Soil moisture retention on slopes under different agricultural land uses in hilly regions of Southern Transdanubia

Abstract

Increasingly severe weather extremes are predicted as one of the consequences of climate change. According to climatic models, weather extremities induce higher risks for both flood and drought in the Carpathian Basin. Throughout the 19th and 20th centuries, flood control relied on cost-intensive engineering structures, but recently ecological solutions have come to the fore. Flood hazard on major rivers could be mitigated if multiple and cumulative water retention opportunities are exploited on the upper sections of tributary catchments. Appropriate land use and landscape pattern changes can shift the infiltration to run-off ratio to the benefit of the former. In the Transdanubian Hills of Southwest Hungary three study areas with different agricultural land use types had been selected and investigated for the impact of landscape micro-features on soil moisture retention capacity with the purpose of conserving water from wet periods for the times of drought. Marked differences in moisture dynamics have been detected between arable land, grasslands and orchards. This fact underlines the need for integrated soil and water conservation. Drought risk was found to be the highest on ploughland. Favourable soil water budgets have been observed in the fields as a function of land use: less intensive types, like grazing land and orchards (particularly tree rows), were identified as places of high water retention capacity. Although serious water stress conditions were also reached in the orchard, it markedly mitigated drought conditions compared to the ploughland.

Comparison of soil moisture indices and field measurements in hilly agricultural lands of SW Hungary

“…The data from our monitoring system for the study period show that the measurement sites at the top slopes were wetter in all the three areas (Nagy et al 2020). This finding contradicts the prediction from TWI, i.e.…”

Trends in extreme precipitation events (SW Hungary) based on a high-density monitoring network

“…et al 2010b), management of ecosystem services (Syrbe, R.-U. and Grunewald, K. 2017) and may also be indispensable for the protection of farmlands, urban areas and habitats of endangered species (Nagy, G. et al 2020). Additionally, weather monitoring networks seem to be suitable to reveal the intensity, location and timing of EPEs, especially in developed areas, where hydrologic, erosional and geomorphic consequences of intense rainfall may threaten human lives and generate significant economic losses.…”

Deep learning‐based training data augmentation combined with post‐classification improves the classification accuracy for dominant and scattered invasive forest tree species

“…Gathering stand‐level data, therefore, is important for implementing sustainable forest management practices in order to preserve biodiversity and multifunctional ecosystem services (Vo et al., 2013). Knowledge on the species composition is also important in quantifying timber volume and above ground biomass (Brahma et al., 2021; Nagy et al., 2020; Vo et al., 2013; Vorster et al., 2020), in nature conservation and landscape protection (Blackman, 2013; Zhang & Xie, 2012), and in tracking the spread of invasive tree species (Asner et al., 2008; Wilfong et al., 2009; Baron et al., 2018; Dyderski & Jagodziński, 2020; Dyderski & Pawlik, 2020; Dyrmann et al., 2021; Lake et al., 2022; da Silva et al., 2023).…”