Water Productivity Improvement in Practice (Water-PIP)
Prepared by IHE Delft
June 2020
Authors:
- Abebe Chukalla (a.chukalla@un-ihe.org),
- Marloes Mul,
- Poolad Karimi
With contributions from: Bich Tran, Quan Pan, Solomon Seyoum
- python 3.7.3
- numpy 1.16.4
- pandas 0.24.2
- GDAL 2.3.3
- pyshp 2.1.0
i) Install python and jupyter notebook: https://www.anaconda.com/products/individual
Read more on Jupyter notebook: https://jupyter.org/, https://packaging.python.org/overview/
a) pip installs python packages in any environment. Install a pip package in the current Jupyter kernel
import sys
!{sys.executable} -m pip install 'package'
b) conda installs any package in conda environments. Install a conda package in the current Jupyter kernel
import sys
!conda install --yes --prefix {sys.prefix} 'package'
Land and water productivity is a measure of gains per unit of resource use (Zwart and Bastiaanssen, 2004). The gain can be described as biophysical, economic or social benefits; and the resource use refers to water use, or land. Water use can be consumption or supply, which can also be characterized as green water (effective rainfall) or blue water (effective irrigation).
Productivity topic is interest of various stakeholders from farmer or irrigation manager to policy makers with various objectives. Farmers are interested to optimise the benefit generated per unit of resource use, i.e. land. While the top priority of the river basin authority is to allocate water resources in equitable, efficient and sustainable manner between different water uses/ users. Thus, at river basin level, the interest is to optimise productivity at river basin level while maintaining equity and sustainability as core values. Policy makers are often interested to increase employment and the overall production and thus national income.
The protocol is aimed at guiding users to use python script to assess land and water productivity, productivity gaps, and other performance indicators such as water consumption, beneficial fraction, equity, adequacy, reliability applying the FAO Water Productivity Open-access portal (WaPOR).
Scope: the assessment is tailored to biophysical water productivity defined as biomass or crop yield per unit of water consumption; and land productivity (i.e. biomass or crop yield); socio-economic productivity analyses is beyond the scope of the protocol.
Scope: the assessment is tailored to biophysical water productivity defined as biomass or crop yield per unit of water consumption, land productivity (i.e. biomass or crop yield), productivity gaps, and other irrigation performance indicators such as seasonal water consumption, seasonal reference evapotranpiration, equity, adequacy, reliability, relative water deficit, and relative biomass/yield reduction. Socio-economic productivity analyses is beyond the scope of the protocol.
The full or part of the protocol can be implemented in rainfed crop production that gets the water sources from exclusively rainfall, or irrigated crop production that gets blue water from surface water, groundwater, or flood /spate/ sources.
The protocol applies identical crop parameters and same start and end of season dates. One can analyse multiple crops, different starting and ending dates or identify bright spots, compare different management intervention strategies and practices at the field/irrigation systems/river basin that falls in similar agro-climatic zones by running the scripts multiple times for different masking boundary; or alternatively by upgrading the script to loop through multiple masking values in a boundary.
The protocol estimate productivity gaps and identify bright spots from fields, schemes or region in similar agro-climatic zones. However, comparison of indicators and assessment of productivity gaps at fields, river basin and country levels, which could fall in different agro-climatic zones, require normalization for climate variation – which is beyond the scope of the protocol.
Target: The protocol is developed for project leads, irrigation managers and researchers who could run python script.
The protocol has six steps.
Seasonal crop water consumption is calculated as the total evapotranspiration over the cropping season.
Equity can be estimated from uniformity of water consumption, which is defined as the coefficients of variation (CV) of seasonal ETa in the area of interest (Karimi et al., 2019; Bastiaanssen et al., 1996).
Beneficial fraction (BF) is the percentage of the water that is consumed as transpiration compared to overall field water consumption (ETa).
Adequacy can be explained by relative evapotranspiration, which is the ratio of actual evapotranspiration over potential evaporation (Equation 3) (Kharrou et al., 2013; Karimi et al., 2019).
Reliability is the measure of the temporal uniformity of water delivery in accordance with the agreement or required, which can be quantified as the temporal variation of relative evapotranspiration (
Land productivity is defined as the above-ground biomass production in ton/ha/season.
Crop yield is calculated as the product of above-ground biomass by harvest index.
Biomass Water productivity is estimated as the ratio of above-ground biomass over actual evapotranspiration.
Crop water productivity is estimated as the ratio of crop yield over actual evapotranspiration.
Aimed at improving both land and water productivity, the attainable productivity (productivity target) in a particular year is estimated at 95 percentile of the respective productivity distributions across fields/ scheme in alike agro-climatic zone.
The bright spots are pixels that have both land and water productivity equal or greater than the target values.
Productivity gap of a crop at a pixel is calculated by subtracting the productivity value from the productivity target.
The aim of the comparison is check if there is consistency between observed and calculated values or data of two sources. The comparison will be done with the aid of visual graph interpretation (against 1:1 line), coefficient of determination, and coefficient of correlation.
The FAO Water Productivity Open Access portal WaPOR (2019), https://wapor.apps.fao.org/home/WAPOR_2/1, is the first comprehensive dataset that combines water use (actual evaporation, transpiration and interception), production (net primary production), land use (land cover classification), phenology, climate (precipitation and reference evapotranspiration) and productivity at continental scale at near real-time covering the period of 2009-now. In addition to the continental level (250 m), WaPOR datasets are available at country (100 m) and project level (30 m).
Ground data such as boundary of the farm, moisture content of fresh biomass, above ground over total biomass, start and end of seasons are required to mask WaPOR data, to estimate seasonal values including biomass, water consumptions etc. Additional crop parameters such as harvest index helps to translate biomass and biomass water productivity to crop yield and crop water productivity.
Resampling WaPOR data to the same spatial resolution, and filtering non-crop land classes are the first steps required to do the analyses.
Github: https://github.com/wateraccounting/WAPORWP
Step-1: WaPOR data pre-processing
Step-2: Seasonal water consumption and production
Step-3: Irrigation performance indicators
Step-4: Calculate land and water productivity
Step-5: Identify bright spots and analyse the productivity gaps
Step-6: Validation: compare results derived from WaPOR and observations
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