherlands, is developing a programme to monitor and improve the use of water in agricultural production. This document is part of the first two outputs of the programme: the development of an operational methodology and the development of an open-access database to monitor land and water productivity. The FAO has developed a publicly accessible near real time database using satellite data that allows the monitoring of agricultural water productivity at different scales. The methodology was developed by the FRAME consortium, consisting of eLEAF, VITO, ITC, University of Twente and Waterwatch foundation, commissioned by and in partnership with the Land and Water Division of FAO. This database is the backbone of the WaPOR project that, now in its second phase, works with ten partner countries to build their capacity in the use of WaPOR data for its different applications, and to generate solutions to local challenges linked to water and land productivity as well as water management.