Updated CSES and SWEML

docs/products/cses/index.md

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+---
+sidebar_position: 6
+title: "CSES"
+description: "Community Streamflow Evaluation System"
+tags:
+  - roset
+  - python
+---
+
+# CSES
+
+Community Streamflow Evaluation System (CSES) is a Python-based, user friendly, fast, and model agnostic streamflow evaluator tool. This tool can be used to evaluate any hydrological model that uses NHDPlus dataset. It allows a user to evaluate the performance of a hydrological model at the collocated USGS gauges and NHDPlus stream reaches. This Python-based tool helps visualize the results and investigate the model performance interactively. The current version of the tool is available on GitHub and can be accessed using the following link.
+
+![Community Streamflow Evaluation System (CSES)](/img/streamfloweval.png)
+
+
+import GitHubReadme from '@site/src/components/GitHubReadme';
+
+<GitHubReadme username="whitelightning450" repo="Community-Streamflow-Evaluation-System" />
+

docs/products/sweml/index.md

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+---
+sidebar_position: 8
+title: "SWEML"
+description: "Snow Water Equivalent Machine Learning"
+tags:
+  - national_snow_model
+---
+
+# Advancing Snow Modeling
+
+The Snow Water Equivalent Machine Learning(SWEML) incorporates ground-based snow measuring sites, remotely-sensed snow cover information, and a Artificial Neural Network to provide point estimations of Snow Water Equivalent. The network was trained on historical data data from NASA’s ASO missions, divided into regions, and then a LightGradientBoost Model was used to preform recursive feature elimination to produce an efficient feature selection and region-specific model. The class contains the required functions for downloading data, pre-processing, running inference, and for producing visualizations.
+
+## Code
+
+The source code for the Snow Model can be found on GitHub:
+
+https://github.com/whitelightning450/SWEML