added figure

Author: ssmahto

paper/paper.bib

@@ -1,15 +1,132 @@
+@article{Giuliani:2021,
+  title={A state-of-the-art review of optimal reservoir control for managing conflicting demands in a changing world},
+  author={Giuliani, M and Lamontagne, JR and Reed, PM and Castelletti, A},
+  journal={Water Resources Research},
+  volume={57},
+  number={12},
+  pages={e2021WR029927},
+  year={2021},
+  url = {https://doi.org/10.1029/2021WR029927},
+  doi = {10.1029/2021WR029927}
+}
+
 @article{Dang:2020,
 	author = {Dang, T. D. and Chowdhury, A. F. M. K. and Galelli, S.},
 	title = {{On the representation of water reservoir storage and operations in large-scale hydrological models: implications on model parameterization and climate change impact assessments}},
 	journal = {Hydrology and Earth System Sciences},
-	volume = {24},
-	year = {2020},
 	number = {1},
+	volume = {24},
 	pages = {397--416},
+	year = {2020},
 	url = {https://hess.copernicus.org/articles/24/397/2020/},
 	doi = {10.5194/hess-24-397-2020}
 }
 
+@article{Galelli:2022,
+  title={Opportunities to curb hydrological alterations via dam re-operation in the Mekong},
+  author={Galelli, Stefano and Dang, Thanh Duc and Ng, Jia Yi and Chowdhury, AFM Kamal and Arias, Mauricio E},
+  journal={Nature Sustainability},
+  volume={5},
+  number={12},
+  pages={1058--1069},
+  year={2022},
+  url = {https://doi.org/10.1038/s41893-022-00971-z},
+  doi = {10.1038/s41893-022-00971-z}
+}
+
+@article{Warner:2012,
+  title={Hegemony and asymmetry: Multiple-chessboard games on transboundary rivers},
+  author={Warner, Jeroen and Zawahri, Neda},
+  journal={International Environmental Agreements: Politics, Law and Economics},
+  volume={12},
+  pages={215--229},
+  year={2012},
+  url = {https://doi.org/10.1007/s10784-012-9177-y},
+  doi = {10.1007/s10784-012-9177-y}
+}
+
+@article{Steyaert:2022,
+  title={ResOpsUS, a dataset of historical reservoir operations in the contiguous United States},
+  author={Steyaert, Jennie C and Condon, Laura E and WD Turner, Sean and Voisin, Nathalie},
+  journal={Scientific Data},
+  volume={9},
+  number={1},
+  pages={34},
+  year={2022},
+  url = {https://doi.org/10.1038/s41597-022-01134-7},
+  doi = {10.1038/s41597-022-01134-7}
+}
+
+@article{Gao:2015,
+  title={Satellite remote sensing of large lakes and reservoirs: From elevation and area to storage},
+  author={Gao, Huilin},
+  journal={Wiley Interdisciplinary Reviews: Water},
+  volume={2},
+  number={2},
+  pages={147--157},
+  year={2015},
+  url = {https://doi.org/10.1002/wat2.1065},
+  doi = {10.1002/wat2.1065}
+}
+
+@article{Bonnema:2017,
+  title={Inferring reservoir operating patterns across the M ekong B asin using only space observations},
+  author={Bonnema, Matthew and Hossain, Faisal},
+  journal={Water Resources Research},
+  volume={53},
+  number={5},
+  pages={3791--3810},
+  year={2017},
+  url = {https://doi.org/10.1002/2016WR019978},
+  doi = {10.1002/2016WR019978}
+}
+
+@article{Busker:2019,
+  title={A global lake and reservoir volume analysis using a surface water dataset and satellite altimetry},
+  author={Busker, Tim and de Roo, Ad and Gelati, Emiliano and Schwatke, Christian and Adamovic, Marko and Bisselink, Berny and Pekel, Jean-Francois and Cottam, Andrew},
+  journal={Hydrology and Earth System Sciences},
+  volume={23},
+  number={2},
+  pages={669--690},
+  year={2019},
+  url = {https://doi.org/10.5194/hess-23-669-2019},
+  doi = {10.5194/hess-23-669-2019}
+}
+
+@article{Das:2022,
+  title={Reservoir Assessment Tool 2.0: Stakeholder driven improvements to satellite remote sensing based reservoir monitoring},
+  author={Das, Pritam and Hossain, Faisal and Khan, Shahzaib and Biswas, Nishan Kumar and Lee, Hyongki and Piman, Thanapon and Meechaiya, Chinaporn and Ghimire, Uttam and Hosen, Kamal},
+  journal={Environmental Modelling \& Software},
+  volume={157},
+  pages={105533},
+  year={2022},
+  url = {https://doi.org/10.1016/j.envsoft.2022.105533},
+  doi = {10.1016/j.envsoft.2022.105533}
+}
+
+@article{Schwatke:2015,
+  title={DAHITI--an innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry},
+  author={Schwatke, Christian and Dettmering, Denise and Bosch, Wolfgang and Seitz, Florian},
+  journal={Hydrology and Earth System Sciences},
+  volume={19},
+  number={10},
+  pages={4345--4364},
+  year={2015},
+  url = {https://doi.org/10.5194/hess-19-4345-2015},
+  doi = {10.5194/hess-19-4345-2015}
+}
+
+@article{Zhao:2018,
+  title={Automatic correction of contaminated images for assessment of reservoir surface area dynamics},
+  author={Zhao, Gang and Gao, Huilin},
+  journal={Geophysical Research Letters},
+  volume={45},
+  number={12},
+  pages={6092--6099},
+  year={2018},
+  url = {https://doi.org/10.1029/2018GL078343},
+  doi = {10.1029/2018GL078343}
+}
 
