J.C. van Dam

Assimilation of satellite data into agrohydrological models to improve crop yield forecasts

This paper addresses the question of whether data assimilation of remotely sensed leaf area index and/or relative evapotranspiration estimates can be used to forecast total wheat production as an indicator of agricultural drought. A series of low to moderate resolution MODIS satellite data of the Borkhar district, Isfahan (Iran) was converted into both leaf area index and relative evapotranspiration using a land surface energy algorithm for the year 2005. An agrohydrological model was then implemented in a distributed manner using spatial information of soil types, land use, groundwater and irrigation on a raster basis with a grid size of 250 m, i.e. moderate resolution. A constant gain Kalman filter data assimilation algorithm was used for each data series to correct the internal variables of the distributed model whenever remotely sensed data were available. Predictions for 1 month in advance using simulations with assimilation at a regional scale were very promising with respect to the statistical data (bias = ±10%). However, longer‐term predictions, i.e. 2 months in advance, resulted in a higher bias between the simulated and statistical data. The introduced methodology can be used as a reliable tool for assessing the impacts of droughts in semi‐arid regions.

Assessing options to increase water productivity in irrigated river basins using remote sensing and modelling tools

In regions where water is more scarce than land, the water productivity concept (e.g. crop yield per unit of water utilized) provides a useful framework to analyse crop production increase or water savings in irrigated agriculture. Generic crop and soil models were applied at field and regional scale, together with geographical and satellite data to analyse water productivity in Sirsa District (India). In this district certain parts show a serious decline in groundwater levels and water shortage, while other parts experience a serious rise of groundwater levels, causing waterlogging and salinization. The regional analysis showed a large spatial variability of water productivity, net groundwater recharge and salinization. Scenario analysis showed that improved crop husbandry, reallocation of canal water from fresh to saline groundwater areas and reduction of seepage losses in saline groundwater areas are effective measures to increase the overall water productivity and to attain sustainable irrigation in Sirsa District.