Drought forecasting based on seasonal climate forecasting in combination with hydrological and crop growth models

Français non disponible
English

The Drought Monitoring and Forecasting System of DIANA aims to estimate present and future drought conditions through a modelling framework that combines hydrological modelling, real-time weather data and seasonal climate forecasts.

The forecasting system consists of three parts

a historical reconstruction of the terrestrial water cycle running over many decades to produce the soil moisture and precipitation climatology which facilitates the comparison of current and predicted conditions;
a real-time monitoring system to track present drought conditions;
bias-corrected and downscaled seasonal forecasting data produces seasonal hydrological predictions and derives drought maps and other hydrological products up to six months in advance.

The system uses drought indices to identify the occurrence and type of a drought event and estimate its severity. The used drought indices include:

The Standardised Precipitation Index (SPI)

Drought events are indicated when the results of the SPI for whichever timescale is being investigated become continuously negative and reach a value of −1. The drought event is considered to be ongoing until SPI reaches a value of 0. The ability of the SPI to be calculated at various timescales allows for several applications. Depending on the drought impact in question, SPI values for three months or less might be helpful for essential drought monitoring, values for six months or less for monitoring agricultural impacts and values for 12 months or longer for hydrological impacts.

The Standardised Precipitation Evapotranspiration Index (SPEI)

SPEI uses the basis of the SPI but includes a temperature component, allowing the index to account for the effect of temperature on drought development through a basic water balance calculation. SPEI has an intensity scale in which both positive and negative values are calculated, identifying wet and dry events. It can be calculated for time periods between one month and 48 months. Monthly updates allow it to be used operationally and the longer the time series of data available, the more robust the results will be. With the same versatility as that of SPI, SPEI can be used to identify and monitor conditions associated with a variety of drought impacts.

The Palmer Drought Severity Index (PDSI)

This index is calculated using monthly temperature and precipitation data and information on the water-holding capacity of soils. It considers moisture received (precipitation) and moisture stored in the soil, accounting for the potential loss of moisture due to temperature influences. Although it was developed mainly to identify droughts affecting agriculture, it has also been used for identifying and monitoring droughts associated with other types of impacts as well.

The Effective Drought Index (EDI)

This index uses daily precipitation data to develop and compute several parameters: effective precipitation (EP), daily mean EP, deviation of EP (DEP), and DEP's standardised value. These parameters can identify the onset and end of water deficit periods. Using the input parameters EDI calculations can be performed for any location in the world. The results are standardised for comparison, giving a clear definition of drought onset, end, and duration. This is a good index for operational monitoring of both meteorological and agricultural drought situations because calculations are updated daily.

The Crop Specific Drought Index (CSDI)

This index, by calculating a basic soil water balance takes into account the impact of drought. It identifies when the drought stress occurred within the development of the crop and what the overall effect on the final yield will be. PDSI and CMI can identify drought conditions affecting a crop, but do not indicate the likely impact on yields.

The Soil Moisture Deficit Index (SMDI)

This is a weekly soil moisture product calculated at four different soil depths, including the total soil column, at 0.61, 1.23 and 1.83 m and can be used as an indicator of short-term drought, especially using the results from the 0.61 m layer.

The Evapotranspiration Deficit Index (ETDI)

This is a weekly product that helps identify water stress for crops. ETDI is calculated along with the Soil Moisture Deficit Index (SMDI), in which a water stress ratio is calculated that compares actual evapotranspiration with reference crop evapotranspiration. The water stress ratio is then compared with the median calculated over a long-term period. ETDI is very useful for identifying and monitoring short-term drought affecting agriculture.

Αll these drought indices identify different types of drought.