 @article{Vu:2022,
 	author = {Vu, D. T. and Dang, T. D. and Galelli, S. and Hossain, F.},
@@ -23,7 +140,6 @@ @article{Vu:2022
 	doi = {10.5194/hess-26-2345-2022}
 }
 
-
 @article{Coetzee:2020,
 	author = {Coetzee, Serena and Ivánová, Ivana and Mitasova, Helena and Brovelli, Maria Antonia},
 	title = {{Open Geospatial Software and Data: A Review of the Current State and A Perspective into the Future}},

paper/paper.md

@@ -45,7 +45,7 @@ Motivated by these modelling challenges, we sought to develop a package that cou
 
 # Functionality
 
-`InfeRes` is available on GitHub (https://github.com/Critical-Infrastructure-Systems-Lab/InfeRes). Its documentation (https://inferes-test.readthedocs.io/en/latest/index.html) provides a detailed explanation of the installation steps and guidelines for running the code. This includes the preparation of the required modules, which can be easily imported in the Python environment via the pip, conda, or conda-forge package manager.
+`InfeRes` is available on GitHub [https://github.com/Critical-Infrastructure-Systems-Lab/InfeRes]. Its documentation [https://inferes-test.readthedocs.io/en/latest/index.html] provides a detailed explanation of the installation steps and guidelines for running the code. This includes the preparation of the required modules, which can be easily imported in the Python environment via the pip, conda, or conda-forge package manager.
 
 The package's core functionality is divided into two main modules, which are run in sequence. The first module (`data_download.py`) downloads the Landsat imageries using the Earth Engine Python API. To that purpose, the user needs to install the *earthengine-api* package and authenticate with the Google Earth Engine account. In principle, the user can download any set of data from the Google Earth Engine using `data_download.py`; however, for the current objective, we simply use the Normalised Difference Water Index (NDWI) and Quality Assessment Bands (QA_PIXEL) from the Landsat data collection. Alternatively, the user can also download the GREEN and NIR bands to calculate NDWI, instead of downloading NDWI directly from the Earth Engine. Note that more storage and time would be required in such case. The data download module also helps users change the data specifications, such as satellite sensor, area of interest, spatial resolution, and selection of bands. The time needed for data download depends on the size of the Landsat images. For instance, when tested on one of the biggest reservoir area (3010 x 5413 pixels of 30 m resolution), it took around 6-8 hours to download 1330 Landsat images (Landsat 5, 7, and 8), which required nearly 45 GB of storage.