GEO-CWB: GIS-Based Algorithms for Parametrising the Responses of Catchment Dynamic Water Balance Regarding Climate and Land Use Changes

Abstract

Parametrising the spatially distributed dynamic catchment water balance is a critical factor in studying the hydrological system responses to climate and land use changes. This study presents the development of a geographic information system (GIS)-based set of algorithms (geographical spatially distributed water balance model (GEO-CWB)), which is developed from integrating physical, statistical, and machine learning models. The GEO-CWB tool has been developed to simulate and predict future spatially distributed dynamic water balance using GIS environment at the catchment scale in response to the future changes in climate variables and land use through a user-friendly interface. The tool helps in bridging the gap in quantifying the high-resolution dynamic water balance components for the large catchments by reducing the computational costs. Also, this paper presents the application and validation of GEO-CWB on the Shannon catchment in Ireland as an example of a large and complicated hydrological system. It can be concluded that climate and land use changes have significant effects on the spatial and temporal patterns of the different water balance components of the catchment.

Hybrid Data-Driven Models for Hydrological Simulation and Projection on the Catchment Scale

“…The models were trained and validated on three types of 30-year (climatic period) daily time series datasets (1983-2013) from the five selected stations shown in Figure 1: (1) observed data (maximum temperature (Tmax) ( • C), minimum temperature (Tmin) ( • C), water level (WL) (m), and water flow (Q)(m 3 /s)); (2) monthly simulated runoff values (mm) by GEO-CWB; and (3) daily runoff values (mm), which were downscaled from the GEO-CWB simulations using the observed daily precipitation data through the developed GIS-based downscaling algorithm [57,58]. All the datasets are related to each of the five main hydrometric stations in the Shannon River catchment.…”

“…A hydrometric station's modeling and forecast results will vary depending on the catchment's climate zone and other characteristics [2]. Geophysical models, such as GEO-CWB, are capable of accurate and reliable modelling of catchments on a coarse scale; however, they are unsuitable for localized point projections due to the enormous computational cost associated with a refined spatial grid [3]. For this reason, there is increasing interest in 'surrogate' models, which are data-driven models trained on results from hydrological models, such as GEO-CWB, and which can be run rapidly to explore both long and short-term forecasts on localized scales.…”

Potential Impacts of Land Use Changes and Climate Variations on Flows in a Basin in Northeastern Brazil

“…Changes in land use cause severe environmental impacts, such as changes in the hydrological processes of in ltration, groundwater recharge, base ow, and surface runoff, affecting water availability and consequently water supply (Gharbia et al 2020;Liu et al 2020). Furthermore, changes in soil cover affect water quality since the removal of natural cover and its replacement by arable areas can increase surface runoff.…”