Dr. Saket Pande
Saket Pande (B.Tech in Civil Engineering, Indian Institute of Technology Delhi, 2000; Ph.D. in Civil and Environment Engineering, Utah State University, 2005) is a hydrologist and a water economist. He has advanced education in both Hydrology and Economics, and has expertise in the fundamentals of Hydrology, Applied Statistics, Economic Theory, and their intersections in real-world applications. Prior to joining TU Delft in 2010, Saket was at SOW-VU (Stichting Onderzoek Wereldvoedsel-voorziening van de Vrije Universiteit), Amsterdam.
In recent years Saket has been extensively researching on how fundamentals of applied probability can explain the issues underlying calibration uncertainty in water systems, especially in basin scale hydrology. He has shown that control on hydrologic model complexity can lead to robust prediction performance. He has also been studying the impacts of hydrologic uncertainty on economic systems. Using his training in economics, Saket has also researched into temporal dynamics of individual decision-making as well as into the fundamentals of welfare economics.
Saket has extensive experience in working in multidisciplinary teams on topics such as uncertainty implications of climate change on water availability, food production and human wellbeing in developing countries like Benin, Ethiopia and Sudan. Saket has been involved in development of innovative statistical and GIS tools for integrating data of different kinds, be it by resolution or source, into a unified modeling framework. Most recently Saket has been involved in conceptualizing coupled human water systems in water scarce regions of the world such as India and Australia and consequently has developed parsimonious socio-hydrological models. Saket’s overarching aim is to use his diverse training to solve real-world problems that are interdisciplinary in nature.
Assessment of farmers perception of climate variability and declining crop productivity in the El-Gadarif state of Sahelian Sudan.
- International peer reviewed articles
*indicates student publication, **indicates publication in cooperation with a student.
1) Pande, S. and Savenije, H.H.G. (2016). A socio-hydrological model for smallholder farmers in Maharashtra, India, Water Resources Research, forthcoming.
2) *Ghazanfari, S., Pande S., Cheema, M. J. M., Alizadeh, A. and Farid, A. (2015). The role of soil moisture accounting in estimation of evaporation and transpiration, Journal of Hydroinformatics, jh2015114.
3) **Mianabadi, H., Mostert, E., Pande, S. and van de Giesen, N. C. (2015). Weighted bankruptcy rules and transboundary water resource allocation, Water Resources Management, 29 (7), 2303-2321.
4) **van Emmerik, T. H. M., Li, Z., Sivapalan, M., Pande, S., Kandasamy, J., Savenije, H. H. G., Chanan, A., and Vigneswaran, S.(2014). Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River basin, Australia, Hydrol. Earth Syst. Sci., 18, 4239-4259.
5) *Shafiei, M, Ghahraman, B, Saghafian, B, Davary, K, Pande, S and Vazifedoust, M (2014). Uncertainty assessment of the agro-hydrological SWAP model application at field scale: A case study in a dry region, Agricultural Water Management,146,324-334.
6) Pande, S, and Ertsen, M (2014) Endogenous change: on cooperation and water availability in two ancient societies,Hydrology and Earth System Sciences,18,5,1745-1760.
7) Pande, S, Ertsen, M, and Sivapalan, M (2014). Endogenous technological and population change under increasing water scarcity, Hydrology and Earth System Sciences, 11 (8).
8) Pande, S, Arkesteijn, L, Savenije, HHG, Bastidas, LA (2014). Hydrological model parameter dimensionality is a weak measure of prediction uncertainty,Hydrology and Earth System Sciences Discussions,11,3,2555-2582.
9) **van Emmerik, THM, Li, Z, Sivapalan, M, Pande, S, Kandasamy, J, Savenije, HHG, Chanan, A, Vigneswaran, S (2014). Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River Basin, Australia, Hydrology and Earth System Sciences Discussions,11,3,3387-3435.
