Aayush Pandit Email & Phone Number

Lawrence, KS, US

Katy, Texas, United States

HEC HMS and 1D HEC RAS with bridge models to evaluate WSE impacts in replacement of 3 bridges.

Drainage report review and QC

2D HEC-RAS modeling of culverts, equalizers to minimize WSE impacts in proposed road widening project

Reviewed and QC final drainage and scour report to be submitted to TXDOT

Lawrence, Kansas, United States

Hydrologic models report wide range of values of R², NSE, KGE, pBIAS... for their models. But what thresholds objectively qualify as benchmarks for acceptable model?To estimate industry benchmark we gathered research from 2010 doing water modeling in several platforms (SWAT, HYPE, QUAL2K..) and compiled findings.

Lawrence, Kansas, United States

We used LSTM (Long short term memory), a class of deep learning AI model, to predict daily Nitrate concentration from 2007 to 2020 in rivers across US. The model is first of its kind and can be used to predict nitrate in any basins based on climate and local site conditions.

Lawrence, Kansas, United States

We developed a SWAT model in Hillsdale lake, Kansas. The model was used to simulate streamflow, sediment, total nitrogen, phosphorus and ultimately chlorophyll a concentration in a lake at the outlet.The model will be useful in predicting future lake trophic status.

Gandakī, Nepal

Certain locations appear prone to climate change impacts. While rising temperature is not true for all places, Its effect certainly is prominent in many locations. Moreover, Basin is accompanied with lots of other hazardous effects in rainfall, flooding, frequency and intensity.

Koteshwor, Kathmandu, Bāgmatī, Nepal

Reversible lane system is a dynamic approach of adjusting traffic via mobilizing incoming and outgoing lane distribution as per traffic demand in respective direction. Its long forgotten, low cost yet highly effective method of immediate congestion minimization in directional traffic. Its one step towards Intelligent Transport Infrastructures and truly.

Bachelor'S Degree, Civil Engineering, 72

Master'S Degree, Water Resources Engineering, 3.96