No abstract

Grasslands are important for their ecological values and for agricultural activities such as livestock production worldwide. Efficient grassland management is vital to these values and activities, and remote sensing technologies are increasingly being used to characterize the spatiotemporal variation of grasslands to support those management practices. For this study, Sentinel-2 satellite imagery was used as an input to develop an open-source and automated monitoring system (Sen2Grass) to gain field-specific grassland information on the national and regional level for any given time range as of January 2016. This system was implemented in a cloud-computing platform (StellaSpark Nexus) designed to process large geospatial data streams from a variety of sources and was tested for a number of parcels from the Haus Riswick experimental farm in Germany. Despite outliers due to fluctuating weather conditions, vegetation index time series suggested four distinct growing cycles per growing season. Established relationships between vegetation indices and grassland yield showed poor to moderate positive trends, implying that vegetation indices could be a potential predictor for grassland biomass and chlorophyll content. However, the inclusion of larger and additional datasets such as Sentinel-1 imagery could be beneficial to developing more robust prediction models and for automatic detection of mowing events for grasslands.

<p>In 2018-2020 water managers in the Netherlands were confronted with extreme drought. This event had a large impact on nature, agriculture, shipping and drinking water supply. To better anticipate dry conditions and improve water management during a drought, up-to-date and accurate information about the meteorological and hydrological situation is crucial. During the 2018 drought it became clear that current information about groundwater levels was scattered across many different organisations. In addition, each organisation had different methods to compare current groundwater levels with historical data to indicate the severity of the drought event. There was a clear need for an uniform indication of drought severity.</p> <p>We developed an online information portal with up-to-date measurements for precipitation and groundwater levels. To quantify the drought severity, the Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiraton Index (SPEI) and Standardized Groundwater Index (SGI) are determined. The availability of long-term records (30> years) of groundwater observations is limited for most regions in the Netherlands. Therefore, the SGI is based on simulations with a time series model for all locations for the same period (27 years). Time series models are developed for 5818 wells with observations. Several criteria have been applied to evaluate the time series model, for example, a minimum value of the explained variance, resulting in 1931 wells for which SGI values are calculated. We have also compared SGI values directly derived from observations with the SGI values from simulated groundwater levels for locations with longer time periods. This comparison indicated that due to errors or missing values in observations, the SGI values from simulations are more reliable to gain a global overview of the drought situation.</p> <p>By combining the information on meteorological and hydrological drought in one decision-support system (www.droogteportaal.nl), water managers and stakeholders can now get an up-to-date overview of the current situation. Due to the uniform determination of drought severity, regions within the Netherlands can be compared. This can help to implement targeted water management decisions for adaptation measures for mitigating drought impacts. Part of the information of the portal is also included in the national drought monitor of Rijkswaterstaat (Dutch Ministry of Infrastructure and Water Management). At the moment, the portal gives forecasted information for 7 days, but the data provides an excellent opportunity to include forecasts on longer timescales ((sub-)seasonal) to improve water management.</p>

<p>Sufficient freshwater is needed for water dependent sectors as agriculture, nature, drinking water, and industry. However, even in low-lying, flood prone countries like the Netherlands, climate change, weather extremes, economic growth, urbanization, land subsidence and increased food production will make it more complex to guarantee sufficient freshwater for all sectors. Specifically, the range of weather extremes from extremely dry to extremely wet is expected to increase and extremes are expected to occur more frequently.</p><p>Over the last decades, drainage, land consolidation and urbanization resulted in declining groundwater tables. Additionally, the freshwater demand of different sectors caused an increased pressure on the regional groundwater system. As a consequence, the annual groundwater table in the Dutch sandy soil areas dropped over time with the effect that, nowadays, freshwater is becoming scarce in dry periods. Agriculture needs to anticipate on these conditions in order to prevent both drought and waterlogging. However, the current Dutch agricultural water management system is historically focused on water discharge and not designed to anticipate on both weather extremes.</p><p>One of the solutions could be to modify the current pipe drainage systems (already existing in 34 % of the agricultural land) to drainage systems with three purposes, called: controlled drainage with subirrigation. First, the drainage systems could discharge water if the risk of waterlogging increases. Second, the drainage system could store water during rainfall in the soil (retain water). Third, (external) water can be actively pumped into the drainage network to raise groundwater tables (recharge water).</p><p>We focus on the data and model output of four experimental sites in the Pleistocene uplands of the Netherlands, where controlled drainage with subirrigation is applied. Field data is collected over ± the years 2017-2021, like water supply, groundwater table, soil moisture content. Water balance components as actual transpiration, drainage and downward seepage are modelled with SWAP (Soil-Water-Atmosphere-Plant model). The effects on crop yield and configuration of the management are also quantified with the model.</p><p>The construction of controlled drainage with subirrigation, topographical location, and a proper management of these systems are important. First, results show that through subirrigation, water can be stored in the soil instead of discharged. The water storage leads to an increase in groundwater tables of ± 0.70 m during the growing season, leading to higher crop yields. By storing external water at the field scale, fast drainage was prevented, which decreased drought vulnerability. Second, results of the four experimental sites show that effects of subirrigation on the water balance components are strongly site dependent. For example, an impermeable layer at a shallow depth is needed for enough resistance to increase the phreatic groundwater level. Furthermore, ditch levels surrounded by the field are important as a shallow groundwater table with low ditch levels results in lateral drainage, an unfavorable effect. Third, results of the experimental sites show that proper management of these systems is important to prevent clogging of the system.</p>