Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes

Z Huang, T Zhao - Wiley Interdisciplinary Reviews: Water, 2022 - Wiley Online Library
Predictive performance is one of the most important issues for practical applications of
ensemble hydroclimatic forecasts. While different forecasting studies tend to use different …

Decomposition of the mean absolute error (MAE) into systematic and unsystematic components

SM Robeson, CJ Willmott - PloS one, 2023 - journals.plos.org
When evaluating the performance of quantitative models, dimensioned errors often are
characterized by sums-of-squares measures such as the mean squared error (MSE) or its …

[HTML][HTML] Export sales forecasting using artificial intelligence

V Sohrabpour, P Oghazi, R Toorajipour… - … Forecasting and Social …, 2021 - Elsevier
Sales forecasting is important in production and supply chain management. It affects firms'
planning, strategy, marketing, logistics, warehousing and resource management. While …

[HTML][HTML] A visualized hybrid intelligent model to delineate Swedish fine-grained soil layers using clay sensitivity

A Ghaderi, AA Shahri, S Larsson - Catena, 2022 - Elsevier
In the current paper, a hybrid model was developed to generate 3D delineated soil horizons
using clay sensitivity (S t) with 1 m depth intervals in a landslide prone area in the southwest …

A rational performance criterion for hydrological model

D Liu - Journal of Hydrology, 2020 - Elsevier
Performance criteria are essential for hydrological model identification or its parameters
estimation. The Kling-Gupta efficiency (KGE), which combines the three components of …

BK-SWMM flood simulation framework is being proposed for urban storm flood modeling based on uncertainty parameter crowdsourcing data from a single functional …

C Liu, W Li, C Zhao, T ** Tool: An open source web application for assessing groundwater sustainability
SW Evans, NL Jones, GP Williams, DP Ames… - … Modelling & Software, 2020 - Elsevier
Decision makers need an accurate understanding of aquifer storage trends to effectively
manage groundwater resources. Groundwater is difficult to monitor and quantify since the …

Extending SC-PDSI-PM with neural network regression using GLDAS data and Permutation Feature Importance

SG Ramirez, RC Hales, GP Williams… - Environmental Modelling & …, 2022 - Elsevier
Abstract The Palmer Drought Severity Index (PDSI) ranges from− 10 to 10 and is used for
monitoring drought extent and severity. PDSI is a monthly global gridded data set with partial …