10) *Shafiei, M, Gharari, S, Pande, S, Bhulai, S(2014). Kernel Density Independence Sampling based Monte Carlo Scheme (KISMCS) for inverse hydrological modeling, In: Ames, DP, Quinn, NWT, Rizzoli, AE (Eds.), 2014. Proceedings of the 7th International Congress on Environmental Modelling and Software (iEMSs), June 15-19, San Diego, California, USA. ISBN: 978-88-9035-744-2.
11) **Pande, S, Arkesteijn, L, Bastidas, L(2014). Complexity regularized hydrological model selection,In: Ames, DP, Quinn, NWT, Rizzoli, AE (Eds.), 2014. Proceedings of the 7th International Congress on Environmental Modelling and Software (iEMSs), June 15-19, San Diego, California, USA. ISBN: 978-88-9035-744-2.
12) Pande, S., Ertsen, M., and Sivapalan, M. (2013). Endogenous technological and population change under increasing water scarcity. Hydrology and Earth System Sciences Discussions, 10, 13505-13537.
13) Pande, S. and Ertsen, M (2013). Endogenous change: on cooperation and water in ancient history. Hydrology and Earth System Sciences Discussions, 10(4), 4829-4868.
14) Pande, S. (2013a). Quantile hydrologic model selection and model structure deficiency assessment 1: Theory, Water Resources Research, 49, 5631–5657, doi:10.1002/wrcr.20411.
15) Pande, S. (2013b). Quantile hydrologic model selection and model structure deficiency assessment 2: Applications, , Water Resources Research, 49, 5658–5673, doi:10.1002/wrcr.20422.
16) *Ghazanfari, S., Pande, S., Hashemy, M., Sonneveld, B. (2013). Diagnosis of GLDAS LSM based aridity index and dryland identification, Journal of Environmental Management, 119, 162-172.
17) *Arkesteijn, L., and Pande S. (2013), On hydrological model complexity, its geometrical interpretations and prediction uncertainty, Water Resour. Res., 49, 7048–7063, doi:10.1002/wrcr.20529.
18) *Shafiei, M., Ghahraman, B., Bahram S., Pande, S., Kamran D. (2013). Assessment of the number and location of rain-gauges using Probabilistic-GIS based approach. Hydrology Research, doi:10.2166/nh.2013.042 (Uncorrected Proof Online).
19) Hrachowitz, M., Savenije, H.H.G., Blöschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E., and Cudennec, C. (2013). A decade of Predictions in Ungauged Basins (PUB)—a review. Hydrological Sciences Journal, 58 (6), 1198–1255.
20) Pande, S.; Savenije, H.H.G.; Bastidas, L. A; Gosain, A. K. (2012). A parsimonious hydrological model for a data scarce dryland region. Water Resources Management, Volume 26, Issue 4, pp 909-926.
21) Sonneveld, B.; Keyzer, M.A.; Adegbola, P. and Pande, S (2012). The impact of climate change on crop production in West Africa: an assessment for the Oueme River Basin in Benin. Water Resources Management, 2012, Volume 26, Issue 2, 553-579.
22) Pande, S., Bastidas, L. A., Bhulai, S., McKee, M. (2012). Parameter dependent convergence bounds and complexity measure for a class of conceptual hydrological models, Journal of Hydroinformatics, Vol 14, No 2 pp 443–463.
23) Pande, S., van den Boom, B., Savenije, H.H.G; Gosain, A. K. (2011). Water valuation at basin scale with application to western India. Ecological Economics Volume 70, Issue 12, 2416–2428.
24) Pande, S., M. McKee, and L.A. Bastidas (2009). Complexity-based robust hydrologic prediction, Water Resources Research, 45, W10406, doi:10.1029/2008WR007524.
25) Barthel, R., B.G.J.S. Sonneveld, J. Gotzinger, M.A. Keyzer, S. Pande, A. Printz, T. Gaiser (2009). Integrated assessment of groundwater resources in the Ouémé basin, Benin. Journal of Physics and Chemistry of Earth, doi:10.1016/j.pce.2008.04.001.
