Many crop water simulation models, sometimes also referred to as agro-hydrological models, are currently available. The model concepts, governing equations and underlying theory of these models are often very divergent.
Some simulation codes use principally empirical equations to describe the processes, while other models include more complex mechanistic equations to capture a certain crop or soil water response. However, most models contain a mixture of empirical and mechanistic concepts.
For the crop growth components of the models, the main distinction that can be made in terms of their underlying equations, is whether they are
- radiation (or light) use efficiency based,
- photosynthesis based, or
- water use efficiency based.
Depending on the analysis required, research question and data availability, a choice needs to be made on the right model to choose.
The concepts behind modeling of soil water dynamics range from the use of a simple bucket-filling model to those that solve more complex algorithms based on the Richards´ equations. The impact of water stress on crop growth is often described by either (i) a tipping bucket concept through f.e. stress response functions or can be (ii) Richards´ potential driven.
FutureWater employs crop water simulation models in various contexts and applications. The model of choice depends on each project and analysis required. Commonly used models are for example: SWAP (Soil, Water, Atmosphere and Plant), the crop module of the Soil Water Assessment Tool, (SWAT) and FAO´s AquaCrop.
Crop water models and remote sensing
Crop water simulation models provide predictions on crop development and growth. Remote sensing can be used to measure crop development by means of indices as NDVI, Leaf Area Index (LAI) and Canopy Cover.
FutureWater uses remote sensing information on crop status to improve crop water simulation models, leading to more accurate and realistic results. Satellite-based information can be used, which has the advantage that it can provide long and consistent timeseries. But also, Flying Sensor-based remote sensing can provide useful high-resolution estimates of crop development.
For example, Canopy Cover can be extracted from this imagery and be used in combination with crop water productivity models to assess yields and water productivity.
Crop water models and climate change impacts
Crop water simulation models can be used to assess climate change impacts on food security. To assess climate change impacts on crop production, a combination of factors need to be considered, principally: temperature-dependent stresses, water availability changes and CO2 changes affecting the biomass assimilation.
Typically this type of analysis require a large number of siulations to be performed over various dimensions: time horizons, regions, crop types, soil types, among others. FutureWater has performed this type of analysis for different agro-climatic regions in the world and different scales of interest (regional to global). FutureWater presents outputs of this type of analysis in a digestible way to decision-makers.
This is a feasibility study on the adoption of more efficient irrigation techniques by oil palm farmers in the Sevilla basin, one of the key basins in the Sierra Nevada, Colombia. The general objective is to identify the local environment at basin scale, the limiting factors and suitable field interventions…
The PROMAC II project is an ongoing project of NCBA Clusa introducing conservation farming practices to various locations in the Manica, Tete and Zambezia provinces, with the objective to increase agricultural productivity. This project incorporates flying sensor activities in the PROMAC II project as a M&E indicator of the practices…
The overall project goal is to improve sustainable food and income security for >100,000 smallholder farmers in Angola, by accelerating their agri-business performance through informed decisions supported by the Mavo Diami services built on weather, soil and crop signals and other relevant data and indicators. Ensuring the services are offered…
The overall project objective is to compile an inventory of agricultural field interventions and develop a training package to evaluate Real Water Savings from irrigated fields, to systems and basins. A guidance document is developed for agricultural field interventions by compiling a literature database containing published experiences and results of…
The project has as its overall aim to increase climate resilient agricultural productivity and food security, with a specific objective to increase the water productivity and profitability of smallholder farmers in Mozambique, prioritizing small (family sector) farmers to increase food and nutritional security. This project will demonstrate what the best…
The novel methodology that is piloted by the World Bank for assessing climate risks versus other risks on water resource projects, called the Decision Tree Framework (DTF), is applied to two two planned investments: (1) flood protection infrastructure and irrigated cropland expansion on the Nzoia river, Kenya; and (2) the…
The SMART-WADI project (SMART Water Decisions for Iran), carried out by a consortium of FutureWater, IHE-Delft, and local partner EWERI, focuses on farmers who irrigate their crops with groundwater. The aim is to provide up-to-date information and advice on water productivity, irrigation and farm management. The project combines the latest…
The objective of this pilot study was to achieve plot-level maps of water productivity and yield to test a methodology to assess the performance of different farmers in order to provide them with recommendations to improve water productivity. More specifically, this pilot study combined high-resolution imagery from Flying Sensors with…
The ThirdEye project supports farmers in Mozambique and Kenya with their decision making in farm and crop management by setting up a network of flying sensors operators. Our innovation is a major transformation in farmers’ decision making regarding the application of limited resources such as water, seeds, fertilizer and labor.…
This study contributes to the agriculture sector climate change impact assessment and adaptation and mitigation strategy identification and evaluation. The study encompasses the three countries of the Southern Caucasus region: Armenia, Azerbaijan, and Georgia. The project also includes components for capacity building among in-country staff, and support of the World…
Methodology Development of adaptation benefit-cost framework: The framework was developed in a manner to make it possible to isolate development- and climate-related benefits and costs of individual projects and to assess the sensitivity of adaptation benefits and costs to the uncertainty inherent in regional climate change scenarios. Development of analytical tools and procedures: The project...