The service creates an outstanding database consisting of:

EO data from the Landsat 8, Sentinel-2 and MODIS Terra;
Meteorological observations and reanalysis (i.e. the analysis of archived data) for the hydrologic reconstruction of soil moisture time series;
Short-range weather forecasts to be used as background forecasts for the data assimilation system;
Seasonal climate forecasts for seasonal drought forecasting;
Maps of the soil mechanical analysis and hydraulic properties;
Digital Elevation Data to support the Weather Research and Forecasting (WRF)-Hydro model;
New Copernicus high-resolution Layers for land use/land cover maps.

The Drought Monitoring and Forecasting System is important at larger geographical scales and certainly at the River Basin or the Water Department levels. Τhis service can support the Drought Management Plans, the River Basin Management Plans, and the Water Index Exploitation Index estimation. The tool was tested at the Guadalquivir case study in Andalucia, Spain.

Guadalquivir case study

The case study area is in the mid-Guadalquivir valley in Andalucía in the south of Spain. This region is well known for its agricultural productivity and its efforts for improving the efficiency of resources. These efforts included significant investment in modernising irrigation systems in most Water Users Associations of the territory. It is a traditional citrus-producing area where citrus orchards occupy more than 60% of the surface and the tendency is to increase the area of woody crops. Managers and farmers can benefit from early warning tools/services to detect water deficits in woody crops.

Description of earth observation methodology for all services

Case study results

Relevance for monitoring and evaluation of the CAP

The drought forecasting tool is a service very relevant to monitoring and evaluation for two reasons.

Databank for evaluating policy impacts on water, soil, and climate: The tool creates a valuable databank for many evaluation exercises. The EO data, the soil and weather data and the land use and land cover data collected for estimating the drought indices can be used to evaluate the impacts of policies and measures on water, soil and climate, and the corresponding impact result indicators. All these data are linked to LPIS and IACS. Therefore, beneficiaries and non-beneficiaries of various measures targeting water and soil conservation can be identified. These data can support the adoption of more sophisticated and advanced evaluation techniques to approximate the net impacts of the assessed actions.

Evaluation of risk management schemes: The tool provides another perspective on drought risk and related risk management. Especially in semi-arid agricultural areas where droughts may be a critical component to farm resilience, especially when viewed with extreme climate change events. Also, droughts impact the biophysical environment, including nutrient concentrations in water bodies and the risk of contamination and soil exposure to erosion if followed by heavy rain.

The drought forecasting tool has been validated at the stage of ‘proof-of-concept’ in the Guadalquivir case study in Andalucia, Spain. The lead partner’s contact person provides the tool and the associated data upon request.

Last modification date:

09/12/2021

Project details

DIANA:
Detection and Integrated Assessment of Non-authorised water Abstractions using Earth Observation

Objectives

To capture and analyse the needs and requirements of DIANA users and stakeholders, including water managers and authorities, farmers’ associations, agricultural cooperatives and agricultural consultants.
To implement an Earth Observation methodology and production line for detecting irrigated areas and estimating irrigation requirements and possibly actual water use.
To design the overall information technology architecture, which realised the project’s suite of demand-driven services based on Earth Observation, on-site observation and model output data.
To monitor the pilot studies' operation and performance, co-evaluate users’ experiences, and validate the pilot studies’ results.
To design a commercially viable and suitable business model to fit the needs of the potential customers as well as the interests of the project’s partners.

Timeframe:

2017 to 2019

Contacts of project holder:

Dimitra Perperidou, AGRO APPS (Greece)

Project website(s):

DIANA

DIANA deliverables

CORDIS database

Territorial coverage:

Belgique, Grèce, Italie, Portugal, Roumanie, Espagne

Relevant CAP Objectives:

4. Climate change action
5. Environmental care

Data Collection Systems Used:

IACS/LPIS
Copernicus
LUCAS Soil or relevant soil inventories
WFD-Waterbase or relevant water inventories

Associated Evaluation Approaches:

Desk research
Impact evaluation ex ante
Scenario analysis
Data analysis

Type of Output:

New / improved data for M&E

Spatial Scale:

Regional

Keywords:

drought forecasting
drought monitoring