26) Sonneveld, B., M.A. Keyzer, K. Georgis, S. Pande, A.S. Ali, A. Takele (2009). Following the Afar: using remote tracking sys3tems to analyse pastoralists’ trekking routes. Journal of Arid Environments, doi:10.1016/j.jaridenv.2009.05.001.
27) **Pande, S., M.A. Keyzer, A. Arouna and B.G.J.S. Sonneveld (2008). Addressing diarrhea prevalence in the West African Middle Belt: social and geographic dimensions in a case study for Benin. International Journal of Health Geographics, 7:17, doi:10.1186/1476-072X-7-17.
28) Pande, S, and M. McKee (2007). Valuing certainty in a consensus-based water allocation mechanism. Water Resources Research, 43, W02427, doi:10.1029/ 2004WR003890.
29) Lyon, K., and S.Pande (2006) The costate variable in a stochastic renewable resource model. Natural Resource Modeling, 19(1), 45-66.
30) Caliendo, F. and S. Pande (2005). Fixed endpoint optimal control. Economic Theory, 26, 1007-1012.
- Books (2)
31)Keyzer, M.A., B.G.J.S. Sonneveld and S. Pande (2007). “The impact of climate change on crop production and health in West Africa: an assessment for the Oueme River Basin in Benin.” Final report for the Rivertwin project, Sixth Framework Program of the European Commission.
32) Pande, S. (2005). “Generalized Local Learning in Water Resources Management.” Unpublished Ph.D. dissertation, Department of Civil and Environmental Engineering, Utah State University.
- Book chapters (2)
33) Pande, S., H.H.G. Savenije, L A Bastidas, A. K Gosain (2010). A parsimonious modeling approach for water management in dryland areas. In S Khan & H Savenije (Eds.), Hydrocomplexity: new tools for solving wicked water problems Vol. 2010. IAHS Red Books (pp. 85-90). Wallingford: IAHS press.
34) Sonneveld, B.G.J.S., S. Pande, M. A. Keyzer, K. Georgis, A. Seid Ali and A. Takele (2010). Land degradation and overgrazing in the Afar Region, Ethiopia: a spatial analysis using Rainfall Use Efficiency’ In: P. Zdruli, M. Pagliai, S. Kapur and A. Faz Cano, eds. Land Degradation and Desertification: Assessment, Mitigation and Remediation, pp. 97-109. Berlin: Springer-Verlag.
- Other (6)
35) Pande, S. (2011), contribution to Predictions Under Change (PUC): Water, Earth and Biota in the Anthropocene. A report to finalized under the aegis of the US National Science Foundation project “water cycle dynamics in a changing environment” (PI: Murugesu Sivapalan), 30+ coauthors and contributors.
36) Keyzer, M. A. and Pande, S. (2010). Classification by crossing and polling for integrated processing of maps and surveys. Staff Working Paper 10-01, Amsterdam: Center for World Food Studies.
37) Keyzer, M. A., and S. Pande (2009) ‘Instrumentalization using quantiles in semiparametric support vector regression’, Working Paper 09-04. Amsterdam, SOW-VU, 61 pp.
38) Keyzer, M.A., S. Pande (2007) ‘Classification by crossing and polling for integrated processing of maps and surveys. An addendum to GRCP-software’, Working Paper 07-04. Amsterdam, SOW-VU, 65 pp.
39) Boom, G.J.M. van den, S. Pande (2007) ‘User manual for the SAS-facility to plot maps’, Working Paper 07-03. Amsterdam, SOW-VU, 38 pp.
40) 30+ general and 6 invited contributions to international conferences and workshops (abstracts/proceedings).
- Working papers (4)
* Comments welcome. Draft versions only!
(-1) Inference of Predictor Relevance: Probabilistic Wrapper Approach to Predictor Subset Selection.
(-2) Autarkic thresholds to basin scale cooperative water management.