Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or saline conditions Mirjam Hack, Dennis Walvoort,

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Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or saline conditions Mirjam Hack, Dennis Walvoort, Joop Kroes, Ruud Bartholomeus, Jan van Bakel and Jos van Dam 24 August 2015

Quantification of the impact of hydrology on agricultural production Presentation Background information Modelling Easily applicable tools: simplified relations soil physical parameters examples

Quantification of the impact of hydrology on agricultural production Background information Why this project? various users: regional government, water managers, drinking water companies -> new tool for optimization of water management for financial compensation for farmers -> in case of water level changes to less optimal conditions (existing tool is not trusted anymore)

Quantification of the impact of hydrology on agricultural production New Tool: WaterVision Agriculture (Dutch: Waterwijzer Landbouw) End users (financers) have asked for: new method, ‘climate proof’ current, existing knowledge current and future climate differences between years effects of extreme weather events current farm management drought, saline conditions or too wet conditions

Quantification of the impact of hydrology on agricultural production WaterVision Agriculture: Based on hydrological simulation model SWAP and crop growth model WOFOST. Products: linked models for experienced users + easily applicable tools simplified relations for assessing crop growth as a function of soil type and groundwater level.

SWAP: Soil-Water-Atmosphere-Plant System Atmosphere Plant Precipitation / Irrigation Atmosphere interception transpiration soil-evaporation Plant Snow surface runoff Surface waters saturated Unsaturated zone drainage/ subsurface infiltration Saturated - Transport of: soil water zone drainage/ soil heat subsurface solutes (salts, tracers) infiltration - Influenced by: Soil heterogeneity Swelling and shrinking deep percolation/ Hysteresis seepage Deep Groundwater

WOFOST (World Food Studies)

WOFOST

Results model testing: crop yields grassland silage maize potato

Examples for application of WaterVision Agriculture Yield reduction (%) Variation between years Variation within years

WaterVision Agriculture Products: linked models for experienced users easily applicable tools and simplified relations, based on: -> multiple SWAP-WOFOST runs -> current weather + 3 climate scenarios -> 5 weather stations -> 72 units of soil physical map -> 2 crops (grassland and silage maize)

Soil physical map BOFEK 2012 (Wösten et al) BOFEK is a physical interpretation of the Dutch national Soil Map, scale 1 : 50 000 BOFEK is clustering of 315 soil units to 72 soil physical units (based on hydrologic assessments) BOFEK provides soil physical characteristics (pF and k(h)) for soil layers per unit

WaterVision Agriculture simplified relations, based on: -> multiple SWAP-WOFOST runs -> based on large parameter sets (meteorology, hydrological boundary conditions, soil data) -> Latin hypercube sampling Presentation simplified relations: online tool, GIS- applications, tables, graphs first examples

WaterVision Agriculture Example: grassland, marine clay soil annual average drought stress (y-axis) as a function of mean highest groundwater level (x-axis)

WaterVision Agriculture Example: silage maize, sandy soil (cambic podzol) annual average oxygen stress (dot size) as a function of -mean highest groundwater level (y-axis) and -mean lowest (x-axis)

WaterVision Agriculture Example: silage maize, sandy soil (cambic podzol) Both drought and oxygen stress (dot size, yield difference) as a function of -mean highest groundwater level (y-axis) and -mean lowest (x-axis)

Concluding remarks WaterVision Agriculture meets the requirements of the users and is based on state-of-the-art process models on hydrology and crop growth simplified relations, for 4 climate scenarios, 5 weather stations, 72 units of soil physical map and 2 crops (grassland and silage maize) products: linked models for experienced users simplified relations (under construction) that can feed into easily applicable tools

Thank you for your attention!